CHAPTER VII DATA ANALYSIS - Shodhgangashodhganga.inflibnet.ac.in/bitstream/10603/18573/13/13_chapter 7.pdf · CHAPTER VII DATA ANALYSIS ... 5 Voveran 50 Clexane 95 Budecort ... 17

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CHAPTER VII

DATA ANALYSIS

7.1 Introduction to data analysis

In this chapter, data obtained from physicians and customers is analyzed to test the theoretical

model of branding and positioning and trust which is detailed in theory building.

The analysis is divided into two parts i.e. (1) Customers i.e. physicians and (2) Consumers i.e

patients. Statistical analysis is performed in three parts, Visual, Descriptive and Inferential

.Each section comprises of visual presentation of data, followed by descriptive explanation

and further inferential statistics wherein bi-variate and multivariate techniques are used to

capture fundamental characteristics of data.

The whole chapter is subdivided according to administration of questionnaire. Initially

secondary data analysis is collected from various sources like Ims India, Ace analyser and

Euromonitor. Secondary data initially provided financial performance of the firms. From

which sample companies are selected and considered for analysis. Descriptive statistics and

trends are produced from the same in the first section. In the second part, data analysis of

primary data is done, which includes consumers and customers/ physicians. After each

hypothesis testing inference/ interpretation is written.

7.2 Section 1

This section discusses the secondary data obtained from various sources for analysis.

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7.2.1 Secondary Data analysis

Secondary data is collected from various secondary sources like ims India, Aceanalyser and

Euromonitor is analyzed and reported in descriptive and visual statistics method. Out of 308

players in pharmaceutical industry listed in ims India the following are selected based on

their ranking in the industry and product range they have. It is being understood from the data

that out of full product range 300 major brands that contribute major value in crore.

TABLE 3 : MAJOR CATEGORIES AND THEIR PERFORMANCE

Categories 2005 2006 2007 2008 2009 2010

Health and Wellness

by Prime Positioning 81,635.3 86,487.6 94,682.8 108,195.3 117,466.4 134,071.1

Bone and Joint

Health 1,302.1 1,350.7 1,378.5 1,530.6 1,652.1 1,809.2

Cardiovascular

Health 4.9 5.8 7.3 9.4 11.5 13.8

Digestive Health 8,638.5 8,895.7 9,539.8 10,615.0 11,548.2 12,632.5

Immune Support 5.1 42.6 66.2 83.0 125.5 159.3

Oral Health 2,172.2 2,278.3 2,464.1 2,775.0 3,067.0 3,315.1

Respiratory Health 968.5 980.0 1,034.3 1,171.2 1,269.4 1,398.5

Urinary Tract Health 0.3 0.4 0.4 0.4 0.4 0.4

Research Sources: Health and Wellness- Euromonitor from

trade sources/national statistics

IMS India 2012 data is being obtained and from all the list of drugs the major 300 which

contributes highest in the sale is listed below.

94

TABLE 4 : TOP BRANDS IN PHARMA SECTORS.

