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CHAPTER 4DATA ANALYSIS
CHAPTER 4DATA ANALYSIS
4.1 Introduction
4.2 Data Presentation
Sr. Section Number Title of Section1 I Government and Tourism2 II Demographic Profile of Stakeholders3 III Tourist Descriptive Analysis4 IV Hoteliers Descriptive Analysis5 V Tour Operators Descriptive Analysis6 VI Comparative Analysis7 VII Selected Intellectuals Descriptive
Analysis8 VIII SWOT Analysis9 IX Analysis of Tourist Amenities10 X Exploration of New Destinations11 XI Hypotheses Testing12 XII Cluster Analysis
Data Analysis
Shivaji University, Kolhapur 137
CHAPTER 4DATA ANALYSIS
4.1 Introduction:
The present chapter articulates presentation and analysis of the data. This is an effort
to suffice the objectives set for this research and to test the hypotheses.
For geared up situation the hypotheses and objectives of research are reproduced
here.
Following hypotheses have been set to test
1. Lack of promotion of tourism destinations hinders development of tourism sector
in Satara District.
2. Availability of infrastructural facilities and tourism development are correlated.
3. Government proposes planning to develop places of tourist interest but the gap
exists in planning and implementation, which leads to failure in attracting
tourists.
Present study purports following objectives
1. To analyze efforts of State Government towards development of tourism industry
in Satara District
2. To study the problems in existing tourism base in Satara District
3. To prepare SWOT matrix on the basis of infrastructural facilities and
environmental aspects prevailing for tourism in Satara District
4. To find out prospects for tourism and explore tourist destinations in Satara
District.
Data Analysis
Shivaji University, Kolhapur 138
4.2 Data Presentation:
Data is presented into 12 sections. Each section is narrating details of entire data, data
of all respondent viz. Government, Tourist, Hotelier, Tour Operator and NGOs/Social
Activist. These 12 sections are titled and presented in following manner.
Section I Government and Tourism
Section II Demographic Profile of Stakeholders
Section III Tourist Descriptive Analysis
Section IV Hoteliers Descriptive Analysis
Section V Tour Operators Descriptive Analysis
Section VI Comparative Analysis
Section VII Selected Intellectuals Descriptive Analysis
Section VIII SWOT Analysis
Section IX Analysis of Tourist Amenities
Section X Exploration of New Destinations
Section XI Hypotheses Testing
Section XII Cluster Analysis
Data Analysis
Shivaji University, Kolhapur 139
Section I
4.2.1 Government and Tourism:
Government of India Government of Maharashtra and local bodies is putting efforts in
the promotion of tourism. Government is assigned the funds for the tourism
development of Satara. The detail analysis is as follows
Distribution of Tourism Development Funds on the Basis of Infrastructure
Government sanctioned funds to the respective district for the development of tourist
destination. Funds to be utilized to improve basic and tourist infrastructure at tourist
destinations in Satara reflects in following table.
Table 4.2.1.1Tourism Development Funds Budgeted and Actually Spent on Basic Infrastructureand Tourist Infrastructure in Satara District since 1999-2011.
(Figures in Rs. Lakhs)
Sr. Basic and Tourist InfrastructureAmountbudgeted
Amountspent
Gap %
Basic Infrastructure1. Construction of Road (wp)* 200.65 151.68 48.97 24.412. Drinking Water 5 5 0 0.003. Footpath or Pathway, Stair Case,
Railing, Fixing Paving Block,Entrance, Fencing (Wp)*
122.8 103.91 18.89 15.38
4. Repair and Maintenance (wp)* 84.66 50.15 34.51 40.765. Surrounding Development,
Landscaping or Survey5.74 5.5 0.24 4.18
6. Toilets and Bathrooms (wp)* 16.99 16.4 0.59 3.477. Total 435.84 332.64 103.2 23.68
Tourist Infrastructure1. Arrangement of SPV Solar System 3.25 2.95 0.3 9.232. Canteen , Tiffin Shade 6.42 6.42 0 0.003. Construction of Hall or Multipurpose
Hall, Entertainment Hall/WaitingRoom (wp)*
19.79 19.77 0.02 0.10
4. Construction of Smarak 13.7 12.73 0.97 7.085. Garden for Children(wp)* 14.59 0 14.59 100.006. Office 8.21 8.21 0 0.007. Parking Place 9.91 9.91 0 0.008. Provision of Other Facility 5 2.07 2.93 58.609. Rest House (wp)* 50 41.18 8.82 17.64
Total 130.87 103.24 27.63 21.11Grand Total 566.71 435.88 130.83 23.09
Source: (District Planning Department, Satara, translated and compiled by researcher)*(wp) - work is progress
Data Analysis
Shivaji University, Kolhapur 140
Table 4.2.1.1 depicts that Satara district officials have spent the funds for tourism
development at different location under the different heads as per sanctioned budget.
However, it has observed that there is marginal gap between amount budgeted and
actual spending. Some of the work is still pending and the amount is yet to be spent
which was shown with (wp)*. Budget was sanctioned for development of Garden but
it was not utilized. Whereas 58.60% gap was found under the head of provision of
other facility but this heading does not give clear idea about nature of other facility,
40.76% gap found at repair and maintenance. 24.41% gap is found on construction of
road and the work in progress. 17.64% gap at rest house projects entire funds were not
utilized as the work in progress, 15.38% on footpath and staircase, railing etc.
However, very meager gap was found in different heads like 9.23% SPV solar system,
7.08% construction of Smarak, 4.18% Surrounding development and landscaping,
3.47% toilets and bathrooms and 0.10% construction of multipurpose hall. The
infrastructure like construction of office, parking place, canteen and Tiffin shade, and
drinking water gap between budgeted amount and actual amount spent was zero.
It is concluded that tourism development funds in Satara were underutilized or cost
overrun. As per the budget control system, actual expenditure exceeds the budget that
would be unfavorable condition and vice versa. In this most of the tourism
infrastructure heads budgeted amount exceeds the expenditure so it shows favourable
situation. However, allowable variance is 5% plus and minus and sometimes based on
nature of product and policy. Nearly 10% plus and /or minus variance is accepted
under the condition of allowable variance for unpredictable expenses. However, in
case of Satara in most of the tourism infrastructure this percentage is higher especially
in case of provision of other facility, road, rest house, repair, and maintenance.
Data Analysis
Shivaji University, Kolhapur 141
Total Amount Spent on Infrastructure
Following table shows the tourism development funds actually spent on basic and
tourist infrastructure at Satara since financial year 1999 to 2011. The total of amount
of basic and tourist infrastructure in previous table has taken out and presented for the
sake of lucidity.
Table 4.2.1.2Actual amount spent on basic and tourist infrastructure in Satara District since 1999 to2011
Sr. Nature of Infrastructure Amount (in Rs. lakhs) Percentage1. Basic Infrastructure 332.64 76.312. Tourist Infrastructure 103.24 23.69Total 435.88 100
Source: (District Planning Department, Satara, documents translated and compiled byresearcher)
Table 4.2.1.2 depicts that 76.31% of tourism funds spent on basic infrastructure and
only 23.69% spent on tourist infrastructure. It can be concluded that Satara district
still lags in the development of basic infrastructure. It is quite essential to provide
basic infrastructure so as at least to reach out to the development of tourist
destination.
Distribution of Tourism Development Funds on the Basis of Taluka
Following table shows the budget sanctioned and actual spending on different tourist
destinations talukawise in the year 1999 to 2011. In Satara district, 11 Talukas viz.
Satara, Karad, Phaltan, Wai, Mahabaleshwar, Koregaon, Jaoli, Maan, Khatav
Khandala and Patan where the funds are sanctioned and spent to make available
facilities for tourist that depict in the following table.
Data Analysis
Shivaji University, Kolhapur 142
Table 4.2.1.3Talukawise Distribution of Funds for Tourism Development in Satara District
(Rs. in lakhs)Sr. Taluka Destination
DevelopmentBudgeted Amount Actual
ExpenditureFacilities MadeAvailable for Tourist
1. Satara Thoseghar, 22.11+17.00* 22.08+17.00 Road, Public Toiletries,Maintenance OfSurroundings,Renovation
Sajjangarh 32.39 26.85(WP)
Yawateshwar 11.24 10.7Dhawadshi 15 14.47Kas 25.00* 15.8
Total 122.74 106.9(87.48%)
2. Karad Agashiv 40 35.69 Road, Renovation
Pal 40.00* 39.08
Total80
74.77(93.46%)
3. Phalatan Santoshgad10.66
10.42(WP)(97.74%)
Road
4. Wai MenawaliVagheshwarTemple
5.56 5.25(WP)Road, Renovation AndMaintenance
NanaPhadniswada 5.56 5.29(WP)
Narsinh Mandir,Dhom 19.1 3.32(WP)
Total 30.22 13.86 (45.86%)5. Mahabal
eshwarPratapgarh
47.99+25.00*9.73(WP)+24.80
Road, Boating, SafetyWall, Fortification,Repair And Renovation
Tapola 18 18Total 90.99 52.53 (57.73%)
6. Koregaon 47.17 37.15 Rest House, Road, SPVSolar System, Garden15.32 12.21(WP)
Total 62.49 49.36 (78.99%)7. Jaoli Bamnoli
7.787.78(100%)
Road. Rest House
8. Maan MaujeKharkhel(Santaji Ghorpade)
9.99.90(100%)
Road, Smarak
9. Khatav Aundh75.11+166.40*
74.72+163.52
Rest House, Road,Waiting Room, Repair,Renovation AndMaintenancMuseum,Tiffney Shade,
Mayani 4.62 4.62Katgun 25.49 22.91Vadgaon 36.96 35.07
Data Analysis
Shivaji University, Kolhapur 143
Mauje Bhosare 30.23 14.12(WP) Toiletries,Multipurpose Hall,Smarak, Garden,Canteen
Total 338.81314.96(92.96%)
10. Khandala Naygao3.7
3.35(90.54%)
Road, Smarak
11. Patan Ramghal 16.74 16.74 Road, Repair AndMaintenance, SafetyRailingShri Shkeshtra
Valmiki 6.97 6.57
Ozarde7.41 7.41
Marul Haveli
31.59+2.95
9.34(WP)+2.48
BahuteshwarMandir
3.17+25*
3.00+24.82
MurumKhodi 2.18 2.13Koyananagar 12.00* 11.91Banpuri 25.00* 24.69Dhareshwar 50.00* 34.88
Total 183.01 143.97(78.67%)
Source: (District Planning Department, Satara)Percentage figures in the bracket drawn on total sanctioned amount to the respectivedestinations.* Shows the funds available from regional tourism development package from state ofMaharashtra.WP- indicates work in progress.
Table 4.2.1.3 inferred that funds have been distributed among 11 Talukas of Satara
district for the year 1999 to 2011. Among these Khatav, taluka has received highest
share of Rs. 338.81 lakhs to undertake projects like construction of rest house, road,
waiting room, repair, renovation and maintenance, museum, Tiffney shade, toiletries,
multipurpose hall, smarak, garden, canteen. Out of these Aundh Museum has received
Rs. 75.11 lakhs of local level of tourism development funds and Rs. 166.40 lakhs
from regional tourism development funds of Government of Maharashtra. Rs. 36.96
lakhs allotted to Vadgaon for Jairamswami Temple, Rs. 30.23 lakhs to Mauje Bhosare
for Prataprao Gujar smarak, Rs. 25.49 lakhs to Katgun the birthplace of Mahatma
Phule and Rs. 4.62 lakhs to Mayani bird Sanctuary. However, Rs. 314.96 lakhs
means 92.96% of actual money spent of sanctioned amount
Data Analysis
Shivaji University, Kolhapur 144
Patan taluka has received Rs. 183.01 lakhs as tourism development funds to undertake
projects such as construction of roads, repair and maintenance, safety railing. Out of
these Rs. 50.00 lakhs for Dhareshwar along with this Rs. 25.00, lakhs allotted through
regional tourism development funds. Rs. 3.17 lakhs for Koynanagar from local
tourism development funds, Rs. 6.97 lakh to Shri Skshetra Valmiki, Rs. 25.00 lakhs to
Banpuri, Rs. 12.00 lakhs to Koyananagar. Tourism budget sanctioned to Marul
Haveli’s Bahuteshwar Temple was Rs. 31.59 and Rs. 2.95 lakhs. Rs.16.74 lakhs to
Ramghal, Rs. 7.41 lakhs to Ozarde Waterfall and Rs. 2.18 Banpuri Naikeba temple.
However, total actual spending is Rs. 78.67 lakhs from sanctioned amount which is
21.33% lesser than budgeted. It is because of some work is in progress.
Rs. 122.74 lakhs sanctioned to Satara Taluka from tourism development funds to
undertake projects such as construction of roads, public toiletries, maintenance of
surroundings, renovation. Out of these Rs. 22.11 lakhs sanctioned to Thoseghar from
local tourism budget and Rs. 17.00 lakhs from regional tourism development budget.
Sajjangarh received Rs. 32.39 lakhs; Kas received Rs. 25 lakhs from regional tourism
development funds, Rs. 15.00 lakhs to Dhawadshi, and Rs. 11.24 Yawateshwar.
However, 87.48% of total actual amount spent for Satara Taluka, which are 12.52%
lesser than sanctioned funds. It is because of some work is in progress.
For Mahabaleshwar Tourism development funds sanctioned of Rs. 90.99 lakhs to
construct road, boating, safety wall, fortification, repair and renovation. Out of these
Rs. 47.99 lakhs allotted to Pratapgarh from local tourism development funds and Rs.
25.00 lakhs from regional tourism development funds. Rs. 18.00 lakhs allotted to
Tapola. However, 57.73% of amount only spent for Mahabaleshwar Taluka, which is
42.27% amount, is yet to be spent as work is in progress.
Karad taluka received Rs. 80.00 lakhs for tourism development and has undertaken
projects such as construction of roads, renovation. Out of these Rs. 40.00 lakhs, each
to Agashiv caves and Pal. However, 93.46% amount spent for Karad Taluka which is
6.54% lesser than actual sanctioned amount.
Koregaon taluka has received budget of Rs. 62.49 lakhs for tourism development
from local tourism development funds to conduct number of projects such as
construction of rest house, road, SPV solar system, garden. Out of these Rs. 47.17
lakhs allotted to Chavaneshwar temple Karanjkhop and Rs. 15.32 lakhs to Kalyangarh
Data Analysis
Shivaji University, Kolhapur 145
Nandgiri temple. However, 78.99% total actual amount spent at Koregaon, which is
21.01% lesser than sanctioned budget. However, Nandgiri project is yet to be
completed.
Wai taluka received Rs. 30.22 lakhs for tourism development to undertake projects
such as construction of roads, renovation, and maintenance. Out of these Rs. 5.56
lakhs allotted for Vageshwari temple Menwali, Rs. 5.56 lakhs for Nana Phadnis Wada
Rs. 19.10 lakhs to Narsinh Temple Dhom. 45.86% total amount spent for Wai Taluka
which is 54.14% lesser than actual allotted funds. However, all projects are in
progress.
Phaltan taluka received only Rs. 10.66 lakhs to Santoshgad for tourism development
and has undertaken construction of road. 97.74% of amount spent for Phaltan Taluka
and the project is in progress.
Rs. 9.90 lakhs budget allotted to Maan taluka Mauje Kharkhel, Santaji Ghorpade
Smarak from local tourism development funds to construct road and Smarak. The
Maan taluka has utilized entire budget sanctioned for the tourism development.
Rs. 7.78 allotted from local tourism development funds to Bamnoli taluka Jaoali to
undertake projects such as construction of road and rest house. The entire budget has
utilized for the development of Bamnoli.
Khandal taluka received least share of local tourism development funds i.e. Rs. 3.70
lakhs to Naygao, a birth place of Savitribai Phule to undertake construction of road
and Smarak. Khandal taluka utilized only 90.54% of sanctioned tourism budget which
is 9.46% lesser than actual sanctioned funds.
The table reveals that Jaoli, Maan taluka utilized entire sanctioned budget, followed
by 97.74% of utilization in Phaltan, 92.96% in Khatav, 90.54% in Khandala, 87.48%
in Satara, 78.67% in Patan, 78.99% in Koregaon, 57.73% in Mahabaleshwar, 46% in
Karad and 45.86% in Wai. The work in taluka viz. Patan, Khatav, Koregaon,
Mahabaleshwar, Wai, Phaltan and Satara is in progress.
It is concluded that Patan and Khatav taluka have larger share of tourism development
funds. It is observed that more than merit of tourist destination, local political leaders
makes large difference in utilizing funds. Satara being district Head Quarter and
having many places worth seeing has not allotted enough funds, which may show
lack of political will. It was also found that though sanctioned amount was not
Data Analysis
Shivaji University, Kolhapur 146
sufficient to develop destination yet much of the amount was not utilized and so
returned back.
Distribution of Funds on the Basis of Nature of Destination
Following table shows allotment and expenditure of tourism budget for the year 1999-
2000 to 2010-11as per nature of different tourist destinations in Satara district.
Generally, tourism budget sanctioned for the development of worth seeing destination
that may attract large tourist flow viz. Historical Monuments, Forts, Temples, Caves,
Pilgrimage Centre, Museum, Waterfall, Lake/Reservoir, Smarak and Sanctuary. This
distribution is discourse in following table.
Table 4.2.1.4Allotment and Expenditure of Tourism Budget as Per Nature of Destination
(Rs. in lakhs)
Sr. Type of DestinationBudget
Sanctioned
% allottedfrom totalamount
Actualamount spent
% ofsanctioned
amountspent
1. Historical Monuments 149.36 15.74 107.19(WP)* 71.77
2. Forts 57.82 6.09 47.57(WP)* 82.273. Temples 70.45 7.43 31.09(WP)* 44.134. Caves 71.55 7.54 47.90(WP)* 66.955. Pilgrimage Centre 143.5 15.13 134.39 93.656. Museum 241.51 25.46 238.24 98.657. Waterfall 58.52 6.17 58.4 99.798. Lake/Reservoir/Nature 43 4.53 41.58 96.79. Smarak 30.23 3.19 14.42 47.710. Sanctuary 82.79 8.73 67.32 81.31
Total 948.73 100 788.1 83.07Source: Figures taken from District Planning Department, Satara andorganized/compiled by researcher into nature/type of tourist destination*WP- work in progress
Table 4.2.1.4 inferred that 25.46% amount sanctioned to Museum, 15.74% to
historical monuments, 15.13% to pilgrimage centers, 8.73% to Sanctuary, 7.54% to
Caves, 7.43% to temples. Very meager amount is sanctioned for Waterfall i.e. 6.17%,
6.09% to forts, 4.53% to Lakes, reservoir/nature and 3.19 % to Smarak.
Data Analysis
Shivaji University, Kolhapur 147
Actual total amount spent is 83.07% of total allotted tourism budget on tourism
development on various types of destinations in Satara district. On individual heads
it was found that 99.79% of sanctioned amount was spent on waterfall,
98.65 on Museum, 96.70% on lakes, and 93.65% on pilgrimage, 82.27% on forts and
71.77% on historical monuments. Temples, Forts, Smaraks have been sanctioned
lesser amount. However, much lesser amount is spent i.e. 44.13 % on Temples,
66.95% on Caves and 47.70% on Smarak. The work is in progress at Forts, temples,
caves and historical monuments. Governments focus is mainly on museum, historical
monuments, and pilgrimage centers in allotment of tourism funds.
Allotments of Tourism Development Funds under ‘C’ Class to Satara District.
Following table shows Tourism Development Funds allotment and actual expenditure
since 1999-2000 to 2010-2011 at Satara district under ‘C’ class, column number 7
shows percentage of change from previous year.
Table 4.2.1.5Year-wise Funds Allotment and Actual Expenditure on Tourism Development from1999 to 2011.
(Figures are in rupees lakhs)Sr.
Year FundsAllotted For
TourismDevelopmentIn Year (Rs.
In Lakhs)
%Growth
Expenditure
%Growth
Gap %Chan
ge
1 2 3 4 5 6 7
1 1999-2000 15.00 - 15.00 - - -2 2000-2001 17.00 13.33 16.80 12 0.20 -3 2001-2002 - - - - - -4 2002-2003 - - - - - -5 2003-2004 18.03 - 18.03 INF* - -6 2004-2005 - - - - - -7 2005-2006 25.45 - 24.39 INF* 1.06 -8 2006-2007 83.50 228.09 77.96 219.63 5.54 4489 2007-2008 30.00 -64.07 30.00 -61.51 0.00 0.0010 2008-2009 125.94 319.8 120.22 300.73 5.72 419.811 2009-2010
114.06 -9.43 66.41 44.75 47.65733.0
412 2010-2011 110.00 -3.56 68.83 3.64 41.17 13.60
Total 488.95 387.81 101.14Source: District Planning Department, Satara* INF-infinite
Data Analysis
Shivaji University, Kolhapur 148
Table 4.2.1.5 depicts the allocation of funds from the district authority for the
development of tourism places of ‘C’ class from 1999 to 2011.
Except the year 2001-2002, 2002-2003 and 2004-2005 the funds has been allocated
for the development of tourism places.
Column number 6 titled gap depicts figures, which are drawn from column number 2
minus column 4 shows the difference between allotted funds and actual expenditure.
In 2001-2002, 2002-2003 and 2004-2005 the fund allotment is zero thus next year
change in % of the growth is not shown.
There is no uniformity in allocation of funds and actual expenditure.
In 1999-2000, there was no gap between budget sanctioned and actual amount spent,
in 2000-2001 there was marginal gap of Rs. 0.20 lakhs and 2001-2002, 2002-2003
there was no budget. In 2003-2004, entire budget was spent, 2004-2005 there was no
budget. In 2005-2006, the gap was Rs. 1.06 lakhs, which increase to greater extent i.e.
Rs. 5.54 lakhs in 2006-2007. In 2007-2008, entire budget was spent. Since 2008 to
2011, there was a gap of Rs. 5.72 lakhs, Rs. 47.65 lakhs, and Rs.41.17 lakhs
respectively.
The allotment of funds for tourism development has risen substantially from 2008-
2009. Until date, government has spent almost 80% of sanctioned amount for the
tourism development.
Both budget allotment and actual expenditure is increasing at greater space since 1999
to 2011.
In 2009-10 and 2010-11 gap is higher i.e. 47.65% and 41.17% respectively. In those
years’ Government spent only 60.36 % of sanctioned amount on tourism
development. This leads to find out the reason behind less spending as compare to
budget.
It has observed that there is no consistency in the sanctioning of funds for tourism
development. Irrespective of lesser amount, sanctioned local bodies could not spend
the same amount and refund is reported of more than 40% of the sanctioned amount.
This draws attention on Government’s planning and implementation.
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Allotment of Regional Tourism Development Funds to Satara District
Following table shows the distribution of allotted funds and actual expenditure for
Satara district tourism development. The funds have been allotted to respective
destinations since 1999 and/or to 2011. However the status for the development is
equally important to expect the potential of tourism that depict in the following
table.
Table 4.2.1.6Distribution of Funds Available Under Regional Tourism Development since 2004-5and/or to 2010-11
(Figures are in rupees lakhs)
SrName of Tourist
DestinationAllotted
fundsActualSpent
SurplusStatus of
Development
1 Pal, Karad 40.00 39.08 0.92 3 Jobs Completed2 Dhareshwar(Diwashi),
Tal Patan 12.00 11.91 0.09 3 Jobs Completed
3 Valmiki PaneriSurroundings Tal. Patan
25.00 24.69 0.31 2 Jobs Completed
4 Koyna Wild LifeSanctuary
50.00 34.88 15.12
3J 3 Jobs Completed,Construction of Suspension
bridge at Ozarde Falldropped because of
permission regretted due totech problem. Thus surpluswith interest deposited into
government Treasury.5 Pratapgarh Tal.
Mahabalshwar25.00 24.80 0.20 3 Jobs Completed
6 Thoseghar Tal. Satara 17.00 17.00 0.00 4 Jobs Completed7 Kas Lake Surroundings
Tal. Satara25.00 15.80 9.20
2JobsUncompleted. Surplusamount deposited to
government by SataraNagarparishad
8 KoynanagarSurroundings Tal. Patan
25.00 24.82 0.18 2 Jobs Completed
9 Aundh Tal. KhatavConstruction of safetywall at Aundh to YamaiDevi Temple Ghat
28.40 26.53 1.87surplus deposited to
Government
10 AundhMuseumRenovation anddevelopment ofsurroundings
100.00 100.00 - 9 Jobs Completed
Data Analysis
Shivaji University, Kolhapur 150
Total ( 1 to 10)Amount Received in2004-2005
347.40 319.51 27.89
11 Bhavani Museum,Aundh renovation likefixing poly carbonatesheet, colouring ofnames at porch, fixingof MRP Domb onbuilding, making corehall for strong room,painting of Entrance
5.24 5.10 0.14
12 Repair of statue atsurrounding of BhavaniMuseum, fixing of newgate, fixing of pavingblock, grill, breaking ofold store building,painting of varandha,making of Guardroomfor pay and parking
6.15 6.05 0.10
All jobs are completed andsurplus amount returned to
government.
13 Tar road at parkingarea, windows atCanteen and Tiffinshade, making of letterat Entrance, soil andgrill for garden,leveling of ground,shifting of scrap,removal of unnecessaryconstruction.
7.23 7.23 0.00
14 Construction of waitingroom for tourist atBhavani museum porch
11.24 10.95 0.29
15 Tar road of parking areaat Bhavani Museum,Aundh, windows atcanteen and tiffinshade, soil and grill forgarden, leveling ofground, shifting ofscrap and removal ofunnecessaryconstruction
6.14 6.09 0.05
16 Fixing of two electricalmotor pump andpipeline at BhavaniMuseum area.
2.00 1.57 0.43
Data Analysis
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Total(11-16)Amount Received in 2007-2008
38.00 36.99 1.01
Total amount received fromMaharashtra tourismDepartment.
385.40 356.50 28.90
Source: District Planning Department, Satara
Table 4.2.1.6 shows that Satara district received Rs. 385.40 lakhs for tourism
development, Out of this Rs. 347.40 received in 2004-2005 and Rs. 38.00 lakhs in
2007-8. There is gap in budgeted amount and actual expenditure. The total amount
has been distributed to Aundh Museum in Khatav taluka until 2010-11 is Rs. 166.40
lakhs. Patan Rs.112.00 for Valmiki.Dhareshwar and Ozarde(Waterfall). Rs. 40 lakhs
are sanctioned to Karad, for Pal pilgrimage centre. In Satara, taluka for the
development of Thoseghar and Kas Rs. 42 lakh has been sanctioned. Rs. 25 lakhs to
Mahabaleshwar for Pratapgarh (Fort). Same jobs undertaken for the tourism
development at Bhavani Museum Aundh are shown twice. It is observed that tourism
needs are not met yet under number of heads, the said amount is not used, and surplus
amount is returned. It can be inferred that concerned department is unable to design
and implement right tourism development policy for the district. There are no special
funds available for tourism development like Kokan development, Marathwada and
Vidharbh Development Package to Satara district in 2011.
It concludes that tourism development funds are regularly allotted to Satara district
thorugh Zilha Parishad under ‘C’ category being Satara as a district place. Funds are
usually spent on basic and tourist infrastructure of the destinations. It is found that
funds are not sanctioned by considering the need of destination but through influence
of political force. Without any marketing strategy or marketing planning funds
allotment is vain. Thus, need arises to make proper marketing planning to promote
destination like Satara. Identification of need of destination is vital for effective
marketing planning. Need of destination is determined by number of factors. But one
important is demographic profile of stakeholder viz. tourist, hoteliers, tour operators.
Researcher has insight into demographic profile of stakeholders of Satara district in
the next section.
Data Analysis
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Section II
4.2.2 Demographic Profile of Stake Holders:
The section details the demographic profile of stakeholders i.e. tourist, hoteliers and
tour operators who put the effort directly and indirectly in the promotion of tourist
destination. The demographic profile of respective stakeholders presents in 3 parts as
demographic profile of tourist, demographic profile of hoteliers and demographic
profile of tour operators with their respective interpretation.
4.2.2.1 Demographic Profile of Tourist:
This part discusses the tourist profile of 326 samples who have visited the 10 well-
known destinations viz. Aundh, Mahabaleshwar, Panchgani, Pratapgarh, Wai,
Sajjangarh, Thoseghar, Kas, Ajinkyatara, and Koyna. The tourists’ origin of state,
gender, age group, and occupation reflected in tourist profile.
Distribution of Tourist’s Origin
Following table presents the distribution of sample tourists as per their origin of state.
Tourists are visiting to different locations of Satara viz. pilgrimage place like Aundh,
Wai. Hill stations like Mahabaleshwar and Panchgani, historical fort Pratapgarh,
Ajinkyatara, holy place Sajjangarh, Thoseghar, beautiful flora of Kas and nature
gifted location Koyna. They are from different origins of states like Uttar Pradesh
(UP), Andhra Pradesh (AP), Delhi, Gujarat, West Bengal (WB), Uttaranchal,
Himachal Pradesh (HP), Punjab, Orissa, Karnatak, Rajsthan, and Goa. Some of the
tourists are from other districts in Maharashtra viz. Pune, Mumbai and the like.
Researcher has broadly classified the samples into, within Maharashtra and Out of
Maharashtra. Further Maharashtra category is sub-classified into Maharashtra
excluding Satara district and only Satara district. The distribution of samples is as
follows.
Data Analysis
Shivaji University, Kolhapur 153
Table 4.2.2.1.1Distribution of Sample Tourists as Per Origin of State
(n=326)
Sr.
OriginofTouristSample
NameoTouristLocation
Out of Maharashtra Maharashtra
Tot
al
U.P
.
A.P
.
Del
hi
Guj
arat
W.B
.
Utt
aran
chal
H.P
.
Pun
jab
Ori
ssa
Kar
nata
k
Raj
stan
Goa M
ahar
asht
ra(E
xclu
ding
Sat
ara
and
Sur
roun
ding
)
Sat
ara
Dis
tric
t
1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16.
1. Aundh 27 3 30
2. Mahabaleshwar
1 1 1 1 24 2 30
3. Panchgani
4 1 4 1 24 1 35
4. Pratapgarh
1 3 1 2 121 1 30
5. Wai 2 2 30 3 376. Sajjanga
rh16 14 30
7. Thoseghar
33 33
8. Kas 1 1 1 1 26 30
9. Ajinkya-Tara
1 1 31 1 34
10. Koyna 1 29 7 37
Total 1 3 2 9 1 1 1 1 1 11 1 1 261 32 326
%
0.31
0.92
0.61
2.76
0.31
0.31
0.31
0.31
0.31
3.37
0.31
0.31
80.0
6 9.82
100
Source: Field Data
Table 4.2.2.1.1 reveals the prime focus of outside tourist seems to be national famous
tourist destinations viz. Mahabaleshwar, Panchgani, and Pratapgarh, which is a
Data Analysis
Shivaji University, Kolhapur 154
package tour as such. The tourist from other district in Maharashtra seems focused
more on Thoseghar, Ajinkytara fort, Wai, a famous museum of Aundh, and the like.
Only 10 % of sample tourists found to visit from other states i.e. out of Maharashtra
visit destinations within Satara district. Respondents who visited from other states
were from Uttar Pradesh, Andhra Pradesh, Delhi, Gujarat, West Bengal, Uttaranchal,
Himachal Pradesh, Punjab, Orissa, Karnataka, Rajasthan, and Goa.
However, most of the tourist’s flow (80.06%) is coming from Maharashtra excluding
Satara district, 9.82% from Satara district, (10%) from other states. From Maharashtra
majority of tourist flow is from Pune, Mumbai, Sangli, and Kolhapur and among
states Gujarat and Karnataka tourist flow is better compared to other states.
It is inferred that tourists who are visiting well-known hill stations Mahabaleshwar
they are likely to visit nearest tourist location viz. Panchgani, Pratapgarh and Wai.
The few tourists who visit Kas were mainly because the Kas site has entered into
world heritage site. Local tourists are equally visiting the destinations at percentage
of 9.82% of total samples.
Distribution of Tourist Genderwise
Following table reveals the distribution of sample tourists as per gender at different
destinations of Satara. Tourists visit aforesaid locations of Satara belongs to both
genders male and female that reflect in the following table. The percentages are
calculated on total frequency destination-wise.
Data Analysis
Shivaji University, Kolhapur 155
Table 4.2.2.1.2Distribution of Sample Tourists as Per Gender at different destinations of Satara
(n=326)
Sr.
GenderName of TouristLocation in SataraDistrict
Male Female Total
F. % F. % F. %
1. 2. 3. 4. 5. 6. 7.
1. Aundh 16 53.3 14 46.67 30 9.20
2. Mahabaleshwar 23 76.67 7 23.33 30 9.20
3. Panchgani 24 68.57 11 31.43 35 10.74
4. Pratapgarh 27 90.00 3 10.00 30 9.20
5. Wai 30 81.08 7 18.92 37 11.35
6. Sajjangarh 20 66.67 10 33.33 30 9.20
7. Thoseghar 29 87.88 4 12.12 33 10.12
8. Kas 21 70.00 9 30.00 30 9.20
9. Ajinkya-Tara 24 70.59 10 29.41 34 10.43
10. Koyna 32 86.49 5 13.51 37 11.35Total 246 75.46 80 24.54 326 100.00
Source: Field Data
Table 4.2.2.1.2 reveals that males are more than females who visit different locations
of Satara. Out of those Pratapgarh, Wai, Thoseghar and Koyna are more preferred
locations by males compared to females and females has given more preference to
visit Aundh rather than other locations of Satara.
75.46% are male tourist on the contrary female are only 24.54%. At Aundh
destination the gender ratio is nearly equal i.e. 53.33% and 46.67%, at
Mahabaleshwar male are highest i.e.76.67percentage as compared to 23.33% of
female, Panchgani male are 68.57 whereas females are 31.43%. Pratapgarh, Wai,
Sajjangarh, Thoseghar, Kas, Ajinkyatara, and Koyna have found to be male
dominated locations since more than 70% of male found visiting these locations.
These destinations are moreover hilly destinations and require some walking to reach
out.
Data Analysis
Shivaji University, Kolhapur 156
Distribution of Tourist Agewise
Following table presents distribution of sample tourists visited at different
destinations as per their age group. Tourists of different age groups visit Satara to see
the locations. Researcher has sought age groups in six intervals ranging from below
15 years, 15-25 to 55 and above with an interval of 10. This distribution reflects in the
following table. Since no sample interviewed to visit destination having age below 15
years hence the column did not included.
Table 4.2.2.1.3Distribution of Sample Tourists as Per Age Group at different destinations of Satara
(n=326)
Sr
Age Group
Name ofDestination
15-25 25-35 35-45 45-5555&above
Total
F % F % F % F % F % F %
1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13.1. Aundh 4 13.33 2 6.67 6 20 6 20 2 40 30 1002. Mahabalesh
war3 10 9 30 11 36.67 3 10 4
13.33
30 100
3. Panchgani 1 2.86 13 37.14 14 40 6 17.14 1 2.86 35 1004. Pratapgarh 2 6.67 16 53.33 9 30.00 2 6.67 1 3.33 30 1005. Wai 7 18.92 16 43.24 8 21.62 4 10.18 2 5.41 37 1006. Sajjangarh 6 20 6 20 9 30 6 20 3 10 30 1007. Thoseghar 7 21.21 14 42.42 9 27.27 2 6.06 1 3.0 33 1008. Kas 8 26.67 16 53.33 5 16.67 1 3.33 30 1009. Ajinkya-
Tara10 29.41 3. 8.82 10 29.41 6 17.65 5
14.71
34 100
10. Koyna 6 16.22 18 48.65 11 29.73 2 5.40 37 100Total
46 14.11 105 32.21103
31.60 42 12.88 30 9.20 326 100
Source: Field Data
Table 4.2.2.1.3 reveals that tourists are found in all age groups but more tourists found
to be in age group of 25-45, which amounts to 63.81% of total sample tourists.
32.21% of tourists found to be in age group of 25-35 whereas 31.60% of tourists from
age group of 35-45. The age group 15-25 more preferred to visit Thoseghar and
Ajinkytara and the percentage is 21.21and 29.41 respectively. The age group 55&
above has preferred Aundh destination to visit compared to other destinations of
Satara. The age group 45-55 has preferred equally all the destinations of Satara. The
Data Analysis
Shivaji University, Kolhapur 157
age group 25-35 has merely preferred all the destinations of Satara but Pratapgarh is
more preferred followed by other destinations like Koyna, Wai, and Thoseghar.
Distribution of Tourist as Per Occupation
Following table represents the distribution of tourist samples available in respective
tourist destinations of Satara as per their occupation. Tourists are of different
occupations. Researcher has categorized into 13 groups viz. unskilled worker,
unskilled worker, petty traders, shop owners, industrialists with no employees, with 1
to 9 employees, with 10+ employees, self employed professional, clerical salesman,
supervisory level, officer executive junior, middle/semi and students/housewife.
Student and housewife consider in one category since they are not earners. This
sample distribution depicts in following table.
Data Analysis
Shivaji University, Kolhapur 158
Table 4.2.2.1.4Distribution of Tourists Samples at respective tourist destination as Per Occupation
(n=326)
Tot
al
10 3.07
13 3.99
4 1.23
13 3.99
9 2.76
9 2.76
3 0.92
36 11.0
4
24 7.36
31 9.51
54 16.5
655 16
.87
65 19.9
4
326
10 Aun
dh
8 26.6
7
2 6.67
4 13.3
3
2 6.67
4 13.3
36 20
.00
4 13.3
3
30
9 Mah
abal
eshw
ar 2 6.67
5 16.6
7
2 6.67
2 6.67
1 3.33
3 10 1 3.33
2 6.67
4 13.3
35 16
.67
3 10 30
8 Panc
hga
ni
5 14.2
91 2.
86
4 11.4
3
1 2.86
4 11.4
36 17
.14
5 14.2
9
9 25.7
1
35
7 Prat
apg
arh
2 6.67
1 3.33
2 6.67
2 6.67
2 6.67
8 26.6
7
2 6.67
2 6.67
3 10 2 6.67
4 13.3
3
30
6 Wai
2 5.41
2 5.41
2 5.41
3 8.11
2 5.41
4 10.8
1
3 8.11
5 13.5
14 10
.81
10 27.0
3
37
5 Sajja
nga
rh
3 10 1 3.33
1 3.33
5 16.6
7
3 10 1 3.33
5 16.6
73 10 8 26
.67
30
4 Tho
segh
ar
3 9.09
4 12.1
212 36
.36
7 21.2
1
7 21.2
1
33
3 Kas
1 3.33
1 3.33
9 30 1 3.33
7 23.3
34 13
.33
5 16.6
7
2 6.67
30
2 Aji
nkya
-T
ara
1 2.94
1 2.94
1 2.94
1 2.94
4 11.7
615 44
.12
11 32.3
5
34
1 Koy
na 1 2.
701 2.
701 2.
701 2.
701 2.
70
2 5.41
8 21.6
2
5 13.5
17 18
.92
3 8.11
7 18.9
2
37
Sr.
1. 2. 3. 4. 5. 6. 7. 8. 9. 10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
Tot
al
F % F % F % F % F % F % F % F % F % F % F % F % F %
Nam
e of
Des
tinat
ion
Occ
upat
ion
Gro
up
Uns
kill
ed W
orke
r
Skill
ed W
orke
r
Petty
Tra
ders
Shop
Ow
ner
Indu
stri
alis
t w
ith
noE
mpl
oyee
s
With
1-9
Em
ploy
ees
wit
h 10
+ E
mpl
oyee
s
Self
E
mpl
oyed
Prof
essi
onal
Cle
rica
l/Sa
lesm
an
Supe
rvis
ory
Lev
el
Off
icer
/Exe
c Ju
nior
Off
ice
Exe
.M
iddl
e/Se
mi
Stud
ent/
Hou
sew
ife
Source: Field Data
Data Analysis
Shivaji University, Kolhapur 159
Table 4.2.2.1.4 reveals that there is relationship between occupation and tourism.
Salaried tourists are of higher category found to have more tourism as compared to
entrepreneurs and petty traders. Self-employed professionals are found to enjoy
tourism.
53.37% of total sample tourists are officers and executive (Junior and Senior),
students and housewives occupation category followed by 11.04% self-employed,
9.51% supervisory level and 7.36% clerical/salesmen, only 6.44% are industrialist.
2/3rd of total respondents of Aundh i.e. 66% are clerical/salesmen, supervisors,
officers/executives (Junior/Middle level), and housewife, followed by unskilled
workers 26.6%, and no self employed sample found as the location is mostly
preferred for pilgrimage. Except petty traders all respondents were of all categories in
almost equal number found visiting Mahabaleshwar since the hill station is preferred
by almost all the occupation category. 82% of sample respondents at Panchgani
belong to self employed, clerical/salesmen, supervisory level, officer/executives
(Junior/Middle/Semi) and students/housewife category. Except unskilled workers, all
respondents were of all categories in almost equal number in Pratapgarh since the fort
is preferred as a sight scene by Mahabaleshwar tourists. Except unskilled workers,
petty traders, clerical salesmen were found visiting Wai in almost equal number in
Wai where housewife were maximum (27%) since it is popular pilgrimage centre.
80.4% of tourist visiting Sajjangarh belongs to self employed, clerical/salesmen,
officer executives(Junior/Middle/Semi), students and housewife category. No
Unskilled and shop owners’ category of tourists found to visit Sajjangarh. Mostly
white-collar working class found in Thoseghar. So the waterfall is almost preferred by
white-collar working class of tourist category. Kas is more (30%) preferred by self
employed professionals, followed by 23.33% supervisory levels staff, 16.67% officers
of middle and semi category and lesser by industrialist and business group (higher
income group). At Ajinkyatara 44.12% of the respondents visited were of
officers/Executives middle/semi followed by 32.35% students/housewife category.
Data Analysis
Shivaji University, Kolhapur 160
At Koyna 59.42%, respondents belong to clerical/salesmen, officer executives junior
and student’s occupational category. Clerical/salesmen, junior executives, and student
mostly prefer the waterfall at Koyna.
4.2.2.2 Demographic Profile of Hoteliers:
There are various categories of hotels operating in Satara district. The researcher hasinterviewed 40 samples. This part discourse the categories, year of establishment andspeciality in food served.
Distribution of Hotels as Per Location
Following table presents the distribution of hoteliers respondents. Researcher has
selected 40 respondents from the important locations of Satara where hotel business is
operated in a great scale compared to other destination of Satara. The distribution is
shown in the following table.
Table 4.2.2.2.1Distribution of Hoteliers Samples
(n=40)
Sr.
Name ofLocation
Frequency Percentage
1. 2. 3.1 Satara 10 252 Wai 5 12.53 Koyna 5 12.54 Mahabaleshwar 10 255 Panchgani 10 25
Total 40 100Source: Field Data
Table 4.2.2.2.1 reveals that total hoteliers respondents are 40. Majority of the
respondents i.e. 25% are each from Mahabaleshwar, Panchgani, and Satara. The rest
of the respondents i.e. 12.5% are from Wai and Koyna each.
Data Analysis
Shivaji University, Kolhapur 161
Distribution of Hotels as Per Category and Establishment
Following table presents the hotelier respondents according to their category wise
establishment. (Percentages are worked out category wise).
Table 4.2.2.2.2Hoteliers Samples as per their Category and year of Establishment
(n=40)
Sr
Year ofEstablishmentCategory
1960-19701970-1980
1980-2000
2000&above Total
F % F % F % F % F %
1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11.1. Resort 1 20 0 0 3 60 1 20 5 1002. Star Graded 2 50 0 0 2 50 4 1003. Downtown 2 9.09 2 9.09 5 22.73 13 59.09 22 1004. Other 1 11.11 0.00 0.00 8 88.89 9 100
Total 6 15 2 5 8 20 24 60 40 100Source: Field Data
Table 4.2.2.2.2 depicts that majority i.e. 60% hotels are established after 2000 and
only 15% are prior to 1970 in Satara district. In Resort category majority (60%) of
resorts established during 1980-2000, 20% in each during ‘1960-1970’ and ‘2000 and
above’. 50% Star graded hotels established prior to 1970 and 50% after
2000. In Downtown category, most of the hotels i.e. 59.09% established after
2000 and 22.73% in 1980-2000 and rest of hotels established prior to 1980. In the
'other category' majority i.e. (88.89%) of hotels are established after 2000 and rest i.e.
11.11% prior to 1970.
Data Analysis
Shivaji University, Kolhapur 162
Distribution of Hotels as Per Spciality in Serving of Food
Following table presents hoteliers as per speciality in food. Availability food is
indispensable at tourist destination to attract and hold the tourist. The availability of
variety as vegetarian, non-vegetarian, Gujarathi Thali, Continental is depicted in the
following table.
Table 4.2.2.2.3Hoteliers as per their Specialty in Food
(n=40)
Sr. Name of Specialty F Percentage1. Vegetarian 7 24.142. Non-Vegetarian 0 0.003. Gujarati 0 0.004. Continental 0 0.005. Vegetarian and Non-vegetarian 22 75.86
Total 29 100.00Source: Field Data
Table 4.2.2.2.3 infers that in ‘speciality in food’ 75.86% hotels serves both vegetarian
and non-vegetarian food whereas rest 24.14% hotels serve pure vegetarian food.
4.2.2.3 Demographic Profile of Tour Operator:
This part depicts the tour operator’s profile on the basis of their type of formation and
establishment.
Distribution of Tour Operators as Per Their Forms of Organisation
Following table represents forms of tour operating organization, i.e. as per their
constitution, proprietary, partnership, private limited and others. The percentages are
worked out as per forms of organization.
Data Analysis
Shivaji University, Kolhapur 163
Table 4.2.2.3.1Forms of Organization
(n=10)
Sr.
Year ofEstablishment
Form ofOrganization P
rior
200
0
%
200-
2005
%
2005
-201
0
%
2010
-on
war
ds
%
Tot
al
1. Proprietary 1 11.11 5 55.56 2 22.22 1 11.11 92. Partnership 0 0 0 0 0 0 0 0 03. Pvt. Ltd 1 100 0 0 0 0 0 0 14. Other 0 0 0 0 0 0 0 0 0
Total 2 20 5 50 2 20 1 10 10Source: Field Data
Table 4.2.2.3.1 reveals that most of the organizations i.e. 90% are proprietary. Out of
them 66.67% organization established prior to 2005 and rest after 2005. There is no
any partnership firm and other type of forms of organization. Only 10% are private
limited who established prior to 2000.
It is found that tourists are visiting Satara mainly from the cities like Pune,
Mumbai, Sangli and Kohapur. People prefer all kinds of destinations with same
zeal and enthusiasm. Salaried people are more preferring Satara. Both male and
female are equally found at Satara and especially they belong to 25 to 45 age-
groups. Hotels of all categories are available in Satara and both type of food is
served. However, tour operators are enough in quantity but they are arranges tours to
take away the local people outside and not to bring the outsiders to Satara. Therefore
there is needed to find out the problems and prospects of tourism sector. So researcher
has studied and analyzed the stakeholders independently in the proceeding sections to
know their niceties. Thus, the first important stakeholder of the tourism sector is
Tourist; researcher has put the effort to know tourist’s niceties in next section tourist
descriptive analysis.
Data Analysis
Shivaji University, Kolhapur 164
Section III
4.2.3 Tourist Descriptive Analysis:
Structured schedule is executed on 326 tourist at ten different places of Satara viz.
Aundh, Mahabaleshwar, Panchgani, Pratapgarh, Wai, Sajjangarh, Thoseghar, Kas,
Ajinkyatara and Koyna were interviewed. This section orate tourists’ perceptions on
15 tourism of products, destination awareness, perception on motivators to tourism,
promotion of tourism, potential to Satara, tourism pattern, pricing of tourism,
satisfaction and importance of tourism services and amenities. The majority of
responses were collected on 5-point likert scales. The said data is analyzed with
statistical tools viz. mean, rank, standard deviations, Spearman’s rank correlation, and
percentages. These detailed analyses are as follows
Perception of Tourist on Attraction of Tourism Product
Distribution of Tourist Genderwise
Following table depicts the perception of sample tourists on attraction of tourist
location in Satara as per their gender. Nature of different tourism products attracts
tourists of both genders male and female. Researcher has considered 15 tourism
products viz. Adventure, Flora, Fauna/Wild Life Sanctuary, Waterfall, Ghats, Hill
Stations, Lake/Reservoir, Scenery Beauty, Valleys, Pilgrimage, Temples, Museum,
Historical Monuments, Forts, and Windmills to know the tourist perception on their
attractions.
Data Analysis
Shivaji University, Kolhapur 165
Table 4.2.3.1Perception of Sample Tourists on Attraction of Tourists Locations as Per Gender
(n=326)
Sr
Gender
Nature ofProducts
Male Female Total
Mean Rank SD MeanRank
SD MeanRank
SD
1. 2. 3. 4. 5. 6. 7. 8. 9. 10.1. Adventure 3.58 13 0.81 3.58 13 0.81 3.58 13 0.81
2. Flora 3.84 9 0.70 3.84 8 0.70 3.84 9 0.70
3.Fauna / Wild LifeSanctuary
3.72 10 0.78 3.72 10 0.78 3.72 10 0.78
4. Waterfall 4.08 3 0.66 4.08 3 0.66 4.08 3 0.66
5. Ghats 3.87 7 0.79 3.87 7 0.79 3.87 7 0.796. Hill Station 4.37 1 0.75 4.37 1 0.76 4.37 1 0.757. Lake/Reservoir 3.90 6 0.79 3.90 6 0.79 3.90 6 0.79
8. Scenery beauty 4.21 2 0.75 4.21 2 0.76 4.21 2 0.75
9. Valleys 3.67 11 0.83 3.67 11 0.83 3.67 11 83
10. Pilgrimage 3.85 8 0.98 3.83 9 0.98 3.85 8 0.98
11. Temples 3.96 5 0.82 3.94 5 0.82 36 5 02
12. Museum 3.53 14 0.89 3.51 14 0.89 3.53 14 0.89
13.HistoricalMonuments
3.67 11 0.87 3.67 11 0.87 3.67 11 0.87
14. Forts 3.97 4 0.80 3.97 4 0.80 3.97 4 0.80
15. Windmills 3.26 15 0.92 3.26 15 0.92 3.26 15 0.92
Correlation Coefficient .996**
Sig. (2-tailed) .000Source: Field Data**. Correlation is significant at the 0.01 level (2-tailed).
Table 4.2.3.1 reveals that the tourists perception about the tourist location at Satara.
Tourism products like hill station, scenic beauty, waterfall and forts attracts them
more compared to windmill, museum, adventure, valleys and historical
monuments.
Gender wise there is no difference in perception of tourism product.
To investigate into the depth of analysis researcher has calculated Spearman’s
rank correlation coefficient of perception of male and female for tourism products.
The score is 0.996, with ‘P’ value 0.000, which is significant at 0.01 levels (2-tailed).
Data Analysis
Shivaji University, Kolhapur 166
Distribution of Tourist Agewise:Following table reveals the perception of sample tourist on attraction of tourists’location as per their age. Tourist of different age groups carries different perceptionon tourism products. The researcher has considered previously mentioned 15 tourismproducts for the same. There are 5 age groups viz. 15-25, 25-35, 35-45, 45-55 and 55and above that considered to check the different perception on tourism products.These data collected through 5-point likert scale and analyzed with different statisticaltools as above-mentioned table. The distribution of total sample tourist as per the agegroup is presented in following table.Table 4.2.3.2Perception of Sample Tourists on Attraction of Tourists Locations Age wise
Sr.
Age Group
Name ofProduct
15-25 25-35 35-45 45-55 55&above
Mea
n
Ran
k
SD Mea
n
Ran
k
SD Mea
n
Ran
k
SD Mea
n
Ran
k
SD Mea
n
Ran
k
SD
1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16.1. Adventure 3.58 13 0.8 3.58 13 0.81 3.58 13 0.8 3.58 13 0.81 4 13 0.812. Flora 3.82 9 0.7 3.82 9 0.72 3.83 9 0.7 3.84 9 0.7 4 8 0.73. Fauna / Wild
LifeSanctuary
3.72 0 0.8 3.72 10 0.78 3.72 10 0.8 3.72 10 0.78 4 10 0.78
4. Waterfall 4.09 3 0.7 4.09 3 0.68 4.08 3 0.7 4.08 3 0.66 4 3 0.665. Ghats 3.87 7 0.8 3.87 7 0.79 3.87 7 0.8 3.87 7 0.79 4 7 0.796. Hill Station 4.33 1 0.8 4.34 1 0.76 4.37 1 0.8 4.37 1 0.75 4 1 0.767. Lake/Reservoi
r3.89 6 0.8 3.89 6 0.81 3.9 6 0.8 3.9 6 0.79 4 6 0.79
8. Scenerybeauty
4.16 2 0.8 4.16 2 0.75 4.2 2 0.8 4.21 2 0.75 4 2 0.76
9. Valleys 3.67 11 0.8 3.67 11 0.83 3.67 11 0.8 3.67 11 0.83 4 11 0.8310. Pilgrimage 3.83 8 1 3.84 8 0.98 3.84 8 1 3.85 8 0.98 4 8 0.9811. Temples 3.94 5 0.8 3.96 5 0.82 .96 0.8 3.96 5 0.82 4 5 0.8212. Museum 3.51 4 .9 3.52 14 0.9 3.52 4 0.9 3.53 14 0.89 4 14 0.8913. Historical
Monuments3.67 11 0.9 3.67 1 0.87 3.67 1 0.9 3.67 1 0.87 4 11 0.87
14. Forts 3.97 4 0.8 3.97 4 0.83 3.97 4 0.8 3.97 4 0.8 4 4 0.815. Windmills 3.26 5 0.9 3.26 15 0.92 3.26 15 0.9 3.26 15 0.92 3 15 0.92Correlation Coefficient age group 15-25 and 25-35 1.000**Sig.(2-tailed) 0.00Correlation Coefficient age group 15-25 and 35-45 1.000**Sig.(2-tailed) 0.00Correlation Coefficient age group 15-25 and 45-55 1.000**Sig.(2-tailed) 0.00Correlation Coefficient age group 15-25 and 55 and above .999**Sig.(2-tailed) .000
Source: Field Data**. Correlation is significant at the 0.01 level (2-tailed).
Data Analysis
Shivaji University, Kolhapur 167
From the 4.2.3.2 table inferred that tourism product such as hill station, scenic beauty,
waterfall and forts attract more to the tourists irrespective of their age group. The
tourism products viz. windmill, museum, adventure, valley, and historical monuments
attract lesser to the tourists irrespective of their age group.
The Spearman’s rank correlation coefficient of perception for tourism products across
different age group is 0.999, with ‘P’ value 0.00, which is significant at 0.01 levels (2-
tailed).
Motivators to TourismFollowing table shows the opinion of sample tourist on motivators to tourism. Peoplego for tourism for different purposes. It is observed that different situations motivatepeople for tourism. Researcher has considered 10 situations that motivates fortourism as motivators’ viz. Availability of Financial Resources like Money, Leisure toreduce the stress, Propensity to Pleasure, More Occasions for Special Gatherings,Influence of Western Culture, Promotion in employment, Cost Effective TransportSystem, Time Saving Transport System, Sponsorship from Employer, Changes inDomestic Culture and asked to the total sample of tourists to assign the ranks for thesame from 1 to 10 on priority basis. This data is observed with concentratedfrequencies area that is put forward in table below.
Table 4.2.3.3Opinion of Sample Tourists on Motivators to Tourism
(n=326)
Sr.
Rank Frequency
Name of Motivator1 2 3 4 5 6 7 8 9 10
Total
1 2 3 4 5 6 7 8 9 10 11 121. Availability of Financial
Resources Like Money31 12 68 29 5 4 2 1 1 14 167
2. Leisure to Reduce The Stress 97 100 32 3 3 3 1 1 0 2 2423. Propensity to Pleasure 140 85 37 9 2 1 0 0 1 1 2764. More Occasions for Special
Gatherings26 19 21 29 9 6 7 6 3 1 127
5. Influence of Western Culture 3 9 6 10 21 6 6 10 3 5 796. Promotion in Employment 1 2 2 3 6 11 7 6 11 7 567. Cost Effective Transport
System3 4 5 4 14 19 17 3 2 0 71
8. Time Saving Transport System 0 1 7 9 11 7 9 18 5 2 69
9. Sponsorship from Employer 1 4 0 7 3 4 7 1 1 0 8
10. Change in Domestic Culture 15 9 12 12 11 7 6 5 2 8 87
Source: Field Data
Data Analysis
Shivaji University, Kolhapur 168
Table 4.2.3.3 reveals that money, leisure, pleasure and gatherings motivates mainly to
the tourist for tourism in Satara.
Table orate that prime motivators to tourism are propensity to pleasure, leisure to
reduce the stress and availability of financial resources like money as the frequency of
respondents is concentrated in this area. The rest factors do not carry much
importance in tourism. Thus, these three main factors need to focus in designing
tourism-marketing strategies followed by ‘more occasions for gathering’.
Distribution of Tourist as Per Travel Package
Following table depicts the distribution of respondents based on travel package
obtained in respective destinations of Satara. People visit to different tourist
destinations through tourism packages, which are generally organized by tour
operators. Researcher is interested to know preference of tourist who visits previously
mentioned locations of Satara through tour packages. Due to dichotomous nature of
question, the collected data has been analyzed using percentages. The opinion of
sample tourists is open in following table.
Table 4.2.3.4Distribution on the Basis of Travel Package Obtained by Tourist Samples fromdifferent places of Satara
(n=326)
Sr.
Opinion
Name of PlacesYes % No %
1. 2. 3. 4. 5.1. Aundh - - 30 1002. Mahabaleshwar - - 30 1003. Panchgani - - 35 1004. Pratapgarh - - 30 1005. Wai - - 37 1006. Sajjangarh - - 30 1007. Thoseghar - - 33 1008. Kas - - 30 1009. Ajinkya-Tara 17 50 34 10010. Koyna - - 37 100
Total 17 5.21 326 100Source: Field Data
Table 4.2.3.4 reveals tourists have least preference for travel package to visit Satara.
Data Analysis
Shivaji University, Kolhapur 169
5.21% of the tourists have enjoyed tourism through travel package to visit Ajinkyatara
locations of Satara. Further, these tourists have travelled to Kas, Sajjangarh, and
Thoesghar. Majority of tourists ie 94.79% have not traveled by package tour to visit
the destinations in Satara. Thus, tourists are more preferring independent tour plan
rather than travel package. It has also not observed in Satara district that tourist visit
destinations through travel packages. The observations may be because of less
number of samples of tour operator specifically out of Satara or it might be that tour
operator outside Satara and Maharashtra did not offer any tourism product of Satara.
Tourist Travel Pattern
Following table shows the distribution of travel pattern of sample tourists of
different places of Satara. Tourist travel alone, with family and may be in-group.
The table below narrates the description of travel pattern of total tourist samples. The
collected data is analyzed with the help of percentage.
Table 4.2.3.5Distribution of Travel Pattern of Sample Tourists of different places
(n=326)
Sr.
Travel Pattern
Name of Places
Alone Family Group
TotalF % F % F %
1. 2. 3. 4. 5. 6. 7. 8.
1. Aundh 2 6.67 18 60 10 33.33 302. Mahabaleshwar 0 0 22 73.33 8 26.67 303. Panchgani 2 5.71 27 77.14 6 17.14 354. Pratapgarh 0 0 13 43.33 17 56.67 305. Wai 2 5.41 18 48.65 17 45.95 376. Sajjangarh 0 0 20 66.67 10 33.33 307. Thoseghar 0 0 13 39.39 20 60.61 338. Kas 1 3.33 26 86.67 3 10.00 309. Ajinkya-Tara 0 0 4 11.76 30 88.24 3410. Koyna 0 0 19 51.35 18 48.65 37
Total 7 2.15 180 55.21 139 42.64 326Source: Field Data
Data Analysis
Shivaji University, Kolhapur 170
Table 4.2.3.5 inferred those tourists prefer to visit Satara with family and group.
Tourist products like forts and waterfall are more likely to visit with groups and
pilgrimage, hill stations and scenic beauty is preferred to visit with family.
Visiting tourist destinations with family and group is more preferred than individual
visits since 55.21% respondents found visited destinations with family followed by
group 42.64% and alone (individual) visits 2.15%. The tourists who have visited
Aundh out of which 60% tourist visited with family and 33.335 visited with group.
The tourists who visited hill stations Mahabaleshwar, out of which 73.33% visited
with family and 26.67% with groups. Tourist who visited Panchgani, out of that
77.14% visited with family and very few i.e. 17.14 visited with group. Tourist who
visited Sajjangarh, out of which 66.67% visited with family and 33.33% visited with
groups. Tourist who visited Kas preferred mainly go with their family and the
percentage is 86.67%. Tourists who visited Ajinkyatara a well-known fort of Satara,
out of that majority visited with group and the percentage is 88. 24% and very few
11.76% visited with family.
Distribution of Tourist as Per their Group Size
Following table shows the distribution of sample tourists visited different destinations
as per their group size. Tourists are likely to enjoy some of the destinations with
group. Researcher is interested to know the size of group with which tourist visited
Satara to see the different locations as Aundh, Mahabaleshwar, Panchgani,
Pratapgarh, Wai, Sajjangarh, Thoseghar, Kas, Ajinkyatar and Koyna. Previous table
evident that tourist travels in-group. The percentages are used for analysis of data and
calculated row-wise. The data is presented in following table. (Figures in bracket are
the percentages drawn on total tourist who visited different destinations of Satara with
group).
Data Analysis
Shivaji University, Kolhapur 171
Table 4.2.3.6Distribution of sample Tourists of different destinations as per their Group Size
(n=139)
Source: Field Data
Table 4.2.3.6 depicts that more groups visits found at Ajinkyatara, Thoseghar, Koyna
and Pratapgarh compared to other destinations of Satara.
Majority 53.2% of tourists visited of which group size was below 10, 28.1% tourists
group size was in between 10-20, 12.9% tourists’ group size was 30-40,
2.88% tourists’ group size was 20-30 and 50 & above each. At Aundh almost all
the tourists who visited with group, their group size is 0-10, at Mahabaleshwar
62.5% tourists’ group size is up to 20. At Panchgani (83.33%), tourist’s group size is
up to 20. At Pratapgarh 94% tourists group size is up to 20, Wai (82%) up to 20,
Sajjangarh almost all up to 20, Thoseghar(90%) up to 20, Kas almost all up to 20,
Ajinkytara majority(56.67%) up to 20 and Koyna 94.4% tourists up to 20 group size.
Thus, almost all the destinations tourist has visited with group size is merely about 20.
The possibility group size is in between 0-20 to visit different locations of Satara.
Sr
Group Size
Name ofPlaces
0-10 10-20 20-30 30-4040-50
50&above
Total
F % F % F % F % F % F % F %
1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15.1. Aundh 10 100 10(7.19) 1002. Mahabales
hwar4 50 1 12.5 337.5 8(5.76) 100
3. Panchgani 2 33.33 3 50 116.7 6(4.32) 1004. Pratapgarh 11 65 5 29 1 5.9 17(12.23) 1005. Wai 6 35 8 47 2 12 1 5.9 17(12.23) 1006. Sajjangarh 3 30 7 70 10(7.19) 1007. Thoseghar 14 70 6 30 20(14.39) 1008. Kas 2 66.7 1 33.3 3(2.16) 1009. Ajinkya-
Tara13 43.33 17 56.67 30(21.58) 100
10. Koyna 9 50 8 44.4 1 5.56 18(12.95) 10011. Total 74 53.2 39 28.1 4 2.88 18 12.9 4 2.88 139(100) 100
Data Analysis
Shivaji University, Kolhapur 172
Distribution of Tourist as Per Purpose of Visit
Following table presents distribution of sample tourists according to their purpose of
visit to the respective destinations of Satara. Tourist may visit destinations with
different purposes i.e. business/conference, enjoying adventure, only for leisure,
religious cause, may be merely enjoying destinations and the recent trend like health
treatment and the like.
Table 4.2.3.7Distributions of Sample Tourists According to their Purpose of Visit
(n=326)
Sr.Purpose of Visit
TotalF. %
1. 2. 3.1. Business/Conference 5 1.532. Culture/Heritage Monuments 2 0.613. Adventure 6 1.844. Leisure 89 27.305. Religion/Pilgrimage 49 15.036. Health Treatment 2 0.617. Friends /Relatives 24 7.368. Tourism 149 45.71
Total 326 100Source: Field Data
Table 4.2.3.7 reveals that Satara destination is more preferred for tourism purpose and
leisure.
Sample tourist visited Satara district for many purposes out of which 45.71% samples
visited purely with purpose of tourism at different locations of Satara, followed by
27.30% samples visited for merely leisure, 15.03% for religion/pilgrimage, 7.36%
accompanying friends and relatives, 1.84% for enjoying adventure, 1.53% for
business/conference and 0.61% each for culture/heritage monuments and for health
treatment.
Distribution of Tourist as Per Mode of Travel
Following table reveals the sample tourists mode of travel to visit the different
destinations of Satara. Tourists have many options to travel like bus, train, plane,
personal car, and two-wheeler and like. The effort has been made in following table to
Data Analysis
Shivaji University, Kolhapur 173
reveal travel mode of total sample tourist who visited the previously mentioned
locations. Percentages are calculated on tourist-visited destination wise.
Table 4.2.3.8Sample Tourists Mode of Travel to Visit the Destination
(n=326)
Source: Field Data* Rent a Vehicle
Table 4.2.3.8 inferred that personal car is more preferred to visit Satara.
68.4% of sample tourists have used personal car to visit different destinations
of Satara. 11.35% tourists use bus as travel mode, 10.14% sample tourist used rental
vehicle, 6.13% samples travelled by Two Wheeler. Train is a made of travel used
by 3.37 % of sample tourist. Personal car as a mode of travel used by tourist at Aundh
86.67%, Koyna 83.78%, Mahabaleshwar 83.33%, Thoseghar 81.82%, and Sajjangarh
73.33%, and Kas 73.33%, Panchgani 62.86% and Wai 48.65%.
However, for Ajinkytara 50% tourists have used rental vehicle and 23.53% have used
personal car. Bus as a mode of transport used at Wai by 35.14% samples, followed by
Ajinkyatara by 20.59%, Pratapgarh 20%, Panchgani 17.14%, 6.06% Thoseghar,
3.33% Mahabaleshwar, 3.33% Kas and 2.7% at Koyna. Very few tourists have used
train as a mode of travel to Kas 16.67%, 14.29% Panchgani, and 3.33% Pratapgarh.
No sample has found who used plane since the facility is not convenient. Two-
Sr.
TouristMode
Name ofPlaces
Bus Train Personal CarTwo
WheelerOther(Pl.Specify)*
Total
F % F % F % F % F % F %
1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13.1. Aundh 26 86.67 4 13.33 30 1002. Mahabalesh
war1 3.33 25 83.33 4 13.33 30 100
3. Panchgani 6 17.14 5 14.29 22 62.86 2 5.71 35 1004. Pratapgarh 6 20 1 3.33 22 73.33 1 3.33 30 1005. Wai 13 35.14 18 48.65 3 8.11 3 8.11 37 1006. Sajjangarh 22 73.33 6 20 2 6.67 30 107. Thoseghar 2 6.06 27 81.82 4 12.12 33 1008. Kas 1 3.33 5 16.67 22 73.33 2 6.67 30 1009. Ajinkya-
Tara7 20.59 8 23.53 2 5.88 17 50 34 100
10. Koyna 1 2.7 31 83.78 3 8.11 2 5.41 37 100Total 37 11.35 11 3.37 223 68.4 20 6.13 35 10.74 326 100
Data Analysis
Shivaji University, Kolhapur 174
wheeler as a mode of travel used by tourist at Sajjangarh 20%, 13.33% Aundh, 8.11%
Wai, 5.88% Koyna, 5.88% Ajinkyatara and 5.71% Panchgani. Rental vehicles is used
for travel at Mahabaleshwar by13.33percentage, at Thoseghar by12.12percentage
samples, 6.67% samples at Sajjangarh, 6.67% samples at Kas, 5.41% Koyna and
Pratapgarh is visited by 3.33% samples.
Distribution of Tourist as Per Length of Stay
Following table shows the distribution of sample tourists’ length of stay at respective
destinations of Satara. People prefer staying at tourist destinations for leisure, comfort
and enough enjoyment. Satara district have few tourist places that do have good
staying arrangements made available preferentially. Few other tourist destinations do
not have staying arrangements at all. Looking towards different forts in Maharashtra
the staying arrangement is not in existing. At few forts scanty arrangements are found
e.g. Fort Panhala (Kolhapur district), the entire chain of forts are worth seen.
Following table traces the length of stay of sample tourist at different destinations.
Tourist stayed different destinations of Satara overnight, day visit and more than two
visits. Parentages are calculated on samples destination wise.
Table 4.2.3.9Sample Tourists Length of Stay at Destination
(n=326)
Source: Field Data
Sr.
Length of Stay
Name of Places
Overnight Day VisitMore ThanTwo Days
Total
F % F % F % F %
1. 2. 3. 4. 5. 6. 7. 8. 9.1. Aundh 30 100 30 1002. Mahabaleshwar 5 16.67 12 40 13 43.33 30 1003. Panchgani 4 11.43 11 31.43 20 57.14 35 1004. Pratapgarh 30 100 30 1005. Wai 4 10.81 21 56.76 12 32.43 37 1006. Sajjangarh 7 23.33 19 63.33 4 13.33 30 1007. Thoseghar 13 39.39 20 60.61 33 1008. Kas 15 50 15 50 30 1009. Ajinkya-Tara 17 50 8 23.53 9 26.47 34 10010. Koyna 9 24.32 24 64.86 4 10.81 37 100
Total 74 22.7 190 58.28 2 9.02 26 100
Data Analysis
Shivaji University, Kolhapur 175
Table 4.2.3.9 depicts that Day visits are more prefer to visit Satara. Destinations like
Aundh, Pratapgarh, Wai, Sajjangarh, Thoseghar, Kas and Koyna are more preferred
for day visit whereas hill stations like Mahabaleshwar and Panchgani prefer to visit
for staying.
58.28% of total sample tourists have made day visit, 22.7% of total sample tourists
stayed overnight, and 19.02% of total sample tourist stayed more than two days at
destinations of Satara.
57.14% samples tourist who visited Panchgani and 43.33% who visited
Mahabaleshwar stayed for more than two days. 50% samples tourist who visited Kas
preferred to stay overnight and 50% made day visit. Majority of sample tourist who
visited Aundh, Pratapgarh, Wai, Sajjangarh, Thoseghar, and Koyna had day visit. It
could be concluded that majority of destinations of Satara are more preferred for day
visit.
Tourist’s Average Spending
Following table shows the distribution of sample tourists as per their average
spending at respective destinations of Satara. The places like Mahabaleshwar,
Panchgani, Wai, Sajjangarh, and Koyna have developed arrangement of lodging.
Other tourist places of interest do not have professionally managed lodging and
boarding arrangements includes Aundh, Pratapgarh, Thoseghar, Kas, and the like.
Data Analysis
Shivaji University, Kolhapur 176
Table 4.2.3.10Sample Tourists Average Spending per person at Destination
(n=326)
Source: Field Data
Table 4.2.3.10 reveals that destinations Mahabaleshwar, Panchgani, Pratapgarh,
Ajinkytara, and Koyna are visited by tourists’ spending across all groups. Tourists
visited above destinations are preferably found spending in upper spending group i.e.
Rs. 1500-2000 and Rs. 2000 and above per day per person.
Destinations Sajjangarh and Koyna seems to be cost economy since 63.33% of
samples of Sajjangarh and 64.88% of samples at Koyna opine spending less than Rs.
500 per day.
In all 88.95% of sample, tourists’ spending was up to Rs. 1500 per day per person.
Majority i.e. 45.71% sample tourists who visited Panchgani have spent between Rs
1000-1500. Majority 63.33% sample tourists who visited Sajjangarh have spent less
than Rs. 500. 63.64% of sample tourists who visited Thoseghar their spending was
Rs. 500-1000. 93.33% sample tourist who visited Kas their average spending was in
between Rs.500 to Rs.1000. 64.86% sample tourist who visited Koyna have spent less
Sr.
AverageSpending
Nae ofPlaces
< Rs. 500Rs. 500-1000
Rs. 1000-1500
Rs. 1500-2000
Rs.2000&above
Total
F % F % F % F % F % F %
1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13.1. Aundh 10 33.33 16 53.33 4 13.33 30 1002. Mahabalesh
war3 10 12 40 12 10 2 6.67 1 1.33 30 100
3. Panchgani 3 8.57 14 40 16 45.71 1 2.86 1 2.86 35 1004. Pratapgarh 4 13.33 17 56.67 3 10 5 16.67 1 3.33 30 1005. Wai 11 29.73 19 51.35 6 16.22 1 2.7 37 1006. Sajjangarh 19 63.33 3 10 4 13.33 4 13.33 30 1007. Thoseghar 10 30.3 21 63.64 2 6.06 33 1008. Kas 1 3.33 28 93.33 1 3.33 30 100
9. Ajinkya-Tara
12 35.29 5 14.71 17 50 34 100
10. Koyna 24 64.86 4 10.81 7 18.92 1 2.7 1 2.7 37 100Total
97 29.75139
42.64 54 16.56 11 3.37 25 7.67 326 100
Data Analysis
Shivaji University, Kolhapur 177
than Rs. 500. It could be inferred that the Satara destinations can come up as budget
tourist destination.
Sample tourist visited Ajinkyatara, out of which 50% of samples average spending
was Rs2000 and above (as tourists had preferred package tour). Rs 2000 and above
average spending was found with other few sample tourist may be due to their
distance or their long stay.
Percentage of Expenses on Major Items
The major heads of expenses at tourist destinations are accommodation,
transportation, food; shopping and entertainment. Following table presents the
distribution of sample tourists as per their daily expenses for major items.
Table 4.2.3.11Sample Tourists Daily Expenses for Major Items at Destination
(n=326)
Sr
PercentageRange
Major Items
5-15 15-25 25-35 35-45 45-55 55& above Total
F % F % F % F % F % F % F %
1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15.1. Accommodati
on3 4.69 13 20.31 24 37.50 14 21.54 8 12.50 3 4.62 65 19.94
2. Food 10 10.99 34 37.36 27 30.77 13 14.29 1 0.85 6 5.13 91 27.91
3. Transportation4 2.00 9 4.50 21 10.50 22 11.00 16 8.00 129 64.18
201
61.66
4. Entertainment 15 51.72 5 17.24 6 20.69 2 6.90 1 3.45 0.00 29 8.90
5. Shopping 13 68.42 5 26.32 1 5.26 0.00 0.00 0.00 19 5.83
Source: Field Data
Table 4.2.3.11 infers that major chunk of budget is spent on transportation while
amounts to nearly 55% of budget opined by 64% of samples. Around 25-35% of
budget spends on accommodation and food opined by 37.5% and 30.77% of samples
respectively. After transportation, food and accommodation are the major areas of
concerned. 30.77% and 20.31% of sample tourist opined to spend around 15-25% of
budget on food and accommodation respectively. Spending on entertainment and
shopping is on last priority on which 5 to 15% of budget is spent.
Data Analysis
Shivaji University, Kolhapur 178
Staying Arrangement by TouristFor tourist destination, attract tourist to stay. At the destination, different staying
arrangements are available viz. Star Hotel, Budget Hotel, Friends and Relatives. Few
tourists might return without staying as well. Following table presents the distribution
of sample tourists’ staying arrangement at different locations of Satara.
Table 4.2.3.12Distribution of Sample tourist’ Staying Arrangement at Destination
(n=326)
Source: Field Data*Note: the variable not applicable is also housed in ‘other’ category of stayingarrangement.
Table 4.2.3.12 reveals that Budget hotels are more preferred by respondents to stay.
Majority 52.76% of total sample tourist did not stayed at destination. 22.7% tourists
made staying arrangement at budget hotel, 10.43% tourists preferred star hotel and
14.11% preferred to stay at friends/relatives place.
Budget hotels are more preferred to stay at Mahabaleshwar, Panchgani, Pratapgarh
(Mahabaleshwar stay), Wai, Kas (Satara stay), and Koyna. Star hotel is preferred to
Sr.
Name of StayingArrangement
Name ofPlaces
Star HotelBudgetHotel
Friends/Relatives
NotApplicable
Total
F % F % F % F % F %
1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11.1. Aundh 30 100 30 1002. Mahabaleshwar 2 6.67 11 36.67 5 16.67 12 40 30 1003. Panchgani
411.4
314 40 4 11.43 13 37.14 35 100
4. Pratapgarh 3 10 10 33.33 1 3.33 16 53.33 30 1005. Wai
410.8
19 24.32 9 24.32 15 40.54 37 100
6. Sajjangarh4
13.33
1 3.33 1 3.33 24 80.00 30 100
7. Thoseghar 2 6.06 4 12.12 27 81.82 33 1008. Kas 14 46.67 3 10 13 43.33 30 1009. Ajinkya-Tara 17 50 13 38.24 4 11.76 34 10010. Koyna 13 35.14 6 16.22 18 48.65 37 100Total
3410.4
374 22.7 46 14.11 172 52.76 326 100
Data Analysis
Shivaji University, Kolhapur 179
stay by 50% of sample tourist who visited Ajinkyatara and they came through the
package tour to see other destinations of Satara. In Sajjangaarh staying arrangement
is available at free of cost. 38.24% of sample tourists who visited Ajinkytara have
made staying arrangement at their friends and relatives house. 24.32% of sample
tourists who visited Wai have made staying arrangement at their friends and relatives
house. Also 16.67% of sample tourists who visited Mahabaleshwar, 16.22% of
sample tourist who visited Koyna, 11.43% of sample tourists who visited Panchgani,
10% of sample tourists who visited Kas and 3.33% of sample tourists who visited
Pratapgarh (Mahabaleshwar) and Sajjangarh each have made staying arrangement at
friends and relatives house.
Type of Visit by Tourist
Following table depicts the account of first time visitors and repeat visitors in the
respective places of Satara. It is observed that both types of visitors are found in the
tourist flow i.e. first time visitor and repeat visitors. The frequency of tourists’ visit
depends mainly on the destinations worth seeing quality and their satisfaction.
Researcher wants to know the percentages of fresh visitors and repeat visitors to see
the previously mentioned places of Satara. The distribution of total sample tourists is
presented in the following table.
Table 4.2.3.13Type of Visit to the Destination by Tourists
(n=326)
Source: Field Data
Sr
Type of VisitName of Places
First Visit Repeat Visit Total
F % F % F %
1. 2. 3. 4. 5. 6. 7.1. Aundh 6 20 24 80 30 1002. Mahabaleshwar 10 33.33 20 66.67 30 1003. Panchgani 16 45.71 19 54.29 35 1004. Pratapgarh 21 70 9 30 30 1005. Wai 12 32.43 25 67.57 37 1006. Sajjangarh 6 20 24 80 30 1007. Thoseghar 27 81.82 6 18.18 33 1008. Kas 28 93.33 2 6.67 30 1009. Ajinkya-Tara 25 73.53 9 26.47 34 10010. Koyna 23 62.16 14 37.84 37 100
Total 174 53.37 152 46.63 326 100
Data Analysis
Shivaji University, Kolhapur 180
Table 4.2.3.13 inferred that fresh visitors are found at the places like Kas (93.33),
Thoseghar (81.82%), Ajinkytara (73.53%), and Pratapgarh (70%). The destinations
like Aundh (80%) that is famous for Yamai pilgrimage and Sajjangarh(80%) a holy
place, Wai which famous for Ganpati temple and a historical place attracts tourist for
repeat visit.. Mahableshwar and Panchgani known hill stations also attracts tourist for
repeat visit. Koyna attracts first time visitors due to its gorgeous nature. Mostly all
destinations at Satara found attracting tourists for repeat visit.
Frequency of Repeat Visit by TouristFollowing table shows the frequency of repeat visit to the different locations of Satara
by sample tourists. It is quiet likely that tourist visited the destination may visit couple
of times. This table is an effort to assess these visits. Percentages are calculated on
152 samples that have made repeat visit to either of the destination. But from column
Number 2 to 9 where percentages are calculated as per destination.
Table 4.2.3.14Frequency of Repeat Visit to the Destination by Tourists
(n=152)
Source: Field Data
Table 4.2.3.14 reveals that all destinations are visited by 46.62% of total sample
tourist. Out of these, 152 samples have made repeat visit to the respective
Sr.
Number ofRepeat Visit
Name of Places
0-5 5-10 10-1515&
aboveTotal
F % F % F % F % F %
1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11.1. Aundh 041.67 2 8.33 10 41.67 2 8.33 24 15.792. Mahabaleshwar 14 70 4 20 1 5 1 5 20 13.163. Panchgani 8 42.11 6 31.58 5 26.32 19 12.504. Pratapgarh 3 33.33 1 11.11 2 22.22 3 33.33 9 5.925. Wai 10 40 8 32 5 20 2 8 25 16.456. Sajjangarh 8 33.33 6 25 3 12.5 7 29.17 24 15.797. Thoseghar 3 50 3 50 6 3.958. Kas 2 100 2 1.329. Ajinkya-Tara 9 100 9 5.9210. Koyna 12 85.71 2 14.29 14 9.21
Total 79 51.97 32 21.05 26 17.11 15 9.87 152 100
Data Analysis
Shivaji University, Kolhapur 181
destinations. The most frequently visited destinations is Aundh, Sajjangarh 15.79% of
samples each out of repeat visited tourist have visited these destination. Kas,
Ajinkytara, and Thoseghar are the least repeat visited destinations. Wai stood first
with 16.45% of tourist visited frequently. Hill stations i.e. Mahabaleshwar, Panchgani
do found visited by 13.16% and 12.50% samples respectively. It can be said that
pilgrimages remain more attraction for repeat visit followed by hill stations.
Pricing Perception by Tourist
Following table presents pricing perception on different items in different
locations of Satara. The tourist samples that have stayed at respective locations have
interviewed to seek their perception on pricing of food and drinks, accommodation,
transport, packaged tours, information material and shopping items. The respondents
who stayed are 119 in numbers. These respondents were asked to rate their perception
on five point likert scale 1 for highly unreasonable, 2 for unreasonable, 3 for neither
reasonable more unreasonable, 4 for reasonable and 5 for highly reasonable. These
responses are purely based on actual availed items at respective places.
Table 4.2.3.15Sample Tourists Perception on Pricing at Destination
(n=119)
Source: Field Data
Sr
PricingPerception
Name of Places Foo
d an
dD
rink
s
Acc
omm
odat
ion
Tra
nspo
rt
Pac
kage
dT
ours
Info
rmat
ion
Mat
eria
l
Sho
ppin
gIt
ems
1. 2. 3. 4. 5. 6. 7.1. Aundh2. Mahabaleshwar 2.58 2.69 3 3 1.863. Panchgani 3.38 3.14 3.42 2 2.67 2.364. Pratapgarh5. Wai 3.54 3.5 3.25 3.1 2.82 3.5
6. Sajjangarh 3.94 3.41 4 4.33 3.567. Thoseghar 3.88 3.46 3.44 3 3 38. Kas 3.93 3.5 3.43 3 3.14 3.389. Ajinkya-Tara10. Koyna 4.08 4.08 3.67
Total 3.58 3.35 3.47 2.89 3.2 2.85
Data Analysis
Shivaji University, Kolhapur 182
Table 4.2.3.15 reveals that packaged tours, information materials and shopping items
are not reasonable from the new point of samples as far as pricing is concerned.
Pricing of transportation is quite reasonable to Sajjangarh and somewhat reasonable
for rest of destinations except Mahabaleshwar. Destination Mahabaleshwar seems to
be costlier in all respect since the score for pricing was reasonability tends from 1.86
to 3 for respective items. Destination Koyna is the most reasonable on the part of food
and accommodation.
Following table presents the perception of pricing by sample tourists who did not stay
at respective locations of Satara. The variables food and drinks, information material
and shopping items are only considered for non-resident tourists.
Table 4.2.3.16Perception of pricing by tourists who did not stay at Destination
(n=190)
Source: Field DataTable 4.2.3.16 reveals that destination Mahabaleshwar is still costlier for non residenttourist for food, information material and shopping items. Samples are foundreasonable prices of food and information material at destination Pratapgarh and Wai.Prices of food seem to be more reasonable at Thoseghar, Kas, and Wai since the meanreasonability is 4 and nearby.
Sr.
Prcing Perception
Name of Places
Foodand
Drinks
InformationalMaterial
ShoppingItems
1. 2. 3. 4.1. Aundh 3.33 3 3.332. Mahabaleshwar 1.88 2 2.253. Panchgani 3.45 3.1 34. Pratapgarh 3.76 3.63 3.65. Wai 3.82 3.33 3.536. Sajjangarh7. Thoseghar 48. Kas 4 3.5 3.369. Ajinkya-Tara10. Koyna 3.4 3 3
Total 3.59 3.43 3.35
Data Analysis
Shivaji University, Kolhapur 183
Section IV
4.2.4 Hoteliers Descriptive Analysis:
This part deals with the status of 40 hoteliers of Satara district. Data orate on purpose
of lodging occupancy, tourists’ origin who stayed, services offered, preference of
customers for hotel services, size of business, awareness, promotion tool, tourist
season, media effectiveness, awareness of destination, perception on tourism services
and amenities available in district, potential to tourism and like. Responses were
collected on 5-point scale. Data analyzed with different statistical tools percentages,
mean, rank, standard deviation, rank correlation etc.
Lodging OccupancyFollowing table shows opinion of hoteliers on percentage of lodging occupancy as per
the purpose of tourist visit at Satara. People sought in the hotel for business/office
purpose, tourism, and other. The percentage of occupancy for each purpose from the
range of 0-20 to 80-100 at the interval of 20 highlight the size of business of each
reason. The data depicts the percentage interval of lodging occupancy in Satara.
Table 4.2.4.1Lodging Occupancy in Sample Hotels
(n=40)
Sr.
Purpose ofVisit
Percentage ofOccupancy
Business/office Tourist Other
F % F % F %
1 2 3 4 5 6 71. 0-20 26 65 1 2.5 32 802. 20-40 5 12.5 6 15 7 17.53. 40-60 4 10 2 5 1 2.54. 60-80 5 12.5 8 20 05. 80-100 0 0 23 57.5 0
Total 40 100 40 100 40 100Source: Field Data
Table 4.2.4.1 reveals that occupancy of tourism lodging is more as compared to other
type of occupancy.
Data Analysis
Shivaji University, Kolhapur 184
Tourism occupancy is in the range of 80-100 opined by 57.5% hoteliers, business
occupancy is below 20 percentages opined by 65% hoteliers, and ‘other purpose’
lodging occupancy is below 20% opined by 80% of sample hoteliers.
Following table shows the opinion of hoteliers on percentage of lodging occupancy of
tourist from different locations. Tourist came from different areas some are from
Satara district, other district, and some times out of Maharashtra and may be from
foreign countries. Lodging occupancy is in percentage range of each area reflecting in
the following table.
Table 4.2.4.2Lodging Occupancy of Tourist from Different Locations
(n=40)
Sr.
Area
OccupancyPercentage
Sat
ara
dist
rict
%
Oth
er d
istr
ict
of M
ahar
asht
ra
%
Out
of
Mah
aras
htra
%
For
eign
%1. 2. 3. 4. 5. 6. 7. 8. 9.
1. 0-20 36 90 2 5 11 27.5 40 1002. 20-40 2 5 4 10 15 37.5 0 03. 40-60 2 5 17 42.5 8 20 0 04. 60-80 0 0 11 27.5 3 7.5 0 05. 80-100 0 0 6 15 3 7.5 0 0
Total 40 100 40 100 40 100 40 100Source: Field Data
Table 4.2.4.2 reveals that occupancy lodging of tourist is more from other district of
Maharashtra followed by rest of other states.
Lodging occupancy from ‘Satara district’, ranges up to is 20% opined by 90% hotel
owners whereas 40-60% lodging occupancy received from tourist from other district
of Maharashtra opined by 42.5% hoteliers and from rest of states in India the
occupancy receives below 40%. Foreign tourists’ occupancy is also less than 20%
opined by all hoteliers.
Data Analysis
Shivaji University, Kolhapur 185
Tourist Preference for Hotel Services
Following table presents opinion of hoteliers on tourist preference for hotel services in
Satara hotel offered many services for tourist but tourist preference depicts in
following table.
Table 4.2.4.3Preference of Hotel Services by Tourists
(n=40)
Sr.Name of Services F Percentage
1. 2. 3.1 Air/Rail Ticket Booking 11 27.52 Hotel Booking 40 1003 Local Transport Vehicle 28 704 Tour Guide 23 57.55 Package Tour 12 306 Entertainment 12 307 Any Other* 1 2.5
Total 40 100Source: Field Data*Any other’ services are not specified by hotelier
Table 4.2.4.3 depicts that ‘Hotel Booking’ is the priority of tourist according to the
hotel owners. Next priority is arrangements of ‘Local Transport Vehicle’ preferred by
70%, of samples. ‘Tour Guide’ preferred by 57.5% of sample. ‘Package Tour’ and
‘Entertainment’ and Air/Rail ticket booking preferred by around 30% of samples.
Data Analysis
Shivaji University, Kolhapur 186
Size of Tourist Hanled by Hotels
Following table discourse number of tourist handled in a year by sample hoteliers inSatara.Table 4.2.4.4Number of Tourist Handled yearly by Sample Hotels
(n=40)
Sr.Number of
TouristF Percentage
Estimated Number ofTourist*
1. 2. 3. 4.1 0-5000 11 27.5 275002 5000-10000 10 25 750003 10000-15000 5 12.5 625004 15000-20000 4 10 700005 20000-25000 5 12.5 1125006 25000-30000 2 5 550007 30000& above 3 7.5 97500Total 40 100 500000
Source: Field Data*Figures are calculated by taking average of number of tourist column
multiplied by frequency i.e. Average of column No. 1 * 2
Table 4.2.4.4 depicts that 27.5% of hotels yearly handle ‘0-5000’ tourists whereas
25% handle ‘5000-10000’ and 12.5% each hotel handles ‘10000-15000’ and ‘20000-
25000’ tourist. ‘15000-20000’ tourists are yearly handled by 10% hotel owners,
‘30000 and above’ tourist handled by 7.5 % and only 5% hotel owner handle ‘25000-
30000’ tourist. Thus, it infers that 15000 tourists are yearly handled by 60% of
respondents and more than 25000 tourists by 12.5% respondents. Estimated amount
of tourist handled by hotelier in Satara counts to five lakhs.
Tourism Season as per Hoteliers’ Opinion
Table depicts opinion of sample hotel owners on tourism season like ‘peak season’,
‘off season’ and ‘special season’ in Satara. The following table depicts the
months/occasions of tourism seasons in Satara district.
Data Analysis
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Table 4.2.4.5Opinion of Sample Hotel Owners on Tourism Season in Satara
(n=40)
Sr
Tourism Season
Month /occasions ofSeason
Peak Off Special
F % F % F %
1. 2. 3. 4. 5. 6. 7.1. April-May, Sept-Oct 5 12.52. June and July(Weekend,
vacations, rainy season)25 62.5
3. Aug-Sept 4 104. Feb- June 6 155. Working and Fasting Days 28 706. Aug-Diwali 2 57. Jan – March 4 108. June-Sept 5 12.59. Rainy Season 1 2.510. April-May 6 1511. Christmas and Diwali 33 82.512. Aug-Oct 1 2.5
Total 40 100 40 100 40 100Source: Field Data
Table 4.2.4.5 discourse that June and July are favourable months in peak season i.e.
occasions of rain, vacations, weekend whereas working and fasting occasions are off-
season and Christmas and Diwali occasions are the special season.
62.5% respondents said that ‘peak season’ is weekend, vacations and rainy season and
very few i.e. 15% sample hoteliers said that Feb and June are months of the peak
season. For ‘Off season’ majority i.e. 70% sample hoteliers opines working and
fasting days are the occasions of off-season. Very few i.e. 5% sample hoteliers opines
August-Diwali are the month and occasions of off-season. For ‘Special season’
majority i.e. 82.5% sample hoteliers felt that Christmas and Diwali are the special
occasions and very few i.e. 2.5% said that August to October are the months of
special season. From this table it could be conclude that difference in the opinion of
sample hoteliers may be due to their destinations speciality.
Data Analysis
Shivaji University, Kolhapur 188
Offerings by Hoteliers
Following table presents the services offered by hoteliers in Satara. There are variousservices offered to the tourist by hotel owners is depicted in the following table.
Table 4.2.4.6Services Offered by Hotelier
(n=40)
Sr.Name of Services F Percentage
1. 2. 3.1 Lodging 40 1002 Communication 40 1003 Parking 35 87.54 Generator 39 97.55 Dinning 29 72.56 Conference Hall 20 507 Aqua-guard 35 87.58 Garden 23 57.59 Rental car 30 75
10 Sight Scene 25 62.511 Permit room 14 3512 Waiting room 32 8013 Entertainment 29 72.514 Doctor on call 37 92.515 Swimming Pool 10 2516 Internet 26 6517 Indoor game 13 32.518 Laundry 37 92.519 Gymnasium 13 32.520 Driver room 23 57.521 Sight scene information/guidelines 32 8022 Guide for sight scenes 27 67.523 Room Service 39 97.524 Cleanliness and Maintenance 40 100
25 Other(if any)* 7 17.5Source: Field Data
* Sona and Steam Bath, Health Resort, Spa, Wi-Fi, Maharashtra Thali,Children Park, Security.
Data Analysis
Shivaji University, Kolhapur 189
Table 4.2.4.6 depicts that cleanliness and maintenance, communication, and lodging
are the main thirst fulfilled by all sample hotels in Satara district and also services of
generator, doctor on call, laundry and room services.
97.5% respondents provide generator and room service, 92.5% laundry and doctor on
call, 87.5% sample hotels provide Acquaguard and parking facility, 80% facilitate
waiting room and sightseeing guidelines, 75% provides rental car, 72.5% each extend
entertainment and dining. 65% of hoteliers provide internet and 62.5% arranges sight
scene. Very few of them offer swimming pool i.e. 25%, 35% sample hotels have
permit room, 32.5% sample hotels have gymnasium and indoor games.
Promotion Technique Adopted
Following table reveals the opinion of hoteliers on promotion techniques adopted.
Table 4.2.4.7Promotion Techniques Adopted by Hotelier
(n=40)
Sr.Name of Technique F Percentage
1. 2. 3.1. Advertisement 29 72.52. Personal Selling(Agents/PROs) 14 35
3. Sales Promotion( discounts/Foodfestivals/ Special offers)
9 22.5
4. Publicity 8 205. Public Relation 19 47.56. Other(if any)* 4 10
Source: Field Data* Word of mouth and Hoardings
Table 4.2.4.7 infers that advertisement is the main tool adopted by respondents.
72.5% respondent uses advertisement as a tool of promotion technique, 47.5% use
public relation, 35% hotels do personal selling (agents/PROs), 22.5% go for sales
promotion and 20% relies on publicity. It means that all the promotion techniques are
adopted by hotels in Satara but there is no uniformity. Most of them use more than
one technique and some of them use all. Thus, advertisement is most preferred by
hoteliers of Satara, followed by public relation.
Data Analysis
Shivaji University, Kolhapur 190
Time Slab for Promotional Activities
Following table discourse, the responses of hoteliers on time slab for promotional
activities. The timing of promotion is reveals in the following table
Table 4.2.4.8Time Slab for Promotional Activities by Hoteliers
(n=40)
Sr.Time Slab for Promotion F Percentage
1. 2. 3.1 All around the year 29 72.52 During the tourism season 8 20
3 Before the season(Please specify the month and duration)* 3 7.54 Other# 2 5
Total 40 100Source: Field Data* 15 days before, Diwali, summer vacation and 31st December# No Need of promotion
Table 4.2.4.8 reveals that majority of hoteliers i.e. 72.5% do promotional activities
throughout the year, 20% do during the tourism season, 7.5% do before the season
and 5% do not feel the need of promotion. The established oldest hotel of Satara do
not feel the need of promotion.
Data Analysis
Shivaji University, Kolhapur 191
Section V
4.2.5 Tour Operators Descriptive Analysis:
This part contains the analysis of 10 tour operators who do the business to take the
tourist from Satara and who bring the tourist to Satara. Out of them 5 are from Satara,
2 from Mahabaleshwar, 2 from Kolhapur and one from Mumbai. To probe into
problems and prospects of tourism sector in Satara, researcher has serene the opinion
of Tour operators through the independent schedule, as they being stakeholder of
tourism sector. It orate size of business in percentage, perception on tourism products
that attract tourist, available tourist services and amenities, preference of promotional
techniques, its effectiveness, destination awareness, tour package, tourist preference
towards services, potential to tourism and like. The data collected on 5-point scale and
somewhere through dichotomous question and open ended questions. Responses
collected through open-ended questions are presented in readable format. The
collected data has been analyzed and presented with its inferences, which are as
follows.