Rank Brand name Rank Brand name Rank Brand name

1 Phensedyl cough 46 Mtp kit 91 Zanocin

2 Augmentin 47 Sporidex 92 Pan-d

3 Corex 48 Novamox 93 Pantodac

4 Human mixtard30/70 49 Betnesol 94 A to z ns

5 Voveran 50 Clexane 95 Budecort

6 Monocef 51 Galvus met 96 Losar

7 Revital 52 Althrocin 97 Mixtard hm 30/70

8 Volini 53 Digene 98 Rantac

9 Betadine 54 Magnex 99 Udiliv

10 Taxim 55 Rabipur 100 Duolin

11 Dexorange 56 Aten 101 Ocid

12 Liv-52 57 Sinarest 102 Aztor

13 Mox 58 Duphaston 103 Mucaine

14 Clavam 59 Gelusil-mps 104 Falcigo

15 Thyronorm 60 Dolonex 105 Telma-h

16 Becosules 61 Pantocid 106 Megapen

17 Asthalin 62 Aerocort 107 Susten

18 Taxim-o 63 Phexin 108 Ascoril +

19 Spasmo-proxyvon 64 Betnovate-c 109 Vertin

20 Zifi 65 Ciplox 110 Otrivin

21 Calpol 66 Cifran 111 Xone

22 Shelcal 67 Folvite 112 Cremaffin

23 Lantus 68 Neurobion forte 113 Chymoral

24 Azithral 69 Zincovit 114 Galvus

25 Combiflam 70 Minipress-xl 115 Rosuvas

26 Manforce 71 Janumet 116 Tonact

27 Pentaxim 72 Amaryl 117 Skinlite

28 Aciloc 73 Betnovate-n 118 Meftal spas

29 Novomix 30 74 Telma 119 Nise

30 Zinetac 75 Eltroxin 120 T-bact

31 Cardace 76 Allegra 121 Glycomet

32 Moxikind-cv 77 Deriphyllin 122 Meronem

33 Eptoin 78 Unwanted-kit 123 Glucored

34 Ceftum 79 Moxclav 124 Lactodex

35 Storvas 80 Electral 125 Roxid

36 Pediasure complete 81 Varil rix 126 Pantocid-d

37 Omez 82 Atorva 127 Gemcal

38 Glycomet-gp 83 Januvia 128 Human actrapid

39 Seroflo 84 Neosporin 129 Pantop

95

40 Prevenar-13 85 Quadriderm-rf 130 Havrix

41 Foracort 86 Losar-h 131 Deca durabolin

42 Orofer-xt 87 Ampoxin 132 Zoryl-m

43 Pan 88 Ultracet 133 Gemer

44 Mikacin 89 Monocef-o 134 Cepodem

45 Dexolac 90 Huminsulin 30/70 135 O2


136 Candid-b 181 Amaryl m 226 Enterogermina

137 Cypon-old 182 Febrex plus 227 Soframycin

138 Ovral-l 183 Grilinctus 228 Stemetil

139 Bett 184 Emeset 229 Dexona

140 Duphalac 185 Gudcef 230 Shelcal-ct

141 Nikoran 186 Sumo 231 Hifen

142 Stamlo 187 Cefolac 232 Polybion sf

143 Pantop-d 188 Envas 233 Zolfresh

144 Mifegest-kit 189 Practin 234 Glynase-mf

145 Dolo 190 Mit's codeine comp 235 Kenacort

146 Rotarix 191 Oflomac 236 Wokadine

147 Mtprost kit 192 Supacef 237 Stugeron

148 Nitrocontin 193 Paracetamol apex 238 Flexon

149 Evion 194 Aciloc-rd 239 Clopilet

150 Dilzem 195 Fortwin 240 Levera

151 Targocid 196 Dalacin c 241 Bevon

152 Oframax 197 Claribid 242 Formonide

153 Wikoryl 198 Omez-d 243 Ativan

154 Prega news 199 Unienzyme 244 Advent

155 Zentel 200 Alprax 245 Candid

156 Methergin 201 Cordarone 246 Hepa-merz

157 Primolut-n 202 Zedex 247 Refresh tears

158 Frisium 203 Macpod 248 Pipzo

159 Amlopres-at 204 Grilinctus-bm 249 Nicardia

160 Hepatoglobine 205 Panderm+ 250 Orofer-s

161 Gluconorm-g 206 Lariago 251 Prothiaden

162 R.b.tone 207 Augpen 252 M2 tone

163 Omnacortil 208 Haemaccel 253 Wysolone

164 Zenflox 209 Jalra-m 254 Seloken

165 Solu-medrol 210 Rapither-ab 255 Tazomac

166 Glyciphage 211 Norflox 256 Okavax

167 Aristozyme 212 Amlodac 257 Biotax

168 Lipicure 213 Meromac 258 Mega-cv

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169 Fortum 214 Mahacef 259 Syntocinon

170 Ondem 215 Zenflox-oz 260 Hcqs

171 Bro-zedex 216 Zyloric 261 Tribet

172 Mt pill 217 Tegrital 262 Sensiclav

173 Ecosprin-av 218 Montaz 263 Amicin

174 Azee 219 Dulcolax 264 Nebicard

175 Nurokind plus 220 Cyclopam 265 Dytor

176 Cetzine 221 Johnson baby 266 Valparin

177 Jalra 222 Mahacef-plus 267 Budamate

178 Onglyza 223 Lyrica 268 Valparin chrono

179 Alburel 224 Avil 269 Asomex

180 Levipil 225 Ampilox 270 Mixtard 30 flexpen


271 Domstal 281 Atocor 291 Zienam

272 Cefakind 282 Tossex 292 Ostocalcium b12

273 Strocit 283 Ceftas 293 Stamlo beta

274 Zocef 284 Trika 294 Pentids

275 Razo 285 Hemfer 295 Ramistar

276 Cobadex 286 Buscopan 296 Topcef

277 Unwanted 287 Ibugesic plus 297 Regestrone

278 Lobate-gm neo 288 Histac 298 Glizid-m

279 Gardenal 289 Human mixtard50/50 299 Xylocaine

280 Beplex forte 290 Urimax 300 Supradyn

TABLE 5 : TOP EIGHT PERFORMERS

Company name Ranking No. of products Total Market(In Crore)