Geographical Distribution of Tour Operators BusinessFollowing table shows the percentage of business of tour operators received from
different geographies. Geographies are composed as Satara, Maharashtra (excluding
Satara), out of Maharashtra and Foreign.
Table 4.2.5.1Tour Operators Receives Business from tourists of Different Geographies
(n=10)
Source: Field Data
Sr.Tour Operator’sBusiness Location
SataraMaharashtra(ExcludingSatara)
Out ofMaharashtra
Foreign
1. Satara 70 302. Satara 75 253. Satara 10 40 48 24. Satara 1005. Satara 1006. Mahabaleshwar 60 407. Mahabaleshwar 5 70 258. Kolhapur 40 309. Kolhapur 85 510. Mumbai 100
Data Analysis
Shivaji University, Kolhapur 192
Table 4.2.5.1 depicts that Satara sample tour operator receives majority business from
Satara. Mahabaleshwar sample tour operator receives business from Maharashtra and
out of Maharashtra. Kolhapur sample tour operator receives business from Satara and
Maharashtra (excluding Satara).
Tourist Purpose as Per Tour Operators’ OpinionFollowing table shows the opinions of tour operators on tourist objectives to visit
Satara. Tour operators have responded to different tourist objects viz. business,
adventure, leisure, pilgrimage, culture and other to visit Satara and registered their
response in percentage figures since the questions was open ended.
Table 4.2.5.2Opinion of Tour Operators on Tourist Objects to Visit Satara
(n=10)
Sr.
Tourist Objects
Tour Operator’sBusiness Location B
usin
ess
Adv
entu
re
Lei
sure
Pil
grim
age
Cul
ture
Oth
ers
1. Satara 5 80 10 2 32. Satara 99 13. Satara 50 304. Satara 5 30 40 20 55. Satara 70 10 206. Mahabaleshwar 1007. Mahabaleshwar 1008. Kolhapur 5 5 30 40 209. Kolhapur 20 50 3010. Mumbai 40 60
Source: Field Data
Table 4.2.5.2 depicts majority of total sample of tour operator opines that that leisure
is the main object of tourist to visit Satara. Tourist also visits to Satara for pilgrimage
opined by sample tour operator of Satara and Kolhapur as both are organizes the
pilgrimage tour packages for Satara and other services like business, adventure,
culture are ignored by total sample tour operators as their interest is only with routine
packages.
Data Analysis
Shivaji University, Kolhapur 193
Perception of Tour Opeators on Tourist Season
Following table reveals the Perception of tour operators on tourist peak season, off-
season and special season for Satara. Data have collected through open-ended
question and presented in original form.
Table 4.2.5.3Perception of Tour Operators on Tourist Season at Satara
(n=10)
Sr.
Tourist Season
Tour Operator’sBusiness Location
Peak SeasonOff
SeasonSpecialSeason
1. Satara Aug-Sept Nov-March2. Satara April-May3. Satara Sept-Oct4. Satara April-May Aug ,Sept5.
SataraApril-May-June, Sept-
Oct6. Mahabaleshwar May-June Rainy7.
MahabaleshwarDiwali And March To
June8. Kolhapur Nov-Dec June-July April9.
Kolhapur Oct-NovMarch-
AprilSchools
10.Mumbai Aug-Sept
KasFlowering
Source: Field Data
Table 4.2.5.3 shows that majority of sample tour operators have their peak season
from April to June and off-season from June to July at Satara. From Mid Aug to mid
Sept is the special season for them at Satara.
Data Analysis
Shivaji University, Kolhapur 194
Tourist Origin According to Tour Operator
Following table shows the origin of tourist who are the customers of tour operator.
Table 4.2.5.4Origins of Tourists Who are the Customer of Tour Operator
(n=10)
Sr. Name of Town F %1 Pune 4 402 Mumbai and Surrounding 6 603 Satara Interiors 2 204 Sangli 2 205 Kolhapur 3 306 Bangalore 1 107 Gujarat 1 108 Surat 1 109 Hydrabad 1 1010 Hubali, Belgaon 1 10
Source: Field Data
Table 4.2.5.4 reveals the majority i.e. 60% tour operators’ perception, about the origin
of tourist traffic for their business is Mumbai and surrounding. 40% felt Pune, 50%
getting the business from out of Maharashtra as 10% each from Bangalore, Gujarat,
Surat, Hydrabad, Karnataka (Hubali and Belgaon), 30% from Kolhapur, and 20%
each from Sangli and Satara interiors. Thus, most of the business comes from
Maharashtra and very meager comes from out of Maharashtra. It can be inferred that
tour operators’ business activity is limited to Maharashtra.
Major Thirst of Tourist According to Tour Operator
Following table shows the opinion of respondents about the thirst of tourist services.
It is the experience of tour operators that tourist demands served services from tour
operators. The services are taken on rank as follows.
Data Analysis
Shivaji University, Kolhapur 195
Table 4.2.5.5Tour operator’s Opinion on Major Thirst of Tourist Services
(n=10)
Sr.Rank Frequency
Name of Services1 2 3 4 5
1 Air and Rail ticket booking 2 3 1 0 02 Hotel Booking 5 2 2 0 03 Local Transport Vehicle 0 5 3 1 04 Tour Guide 0 0 2 4 05 Package Tour 3 0 0 1 36 Entertainment 0 0 0 0 1
Source: Field Data
Table 4.2.5.5 orates on six thirsts areas of tourist services in the view of tour operator.
Most of the tour operators’ opines that major thirst is hotel booking and local
transport vehicle since the frequency is more concentrated to first priority
followed by package tour and ‘air and rail ticket booking’. No single tour operator
feels entertainment services can be major thirst of tourist.
Tourist Handled by Tour Operator
Following table presents the opinion of tour operators on average tourist handled by
them in a year.
Table 4.2.5.6Average Tourist Handled in a year by Tour Operators
(n=10)
Sr. Number of Tourist F %1. 100-1000 4 402. 1000-10000 4 403. 10000 and above 2 20
Total 10 100Source: Field Data
Table 4.2.5.6 reveals that 60% of tour operators have handled more than 1000
tourists. 40% tour operators handled up to 1000 tourists, and 40% have handled 1000-
10000 tourists and 20% have handled more than 10000 tourists in a year.
Data Analysis
Shivaji University, Kolhapur 196
Tour Packages by Tour Operator
Following table presents the tour package offered by tour operators for Satara
destination. The data is qualitative in nature.
Table 4.2.5.7Tour Package Offered by Tour Operator for Satara
Sr. Name of Package1. Kas-Thoseghar-Sajjangarh2. Sajjangarh--Chaphal-Gondawale-Ajinkya Fort and Kas-Bamnoli-Satara3. 11Maruti( God Hanuman), Gondawale-Sajjangarh-Chaphal,Mahabaleshwar-
Panchgani-Pratapgarh4. Mahabaleshawar-Panchgani; Wai; Kaas; Audh; Koynanagar5. Kas-Thoseghar-Sajjangarh, Aundh Museum6. Mahabaleshwar and Panchgani7. Mahabaleshwar Sight Scene 11 Points and 7 Points Two Packages, Panchgani
Darshan, Pratapgarh, Mini Kashmir-Tapola,Watersport, TriveniSangam,Bamnoli Point and Shooting Point
8. Mahabaleshwar, 11 Maruti9. 11 Maruti, Aundh, Chaphal School Trip10. Thoseghar-Sajjangarh-Satara-Kas- Bamnoli- Ajinkya Tara-SataraSource: Field Data
Table 4.2.5.7 reveals that various options for the tourist who wish to visit Satara. It
has observed that majority of them offer ‘11 Maruti’ Tour package and ‘Kas-
Thoseghar- Sajjangarh’ tour package. Recently the Mumbai tour operators have
started offering ‘Kas-Thoseghar-Sajjangarh’ and ‘Thoseghar-Sajjangarh-Satara-Kas-
Bamnoli- Ajinkya Tara-Satara’ packages.
Promotion Slab for Tour Operator
Following table depicts Promotional activities are undertaken by tour operators.
Researcher assessed opinion of tour operators as to when the promotion activities are
undertaken.
Data Analysis
Shivaji University, Kolhapur 197
Table 4.2.5.8Time Slab for Promotion Activities by Tour Operator
(n=10)
Sr. Time Period F %1 All Around the Year 5 502 During Tourism Season 2 203 Before the Season 0 004 Other* 3 30
Total 10 100Source: Field Data*Other means no need to promote the business.
Table 4.2.5.8 depicts that 50% of the tour operators’ conduct promotional activities
‘all around the year’, whereas 30% respondents do not find any need to promote the
business and 20% tour operators conduct promotional activities ‘during tourist
season’. It infers that 80% tour operators do not take any promotional measures
during tourism season. 30% tour operators do not find any need because they do their
business through franchise.
Data Analysis
Shivaji University, Kolhapur 198
Section VI
4.2.6 Comparative Analysis:
This part narrates the comparative opinions of stakeholder viz. tourist, hoteliers and
tour operators. Many questions were asked to all stakeholders for an effort to assess
perceptual differences. The comparative analysis were held on destination awareness,
opinions on its worth seeing, promotion of Satara, media effectiveness, media
preference, potential to Satara, tourism services and amenities available in Satara. The
responses are collected on 5-point scale and analyzed by tools using mean, standard
deviation and rank is calculated for analyzing the data that is presented in followed
tables. A percentage is also used as per the requirement of data. Each table describes
the opinion of each stakeholder and comparative opinions analyzed at the end of all
individual opinions. Obtained figures, information from officials and observation is
considered for discussion. Being tourist as target customer his opinion is compared
with others.
4.2.6.1 Awareness of Destination:
This part depicts the awareness of stakeholder viz. tourist, hoteliers, and tour
operators of different destinations of Satara. There are numbers of worth seeing
tourist destinations in Satara. Researcher has taken 38 tourist destinations of Satara to
test viz. Thoseghar, Sajjangarh, shri Shkestra Mahuli, Kas, Dhawadshi, Yawateshwar,
Agashiv, Pal, Santoshgad, Nana Phadniswada, Narsinhmandir(Dhom), Pratapgarh,
Tapola, Chavaneshwar, Kalyangad, Bamnoli, Mauje Kharkhel, Aundh, Mayani,
Katgun, Jairamswami Vadgaon, Mauje Bhosare, Naygaon, Ramghal, Ozarde and
Marul Haveli to know its awareness by visited tourists. The destinations viz.
Mahabaleshwar and Panchgani has not been added. Researcher has also probe into the
opinions of sample tourists on worth seeing-visited destinations of Satara. The data is
to be collected through dichotomous type of questions . The collected responses were
analyzed with the percentage method.
Data Analysis
Shivaji University, Kolhapur 199
Awareness by Tourist
Following table represents the awareness of different tourist destinations of Satara by
sample tourist. The photographs taken by researcher has attached for more
clarification and to get an idea of destinations.
Table 4.2.6.1.1Awareness of Sample Tourist of Different Tourist Destinations in Satara
(n=326)
Sr.
Opinion
Name of Places
Visited DestinationOpinion About its Worth
seeing
Yes % No % Yes %No
%
1. 2. 3. 4. 5. 6. 7. 8. 9.1. Thoseghar 156 47.9 170 52.15 153 100 0 0.002. Sajjangad 191 58.6 135 41.41 191 97.45 5 2.553. Shri Shkestra
Mahuli51 15.6 275 84.36 47 95.92 2 4.08
4. Kas 141 43.3 185 56.75 139 97.20 4 2.805. Dhawadshi 11 3.37 315 96.63 7 53.85 6 46.156. Yavateshwar 52 16 274 84.05 47 100 0 0.007. Agashiv 18 5.52 308 94.48 18 66.67 9 33.338. Pal 39 12 287 88.04 31 100 0 0.009. Santoshgad 2 0.61 324 99.39 2 20.00 8 80.0010. Nana Phadniswada 37 11.3 289 88.65 30 88.24 4 11.7611. Narsinha
Mandir(Dhom)33 10.1 293 89.88 30 100 0 0.00
12. Pratapgarh 203 62.3 123 37.73 203 97.60 5 2.4013. Tapola 125 38.3 201 61.66 121 100 0 0.0014. Chavneshwar 36 11 290 88.96 36 97.30 1 2.7015. Kalayangad 4 1.23 322 98.77 3 100 0 0.0016. Bamnoli 48 14.7 278 85.28 48 100 0 0.0017. Mauje Kharkhel
(SantajiGhorpadeSamadhi)
23 7.06 303 92.94 13 68.42 6 31.58
18. Aundh81 24.8 245 75.15 87 87.00
13
13.00
19. Mayani 43 13.2 283 86.81 30 83.33 6 16.6720. Katgun 14 4.29 312 95.71 8 88.89 1 11.1121. Jairamswami,
Vadgaon4 1.23 22 98.77 3 100 0 0.00
22. MaujeBhosare,(PratapraoGujar Smarak)
4 1.23 322 98.77 4 80.00 1 20.00
Data Analysis
Shivaji University, Kolhapur 200
23. Naygao( SavitribaiPhule Birthplace)
17 5.21 309 94.79 16 84.21 3 15.79
24. Ramghal 9 2.76 317 97.24 6 85.71 1 14.2925. Ozarde Panchdhara
Waterfall65 19.9 261 80.06 54 100 0 0.00
26. Marul Haveli 10 3.07 316 96.93 20 83.33 4 16.6727. Koyananagar
Dam/Nehrugarden92 28.2 234 71.78 78 95.12 4 4.88
28. Banpuri, Naikeba 25 7.67 301 92.33 22 91.67 2 8.3329. Valmiki 13 3.99 313 96.01 13 81.25 3 18.7530. Dhareshwar 16 4.91 310 95.09 16 100 0 0.0031. Koyna 92 28.2 234 71.78 71 89.87 8 10.1332. Vasota 40 12.3 286 87.73 24 88.89 3 11.1133. Pateshwar 20 6.13 306 3.87 30 93.75 2 6.2534. Gondawale 63 19.3 263 80.67 51 92.73 4 7.2735. Natraj Mandir 46 14.1 280 85.89 41 85.42 7 14.5836. Shivaji Museuem 31 9.51 295 90.49 24 85.71 4 14.2937. Petri 24 7.36 302 92.64 25 78.13 7 21.8838. Shikhar Shingnapur 57 17.5 269 82.52 46 100 0 0.00Source: Field Data
Table 4.2.6.1.1 depicts that Pratapgarh and Sajjangarh is mainly seen by tourists.
Out of 38 destinations only 8 destinations viz. Pratapgarh (62.3), Sajjangarh (58.6%),
Thoseghar (47.9%), Kas (43.3%), Tapola (38.3%), Aundh (24.8%), and Koyna/
Koynanagar (28.2%) are visited by tourists and almost all the tourists felt these
locations are worth seeing. Tourists overlook rests 30 destinations and awareness
percentage is in between 2 to 20% only. However, the sample tourists who have
visited these destinations feel worth seeing perception about these destinations, which
accounts to 80 to 100%. Therefore, it is inferred that only the tourists visit few known
destinations and most of the destinations are aware nor they are visited by the tourists.
It shows that destinations are not properly popularized to attract tourists.
Data Analysis
Shivaji University, Kolhapur 201
Awareness by Hotels
As like tourists researcher has also asked the same questions to sample hoteliers.
Following table shows the sample hoteliers opinion on visited destination in Satara
Table 4.2.6.1.2Sample Hoteliers Visited the Tourist Destinations in Satara
(n=40)
Sr
Opinion
Name of TouristPlaces in Satara
District
Visited DestinationOpinion about its worth
seeing
Yes % No %Yes
% No %
1. 2. 3. 4. 5. 6. 7. 8. 9.1. Thoseghar 23 57.5 17 42.5 23 100 0 02. Sajjangad 23 57.5 17 42.5 23 100 0 03. Shri Shkestra
Mahuli16 40 24 60 15 93.75 1 6.25
4. Kas 22 55 18 45 22 100 0 05. Dhawadshi 10 25 30 75 9 90 1 106. Yavateshwar 15 37.5 25 62.5 15 100 0 07. Agashiv 8 32 80 8 100 0 08. Pal 12 30 28 70 11 92.67 1 8.339. Santoshgad 3 7.5 37 92.5 3 100 0 010. Nana Phadniswada 8 20 32 80 8 100 0 011. Narsinha mandir
(Dhom)8 20 32 80 8 100 0 0
12. Pratapgad 7 17.5 33 82.5 7 100 0 013. Tapola 35 87.5 5 12.5 35 100 0 014. Chavneshwar 31 77.5 9 22.5 31 100 0 015. Kalayangad 4 10 36 90 4 100 0 016. Bamnoli 4 10 36 90 4 100 0 017. Mauje Kharkhel(
Santaji Ghorpade)18 45 22 55 18 100 0 0
18. Aundh 4 10 36 90 4 100 0 019. Mayani 20 50 20 50 20 100 0 020. Katgun 8 20 22 55 8 100 0 021. Jairamswami,
Vadgaon5 12.5 35 87.5 5 100 0 0
22. MaujeBhosare,(PratapraoGujar smarak)
5 12.5 35 87.5 5 100 0 0
23. Naygao( SavitribaiPhule Birthplace)
3 7.5 37 92.5 3 100 0 0
Data Analysis
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Source: Field Data
Table 4.2.6.1.2 depicts that out of 38 destinations hoteliers have seen very few
destinations as Tapola by 87.5%, Shikhar Shingnapur by 80%, 77.5% hoteliers have
seen Chavaneshwar, 65% Banpuri(Naikeba), 57.5% each Thoseghar and Sajjangarh,
55% Kas and 50% Mayni. Hoteliers do not often see rest 30 destinations. Gondawale
and Natraj mandir 42.5%, 40% each have visited Vasota and Marul haveli, Mauje
Karkhel 45%, 40% Skshetra Mauli and 37.5% Yawateshwar. Majority of hoteliers
does not know rests of the destinations. Those who have visited they feel all are worth
seeing but according to few hoteliers’ 8.33% sample hoteliers feel ‘Pal’ and 6.25%
thinks ‘Skshetra Mahuli’ and 10% think ‘Dhawadshi’ are not worth seeing. Thus,
excluding these three destinations, most of the destinations are worth seeing for tourist
and these are not seen by most of the hotel owners so need to be aware of the same.
Thus, it concludes that there is lack of awareness among the hoteliers about the
destinations available in Satara.
24. Ramghal 7 17.5 33 82.5 7 100 0 025. Ozarde Panchdhara
Waterfall7 17.5 33 82.5 7 100 0 0
26. Marul Haveli 16 40 24 60 16 100 0 027. Koyananagar
dam/Nehrugarden7 17.5 33 82.5 7 100 0 0
28. Banpuri, Naikeba 26 65 14 35 26 100 0 029. Dhareshwar 8 20 32 80 8 100 0 030. Valmiki 5 12.5 35 87.5 5 100 0 031. Koyna 7 17.5 33 82.5 7 100 0 032. Vasota 16 40 24 60 16 100 0 033. Pateshwar 5 12.5 35 87.5 5 100 0 034. Gondawale 17 42.5 23 57.5 17 100 0 035. Natraj Mandir 17 42.5 23 57.5 17 100 0 036. Shivaji Museuem 14 35 26 65 14 100 0 037. Petri 9 22.5 31 77.5 9 100 0 038. Shikhar Shingnapur 32 80 8 20 32 100 0 0
Data Analysis
Shivaji University, Kolhapur 203
Awareness by Tour Operators
Unlike tourists and hoteliers even tour operators are also interviewed on same
variables. Following table talks about the sample tour operators visited locations in
Satara.
Table 4.2.6.1.3Sample Tour Operators visited the Tourist locations in Satara
(n=10)
Sr.
Name of TouristPlaces in Satara
District
Seen DestinationOpinion about Worth
seeing
Yes % No % Yes % No %
1. 2. 3. 4. 5. 6. 7. 8. 9.1. Thoseghar 9 90 1 10 9 100
2. Sajjangad 9 90 1 10 9 1003. Shri Shkestra
Mahuli5 50 5 50 5 83.33 1 16.7
4. Kas 9 90 1 10 9 1005. Dhawadshi 1 10 9 90 1 50 1 506. Yavateshwar 6 60 4 40 6 100
7. Agashiv 0 0 10 100 0 100
8. Pal 2 20 8 80 2 1009. Santoshgad 0 0 0 100 010. Nana Phadniswada 4 40 6 0 4 66.67 2 33.3
11. Narsinhamandir(Dhom)
2 20 8 0 2 .67 1 33.3
12. Pratapgarh 4 40 6 0 4 80 1 20
13. Tapola 9 90 1 10 9 10014. Chavneshwar 7 70 3 30 7 10015. Kalayangad 1 10 9 90 1 100
16. Bamnoli1
10
9 90 1 100
17. Mauje Kharkhel(Santaji Ghorpade)
7 70 3 30 7 100
18. Aundh 0 0 10 100 0 10019. Mayani 9 90 1 10 9 10020. Katgun 4 40 6 60 4 10021. Jairamswami,
Vadgaon0 0 10 100 0 100
Data Analysis
Shivaji University, Kolhapur 204
22. MaujeBhosare,(PratapraoGujar smarak)
1 0 9 90 1 100
23. Naygao( SavitribaiPhule Birthplace)
0 0 10 100 0 100
24. Ramghal 0 0 10 100 0 100
25. Ozarde PanchdharaWaterfall
2 20 8 80 2 100
26. Marul Haveli 6 60 4 40 6 10027. Koyananagar
dam/Nehrugarden0 0 0 100 0 100
28. Banpuri, Naikeba6
60
4 40 6 100
29. Dhareshwar 2 20 8 80 2 10030. Valmiki 2 20 8 80 2 100
31. Koyna 1 10 9 90 1 100
32. Vasota 7 70 3 30 7 87.5 1 12.5
33. Pateshwar 7 70 3 30 7 87.5 1 12.5
34. Gondawale 5 50 5 50 5 100
35. Natraj Mandir 7 70 3 30 7 100
36. Shivaji Museuem 5 50 5 50 5 100
37. Petri 5 50 5 50 5 100
38. Shikhar Shingnapur 6 60 4 40 6 85.7 1 14.3Source: Field Data
Table 4.2.6.1.3 depicts that most of tour operators i.e. 90% visit Thoseghar,
Sajjangarh, Kas, Tapola, Mayni, followed by 70% tour operators visited to
Chavaneshwar, Mauje Kharkhel, Vasota, Natraj mandir. 60% visit to Banpuri,
Marul Haveli and Yewateshwar. Whereas locations like Agashiv, Santoshgarh,
Aundh, Jairamswami (Vadgaon), Naygaon, Ramghal, Koynanagar dam has not
seen at all by these tour operators, followed by 90% tour operator did not visited
locations like Dhawadshi, Kalyangarh, Bamnoli, Mauje Bhosare and Koyna while
80% did not visits Valmiki, Dhareshwar, Ozarde, Narsinh Mandir and Pal. Nana
Phadniswada, Pratapgarh and destination Katgun were not visited by 60% of tour
operators. It infers that more than 50% of locations as mentioned above were not
visited by tour operator since they were not aware of them. Those who have visited
locations feel the locations are worth seeing.
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Data depicts that Pratapgarh and Sajjangarh the well-known destinations only were
seen by majority of tourist.Whereas Tapola, Shikhar Shingnapur, Chavaneshwar,
Banpuri (Nikeba), Thoseghar, and Sajjangarh destinations are seen by majority of
sample hotel owners. Thoseghar, Sajjangarh, Kas, Mayani,Tapola, Chavaneshwar,
Vasota, Pateshwar, Natraj Mandir,Aundh,Marul Haweli,Shikhar Shingnapur
destinations are seen by majority of tour operators. It infers that stakeholders had not
seen most of the destinations and they are not aware of these destinations. There was
no single stakeholder who has not seen all the destinations nor had noticed all of
them. Tour operators knew more destinations compared to hoteliers or tourist.
It is observed that tourist are interested to visit other destinations of Satara, hoteliers
are not taking initiative to make them aware unless tourist show their interest. Tour
operators emphasizes on traditional tour packages like 11 Maruti, Sajjangarh and
shows more interest to promote only few destinations which are popular like Kas,
Thoseghar and Sajjangarh. There is lack of communication of destinations by
hoteliers and tour operators to tourist. Researcher has also observed most of the
destinations were neither seen nor they were aware by government officials who
sanctioned and implemented tourist development plans. Thus, it infers that most of the
destinations of Satara are unexploited to be developed district as a tourist destination.
Data Analysis
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4.2.6.2 Effectiveness of Media in Promotion of Tourism:
This part talks on the perception of all the stakeholders on media effectiveness in
promotion of tourism. There are 11 Medias options considered to know its
effectiveness by stakeholders. Media plays important role in the promotion of
destinations. These responses are mirrored in the following table with its respective
mean, standard deviation, and rank with spearman’s correlation score.
Media Effectiveness as Per Tourist
Following table presents opinion of sample tourists on effectiveness of media in the
promotion of tourism. It reflects the Medias preference by sample tourist to know the
respective destinations of Satara.
Table 4.2.6.2.1Opinion of Sample Tourists on Effectiveness of Media in Promotion of Tourism
(n=326)
Sr.
Gender
Media
Male Female Total
Mean S.D. Rank Mean S.D. Rank Mean S.D. Rank
1. 2. 3. 4. 5. 6. 7. 8. 9. 10.1. Newspaper
Advertisement3.95 0.65 6 3.95 0.66 6 3.95 0.65 6
2. Television Advertisement 4.01 0.72 3 4.01 0.72 3 4.01 0.72 33. Magazine Advertisement 3.78 0.78 8 3.76 0.78 8 3.78 0.78 84. Information aterials(Brochures,
Guides, Souvenirs, Folders,Handbooks)
3.98 0.95 4 3.97 0.96 4 3.98 0.95 4
5. Posters 3.55 0.81 9 3.55 0.81 9 3.55 0.81 96. Website/Internet Ad 4.31 0.85 2 4.31 0.85 2 4.31 0.85 27. Motivation by Tour
Operators3.85 1.00 7 3.86 1.00 7 3.85 1.00 7
8. Word-of-Mouth 4.46 0.70 1 4.47 0.70 1 4.46 0.70 19. Newspaper Articles
Related to Tourism3.97 0.88 5 3.97 0.88 4 3.97 0.88 5
10. Publication of in HouseLetters
3.54 0.71 10 3.54 0.71 10 3.54 0.71 10
11. Yellow Pages 2.55 0.85 11 2.55 0.85 11 2.55 0.85 11Correlation Coefficient male and female .991**
Sig. (2-tailed) .000Source: Field Data**. Correlation is significant at the 0.01 level (2-tailed).
Data Analysis
Shivaji University, Kolhapur 207
Table 4.2.6..2.1 depicts that Word of Mouth (WOM), Website/Internet advertisement,
and Television are most preferred media in the promotion of tourism and yellow
pages, publication of in house letters and a poster are the least preferred by
respondents
Word of Mouth (WOM), Website/Internet advertisement and Television carries mean
score more than 4 and received rank 1st, 2nd and 3rd respectively. Media like yellow
pages, publication of in house letters, and a poster whose mean score is below 4 and
received ranks are 11, 10 and 9 respectively.
The Spearman’s rank correlation coefficient of perception of male and female on
effectiveness of media for tourism is 0.991 with ‘P’ value 0.00, which is significant at
0.01 levels (2-tailed). This signifies perception of effectiveness of media in promotion
of tourism is uniform in male and female.
Media Effectiveness as Per Hoteliers
Following table presents opinion of sample hoteliers on effectiveness of media for
promotion. For effective communication, media weightage according to the
respondents is reveal in the following table.
Table 4.2.6.2.2Opinion of Sample Hoteliers on Effectiveness of Media for Promotion
(n=40)
Source: Field Data3
Sr.Media Mean SD Rank
1. 2. 3. 4.1. Newspaper Advertisement 3.04 3.04 92. Television Advertisement 3.42 3.42 53. Magazine Advertisement 3.19 3.19 84. Information Materials(Brochures, Guides,
Souvenirs, Folders, Handbooks)4.00 4.00 3
5. Posters 3.81 3.81 46. Website/Internet Ad 3.13 3.13 107. Motivation by Tour Operators 4.51 4.51 28. Word-of-Mouth 4.00 4.00 69. Newspaper Articles Related to Tourism 4.65 4.65 110. Publication of in House Letters 3.56 3.56 711. Yellow Pages 2.91 2.91 11
Data Analysis
Shivaji University, Kolhapur 208
Table 4.2.6.2.2 depicts that media like ‘newspaper articles related to tourism’,
‘motivation by tour operators’ and ‘information materials’ are more effective for
promotion as they received rank first, second and third respectively and their mean
score is more than 4. The l The least effective media are ‘website/internet
advertisement’, ‘newspaper advertisement’ and ‘magazine advertisement’ as the mean
score is less than 4 and ranks are in bottom three i.e.10th, 9th and 8th respectively.
Less effective media are ‘website/internet advertisement’, ‘newspaper advertisement’
and ‘magazine advertisement’ as the mean score is less than 4 and ranks are in bottom
three i.e.10th, 9th and 8th respectively.
Media Effectiveness as Per Tour Operator
Following table shows the opinion of sample tour operators on effectiveness of media
for promotion.
Table 4.2.6.2.3Opinion of Sample Tour Operators on Effectiveness of Media for Promotion
(n=10)
Sr. Media Mean SD Rank1. Newspaper Advertisement 4.10 0.74 32. Television Advertisement 4.00 0.50 53. Magazine Advertisement 3.67 0.87 94. Information Materials(Brochures, Guides,
Souvenirs, Folders, Handbooks)4.33 0.71 4
5. Posters 4.25 0.89 76. Website/Internet Ad 4.78 0.44 27. Motivation by Tour Operators 4.50 0.53 58. Word-of-Mouth 4.60 0.52 19. Newspaper Articles Related to Tourism 4.25 0.71 710. Publication of in House Letters* 3.43 0.98 1011. Yellow Pages 2.83 1.17 11Correlation Coefficient .073Sig. (2-tailed) .831
Source: Field Data* Publication of in House Letters is the in-house publication of Chudhari Travels thatshares tourist experiences on traveled area.
Table 4.2.6.2.3 reveals that media of promotion like ‘Word of mouth’,
‘Website/internet advertisement’, ‘Newspaper advertisement’ and ‘Information
Data Analysis
Shivaji University, Kolhapur 209
material’ are more effective in the perception of tour operator , as they received
rank 1st,2nd,3rd and 4th respectively and their mean score is more than 4. ‘Yellow
pages’, ‘Publication of in house letters’, and ‘Magazine advertisement’ are the least
effective media according to the perception of tour operators as they received rank 11,
10 and 9 respectively and the mean score is less than 4.
To investigate into the depth of analysis researcher has tested with the help of
spearman’s rank correlation’ the perception of tour operator and hoteliers. The
correlation coefficient is .073, with ‘P’ value 0.831, which is insignificant at 0.05
levels (2-tailed). It reveals that there is no uniformity into the opinion of tour
operators and hoteliers regarding media preference for promotion.
Data reveals that Word of Mouth (WOM), Website/Internet advertisement, and
Television are effective tools in tourist point of view. Whereas hoteliers thinks
‘newspaper articles related to tourism’, ‘motivation by tour operators’ and
‘information materials’ as a effective tool. However, tour operators think ‘Word of
mouth ’, ‘Website/internet advertisement, Newspaper advertisement, and ‘Information
material’ are more effective tool for communication. Therefore, there is difference of
opinion on effectiveness of media. One should consider those media that target
customers feel effective. It infers that word of mouth; website and television would be
effective tool for tourism promotion.
4.2.6.3 Source Usage for Promotion:
This part deals the sources used by different stakeholders for promotion. Each
stakeholder has his or her own objectives as per the nature of business. However, for
the sake of promotion of tourism researcher intend to find out the gap between source
used by tourist to know the destination with efforts of hoteliers and tour operators for
the same. Four advertising media are considered to know their efforts.
Data Analysis
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Media Preference by Hoteliers
Following table depicts the opinion of hoteliers on media preference for promotion.
For advertisement respondents preference to various media on priority basis is
discourse in the following table.
Table 4.2.6.3.1Media Preferred by Hotelier for Promotion
(n=40)
Sr.
Rank Frequency
Name of Media1 2 3 4 5 Total
1 2 3 4 5 6 71 TV 1 2 3 4 5 152 Newspaper 3 0 2 1 0 63 Website 5 5 1 0 0 114 Brochure 20 4 0 3 0 275 Other* 1 14 6 0 0 21
Source: Field Data* Visiting cards, hoardings, word of mouth and Tour operator
Table 4.2.6.3.1 reveals about the media preference by hoteliers. It has found that
brochure is most preferred, followed by website and other (Visiting cards, hoardings,
word of mouth and Tour operator).
Television as a media used for the promotion is rear by hotel owners.
Media Preference by Tour Operator
Following table depicts media preference by tour operator for the promotion of their
product. Preferences are taken on ranks.
Table 4.2.6.3.2Media Preference by Tour Operator for Promotion
(n=10)
Sr.Rank FrequencyMedia Preference
1 2 3 4 5 Total
1. TV 0 0 1 1 0 22. Newspaper 2 1 2 0 0 53. Website 5 2 1 0 0 84. Brochure 3 3 2 0 0 85. Other 1 1 0 0 0 2
Source: Field Data
Data Analysis
Shivaji University, Kolhapur 211
Table 4.2.6.3.2 depicts that for promotion tour operators prefers website andbrochures rather than other options like television, newspaper and ‘other’ since therank frequency is concentrated on these two media.
Actual Source Used by TouristFollowing table represents sources used by sample tourists to know the respectivelocations of Satara. The data is presented location wise.Table 4.2.6.3.3Sources Used by Sample Tourists to Know the Destination
(n=326)
Source: Field Data*Magazine
Sr
Name of Source
Name of Places
Tel
evis
ion
Ad
New
spap
er
Tra
vel G
uide
Tra
vel
Age
nt/T
our
oper
ator
Web
site
Pers
onal
Eff
ort
Frie
nds/
Rel
ati
ves
Oth
er(P
l.Sp
ecif
y)*
Tot
al
F % F % F % F % F % F % F % F % F %
1. 2. 3. 4. 5. 6. 7. 8. 9. 10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
1. Aundh4
13.3
3
26
86.6
7
30 100
2. Mahabaleshwar 1
3.33 10
33.3
3
6 20 13
43.3
3
30 100
3. Panchgani
1
2.86 8
22.8
6
24
68.5
7
2
5.71 35 100
4. Pratapgarh
1
3.33 4
13.3
3
3 10 11
36.6
7
11
36.6
7
30 100
5. Wai
4
10.8
1
7
18.9
2
7
18.9
2
19
51.3
5
37 100
6. Sajjangarh
1
3.33 3 10 1
3.33 11
36.6
7
9 30 5
16.6
7
30 100
7. Thoseghar
33 100
33 100
8. Kas
6 20 22
73.3
3
2
6.67 30 100
9. Ajinkya-Tara
1
2.94 17 50 1
2.94 15
44.1
2
34 100
10. Koyna
1 2.7 1 2.7 3
8.11 32
86.4
9
37 100
Total
1
0.31 4
1.23 1
0.31 27 8.28 30 9.2
50
15.3
4
204
62.5
8
9
2.76
326
100
Data Analysis
Shivaji University, Kolhapur 212
Table 4.2.6.3.3 inferred that respondents preferred to reliable source ‘friends and
relatives’ to know the destinations of Satara. It infers that local community plays
important role in the promotion of tourism.
62.58% of tourists have adopted source ‘friends and relatives’ to know the
destination, followed by 15.34% tourists used ‘personal effort’.
Friends and relatives have been used the major source of information by majority of
tourists. Destination Aundh is visited by 86.67%, Mahabaleshwar is visited by
43.33% of tourists with this source, 68.57% of tourists visited Panchgani, 36.67%
tourists visited Pratapgarh, 51.35% Wai, and the entire tourists visited Thoseghar
through the source of friends and relatives. Kas is known to 73.33% of tourists
through friends and 88.49% of tourists known Koyna through friends and relatives.
Ajinkyatara is visited by 50% of tourist with source of information tour operator and
travel agent. However, 36.67% of the tourists have used ‘personal effort’ to know the
destination Sajjangarh and Pratapgarh. Personal efforts made out of curiosity, sample
tourists have searched and collected information from all the possible sources and not
specific.
Data depicts that brochure is more preferred by hoteliers and very few go for website.
Whereas website is more preferred by tour operators and few go for brochure.
However, tourist widely uses ‘friends and relatives’ a reliable source to know the
destinations of Satara. It found the gap between target customer (tourist), service
providers (hoteliers and tour operators). Researcher has also noticed that government
is not taking effort to reach to tourist.
4.2.6.4 Potential of Tourism in Satara District:
This part contains perception of stakeholders on potential of tourism in Satara
District. It is observed that majority of the people have neither visited nor aware of
these worth seeing destinations. It is noticed that the tourist flow is intensifying
compared to earlier years. To know the opinion of tourist on potential to Satara seven
statements were developed. These statements assess the perception of stakeholders on
potential to attract tourists, use of package tour to attract tourists, adequacy of existing
Data Analysis
Shivaji University, Kolhapur 213
hotel facility and celebrity advertisement. These responses are analyzed with the help
of mean, standard deviation, rank, and spearman’s rank correlation.
Perception of Tourist on Potential
Following table shows the perception of sample tourists on potential of tourism in
Satara district. Researcher is also interested to know the perceptual gender difference
for the same. These details are mirrored in following table.
Table 4.2.6.4.1Perception of Sample Tourists on Potential of Tourism in Satara District
(n=326)
Sr.
Gender
Perception
Male Female TotalM
ean
SD Ran
k
Mea
n
S.D
Ran
k
Mea
n
S.D
Ran
k
1. 2. 3. 4. 5. 6. 7. 8. 9. 10.1. Satara District has Potential to
Attract Tourist fromMaharashtra/India.
4.16 0.65 1 4.17 0.66 1 4.16 0.65 1
2. Few Destinations Only in SataraHave Potential to Attract ForeignTourist.
3.77 0.80 4 3.78 0.80 4 3.77 0.80 4
3. Satara District has Few Unexploitedbut Worth Seeing TouristDestination.
3.66 0.76 6 3.67 0.76 6 3.66 0.76 6
4. Package Tours Would be of GreatTourist Attraction for The Tourist inMaharashtra.
3.67 0.84 5 3.68 0.85 5 3.67 0.84 5
5. Package Tours Would be of GreatAttractions for the Tourist Outside ofMaharashtra.
3.84 0.80 3 3.84 0.81 3 3.84 0.80 3
6. Existing Hotel Facility is Adequatefor Tourist in Satara District.
3.660.
756 3.66 0.76 7 3.66 0.75 6
7. Advertisement by Celebrity WouldHelp Much to Attract Tourist toSatara.
3.85 0.85 2 3.86 0.84 2 3.85 0.85 2
Correlation Coefficient male and female .964**
Sig. (2-tailed) .000Source: Field Data**. Correlation is significant at the 0.01 level (2-tailed).
Table 4.2.6.4.1 depicts that Satara has potential for tourism and there is no gender
difference in the perception.
All the seven statements show the mean score above three. Statement viz. Satara
district has potential to attract tourist from Maharashtra/India received first rank, as
Data Analysis
Shivaji University, Kolhapur 214
the mean score is highest (4.16). Followed by statement viz. advertisement by
celebrity would help much to attract tourist to Satara whose mean score is 3.85 and
received rank is 2nd and statement i.e. package tours would be of great attraction for
the tourist outside of Maharashtra received rank 3rd since the mean score is 3.84. It
focuses on potential of tourism in Satara.
The Spearman’s rank correlation of gender perception on potential of tourism is 0.964
with ‘P’ value 0.00, which is significant at 0.01 levels (2-tailed). Thus, there is
uniformity in the opinion of both male and female on potential of tourism in Satara to
attract the tourist.
Perception of HoteliersFollowing table presents the perception of hoteliers on potential of tourism in Satara.
Table 4.2.6.4.2Perception of Sample Hoteliers on Potential of Tourism in Satara District
(n=40)
Source: Field Data)
Table 4.2.6.4.2 represents perception of sample hotelier about the potential of tourism
with seven statements. The first rank received to the ‘Satara district has potential to
attract tourist from Maharashtra/India’ as the mean score is highest 4.48, 2nd rank
received to statement ‘existing hotel facility is adequate for tourist in Satara district’
as the means score is 4.08 and 3rd rank goes to ‘package tours would be of great
Sr.Statements of Perception Mean S.D Rank
1. 2. 3. 4.1. Satara District has Potential to Attract Tourist from
Maharashtra/India.4.48 0.55 1
2. Few Destinations Only in Satara Have Potential toAttract Foreign Tourist.
3.80 0.88 6
3. Satara District has Few Unexploited but WorthSeeing Tourist Destination.
3.98 0.73 4
4. Package Tours Would be of Great Tourist Attractionfor The Tourist in Maharashtra.
3.68 0.73 7
5. Package Tours Would be of Great Attractions for theTourist Outside of Maharashtra.
4.03 0.62 3
6. Existing Hotel Facility is Adequate for Tourist inSatara District.
4.08 0.89 2
7. Advertisement by Celebrity Would Help Much toAttract Tourist to Satara.
3.95 0.90 5
Data Analysis
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attraction for the tourist outside of Maharashtra’ as the mean score is 4.03. So the
mean score of these three statements is more than 4. It infers that Satara has potential
to attract tourist. Thus, hotel facility and tour operator may help to increase tourism
development and tourist flow in Satara. The rest of the statements do not reflect the
confidence as the mean score is less than four i.e. neither agree nor disagree.
Perception of Tour Operators
Following table talks on perception of sample tour operators on potential of tourism in
Satara district.
Table 4.2.6.4.3Perception of Sample Tour Operators on Potential of Tourism in Satara District
(n=10)
Sr Perception about potential of tourism Mean SD Rank1. Satara District has Potential to Attract Tourist from
Maharashtra/India.4.3 0.48 1
2. Few Destinations Only in Satara Have Potential toAttract Foreign Tourist.
4 0.82 4
3. Satara District has Few Unexploited but Worth SeeingTourist Destination.
4.2 0.63 2
4. Package Tours Would be of Great Tourist Attractionfor The Tourist in Maharashtra.
3.8 0.79 6
5. Package Tours Would be of Great Attractions for theTourist Outside of Maharashtra.
4.1 0.88 3
6. Existing Hotel Facility is Adequate for Tourist inSatara District.
3.4 0.97 7
7. Advertisement by Celebrity Would Help Much toAttract Tourist to Satara.
4 0.94 4
Correlation Coefficient .090Sig. (2-tailed) .848Source: Field Data
Table 4.2.6.4.3 reveals that the four statements focuses on the potential of tourism as’
Satara District has Potential to Attract Tourist from Maharashtra/India’ that received
1st rank as the mean score is 4.3, ‘Satara District has Few Unexploited but Worth
Seeing Tourist Destination’ received second rank as the mean score is 4.2, ‘Package
Tours Would be of Great Attractions for the Tourist Outside of Maharashtra’ received
third rank as the mean score is 4.1 and ‘Advertisement by Celebrity Would Help
Much to Attract Tourist to Satara’ received fourth rank as the mean score is 4.
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To look into the depth of analysis researcher test the spearman’s rank correlation
between perceptions of tour operator with hotel owners on potential of tourism in
Satara. The correlation coefficient is 0.090 with ‘P’ value 0.848, which is insignificant
at 0.05 levels (2-tailed). This reveals that there is no uniformity into opinions among
tour operators and hoteliers.
Researcher is interested in first 3 ranked statements by tourist to infer the data. Data
focuses that all stakeholders strongly agreed with statement ‘Satara district has
potential to attract tourist from Maharashtra/India’ but there is difference of opinion
about other two statements that are ranked by tourist second and third.
Tourist strongly agreed on statement that ‘celebrity would help much to attract tourist
to Satara’ whereas hoteliers and tour operator do not agree since they ranked these
statement 5th and 4th respectively.
Tourist strongly agreed on statement ‘Package tour would be of great attraction for
the tourist outside of Maharashtra’ but tour operator and hotelier do not strongly agree
as they have given sixth and seventh rank respectively. It infers that all are carrying
similar perception that Satara district has potential to attract tourist from
Maharashtra/India.
4.2.6.5 Perception on Promotion of Tourism in Satara District:
This part deals with the perception of stakeholders on promotion of tourism in Satara
District. Promotion is important tool in marketing mix to deliver satisfaction to the
target customer. Different tools are used to promote tourism products like
advertisement, publicity, personal selling, and sales promotion. Researcher has
developed three statements viz. advertisement play important role in tourism, need of
promotion activities and lack of promotion hinder tourism development of Satara
District and collected the responses on 5 point scale as 1 for strongly disagree, 2 for
disagree, 3 for neither agree nor disagree, 4 for agree and 5 for strongly agree. Data
analyzed with Mean, Standard Deviation, rank and Spearman’s rank correlation. Each
stakeholder opinion described in following tables.
Data Analysis
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Perception of Tourist
Following table shows the perception of sample tourists on promotion of tourism in
Satara district. It is observed that there is a lack of promotion in tourism sector of
Satara. To support the observation and to know its necessity the opinion of tourist
(Customer) on promotion of tourism in Satara is taken into granted. There may be
difference of opinions between male and female. Responses on the aforesaid
statements are existing in following table.
Table 4.2.6.5.1Perception of Sample Tourists on Promotion of Tourism in Satara District
(n=326)
Sr.
Name ofDestinationStatement ofPerception
Male Female Total
Mean S.D. Rank Mean S.D. Rank Mean S.D. Rank
1. 2. 3. 4. 5. 6. 7. 8. 9. 10.
1.AdvertisementPlay ImportantRole in Tourism
4.08 0.73 2 4.08 0.73 2 4.08 0.73 2
2.Need ofPromotionalActivities
4.19 0.74 1 4.19 0.74 1 4.19 0.74 1
3.
Lack ofPromotionHinder TourismDevelopment ofSatara District
4.02 0.89 3 4.01 0.89 3 4.02 0.89 3
Correlation Coefficient of male and female 1.000**
Sig. (2-tailed) 0.00
Source: Field Data**. Correlation is significant at the 0.01 level (2-tailed).
Table 4.2.6.5.1 infers that all three statements draw the attention on need of
promotion for tourism development in Satara district since the mean score is four.
Among the three statement the statement ‘need of promotional activities’ received 1st
rank due to its mean score is 4.19, ‘advertisement plays important role in
tourism’ received 2nd rank and has mean score 4.08 and the statement “lack of
promotion hinders tourism development of Satara district” received 3rd rank since
mean score is lesser compared to other two statements i.e. 4.02.
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The Spearman’s rank correlation between the opinions of male and female to the
perception on promotion of tourism in Satara is 1.000 with ‘P’ value 0.00, which is
significant at 0.01 levels (2-tailed). This reveals that there is uniformity into the
opinions of male and female.
Hoteliers Perception
Following table talks the perception of hoteliers on promotion of tourism in Satara
district.
Table 4.2.6.5.2Hoteliers’ Perception on Promotion of Tourism in Satara District
(n=40)
Source: Field Data
Table 4.2.6.5.2 infers that there is need of promotional activities for the tourism in
Satara district and advertisement will play important role for the same.
The statement ‘need of promotional activities’ received 1st rank as the mean score is
4.27 Followed by the statement ‘advertisement play important role in tourism’ with
the mean score is 4.02 received 2nd rank, ‘Lack of promotion hinders tourism
development of Satara district’ received 3rd rank and mean score is 3.95. The mean
score of a first two statements is more than 4. It signifies promotion is indispensable
to Satara tourism development.
Sr.Statement of Perception
Mean SD Rank
1. 2. 3. 4.1. Advertisement Play Important Role in
Tourism4.02 0.70 2
2. Need of Promotional Activities 4.27 0.85 13. Lack of Promotion Hinder Tourism
Development of Satara District3.95 0.68 3
Data Analysis
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Tour Operators Perception
Following table reveals the perception of tour operators on promotion of tourism in
Satara district.
Table 4.2.6.5.3Tour Operators Perception on Promotion of Tourism in Satara District
(n=10)
Sr Statement of Perceptions Mean SD Rank1. Advertisement Play Important Role in
Tourism4.4 0.52 2
2. Need of Promotional Activities 4.8 0.42 13. Lack of Promotion Hinder Tourism
Development of Satara District4.3 0.95 3
Correlation Coefficient 1.000**
Significant(2-tailed) .00Source: Field Data
Table 4.2.6.5.3 infer that statement ‘need of promotional activities’ received rank 1st
as the mean score is 4.8 and statement ‘advertisement play important role in tourism’
received second rank as the mean score is 4.4 and 3rd rank received to the statement ‘
lack of promotion hinders tourism development of Satara district’ carries mean score
4.3. Thus it concludes that according to the perception of tour operators there is need
of promotion activities in Satara.
To investigate into the depth of analysis researcher has test the spearman’s rank
correlation between the perception of hoteliers and tour operators. The correlation
coefficient score is 1.000 with ‘P’ value 0.00, which is significant. It reveals uniform
opinions between tour operator and hotelier
It is notice that all stakeholders strongly agreed on three statements viz. ‘Need of
Promotional Activities’, ‘Advertisement Play Important Role in Tourism’ and ‘Lack
of Promotion Hinders Tourism Development of Satara District’. All are carrying
uniform opinion that Satara needs promotional activities. Lack of promotion hindered
tourism development and advertisement will be helpful to promote tourism.
Data Analysis
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4.2.6.6 Perception of Stakeholders on Satisfaction towards the tourist Servicesand Amenities available in Satara:
This part depicts the perception of stakeholders on satisfaction of tourist services and
amenities available in Satara district. There are 33 tourist services and amenities are
considered to know their opinions. Researcher is intending to find out the gap
between perception of tourist with service provider hoteliers and tour operators. Data
is collected on 5-point likert scale and analyzed with mean, standard deviation, and
rank score. To probe into the depth of analysis researcher has calculated spearman’s
rank correlation between perceptions of tourist and other stakeholders i.e. hotelier and
tour operator.
Satisfaction Level of Stakeholders
Following table orate on sample units as tourists, hoteliers, tour operators’ opinion on
satisfaction of tourists’ services and amenities in Satara.
Table: 4.2.6.6.1Satisfaction of Tourism Stakeholders towards the Tourist Services and Amenities
Sr.
Stakeholders’Perception
Tourist Service andAmenities
Tourists’Satisfaction
Hoteliers’Satisfaction
Tour Operators’Satisfaction
MeanRank
S.D. MeanRank
S.D. MeanRank
S.D.
1. 2. 3. 4. 5. 6. 7. 8. 9. 10.
1.Air ConnectivityStatus
1.29 33 0.49 1.17 33 0.38 1.71 33 1.11
2. Rail ConnectivityStatus
1.96 32 0.76 2.20 32 0.91 2.90 15 0.99
3. Quality of the Roads 3.17 16 0.95 2.90 25 1.08 3.00 11 0.944. Quality of Way Side
Amenities Availableon This Road
3.30 14 0.80 3.40 16 0.98 2.80 18 1.40
5. Public ConveniencesAlong Roads/Streets
3.02 23 0.96 3.13 22 1.18 2.60 22 1.35
6. Sewage and DrainageSystem
3.11 20 0.94 3.00 24 1.13 2.11 31 0.78
7. Garbage Disposal 3.16 17 0.85 3.10 23 1.12 2.30 28 1.068. Condition of City
Roads2.79 29 1.09 2.90 25 1.13 2.20 29 1.14
9. Drinking WaterSupply
3.43 11 0.81 3.67 12 0.77 2.80 18 1.14
10. Condition of StreetLighting
3.40 12 0.86 3.40 16 1.01 2.90 15 1.20
Data Analysis
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11. Traffic Management 2.92 28 1.12 2.90 25 1.30 2.20 29 0.9212. Condition of Traffic or
Transport Signage3.10 21 1.02 3.73 11 0.82 3.00 11 1.15
13. Availability ofCommercialTransportations
3.52 10 0.83 4.13 2 0.52 3.90 2 0.74
14. Behaviour of theDrivers of CommercialTransportations
3.75 6 0.71 4.13 2 0.40 3.80 3 0.79
15. Availability ofAuthorized TourOperators
2.99 24 0.87 3.58 13 0.75 3.40 10 0.97
16. Availability of Hotels 3.55 8 0.90 4.03 4 0.53 4.00 1 0.8217. Behaviour of Service
Staff at the Hotel3.67 7 0.74 3.83 8 0.90 3.60 6 0.70
18. Tariff Structure of theHotel Rooms
3.12 19 0.82 3.38 18 0.78 3.50 7 0.85
19. Hygiene at WaysideRestaurants andDhabas
3.16 18 0.97 4.03 4 0.80 3.44 8 0.88
20. Availability of PetrolPump
3.09 22 1.11 3.25 20 1.10 3.70 5 0.48
21. Behaviour of ServicePersonnel at WaysideRestaurants andDhabas
3.76 4 0.67 3.75 10 0.49 3.44 8 0.88
22. Levels of Road Taxeson Vehicles(Tax Rates)
2.78 30 0.94 3.14 21 0.72 2.67 21 1.32
23. Administration of theRoad Taxes
2.99 25 0.95 3.36 19 0.64 2.89 17 1.17
24. Public Utilities at theTourist Attraction
2.65 31 1.25 2.24 31 1.15 2.10 32 0.88
25. General CleanlinessTourist Attraction andArea Around it
3.25 15 0.97 2.85 28 1.00 2.50 24 0.97
26. Condition of SignageWithin the TouristAttraction
3.36 13 1.25 3.43 15 0.75 2.60 22 0.97
27. Parking Facility at theTourist Attraction
2.95 27 1.24 2.63 30 1.19 2.50 24 0.97
28. Availability of TrainedTourist Guides
2.98 26 1.10 3.46 14 1.02 2.40 27 1.35
29. Behaviour of theGuides at the TouristAttraction
3.53 9 0.75 3.94 7 0.61 3.00 11 1.22
30. Conservation ofHeritage Sites
3.76 3 0.85 2.76 29 1.02 2.50 24 0.97
31. Promptness at theTicketing Window ofthe Monument/TouristAttraction
4.19 1 0.65 4.00 6 0.55 3.00 11 0.87
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32. Power SupplySituation
3.75 5 0.66 3.78 9 0.77 2.80 18 1.03
33. Telephone/MobileServices
3.93 2 0.86 4.43 1 0.55 3.80 3 1.23
Correlation Coefficient Tourist and Hoteliers .358*
Sig. (2-tailed) .041
Correlation Coefficient Tourist and Tour operator .294
Sig. (2-tailed) .097
Correlation Coefficient Hoteliers and Tour operator .767**
Sig. (2-tailed) .000Source: Field Data*. Correlation is significant at the 0.05 level (2-tailed).**. Correlation is significant at the 0.01 level (2-tailed).
Table 4.2.6.6.1 depicts stakeholder viz. tourists, hoteliers, and tour operators’
satisfaction level towards 33 tourist services and amenities. Tourists are strongly
satisfied with promptness of ticketing window of the monuments/tourist attraction,
telephone/mobile services, conservation of heritage sites and behaviour of service
personnel at wayside restaurants and Dhabas. Whereas hoteliers are strongly satisfied
with the telephone and mobile services, hygiene at wayside restaurants and Dhabas,
availability of commercial transportation and behaviour of the drivers of commercial
transportation. Tour operators are strongly satisfied with the availability of hotels,
availability of commercial transportation, behaviour of commercial transportation and
telephone and mobile services since the mean score is more than 3
However tourists are strongly dissatisfied with the air and rail connectivity, public
utilities at the tourist attraction and levels of road taxes on vehicles. Hoteliers are
dissatisfied with air and rail connectivity, public utilities and parking facility at the
tourist attraction. Tour operators are dissatisfied with the air connectivity, public
utilities at the tourist attraction, sewage and drainage system, condition of city roads
and traffic management since the mean sore is less than 3
To probe into the depth of analysis researcher has calculated spearman’s rank
correlation between perception of stakeholders towards the satisfaction level of tourist
services and amenities. Spearman’s rank correlation coefficient score is 0.358, 0.294
and 0.767 respectively, with 041, .097 and 0.000 ‘P’ value respectively, which is
significant at (tourists and hotelier) 0.05 level and (hoteliers and tour operator) 0.01
levels (2-tailed). But the tour operators ‘P’ value is more i.e. 0.97 at 0.05 levels which
Data Analysis
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is insignificant. Thus, perception of tourists and hoteliers has significant relation
whereas the tour operator does not. There is a gap between the perception of tourist
and tourist service provider (tour operator) and not the hoteliers
(T-Test)
The data of satisfaction towards 33 tourist services were obtained on 5 point scalewith median of 3 to see the overall distribution of stakeholders. One sample‘t’ test hasbeen used with test value ‘3’. Following table narrates the‘t’ test.
One-Sample Test
Sr.Satisfaction
Test Value = 3
t dfSig.(2-tailed)
MeanDifference
95% ConfidenceInterval of theDifferenceLower Upper
1 Tourist 2.026 32 .051 .19333 -.0010 .38772 Hoteliers 2.771 32 .009 .32212 .0853 .55893 Tour
Operators-.865 32 .393 -.08909 -.2989 .1207
The calculated ‘t’ is significant in case of hoteliers since the ‘p’ value is 0.009. The
same is insignificant in case of tour operators and the ‘t’ is on border since the ‘p’
value is .051 regarding tourist. Overall satisfaction count dwindles around mid point
i.e. test value 3 which is not much significant.
4.2.6.7 Perception of Stakeholders on importance towards the tourist Servicesand Amenities available in Satara:
This part depicts the perception of stakeholders on importance of tourist services and
amenities available in Satara district. There are 33 tourist services and amenities are
considered to know their opinions. Researcher is intending to find out the gap
between perception of tourist with hoteliers and as well with tour operators. Data is
collected on 5-point likert scale and simple statistical tools like mean, standard
One-Sample Statistics
Sr. Satisfaction N Mean Std. Deviation Std. Error Mean1 Tourist 33 3.1933 .54809 .095412 Hoteliers 33 3.3221 .66781 .116253 Tour Operators 33 2.9109 .59167 .10300
Data Analysis
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deviation, and rank are used for analysis. To investigate in depth of analysis
researcher has calculated Spearman’s rank correlation between perceptions of tourist
and other stakeholders i.e. hotelier and tour operator.
Importance Level of Stakeholders
Following table shows the distribution of importance level of tourist services and
amenities in the view of three-sample unit viz. tourist, hoteliers and tour operators.
Table 4.2.6.7.1Distribution of Importance level of tourist services and Amenities in the view of threesample units viz. Tourists, Hoteliers, and Tour Operators
Sr.
Stakeholders’ Perception
Tourist Service andAmenities
Tourists’Perception
Hoteliers’Perception
Tour Operators’Perception
Mean
Rank
S.D.Mean
Rank
S.D.Mean
Rank
S.D.
1. 2. 3. 4. 5. 6. 7. 8. 9. 10.1. Air Connectivity Status 2.83 33 1.30 3.18 33 1.39 2.6 33 1.432. Rail Connectivity Status 3.10 32 1.23 3.53 32 1.13 3.1 32 1.23. Quality of the Roads 4.45 8 0.56 4.40 6 0.55 4.6 3 0.524. Quality of Way Side
Amenities Available onThis Road
4.29 15 0.68 4.25 19 0.49 4.2 20 0.42
5. Public ConveniencesAlong Roads/Streets
4.2318
0.664.33
11
0.47
4.2 200.63
6. Sewage and DrainageSystem
4.2024
0.654.43
3 0.50 4.3 11 0.48
7. Garbage Disposal4.21
19
0.654.43
3 0.50 4.3 11 0.67
8. Condition of City Roads 4.39 13 0.57 4.48 2 0.51 4.6 3 0.79. Drinking Water Supply
4.44 9 0.56 4.43 3 0.50 4.8 10.42
10. Condition of StreetLighting
4.24 7 0.67 4.15 26 0.43 4.2 20 0.63
11. Traffic Management 4.42 11 0.61 4.25 19 0.49 3.9 30 1.112. Condition of Traffic or
Transport Signage4.47 7 0.58 4.28 17 0.45 4.5 5 0.53
13. Availability ofCommercialTransportations
4.32 14 0.59 4.30 16 0.56 4.2 20 0.42
14. Behaviour of the Driversof CommercialTransportations
4.16 26 0.69 4.35 10 0.48 4.5 5 0.53
15. Availability ofAuthorized TourOperators
3.14 31 1.24 4.05 29 0.45 4 29 0.82
16. Availability of Hotels 4.14 27 0.96 4.38 8 0.49 4.5 5 0.53
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17. Behaviour of ServiceStaff at the Hotel
4.2023
0.54 4.33 11 0.47 4.2 20 0.42
18. Tariff Structure of theHotel Rooms
4.16
25
0.52
4.21
24
0.52
4.220
0.42
19. Hygiene at WaysideRestaurants and Dhabas
4.26 16 0.52 4.40 6 0.50 4.3 11 0.48
20. Availability of PetrolPump
4.20 22 0.54 4.28 17 0.60 4.3 11 0.67
21. Behaviour of ServicePersonnel at WaysideRestaurants and Dhabas
4.21 21 0.57 4.15 26 0.43 4.2 20 1.03
22. Levels of Road Taxes onVehicles(Tax Rates)
3.97 30 0.64 3.94 31 0.47 4.3 11 0.67
23. Administration of theRoad Taxes
4.04 29 0.57 4.00 30 0.59 4.3 11 0.48
24. Public Utilities at theTourist Attraction
4.59 4 0.55 4.33 11 0.47 4.5 5 0.71
25. General CleanlinessTourist Attraction andArea Around it
4.60 2 0.57 4.33 11 0.47 4.3 11 0.67
26. Condition of SignageWithin the TouristAttraction
4.57 6 0.55 4.25 19 0.44 4.2 20 0.63
27. Parking Facility at theTourist Attraction
4.58 5 0.56 4.38 8 0.49 4.3 11 0.67
28. Availability of TrainedTourist Guides
4.21 20 0.91 4.23 23 0.58 4.3 11 0.48
29. Behaviour of the Guidesat the Tourist Attraction
4.09 28 0.77 4.24 22 0.61 4.2 20 0.44
30. Conservation of HeritageSites
4.60 2 0.58 4.20 25 0.55 4.5 5 0.53
31. Promptness at theTicketing Window of theMonument/TouristAttraction
4.39 12 0.59 4.11 28 0.52 3.9 30 0.74
32. Power Supply Situation 4.44 10 0.67 4.33 11 0.47 4.4 10 0.733. Telephone/Mobile
Services4.72 1 0.46 4.58 1 0.50 4.8 1 0.42
Correlation Coefficient Tourist and Hoteliers .479**
Sig. (2-tailed) .005Correlation Coefficient Tourist and Tour operator .565**
Sig. (2-tailed) .001Correlation Coefficient Hoteliers and Tour operator .642**
Sig. (2-tailed) .000Source: Field Data**. Correlation is significant at the 0.01 level (2-tailed).
Data Analysis
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Table 4.2.6.7.1 reveals that air and rail connectivity, availability of tour operators as if
services are least important in the view of all the stakeholders. However, about level
of road taxes on vehicles opinion of hoteliers and tourists are the same i.e. least
important. As per tour operators, opinion traffic management and promptness at the
ticketing window of the monument/tourist attraction are least important.
Administration of the road taxes is least important as hotelier’s opinion. All
stakeholders felt telephone and mobile is most important service. But conservation of
heritage, public utility and general cleanliness at tourist attraction are most important
as per tourist opinion. Hoteliers and tour operators felt most important civic amenities
viz. sewage and drainage system, garbage disposal, condition of city roads and
drinking water supply. Tour operators felt quality of roads is most important for
tourism development in Satara.
To look into the depth of analysis researcher has calculated Spearman’s rank
correlation between perception of stakeholders towards the importance level of tourist
services and amenities. Spearman’s rank correlation coefficient score is 0.479 and
0.565, 0.642 respectively, with .005, 0.001 and .000 ‘P’ value respectively, which is
significant at (tourists and hoteliers), (tourist and tour operators) and (hotelier and
tour operator) 0.01 levels (2-tailed) Thus, perception of stakeholders has significant
relation on importance of tourist services and amenities.
The data of satisfaction towards 33 tourist services were obtained on 5-point scale
with median 3 to see the overall distribution of stakeholders. One sample‘t’ test has
been used with test value ‘3’. Following table narrates the‘t’ test.
Sr.One-Sample Statistics
Importance N MeanStd.Deviation
Std. ErrorMean
1 Tourist 33 4.2079 .42315 .073662 Hoteliers 33 4.2276 .26655 .046403 Tour Operators 33 4.2340 .41730 .07264
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Sr.
One-Sample Test
Importance
Test Value = 3
t dfSig. (2-tailed)
MeanDifference
95% Confidence Intervalof the Difference
Lower Upper1 Tourist 16.398 32 .000 1.20788 1.0578 1.35792 Hoteliers 26.456 32 .000 1.22758 1.1331 1.32213 Tour
Operators16.988 32 .000 1.23401 1.0860 1.3820
The calculated‘t’ is significant in case of hoteliers and tour operators since the ‘p’
value is 0.00. Overall importance count dwindles around point i.e. test value 4 which
is significant.
To conclude, the satisfaction and importance towards tourist services and amenities
there found difference of opinion amongst stakeholders for satisfaction but uniformity
found in case of importance of these amenities.
Data Analysis
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Section VII
4.2.7 Selected Intellectuals Descriptive Analysis:
This section depicts the opinion on proposed projects in the 15 prospective
destinations of Satara. The projects are perceived by researchers twenty respondents
interviewed for the same. It consist government officials, newspaper reporters,
editors, social activist and towering personality of Satara on feasibility of tourism.
The said responses collected on 5 point scale 1 for not at all feasible to 5 for highly
feasible. The data analyzed and presented with mean, rank, and standard deviation.
Intellectuals’ Opinion of Feasibility of Tourism Project
Following table shows the opinion of governmental officials, newspaper reporters andeditors, social activists, and towering personality on feasibility of tourismdevelopment project at Satara district.
Table 4.2.7.1Opinion of Selected Intellectuals on Proposed Projects
Sr.
Location Name of Project Mean Rank S.D.
1. Bamnoli
Houseboat – Tapola, Bamnoli 3.71 19 1.06
Water Sports 3.57 20 1.12Mountaineering Institute 3.73 18 1.27Health Resorts 2.76 23 1.61Summer camps 4.60 2 0.60
2. Kas
Kite Festival 4.9 8 1.29Flora and Fauna 4.55 4 0.60Dirt Biking 2.00 27 1.64Dirt Cycling 3.11 22 1.49
3. ThosegharHanging pool 4.00 15 0.46Bungee Jump 2.00 27 1.53
4. AjinkyafortRappelling and Caving 4.55 4 0.60Paragliding and Parasailing 4.45 7 0.94Light and Sound Show 4.47 6 0.70
5. SaddavaghapurDirt Biking 1.76 29 1.44Dirt Cycling 3.25 21 1.34
6. Chalkewadi Tents 4.11 14 0.46
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7. Koyna
Residential Schools like Panchgani 2.41 26 1.62
Health Resorts 4.17 10 0.38Village tourism 4.76 1 0.44Eco Tourism 4.19 8 0.51
8. Yarad Riverside Tourism 4.11 13 0.479. Valmiki Winter camp 2.56 25 1.72
10. BanpuriA plateau valley, nature, small
waterfalls, windmills andForest,
4.13 12 0.34
11. Karad Village Tourism 4.16 11 0.37
12.
Saap(Rahimatpur), NanaPhadniswada(Wai), Vathar(Nimbalkarvada),Jalmandir, Adalatvada,Rajwada,(satara
Historical Havelis 3.84 17 0.76
13. Yawateshwar Health and Mediation Centres 2.63 24 1.64
14.
Gondawale/Sajjangarh/Aundh/Pal/Chphal/Wai/Bawadhan/Banpuri/PusegaonMaharah/Mhaswad/
Pilgrimage Tourism 4.57 3 0.51
15.Agashiv caves,Karad
Mediation Camp 3.85 16 1.04
Source: Field Data
The table 4.2.7.1 depicts prospects of Satara district to be developed as a tourist
destination with the help of 22 projects out of 29 (consideration by researcher) at a 15
different locations of Satara. Table shows feasibility of 22 projects out of 29 in
different locations of Satara District since the mean score is higher than 3. Out of that
Village tourism (Koyna), Summer camp (Bamnoli), Pilgrimage tourism (Gondawale,
Sajjangarh, Aundh, Pal, Chaphal, Wai, Bawadhan, Banpuri, Pusegaon, Mhaswad)
reflect most feasible tourism projects as they received highest mean score and rank
first 4 respectively. However, seven projects shows less feasibility as their mean
score is less than 3. Dirt Biking (Saddavaghapur, Kas), Bungee jump(Thoseghar),
Data Analysis
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residential school (Koyna) and Winter camp (Valmiki) like tourism projects shows
less feasibility in their respective locations since the ranks received are 29 to 25
respectively.
Since the local intellectuals responded favourable opinions on the project where mean
score is 4 and more. These locations can be come up as new tourist products. These
products may help capitalizing opportunity of product life cycle.
Data Analysis
Shivaji University, Kolhapur 231
Section VIII
4.2.8 SWOT Analysis:
The SWOT highlights the Strengths, Weaknesses, Opportunities, and Threats based
on infrastructural facilities and environmental aspects prevailing for tourism in Satara
District. The present work is based on researcher’s observation, interview, and
discussions with tourists, hoteliers, tour operators, NGOs, Government officials,
Social activist, and towering personalities of Satara.
SWOT Matrix
STRENGTHS WEAKENSSES
1. District Bounded With GorgeousNature.
2. Rich Historical Background.3. Geographical Diversity.4. National Highway.5. Better Transportation.6. Affordable Tourist Services.7. World Heritage Sites.8. Hill Station.9. Good Locations for Cinema
Shooting.10. Tourists Satisfaction towards
important services ‘promptness ofticketing window of themonument/tourist attraction’,Conservation of heritage site,‘telephone/mobile services’, and‘behaviour of service personnel atwayside restaurants and dhabas’ arestrengths of Satara.
1 Earthquake Prone Area.2 Absence ‘Sahyog’.3 Inconvenient Frequency Of Rail.4 Tourism Season Depends On Good
Rainfall And Climatic Condition.5 Dissatisfaction with important services
viz. ‘Condition of city roads’, ‘trafficmanagement’, ‘public utilities at touristattraction’ , ‘parking facility at thetourist attraction’, general cleanliness attourist attraction and area around’,‘quality of roads’ , ‘condition of trafficand transport signage’ are theweaknesses of Satara.
OPPORTUNITIES THREATS
1. Tourist flow is increasing.2. World Heritage.3. Emerging trend of Agro Tourism
and rural tourism.4. Bio Diversity Act.
1 Absence of political desire.2 Legal threats to implement the tourism
plan.3 Lack of coordination.4 Active Environmentalists.5 World Heritage Nature site and TigerConservation project will hinder theinfrastructural development.
Data Analysis
Shivaji University, Kolhapur 232
Strengths:
1. Habitant places in Satara district are bounded with gorgeous nature and ranges of
Sahyadri. A wide variety of beauty to see in Sahyadri ranges. Richest of its glory
and owing to flora and fauna, valleys, clouds, river, streams, variety of birds, water
reservoir Koyna and backflow, more than 10 lakes like Kas, Mayani,Venna etc.
More than 10 dams like Koyna, Dhom, Kanher, Urmodi, Veer, Balkwadi, Tarli,
Marathwadi, etc. Satara District is gifted with two Popular Hill Station viz
Mahabaleshwar and Panchagani. Budhist caves like Agashiv caves, Shirwal, and
many other caves like Ramghal, Morghal, Lahore, Rajapuri, Yarphal, Yeradwadi,
Helwak, Chaphal, etc. Satvahankalin or Hemandpati Tempels at Parli, Asle,
Dandeghar, Nagewadi, Vaduth, Khinai, Deur, Kikali, Mhavashi, Marul Haveli,
Bhaule, Aswali, Kanheri, Lohom, Vadagaon, Gursale, Ambheri, Khatav,
Nagnathwadi, Katharkhatav, Mhaswad, Nigadi, Chimangaon, Bhogaon, Kole,
Bawadhan etc., more than 25 Shivkalin forts54 Pratapgarh, Sajjangarh, Ajinkya
Tara, Vasantgarh, Sadashivgarh, Santoshgarh, Varugadh, Vasota, Pandavgarh,
Vairatgarh, Bhairavgarh, Dathegarh etc. Havelis55 and palaces at Satara, Saap near
Rahimatpur, Phltan, Vathar etc. Koyna Wild Life Sanctuary, Sayahadri Tiger
Project, and Koyna Power Project.
2. Quadrilateral national highway number 4 (proposed to be 6 lane) with service road
passes 120 Kilometers through Satara district and connects Mumbai (capital of
Maharashtra) via Pune in the north and Kolhapur ( a holy, heritage destination) in
South heading to Bangalore (Capital of Karnataka). Almost entire existing tourist
destinations are connected through state highway and within distance of 50 to 100
Km. from head quarter Satara.
3. Tourist related services are affordable and reasonable in Satara. Satara is ‘C’ grade
town.
4. Geographical Structure of Satara district is very diverse where almost one third of
its area is covered by Sahyadri ranges, which are hilly having forest, and declared
as eco sensitive zone. One third of its land is fertile which is in Krishna and
54 Shivkalin forts are the forts in the Shivaji’s (King of Maratha Kingdom inMaharashtra) tennure.
55 Haveli is the mansion or small palace of Prime Minister of kingdom.
Data Analysis
Shivaji University, Kolhapur 233
Koyana river basin and rest one third is dry terrain of which large area comes in
Deccan plateau.
5. Satara district grows many rare varieties of fruits (Ranmeva /Dongarimeva56) such
as Mulberry, Rasberry, Blueberry, Blackberry, Jumbo plums. It is also well-known
for Strawberry. Satara is known for its local sweets Kandi Pedha 57 , and
Mahbaleshwars jams and jelly sweets, which are very popular.
6. Kas and Koyna plateau of Satara District have been recognized and has place in
World Heritage site by UNESCO.
7. Temperature- Temperature-Max.-37.5 DegC., Min.-11.6 Deg. C. Rainfall- 2643
mm (Average) Satara has moderate temperature. It does not hinder tourists to visit
throughout the year.
8. More frequency of Non-stop Bus services to metro towns Mumbai, Pune and
Kolhapur.
9. Satara’s Natraj Mandir is only a 2nd Temple of its kind.
10. Oldest and biggest tree of India is located in Mhasve.
11. Worth seeing locations of Satara as Wai, Mahabaleshwar, Panchgani, Rahimatpur
and Satara attracts for cinema shooting.
12. Satara is known for rich historical background so with its ruins and its remnant.
13. Analysis of tourist services and amenities (refer Table No. 5.1.1) infer that
twenty-four services out of 33 are of high importance for the tourist and they are
highly satisfied with them. It means these are the strengths of Satara to develop as
a tourist destination. These tourist services and amenities are viz. ‘promptness of
ticketing window of the monument/tourist attraction’, ‘telephone/mobile
services’, and ‘behaviour of service personnel at wayside restaurants and dhabas’
and like.
Weaknesses:
1. The location Koyna Dam and surrounding are earthquake prone area
2. Sensitive zone like Koyna dam and surrounding will restrict tourist flow for
security purpose.
56 Dongrimeva term made up of two words dongri (hill) and Meva (Sweet), the berriesthat are avilable in the hilly region.57 Kandipedha, is a local sweets made up of milk solids and sugar.
Data Analysis
Shivaji University, Kolhapur 234
3. Lack of co-ordination between different departments and Absence of one
important ‘S’, ‘Sahyog’ of Tourism Policy 2006.
4. Inconvenient and less frequency of rail facility and only airstrip is available at
Karad, which is most of the time non-operational so Satara is inefficient to raise
tourist flow of outside states and countries.
5. Satara tourist season is depends on mainly good rainfall at destination like Kas
Flora, Thoseghar waterfall, Koyna Lake, hill stations like Mahableshwar and
Panchgani which depends on favourable climatic conditions.
6. Condition of city roads and roads that leads to potential tourist destinations are
narrow and in bad conditions.
7. Analysis of tourist services and amenities (Please refer the table No. 5.10.11)
focuses on tourist perception on 33 services and amenities in Satara. ‘Condition of
city roads’, ‘traffic management’, ‘public utilities at tourist attraction’ , ‘parking
facility at the tourist attraction’, general cleanliness at troust attraction and area
around’, ‘quality of roads’ , ‘condition of traffic and transport signages’ and
‘condition of signages within the tourist attraction’ are the services and amenities
which lie in 4th quadrant which reflects high importance and low satisfaction
level.
Opportunities:
1. Tourist flow is increasing at Satara. Narration is as follows
Tourist Arrival is in between July 2009 to June 2010 and the destinations are covered
like Mahabaleshwar, Panchgani, Shri Bhavani museum, Thoseghar,Kas Lake,
Ajinkya Fort, Sajjangad, Koyna lake.
Tourist Arrival
Following table shows tourist Arrival in between July 2009 to June 2010 and the
destinations are covered like Mahabaleshwar, Panchgani, Shri Bhavani museum,
Thoseghar, Kas Lake, Ajinkya Fort, Sajjangad, Koyna Lake.
Data Analysis
Shivaji University, Kolhapur 235
Table 4.2.8.1Tourist Arrival in Satara
(Numbers are individual tourists)
Sr.Type ofTourist
TotalActual figure
given
1. Foreign 4776 47772. Domestic 1550981 15509833. Total 1555757 1555760
Source: Incredible India, “Tourism Survey for State of Maharashtra”, Final Report,Ministry of Tourism (Market Research Division), Government of Indiahttp://www.tourism.gov.in/writereaddata/CMSPagePicture/file/marketresearch/statisticalsurveys/Maharashtra.pdf, dated 10/12/2011 at 4:05 PM
Tourist Arrival at Kas
Following table depicts the tourist arrival during 2008-9 to 2011-12 at Kas.
Table 4.2.8.2Tourist Arrival at Kas
(Numbers are individual tourists)
Source: Figures obtained from Deputy Conservator of Forest office, Satara
Above table 4.2.8.1 and 4.2.8.2 shows, the figures of tourist arrival are significant.
The increase in number of tourist is also significant as far as Kas is concerned. At
other places also there found significant increase in tourist arrival.
Sr. Year visitedDomesticvisitors
Foreignvisitors
Total No.of visitors
% change overprevious year
1. 2008-09 8972 - 8972 02. 2009-10 49347 - 49347 81.823. 2010-11 129927 43 129970 62.034. 2011-12 350000 - 350000 62.87
Data Analysis
Shivaji University, Kolhapur 236
Table 4.2.8. 3Tourist Arrival in Satara at different locations
(Numbers are individual tourists)
Sr.Year
Thoseghar Aundh Pratapgarh PanchganiMahabales
hwarKoyna
TouristArrival(Estimated)
% ofGrowthoverpreviousyear
TouristArrival(Estimated)
% ofGrowthoverpreviousyear
Tourist
Arrival
(Estimate
d)
% ofGrowthoverpreviousyear
TouristArrival(Estimated)
%ofGrowthoverprevious
year
TouristArrival(Estimated)
%ofGrowthoverprevious
year
TouristArrival(Estimated)
%ofGrowthoverprevious
year
1.
1999
-20
00
1323
2 0
2.
2000
-20
01
1032
574
0
1343
674
0
6369
1
79.2
2
3.
2001
-20
02
500-
600 0
6895
44
-49.
75
8766
45
-53.
27
8641
4
26.3
0
4.
2002
-20
03
750-
800
25
3560
1
0
7945
64
13.2
2
901,
110
2.71
9691
4
10.8
3
5.
2003
-20
04
000-
1100
27.2
7
9022
0
60.5
4
7779
87
-2.1
3
9312
10
3.23
1141
50
15.1
0
6.
2004
-20
05
1300
15.3
8
6908
3
-30.
60
8459
08
8.03
9838
00
5.35
1173
20
2.70
7.
2005
-20
06
800-
2000 35
3429
8
-10
1.42
7139
87
-18.
48
9010
18
-9.1
9
1268
51
7.51
8.
2006
-20
07
3300
-35
00
42.8
6
4997
9
31.3
8
8126
54
12.1
4
9231
00
2.39
1316
89
3.67
9.
2007
-20
08
5000
-60
00
41.6
7
4531
0
-10.
30
9093
21
10.6
3
1127
960
18.1
6
1389
14
5.20
Data Analysis
Shivaji University, Kolhapur 237
Source: Bhavani Museum office, Aundh, Forest Satara Taluka Office, Near S.T.Stand,Satara, Mahabaleshwar Forest Office, Pratapsinh Uddyan, Pratapgarh, NagarpalikaPanchgani, Nagarpalika Mahabaleshwar, Neharu Garden, Koyna PWD officeNA: Not availableNote: Tourist arrival was 43800 at Sajjangarh during July 2010 to June 2011. It isobserved that Tourist flow was doubled in 2012.
The above figures reveal that tourist flow is increasing to see the gorgeous nature of
Satara. It is increasing towards nature tourism like Kas, Thoseghar, and Koyna. Satara
has been gifted with beautiful nature, which can attract large number of tourist the
nation within and foreign countries.
2. UNESCO has recognized Kas and Koyna as World Nature Heritage Destinations.
The destinations would receive funds to conservation. This is likely to attract
foreign tourists UNSECO officials repeatedly.
3. Emerging trend of Agro Tourism where tourist can share farming life since
Satara’s cultivable land area is 799.4 thousand hectares, Village Tourism where
tourist can experience village life since there are 1727 villages in Satara, Rural
Tourism where tourist can share rural culture and traditions like Bagad at
Bawadhan, bullock-cart race in dry terrain of Mhasawad and surroundings, 1542
Sq Km forest area gives tourists scope for Eco Tourism and Heritage tourism
where tourist can enjoy historical sites while Satara has rich history of Shivaji
10.
2008
-20
09
8000
-85
00
29.4
1
3470
9
-30.
54
1144
190
0.53
1343
603
16.0
5
1268
18
-9.5
4
11.
2009
-20
10
1200
0-13
000
34.6
2
8877
8
0
5064
5
31.4
7
1262
700
9.39
1467
702
8.46
1277
29
0.71
12.
2010
-20
1117
00 0-18
00 027
.78
8098 8 -
9.61
871 23
29 0 -11
7.4
513
7865
5
8.41
1576
465
6.90
1442 50
11.4
5
13.
2011
-20
12
2500
0-27
000
33.3
3
8247
4
1.80
178
3295
5
29.3
3
NA
NA
1623
765 2.91
1159
99
-24.
35
Data Analysis
Shivaji University, Kolhapur 238
Maharaj and their descendants. Many social activist and saints were also part of
this beautiful land.
4. Bio Diversity Act passed to protect and Conserve the Nature and Wild Life. The
Bio Diversity Act provides provisions for regulated access to biological resources
by bonafide end-users for various purposes including scientific research,
commercial activities, and sustainable use of non-timber forest produce. The Act
is implemented through three functional bodies’ viz., NBA at the national level,
State Biodiversity Boards (SBBs) in different states, and Biodiversity
Management Committees (BMCs) at the level of local community (Panchayat).
The Act, according to Section 21 and Rule 20 of the Biodiversity Rules, insists
upon including appropriate benefit sharing provisions in the access agreement and
mutually agreed terms related to access and transfer of biological resources or
knowledge occurring in or obtained from India for commercial use, bio-survey,
bio-utilization or any other monetary purposes.
5. It has observed that trend of rural tourism where art and craft is indispensable.
Handicraft industries as Kale Tal-Karad is known for Stone carving, and entire
Man taluka is known for Sheppard’s local bedding (Jen).
6. Two Best museums Shivaji at Satara Headquarter and Aundh. Aundh can be the
best museum housed rare painting and sculptures of well-known artist from
worldwide. Shivaji museum is having large collection from Maratha Empire.
7. Many upcoming destinations like Kas-Lake, Kas Flora, and Thoseghar Waterfall,
Sajjangarh, Gondawale, Pusegaon, Chaphal, Koyna Lake, Ozarde waterfall,
Agashiv Caves, Aundh Museum, and Shivaji Museum etc.
Threats:
1. It observed that political desire is absent for the improvement and development of
Satara.
2. It is observed by researcher while encountering the discussion with bureaucrats of
the concerned department that legal threat to implement the tourism plan in
potential area which is under control of Archeological department/forest
Department (Thoseghar/Agashiv)
Data Analysis
Shivaji University, Kolhapur 239
3. Researcher observed that there is a lack of coordination between Tourism,
Archaeological, Forest, Irrigation, and Administrative department concerned with
Mayni bird Sanctuary.
4. Active Environmentalist in Satara District.58
5. UNESCO, Large Area lying in World Heritage Nature site and Tiger
Conservation project will hinder the infrastructural development. 59 (Wildlife
Protection Act 1972) Environment (Protection) Act 1986, a professional body
which will be responsible for the protection and sustainable development of the
Western Ghats).
58Wednesday, October 06, 2010 AT 12:00 AM (IST)Tags: environment, kas pathar, satara, western maharashtra, Tuesday,September 07, 2010 AT 12:31 AM (IST)Tags: kas pathar, satara, western maharashtra
59 http://articles.timesofindia.indiatimes.com/2012-03-27/pune/31244228_1_sandeep-shrotri-kas-plateau, accessed on 28 May 2012,http://articles.timesofindia.indiatimes.com/2011-07-14/pune/29772623_1_kas-plateau-illegal-constructions, 15 July 2011.
Data Analysis
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Section IX
4.2.9 Analysis of Tourist Services and Amenities:
In the previous section of data analysis the satisfaction and importance towards tourist
services and amenities has been assessed. In this section, the same analysis is
extended to every destination and the section concludes with perceptual gap
comprehensive of all stakeholders. The perceptual gap between importance and
Satisfaction level is analyzed with the help of 33 tourist services and amenities60 and
the similar sequence kept throughout the analysis. In the graph, only serial numbers of
these services and amenities are used. Since the data is collected using five-point
scale, the graph is demarked at midpoint 3 at both the axis. Wherever necessities the
serial number of services and amenities are given in the bracket after mention of
services for easy reference to the graph.
Infrastructural Gap at Koyna
The perceptual satisfaction and importance of respondents towards infrastructure
facilities are presented with the help of mean score, ranks, and standard deviation
(S.D).
Table 4.2.9.1Perceptual Gap between Importance and Satisfaction of Tourist towards TouristServices and Amenities at Koyna
(n=37)
Sr Tourist Services and AmenitiesSatisfaction Importance
Mean Rank S.D. Mean Rank S.D.1. Air Connectivity Status 1.35 33 0.48 2.65 33 1.032. Rail Connectivity Status 1.65 32 0.48 2.78 32 1.033. Quality of the Roads 3.16 19 0.55 4.24 8 0.434. Quality of Way Side Amenities Available
on This Road3.41 14 0.55 4.00 18 0.58
5. Public Conveniences AlongRoads/Streets
3.38 15 0.55 3.92 25 0.55
6. Sewage and Drainage System 3.16 19 0.50 3.92 27 0.557. Garbage Disposal 3.19 18 0.40 3.86 28 0.54
60 ‘Infrastructure Gaps in Tourism Sector at Five Tourist Destinations in India Based onPerception of Tourists’, report of Government of India, Ministry of Tourism, June 2010,accessed on 14 October, 2010, 11:09pm.
Data Analysis
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8. Condition of City Roads 2.73 27 0.87 4.00 18 0.539. Drinking Water Supply 3.70 6 0.62 3.97 22 0.5510. Condition of Street Lighting 3.27 16 0.73 3.92 25 0.6411. Traffic Management 2.59 28 1.04 4.41 6 0.5012. Condition of Traffic or Transport Signage 2.92 23 0.76 4.46 4 0.5113. Availability of Commercial
Transportations3.58 10 0.55 4.14 13 0.59
14. Behaviour of the Drivers of CommercialTransportations
3.61 9 0.50 4.11 15 0.61
15. Availability of Authorized TourOperators
3.25 17 0.45 3.51 31 0.65
16. Availability of Hotels 3.62 8 0.64 4.16 11 0.5517. Behaviour of Service Staff at the Hotel 3.52 13 0.51 4.00 18 0.4818. Tariff Structure of the Hotel Rooms 3.15 21 0.37 3.97 23 0.4219. Hygiene at Wayside Restaurants and
Dhabas3.00 22 0.71 3.95 24 0.40
20. Availability of Petrol Pump 2.51 30 0.73 4.00 18 0.3321. Behaviour of Service Personnel at
Wayside Restaurants and Dhabas3.56 12 0.50 4.03 17 0.29
22. Levels of Road Taxes on Vehicles(TaxRates)
3.65 7 0.63 4.16 11 0.50
23. Administration of the Road Taxes 3.57 11 0.77 4.14 13 0.5424. Public Utilities at the Tourist Attraction 2.30 31 1.08 4.49 2 0.5125. General Cleanliness Tourist Attraction
and Area Around it2.84 24 0.76 4.43 5 0.50
26. Condition of Signage Within the TouristAttraction
2.76 26 1.14 4.54 1 0.51
27. Parking Facility at the Tourist Attraction 2.57 29 1.39 4.49 2 0.6128. Availability of Trained Tourist Guides 2.78 25 0.97 3.57 30 1.0729. Behaviour of the Guides at the Tourist
Attraction4.33 1 0.58 3.62 29 0.95
30. Conservation of Heritage Sites 3.73 4 0.56 4.19 10 0.6231. Promptness at the Ticketing Window of
the Monument/Tourist Attraction3.92 2 0.65 4.35 7 0.68
32. Power Supply Situation 3.83 3 0.51 4.05 16 0.5733. Telephone/Mobile Services 3.73 4 0.77 4.22 9 0.53
Rank Correlation Coefficient 0.394Significant(2-tailed) 0.023*Correlation is significant at the 0.05 level (2-tailed).
Source: Field Data
Data Analysis
Shivaji University, Kolhapur 242
Graph: 1.
Table 4.2.9.1 reveals the mean score of satisfaction and importance of tourist services
amenities in Koyna. Tourists are satisfied with twenty-two tourist services and
amenities since the mean score is higher than 3 (quadrant Ist in the graph). The
dissatisfaction lies with these eleven tourist services and facilities, which are
important in nature, as the mean score is less than 3. Tourists are strongly satisfied
with ‘behaviour of the guide at tourist attraction’, which receives first rank, 2nd rank to
the ‘promptness of ticketing window of the Monument/Tourist attraction’, 3rd rank to
the ‘power supply’ and 4th rank each to ‘telephone and mobile services’ and
‘conservation of heritage site’. However, tourists are strongly dissatisfied with the
‘air’(1) and ‘rail(2) connectivity as ranks are thirty three and thirty two but these
services are marked as less important, availability of petrol pump receives thirty rank
and public utilities 31 rank.
Thirty-one tourist services and amenities are important to the tourist at the
Data Analysis
Shivaji University, Kolhapur 243
destination as their mean score is more than 3 but two are not important since the
mean score is less than 3. Services and amenities like ‘condition of signage within the
tourist attraction’ receives 1st rank, 2nd rank to ‘parking facility at the tourist
attraction’ and ‘public utilities at the tourist attraction’ each and 4th rank to ‘condition
of traffic and transport signage’ are most important. On the contrary, least important
are ‘air connectivity’ (1), ‘rail connectivity’ (2) that receives 33 and 32 ranks,
availability of tour operator receives 31 rank and 30 rank to the availability of trained
tourist guide.
To probe into the depth of analysis researcher has calculated Spearman’s rank
correlation coefficient of satisfaction and importance of tourist services and facilities.
The score is 0.394, which is significant at 0.05 levels (2-tailed).
For better understanding, the 33 variables are plotted on a graph of importance and
satisfaction scale with the median value 3, the graph has divided into 4 quadrants. 1st
quadrant shows high satisfaction and high importance level, 2nd shows high
satisfaction and low importance, 3rd shows low satisfaction and low importance and
4th quadrant shows low satisfaction and high importance of the tourist services and
amenities. In the first quadrant, 20 variables are in a sound position to depict the
highest satisfaction and highest importance. Among them tourist were most satisfied
about the ‘behaviour of guide’ but not in a proportionate importance. ‘Quality of
road,’ ‘availability of commercial transportation’, ‘administration of road taxes,’
‘quality of wayside amenities’, and ‘garbage disposal services and amenities’ did not
find much gap in their satisfaction and importance level. However, ‘promptness at the
ticket window’ and ‘power supply situation’ the gap is very meager. In the second
quadrant, there is no single variable. Third quadrant shows two variables i.e. ‘air’ and
‘rail’ connectivity. It means these two services do not demand the attention. Fourth
quadrant depicts 10 variables viz. Public utilities, parking facilities, traffic
management, condition of signage within tourist attraction, General cleanliness,
availability of petrol pump, condition of city roads, hygiene at wayside restaurant,
Dhabas and availability of trained tourist guide which highlights highest gap in
satisfaction and importance level.
Quadrant 4 is important to focus since these parameters are very important and
carries dissatisfaction in the opinion of sample tourists. Variable number 24, 26
Data Analysis
Shivaji University, Kolhapur 244
and 27 viz. ‘public utilities at tourist attraction,’ ‘condition of signage within the
tourist attraction’ and ‘parking facility at the tourist attraction’ need to be addressed
Infrastructural Gap at Mahabaleshwar
The perceptual satisfaction and importance of respondents towards infrastructure
facilities are presented with the help of mean score, ranks and standard deviation
(S.D).
Table 4.2.9.2Perceptual Gap between Importance and Satisfaction of Tourist towards TouristServices and Amenities at Mahabaleshwar
(n=30)
Sr.
Tourist Services and Amenities
Satisfaction Importance
Mean
Rank
S.D.Mea
n
Rank
S.D.
1. Air Connectivity Status 1.60 32 0.50 2.90 31 1.322. Rail Connectivity Status 1.80 31 0.71 2.97 30 1.353. Quality of the Roads 3.13 23 0.90 4.43 10 0.734. Quality of Way Side Amenities
Available on This Road3.23 21 1.14 4.27 23 0.78
5. Public Conveniences AlongRoads/Streets
2.77 25 0.86 4.40 12 0.72
6. Sewage and Drainage System 3.63 11 0.67 4.20 24 0.557. Garbage Disposal 3.80 8 0.48 4.17 26 0.388. Condition of City Roads 3.30 20 0.65 4.30 19 0.539. Drinking Water Supply 3.63 11 0.89 4.50 8 0.6810. Condition of Street Lighting 3.37 18 1.07 4.40 12 0.6211. Traffic Management 3.50 14 0.94 4.33 18 0.6612. Condition of Traffic or Transport
Signage3.37 18 1.00 4.30 19 0.53
13. Availability of CommercialTransportations
4.30 1 0.53 4.67 4 0.55
14. Behaviour of the Drivers of CommercialTransportations
3.80 8 0.66 4.37 15 0.56
15. Availability of Authorized TourOperators
2.67 27 0.87 2.07 32 1.01
16. Availability of Hotels 4.27 2 0.64 4.83 1 0.3817. Behaviour of Service Staff at the Hotel 3.97 5 0.32 4.43 10 0.5018. Tariff Structure of the Hotel Rooms 2.73 26 0.83 4.50 8 0.5119. Hygiene at Wayside Restaurants and
Dhabas3.47 17 0.57 4.57 6 0.50
Data Analysis
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20. Availability of Petrol Pump 2.57 28 0.82 4.40 12 0.5021. Behaviour of Service Personnel at
Wayside Restaurants and Dhabas3.90 7 0.80 4.03 28 0.61
22. Levels of Road Taxes on Vehicles(TaxRates)
1.83 30 0.59 4.07 27 0.83
23. Administration of the Road Taxes 2.23 29 0.90 4.30 19 0.5324. Public Utilities at the Tourist Attraction 2.93 24 1.05 4.57 6 0.5025. General Cleanliness Tourist Attraction
and Area Around it3.73 10 0.45 4.30 19 0.70
26. Condition of Signage Within the TouristAttraction
3.50 14 0.86 4.20 24 0.71
27. Parking Facility at the Tourist Attraction 3.50 14 0.86 4.37 15 0.6128. Availability of Trained Tourist Guides 3.63 11 0.49 4.37 15 0.7229. Behaviour of the Guides at the Tourist
Attraction3.17 22 0.41 3.97 29 0.49
30. Conservation of Heritage Sites 4.03 4 0.61 4.73 3 0.4531. Promptness at the Ticketing Window of
the Monument/Tourist Attraction* * * * * *
32. Power Supply Situation 4.03 3 0.33 4.60 5 0.5633. Telephone/Mobile Services 3.93 6 0.52 4.83 1 0.38
Rank Correlation Coefficient .588**
Significant(2-tailed) .000*Correlation is significant at the 0.01 level (2-tailed).
Source: Field Data*As there were no ticketing window so no responses.
Graph: 2.
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Table 4.2.9.2 reveals that tourists are satisfied with twenty-four tourist services and
amenities at Mahabaleshwar since their mean score is more than 3(quadrant Ist in the
graph) whereas dissatisfied with nine tourist service and amenities since the mean
score is less than 3.
Tourist are highly satisfied with the ‘availability of commercial transportation’,
‘availability of hotels’, ‘power supply’ and ‘conservation of heritage sites’ since they
receive first, second, third and fourth ranks respectively. Tourists are strongly
dissatisfied with the ‘air’(1) and ‘rail’(2) connectivity, ‘level of road taxes’ and
‘administration of the road taxes,’ ‘promptness in ticket window’ as they received
32th , 31st , 30th and 29th ranks respectively.
Tourist services as air (1), rail (2) and tour operator (15) are not important to the
tourists who have visited the destination as their mean score is less than 3. But
remaining thirty services tourist felt important since the mean score is more than 3.
‘Telephone/mobile’ services receives 1st rank, 2nd to ‘availability of hotels’, 3rd rank to
‘conservation of heritage site’ and 4th rank to ‘availability of commercial
transportation’ which are the most important services and amenities to the tourist.
However, ‘availability of authorized tour operator’ receives 32th rank, ‘air’ and ‘rail’
connectivity receives 31st and 30th ranks respectively and 29th rank to ‘behaviour of
guide at the tourist attraction’ are least important at Mahabaleshwar.
Spearman’s rank correlation coefficient of satisfaction and importance of tourist
services and facilities at Mahabaleshwar is 0.588, which is the significant at 0.01
levels (2-tailed). This signifies uniformity into opinions towards satisfaction and
importance.
In the first quadrant twenty-three variables shows high importance as well the high
satisfaction level. Out of this availability of hotels, availability of commercial
transportation, conservation of site, telephone and mobile service, power supply
shows highest gap. Tourist facilities, other services are the strengths of
Mahabaleshwar. No single variables lie in second quadrant. Three variables lie in the
third quadrant i.e. promptness of ticket window, availability of authorized tour
operator which shows the low importance and low satisfaction. Whereas ‘air’ and
‘rail’ connectivity is on the boundary of importance and satisfaction level. This infers
that ‘air’ and ‘rail’ connectivity is important at Mahabaleshwar. Eight variables lie in
Data Analysis
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the fourth quadrant, which shows the highest importance and lowest satisfaction level.
‘Taxes and permits’, ‘petrol pump’ and ‘tariff structure of hotel,’ ‘public convenience
along the road,’ ‘quality of roads’ and ‘public utilities at tourist attraction’ tourist
facilities and amenities shows gap in their importance and satisfaction level.
Quadrant 4 is important to focus since these parameters are most important and
carries more dissatisfaction in the opinion of sample tourists. Variable number 23, 20
and 18 viz. administration of road taxes, availability of petrol pump and tariff
structure of hotel rooms in Mahabaleshwar need to be address.
Infrastructural Gap at Panchgani
The perceptual satisfaction and importance of respondents towards infrastructure
facilities are presented with the help of mean score, ranks, and standard deviation
(S.D).
Table 4.2.9.3Perceptual Gap between Importance and Satisfaction of Tourist towards TouristServices and Amenities at Panchgani
(n=35)
Sr.
Tourist Services and AmenitiesSatisfaction Importance
Mean Rank S.D. Mean Rank S.D.1. Air Connectivity Status 1.29 32 0.62 3.31 31 1.212. Rail Connectivity Status 2.14 31 0.77 3.51 30 1.253. Quality of the Roads 3.71 11 0.46 4.54 12 0.514. Quality of Way Side Amenities
Available on This Road3.86 4 0.36 4.49 15 0.61
5. Public Conveniences AlongRoads/Streets
3.37 22 0.69 4.37 20 0.60
6. Sewage and Drainage System 3.66 14 0.84 4.59 11 0.567. Garbage Disposal 3.83 6 0.51 4.63 8 0.498. Condition of City Roads 3.77 7 0.43 4.66 5 0.549. Drinking Water Supply 3.49 19 0.78 4.74 2 0.4410. Condition of Street Lighting 3.69 12 0.53 4.71 3 0.4611. Traffic Management 3.43 20 0.70 4.66 5 0.4812. Condition of Traffic or Transport
Signage3.34 23 0.94 4.63 8 0.49
13. Availability of CommercialTransportations
3.77 7 0.65 4.46 16 0.51
14. Behaviour of the Drivers ofCommercial Transportations
3.88 3 0.59 4.54 12 0.51
15. Availability of Authorized TourOperators
3.40 21 0.89 2.29 32 1.30
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16. Availability of Hotels 3.74 10 0.82 4.71 3 0.4617. Behaviour of Service Staff at the
Hotel3.85 5 0.66 4.17 26 0.38
18. Tariff Structure of the Hotel Rooms 2.91 27 1.01 4.17 26 0.3819. Hygiene at Wayside Restaurants and
Dhabas3.66 14 0.80 4.37 20 0.49
20. Availability of Petrol Pump 3.11 26 0.83 4.26 23 0.4421. Behaviour of Service Personnel at
Wayside Restaurants and Dhabas3.77 7 0.65 4.09 29 0.62
22. Levels of Road Taxes onVehicles(Tax Rates)
2.66 29 1.08 4.17 26 0.71
23. Administration of the Road Taxes 2.69 28 1.11 4.20 25 0.5324. Public Utilities at the Tourist
Attraction2.66 9 0.84 4.46 16 0.51
25. General Cleanliness TouristAttraction and Area Around it
3.51 18 0.74 4.54 12 0.51
26. Condition of Signage Within theTourist Attraction
3.63 16 0.81 4.63 8 0.49
27. Parking Facility at the TouristAttraction
3.20 24 0.76 4.46 16 0.51
28. Availability of Trained TouristGuides
3.57 17 0.65 4.29 22 0.67
29. Behaviour of the Guides at theTourist Attraction
3.20 24 0.58 4.23 24 0.60
30. Conservation of Heritage Sites 3.68 13 0.48 4.43 19 0.5031. Promptness at the Ticketing Window
of the Monument/Tourist Attraction* * * * * *
32. Power Supply Situation 3.91 2 0.70 4.66 5 0.4833. Telephone/Mobile Services 4.31 1 0.58 4.77 1 0.43
Rank Correlation Coefficient .672**
Significant(2-tailed) .000*Correlation is significant at the 0.01 level (2-tailed).
Source: Field Data
*As there were no ticketing window so no responses.
Data Analysis
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Graph 3.
Table 4.2.9.3 depicts the tourist are satisfied with twenty-seven tourist services as the
mean score is more than three (quadrant Ist in the graph) and dissatisfied with six as
score is less than 3. Tourists are strongly satisfied with mainly ‘telephone/mobile
services’(33) whose rank is 1st, 2nd to power supply(32), 3rd to ‘behaviour of the
drivers of commercial transportation’(14) and 4th rank to ‘quality of wayside
amenities available on this road’(4). However, tourists are strongly dissatisfied mainly
with the ‘air’ and ‘rail’ connectivity whose ranks are 32 and 31 respectively. Services
like ‘level of road taxes on vehicles’ (22) and ‘public utilities at the tourist attraction’
(24) receive 29 ranks each.
‘Availability of authorized tour operator’(15) tourists felt unimportant as the mean is
less than 3 and remaining thirty-two amenities are important at Panchgani which
mean score is more than 3. Out of that 1st rank receives to ‘telephone/mobile
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services’, 2nd rank to ‘drinking water supply’(9), 3rd rank each to ‘condition of street
light’(10) and availability of hotels which reflects the highest importance level.
However, ‘availability of authorized tour operator’ receives rank 32 and 31st to ‘air
connectivity’ and 30th to ' rail’ and 29th rank to ‘behaviour of service personnel at
wayside restaurant and Dhabas’ (21).
Satisfaction and importance of tourist services and amenities Spearman’s rank
correlation coefficient score is 0.672. That is significant at the 0.01 levels (2-tailed).
This signifies uniformity into opinions of sample tourists’ satisfaction and importance
hence, quadrant number one is found to be heavy.
Twenty-two variables are positioned on the 1st quadrant. Among these ‘traffic and
transport management facilities’, ‘parking facility’, ‘availability of petrol pump,’
‘general cleanliness’ and ‘quality of road facilities’ shows highest gap whereas other
facilities having least gap. Single variable viz. availability of authorized tour operator
is on the second quadrant showing high satisfaction and least importance.
‘Promptness of ticket window’ is positioned in the third quadrant. Thus, this facility is
not essential at Panchgani. Seven variables viz. ‘air connectivity’, ‘rail connectivity’,
‘level of road taxes’ and ‘its administration’, ‘Public utilities at the tourist attraction’,
‘tariff structure of hotel rooms’(18) and ‘petrol pump’ positioned in the 4th quadrant
which shows the highest gap in their satisfaction and importance level. Thus, this area
demands the attention for tourism development as tourists are more dissatisfied with
services and these facilities shows high importance to them.
Thus, quadrant 4 is important to focus since these parameters are most important and
carries low satisfaction in the opinion of sample tourists. Variable numbers 22, 23 and
24 viz. ‘levels of road taxes on vehicles’, ‘administration of road taxes’ (23) and
‘public utilities at tourist attraction’ in Panchgani need to be addressed.
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Infrastructural Gap at Wai
The perceptual satisfaction and importance of respondents towards infrastructure
facilities are presented with the help of mean score, ranks, and standard deviation
(S.D).
Table 4.2.9.4Perceptual Gap between Importance and Satisfaction of Tourist towards TouristServices and Amenities at Wai
(n=37)
Sr. Tourist Services and AmenitiesSatisfaction Importance
Mean Rank S.D. Mean Rank S.D.1. Air Connectivity Status 1.05 32 0.23 2.76 32 1.422. Rail Connectivity Status 2.00 29 0.85 2.95 31 1.413. Quality of the Roads 3.35 6 1.06 4.49 4 0.514. Quality of Way Side Amenities
Available on This Road3.32 8 0.91 4.35 11 0.79
5. Public Conveniences AlongRoads/Streets
2.95 15 1.05 4.11 22 0.97
6. Sewage and Drainage System 2.16 28 1.17 4.32 12 0.477. Garbage Disposal 2.43 24 0.99 4.24 14 0.768. Condition of City Roads 3.05 13 0.81 4.62 2 0.499. Drinking Water Supply 2.97 14 1.07 4.54 3 0.5110. Condition of Street Lighting 3.38 4 0.59 4.43 7 0.6911. Traffic Management 2.81 17 1.29 4.11 22 0.5712. Condition of Traffic or Transport
Signage2.68 19 1.20 4.22 17 0.82
13. Availability of CommercialTransportations
3.14 12 0.79 4.08 24 0.55
14. Behaviour of the Drivers ofCommercial Transportations
2.57 21 0.85 4.13 21 0.72
15. Availability of Authorized TourOperators
1.69 30 1.03 4.07 25 0.96
16. Availability of Hotels 3.38 4 0.76 4.32 12 0.5817. Behaviour of Service Staff at the
Hotel3.30 11 0.87 4.07 25 0.69
18. Tariff Structure of the Hotel Rooms 3.31 9 0.88 3.82 27 0.8219. Hygiene at Wayside Restaurants and
Dhabas3.42 3 0.90 4.19 18 0.52
20. Availability of Petrol Pump 2.95 15 1.33 4.38 10 0.5921. Behaviour of Service Personnel at
Wayside Restaurants and Dhabas3.54 2 0.96 4.16 20 0.65
22. Levels of Road Taxes onVehicles(Tax Rates)
2.32 26 0.71 3.57 30 0.83
23. Administration of the Road Taxes 2.65 20 1.01 3.78 28 0.89
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24. Public Utilities at the TouristAttraction
2.22 27 1.13 4.24 14 0.76
25. General Cleanliness TouristAttraction and Area Around it
2.54 22 1.04 4.46 5 0.73
26. Condition of Signage Within theTourist Attraction
2.49 23 1.33 4.43 7 0.55
27. Parking Facility at the TouristAttraction
2.81 17 0.94 4.24 14 0.72
28. Availability of Trained TouristGuides
1.64 31 0.70 3.70 29 1.33
29. Behaviour of the Guides at theTourist Attraction
2.33 25 1.53 4.19 19 0.70
30. Conservation of Heritage Sites 3.30 10 1.15 4.46 5 0.7331. Promptness at the Ticketing
Window of the Monument/TouristAttraction
* * * * * *
32. Power Supply Situation 3.35 6 0.72 4.41 9 0.5033. Telephone/Mobile Services 4.14 1 0.75 4.78 1 0.42
Rank Correlation Coefficient .673**
Significant(2-tailed) .000*Correlation is significant at the 0.01 level (2-tailed).
Source: Field Data*As there were no ticketing window so no responses.
Graph 4
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Table 4.2.9.4 inferred that tourists are satisfied with fourteen tourist services as their
mean score is more than 3(quadrant Ist in the graph) and dissatisfied with nineteen
which mean score is less than 3 in Wai. ‘Telephone/mobile’ services receives 1st rank,
‘behaviour of service personnel at wayside restaurants and dhabas’ 2nd rank, 3rd rank
to ‘hygiene of wayside restaurant and dhabas’(19) and 4 rank to ‘availability of
hotels’(16) and ‘condition of street lighting’(10) each where tourist are strongly
satisfied. On the other hand, ‘air connectivity’, ‘availability of trained tourist guide’
(28) receives 32 and 31 rank respectively whereas ‘availability of authorized tour
operator’ receives 30th and 29th rank to ‘rail connectivity’ which reflect strong
dissatisfaction.
Only ‘air’ and ‘rail’ connectivity these two-tourist facilities tourists felt unimportant
as their mean score is less than 3 and remaining twenty-one are important because the
mean score is more than 3. Out of them ‘telephone/mobile services’, ‘drinking water
supply’, ‘condition of city roads’ and ‘quality of roads’ are most important as the
ranks are 1st four respectively. ‘Air connectivity’ and ‘rail connectivity’, ‘availability
of road taxes on vehicles’ and ‘availability of trained tourist guide’ status are least
important as the ranks are last four ie 32 to 29th respectively.
The Spearman rank correlation score is 0.673, which is significant at the 0.01 level (2-
tailed). This signifies uniformity into the opinion of tourist about satisfaction and
importance of tourist services and amenities at Wai.
1st quadrant shows eleven variables that reveal high satisfaction and high importance
towards tourist services and amenities. Second quadrant is empty, no single variable
found in this quadrant. Third quadrant having three variables viz. ‘promptness of
ticket window’ and ‘air’ and ‘rail’ connectivity, which are least, satisfied as well least
important to the tourist. Fourth quadrant having 19 variables that highlights its high
importance and low satisfaction level. The services viz. levels of road taxes on
vehicles, administration of road taxes, availability of trained tourist guide, behaviour
of the guide at the tourist attraction, condition of traffic and transport signage,
availability of authorized tour operators, sewage and drainage system, public utilities
at the tourist attraction, general cleanliness tourist attraction and area around it,
condition of signage within tourist attraction, parking facility at the tourist attraction,
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garbage disposal, behaviour of driver of commercial transportation, air connectivity,
availability of commercial transportation, traffic management, public convenience
along roads/streets, behaviour of service personnel at wayside restaurants and Dhabas
and drinking water supply shows tourists more dissatisfaction and high importance. It
means the Wai is still undeveloped for tourism. It demands more tourist facility and
services, which are lacking and are most important to the tourist who visited to the
Wai.
Therefore, quadrant 4 is important to focus since these parameters are most important
and carries dissatisfaction in the opinion of sample tourists. Variable number 6, 24, 26
and 25 viz. sewage and drainage system, public utilities at tourist attraction, condition
of signage within tourist attraction and general cleanliness of tourist attraction and
area around it in Wai need to be address.
Infrastructural Gap at Pratapgarh
The perceptual satisfaction and importance of respondents towards infrastructure
facilities are presented with the help of mean score, ranks, and standard deviation
(S.D).
Table 4.2.9.5Perceptual Gap between Importance and Satisfaction of Tourist towards TouristServices and Amenities at Pratapgarh
(n=30)
Sr.
Tourist Services and AmenitiesSatisfaction Importance
Mean
Rank
S.D.Mean
Rank
S.D.
1. Air Connectivity Status 1.00 33 0.00 3.17 32 1.262. Rail Connectivity Status 1.25 31 0.44 3.63 31 1.253. Quality of the Roads 3.40 19 0.81 4.57 6 0.684. Quality of Way Side Amenities
Available on This Road3.57 16 0.77 4.50 8 0.57
5. Public Conveniences AlongRoads/Streets
3.00 27 1.13 4.50 8 0.82
6. Sewage and Drainage System 3.13 23 0.73 4.20 24 0.617. Garbage Disposal 3.00 27 0.98 4.17 25 0.758. Condition of City Roads 3.13 23 0.68 4.27 20 0.649. Drinking Water Supply 3.10 25 0.84 4.43 12 0.5010. Condition of Street Lighting 3.54 17 0.52 3.73 30 0.9411. Traffic Management 3.33 21 0.84 4.33 17 0.48
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12. Condition of Traffic orTransport Signage
3.63 14 0.89 4.43 12 0.50
13. Availability of CommercialTransportations
4.10 3 0.61 4.37 15 0.67
14. Behaviour of the Drivers ofCommercial Transportations
4.23 2 0.68 4.27 20 0.91
15. Availability of Authorized TourOperators
2.83 29 0.98 * * *
16. Availability of Hotels 4.00 6 0.67 4.13 26 0.5117. Behaviour of Service Staff at the
Hotel3.70 12 0.67 4.43 12 0.57
18. Tariff Structure of the HotelRooms
3.09 26 1.04 4.33 17 0.48
19. Hygiene at Wayside Restaurantsand Dhabas
3.50 18 0.68 4.30 19 0.53
20. Availability of Petrol Pump 1.07 32 0.26 4.27 20 0.5821. Behaviour of Service Personnel
at Wayside Restaurants andDhabas
3.63 14 0.72 4.37 15 0.56
22. Levels of Road Taxes onVehicles(Tax Rates)
3.19 22 0.81 3.95 29 0.67
23. Administration of the RoadTaxes
3.40 19 0.75 4.05 28 0.60
24. Public Utilities at the TouristAttraction
2.57 30 0.97 4.57 6 0.57
25. General Cleanliness TouristAttraction and Area Around it
3.70 12 0.65 4.60 4 0.67
26. Condition of Signage Within theTourist Attraction
4.03 5 0.89 4.70 2 0.47
27. Parking Facility at the TouristAttraction
3.73 11 0.64 4.60 4 0.50
28. Availability of Trained TouristGuides
3.77 10 0.86 4.47 11 0.68
29. Behaviour of the Guides at theTourist Attraction
4.10 4 0.70 4.50 8 0.51
30. Conservation of Heritage Sites 3.93 7 0.58 4.67 3 0.4831. Promptness at the Ticketing
Window of theMonument/Tourist Attraction
4.30 1 0.70 4.23 23 0.63
32. Power Supply Situation 3.83 9 0.75 4.07 27 1.2033. Telephone/Mobile Services 3.90 8 0.55 4.73 1 0.52
Rank Correlation Coefficient .583**
Significant(2-tailed) .000*Correlation is significant at the 0.01 level (2-tailed).
Source: Field Data* There was no response on importance of tour operator.
Data Analysis
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Graph 5
Table 4.2.9.5 reveals that tourist who visited to Pratapgarh are satisfied with twenty-
eight tourist services because the mean score is more than 3 (quadrant Ist in the graph)
and dissatisfied with the five services because the mean score is less than 3. Among
these ‘promptness at the ticketing window of the monuments/tourist attraction’,
‘behaviour of driver of commercial transportations’, ‘availability of commercial
transportation’ and ‘behaviour of guide at tourist attraction’ shows strong satisfaction
level as their ranks are among first four respectively. However, the ‘air connectivity’,
‘availability of petrol pump’, ‘rail connectivity’ and ‘public utilities at the tourist
attraction’ status depicts strong dissatisfaction since the ranks are last between 33 to
30th respectively.
The destination demands importance towards all thirty-three tourist services and
amenities because their mean score is more than three. Out of that ‘telephone /mobile
services’, ‘condition of signage within the tourist attraction’, ‘conservation of heritage
sites’ and ‘parking facility at tourist attraction’ shows high importance by tourists as
the ranks are among first four respectively. Whereas ‘air’ and ‘rail’ connectivity,
Data Analysis
Shivaji University, Kolhapur 257
‘condition of street light’ and ‘levels of road taxes’ status shows least important as
the ranks are last and are between 32 to 29 respectively.
The calculation of Spearman’s rank correlation coefficient of satisfaction and
importance of tourist facilities and services is 0.583, which is significant at the 0.01
level (2-tailed). It shows that there is uniformity into the opinion of satisfaction and
importance of tourist services and amenities
Twenty-six variables found in the first quadrant. It means most of the important
tourist services and amenities are available to the tourist at the destination as well they
are satisfied with them. This is an encouraging clue in the tourism development.
‘Parking facility’, ‘condition of signage’ (26) and ‘telephone and mobile’ tourist
services shows highest gap in tourists ‘satisfaction and importance level. No single
variable found in second quadrant. Only one variable i.e. ‘availability of authorized
tour operator’ is found in the third quadrant. However, its importance level is on very
low. Six variables are found in the fourth quadrant. The variables as ‘air’ and ‘rail’
connectivity whose gap is very meager although other services like ‘petrol pump’,
‘public utilities at the tourist attraction’ , ‘garbage disposal’ and ‘drinking water
supply’ shows highest gap between tourist’s satisfaction and importance level. This
quadrant needs to focus for the development of tourism sector at Pratapgarh.
Quadrant 4 is important to focus since these parameters are most important and
carries low satisfaction in the opinion of sample tourists. Variable number 20 and 24
viz. ‘availability of petrol pump’ and ‘public utilities at tourist attraction’ in
Pratapgarh needs to be address.
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Infrastructural Gap at Sajjangarh
The perceptual satisfaction and importance of respondents towards infrastructure
facilities are presented with the help of mean score, ranks, and standard deviation
(S.D).
Table 4.2.9.6Perceptual Gap between Importance and Satisfaction of Tourist towards TouristServices and Amenities at Sajjangarh
(n=30)
Sr Tourist Services and AmenitiesSatisfaction Importance
Mean Rank S.D. Mean Rank S.D.1. Air Connectivity Status 1.00 30 0.00 2.03 32 1.502. Rail Connectivity Status 2.03 29 0.89 2.77 31 1.633. Quality of the Roads 3.40 13 0.97 4.80 4 0.484. Quality of Way Side Amenities
Available on This Road3.40 13 0.77 4.40 21 0.67
5. Public Conveniences AlongRoads/Streets
2.83 22 1.29 4.47 18 0.57
6. Sewage and Drainage System 2.90 21 1.30 4.37 24 0.817. Garbage Disposal 3.07 20 1.20 4.40 21 0.568. Condition of City Roads 2.63 25 1.16 4.60 13 0.569. Drinking Water Supply 3.50 11 0.90 4.63 11 0.5610. Condition of Street Lighting 3.27 17 1.01 4.37 24 0.6111. Traffic Management 2.77 24 1.17 4.50 17 0.5712. Condition of Traffic or Transport
Signage3.23 19 1.17 4.53 15 0.51
13. Availability of CommercialTransportations
3.57 10 1.07 4.53 16 0.82
14. Behaviour of the Drivers ofCommercial Transportations
3.87 3 0.63 4.23 27 0.57
15. Availability of Authorized TourOperators
2.22 28 1.64 4.75 7 0.45
16. Availability of Hotels 2.37 27 1.27 2.83 30 1.9117. Behaviour of Service Staff at the
Hotel3.30 16 1.42 4.40 21 0.52
18. Tariff Structure of the HotelRooms
3.67 8 1.22 4.56 14 0.53
19. Hygiene at Wayside Restaurantsand Dhabas
2.40 26 1.30 4.20 28 0.41
20. Availability of Petrol Pump 3.63 9 1.33 4.13 29 0.6321. Behaviour of Service Personnel at
Wayside Restaurants and Dhabas4.29 2 0.76 4.70 9 0.47
22. Levels of Road Taxes onVehicles(Tax Rates)
3.25 18 1.04 4.67 10 0.50
23. Administration of the Road Taxes 3.38 15 0.74 4.63 12 0.52
Data Analysis
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24. Public Utilities at the TouristAttraction
3.70 7 0.88 4.77 5 0.43
25. General Cleanliness TouristAttraction and Area Around it
3.77 6 0.82 4.90 1 0.31
26. Condition of Signage Within theTourist Attraction
3.83 4 0.99 4.77 5 0.43
27. Parking Facility at the TouristAttraction
2.83 22 0.99 4.87 3 0.35
28. Availability of Trained TouristGuides
* * * 4.47 18 0.68
29. Behaviour of the Guides at theTourist Attraction
* * * 4.47 18 0.51
30. Conservation of Heritage Sites 3.83 4 0.99 4.90 1 0.3131. Promptness at the Ticketing
Window of the Monument/TouristAttraction
* * * * * *
32. Power Supply Situation 3.47 12 0.94 4.37 24 0.4933. Telephone/Mobile Services 4.53 1 0.63 4.73 8 0.45
Rank Correlation Coefficient .597**
Significant(2-tailed) .000**. Correlation is significant at the 0.01 level (2-tailed).
Source: Field Data*As there were no facilities so there was no response from sample tourists.Graph 6
Data Analysis
Shivaji University, Kolhapur 260
Table 4.2.9.6 inferred that twenty-three variables’ satisfaction level mean score is
more than three (quadrant Ist in the graph). It shows tourists are satisfied about
twenty-three services, which are available at Sajjangarh. Remaining ten variables
mean score is less than three that means their dissatisfaction.
As 1st rank to ‘telephone/mobile services’, 2nd to ‘behaviour of service personnel at
way side restaurants and dhabas’, 3rd to ‘behaviour of driver of commercial
transportations’ , 4th rank each to ‘condition of signage within the tourist attraction’
and ‘conservation of heritage site’ that shows tourists’ have high satisfaction level. As
rank thirty to ‘air connectivity’, 29 to ‘rail connectivity’, 28 to ‘authorized tour
operators’ and 27 to ‘availability of hotels’ this shows strong dissatisfaction. Yet,
these services are not at all available at the destination.
Thirty tourist services are important to the tourists who visited to the destination as
their mean score is more than 3. Remaining three mean score is less than 3 which
shows they are not important to the tourist. ‘Conservation of heritage site’, ‘General
Cleanliness of tourist attraction’ has 1st rank each; ‘parking facility at the tourist
attraction’ carries 3rd rank and 4th rank the ‘quality of roads’ this shows high
importance level. Whereas ‘air,’ ‘rail’ connectivity, ‘availability of hotels’ and ‘petrol
pump’ shows least importance at the tourist as their ranks are thirty-two to twenty-
nine respectively.
The Spearman’s rank correlation Coefficient is 0.597 that is significant at the 0.01
level (2-tailed). This depicts that there is uniformity into the opinion of satisfaction
and importance of tourist services and amenities.
The first quadrant shows nineteen variables where tourists have high satisfaction level
and high importance. Among them ‘parking facility’, ‘condition of traffic and
transport signage’, ‘levels of road taxes on vehicles’, ‘general cleanliness’ and
‘quality of roads’ where tourist having satisfaction but compared to its importance
level it is average. No single variable found in second quadrant. In addition, third
quadrant depicts four variables, out of them promptness at ticket window received
least satisfaction and least importance since this services is neither available nor
essential. ‘Air’ and ‘rail’ connectivity and ‘availability of hotels’ like services also lie
in this quadrant but quiet closer to the average importance level. Fourth quadrant
shows ten variables, which reflect the high importance level of tourist services and
Data Analysis
Shivaji University, Kolhapur 261
amenities and lower satisfaction level of tourist. Out of them ‘availability of trained
guide’ and ‘behaviour of guide’ like facilities shows highest gap. The ‘hygiene at
wayside restaurants and dhabas’, ‘condition of city roads’ and ‘drinking water supply’
like facilities shows average gap between satisfaction and importance. It observed that
‘guide facility’ is not at all available at destination so the question of guide behaviour
does not arise.
Therefore, quadrant 4 is important to focus since these parameters are most important
and carries dissatisfaction in the opinion of sample tourists. Variable number 28
‘availability of tourist guide ‘lies in four quadrant since these facilities are not
available at all in Sajjangarh so question of variable number 29 i.e. behaviour of guide
is out of question. Variable numbers 15 and 8 as ‘availability of authorized tour
operator’ and ‘condition of city roads’ need to be address.
Infrastructural Gap at Aundh
The perceptual satisfaction and importance of respondents towards infrastructure
facilities are presented with the help of mean score, ranks and standard deviation
(S.D).
Table 4.2.9.7Perceptual Gap between Importance and Satisfaction of Tourist towards TouristServices and Amenities at Aundh
(n=30)
Sr.
Tourist Services andAmenities
Satisfaction Importance
MeanRank
S.D. Mean Rank S.D.
1. Air Connectivity Status 1.38 31 0.49 2.47 32 0.902. Rail Connectivity Status 2.00 30 0.00 2.47 32 0.903. Quality of the Roads 3.53 18 0.73 4.40 17 0.504. Quality of Way Side
Amenities Available on ThisRoad
3.13 19 0.63 4.47 15 0.51
5. Public Conveniences AlongRoads/Streets
2.93 24 0.94 4.33 20 0.48
6. Sewage and Drainage System 3.00 20 0.00 4.23 22 0.437. Garbage Disposal 4.00 9 0.00 4.54 14 0.518. Condition of City Roads 2.75 27 0.68 4.35 19 0.499. Drinking Water Supply 3.00 20 0.00 4.62 12 0.5010. Condition of Street Lighting 3.00 20 0.00 4.15 25 0.3711. Traffic Management 4.00 9 0.00 4.81 8 0.40
Data Analysis
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12. Condition of Traffic orTransport Signage
2.91 25 0.60 4.69 11 0.47
13. Availability of CommercialTransportations
2.74 28 0.75 4.21 23 0.41
14. Behaviour of the Drivers ofCommercial Transportations
4.00 9 0.00 3.17 30 0.38
15. Availability of AuthorizedTour Operators
3.00 20 0.00 3.00 31 0.00
16. Availability of Hotels 2.80 26 0.79 3.58 29 0.7217. Behaviour of Service Staff at
the Hotel4.00 9 0.00 4.17 24 0.56
18. Tariff Structure of the HotelRooms
4.00 9 0.00 4.46 16 0.51
19. Hygiene at WaysideRestaurants and Dhabas
2.71 29 0.62 4.79 10 0.41
20. Availability of Petrol Pump 4.00 9 0.00 4.29 21 0.4621. Behaviour of Service
Personnel at WaysideRestaurants and Dhabas
4.33 5 0.48 4.38 18 0.49
22. Levels of Road Taxes onVehicles(Tax Rates)
3.63 17 0.50 3.83 27 0.38
23. Administration of the RoadTaxes
3.75 16 0.45 3.67 28 0.48
24. Public Utilities at the TouristAttraction
4.40 3 0.50 4.93 1 0.25
25. General Cleanliness TouristAttraction and Area Around it
4.33 5 0.48 4.93 1 0.25
26. Condition of Signage Withinthe Tourist Attraction
4.60 1 0.50 4.93 1 0.25
27. Parking Facility at the TouristAttraction
4.53 2 0.51 4.93 1 0.25
28. Availability of Trained TouristGuides
* * * 4.93 1 0.25
29. Behaviour of the Guides at theTourist Attraction
* * * 4.07 26 0.25
30. Conservation of Heritage Sites 4.27 8 0.45 4.93 1 0.2531. Promptness at the Ticketing
Window of theMonument/Tourist Attraction
4.40 3 0.50 4.80 9 0.41
32. Power Supply Situation 3.93 15 0.45 4.60 13 0.5033. Telephone/Mobile Services 4.33 5 0.48 4.93 1 0.25
Rank Correlation Coefficient .563**
Significant(2-tailed) .001**. Correlation is significant at the 0.01 level (2-tailed).
Source: Field Data*As there were no facilities so, there were no responses.
Data Analysis
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Graph 7
Table 4.2.9.7 draws the inferences that tourists who visited to Aundh are satisfied
with the twenty-five tourist services which are available at the destination as the mean
score is more than 3(quadrant Ist in the graph). However, dissatisfied with the eight
services since the mean score is less than 3. Tourist shows strong satisfaction towards
the services like ‘condition of signage within the tourist attraction’ that receives 1st
rank, 2nd to ‘parking facility at the tourist attraction’ (27) and 3rd each to ‘public
utilities at the tourist attraction’ and ‘promptness at the ticket window’. ‘Air’ and
‘rail’ connectivity, ‘hygiene of wayside restaurant and dhabas’ and ‘availability of
commercial transportation’ services shows strong dissatisfaction as the ranks are
thrity-one and twenty-eight respectively.
Thirty-one tourist services and amenities are important at the Aundh destination as the
mean score is more than 3. ‘Air’ and ‘rail’ connectivity like services tourist felt least
important which is closer to the average but not average since the mean score is less
Data Analysis
Shivaji University, Kolhapur 264
than 3. Among all thirty-three tourist services the priority has been given to the
‘public utilities at the tourist attraction’, ‘general cleanliness’, ‘condition of signage
within tourist attraction’ and ‘availability of trained tourist guides’ , ‘conservation of
site’ and ‘telephone and mobile services’ for their importance as they received 1st rank
each. On the contrary 32 rank each to ‘air’ and ‘rail’ connectivity and 31 rank
receives to ‘availability of authorized tour operator’ and 30 rank to ‘behaviour of the
drivers of commercial transportation’ which inferred that these services carries least
importance.
Spearman’s rank correlation coefficient between satisfaction and importance level of
tourist facilities and services is 0.563, which is significant at the 0.01 level (2-tailed).
This shows that there is uniformity into the opinion of satisfaction and importance of
tourist services and amenities.
First quadrant highlights about twenty-five variables, which show higher satisfaction
and higher importance. Among them, one variable viz. ‘availability of authorized tour
operator’ is on border which shows average common mean score 3. ‘Drinking water’,
‘sewage and drainage system’(6), ‘condition of street light’ facilities lay on the
average (median) line average satisfaction but more importance so still it demands
attention for improvement. Second quadrant is empty, so no tourist services are
showing their higher satisfaction and least importance. In the third quadrant ‘air’ and
‘rail’ connectivity, the two variables appeared which shows least importance and least
satisfaction. However, in the fourth quadrant six variables have appeared. Out of them
four variables viz. ‘availability of commercial transportation’, ‘condition of city
roads’, ‘hygiene at wayside restaurants and dhabas’ and ‘condition of traffic and
transport signage showing highest gap in satisfaction and importance level.
Quadrant 4 is important to focus since these parameters are most important and
carries dissatisfaction in the opinion of sample tourists. Trained tourist guide is not
available so the behaviour of guide is out of question as the variable number 28 and
29 lies in quadrant IV. Variable numbers 19 and 12 viz. ‘hygiene at wayside
restaurant and Dhabas’ and ‘condition of traffic and transport signage’ need to be
address.
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Infrastructural Gap at Ajinkyatara
The perceptual satisfaction and importance of respondents towards infrastructure
facilities are presented with the help of mean score, ranks, and standard deviation
(S.D).
Table 4.2.9.8Perceptual Gap between Importance and Satisfaction of Tourist towards touristServices and Amenities at Ajinkyatara
(n=34)
Sr. Tourist Services and AmenitiesSatisfaction Importance
MeanRank
S.D. MeanRank
S.D.
1. Air Connectivity Status 1.25 30 0.50 3.18 31 1.382. Rail Connectivity Status 2.59 27 1.00 3.94 23 0.663. Quality of the Roads 2.65 26 1.00 4.47 3 0.804. Quality of Way Side Amenities
Available on This Road3.06 19 1.03 3.53 29 1.07
5. Public Conveniences AlongRoads/Streets
2.41 29 1.42 3.76 25 0.75
6. Sewage and Drainage System 3.06 19 0.83 3.35 30 1.277. Garbage Disposal 3.00 21 0.79 3.59 27 1.288. Condition of City Roads 2.76 23 1.03 4.35 7 0.499. Drinking Water Supply 3.35 13 0.93 4.47 3 0.6210. Condition of Street Lighting 2.76 23 0.97 4.35 7 0.6111. Traffic Management 3.35 13 0.86 3.94 23 1.2012. Condition of Traffic or Transport
Signage3.25 15 0.77 4.12 17 0.78
13. Availability of CommercialTransportations
3.53 11 0.52 4.21 12 0.70
14. Behaviour of the Drivers ofCommercial Transportations
3.71 4 0.73 4.15 16 0.80
15. Availability of Authorized TourOperators
3.58 9 0.51 3.00 32 1.34
16. Availability of Hotels 3.88 2 0.62 4.00 21 0.9717. Behaviour of Service Staff at the
Hotel3.69 6 0.48 4.08 20 0.76
18. Tariff Structure of the Hotel Rooms 3.36 12 0.67 4.08 19 0.7919. Hygiene at Wayside Restaurants and
Dhabas3.60 8 0.52 4.27 11 0.47
20. Availability of Petrol Pump 3.85 3 0.69 4.21 12 0.8021. Behaviour of Service Personnel at
Wayside Restaurants and Dhabas3.64 7 0.50 4.17 15 0.72
22. Levels of Road Taxes onVehicles(Tax Rates)
2.86 22 0.95 3.55 28 1.04
23. Administration of the Road Taxes 3.57 10 0.51 4.11 18 0.60
Data Analysis
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24. Public Utilities at the TouristAttraction
2.42 28 1.24 4.18 14 0.73
25. General Cleanliness TouristAttraction and Area Around it
2.73 25 1.03 4.41 6 0.62
26. Condition of Signage Within theTourist Attraction
3.15 17 1.28 4.35 7 0.70
27. Parking Facility at the TouristAttraction
3.24 16 1.39 4.47 3 0.51
28. Availability of Trained TouristGuides
* * * 4.00 21 0.61
29. Behaviour of the Guides at theTourist Attraction
* * * 3.71 26 0.77
30. Conservation of Heritage Sites 3.09 18 1.22 4.29 10 0.6931. Promptness at the Ticketing
Window of the Monument/TouristAttraction
* * * * * *
32. Power Supply Situation 3.71 5 0.92 4.76 1 0.4433. Telephone/Mobile Services 4.06 1 0.83 4.65 2 0.49
Rank Correlation Coefficient .358*
Significant(2-tailed) .041*. Correlation is significant at the 0.05 level (2-tailed).
Source: Field Data*As there were no facilities, so there was no response.
Graph 8
Data Analysis
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Table 4.2.9.8 highlights satisfaction and importance level of tourist facilities and
services at Ajinkytara. Tourists are satisfied with twenty-four services since the mean
score is more than three (quadrant Ist in the graph) whereas dissatisfied with nine
services. Tourist are strongly satisfied with the services like ‘telephone/mobile
services’, ‘availability of hotels’, ‘availability of petrol pump’ and ‘behaviour of
driver of commercial transportation’ as they received first to fourth rank. They are
strongly dissatisfied with ‘air connectivity’, ‘public convenience along roads/streets’,
‘public utilities at tourist attraction’ and ‘rail connectivity’ status where they received
thirty to twenty-seven rank respectively.
All tourist services are important and essential at the tourist destination as their mean
score is more than 3. Services like ‘power supply situation’ receives 1st rank , 2nd to
‘telephone/mobile services’, 3rd each to ‘parking facility’, ‘drinking water supply’
and ‘quality of roads’ that carries high importance level as their ranks are 1st to 4th
respectively. Some services like ‘availability of authorized tour operators’, ‘air
connectivity’, ‘sewage and drainage system’ and ‘quality of way side amenities
available on this road carries least importance with tourists point of view as their
ranks are thirty-two, thirty-one, thirty and twenty-nine respectively.
Spearman’s rank correlation coefficient is 0.358, which is significant at the 0.05 level
(2-tailed). It shows the uniformity into the opinion of Satisfaction and importance of
tourist services and amenities.
Twenty-four variables appeared in the first quadrant. Out of them one variable i.e.
‘availability of authorized tour operator’ is more towards the average importance and
higher satisfaction whereas ‘sewage and drainage system’, ‘quality of way side
amenities’, ‘garbage disposal’(7), ‘conservation of heritage site’(30) are on the
average side of satisfaction. No single variable appeared in second and third
quadrant. Nine variables appeared in the fourth quadrant. Out of them ‘air
connectivity’, ‘levels of road taxes’ shows least gap but the other facilities like ‘public
convenience along roads/streets’, ‘rail connectivity’, ‘public utilities at the tourist
attraction’, ‘condition of city roads’, ‘quality of roads’, ‘condition of street light’
reflects highest gap between the satisfaction and importance level of tourist because
tourist’s satisfaction level is far behind the importance of services.
Thus, quadrant 4 is important to focus since these parameters are most important and
Data Analysis
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carries high dissatisfaction in the opinion of sample tourists. Variable number 24, 8, 3
and 25 viz. ‘Public utilities at tourist attraction’, ‘condition of city roads’, ‘quality of
roads’ and ‘general cleanliness at tourist attraction and area around it’(25) in
Ajinkyatara need to be address.
Infrastructural Gap at Kas
The perceptual satisfaction and importance of respondents towards infrastructure
facilities are presented with the help of mean score, ranks and standard deviation
(S.D).
Table 4.2.9.9Perceptual Gap between Importance and Satisfaction of Tourist towards TouristServices and Amenities at Kas
(n=30)
Sr Tourist Services and AmenitiesSatisfaction Importance
Mean Rank S.D. Mean Rank S.D.1. Air Connectivity Status 1.25 30 0.44 3.33 33 0.962. Rail Connectivity Status 2.13 26 0.68 3.57 32 0.863. Quality of the Roads 2.90 23 0.84 4.30 11 0.474. Quality of Way Side Amenities
Available on This Road3.07 21 0.91 4.33 9 0.48
5. Public Conveniences AlongRoads/Streets
3.13 20 0.94 4.24 13 0.51
6. Sewage and Drainage System 2.97 22 0.89 4.17 18 0.467. Garbage Disposal 2.87 24 0.73 4.10 20 0.408. Condition of City Roads 1.97 28 1.13 4.47 4 0.579. Drinking Water Supply 3.50 12 0.51 4.33 9 0.4810. Condition of Street Lighting 3.67 7 0.48 4.20 14 0.4111. Traffic Management 3.23 16 1.14 4.30 11 0.4712. Condition of Traffic or Transport
Signage3.70 5 0.84 4.40 8 0.50
13. Availability of CommercialTransportations
3.59 9 0.50 4.10 20 0.40
14. Behaviour of the Drivers ofCommercial Transportations
3.72 4 0.70 4.10 20 0.48
15. Availability of Authorized TourOperators
3.30 15 0.47 3.67 30 0.84
16. Availability of Hotels 3.57 10 0.73 4.20 14 0.41
Data Analysis
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17. Behaviour of Service Staff at theHotel
3.67 7 0.55 4.17 18 0.38
18. Tariff Structure of the Hotel Rooms 3.17 18 0.65 4.00 24 0.2619. Hygiene at Wayside Restaurants and
Dhabas3.40 13 0.67 3.93 28 0.25
20. Availability of Petrol Pump 3.73 3 0.64 4.07 23 0.4521. Behaviour of Service Personnel at
Wayside Restaurants and Dhabas3.70 5 0.47 4.00 24 0.26
22. Levels of Road Taxes onVehicles(Tax Rates)
2.70 25 1.06 3.97 27 0.18
23. Administration of the Road Taxes 3.23 16 0.57 4.00 24 0.2624. Public Utilities at the Tourist
Attraction1.97 28 1.33 4.67 1 0.48
25. General Cleanliness TouristAttraction and Area Around it
3.33 14 0.92 4.47 4 0.57
26. Condition of Signage Within theTourist Attraction
3.17 18 0.87 4.20 14 0.48
27. Parking Facility at the TouristAttraction
2.00 27 1.20 4.50 3 0.51
28. Availability of Trained TouristGuides
1.09 31 0.30 3.87 29 0.97
29. Behaviour of the Guides at theTourist Attraction
* * * * 31 0.93
30. Conservation of Heritage Sites 3.57 10 0.50 4.47 4 0.6831. Promptness at the Ticketing
Window of the Monument/TouristAttraction
* * * 4.20 14 0.41
32. Power Supply Situation 3.88 2 0.50 4.43 7 0.5033. Telephone/Mobile Services 3.97 1 0.49 4.63 2 0.49
Rank Correlation Coefficient .190Significant(2-tailed) .290Correlation is not significant at the 0.05 level (2-tailed).
Source: Field Data*As there were no facilities, so there was no respons.
Data Analysis
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Graph 9
Table 4.2.9.9 shows that tourists are satisfied with twenty-three facilities as the mean
score is more than 3(quadrant Ist in the graph) and dissatisfied with ten tourist
facilities and services since the mean is less than 3. Among these facilities, tourists are
strongly satisfied with the ‘telephone/mobile services’, ‘power supply’ (32),
‘availability of petrol pump’, ‘behaviour of driver of commercial transportation’ as
they received first four ranks respectively. However tourist who visited to the
destination are strongly dissatisfied with the services like ‘availability of trained
tourist guide’, ‘air connectivity’, ‘condition of city roads’ and ‘public utilities at the
tourist attraction’ as they received from 31 to 28 rank respectively.
The tourist who visited to the destination they think all the thirty-three facilities are
important at Kas as their mean score is more than 3. But they think the facilities like
‘public utilities at the tourist attraction’, ‘telephone and mobile services’, ‘parking
facility at the tourist attraction’ and ‘general cleanliness’ as well as ‘conservation of
heritage sites’ are the most important tourist services of Kas as they received 1st four
Data Analysis
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ranks respectively. However, the least important services are ‘air connectivity’, ‘rail
connectivity’ and ‘behaviour of the guides’ and ‘availability of authorized tour
operators’ as they got thirty-three to thirty ranks respectively.
The Spearman’ rank correlation Coefficient between rank of satisfaction and rank of
importance is 0.190, which is not significant at a 0.05 level of (2-tailed). This shows
that there is no uniformity into the opinion of satisfaction and importance of tourist
services and amenities.
Nineteen variables appeared in first quadrant, which reflect high satisfaction and high
importance. Out of them three variables are on average importance side and higher
satisfaction viz. ‘tariff structure of the hotel rooms’(18), ‘administration of the road
taxes’(23) and ‘availability of petrol pump’. The services like ‘quality of way side
amenities available on this road’, ‘public convenience along roads/streets,’ ‘general
cleanliness,’ ‘condition of signage within the tourist attraction’ and ‘traffic
management’ are close towards the average satisfaction and higher importance level.
‘Power supply’ and ‘telephone/mobile’ services both appeared on higher side of
satisfaction and importance level. Two variables appeared in second quadrant, which
shows high satisfaction and low importance. They are ‘availability of authorized tour
operators’ and ‘hygiene at wayside restaurants and dhabas’. Five variables appeared
in 3rd quadrant which reflects low importance and low satisfaction. They are ‘air’ and
‘rail’ connectivity, ‘availability of trained tourist guide’ and their behaviour, but
‘levels of road taxes on vehicles’ is near to average of both satisfaction and
importance level. Seven variables appeared in the fourth quadrant that shows their
high importance and low satisfaction. Among this, one variable viz. ‘promptness of
ticketing window’ is at zero level of satisfaction as this service is not at all available at
Kas. ‘Garbage disposal’, ‘sewage and drainage system’ and ‘quality of roads’ are
close to the average level of satisfaction whereas the ‘condition of city roads’, ‘public
utilities at the tourist attraction’ and ‘parking facility at the tourist attraction’ like
facilities reflects higher gap i.e. more dissatisfaction and high importance. These
facilities are needed to be developed.
So it reveals that quadrant 4 is important to focus since these parameters are most
important and carries dissatisfaction in the opinion of sample tourists. Variable
number 8, 27 and 24 viz. ‘Conditions of city roads’, ‘parking facility at the tourist
Data Analysis
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attraction’, ‘public utilities at the tourist attraction’ need to be address. ‘Ticketing
window facility’ is not available at all in Kas so the variable 31 lies in four quadrant
where satisfaction for this facility is zero level.
Infrastructural Gap at Thoseghar
The perceptual satisfaction and importance of respondents towards infrastructure
facilities are presented with the help of mean score, ranks, and standard deviation
(S.D).
Table 4.2.9.10Perceptual Gap between Importance and Satisfaction of Tourist towards Touristservices and Amenities at Thoseghar
(n=33)
Sr Tourist Services and AmenitiesSatisfaction Importance
Mean Rank S.D. Mean Rank SD1. Air Connectivity Status 1.47 31 0.62 2.64 32 1.172. Rail Connectivity Status 2.24 24 0.66 2.88 31 1.173. Quality of the Roads 2.21 25 1.05 4.33 13 0.484. Quality of Way Side Amenities
Available on This Road2.79 16 0.60 4.27 16 0.45
5. Public Conveniences AlongRoads/Streets
3.03 15 0.53 4.12 23 0.33
6. Sewage and Drainage System 3.36 11 0.65 4.24 19 0.447. Garbage Disposal 3.18 14 0.46 4.21 20 0.428. Condition of City Roads 1.70 28 1.05 4.30 15 0.539. Drinking Water Supply 3.64 9 0.55 4.27 16 0.5210. Condition of Street Lighting 3.48 10 0.83 4.12 23 0.6011. Traffic Management 1.55 29 0.83 4.67 8 0.5412. Condition of Traffic or Transport
Signage2.18 6 0.73 4.76 7 0.44
13. Availability of CommercialTransportations
2.64 19 0.68 4.42 11 0.50
14. Behaviour of the Drivers ofCommercial Transportations
3.70 7 0.47 4.25 18 0.44
15. Availability of Authorized TourOperators
3.29 12 0.46 3.19 30 1.33
16. Availability of Hotels 3.77 3 0.43 4.31 14 0.6417. Behaviour of Service Staff at the Hotel 3.76 4 0.60 4.12 23 0.33
Data Analysis
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18. Tariff Structure of the Hotel Rooms 3.23 13 0.51 4.00 27 0.2519. Hygiene at Wayside Restaurants and
Dhabas2.58 20 0.76 4.18 22 0.39
20. Availability of Petrol Pump 3.85 1 0.36 4.06 26 0.35
21. Behaviour of Service Personnel atWayside Restaurants and Dhabas
3.76 5 0.44 4.21 20 0.48
22. Levels of Road Taxes on Vehicles(TaxRates)
2.58 21 0.61 3.97 28 0.30
23. Administration of the Road Taxes 2.55 22 0.67 3.94 29 0.3524. Public Utilities at the Tourist Attraction
1.45 32 0.83 4.91 4 0.29
25. General Cleanliness Tourist Attractionand Area Around it
2.12 27 0.55 4.94 1 0.24
26. Condition of Signage Within theTourist Attraction
2.73 17 0.94 4.82 6 0.39
27. Parking Facility at the TouristAttraction
1.48 30 0.94 4.94 1 0.24
28. Availability of Trained Tourist Guides 2.71 18 0.64 4.58 10 0.7929. Behaviour of the Guides at the Tourist
Attraction3.64 8 0.56 4.39 12 0.79
30. Conservation of Heritage Sites 3.85 1 0.36 4.94 1 0.2431. Promptness at the Ticketing Window
of the Monument/Tourist Attraction* * * * * *
32. Power Supply Situation 3.76 5 0.61 4.61 9 0.8333. Telephone/Mobile Services 2.55 2 1.23 4.91 4 0.29
Rank Correlation Coefficient -.044Significant(2-tailed) .808Correlation is not significant at the 0.05 level (2-tailed).
Source: Filed Data*As there were no facilities, so there were no responses.
Data Analysis
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Graph 10
Table 4.2.9.10 depicts sixteen variables which show the satisfaction as their mean
score is more than 3(quadrant Ist in the graph) whereas remaining seventeen variables
reflecting dissatisfaction as their mean score is less than 3. Tourist are strongly
satisfied with the services like ‘conservation of heritage sites’, ‘availability of petrol
pump’, ‘ availability of hotels’, ‘behaviour of service staff at the hotel’ as the ranks 1st
, 2nd 3rd and 4th respectively. However, tourist are strongly dissatisfied with ‘public
utilities at the tourist attraction’, ‘air connectivity’, ‘parking facility’ and ‘traffic
management’ as they received 32th , 31st , 30th and 29th ranks respectively.
Tourists think that thirty-one services are important at Thoseghar as their mean score
is more than 3 whereas two facilities viz. ‘air’ and ‘rail’ connectivity are not
important as their mean score is less than 3. ‘Parking facility at the tourist attraction’,
‘conservation of heritage sites’, ‘general cleanliness’, ‘telephone mobile’ like services
and ‘public utilities at the tourist attraction’, tourist think most important as their
Data Analysis
Shivaji University, Kolhapur 275
ranks 1st to 4th. But ‘air’ and ‘rail’ connectivity and ‘availability of authorized tour
operators’ and ‘administration of road taxes’ are least important in tourist point of
view because the ranks are 32, 31st , 30th and 29th respectively.
The Spearman’s rank correlation coefficient is -0.044, which is insignificant at the
0.05 level of (2-tailed). It reveals that there is no uniformity into the opinion of
sample tourist about satisfaction and importance of tourist services and amenities.
Sixteen variables are positioned in the 1st quadrant that reflects high importance and
high satisfaction level at the destination. ‘Public convenience along roads/streets’(5),
‘sewage and drainage system’, ‘garbage disposal’ i.e. ‘civic administration’ like
facility have average satisfaction but high importance so gap is more. On the other
hand, ‘conservation of heritage’ and ‘power supply’ carries high level of importance
and satisfaction. ‘Availability of authorized tour operators’ like service is near to the
average of importance level. Remaining services and amenities carried noticeable gap
in their importance and satisfaction. Second quadrant is empty. Third quadrant shows
one variable i.e. ‘promptness at the ticketing window’ that is less important as well
less satisfaction level according to the tourist perception. Seventeen variables are
found in the fourth quadrant, which shows high importance and low satisfaction. Out
of them two variables ‘air’ and ‘rail’ connectivity are close to the lower satisfaction
and lower importance somehow few tourist may demand this service at Thoseghar.
Facilities like ‘condition of city road’, ‘traffic management’, ‘public utilities at the
tourist attraction’, ‘parking facility’, ‘general cleanliness at the tourist attraction and
area around it’, ‘condition of traffic signage’ showing noticeable gap on negative side
between satisfaction and importance so needed to be developed or it is emergency to
be developed as a tourist destination.
From the table it can be concluded that quadrant 4 is important to focus since these
parameters are most important and carries more dissatisfaction in the opinion of
sample tourists. Variable number 8, 11, 24, 27, 25 and 12 viz. ‘Condition of city
roads’, ‘traffic management’, ‘public utilities at tourist attraction’, ‘parking facility at
the tourist attraction’, ‘general cleanliness at the tourist attraction’ and ‘condition of
traffic and transport signage’ need to be attend.
Data Analysis
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Infrasturctural Gap at Satara District as a Whole
The perceptual satisfaction and importance of respondents towards infrastructure
facilities are presented with the help of mean score, ranks, and standard deviation
(S.D).
Table 4.2.9.11Perceptual Gap between Importance and Satisfaction of Tourist towards TouristServices and Amenities at Satara District as a Whole.
(n=326)
Sr.
Tourist Services and AmenitiesSatisfaction Importance
Mean Rank S.D. Mean Rank S.D.1. Air Connectivity Status 1.29 33 0.49 2.83 33 1.302. Rail Connectivity Status 1.96 32 0.76 3.10 32 1.233. Quality of the Roads 3.17 16 0.95 4.45 8 0.564. Quality of Way Side Amenities
Available on This Road3.30 14 0.80 4.29 15 0.68
5. Public Conveniences AlongRoads/Streets
3.02 23 0.96 4.23 18 0.66
6. Sewage and Drainage System 3.11 20 0.94 4.20 24 0.657. Garbage Disposal 3.16 17 0.85 4.21 19 0.658. Condition of City Roads 2.79 29 1.09 4.39 13 0.579. Drinking Water Supply 3.43 11 0.81 4.44 9 0.5610. Condition of Street Lighting 3.40 12 0.86 4.24 17 0.6711. Traffic Management 2.92 28 1.12 4.42 11 0.6112. Condition of Traffic or Transport
Signage3.10 21 1.02 4.47 7 0.58
13. Availability of CommercialTransportations
3.52 10 0.83 4.32 14 0.59
14. Behaviour of the Drivers ofCommercial Transportations
3.75 6 0.71 4.16 26 0.69
15. Availability of Authorized TourOperators
2.99 24 0.87 3.14 31 1.24
16. Availability of Hotels 3.55 8 0.90 4.14 27 0.9617. Behaviour of Service Staff at the
Hotel3.67 7 0.74 4.20 23 0.54
18. Tariff Structure of the Hotel Rooms 3.12 19 0.82 4.16 25 0.5219. Hygiene at Wayside Restaurants and
Dhabas3.16 18 0.97 4.26 16 0.52
20. Availability of Petrol Pump 3.09 22 1.11 4.20 22 0.5421. Behaviour of Service Personnel at
Wayside Restaurants and Dhabas3.76 4 0.67 4.21 21 0.57
22. Levels of Road Taxes onVehicles(Tax Rates)
2.78 30 0.94 3.97 30 0.64
Data Analysis
Shivaji University, Kolhapur 277
23. Administration of the Road Taxes 2.99 25 0.95 4.04 29 0.5724. Public Utilities at the Tourist
Attraction2.65 31 1.25 4.59 4 0.55
25. General Cleanliness TouristAttraction and Area Around it
3.25 15 0.97 4.60 2 0.57
26. Condition of Signage Within theTourist Attraction
3.36 13 1.25 4.57 6 0.55
27. Parking Facility at the TouristAttraction
2.95 27 1.24 4.58 5 0.56
28. Availability of Trained TouristGuides
2.98 26 1.10 4.21 20 0.91
29. Behaviour of the Guides at theTourist Attraction
3.53 9 0.75 4.09 28 0.77
30. Conservation of Heritage Sites 3.76 3 0.85 4.60 2 0.5831. Promptness at the Ticketing Window
of the Monument/Tourist Attraction4.19 1 0.65 4.39 12 0.59
32. Power Supply Situation 3.75 5 0.66 4.44 10 0.6733. Telephone/Mobile Services 3.93 2 0.86 4.72 1 0.46
Rank Correlation Coefficient .662**
Significant(2-tailed) .000**. Correlation is significant at the 0.01 level (2-tailed).
Source: Field Data
Graph 11
Data Analysis
Shivaji University, Kolhapur 278
Table 4.2.9.11 shows satisfaction level of tourist who visited to Satara as they are
satisfied with the twenty three variables as the mean score is more than 3(quadrant Ist
in the graph). On the contrary tourist are dissatisfied with the ten variables while their
mean score is less than3. Tourists are strongly satisfied with the facilities like
‘promptness of ticketing window of the monument/tourist attraction’,
‘telephone/mobile services’, ‘conservation of heritage sites’, and ‘behaviour of
service personnel at wayside restaurants and dhabas’ as they received rank first to
fourth respectively. But the tourist are strongly dissatisfied with the tourist amenities
like ‘air’, ‘rail’ connectivity, ‘public utilities at tourist attraction’ and ‘levels of road
taxes on vehicles’ as they have thirty-three to thirty ranks respectively.
In tourist point of view except two all facilities and amenities are important to the
tourist at Satara since their mean score is more than 3. Only two facilities viz. ‘air’
and ‘rail’ carries least importance in tourist point of view as their mean score is less
than 3. Among them ‘telephone/mobile services’, ‘general cleanliness at the tourist
attraction’, ‘conservation of heritage site and area around it’, ‘public utilities at the
tourist attraction’ as they received rank first, second, third and fourth respectively.
According to the tourist, services and amenities like ‘air’ and ‘rail’ connectivity,
‘availability of authorized tour operators’ and ‘levels of road taxes on vehicles’
carrying least importance since the ranks are 33, 32, 31 and 30 respectively.
Spearman rank correlation coefficient is 0.662, which is significant at the 0.01 level
(2-tailed). This reveals that there is uniformity into the opinion of tourist of
satisfaction and importance.
1st quadrant highlights twenty four variables which show high importance as well as
high satisfaction level. Most of the variables viz. ‘quality of roads’, ‘condition of
traffic and transport signage’, ‘hygiene at wayside restaurant and dhabas’,
‘administration of road taxes’, ‘general cleanliness’ and ‘condition of signage within
the tourist attraction’ are close to the average satisfaction level but carries high
importance level so need to be attend in the tourism development. One variable i.e.
availability of authorized tour operator is positioned in the second quadrant but very
close towards the average importance and average satisfaction. Two variables as ‘air’
and ‘rail’ connectivity lie in the third quadrant carrying least importance and low
satisfaction so it can be neglected. However, the most important is fourth quadrant
Data Analysis
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which reflects high importance and low satisfaction having six variables all are near
to the average of satisfaction but has highest importance level. These are ‘public
utilities at the tourist attraction’, ‘traffic management’, and ‘condition of traffic and
transport signage,’ ‘condition of city roads’, quality of roads’, ‘parking facility’,
‘general cleanliness at tourist attraction and area around ’ and ‘condition of signages
within tourist attraction’. Thus, these services and amenities demand more attention
for the development of Satara as a tourist destination because it shows high
dissatisfaction but high importance of services.
Quadrant 4 is important to focus since these parameters are most important and
carries dissatisfaction in the opinion of sample tourists. Variable number 8, 11 and 24
,27, 25, 3, 12, 26 viz. ‘Condition of city roads’, ‘traffic management’, ‘public utilities
at tourist attraction’ , ‘parking facility at the tourist attraction’, general cleanliness at
troust attraction and area around’, ‘quality of roads’ , ‘condition of traffic and
transport signages’ and ‘condition of signages within the tourist attraction’ in Satara
need to be address.
Infrastructural Gap in Hoteliers Point of View
The perceptual satisfaction and importance of respondents towards infrastructure
facilities are presented with the help of mean score, ranks, and standard deviation
(S.D).
Table 4.2.9.12Perceptual Gap between Importance and Satisfaction of Hoteliers towards TouristServices and Amenities at Satara District as a Whole
(n=40)
Sr Tourist Services and AmenitiesSatisfaction Importance
Mean Rank S.D. Mean Rank S.D.1. Air Connectivity Status 1.17 33 0.38 3.18 33 1.392. Rail Connectivity Status 2.20 32 0.91 3.53 32 1.133. Quality of the Roads 2.90 25 1.08 4.40 6 0.554. Quality of Way Side Amenities
Available on This Road3.40 16 0.98 4.25 19 0.49
5. Public Conveniences AlongRoads/Streets
3.13 22 1.18 4.33 11 0.47
6. Sewage and Drainage System 3.00 24 1.13 4.43 3 0.507. Garbage Disposal 3.10 23 1.12 4.43 3 0.508. Condition of City Roads 2.90 25 1.13 4.48 2 0.519. Drinking Water Supply 3.67 12 0.77 4.43 3 0.50
Data Analysis
Shivaji University, Kolhapur 280Source: Field Data
10. Condition of Street Lighting 3.40 16 1.01 4.15 26 0.4311. Traffic Management 2.90 25 1.30 4.25 19 0.4912. Condition of Traffic or Transport
Signage3.73 11 0.82 4.28 17 0.45
13. Availability of CommercialTransportations
4.13 2 0.52 4.30 16 0.56
14. Behaviour of the Drivers ofCommercial Transportations
4.13 2 0.40 4.35 10 0.48
15. Availability of Authorized TourOperators
3.58 13 0.75 4.05 29 0.45
16. Availability of Hotels 4.03 4 0.53 4.38 8 0.4917. Behaviour of Service Staff at the
Hotel3.83 8 0.90 4.33 11 0.47
18. Tariff Structure of the HotelRooms
3.38 18 0.78 4.21 24 0.52
19. Hygiene at Wayside Restaurantsand Dhabas
4.03 4 0.80 4.40 6 0.50
20. Availability of Petrol Pump 3.25 20 1.10 4.28 17 0.6021. Behaviour of Service Personnel at
Wayside Restaurants and Dhabas3.75 10 0.49 4.15 26 0.43
22. Levels of Road Taxes onVehicles(Tax Rates)
3.14 21 0.72 3.94 31 0.47
23. Administration of the Road Taxes 3.36 19 0.64 4.00 30 0.5924. Public Utilities at the Tourist
Attraction2.24 31 1.15 4.33 11 0.47
25. General Cleanliness TouristAttraction and Area Around it
2.85 28 1.00 4.33 11 0.47
26. Condition of Signage Within theTourist Attraction
3.43 15 0.75 4.25 19 0.44
27. Parking Facility at the TouristAttraction
2.63 30 1.19 4.38 8 0.49
28. Availability of Trained TouristGuides
3.46 14 1.02 4.23 23 0.58
29. Behaviour of the Guides at theTourist Attraction
3.94 7 0.61 4.24 22 0.61
30. Conservation of Heritage Sites 2.76 29 1.02 4.20 25 0.5531. Promptness at the Ticketing
Window of the Monument/TouristAttraction
4.00 6 0.55 4.11 28 0.52
32. Power Supply Situation 3.78 9 0.77 4.33 11 0.4733. Telephone/Mobile Services 4.43 1 0.55 4.58 1 0.50Rank Correlation Coefficient .311Significant(2-tailed) .078Correlation is not significant at the 0.05 level (2-tailed).
Data Analysis
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Graph 12
Table 4.2.9.12 reveals that Hoteliers are satisfied with twenty-four tourist services and
amenities seeing that the mean score is more than 3(quadrant Ist in the graph).
Whereas dissatisfied with nine services as the mean score is less than 3. Hoteliers are
strongly satisfied with the ‘telephone/mobile services’, ‘availability of commercial
transportation’ and ‘behaviour of the drivers of commercial transportation’,
‘availability of hotels’ and ‘hygiene at wayside restaurants and dhabas’ because ranks
are 1st, 2nd, 3rd and 4th respectively. However, they are strongly dissatisfied with the
‘air’ and ‘rail’ connectivity, ‘public utilities at the tourist attraction’ and ‘parking
facility’ whose ranks are thirty-three to thirty respectively.
According to hoteliers, all thirty-three tourist services and amenities are important at
the destination since the mean score is 3. But the most important services are
‘telephone and mobile services’ i.e. communication that receives 1st rank, 2nd to
‘condition of city roads’ and 3rd rank each to ‘drinking water supply’, ‘garbage
Data Analysis
Shivaji University, Kolhapur 282
disposal’ and ‘sewage and drainage system’ i.e. civic administration. The least
important services are ‘air’ and ‘rail’ connectivity, ‘levels of road taxes’ and
‘administration of the road taxes’ whose ranks are 33 to 30 respectively.
Spearman’s rank correlation coefficient is 0.311, which is not significant at 0.05
levels (2-tailed). This refers that there is no uniformity into the opinion of satisfaction
and importance.
Twenty-three variables appeared in the 1st quadrant which shows the highest
satisfaction and highest importance level of tourist services and amenities in hoteliers’
point of view. Only one service i.e. ‘telephone and mobile services’ is in highest
position as well ‘administration of road taxes’ is very close to the average importance
level. The services like ‘garbage disposal’, ‘public convenience along roads/streets’,
and ‘quality of wayside amenities available on this road’ and ‘availability of pertol
pump’ are closer to the average satisfaction and carries high importance level. Other
variables appeared on highest side of satisfaction rather than its importance. Level of
road taxes on vehicle lie in the 2nd quadrant, which reflects high satisfaction and lower
importance, but the importance level is close to the average importance. ‘Air’ and
‘rail’ connectivity services are positioned in the third quadrant, which shows the low
satisfaction and low importance level. Eight variables appeared in the fourth
quardrant, which is more important because of their high importance and lower
satisfaction level. They are ‘public utilities at the tourist attraction’, ‘general
cleanliness at tourist attraction and area surround it’, ‘parking facility at the tourist
attraction’, ‘conservation of heritage sites’, ‘traffic management’, ‘sewage and
drainage system’, ‘quality of roads’, ‘condition of city roads’. A ‘public utility at the
tourist attraction’ is the priority in the development of tourist destination in Satara.
Condition of city roads, sewage and drainage system, quality of roads and traffic
management are nearer to the average satisfaction level so with little stretch it can be
improved to the extent of tourist satisfaction.
It concludes that quadrant four is important to focus since these parameters are most
important and carries dissatisfaction in the opinion of sample tourists. Variable
number 24, 25 and 27 viz. ‘Public utilities a tourist attraction’, ‘general cleanliness’
and ‘parking facility at the tourist attraction’ need to be attended to.
Data Analysis
Shivaji University, Kolhapur 283
Infrastructural Gap inTour Operators Point of View
The perceptual satisfaction and importance of respondents towards infrastructure
facilities are presented with the help of mean score, ranks, and standard deviation
(S.D).
Table 4.2.9.13Perceptual Gap between Importance and Satisfaction of Tour Operators towardsTourist Services and Amenities at Satara District as a Whole
(n=10)
Sr. Tourist Service and AmenitiesSatisfaction Importance
Mean Rank S.D. Mean Rank S.D.
1. Air Connectivity Status 1.71 33 1.11 2.6 33 1.432. Rail Connectivity Status 2.90 15 0.99 3.1 32 1.23. Quality of the Roads 3.00 11 0.94 4.6 3 0.524. Quality of Way Side Amenities
Available on This Road2.80 18 1.40 4.2 20 0.42
5. Public Conveniences AlongRoads/Streets
2.60 22 1.35 4.2 20 0.63
6. Sewage and Drainage System 2.11 31 0.78 4.3 11 0.487. Garbage Disposal 2.30 28 1.06 4.3 11 0.678. Condition of City Roads 2.20 29 1.14 4.6 3 0.79. Drinking Water Supply 2.80 18 1.14 4.8 1 0.4210. Condition of Street Lighting 2.90 15 1.20 4.2 20 0.6311. Traffic Management 2.20 29 0.92 3.9 30 1.112. Condition of Traffic or Transport
Signage3.00 11 1.15 4.5 5 0.53
13. Availability of CommercialTransportations
3.90 2 0.74 4.2 20 0.42
14. Behaviour of the Drivers ofCommercial Transportations
3.80 3 0.79 4.5 5 0.53
15. Availability of Authorized TourOperators
3.40 10 0.97 4 29 0.82
16. Availability of Hotels 4.00 1 0.82 4.5 5 0.5317. Behaviour of Service Staff at the
Hotel3.60 6 0.70 4.2 20 0.42
18. Tariff Structure of the Hotel Rooms 3.50 7 0.85 4.2 20 0.4219. Hygiene at Wayside Restaurants and
Dhabas3.44 8 0.88 4.3 11 0.48
20. Availability of Petrol Pump 3.70 5 0.48 4.3 11 0.6721. Behaviour of Service Personnel at
Wayside Restaurants and Dhabas3.44 8 0.88 4.2 20 1.03
22. Levels of Road Taxes onVehicles(Tax Rates)
2.67 21 1.32 4.3 11 0.67
23. Administration of the Road Taxes 2.89 17 1.17 4.3 11 0.4824. Public Utilities at the Tourist
Attraction2.10 32 0.88 4.5 5 0.71
Data Analysis
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25. General Cleanliness TouristAttraction and Area Around it
2.50 24 0.97 4.3 11 0.67
26. Condition of Signage Within theTourist Attraction
2.60 22 0.97 4.2 20 0.63
27. Parking Facility at the TouristAttraction
2.50 24 0.97 4.3 11 0.67
28. Availability of Trained TouristGuides
2.40 27 1.35 4.3 11 0.48
29. Behaviour of the Guides at theTourist Attraction
3.00 11 1.22 4.2 20 0.44
30. Conservation of Heritage Sites 2.50 24 0.97 4.5 5 0.5331. Promptness at the Ticketing Window
of the Monument/Tourist Attraction3.00 11 0.87 3.9 30 0.74
32. Power Supply Situation 2.80 18 1.03 4.4 10 0.733. Telephone/Mobile Services 3.80 3 1.23 4.8 1 0.42Rank Correlation Coefficient .642**
Significant(2-tailed) .000**. Correlation is significant at the 0.01 level (2-tailed).
Source: Field Data
Graph 13
Data Analysis
Shivaji University, Kolhapur 285
Table 4.2.9.13 reveals that Tour operators are satisfied with the fourteen tourist
services and amenities which are available at Satara since their mean score is more
than 3(quadrant Ist in the graph). However, they are dissatisfied with the nineteen
services and amenities as the mean score is less than 3. Tour operators are strongly
satisfied with services that are ‘availability of hotels’, ‘availability of commercial
transportation’, ‘behaviour of drivers of commercial transportation’ and ‘telephone
and mobile services’ whose ranks are one, two and three respectively. However,
strong dissatisfaction with the ‘air connectivity’, ‘public utilities at tourist attraction’,
‘sewage and drainage system’, ‘traffic management’, ‘condition of city roads’, ‘public
utilities at tourist attraction’, ‘condition of city roads’ and ‘traffic management’ as
their ranks are thirty-three to twenty-nine respectively.
All the tourist services and amenities are important except ‘air connectivity’ as the
mean score is more than 3. ‘Drinking water supply,’ ‘Telephone and mobile’ services
receive 1st rank each, and 3rd rank each to ‘condition of city roads’ and ‘quality of
roads’ which are most important. But ‘air connectivity’, ‘rail connectivity,’ ‘traffic
management’ and ‘promptness of ticketing window’ finds least importance since the
ranks are thirty three to twenty respectively.
Spearman’s rank correlation coefficient is 0.311, which is not insignificant at 0.05
levels (2-tailed). This signifies that there is no uniformity into the opinion of
satisfaction and importance.
The first quadrant is reflecting the highest importance as well highest satisfaction
levels of which fourteen variables are positioned. Out of them four variables viz.
‘promptness of ticketing window’, ‘behaviour of guide at tourist attraction’,
‘condition of traffic’, ‘transport signage’ and ‘quality of roads’ are on the border of
satisfaction and very close to the highest importance level. Second quadrant is empty;
it means there is no single variable carrying low importance and highest satisfaction.
‘Air connectivity’ finds only in third quadrant, which reflects low satisfaction and low
importance. Sixteen variables found in fourth quadrant viz. rail connectivity, traffic
management, sewage and drainage system, public utilities at the tourist attraction,
parking facility at the tourist attraction, availability of trained tourist guide, general
cleanliness at tourist attraction and area around it, condition signage within tourist
attraction, levels of road taxes on vehicles, quality of roads, condition of traffic or
Data Analysis
Shivaji University, Kolhapur 286
transport signage, quality of wayside amenities available on this road, administration
of road taxes, condition of street light, drinking water supply, behaviour of guide at
tourist attraction, promptness of ticket window and power supply situation which
depicts highest importance level and lower satisfaction level. Among these services
‘public convenience along roads/streets’, ‘general cleanliness of tourist attraction and
area around it’, ‘parking facility’, ‘conservation of heritage sites’, ‘availability of
trained tourist guide’, ‘drinking water supply’, ‘traffic management’, ‘sewage and
drainage system’, ‘public utilities at tourist attraction’ and ‘condition of city roads’
are needed to be developed as these services reveals high importance to the tourist and
however, more dissatisfaction towards the services.
It concludes that Quadrant 4 is important to focus since these parameters are most
important and carries dissatisfaction in the opinion of sample tourists. Variable
number 6, 24, 8, 30 and 7 viz. ‘Sewage and drainage system’, ‘public utilities at
tourist attraction’, ‘condition of city roads’, ‘conservation of heritage site’ and
‘garbage disposal’ need to be address.
Infrastructural Gap According to All Stakeholders
The perceptual satisfaction and importance of respondents towards infrastructure
facilities are presented with the help of mean score.
Table 4.2.9.14Perceptual Gap between Importance and Satisfaction of Stakeholders towards TouristServices and Amenities at Satara District as a Whole
Sr
Stakeholders’ Perception
Tourist Service and Amenities
Satisfaction Mean Importance Mean
Tourist
Hoteliers
Touroperator
Tourist
Hoteliers
Touroperator
1. 2. 3. 4. 5. 6. 7.1. Air Connectivity Status 1.29 1.17 1.71 2.83 3.18 2.62. Rail Connectivity Status 1.96 2.20 2.90 3.10 3.53 3.13. Quality of the Roads 3.17 2.90 3.00 4.45 4.40 4.64. Quality of Way Side Amenities
Available on This Road3.30 3.40 2.80 4.29 4.25 4.2
5. Public Conveniences AlongRoads/Streets
3.02 3.13 2.60 4.23 4.33 4.2
6. Sewage and Drainage System 3.11 3.00 2.11 4.20 4.43 4.3
Data Analysis
Shivaji University, Kolhapur 287
7. Garbage Disposal 3.16 3.10 2.30 4.21 4.43 4.38. Condition of City Roads 2.79 2.90 2.20 4.39 4.48 4.69. Drinking Water Supply 3.43 3.67 2.80 4.44 4.43 4.810. Condition of Street Lighting 3.40 3.40 2.90 4.24 4.15 4.211. Traffic Management 2.92 2.90 2.20 4.42 4.25 3.912. Condition of Traffic or Transport
Signage3.10 3.73 3.00 4.47 4.28 4.5
13. Availability of CommercialTransportations
3.52 4.13 3.90 4.32 4.30 4.2
14. Behaviour of the Drivers ofCommercial Transportations
3.75 4.13 3.80 4.16 4.35 4.5
15. Availability of Authorized TourOperators
2.99 3.58 3.40 3.14 4.05 4
16. Availability of Hotels 3.55 4.03 4.00 4.14 4.38 4.517. Behaviour of Service Staff at the
Hotel3.67 3.83 3.60 4.20 4.33 4.2
18. Tariff Structure of the HotelRooms
3.12 3.38 3.50 4.16 4.21 4.2
19. Hygiene at Wayside Restaurantsand Dhabas
3.16 4.03 3.44 4.26 4.40 4.3
20. Availability of Petrol Pump 3.09 3.25 3.70 4.20 4.28 4.321. Behaviour of Service Personnel at
Wayside Restaurants and Dhabas3.76 3.75 3.44 4.21 4.15 4.2
22. Levels of Road TaxesonVehicles(Tax Rates)
2.78 3.14 2.67 3.97 3.94 4.3
23. Administration of the Road Taxes 2.99 3.36 2.89 4.04 4.00 4.324. Public Utilities at the Tourist
Attraction2.65 2.24 2.10 4.59 4.33 4.5
25. General Cleanliness TouristAttraction and Area Around it
3.25 2.85 2.50 4.60 4.33 4.3
26. Condition of Signage Within theTourist Attraction
3.36 3.43 2.60 4.57 4.25 4.2
27. Parking Facility at the TouristAttraction
2.95 2.63 2.50 4.58 4.38 4.3
28. Availability of Trained TouristGuides
2.98 3.46 2.40 4.21 4.23 4.3
29. Behaviour of the Guides at theTourist Attraction
3.53 3.94 3.00 4.09 4.24 4.2
30. Conservation of Heritage Sites 3.76 2.76 2.50 4.60 4.20 4.531. Promptness at the Ticketing
Window of the Monument/TouristAttraction
4.19 4.00 3.00 4.39 4.11 3.9
32. Power Supply Situation 3.75 3.78 2.80 4.44 4.33 4.433. Telephone/Mobile Services 3.93 4.43 3.80 4.72 4.58 4.8Source: Field Data
Data Analysis
Shivaji University, Kolhapur 288
Graph 14
Low Importance High
Table 4.2.9.14 reveals the opinion of tourist, hotelier and tour operator on 33 tourist
services and amenities at Satara. For Air (1) and rail (2) connectivity. Tourist, hotelier
and tour operators are dissatisfied with services and tourist and tour operator do not
feel its importance level for tourism development but hoteliers said it is important for
tourism development. It shows there is a difference of opinion among the
stakeholders.
For Road Connectivity (3, 4), Tourist and tour operators are satisfied with quality of
roads (3) as the mean score is more than 3 but hoteliers are not as their mean score is
less than 3 and tourist and hoteliers are satisfied with quality of way side amenities
available on this road (4) since the mean score is more than 3 but the tour operators
Data Analysis
Shivaji University, Kolhapur 289
are not as the mean score is less than 3. All stakeholders feel road connectivity is most
important in Satara for tourism development.
For Civic Administration (5 to 10) tourist and hoteliers are satisfied with Public
Conveniences along Roads/Streets (5), Sewage and Drainage System (6) and Garbage
Disposal since the mean score is more than 3 but tour operators are not as the mean
score is less than 3. For condition of city roads (8) all carries similar opinion that
dissatisfaction as the mean score is less than 3. For Drinking water supply(9) and
condition of street lighting(10) tourist and hoteliers are satisfied as the mean score is
more than 3 but hotelier is dissatisfied for the same as the mean score is less than 3.
However all carries similar opinion on the most importance of civic administration for
tourism development is Satara since the mean score is more than 4.
For Traffic and Transport Services (11 to 14) all stakeholders are dissatisfied with
traffic management (11) since the mean score is less than 3 but satisfied with
condition of traffic and transport signage(12), availability of commercial
transportation(13) and behaviour of drivers of commercial transportations(14) as the
mean score is more than 3. According to them traffic and transport services are most
important in Satara tourism development.
For Tourist Facilities (15 to 21) Tourist are dissatisfied with the availability of
authorized tour operators (15) as the mean score is less than 3 whereas the hoteliers
and tour operators are satisfied for the same since the mean score is more than 3. All
stakeholders are satisfied with availability of hotels (16), Behaviour of Service Staff
at the Hotel (17), Tariff Structure of the Hotel Rooms (18), Hygiene at Wayside
Restaurants and Dhabas (19), Availability of Petrol Pump (20) and Behaviour of
Service Personnel at Wayside Restaurants and Dhabas (21) since the mean score is
more than 3. According to stakeholders, tourist facilities are most important for
tourism development at Satara since the mean score is more than 4.
For Taxes/ Permits (22 and 23), Tourist and tour operators are dissatisfied as the mean
score is less than 3 and hoteliers are satisfied since the means score is more than 3.
According to Stakeholders taxes and permits is most important as the mean score is
more than 3.
For Maintenance and Management of Tourist Attraction (24 to 31) All stakeholders
are satisfied with behaviour of the guide at the tourist attraction (29) and promptness
Data Analysis
Shivaji University, Kolhapur 290
at the ticketing window of the monument/tourist attraction(31) since the mean score is
more than 3. They are dissatisfied with the public utilities at the tourist attraction (24),
parking facility at the tourist attraction (27) as the mean score is less than 3. Tourist
are satisfied with general cleanliness of tourist attraction and area around it (25) as the
mean score is more than 3 but hoteliers and tour operators are not as the mean score is
less than 3. Tourist and hoteliers are satisfied with the condition of signage within the
tourist attraction (26) since the mean score is more than 3 but tour operators are not as
the mean score is less than 3. Tourist and Tour operators are not satisfied with
availability of trained tourist guide (28) as the mean score is less than 3 but hoteliers
are satisfied for the same as the mean score is more than 3. Tourist are satisfied with
the conservation of heritage sites(30) since the mean score is more than 3 but hoteliers
and tour operators are not as the mean score is less than 3. According to all
stakeholders, maintenance and Management of Tourist attraction services and
amenities are most important at Satara since the mean score is more than 4.
For Other Services (32 and 33) Tourist, hoteliers, and tour oprators are satisfied on
telephone and mobile services (33) as the mean score is more than 3. Tourist and
hoteliers are satisfied with power supply since the mean score is more than 3 but the
tour operators are not as the mean score is less than 3. According to stakeholders
power supply and telephone services are most important for tourism development at
Satara.
It concludes that all are dissatisfied with air(1) and rail(2) connectivity, condition of
city roads(8), traffic management(11), public utilities at the tourist attraction(24),
parking facilities(27). Thus, need to be address for the tourism development at Satara.
It shows the weakness of Satara on infrastructural base.
All are satisfied with condition of traffic and transport signage(12), availability of
commercial transportation (13), behaviour of driver of commercial transportations
(14), availability of hotels(16), behaviour of service staff at the hotels(17), tariff
structure of the hotel rooms (18), hygiene of wayside restaurant and Dhabas(19),
availability of petrol pump (20), behaviour of service personnel at wayside restaurants
and Dhabas(21), behaviour of the guide at the tourist attraction(29), promptness at the
ticketing window of the monument/tourist attraction(31), power supply (32) and
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telephone and mobile services(33). It shows the strengths of Satara on infrastructure
base.
There are differences of opinion among the perception of tourist and service provider
i.e. hoteliers and tour operators on some of the tourist services and amenities. As the
tourists are dissatisfied with the availability of tour operators (15), level of road taxes
(22) and administration of the road taxes (23), availability of trained tourist guide (28)
but service providers do not carry similar opinion. According to tourist, hoteliers and
tour operators, all these tourist services and amenities are most important except air
service, which is not important to the tourist whereas it is important to the hoteliers.
X-axis represents the importance level and y-axis represents the satisfaction level. 3 is
the median value divide the graph into 4 quadrants. Ist quadrant depicts high
importance and high satisfaction where 13 variables in a sound position. IInd quadrant
depicts low importance and high satisfaction where no single variable found. In IIIrd,
quadrant depicts one variable that shows less importance and less satisfaction i.e. air
connectivity. However, in IVth quadrant 19 variables that shows high importance but
least satisfaction with slight difference of opinion among the stakeholders on
perception of tourist services and amenities.
Factor Analysis:
The responses towards tourist amenities on five-point scale were taken from tourist.
Thirty-three tourist amenities were executed. Researcher with view to find out
commonalities into preferences factor analysis has been applied.
KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .784
Bartlett's Test ofSphericity
Approx. Chi-Square 5.85
df 528
Sig. .000
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The KMO and Bartlett’s measure comes to 0.784, which shows data adequacy to go
for factor analysis.
Total Variance Explained
Component
Initial Eigen valuesExtraction Sums ofSquared Loadings
Rotation Sums of SquaredLoadings
Total% of
VarianceCumulat
ive %Total
% ofVariance
Cumulative %
Total% of
VarianceCumulat
ive %
1 7.129 21.604 21.604 7.129 21.604 21.604 4.728 14.327 14.327
2 3.938 11.933 33.536 3.938 11.933 33.536 3.291 9.972 24.299
3 2.523 7.644 41.181 2.523 7.644 41.181 3.132 9.491 33.790
4 2.208 6.692 47.872 2.208 6.692 47.872 2.702 8.189 41.979
5 1.702 5.158 53.031 1.702 5.158 53.031 2.029 6.149 48.129
6 1.606 4.867 57.898 1.606 4.867 57.898 1.995 6.046 54.174
7 1.389 4.209 62.106 1.389 4.209 62.106 1.765 5.349 59.523
8 1.243 3.766 65.872 1.243 3.766 65.872 1.680 5.092 64.615
9 1.021 3.093 68.965 1.021 3.093 68.965 1.436 4.350 68.965
Extraction Method: Principal Component Analysis.
The responses of 326 samples were executed with the help of factor analysis. Nine
factors have been extracted using principal component methods, which explain
68.96% of variance.
The rotated component matrix has been work out to find out the nine factors and thevariables belongs to every factor.
Rotated Component MatrixComponent
TouristServicesCode
1 2 3 4 5 6 7 8 9
C7I .842 .046 .157 -.019 .028 .152 .091 -.006 -.034C6I .799 .055 .149 -.055 -.008 .135 .074 -.023 -.036C9I .795 .194 -.032 -.094 .069 .037 .044 .146 -.006C11I .780 .157 .074 .159 .019 -.082 .017 -.118 -.051C8I .746 .238 .000 .051 -.037 .117 -.113 .257 .162C12I .660 .274 .079 .298 .006 -.065 -.104 -.074 .090C10I .656 .187 .042 -.057 .037 .019 -.160 .320 .376C19I .261 .806 .280 .009 -.161 .010 .100 .091 -.028
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C20I .304 .774 .151 -.016 -.037 -.032 -.059 .191 .105C21I .236 .749 .088 .058 -.197 .026 .078 -.035 .006C13I .510 .518 .184 -.021 -.035 .053 .086 -.097 .039C14I .245 .518 .125 .160 .224 .148 -.137 -.228 .191C23I .166 .092 .883 -.121 -.105 -.024 -.016 .033 .032C22I .176 .090 .875 -.029 -.130 -.068 -.029 .006 .016
C18I-
.004.479 .634 -.001 .285 -.014 -.020 .048 -.092
C17I .004 .470 .611 -.015 .293 .066 -.091 .075 -.049C16I .173 .357 .559 -.166 .245 -.006 -.122 .054 .260C25I .060 -.004 -.055 .767 -.085 .139 .085 .117 .043C24I .017 .129 -.001 .744 -.079 .169 -.006 .099 -.046C27I .085 -.140 -.097 .725 .003 -.038 244 091 -.173
C26I-
.027.067 -.061 .653 -.097 .173 .173 -.070 .029
C1I .045 -.156 .038 -.119 .880 -.003 .106 .022 -.081C2I .021 -.011 .020 -.129 .860 .121 .082 .026 068C4I .133 .008 .141 .208 -.056 .816 -.049 -.070 -.009C5I .115 -.027 -.040 .130 .166 .714 .124 .051 -.179C3I .006 .102 -.198 127 .037 .704 .004 .119 .228C29I .064 .050 -.092 .094 .078 -.021 .831 -.035 .039
C28I-
.085.042 -.009 .294 .137 .069 .653 .076 .058
C30I .048 -.100 -.034 .295 -.045 .063 .474 .224 -.344C32I 085 -.033 .141 .053 .040 -.121 .069 .774 .088C33I .044 .118 -.052 .226 .022 .279 .048 .729 -.038
C31I-
.161-.027 .100 191 .144 -.097 -.247 -.247 -.706
C15I .001 .094 .399 .155 .174 -.124 -.296 -.208 .603
Extraction Method: Principal Component Analysis.Rotation Method: Varimax with Kaiser Normalization.a. Rotation converged in 18 iterations.
From above rotated component matrix, following factors has been derived.
Researcher has proposed the labels to the factors, which are mention at the title.
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Table 4.2.9.15Factor Civic Infra of tourist samples
Factor I- Factor Civic Infra
Component Tourist Services and AmenitiesFactor
LoadingC7I Garbage Disposal 0.842C6I Sewage and Drainage System 0.799C9I Drinking Water Supply 0.795C11I Traffic Management 0.780C8I Condition of City Roads 0.746C12I Condition of Traffic or Transport Signage 0.660C10I Condition of Street Lighting 0.656
Civic infra is the factor extracted from the 7 variables.
Table 4.2.9.16Factor Tourist Infra of tourist samples
Tourist infra is the factor extracted from five variables.
Table 4.2.9.17Factor Accommodation and Taxes of tourist samples
Factor Accommodation and Taxes extracted from five variables.
Factor II- Factor Tourist Infra
Component Tourist Services and AmenitiesFactor
LoadingC19I Hygiene at Wayside Restaurants and Dhabas 0.806C20I Availability of Petrol Pump 0.774
C21IBehaviour of Service Personnel at WaysideRestaurants and Dhabas
0.749
C13I Availability of Commercial Transportations 0.518
C14IBehaviour of the Drivers of CommercialTransportations
0.518
Factor III- Factor Accommodation and Taxes
Component Tourist Services and AmenitiesFactor
LoadingC23I Levels of Road Taxes on Vehicles(Tax Rates) 0.883C22I Administration of the Road Taxes 0.875C18I Availability of Hotels 0.634C17I Behaviour of Service Staff at the Hotel .0611C16I Tariff Structure of the Hotel Rooms 0.559
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Table 4.2.9.18Factor Maintenance and Management of Tourist Attraction of tourist samples
Factor Maintenance and Management of Tourist Attraction is extracted from 4variables.
Table 4.2.9.19Factor Transportation Facility of tourist samples
Factor Transportation Facility is extracted from 2 variables.
Table 4.2.9.20
Factor Road Infra of tourist samples
Factor road infra is extracted from three variables.
Factor IV- Factor Maintenance and Management of Tourist Attraction
Component Tourist Services and AmenitiesLoadingFactor
C25I Public Utilities at the Tourist Attraction 0.767
C24IGeneral Cleanliness Tourist Attraction andArea Around it
0.774
C27ICondition of Signage Within the TouristAttraction
0.725
C26I Parking Facility at the Tourist Attraction 0.653
Factor V- Factor Transportation Facility
Component Tourist Services and AmenitiesLoadingFactor
C1I Air Connectivity Status 0.880C2I Rail Connectivity Status 0.860
Factor VI- Factor Road InfraComponent Tourist Services and Amenities Loading Factor
C4I Quality of the Roads 0.816
C5IQuality of Way Side Amenities Availableon This Road
0.714
C3I Public Conveniences Along Roads/Streets 0.704
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Table 4.2.9.21Factor Conservation and Guidance of tourist samples
Factor Conservation and Guidance is extracted from 3 variables.
Table 4.2.9.22Factor Essential Services of tourist samples
Factor Essential Services is extracted from 2 variables.
Table 4.2.9.23Factor Peripheral Services of tourist samples
Factor Peripheral Services is extracted from two variables.
Researcher has referred the report of Government of India, Tourism Ministry
marketing research department to develop structure as per the need of study the
structure is mentioned in detailed in research methodology chapter. In the said scale,
the structure used 33 variables to measure the tourist perception on importance of
tourist services and amenities at destination. Researcher has analyzed the data
collected with the help of said scale using factor analysis as above and extracted nine
Factor VII-Conservation and GuidanceComponent Tourist Services and Amenities Loading Factor
C29IAvailability of Trained TouristGuides
0.831
C28IBehaviour of the Guides at theTourist Attraction
0.653
C30I Conservation of Heritage Sites 0.474
Factor VIII-Essential Services
Component Tourist Services and AmenitiesLoadingFactor
C32I Power Supply Situation 0.774C33I Telephone/Mobile Services 0.729
Factor IX-Peripheral ServicesComponent
Tourist Services and AmenitiesLoadingFactor
C31IPromptness at the Ticketing Window of theMonument/Tourist Attraction
0.706
C15I Availability of Authorized Tour Operators 0.603
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factors with the labels ‘civic infra’, ‘tourist infra’, ‘accommodation and taxes’,’
maintenance and management of tourist attraction’, ‘transportation facility’, ‘road
infra’, ‘conservation and guidance’, ‘essential service’ and ‘peripheral service’.
Comparing both scale it has found that in earlier structure contains 33 variables under
9 heads viz. Air facility, Road facility, Road Connectivity, Civic Administration,
Traffic and Transport Management, Tourist Facilities, Taxes/Permits, Maintenance,
Management of tourist Attraction and Other Services. After factor analysis nine
factors are extracted some of the variables has shifted their place from one group to
another group e.g. In the first loaded factor there are 7 variables, one variable of civic
administration missed and 2 variables of traffic and transport management added into
factor I. In the IInd loaded factor 5 variables are grouped out of these 3variables are
from tourist facilities and 2 from traffic and transport management. In the 3rd loaded
factor 5 variables are grouped, out of these 2 are from taxes/permits category and 3
from tourist facilities. In IVth loaded factor 4 variables are grouped all are from
maintenance and management of tourist attraction titled. In V loaded factor 2
variables are grouped and they are from separate identity of air facility and rail
facility. In VI loaded factor3 variable are grouped out of these 2 from road
connectivity and one from public convenience along roads/streets titled. In VII loaded
factor 3 variables are grouped all from maintenance and management of tourist
attraction titled. In VIII loaded factor 2 variables are grouped they are from other
service titled. In IX loaded factor 2 variables are grouped out of these one belong to
tourist facility and one from maintenance and management of tourist attraction titled.
Thus some of the variables remained in the groups and some of have shifted their
place. Researcher has renamed as per their nature of services to suffice the purpose of
study.
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Section X
4.2.10 Exploration of Destination:
Tourist visits only known famous places in Satara. There are number of destinations
worth seeing in Satara. Researcher observed majority of stakeholders like hoteliers,
tour operators, and government officials are not aware of many worth seeing
destinations. There is scope to explore few of them to develop and promote Satara as
a versatile tourist destination.
4.2.10.1 Vajrai Destination:
1. Name of Destination- Vajrai Waterfall, a place very close to Kas Lake yet
remained unnoticed by tourists. A beautiful destination, which is worth seen in
rainy season.
2. Reach- 31 Km away from Satara and Just 6 Km from Kas Lake.
3. Attractions to See
a. Waterfallb. Uramodi dams Backflowc. Misty and foggy environmentd. Mountain Ranges with valliese. Beautiful Naturef. Dense Forestg. Ideal for Trekkingh. Ideal Village Tourismi. Existence of Wild Animals like Bison, Bear and Leopard.j. Good location for Summer Campk. Mahakali and Vajrai Goddess Templel. Sunrise Pointm. Sunset pointn. Calm and Quiet location and free from pollution, Healthy Natural
Environment.o. A mine of Ayurvedic medicinal herbal plants.
4. Places of Tourist interest in vicinity
a. Kas Lake(from Vajrai 8 Km.)b. Kas Flora( from Vajrai 10 Km.)c. Bamnoli ( from Vajrai 18 Km)d. Tapola (from Vajrai 60 Km. but from Bamnoli ½ hour boating to Tapola)
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5. Rout Map-
6. Existing Tourism Services and Facilities
a. Road Connectivity- Road Connectivity is good; quality of road is also
good.
b. Civic Amenities- Drinking water supply
c. Traffic and Transport Facilities- thinly populated, very few i.e. 40-50
families are living. No traffic flow, less transport options.
d. Tourist Facilities- Opportunity to test local food.
e. Maintenance and Management of tourist Attractions- thinly populated and
more dense forest so less chance for garbage disposal or automatically
maintained clean, parking facility is available, trained guide can be made
available, behavior is excellent, local community has conserved the nature
since the local people are going to act as a guide there.
f. Other Services- Power supply, telephone and mobile services are good
7. Required Facilities to explore as a tourist destination
a. Quality of wayside amenities, Public convenience along road.
b. Civic Amenities- Sawage and drainage system, garbage disposal, condition
of street light.
c. Traffic and transport Facilities- traffic signage, commercial transportation
d. Tourist Facilities- hotels, petrol pump and restaurant and Dhaba
e. Maintenance and Management of tourist Attractions- public toilets.
Bamnoli Kas Plateau12km Kas Lake
1km 2km . 22km
Kas
6km.
Vajari
Sataraa
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8. How to Promote
Vajrai Waterfall, a good opportunity for tourist to visit this location who comes for
Kas Lake or Kas Flora. Accommodation facility needs to develop in the form of
Dharmshala and youth Hostels. This kind of destination can be boon to tourists who
likes to be away from busy metro life, nature lover, lonely and isolated environment,
people who are fond of adventure. Sustainable, village and Nature Tourism can be
possible. Vajrai is a good destination in rainy and winter season.
4.2.10.2 Parli Destination:
1. Name of Destination- Parli Temple
2. Reach- 10 Km away from Satara and in basement of Sajjangarh and
Uramodi Dam
3. Attractions to Seea. Mountain Rangesb. Beautiful Naturec. Ideal for Village Tourismd. The temple is a small model of Khajurao sculpturee. The temple is oldest Hemandpati Templef. A unique Shivling with five faces carved on it.g. A panoramic view of Urmodi Damh. Sunrise Pointi. Sunset pointj. Calm and Quiet location and free from pollution, Healthy Natural
Environment.
4. Rout Map
Parli Bogda(Tunnel)
1km 6km 3km.
Sajjangarh
2km
Satara
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5. Nearby Other Places to Visit
a. Sajjangarhb. Kelwali and Sandwali Waterfallc. Urmodi Damd. Thoseghare. Chalkewadi Wind Project
6. Existing Tourism Services and Facilities
a. Road Connectivity- Road Connectivity is good; quality of road is also good.
Quality of wayside amenities are good, Public convenience along road is also
excellent.
b. Civic Amenities- Drinking water supply is good. Sewage and drainage
system garbage disposal; condition of street light is available.
c. Traffic and Transport Facilities- thinly populated, tourist are unaware about
the destination so no tourist traffic flow as of date good commercial
transportation facilities existed.
d. Tourist Facilities- Restaurants are available, presentably catering local needs.
e. Maintenance and Management of tourist Attractions- Maintained Cleanliness,
parking facility is available.
f. Other Services- Power supply, telephone and mobile services are existed.
7. Required Facilities to explore as a tourist destination
a. Civic Amenities- Traffic and transport Facilities- traffic signage,
b. Tourist Facilities- Accommodation, hotels, petrol pump.
c. Maintenance and Management of tourist Attractions- public toilets and guide
facility.
8. How to Promote
A Parli a good destination to see the stone carving, Oldest Hemandpati temple,neglected by local community and government, a good heritage site presenting asmall model of Khajurao sculpture. There is a good view of Sajjangarh. Thedestination Parli is on the way of Sajjangarh and Thoseghar hence tourist can bediverted and make arrangement of budgeted accommodation i.e. Bed and Breakfast, agood site for Water Park, accessibility towards two waterfall destination i.e. Kelwaliand Sandwali which are also known for trekking.
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Section XI
4.2.11 Hypotheses Testing:
Introduction: This part discuss on the testing of hypotheses that was set in the research
proposal. There are 3 hypotheses tested with testing tools like independent sample ‘t’
test, one sample ‘t’ test, spearman’s rank correlation etc. This part was calculated with
the help of SPSS and results presented with their respective calculations for detailed
references.
This last section of analysis deals with hypotheses testing. Study put forth three
hypotheses to test as follows.
1. Lack of promotion of tourism destinations hinders development of tourism
sector in Satara district.
2. Availability of infrastructural facilities and tourism development are
correlated.
3. Government proposes planning to develop the places of tourist interest but the
gap exists in planning and implementation, which deals to failure in attracting
tourists.
Hypothesis 1:Lack of promotion of tourism destinations hinders development of tourism sector inSatara District.
For this hypothesis researcher has used data of (refer tourist schedule’ section I, sub
section ‘E’ in annexure I) perceptions of tourists about promotion of tourism with
three statements. The data are presented in four sections as first section contains total
tourist response, second section deals with destination wise tourist response, third
section contains hoteliers’ response, and fourth section is of tour operators’ response.
One sample‘t’ test is used with median value 3. The scale used to assess sample
respondent is five point scale with a mid value is three. The hypotheses is tested
across three stakeholders i.e. tourist, hoteliers and tour operators. The independent
testing of hypothesis has also done on tourist’s opinions destination-wise.
1. Total Tourist Opinion on Promotion2. Destination wise Tourist Opinion3. Hoteliers Opinion4. Tour Operators Opinion
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1. Total Tourist Opinion:
Following table presents descriptive statistics related with these three statements.
Sample Tourist Opinion on Promotion.
Table 4.2.11.1Tourists Descriptive Statistics
One-Sample Statistics
Sr.Perception about promotionof Tourism
N MeanStd.
DeviationStd. Error
Mean1. Advertisement play
important role in tourism326 4.08 .72 .04
2. Felt need of promotionalactivities
326 4.20 .74 .04
3. Lack of advertisementrestrict tourismdevelopment
326 4.02 .89 .05
Source: Compiled by Researcher
Sample opines that advertisement plays important role in tourism visa- visa the better
need of promotional activities. Samples highly argue with that lack of advertisement
restrict tourism development since the mean score is above four. All these statements
mean score is above 4 with little S.D states less variations in opinion.
Following table shows the one sample ‘t’ test of three statements.
Table 4.2.11.2Hypothesis Test of Sample Tourist Opinion on Promotion
One-Sample Test
SrPerception about promotion
of Tourism
Test Value = 3
t df
Sig.(2-tailed)
MeanDifference
95%Confidence
Interval of theDifference
Lower Upper1. Advertisement play
important role in tourism26.79 325 .000 1.07 .99 1.15
2. Felt need of promotionalactivities
29.23 325 .000 1.19 1.11 1.27
3. Lack of advertisementrestrict tourismdevelopment
20.64 325 .000 1.01 .92 1.11
Source: Compiled by Researcher
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The‘t’ score for statement first, second and third are 26.79, 29.23 and
20.64respectively, with a ‘P’ value 0.00, the test is significant. It is inferred that
promotion is important and promotion is absent in Satara. Hence, the null hypothesis
is rejected. The alternative hypothesis i.e. lack of promotion of tourism destination
hinders the development of tourism sector in Satara district, is accepted.
2. Destination wise Tourist Response:
Researcher has tested the hypothesis with the samples visited destination-wise. In an
effort to find out opinions of different Strata of samples visited to variety of tourist
destinations. It is believed that the respective destinations are visited by different
strata of tourists having distinct characteristics. The testing of hypothesis destinations
wise is as follows
Following table presents descriptive statistics related with these three statements.
Sample Tourist Opinion on Promotion at Aundh
Table 4.2.11.3Tourists Descriptive Statistics at Aundh
One-Sample StatisticsSr. Perception about promotion
of TourismN Mean
Std.Deviation
Std. ErrorMean
1. Advertisement playimportant role in tourism
30 4.00 .00a .00
2. Felt need of promotionalactivities
30 3.87 .63 .11
3. Lack of advertisementrestrict tourismdevelopment
30 4.00 .74 .14
a. t cannot be computed because the standard deviation is 0.Source: Compiled by Researcher
Sample preaches with less confidence that there is need of promotional activities as
the mean score of this statement is less than 4 but more than 3. But samples argue
more with advertisement play important role and lack of advertisement restrict
tourism development since the mean score is four as these two statements mean is
above 4 with little S.D.
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Following table shows the one sample‘t’ test of three statements.
Table 4.2.11.4Hypothesis Test of Sample Tourist Opinion on Promotion at Aundh
One-Sample Test
Sr.Perception aboutpromotion of Tourism
Test Value = 3
t df
Sig.(2-tailed)
MeanDifference
95% ConfidenceInterval of the
DifferenceLower Upper
1. Felt need of promotionalactivities
7.54 29 .00 .86 .63 1.10
2. Lack of advertisementrestrict tourismdevelopment
7.37 29 .00 1.00 .72 1.28
Source: Compiled by Researcher
The ‘t’ score for statement second and third are 7.54 and 7.37 respectively, with a ‘P’value 0.00, the test is significant. It is inferred that promotion is important andpromotion lacks in Satara. Hence, the null hypothesis is rejected. The hypothesis i.e.lack of promotion of tourism destination hinders the development of tourism sector inSatara district, especially opinions of tourist at Aundh is accepted.
Tourist Descriptive Statistics at Panchgani
Following table presents descriptive statistics related with these three statements.
Table 4.2.11.5Sample Tourist Opinion on Promotion at Panchgani
One-Sample Statistics
Sr. Perception about promotion of Tourism N MeanStd.Deviation
Std.ErrorMean
1. Advertisement play important role intourism
35 3.94 .68 .12
2. Felt need of promotional activities 35 4.03 .66 .113. Lack of advertisement restrict tourism
development35 3.97 .82 .14
Source: Compiled by Researcher
Sample discourse that advertisement plays important role in tourism, lack ofadvertisement restrict tourism development since the mean score is less than four butmore than three. Samples highly argue with need of promotional activities since themean score is 4.03. First and third statements mean is less than four and that to ofsecond statement is above four with little S.D.
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Following table shows the one sample ‘t’ test of three statements.
Table 4.2.11.6Hypothesis Test of Panchgani Sample Tourist Opinion on Promotion
One-Sample Test
Sr.Perception about
promotion of Tourism
Test Value = 3
t dfSig. (2-tailed)
MeanDifferenc
e
95% ConfidenceInterval of the
DifferenceLower Upper
1. Advertisement playimportant role intourism
8.16 34 .00 .94 .71 1.18
2. Felt need ofpromotional activities
9.17 34 .00 1.03 .80 1.26
3. Lack ofadvertisementrestrict tourismdevelopment
6.99 34 .00 .97 .69 1.25
Source: Compiled by Researcher
The ‘t’ score for statement first, second and third are 8.16, 9.17 and 6.99 respectively
with a ‘P’ value 0.00, the test is significant. It is inferred that promotion is essential
and it lacks in Satara. Hence, the null hypothesis is rejected. The hypothesis i.e. lack
of promotion of tourism destination hinders the development of tourism sector in
Satara district, especially opinions of tourist at Panchgani is accepted.
Tourist Descriptive Statistics at Pratapgarh
Following table presents descriptive statistics related with these three statements.
Table 4.2.11.7Sample Tourist Opinion on Promotion at Pratapgarh
One-Sample Statistics
Sr.Perception about
promotion of TourismN Mean S.D.
Std. ErrorMean
1. Advertisement playimportant role in tourism
30 4.17 .53 .10
2. Felt need of promotionalactivities
30 4.13 .57 .10
3. Lack of advertisementrestrict tourism development
30 3.93 .83 .15
Source: Compiled by Researcher
Sample orate that lack of advertisement restrict tourism development as the mean
score is 3.93 which is less than 4 but more than 3. However, Samples very much
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favour with 1st two statements that advertisement play important role in tourism and
need of promotional activities since the mean score is 4.17 and 4.13 respectively. Two
statements mean score is above 4 with little S.D and one statement is below 4 but
more than3.
Following table shows the one sample ‘t’ test of three statements.
Table 4.2.11.8Hypothesis Test of Pratapgarh Sample Tourist Opinion on Promotion
One-Sample Test
Sr.Perception aboutpromotion ofTourism
Test Value = 3
t dfSig.(2-
tailed)
MeanDifference
95% ConfidenceInterval of the
DifferenceLower Upper
1. Advertisementplay important rolein tourism
12.04 29 .00 1.17 .97 1.36
2. Felt need ofpromotionalactivities
10.86 29 .00 1.13 .92 1.35
3. Lack ofadvertisementrestrict tourismdevelopment
6.17 29 .00 .93 .62 1.24
Source: Compiled by Researcher
The ‘t’ score for statement first, second and third are 12.04, 10.86 and 6.17
respectively with a ‘P’ value 0.00, the test is significant. It is inferred that promotion
is indispensable and it absent in Satara. Hence, the null hypothesis is rejected. The
hypothesis i.e. lack of promotion of tourism destination hinders the development of
tourism sector in Satara district, especially opinions of tourists at Pratapgarh is
accepted.
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Tourist Descriptive Statistics at Sajjangarh
Following table presents descriptive statistics related with these three statements.
Table 4.2.11.9Sample Tourist Opinion on Promotion at Sajjangarh
One-Sample Statistics
Sr.Perception about promotion of
TourismN Mean
Std.Deviation
Std.ErrorMean
1. Advertisement play important role intourism
30 3.97 1.15 .21
2. Felt need of promotional activities 30 3.97 1.03 .183. Lack of advertisement restrict tourism
development30 3.70 1.26 .23
Source: Compiled by Researcher
Sample opines that advertisement plays important role in tourism there is need of
promotional activities and lack of advertisement restrict tourism development.
Samples have belief on advertisement play important role in tourism and need of
promotional activities since the mean score is 3.97, which is very close to four. All
these statements mean score is above three with little S.D.
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Following table shows the one sample ‘t’ test of three statements.
Table 4.2.11.10Hypothesis Test of Sajjangarh Sample Tourist Opinion on Promotion
One-Sample Test
Sr.Perception aboutpromotion of Tourism
Test Value = 3
t dfSig.(2-
tailed)
MeanDifference
95% ConfidenceInterval of the
DifferenceLower Upper
1. Advertisement playimportant role intourism
4.57 29 .000 .97 .53 1.40
2. Felt need ofpromotionalactivities
5.12 29 .000 .97 .58 1.35
3. Lack ofadvertisement restricttourism development
3.03 29 .005 .70 .23 1.17
Source: Compiled by Researcher
The‘t’ score of above three statements are 4.57, 5.12 and 3.03 respectively with a ‘P’
value 0.00, the test is significant. It proves that promotion is crucial and that lacks in
Satara. Hence, the null hypothesis is rejected. The hypothesis i.e. lack of promotion
of tourism destination hinders the development of tourism sector in Satara district,
especially opinions of tourist at Sajjangarh is accepted.
Tourist Descriptive Statistics at Wai
Following table presents descriptive statistics related with these three statements.
Table 4.2.11.11Sample Tourist Opinion on Promotion at Wai
One-Sample Statistics
Sr.Perception about promotion
of TourismN Mean
Std.Deviation
Std. ErrorMean
1. Advertisement play importantrole in tourism
37 4.22 .85 .14
2. Felt need of promotionalactivities
37 4.54 .65 .11
3. Lack of advertisement restricttourism development
37 3.94 1.18 .19
Source: Compiled by Researcher
Data Analysis
Shivaji University, Kolhapur 310
Sample discourses that lack of advertisement restrict tourism development. However,
Samples highly believes that advertisement play important role in tourism and need of
promotional activities while the mean score is 4.54. First two statements mean score
is above 4 and last is less than 4 with little S.D.
Following table shows the one sample ‘t’ test of three statements.
Table 4.2.11.12Hypothesis Test of Wai Sample Tourist Opinion on Promotion
One-Sample Test
Sr.Perception about
promotion of Tourism
Test Value = 3
t dfSig.(2-
tailed)
MeanDifference
95% ConfidenceInterval of the
DifferenceLower Upper
1. Advertisement playimportant role intourism
8.66 36 .000 1.21 .93 1.50
2. Felt need ofpromotional activities
14.43
36 .000 1.54 1.32 1.76
3. Lack of advertisementrestrict tourismdevelopment
4.89 36 .000 .94 .55 1.34
Source: Compiled by Researcher
The ‘t’ score for statement first, second and third are 8.66, 14.42 and 4.48 respectively
with a ‘P’ value 0.00, the test is significant. It is inferred that promotion is essential
and it lacks in Satara. Hence, the null hypothesis is rejected. The hypothesis i.e. lack
of promotion of tourism destination hinders the development of tourism sector in
Satara district, especially opinions of tourist at Wai is accepted.
Data Analysis
Shivaji University, Kolhapur 311
Tourist Descritive Statastics at Mahabaleshwar
Following table presents descriptive statistics related with these three statements.
Table 4.2.11.13Sample Tourist Opinion on Promotion at Mahabaleshwar
One-Sample Statistics
Sr. Perception about promotion of Tourism N Mean S.D.Std. Error
Mean1. Advertisement play important role in
tourism30 3.80 .84 .15
2. Felt need of promotional activities 30 3.90 .84 .153. Lack of advertisement restrict tourism
development30 3.77 .93 .17
Source: Compiled by Researcher
Sample orate that advertisement plays important role in tourism, tourist felt there is
better need of promotional activities and lack of advertisement restrict tourism
development . Samples argue with need of promotional activities since the mean score
is 3.90. All these statements mean is more than 3 with little S.D.
Following table shows the one sample‘t’ test of three statements.
Table 4.2.11.14Hypothesis Test of Mahabaleshwar Sample Tourist Opinion on Promotion
One-Sample Test
Sr.Perception aboutpromotion of Tourism
Test Value = 3
t dfSig.(2-tailed)
MeanDifference
95% ConfidenceInterval of theDifferenceLower Upper
1. Advertisement playimportant role intourism
5.17 29 .000 .80 .48 1.12
2. Felt need ofpromotional activities
5.83 29 .000 .90 .58 1.22
3. Lack of advertisementrestrict tourismdevelopment
4.49 29 .000 .76 .42 1.12
Source: Compiled by Researcher
The ‘t’ score above three statements are 5.17, 5.83 and 4.49 respectively with a ‘P’
value 0.00, the test is significant. It is proves that promotion is important and it lacks
in Satara. Hence, the null hypothesis is rejected. The hypothesis i.e. lack of
Data Analysis
Shivaji University, Kolhapur 312
promotion of tourism destination hinders the development of tourism sector in Satara
district, especially opinions of tourist at Mahabaleshwar is accepted.
Tourist Descriptive Statastics at Koyna
Following table presents descriptive statistics related with these three statements.
Table 4.2.11.15Sample Tourist Opinion on Promotion at Koyna
One-Sample Statistics
Sr.Perception about promotion of
TourismN Mean S.D.
Std. ErrorMean
1. Advertisement play important rolein tourism
37 4.16 .55 .091
2. Felt need of promotional activities 37 4.27 .56 .0923. Lack of advertisement restrict
tourism development37 4.16 .65 .106
Source: Compiled by Researcher
Sample preaches on all above statements that advertisement play important role in
tourism and lack of advertisement restrict tourism development and highly argues
with need of promotional activities since the mean score is more than four. All these
statements mean is above 4 with little S.D.
Following table shows the one sample‘t’ test of three statements.
Table 4.2.11.16Hypothesis Test of Koyna Sample Tourist Opinion on Promotion
One-Sample Test
SrPerception aboutpromotion of Tourism
Test Value = 3
t df
Sig.(2-
tailed)
MeanDifference
95% ConfidenceInterval of the
DifferenceLower Upper
1. Advertisement playimportant role in tourism
12.77 36 .000 1.16 .98 1.35
2. Felt need of promotionalactivities
13.79 36 .000 1.27 1.08 1.46
3. Lack of advertisementrestrict tourismdevelopment
10.94 36 .000 1.16 .95 1.38
Source: Compiled by Researcher
Data Analysis
Shivaji University, Kolhapur 313
The ‘t’ score for statement first, second and third are 12.77, 13.79 and 10.94
respectively with a ‘P’ value 0.00, the test is significant. It clears that promotion is
essential and promotion lacks in Satara. Hence, the null hypothesis is rejected. The
hypothesis i.e. lack of promotion of tourism destination hinders the development of
tourism sector in Satara district, especially opinions of tourist at Koyna is accepted.
Tourist Descritive Statastics at Thoseghar
Following table presents descriptive statistics related with these three statements.
Table 4.2.11.17Sample Tourist Opinion on Promotion at Thoseghar
One-Sample Statistics
Sr.Perception about promotion ofTourism
N Mean S.D.Std. ErrorMean
1. Advertisement play important role intourism
33 4.39 .66 .11
2. Felt need of promotional activities 33 4.51 .62 .113. Lack of advertisement restrict tourism
development33 4.33 .64 .11
Source: Compiled by Researcher
Sample opine that advertisement plays important role in tourism, tourist felt there is
better need of promotional activities and lack of advertisement restrict tourism
development. Samples highly argue with that lack of advertisement restrict tourism
development since the mean score is four. All these statements mean is above 4 with
little S.D.
Data Analysis
Shivaji University, Kolhapur 314
Following table shows the one sample ‘t’ test of three statements.
Table 4.2.11.18Hypothesis Test of Thoseghar Sample Tourist Opinion on Promotion
One-Sample Test
Sr.Perception about
promotion of Tourism
Test Value = 3
t dfSig.(2-
tailed)
MeanDifference
95% ConfidenceInterval of the
DifferenceLower Upper
1. Advertisement playimportant role intourism
12.15 32 .000 1.39 1.16 1.63
2. Felt need ofpromotional activities
14.07 32 .000 1.51 1.29 1.73
3. Lack of advertisementrestrict tourismdevelopment
11.86 32 .000 1.33 1.10 1.56
Source: Compiled by Researcher
The ‘t’ score for statement first, second and third are 12.15, 14.07 and 11.86
respectively with a ‘P’ value 0.00, the test is significant. It is inferred that promotion
is essential and it lacks in Satara. Hence, the null hypothesis is rejected. The
hypothesis i.e. lack of promotion of tourism destination hinders the development of
tourism sector in Satara district, especially opinions of tourist at Thoseghar is
accepted.
Data Analysis
Shivaji University, Kolhapur 315
Tourist Descriptive Statastics at Kas
Following table presents descriptive statistics related with these three statements.
Table 4.2.11.19Sample Tourist Opinion on Promotion at Kas
One-Sample Statistics
SrPerception about promotion ofTourism
N Mean S.D.Std. ErrorMean
1. Advertisement play important rolein tourism
30 4.13 .73 .13
2. Felt need of promotional activities 30 4.13 .63 .113. Lack of advertisement restrict
tourism development30 3.87 .63 .11
Source: Compiled by Researcher
Sample orate that lack of advertisement restrict tourism development as the mean
score is above 3. Samples highly argue with that advertisement plays important role in
tourism and need of promotional activities, as the mean score is 4.13. First two
statements mean is 4 with little S.D.
Following table shows the one sample‘t’ test of three statements.
Table 4.2.11.20Hypothesis Test of Kas Sample Tourist Opinion on Promotion
One-Sample Test
Sr.Perception aboutpromotion of Tourism
Test Value = 3
t dfSig.(2-
tailed)
Mean
Difference
95% ConfidenceInterval of the
Difference
Lower Upper
1. Advertisement playimportant role in tourism
8.50 29 .000 1.13 .86 1.40
2. Felt need of promotionalactivities
9.87 29 .000 1.13 .90 1.37
3. Lack of advertisementrestrict tourismdevelopment
7.54 29 .000 .87 .63 1.10
Source: Compiled by Researcher
The‘t’ score of above three statements are 8.50, 9.87 and 7.54 respectively with a ‘P’
value 0.00, the test is significant. It is evident that promotion is important and it lacks
Data Analysis
Shivaji University, Kolhapur 316
in Satara. Hence, the null hypothesis is rejected. The hypothesis i.e. lack of
promotion of tourism destination hinders the development of tourism sector in Satara
district, especially opinions of tourist at Kas is accepted.
Tourist Descriptive Statastics at AjinkyataraFollowing table presents descriptive statistics related with these three statements.Table 4.2.11.21Sample Tourist Opinion on Promotion at Ajinkyatara
One-Sample Statistics
Sr.Perception about promotionof Tourism
N Mean S.D.Std. ErrorMean
1. Advertisement playimportant role in tourism
34 3.94 .60 .10
2. Felt need of promotionalactivities
34 4.47 .79 .13
3. Lack of advertisement restricttourism development
34 4.41 .82 .14
Source: Compiled by Researcher
Samples discourse that advertisement plays important role in tourism, better need ofpromotional activities and lack of advertisement restricts tourism development.Samples highly argue with need of promotional activities and lack of advertisementrestricts tourism development since the mean score is 4.47 and 4.41 respectively.Second and third statements mean score is above 4 with little S.D.
Following table shows the one sample‘t’ test of three statements.Table 4.2.11.22Hypothesis Test of Ajinkyatara Sample Tourist Opinion on Promotion
One-Sample Test
Sr.Perception about promotion of
Tourism
Test Value = 3
t dfSig. (2-tailed)
MeanDifference
95% ConfidenceInterval of the
DifferenceLower Upper
1. Advertisement play importantrole in tourism
9.15 33 .00 .94 .73 1.15
2. Felt need of promotionalactivities
10.89 33 .00 1.47 1.19 1.74
3. Lack of advertisement restricttourism development
10.03 33 .00 1.41 1.12 1.70
Source: Compiled by Researcher
Data Analysis
Shivaji University, Kolhapur 317
The ‘t’ score of above three statements are 9.15, 10.89 and 10.03 respectively with a
‘P’ value 0.00, the test is significant. It is proves that promotion is important and it is
lacks in Satara. Hence, the null hypothesis is rejected. The hypothesis i.e. lack of
promotion of tourism destination hinders the development of tourism sector in Satara
district, especially opinions of tourist at Ajinkyatara is accepted.
The hypothesis is tested using sample opinions of Hoteliers
3 Hoteliers Opinion:
Following table presents descriptive statistics related with these three statements.
Table 4.2.11.23Sample Hoteliers’ Opinion on Promotion
One-Sample Statistics
Sr. Perception about promotion of Tourism N Mean S.D.Std.ErrorMean
1. Advertisement play important role in tourism 40 4.02 .70 .112. Felt need of promotional activities 40 4.27 .85 .133. Lack of advertisement restrict tourism
development40 3.95 .68 .11
Source: Compiled by Researcher
Sample hoteliers orate that advertisement plays important role in tourism and there is
key need of promotional activities. But samples quite reluctant with statement that
lack of advertisement restrict tourism development as mean score is less than 4. But
highly argue with advertisement play important role in tourism and need of
promotional activities as the mean score is 4.27. First two statements mean score is
above 4 with little S.D.
Data Analysis
Shivaji University, Kolhapur 318
Following table shows the one sample ‘t’ test of three statements.
Table 4.2.11.24Hypothesis Test of Sample Hoteliers’ Opinion on Promotion
One-Sample Test
Sr.
Perception aboutpromotion of Tourism
Test Value = 3
T df
Sig.(2-tailed)
MeanDifference
95% ConfidenceInterval of theDifferenceLower Upper
1. Advertisement playimportant role in tourism
9.29 39 .00 1.02 .80 1.25
2. Felt need of promotionalactivities
9.52 39 .00 1.27 1.00 1.54
3. Lack of advertisementrestrict tourismdevelopment
8.87 39 .00 .95 .73 1.17
The‘t’ score for statement first, second and third are 9.29, 9.52 and 8.87 respectively
with a ‘P’ value 0.00, the test is significant. It is evident that promotion is vital which
lacks in Satara. Hence, the null hypothesis is rejected. The hypothesis i.e. lack of
promotion of tourism destination hinders the development of tourism sector in Satara
district as opined by hoteliers.
The hypothesis is tested using sample opinions of Tour operators
4. Tour Operators’ Opinion:
Following table presents descriptive statistics related with these three statements.
Table 4.2.11.25Sample Tour Operators’ Opinion on Promotion
Sr.One-Sample StatisticsPerception about promotion ofTourism
N MeanStd.Deviation
Std. ErrorMean
1. Advertisement play importantrole in tourism
10 4.40 .51 .16
2. Felt need of promotionalactivities
10 4.80 .42 .13
3. Lack of advertisement restricttourism development
10 4.30 .94 .30
Source: Compiled by Researcher
Data Analysis
Shivaji University, Kolhapur 319
Sample tour operators opine that advertisement plays important role in tourism, tour
operators felt there is better need of promotional activities and lack of advertisement
restrict tourism development. Samples highly argue with need of promotion activities
since the mean score is 4.80. All these statements mean score is above 4 with little
S.D.
Following table shows the one sample ‘t’ test of three statements.
Table 4.2.11.26Hypothesis Test of Sample Tour Operators’ Opinion on Promotion
Sr.
One-Sample Test
Perception aboutpromotion of Tourism
Test Value = 3
Tdf
Sig.(2-tailed)
MeanDifference
95% ConfidenceInterval of theDifferenceLower Upper
1. Advertisement playimportant role intourism
8.57 9 .000 1.40 1.03 1.77
2. Felt need ofpromotional activities
13.50 9 .000 1.80 1.50 2.10
3. Lack of advertisementrestrict tourismdevelopment
4.33 9 .002 1.30 .62 1.98
Source: Compiled by Researcher
The‘t’ score for statement first, second and third are 8.57, 13.50 and 4.33 respectively.
It with a ‘P’ value 0.00, and 0.002 the test is significant. It is evident that promotion is
fundamental which lacks in Satara. Hence, the null hypothesis is rejected. The
hypothesis i.e. lack of promotion of tourism destination hinders the development of
tourism sector in Satara district, as opined by tour operators.
To conclude on hypothesis number 1, the null hypothesis is rejected and the
alternative hypothesis i.e. lack of promotion of tourist in Satara district is accepted.
Data Analysis
Shivaji University, Kolhapur 320
Hypothesis 2:
Second hypothesis set to test for the study is Availability of infrastructural facilitiesand tourism development is correlated.
For this hypothesis researcher has used Karl Pearson Correlation between averages of
satisfaction index towards infrastructural facilities with tourist arrival of recent year
2010-2011.
Following table depicts the destination wise tourists’ average satisfaction level and
previous year 2010-11 tourist arrival figures.
Table 4.2.11.27Average Satisfaction and Tourist Arrival at Satara
Sr. DestinationsAverageSatisfaction
Previous YearArrival#
1. Mahabaleshwar 3.31 16237652. Panchgani 3.38 13786553. Wai 2.83 *4. Pratapgarh 3.35 329555. Aundh 3.56 824746. Koyna 3.12 1159997. Sajjangarh 3.22 3000008. Thoseghar 2.82 270009. Kas 3.12 35000010. Ajinkya Tara 3.20 *Source: Compiled by Researcher# previous year refers to year 2011-12* Figures are not available
Table 4.2.11.27 presents the tourists average satisfaction level with 33 tourism
services and amenities and tourist arrival figure in respective destinations in Satara.
Tourist average satisfaction level is average that signifies the tourists are not strongly
satisfied with the available infrastructure. The tourist arrival figures are not also
similar as it starts from 27000 to 1623765 in a previous year. The highest tourist
arrival at Mahabaleshwar and followed by Panchgani but satisfaction level is average
as the mean score is less than 4.
Data Analysis
Shivaji University, Kolhapur 321
Following table presents the descriptive statistics of availability of infrastructuralfacilities of tourism development.
Table 4.2.11.28Descriptive Statistics of Tourism Development
Sr.Descriptive Statistics
Pariculars Mean S.D. N1. Average Satisfaction 3.23 .22 82. Previous year arrival 4.90 639199.68 8
Source: Compiled by Researcher
The total average samples tourist satisfaction mean score is lesser than 4 but tourist
previous year arrival mean score is more than 4 and more deviation finds in tourist
arrival in different destination. Therefore, it can infer that arrival and satisfaction does
not have any relation.
The following table depicts the Pearson correlation of aveage satisfaction mean with
previous year arrival mean.
Table 4.2.11.29Hypothesis Testing of Average Satisfaction and Previous Year Arrival with PearsonCorrelation
Sr.Correlations
AverageSatisfaction
Previous yeararrival
1. AverageSatisfaction
PearsonCorrelation
1 .28
Sig. (2-tailed) .49N 8 8
2. Previous yeararrival
PearsonCorrelation
.28 1
Sig. (2-tailed) .49N 8 8
Source: Compiled by Researcher
The above table shows Pearson correlation 0.28, with ‘P’ value 0.49, which is not
significant at 0.05 levels (2-tailed). Hence, it is inferred that there is no correlation
between average tourist satisfaction levels with tourist arrival figure of previous year.
Therefore, this test proves that availability of infrastructure facilities and tourism
Data Analysis
Shivaji University, Kolhapur 322
development are not correlated. Thus, the null hypothesis is accepted that
availability of infrastructure and tourism development is not correlated.
For this hypothesis researcher has also tested ‘Karl Pearson Correlation’ between
spending on infrastructural development and tourist arrival at respective tourist
destinations in Satara District since1999-2000 to 2010-11.
Following table presents the total amount of spending on infrastructure and tourist
arrival for 1999-2000 to 2010-2011.
Table 4.2.11.30Total Spending On Infrastructural Development with Tourist Arrival
Sr.Name ofDestination
Total spent on infrafor last 10 yearsAmount(in lakhs)
Last 10 yearstourist arrival
1. Mahabaleshwar 278.35 140000522. Panchgani * 103620843. Wai 13.86 *4. Pratapgarh 9.73 4660905. Aundh 74.72 2522406. Koyna 7.44 14039717. Sajjangarh 26.85 3000008. Thoseghar 39.8 818009. Kas 237.45 53828910. Ajinkya Tara * *
Source: Compiled by Researcher*figures not available
Table 4.2.11.30 reveals amount spent on infrastructure is neither uniform at various
destinations of Satara and nor tourist arrival. The highest tourist arrival are at
Mahabaleshwar (140000052) and Panchgani (10362084) compared to other
destinations of Satara. Expenditure on tourism development is equally higher at
Mahabaleshwar compared to other destinations. However, for Panchgani the
expenditure did not occurred through ‘C’ category tourism expenses at district level as
in the other destinations. Since the majority of properties are private and local
government, bear the expenses at local level, in the case of Panchgani.
Data Analysis
Shivaji University, Kolhapur 323
Following table presents the details of total spending for infrastructure of and their
tourist arrival since 1999-2000 to 2010-11.
Table 4.2.11.31Descriptive Statistics since 1999-2000 to 2010-11
Sr.Descriptive Statistics
Particulars Mean S.D. N1. Total Spending for Infrastructure of
1999-2000 to 2010-1196.33 113.24 7
2. Tourist Arrival 2.43 5.11 7Source: Compiled by Researcher
Above table, infer that two variables total spending and tourist arrival mean is not
matching the difference between means is very large with large standard deviation.
Following table shows pearon correlations between total spending for infrastructure
of with total tourist arrival from 1999-2000 to 2010-11.
Table 4.2.11.32Hypothesis Testing with Pearson Correlation
Source: Compiled by Researcher
The above test figures shows that Pearson correlation is 0.70, with ‘P’ value 0.81,
which is not significant at 0.05 levels (2-tailed). Thus, there is no correlation between
total spending at destination with previous tourist arrival figure. Hence, it is inferred
that null hypothesis is accepted as availability of infrastructure facilities and tourism
developments are not correlated.
Sr.
Correlations
Particulars
TotalSpending
forInfrastruct
ure ofLast years
TouristArrival
1. Total Spending forInfrastructure ofLast years
Pearson Correlation 1 .70Sig. (2-tailed) .081N 7 7
2.Tourist Arrival
Pearson Correlation .70 1Sig. (2-tailed) .08N 7 7
Data Analysis
Shivaji University, Kolhapur 324
To probe into the depth the hypothesis is tested destination-wise by using Karl
Pearson Correlation between spending on infrastructural development and tourist
arrival as follows.
The data are amount spend on infrastructural development year wise to the respective
destination and tourist arrival at that year was available with few destinations.
Researcher tested the data using Pearson Correlation to check its relation. The data in
desired form was available at destination, Thoseghar, Koyna and only one-year data
was available of fort Pratapgarh.
Following table shows the amount spent on infrastructural development at Thoseghar
and the tourist arrival figure of the destination.
Table 4.2.11.33Amount Spent and Tourist Arrival at Thoseghar
Sr. YearAmount Spent(inlakhs)
Tourist Arrival (innos.)
1. 1999-2000 5.08 6002. 2008-2009 5 85003. 2010-2011 12 18000
Source: Compiled by Researcher
Table 4.2.11.33 reveals that higher amount is spent during 2010-11 compared to
previous year 1999-2000 Rs. 5.08 and Rs. 5 lakhs during 2008-9. The tourist arrival
figure is also grown by 9500 during 2010-11.
Data Analysis
Shivaji University, Kolhapur 325
Following table shows the descriptive statistics of average amount spent and tourist
arrival at Thoseghar.
Table 4.2.11.34Descriptive Statistics of Thoseghar
Source: Compiled by Researcher
From table it is infer that there is mean difference between amount spent and tourist
arrival at Thoseghar with larger standard deviation.
To test the hypothesis researcher has used Pearson correlation method for amounts
spent on infrastructural development and tourist arrival at Thoseghar.
Following table presents the Pearson correlation test to check the significant relation
between infrastructural development and tourism development.
Table 4.2.11.35Hypothesis Testing of Infrastructural Development and Tourism at Thoseghar
Sr. CorrelationsParticulars Amount Spent Tourist Arrival
1. AmountSpent
Pearson Correlation 1 .89Sig. (2-tailed) .31N 3 3
2. TouristArrival
Pearson Correlation .89 1Sig. (2-tailed) .31N 3 3
Source: Compiled by Researcher
The Pearson correlation is 0.89 at 0.05 levels (2-tailed), with ‘P’ value 0.31 the test is
not significant. Therefore, there is no correlation between average satisfaction levels
of tourist with previous tourist arrival figure at Thoseghar. Thus, null hypothesis is
accepted i.e. infrastructural and tourism is not correlated.
Descriptive StatisticsSr. Funds Mean Std. Deviation N1. Amount Spent 7.36 4.019 32. Tourist Arrival 9033.33 8712.252 3
Data Analysis
Shivaji University, Kolhapur 326
Following table shows, the amount spent on infrastructural development at Koyna andthe tourist arrival figure of the destination.
Table 4.2.11.36Amount Spent and Tourist Arrival at Koyna
Sr. YearAmount spent(inLakhs)
Tourist( in Nos)
1. 2007-2008 7.41 138914
2. 2008-2009 3 126818
Source: Compiled by Researcher
Table 4.2.11.36 reveals that higher amount (Rs.7.41 lakhs) was spend at Koyna in
2007-8 as compared to Rs. 3 lakhs during 2008-9 and tourist arrival figure was more
by 12096 compared to 2008-9.
Following table shows the descriptive statistics of average amount spent and tourist
arrival at Koyna.
Table 4.2.11.37Descriptive Statistics of Koyna
Sr. Descriptive StatisticsParticulars Mean Std. Deviation N
1. Amount Spent 5.20 3.12 22. Tourist Arrival 1.33 8553.16 2
Source: Compiled by Researcher
Table 4.2.11.37 depicts that amount spent of infrastructural development at Koyna is
higher i.e. 5.20 than tourist arrival mean 1.33 with more S.D.
Data Analysis
Shivaji University, Kolhapur 327
Following table presents the Pearson correlation test to check the significant relation
between infrastructural development and tourism development.
Table 4.2.11.38Hypothesis Testing of Infrastructural Development and Tourism at Koyna
Sr.Correlations
ParicularsAmountSpent
TouristArrival
1. Amount Spent PearsonCorrelation
1 1.000**
Sig. (2-tailed) .N 2 2
2. Tourist Arrival PearsonCorrelation
1.000** 1
Sig. (2-tailed) .N 2 2
**. Correlation is significant at the 0.01 level (2-tailed).Source: Compiled by Researcher
The Pearson correlation is 1.00, with ‘P’ value 0.00, which is significant at 0.01 levels
(2-tailed). Thus, it proves that there is positive correlation between availability of
infrastructure facilities and tourism development. So the null hypothesis is rejected.
Hypothesis, Infrastructural development, and tourism are correlated.
Following table shows the amount spent on infrastructural development at Pratapgarh
and the tourist arrival figure of the destination.
Table 4.2.11.39Amount Spent and Tourist Arrival at Pratapgarh
Sr. YearAmount Spent(inlakhs)
TouristArrival(in Nos)
1. 2008-2009 9.73 34709
Source: Compiled by Researcher
Only single one-year tourism expenditure and tourist arrival present at Pratapgarh. So
it cannot be compared for calculation.
Data Analysis
Shivaji University, Kolhapur 328
Hypothesis 3:
The third hypothesis put to test was Government proposes planning to develop theplaces of tourist interest but the gap exists in planning and implementation, whichdeals to failure in attracting tourists.For this hypothesis researcher has tested the gap between amount sanctioned for thedevelopment of a tourist destination and the amount actually spent.The funds for tourism development have allocated to basic infrastructuraldevelopment and tourist infrastructural development in Satara district. The fundsbudgeted and actual spending are compared by using independent sample ‘t’ test.Following table reveals the funds spending on basic and tourist infrastructure inSatara during 1999-2010.
Table 4.2.11.40Amount Budgeted and Amount Spent on basic infrastructure and tourist infrastructuresince 1999-2010
(Figures in Rs. Lakhs)
Sr.
Basic and Tourist Infrastructure Amountbudgeted
AmountspentBasic Infrastructure
1. Construction of Road (wp)* 200.65 151.682. Drinking Water 5 53. Footpath or Pathway, Stair Case, Railing, Fixing
Paving Block, Entrance, Fencing (Wp)*122.8 103.91
4. Repair And Maintenance (wp)* 84.66 50.155. Surrounding Development, Landscaping or
Survey5.74 5.5
6. Toilets And Bathrooms (wp)* 16.99 16.4Total 435.84 332.64
Tourist Infrastructure10. Arrangement of SPV Solar System 3.25 2.9511. Canteen , Tiffin Shade 6.42 6.4212. Construction of Hall or Multipurpose Hall,
Entertainment Hall/Waiting Room (wp)*19.79 19.77
13. Construction of Smarak 13.7 12.7314. Garden For Children(wp)* 14.59 015. Office 8.21 8.2116. Parking Place 9.91 9.9117. Provision of Other Facility 5 2.0718. Rest House (wp)* 50 41.18
Total 130.87 103.24Grand Total 566.71 435.88
Source: (District Planning Department, Satara, translated and compiled byresearcher)*(wp) - work is progress
Data Analysis
Shivaji University, Kolhapur 329
Following table, preach the mean and standard deviation of budgeted amount and
amount spent for basic and tourist infrastructure in Satara.
Table 4.2.11.41Group Statistics of Amount Budgeted and Amount Spent
Group Statistics
Sr. Particulars Gap N Mean S.D.Std. Error
Mean1. Amount budgeted 1 15 37.78 56.68 14.632. Amount Spent 2 15 29.06 43.46 11.22
Source: Compiled by Researcher
Table 4.2.11.41 discourse the mean of budgeted amount and amount spent on basicand tourist infrastructure. Amount budgeted is higher than amount spent since themean score is 37.78 and 29.06 respectively with more S.D.
Following table discourse about the independent sample‘t’ test of amount budgetedand actual amount spent on infrastructure in Satara.
Table 4.2.11.42Hypothesis Test with Independent Sample ‘t’ Test
Source: Compiled by Researcher
The test is insignificant at 95% confidence interval with 28 df the t statistics is 0.47,with ‘P’ value 0.42 that is not significant at 0.05 level. The gap between amountsanctioned and the amount spent is negligible. Hence the null hypothesis is acceptedand the alternative hypothesis i.e. Government proposes planning to developmentthe places of tourist interest but the gap exists in planning and implementation thatdeals to failure in attracting tourists has rejected.
Independent Samples TestLevene's Test forEquality of Variances
t-test for Equality of Means
FSig
.t df
sig.(2-
tailed)
MeanDifference
Std.ErrorDifference
95% ConfidenceInterval of the
DifferenceLower Upper
AmountbudgetedandactualSpent
Equalvariancesassumed
.68 .42 .48 28 .640 8.72 18.44 -29.05 46.50
Equalvariancesnotassumed
.4726.23
.640 8.72 18.44 -29.17 46.61
Data Analysis
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Section: XII
4.2.12 Cluster Analysis:
Data of Entire Tourist Samples.
The data of entire samples run through cluster analysis using hierarchical method tofind out number of clusters.
Table 4.2.12.1Case Processing Summary entire data for cluster.
Cases
Valid Missing Total
N Percent N Percent N Percent
326 100.0 0 .0 326 100.0
a. Squared Euclidean Distance used
b. Average Linkage (Between Groups)
Table 4.2.12.2Agglomeration Schedule
Stage
Cluster Combined
Coefficients
Stage Cluster FirstAppears
Next StageCluster 1 Cluster 2 Cluster 1 Cluster 2
313 1 31 3.277 299 294 319
314 3 14 3.312 308 0 322
315 17 30 3.494 306 304 317
316 4 10 3.909 302 312 320
317 5 17 4.338 310 315 324
318 2 8 4.979 305 311 321
319 1 135 5.159 313 276 321
320 4 26 8.115 316 309 323
321 1 2 8.350 319 318 324
322 3 22 9.098 314 272 323
323 3 4 13.940 322 320 325
324 1 5 14.222 321 317 325
325 1 3 65.685 324 323 0
From above agglomeration table, it is evident that three or six clusters can be
extracted from the data. Since the gap between cluster seven and six is major and that
Data Analysis
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to between cluster 4 and 3 is major. Since the sample size is sufficient to devise six
clusters hence, the six-cluster alternative has been run through software.
The cluster analysis is used using K-means cluster. The results are as follows:
Convergence achieved in three iterations.
Table 4.2.12.3Final Cluster Centers Entire Data
Sr.Demographic Variables
Cluster
1 2 3 4 5 6
1 Gender 1 2 1 1 1 1
2 Age 5 6 3 4 4 3
3 Occupation 12 1 3 6 9 12
Above table shows final cluster centers of six clusters per variable. The narration of
each cluster is as follows:
Cluster One consists of male belongs to 45-55 age group and occupied as officer
executive middle and semi category.
Cluster Two – female belongs to 55 and above age group performing unskilled jobs.
Cluster Three - male belongs to 25-35 age group and occupation as petty traders.
Cluster Four- male belongs to 35-45 and occupation as industrialist with 1-9
employees.
Cluster Five- male belongs to 35-45 and occupation as clerical and salesmen.
Cluster Six- male belongs to 25-35 age group and occupation as Officer Executive’s
middle/semi.
Table 4.2.12.4Distances between Final Cluster Centers Entire Data
Cluster 1 2 3 4 5 6
1 10.355 8.787 6.026 2.959 2.229
2 10.355 3.064 4.657 7.893 11.480
3 8.787 3.064 2.802 5.944 9.422
4 6.026 4.657 2.802 3.306 6.891
5 2.959 7.893 5.944 3.306 3.596
6 2.229 11.480 9.422 6.891 3.596
Data Analysis
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Above table shows the distance between final cluster centers. The distance seems to
be significant. The distance between cluster 4 and 3, 5 and 1 and 6 and 1 has
proximity. Other clusters are at sufficient distance.
Table 4.2.12.5ANOVA for cluster entire data
Sr. Variable Cluster Error
F Sig.Mean Square df Mean Square df
1 Gender .869 5 .175 320 4.964 .000
2 Age group 52.240 5 .507 320 103.114 .000
3 Occupation 692.296 5 .681 320 1.016E3 .000
Above table depicts that F statistics is significant with all variables shows that there is
significant difference into the samples belongs to different clusters with respect to
variables used.
Table 4.2.12.6Number of Cases in each Cluster for entire data
Sr.ClusterNumber
Cases incluster
Percentage
1 1 83.000 25.46
2 2 12.000 3.68
3 3 27.000 8.28
4 4 22.000 6.75
5 5 87.000 26.69
6 6 95.000 29.14
Total 326.000 100
Above table shows, the numbers of cases fall in every cluster. Cluster number sixth is
the biggest carries 29.14% of total samples followed by cluster 5 carries 26.69% of
samples. Cluster number one carries 25.46 % of samples the smallest cluster is
number 2 carries 3.68 % of samples followed by cluster number 4 carries 6.75% of
samples.
Data Analysis
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Destination wise Cluster Analysis
Cluster analysis has been attempted for the tourist destinations independently to find
out segments destination wise.
Table 4.2.12.7Case Processing Summary Destinationwise
Destinationcode
Cases
Valid Missing Total
N Percent N Percent N Percent
1 30 100.0 0 .0 30 100.0
2 35 100.0 0 .0 35 100.0
3 37 100.0 0 .0 37 100.0
4 30 100.0 0 .0 30 100.0
5 30 100.0 0 .0 30 100.0
6 37 100.0 0 .0 37 100.0
7 30 100.0 0 .0 30 100.0
8 33 100.0 0 .0 33 100.0
9 30 100.0 0 .0 30 100.0
10 34 100.0 0 .0 34 100.0
a. Squared Euclidean Distance used
b. Average Linkage (Between Groups)
Above table depicts case summary of every destination. The entire samples were
process for cluster analysis. The minimum number of samples of 30 found at
destination Mahabaleshwar, Pratapgarh, Aundh, Sajjangarh and Kas. The maximum
numbers of samples found with destination Wai, Koyna Panchgani and Thoseghar.
The samples are processed through hierarchical cluster to find out number of clusters
the agglomeration schedule is as follows:
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Table 4.2.12.8Agglomeration Schedule DestinationWise
Destination StageCluster Combined
CoefficientsStage Cluster First
Appears NextStage
Cluster 1 Cluster 2 Cluster 1 Cluster 2
Mah
abal
esw
ar
1 15 29 .000 0 0 7
18 5 28 2.000 0 0 20
19 3 14 2.400 14 0 25
20 5 17 3.000 18 10 28
21 4 10 3.500 13 0 24
22 1 2 3.583 17 15 23
23 1 16 6.100 22 0 26
24 4 26 6.833 21 11 27
25 3 22 9.000 19 0 27
26 1 8 9.727 23 6 28
27 3 4 13.857 25 24 29
28 1 5 15.143 26 20 29
29 1 3 70.759 28 27 0
Pan
chag
ani
1 46 63 .000 0 0 14
27 36 40 1.667 24 20 30
28 34 38 2.350 22 21 31
29 32 61 3.500 23 0 33
30 36 45 4.208 27 26 32
31 31 34 4.472 18 28 32
32 31 36 7.021 31 30 33
33 31 32 16.100 32 29 34
34 31 33 53.690 33 25 0
Wai
1 94 102 .000 0 0 17
29 67 73 2.000 9 0 30
30 67 74 4.000 29 22 33
31 66 80 4.500 28 26 33
32 69 72 6.200 18 23 34
33 66 67 9.143 31 30 35
34 68 69 9.411 25 32 36
35 66 70 23.846 33 6 36
36 66 68 46.506 35 34 0
Pra
tapg
arh
1 105 131 .000 0 0 16
22 105 111 2.810 16 18 28
23 103 125 4.250 21 0 25
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24 106 116 4.500 17 19 26
25 103 114 5.760 23 20 27
26 106 110 9.000 24 13 29
27 103 104 11.200 25 0 28
28 103 105 15.845 27 22 29
29 103 106 42.630 28 26 0
Aun
dh
1 159 162 .000 0 0 14
22 133 134 1.500 21 20 26
23 139 143 2.375 16 13 24
24 137 139 3.500 18 23 25
25 135 137 5.300 19 24 26
26 133 135 9.667 22 25 27
27 133 136 14.812 26 15 29
28 138 142 26.500 17 14 29
29 133 138 96.100 27 28 0
Koy
ana
1 196 197 .000 0 0 2
29 166 173 2.000 0 0 30
30 166 171 3.000 29 0 34
31 165 179 3.400 26 0 33
32 163 164 4.000 27 28 35
33 165 169 6.500 31 25 35
34 166 186 9.167 30 19 36
35 163 165 10.825 32 33 36
36 163 166 51.012 35 34 0
Saj
jang
arh
1 228 229 .000 0 0 2
19 223 224 2.000 0 0 22
20 204 205 2.167 11 14 21
21 201 204 3.200 16 20 23
22 217 223 3.500 12 19 24
23 201 222 6.312 21 10 26
24 200 217 7.556 18 22 28
25 212 214 8.000 0 0 27
26 201 211 8.750 23 13 28
27 203 212 9.000 17 25 29
28 200 201 18.132 24 26 29
29 200 203 73.632 28 27 0
Tho seg
har 1 261 262 .000 0 0 2
25 244 246 1.500 22 0 29
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26 238 256 2.000 14 0 29
27 233 248 2.000 18 0 32
28 230 253 2.182 24 7 30
29 238 244 2.556 26 25 30
30 230 238 4.048 28 29 31
31 230 241 6.826 30 23 32
32 230 233 8.456 31 27 0
Kas
1 266 292 .000 0 0 20
20 266 267 1.500 1 13 24
21 263 269 1.667 11 19 23
22 271 282 2.150 15 14 25
23 263 265 2.429 21 8 28
24 264 266 3.250 18 20 26
25 271 277 3.278 22 12 27
26 264 268 5.333 24 17 27
27 264 271 6.261 26 25 28
28 263 264 12.521 23 27 29
29 263 275 51.966 28 0 0
Aji
nkya
tara
1 321 326 .000 0 0 20
27 294 310 2.100 25 22 30
28 295 297 2.500 24 0 32
29 293 298 2.861 21 26 30
30 293 294 4.143 29 27 31
31 293 300 10.210 30 23 32
32 293 295 14.167 31 28 33
33 293 296 67.364 32 0 0
From above agglomeration table, it is evident that from destination code
1(Mahabaleshwar) 6 to 7 clusters can be extracted from the data. Whereas destination
code 2(Panchgani) 2 clusers, destination code 3(Wai) 4 clusters, destination code
4(Pratapgarh) 4 clusters, destination code 5(Aundh) 3 clusters, destination code 6
(Koyna) 4 clusters, destination code 7(Sajjangarh) 4 clusters, destination code 8
(Thoseghar) 3 clusters, destination code 9 (Kas) clusters 2, destination code 10
(Ajinkyatara) 3 clusters extracted from the data
The cluster analysis used by using K-means cluster. The results are as follows:
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Destination Mahabaleshwar
Table 4.2.12.9Final Cluster Centers for Mahabaleshwar
Sr. Variable Cluster
1 2 3 4 5 6 7
1 Gender 2 1 1 1 1 2 1
2 Age group 6 4 3 6 4 2 4
3 Occupation 1 5 2 4 9 13 12
Above table shows final cluster centers of seven clusters per variable.
Cluster One- consists of female belongs to 55 & above age group and occupied as
unskilled.
Cluster Two – male belongs to 35-45 age group and occupied industrialist and
businessmen.
Cluster Three – male belongs to 25-35 age group and occupation skilled workers.
Cluster Four- male belongs to 55 & above and occupation as shop owners.
Cluster Five- male belongs to 45-55 and occupation as clerical and salesmen.
Cluster Six- female belongs to 15-25 age group and occupation as housewife.
Cluster Seven- male belongs to 35-45 age group and occupation as officer/executive
middle/semi.
Table 4.2.12. 10Distances between Final Cluster Centers for Mahabaleshwar
Cluster 1 2 3 4 5 6 7
1 4.738 2.915 3.640 8.073 12.649 10.790
2 4.738 3.189 2.386 3.880 8.233 6.564
3 2.915 3.189 3.775 7.051 11.277 9.746
4 3.640 2.386 3.775 4.717 9.447 7.334
5 8.073 3.880 7.051 4.717 4.743 2.748
6 12.649 8.233 11.277 9.447 4.743 2.662
7 10.790 6.564 9.746 7.334 2.748 2.662
Above table shows the distance between final cluster centers. The distance seems to
be significant. The distance between cluster 4 and 3 has proximity.
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Table 4.2.12. 11ANOVA for Mahabalwshwar
Sr. Variable Cluster Error
F Sig.Mean Square df Mean Square df
1 Gender .533 6 .094 23 5.662 .001
2 Age Group 4.439 6 .558 23 7.955 .000
3 Occupation 86.580 6 .452 23 191.679 .000
Above table depicts that ‘F’ statistics is significant with all variables shows that there
is significant difference into the samples belongs to different clusters with respect to
variables used.
Table 4.2.12.12Number of Cases in each Cluster at Mahabalwshwar
Sr.ClusterNumber
Cases incluster
Percentage
1 1 1 3.332 2 3 10.003 3 6 20.004 4 2 6.675 5 6 20.006 6 3 10.007 7 9 30.00
Total 30 100
Above table shows, the number of cases falls in every cluster. Cluster number seventh
is the biggest carries 30 % of total samples followed by cluster 3 and 5 each carries
20% of samples. Smallest cluster is number 1 carries 3.33 % of samples.
Destination Panchgani
Table 4.2.12.13Final Cluster Centers for Panchagani
Sr. Variable Cluster
1 2
1 Gender 1 1
2 Age group 4 4
3 Occupation 12 6
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Above table shows final cluster centers of two clusters per variable.
Cluster One- consist of male belongs to 35-45 age group and occupied as officer
/executive middle/semi.
Cluster Two – male belongs to 35-45 age group and occupied industrialist and
businessmen with 1-9 employees.
Table 4.2.12. 14Distances between Final Cluster Centers for Panchagani
Cluster 1 2
1 5.994
2 5.994
Above table shows the distance between final cluster centers.
Table 4.2.12. 15ANOVA for Panchagani
Sr. Variable Cluster Error
F Sig.Mean Square df Mean Square df
1 Gender .643 1 .209 33 3.075 .089
2 Age group .560 1 .759 33 .738 .396
3 Occupation 255.431 1 2.228 33 114.621 .000
Above table depicts that ‘F’ statistics is significant with only one variable and not
with other two variables and shows that there is significant difference into the samples
belongs to different clusters with respect to occupation and not with gender and age.
Table 4.2.12.16Number of Cases in each Cluster at Panchagani
Sr. ClusterNumber
Cases incluster
Percentage
1 1 25 71.43
2 2 10 28.57
Total 35 100
Above table shows, the number of cases falls in every cluster. Cluster number first is
the biggest carries 71.43 % of total samples. Smallest cluster is number 2 carries
28.57 % of samples.
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Destination Wai
Table 4.2.12.17Final Cluster Centers for Wai
Sr. Variable Cluster
1 2 3 4
1 Gender 1 1 1 1
2 Age group 4 4 3 5
3 Occupation 7 4 12 10
Above table shows final cluster centers of four clusters per variable.
Cluster One- consist of male belongs to 35-45 age group and occupied as
industrialist/businessmen with 10+ employees.
Cluster Two – male belongs to 35-45 age group and occupied shop owners.
Cluster Three- male belongs to 25-35 age group and officer/executive middle/semi.
Cluster Four –male belongs to 45-55 age group and supervisory level occupation.
Table 4.2.12.18Distances between Final Cluster Centers for Wai
Cluster 1 2 3 4
1 3.452 5.478 3.540
2 3.452 8.893 6.906
3 5.478 8.893 2.831
4 3.540 6.906 2.831
Above table shows the distance between final cluster centers.Table 4.2.12.19ANOVA for Wai
Sr. Variable Cluster Error
F Sig.Mean Square df Mean Square df
1 Gender .228 3 .151 33 1.504 .232
2 Age group 6.272 3 .730 33 8.586 .000
3 Occupation 135.120 3 .779 33 173.350 .000
Above table depicts that ‘F’ statistics is significant with age group and occupation
variable and not with gender since the convenient sampling technique. It shows that
Data Analysis
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there is significant difference into the samples belongs to different clusters with
respect to age group and occupation and not with gender.
Table 4.2.12.20Number of Cases in each Cluster at Wai
Sr. ClusterNumber
Cases incluster
Percentage
1 1 9 24.322 2 6 16.223 3 16 43.244 4 6 16.22
Total 37 100
Above table shows, the number of cases falls in every cluster. Cluster number three is
the biggest carries 43.24 % of total samples.
Destination Pratapgarh
Table 4.2.12.21Final Cluster Centers for Pratapgarh
Sr. Variable Cluster
1 2 3 4
1 Gender 1 1 1 1
2 Age group 3 4 3 4
3 Occupation 3 12 8 6
Above table shows final cluster centers of four clusters per variable.
Cluster One- consist of male belongs to 25-35 age group and occupied as petty
traders.
Cluster Two – male belongs to 35-45 age group and occupied officer/executive
middle/semi.
Cluster Three- male belongs to 25-35 age group and self employed professionals.
Cluster Four –male belongs to 35-45 age group and industrialist with 1 to 9
employees.
Data Analysis
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Table 4.2.12.22Distances between Final Cluster Centers for Pratapgarh
Cluster 1 2 3 4
1 9.142 5.510 2.693
2 9.142 3.642 6.628
3 5.510 3.642 3.073
4 2.693 6.628 3.073
Above table shows the distance between final cluster centers. Distance is seems to be
identical.
Table 4.2.12.23ANOVA for Pratapgarh
Sr. Variable Cluster Error
F Sig.Mean Square df Mean Square df
1 Gender .233 3 .077 26 3.033 .047
2 Age group .933 3 .718 26 1.300 .296
3 Occupation 100.993 3 .726 26 139.013 .000
Above table depicts that ‘F’ statistics is not significant with age group and gender
variable and only significant with occupation since the convenient sampling
technique. It shows that there is significant difference into the samples belongs to
different clusters with respect to d occupation and not with gender and age group.
Table 4.2.12.24Number of Cases in each Cluster at Pratapgarh
Sr. ClusterNumber
Cases incluster
Percentage
1 1 5 16.672 2 9 30.003 3 12 40.004 4 4 13.33
Total 30 100.00
Above table shows the number of cases falls in every cluster. Cluster number three is
the biggest carries 40 % of total samples.
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Destination Aundh
Table 4.2.12.25Final Cluster Centers for Aundh
Sr. Variable Cluster
1 2 3
1 Gender 1 2 2
2 Age group 4 4 6
3 Occupation 12 8 1
Above table shows final cluster centers of three clusters per variable.
Cluster One consists of male belongs to 35-45 age group and occupied as
officer/executive.
Cluster Two – female belongs to 35-45 age group and self-employed professionals.
Cluster Three- female belongs to 55 & above age group and unskilled.
Table 4.2.12.26Distances between Final Cluster Centers for Aundh
Cluster 1 2 3
1 3.542 11.190
2 3.542 7.653
3 11.190 7.653
Above table shows distance between each cluster with final cluster. The distance is
identical.
Table 4.2.12.27ANOVA for Aundh
Sr. Variable Cluster Error
F Sig.Mean Square df Mean Square df
1 Gender .555 2 .235 27 2.356 .114
2 Age group 10.333 2 1.407 27 7.342 .003
3 Occupation 308.733 2 .963 27 320.608 .000
Above table depicts that ‘F’ statistics is significant with age group and occupation
variable and not significant with gender since the convenient sampling technique. It
shows that there is significant difference into the samples belongs to different clusters
with respect to age group and occupation.
Data Analysis
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Table 4.2.12.28Number of Cases in each Cluster at Aundh
Sr. ClusterNumber
Cases incluster
Percentage
1 1 14 46.662 2 8 26.673 3 8 26.67
Total 30 100.00
Above table shows, the number of cases falls in every cluster. Cluster number one is
the biggest carries 40.66 % of total samples.
Destination KoynaTable 4.2.12.29Final Cluster Centers for Koyna
Sr. Variable Cluster
1 2 3 4
1 Gender 1 1 1 1
2 Age group 2 3 4 4
3 Occupation 13 9 11 4
Above table shows final cluster centers of four clusters per variable.
Cluster One -consist of male belongs to 15-25 age group and occupied as student.
Cluster Two – male belongs to 25-35 age group and clerical/salesmen.
Cluster Three- male belongs to 35-45 age group and officer/executives.
Cluster Four- male belongs to 35-45 age group and shop owner.
Table 4.2.12.30Distances between Final Cluster Centers for Koyna
Cluster 1 2 3 4
1 3.947 2.138 9.153
2 3.947 2.299 5.235
3 2.138 2.299 7.459
4 9.153 5.235 7.459
Above table shows distance between each cluster with final cluster.
Data Analysis
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Table 4.2.12.31ANOVA for Koyna
Sr. Variable Cluster Error
F Sig.Mean Square df Mean Square df
1 Gender .140 3 .118 33 1.187 .330
2 Age group 3.411 3 .381 33 8.948 .000
3 Occupation 88.381 3 .640 33 138.048 .000Above table depicts that ‘F’ statistics is significant with age group and occupation
variable and not significant with gender since the convenient sampling technique. It
shows that there is significant difference into the samples belongs to different clusters
with respect to age group and occupation.
Table 4.2.12.32Number of Cases in each Cluster at Koyna
Sr ClusterNumber
Cases incluster
Percentage
1 1 6 16.222 2 15 40.543 3 11 29.734 4 5 13.51
Total 37 100.00Above table shows, the number of cases falls in every cluster. Cluster number 2 is the
biggest carries 40.66 % of total samples.
Destination Sajjangarh
Table 4.2.12.33Final Cluster Centers for Sajjangarh
Sr. Variable Cluster
1 2 3 4
1 Gender 1 1 2 1
2 Age group 4 2 5 4
3 Occupation 9 12 12 3
Above table shows final cluster centers of four clusters per variable.
Cluster One - consists of male belongs to 35-45 age group and occupied as
clerical/salesmen.
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Cluster Two – male belongs to 15-25 age group and officer/executive middle/semi.
Cluster Three- consists female belongs to 45-55 age group with officer/executive
middle/semi.
Cluster Four- belongs to male and the age group 35-45 with petty traders’ occupation.
Table 4.2.12.34Distances between Final Cluster Centers for Sajjangarh
Cluster 1 2 3 4
1 4.102 3.614 5.764
2 4.102 2.418 9.760
3 3.614 2.418 9.257
4 5.764 9.760 9.257
Above depicts distance between each cluster with final cluster centers.
Table 4.2.12.35ANOVA for Sajjangarh
Sr. Variable Cluster Error
F Sig.Mean Square df Mean Square df
1 Gender .561 3 .192 26 2.926 .053
2 Age group 7.325 3 .955 26 7.671 .001
3 Occupation 116.243 3 .874 26 132.928 .000
Above table shows that ‘F’ statistics is significant with age group and occupation
variable and not significant with gender. It shows that there is significant difference
into the samples belongs to different clusters with respect to age group and
occupation.
Table 4.2.12.36Number of Cases in each Cluster at Sajjangarh
Sr. ClusterNumber
Cases incluster
Percentage
1 1 9 30.002 2 7 23.333 3 9 30.004 4 5 16.67
Total 30 100.00
Above table depicts that cluster one and three carries highest samples with 30% each
of total samples. Smallest cluster is 4 which carries 16.67% of samples.
Data Analysis
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Destination Thoseghar
Table 4.2.12.37Final Cluster Centers for Thoseghar
Sr. Variable Cluster
1 2 3
1 Gender 1 1 1
2 Age group 3 2 4
3 Occupation 10 13 12
Above table shows final cluster centers of three clusters per variable.
Cluster One- consist of male belongs to 25-35 age group and occupied as supervisory
level.
Cluster Two – male belongs to 15-25 age group and students.
Cluster Three- male belong to35-45age group with officer/executive middle/semi.
Table 4.2.12.38Distances between Final Cluster Centers for Thoseghar
Cluster 1 2 3
1 2.753 1.963
2 2.753 2.616
3 1.963 2.616
Above table depicts that distance between each cluster with final cluster centre.
Table 4.2.12.39ANOVA for Thoseghar
Sr. Variable Cluster Error
F Sig.Mean Square df Mean Square df
1 Gender .079 2 .112 30 .706 .502
2 Age group 10.594 2 .312 30 33.966 .000
3 Occupation 18.007 2 .377 30 47.724 .000
Above table shows that ‘F’ statistics is significant with age group and occupation
variable and not significant with gender. It shows that there is significant difference
into the samples belongs to different clusters with respect to age group and
occupation.
Data Analysis
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Table 4.2.12.40Number of Cases in each Cluster at Thoseghar
Sr ClusterNumber
Cases incluster
Percentage
1 1 18 48.652 2 7 18.923 3 8 21.62
Total 37 100.00Above table depicts that cluster one carries highest percentage of membership i.e.
48.65% of total samples. In addition, cluster 2 carries lowest i.e. 18.92%.
Destination Kas
Table 4.2.12.41Final Cluster Centers for Kas
Sr. Variable Cluster
1 2
1 Gender 1 1
2 Age group 4 4
3 Occupation 8 11
Above table shows final cluster centers of two clusters per variable.
Cluster One -consists of male belongs to 35-45 age group and occupied as self-
employed professionals.
Cluster Two – male belongs to 35-45 age group and occupied as officer/executive
juniors.
Table 4.2.12.42Distances between Final Cluster Centers for Kas
Cluster 1 2
1 3.529
2 3.529
Above table depicts the distance between final clusters with corresponding cluster.
Data Analysis
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Table 4.2.12.43ANOVA for Kas
Sr. Variable Cluster Error
F Sig.Mean Square df Mean Square df
1 Gender .050 1 .223 28 .224 .640
2 Age group .022 1 .605 28 .037 .849
3 Occupation 89.606 1 1.596 28 56.136 .000
Above table shows that ‘F’ statistics is significant with occupation variable and not
significant with gender and age group. It shows that there is significant difference into
the samples belongs to different clusters with respect to occupation and not gender
and age group.
Table 4.2.12.44Number of Cases in each Cluster at Kas
Sr ClusterNumber
Cases incluster
Percentage
1 1 12 402 2 18 60
Total 30 100
Above table depicts that cluster second carries higher sample cases i.e. 60% whereas
cluster one carries only 40%.
Destination Ajinkyatara
Table 4.2.12.45Final Cluster Centers for Ajinkyatara
Sr. Variable Cluster
1 2 3
1 Gender 1 1 1
2 Age group 2 3 5
3 Occupation 13 4 11
Above table shows final cluster centers of three clusters per variable.
Cluster One -consist of male belongs to 15-25 age group students.
Cluster Two – male belongs to 25-35 age group and occupied as shop owners.
Data Analysis
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Table 4.2.12. 46Distances between Final Cluster Centers for Ajinkyatara
Cluster 1 2 3
1 9.064 3.023
2 9.064 7.654
3 3.023 7.654
Above table shows distance between each cluster with final cluster centre.
Table 4.2.12.47ANOVA for Ajinkyatara
Sr. Variable Cluster Error
F Sig.Mean Square df Mean Square df
1 Gender .112 2 .220 31 .508 .607
2 Age group 24.040 2 .628 31 38.261 .000
3 Occupation 38.660 2 .895 31 43.204 .000
Above table shows that ‘F’ statistics is significant with age group and occupation
variable and not significant with gender. It shows that there is significant difference
into the samples belongs to different clusters with respect to age group and occupation
and not with gender.
Table 4.2.12.48Number of Cases in each Cluster at Ajinkyatara
Sr. ClusterNumber
Cases incluster
Percentage
1 1 10 29.412 2 1 2.943 3 23 67.65
Total 34 100
Above table clears that cluster three carries highest membership samples i.e. 67.65%
and smallest cluster is two who carries 2.94% of membership cases.
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Following table shows the cluster of highest sample tourist in each destination.
Table 4.2.12.49Summary of Destinationwise Major Cluster
Sr.Name of
Destination
Numberof
clusters
Demographic Background
GenderAge
groupOccupation
1 Mahabaleshwar 7 1(male) 4(35-45)12(Officer/Executive
Middle/Semi
2 Panchghani 2 1(male) 4(35-45)12(Officer/Executive
Middle/Semi
3 Wai 4 1(male) 3(25-35)12(Officer/Executive
Middle/Semi
4 Pratapgarh 4 1(male) 3(25-35)8(Self Employed
professionals)
5 Aundh 3 1(male) 4(35-45)12(Officer/Executive
Middle/Semi6 Koyna 4 1(male) 3(25-35) 9( Clerical/Salesmen)
7 Sajjangarh 41 & 2
(male&female)
4/5(35-45)/(45-
55)
9/12(Officer/ExecutiveMiddle/Semi
8 Thoseghar 3 1(male) 3(25-35) 10(Supervisory level)9 Kas 2 1(male) 4(35-45) 11(Officer/Executive/Junior)10 Ajinkyatar 3 1(male) 5(45-55) 11(Officer/Executive/Junior)
The clusters derived from entire samples have used further to assess samples opinions
cluster wise on tourism product that attract tourists in Satara district. Respondents’
opinion on tourism products have assessed on five-point scale that 1 for not at all
attracts, 2 for not attracts, 3 for neither attracts nor distracts, 4 for attracts and 5 for
highly attracts. Each tourism product analyzed independently with entire cluster group
i.e. 6 and presented in following table.
Product Perception on Tourism Product Attraction
The total samples processed with 15-tourism products viz. Adventure, Flora, Fauna,
Waterfall, Ghats, Hill stations, Lake/Reservoir, Scenery/Beauty, Valleys, Pilgrimage,
Temples, Museum, Historical Monuments, Forts, and Windmills. The summery of
case processing is as follows.
Data Analysis
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Table 4.2.12.50Analysis of Tourism Product Attraction
Sr.Name of Tourism
Products
CasesValid Missing Total
N Percent N Percent N1 Adventure 200 61.3% 126 38.7% 3262 Flora 226 69.3% 100 30.7% 3263 Fauna 193 59.2% 133 40.8% 3264 Waterfall 243 74.5% 83 25.5% 3265 Ghats 241 73.9% 85 26.1% 3266 Hill Stations 319 97.9% 7 2.1% 3267 Lake/ Reservoir 271 83.1% 55 16.9% 3268 Scenery/Beauty 283 86.8% 43 13.2% 3269 Valleys 252 77.3% 74 22.7% 32610 Pilgrimage 214 65.6% 112 34.4% 32611 Temples 230 70.6% 96 29.4% 32612 Museum 198 60.7% 128 39.3% 32613 Historical Monuments 224 68.7% 102 31.3% 32614 Forts 255 78.2% 71 21.8% 32615 Windmills 193 59.2% 133 40.8% 326
The entire samples have taken for study; have not marked their opinion towards all 15tourism products since the opinions taken on perceptions of sample tourist. Hence, themissing frequency found in above table. The maximum opinions i.e. 97.9% havefound for Hill stations and least i.e. 59.2% for Fauna and Windmills.
Adventure Tourism Product
Following table shows opinion of total samples on attraction of adventure tourism inrespective cluster in Satara district.
Table 4.2.12.51Attraction of Adventure Tourism Product
Sr. OpinionClusters
Total1 2 3 4 5 6
f % f % f % f % f % f %1 Not at all attracts 1 2.22 0 0.00 1 9.49 1 7.69 0 0.00 0 0.00 32 Not attracts 1 2.22 1 10.00 0 0.00 1 7.69 4 6.90 2 3.17 93 Neither attracts
nor distracts19 42.22 8 80.00 2 18.18 7 53.85 27 46.55 18 28.57 81
4 Attracts 22 48.89 1 10.00 8 72.33 2 15.38 21 36.21 30 47.62 845 Highly attracts 2 4.44 0 0.00 0 0.00 2 15.38 6 10.34 13 20.63 23
Total 45 100 10 100 11 100 13 100 58 100 63 100 200Source: Field Data
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Table 4.2.12.51 depict that ‘Adventure’ of Satara attracts cluster 3rd as it carries
highest i.e.72.33% and of having demographic profile as ‘male’ of ‘25-35’ age group
which belongs to ‘petty traders’ as an occupation. Followed by cluster 6th this carries
68.25% consist male of similar age group differ in occupation as ‘officer executive’s
middle/semi’. However second cluster has least percentage i.e. 10% which attract
‘Adventure’ of Satara who are female of age group ‘55 and above’ and belonging to
‘unskilled jobs’ (housewife). Young male tourist of age group ‘25-35’ are more
attracted to ‘Adventure’ of Satara.
Flora Tourism Product
Following table shows opinion of total samples on attraction of Flora in respective
cluster in Satara district.
Table 4.2.12.52Attraction of Flora Tourism Product
Sr OpinionClusters
Total1 2 3 4 5 6f % f %f % f % f % f %
1 Not attracts 1 1.64 1 10 1 8.33 0 0 2 3.13 4 5.97 92 Neither
attracts nordistracts
11 18.03 8 80 2 16.67 4 33.33 16 25.00 8 11.94 49
3 Attracts 38 62.30 0 0 8 66.67 6 50.00 37 57.81 49 73.13 1384 Highly
attracts11 18.03 1 10 1 8.33 2 16.67 9 14.06 6 8.96 30
Total 61 100 10 100 12 100 12 100 64 100 67 100 226
Table 4.2.12.52 shows that ‘flora’ of Satara attracts almost all clusters since the
highest percentage i.e. more than 70% samples carries in all clusters. However, the
distinct cluster second shows least percentage i.e. 10% since they are ‘female’ belongs
to ‘55 and above’ age group of ‘unskilled job’. It infers that ‘Flora’ of Satara attracts
all tourists but ‘female’ belongs to ‘55 and above’ age group of ‘unskilled job’ did not
attract.
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Fauna Tourism Product
Following table shows opinion of total samples on attraction of Fauna in respective
cluster in Satara district.
Table 4.2.12.53Attraction of Fauna Tourism Product
Sr. Opinion
Clusters
Total1 2 3 4 5 6
f % f % f % f % f % f %1 Not at all attracts 1 2.33 0 0 0 0 0 0 0 0 0 0 12 Not attracts 0 0.00 1 10 1 10 1 8.33 1 1.72 3 5 73 Neither attracts
nor distracts13 30.23 9 90 1 10 5 41.67 20 34.48 18 30 66
4 Attracts 24 55.81 0 0 6 60 3 25.00 30 51.72 27 45 905 Highly attracts 5 11.63 0 0 2 20 3 25.00 7 12.07 12 20 29
Total 43 100 10 100 10 100 12 100 58 100 60 100 193
Table 4.2.12.53 shows that ‘fauna’ of Satara highly attracts third clusters followed by
first, fifth and sixth respectively but not to second cluster. It also shows that cluster 4
carries only 50% samples who perceive the ‘fauna’ attracts them and they are ‘males’
of age group ‘35-45’ and having occupation as ‘industrialist with 1-9 employees’.
The cluster 3rd shows higher attraction it is ‘male’ of age group ‘25-35’ belong to
‘petty traders’ as an occupation. Moreover, cluster number 2nd is distinct of ‘female’
of ‘55 and above’ age group of ‘unskilled job’. It concludes that Fauna highly attracts
‘petty traders’ of ‘25-35’ age group ‘male’ category followed by ‘officer/ executive
middle/semi’ and ‘clerical & salesmen ‘.
Data Analysis
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Waterfall Tourism Product
Following table shows opinion of total samples on attraction of ‘Waterfall’ inrespective cluster in Satara district.
Table 4.2.12.54Attraction of Waterfall Tourism Product
Sr. OpinionClusters
Total1 2 3 4 5 6f % f % f % f % f % f %
1 Not attracts 0 0 0 0 0 0 0 0 1 1.49 1 1.30 22 Neither
attracts nordistracts
11 17.46 9 90 1 8.33 2 14.29 12 17.91 3 3.90 38
3 Attracts 41 65.08 1 10 8 66.67 7 50.00 40 59.70 44 57.14 1414 Highly
attracts11 17.46 0 0 3 25.00 5 35.71 14 20.90 29 37.66 62
Total 63 100 10 100 12 100 14 100 67 100 77 100 243
Table 4.2.12.54 shows that ‘Waterfall’ of Satara highly attracts all clusters as thepercentage is above 70% except cluster number 2nd of which only 10% tourist’waterfall’ attracts. It infers that ‘waterfall’ of Satara attracts all tourists but ‘female’ of‘55 and above’ age group performing ‘unskilled job’ is exception to it.
Ghats Tourism Product
Following table shows opinion of respective cluster in Satara district in respect to
‘Ghats’ attraction by tourist samples.
Table 4.2.12.55Attraction of Ghats Tourism Product
Sr. OpinionClusters
Total1 2 3 4 5 6f % f % f % f % f % f %
1 Not at all attracts 0 0 0 0 0 0 0 0 1 1.41 0 0 12 Not attracts 1 2 0 0 1 6.67 1 6.25 1 1.41 1 1.28 53 Neither attracts
nor distracts21 42 8 72.73 3 20.00 3 18.75 19 26.76 17 21.79 71
4 Attracts 21 42 1 9.09 7 46.67 6 37.5 38 53.52 38 48.72 1115 Highly attracts 7 14 2 18.18 4 26.67 6 37.5 12 16.90 22 28.21 53
Total 50 100 11 100 15 100 16 100 71 100 78 100 241
Table 4.2.12.55 shows that ‘Ghats’ of Satara attracts to clusters viz. 6,5,4,3 and 1, but
among them cluster one it attracts comparatively less since the percentage of this
cluster one is 56 and rest of cluster percentage is above 70%. However, cluster
Data Analysis
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number 2nd carries less percentage i.e. 27.27 since the cluster unique. It infers that
‘Ghats’ of Satara attracts young category of ‘male’ tourists irrespective of their
occupation.
Hill Stations Tourism Product
Following table shows opinion of total samples on attraction of ‘Hill stations’ in
respective cluster in Satara district.
Table 4.2.12.56Attraction of ‘Hill stations’ Tourism Product
Sr OpinionClusters
Total1 2 3 4 5 6f % f % f % f % f % f %
1 Not at all attracts 0 0 0 0 0 0 0 0 0 0 1 1.09 12 Not attracts 1 1.23 0 0 1 3.70 1 4.55 2 2.33 0 0.00 53 Neither attracts
nor distracts8 9.88 9 81.82 3 11.11 0 0.00 7 8.14 5 5.43 32
4 Attracts 26 32.10 1 9.09 13 48.15 8 36.36 39 45.35 31 33.70 1185 Highly attracts 46 56.79 1 9.09 10 37.04 13 59.09 38 44.19 55 59.78 163
Total 81 100 11 100 27 100 22 100 86 100 92 100 319
Table 4.2.12.56 shows that except cluster 2nd ‘Hill stations’ of Satara highly attract all
clusters. It infers that ‘Hill stations’ of Satara attracts ‘male’ ‘young’ and ‘mid aged’
tourists irrespective of their occupation.
Lake/Reservoir Tourism Product
Following table shows opinion of total samples on attraction of ‘Lake/Reservoir’ in
respective cluster in Satara district.
Table 4.2.12.57Attraction of Lake/Reservoir Tourism Product
Sr OpinionClusters
Total1 2 3 4 5 6f % f % f % f % f % f %
1 Not at all attracts 0 0 0 0 0 0 0 0 0 0 2 2.44 22 Not attracts 1 1.43 1 9.09 3 18.75 1 5.56 1 1.35 2 2.44 93 Neither attracts
nor distracts16 22.86 8 72.73 4 25 5 27.78 11 14.86 16 19.51 60
4 Attracts 43 61.43 1 9.09 7 43.75 7 38.89 45 60.81 41 50.00 1445 Highly attracts 10 14.29 1 9.09 2 12.5 5 27.78 17 22.97 21 25.61 56
Total 70 100 11 100 16 100 18 100 74 100 82 100 271
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Table 4.2.12.57 shows that Lake/Reservoir of Satara attracts more to clusters viz.
6,5,4,3 and 1, but among them cluster three attracts comparatively less since the
percentage of cluster three is 56.25% and rest of cluster percentage is above 60%, the
difference is hardly few percentage it may be because of its occupation ‘Petty traders’.
However, cluster number 2nd carries less percentage i.e. 18.18. It infers that
‘Lake/Reservoir’ of Satara attracts ‘male’ of all age group and its occupation matters
to some extent to perceive the attractiveness of ‘Lake/Reservoir’.
Scenery/Beauty Tourism Product
Following table shows opinion of total samples on attraction of ‘Scenery/Beauty’ in
respective cluster in Satara district.
Table 4.2.12.58Attraction of Scenery/Beauty Tourism Product
Sr. OpinionClusters
Total1 2 3 4 5 6f % f % f % f % f % f %
1 Not attracts 1 1.39 0 0 1 5.88 1 5.56 1 1.27 0 0 42 Neither attracts nor
distracts12 16.67 9 81.82 3 17.65 2 11.11 12 15.19 7 8.14 45
3 Attracts 23 31.94 1 9.09 8 47.06 9 50.00 40 50.63 41 47.67 1224 Highly attracts 36 50.00 1 9.09 5 29.41 6 33.33 26 32.91 38 44.19 112
Total 72 100 11 100 17 100 18 100 79 100 86 100 283
Table 4.2.12.58 shows that ‘Scenery/ beauty’ of Satara highly attracts to all clusters
since percentage is 75% and above except cluster number 2. It infers that
‘Scenery/beauty’ of Satara attracts ‘male’ tourists of all age group and occupational
category.
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Valleys Tourism Product
Following table shows opinion of total samples on attraction of ‘Valleys’ in respective
cluster in Satara district.
Table 4.2.12.59Attraction of Valleys Tourism Product
Sr OpinionClusters
Total1 2 3 4 5 6f % f % f % f % f % f %
1 Not at all attracts 0 0 1 10 1 6.25 0 0 0 0 4 4.82 62 Not attracts 1 1.85 0 0 1 6.25 1 5.56 1 1.41 6 7.23 103 Neither attracts nor
distracts18 33.33 8 80 2 12.5 9 50.00 18 25.35 21 25.30 76
4 Attracts 31 57.41 1 10 9 56.25 5 27.78 42 59.15 41 49.40 1295 Highly attracts 4 7.41 0 0 3 18.75 3 16.67 10 14.08 11 13.25 31
Total 54 100 10 100 16 100 18 100 71 100 83 100 252
Table 4.2.12.59 shows that ‘Valleys’ of Satara attracts more to clusters 1st, 3rd, 5th, and
6th since percentage is nearly 60%. However, cluster number 4th shows less
percentage towards attraction of ‘valleys’ and second cluster carries 10%, which is
very meager. The noticeable difference in 4th cluster due to its occupation and in 2nd
cluster as it is identical group of ‘female’ ‘housewife’ of age group ‘55 and above’. It
infers that valleys of Satara attract salaried male tourists.
Pilgrimage Tourism ProductFollowing table shows opinion of total samples on attraction of ‘Pilgrimage’ in
respective cluster in Satara district.
Table 4.2.12.60Attraction of Pilgrimage Tourism Product
Sr OpinionClusters
Total1 2 3 4 5 6f % f % f % f % f % f %
1 Not at all attracts 1 2 1 10 1 7.14 1 5.88 1 1.69 5 7.81 102 Not attracts 0 0 0 0 1 7.14 0 0.00 1 1.69 3 4.69 53 Neither attracts nor
distracts7 14 0 0 4 28.57 2 11.76 21 35.59 12 18.75 46
4 Attracts 29 58 1 10 6 42.86 11 64.71 19 32.20 34 53.13 1005 Highly attracts 13 26 8 80 2 14.29 3 17.65 17 28.81 10 15.63 53
Total 50 100 10 100 14 100 17 100 59 100 64 100 214
Table 4.2.12.60 shows that Pilgrimage of Satara highly attracts cluster 2nd, whichshows 90% of sample tourist followed by rest of the group. It infers that ‘pilgrimage’
Data Analysis
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of Satara attracts all category of tourist irrespective of their gender, age group, andoccupation but highly attracts ‘female’ of age group ‘55 and above’ ‘unskilled job’ asan occupation.
Temples Tourism ProductFollowing table shows opinion of total samples on attraction of Temple in respectivecluster in Satara district.
Table 4.2.12.61Attraction of Temples Tourism Product
Sr. OpinionClusters
Total1 2 3 4 5 6f % f % f % f % f % f %
1 Not at all attracts 1 1.89 0 0 1 7.14 1 7.14 1 1.52 0 0 42 Not attracts 0 0.00 0 0 0 0.00 0 0.00 1 1.52 1 1.41 23 Neither attracts nor
distracts11 20.75 0 0 3 21.43 3 21.43 25 37.88 10 14.08 52
4 Attracts 28 52.83 1 8.33 8 57.14 7 50.00 28 42.42 41 57.75 1135 Highly attracts 13 24.53 11 91.67 2 14.29 3 21.43 11 16.67 19 26.76 59
Total 53 100 12 100 14 100 14 100 66 100 71 100 230
Table 4.2.12.61 shows that temples of Satara highly attracts to cluster 2nd, whichshows 100% of sample tourist followed by rest of the group which carries more than65%. It infers that Satara temples attracts all category of tourist irrespective of theirgender, age group, and occupation but highly attracts ‘female’ of age group ‘55 andabove’ having ‘unskilled job’ as an occupation.
Museum Tourism ProductFollowing table shows opinion of total samples on attraction of ‘Museum’ inrespective cluster in Satara district.
Table 4.2.12.62Attraction of Museum Tourism Product
Sr. OpinionClusters
Total1 2 3 4 5 6f % f % f % f % f % f %
1 Not at all attracts1 2.17 1 10 1 8.33 1 7.69 1 1.79 3 4.92 82 Not attracts 0 0.00 0 0 1 8.33 1 7.69 3 5.36 5 8.20 103 Neither attracts
nor distracts13 28.26 8 80 3 25.00 3 23.08 29 51.79 14 22.95 70
4 Attracts 27 58.70 1 10 6 50.00 7 53.85 17 30.36 32 52.46 905 Highly attracts 5 10.87 0 0 1 8.33 1 7.69 6 10.71 7 11.48 20
Total 46 100 10 100 12 100 13 100 56 100 61 100 198
Data Analysis
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Table 4.2.12.62 shows that Museum of Satara highly attracts to cluster 1st, 4th and 3rd
which shows more than 60% of sample tourist but cluster 5th , which shows less i.e.
41.07% of sample tourist followed by cluster 2nd. It infers that Satara museum attracts
male category of tourist but difference was notice at occupation level so the ‘male’ of
all age group except ‘clerical and salesmen’ attracts towards museum.
Historical monuments Tourism Product
Following table shows opinion of total samples on attraction of Historical monuments
in respective cluster in Satara district.
Table 4.2.12.63Attraction of Historical monuments Tourism Product
Sr. OpinionClusters
Total1 2 3 4 5 6f % f % f % f % f % f %
1 Not at all attracts 1 1.96 0 0 1 5.56 1 7.14 1 1.56 1 1.52 52 Not attracts 1 1.96 0 0 0 0.00 1 7.14 4 6.25 3 4.55 93 Neither attracts nor
distracts18 35.29 9 81.82 3 16.67 3 21.43 28 43.75 15 22.73 76
4 Attracts 26 50.98 1 9.09 10 55.56 4 28.57 22 34.38 36 54.55 995 Highly attracts 5 9.80 1 9.09 4 22.22 5 35.71 9 14.06 11 16.67 35
Total 51 100 11 100 18 100 14 100 64 100 66 100 224
Table 4.2.12.63 shows that ‘Historical Monuments’ of Satara highly attracts to cluster
1st, 3rd 4th and 6th which shows more than 60% of sample tourist but cluster 5th ,
which shows less i.e. 48.44% of sample tourist followed by cluster 2nd 18.18%. It
infers that Satara ‘museum’ attracts male category of tourist but difference notices at
occupation level and gender so the male of all age group except ‘clerical and
salesmen’ attracts historical monuments of Satara as 5th cluster belongs to ‘clerical
and sales person’ occupational category and 2nd cluster carries only female.
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Forts Tourism Product
Following table shows opinion of total samples on attraction of ‘Forts’ in respective
cluster in Satara district.
Table 4.2.12.64Attraction of Forts Tourism Product
Sr. OpinionClusters
Total1 2 3 4 5 6f % f % f % f % f % f %
1 Not at all attracts 1 1.45 0 0 1 5.56 1 6.25 1 1.49 0 0 42 Not attracts 0 0.00 0 0 0 0.00 0 0 2 2.99 0 0 23 Neither attracts
nor distracts14 20.29 8 72.73 1 5.56 2 12.5 25 37.31 5 6.76 55
4 Attracts 43 62.32 1 9.09 12 66.67 5 31.25 25 37.31 44 59.46 1305 Highly attracts 11 15.94 2 18.18 4 22.22 8 50 14 20.90 25 33.78 64
Total 69 100 11 100 18 100 16 100 67 100 74 100 255
Table 4.2.12.64 shows that Forts of Satara highly attracts to cluster 1st, 3rd 4th, 6th and
5th of which cluster 5th carries comparatively less percentages i.e 58.21 and rest of
cluster carries high percentages i.e. above 75% . However, cluster second shows
27.27 % of sample tourist who attracts ‘forts’ of Satara. The difference noticed as
second cluster uniqueness due to its gender and fifth cluster occupation ‘clerical and
salesmen’ occupational category. It infers that Satara ‘fort’ attracts all male
irrespective of his age group category except ‘clerical and salesmen’ as an occupation.
Windmills Tourism Product
Following table shows opinion of total samples on attraction of Windmill in
respective cluster in Satara district.
Table 4.2.12.65Attraction of Windmills Tourism Product
Sr. OpinionClusters
Total1 2 3 4 5 6f % f % f % f % f % f %
1 Not at all attracts 1 2.33 1 10 1 9.09 1 8.33 2 3.70 8 12.70 142 Not attracts 4 9.30 0 0 1 9.09 0 0.00 2 3.70 3 4.76 103 Neither attracts nor
distracts24 55.81 8 80 3 27.27 4 33.33 31 57.41 22 34.92 92
4 Attracts 13 30.23 0 0 6 54.55 6 50.00 16 29.63 25 39.68 665 Highly attracts 1 2.33 1 10 0 0.00 1 8.33 3 5.56 5 7.94 11
Total 43 100 10 100 11 100 12 100 54 100 63 100 193
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Table 4.2.12.65 shows that ‘Windmill’ of Satara attracts more to cluster 4th and 3rd of
which the percentage is 58.33 and 54.55 respectively. Rest of cluster carries less than
50% of samples. Thus, it infers that ‘windmill’ attracts more to young male belong to
‘25-45’ age group having occupation as a ‘petty traders’ and/or’ industrialist with 1-9
employees’.
Conclusion:
The chapter discusses data, which is analyzed from desired perspectives. The analysis
involves macro analysis and wherever it is required, it did. The data is analyzed by
using relevant statistical tools. To keep data at minimal quantity and used of
inferential statistics. Since, the topic deals with tourism where qualitative observations
are very important to note. Hence, wherever it is a need to explain quantitative data
with the help of researchers own observations and experience the effort has been
made of such discussion to make analysis lucid and interesting to read. The findings
and discussions of earlier researches have taken out into next chapter. The chapter
also discusses suggestions followed by findings.