Cadilla

6 835 217.8

Cipla

2 948 273.39

Dr redddy

16 292 117.56

Glaxo Smithkline

4 216 236.06

Lupin

10 645 162.82

Ranbaxy

5 700 231.22

97

Sanofi Aventis Pasteur

11 166 162.29

Sun

3 566 243.92

Source: IMS India

From the above table it is clear that minimum number of products that the chosen companies

have is 166 and maximum is 948. The range found out is 782. The average products that the

companies have are 546 with standard deviation of 292. When the data then is separated

based on the ranks it is observed that first 5 rank holders have maximum product excepting

Glaxo smithkline.

GRAPH 2: RANKING OF COMPANIES AND PRODUCT COUNT

Source: ims India 2012

23

45

6

10 1116

948566

216

700 835645

166

292

1

10

100

1000

Ranking

No. of products

98

Interpretation: From the above chart it is seen that cipla has got highest number of products

and highest rank. From the above Bar chart it is very clear that companies having major

number of products have good standing in market with top rankings.

GRAPH 3: TOTAL MARKET (IN CRORE)

Source: Ims india 2012

Interpretation: From the above chart it is evident that cipla with high rank also has got

highest market. And Dr, Reddy‘s got lowest in the comparison of other eight players. This

financial data is considered to understand the performance of companies to test the

hypothesis.

273.39243.92 236.06 231.22

217.8

162.82 162.29

117.56

0

50

100

150

200

250

300

Total Market(In Crore)

Total Market(In Crore)

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TABLE 6: FINANCIAL DATA OF MAJOR PLAYERS.

Company

Name

Year

End

Net

Sales

Rs.

Millio

n

Net

SalesVa

r%

NP

Rs.

Millio

ns

Quar

ter

End

Sales (Rs.)

Millions

Sale

s

Var

%

NP

Var%

Cadila

Healthcare

2012

03 31508 7.89 6575

20120

3 7837.8 6959.5

12.6

2 55.3

Cipla

2012

03 69775 10.21

11239

.6

20120

3

18655.

7

16677.

4

11.8

6 36.33

Dr Reddys

Lab

2012

03 67397 27.06 9124

20120

6

18045.

4

16969.

6 6.34 -60.87

Glaxosmith

kline Phar

2011

12

23380.

34 10.72

6313.

6

20120

3 6298.5 6098.1 3.29

26615.

22

Lupin

2012

03

53848.

3 19.8

8043.

7

20120

6

17802.

9

11057.

1

61.0

1 391.04

Ranbaxy

Labs.

2011

12

76853.

34 35.55

-

30520

.5

20120

3

19205.

22

11267.

25

70.4

5

-

1663.5

6

Sun Pharma

Inds.

2011

03 31047 24.91 13838

20120

3

11970.

7 8123.1

47.3

7 88.31

Source: Ace Analyser

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From the above table the year-end sale, net sales and variations in the sales can be observed.

To comment on the variation support of visual statistics is taken and is displayed below.

GRAPH 4: SALES VARIATION OF MAJOR PHARMACEUTICAL COMPANIES

The above bubble chart is made by considering two variable sale and percentage variation

in sales. It can be interpreted from the graph that the sales variation is maximum in Ranbaxy,

Lupin and Sun pharma ltd considering sales at the same time.

GRAPH 5: NET PROFIT IN MILLIONS

When the single variable is considered that is sales, it is observed that Ranbaxy, Cipla and

Dr. Reddy‘s are amongst the highest in the league.

12.62 11.866.343.29

61.01

70.45

47.37

-10

0

10

20

30

40

50

60

70

80

90

0 5000 10000 15000 20000

Cadila Healthcare Cipla Dr Reddys Lab

Glaxosmithkline Phar Lupin Ranbaxy Labs.

Sun Pharma Inds.

31508

69775 67397

23380.34

53848.3

76853.34

31047

0100002000030000400005000060000700008000090000

NP in Millions

NP Rs. Millions

101

After analyzing the secondary data from ims India about eight major players, the data on

personality scale is asked from physicians. The scale is adapted for measuring Brand

personality from Aaker (1997). Some important traits related to pharmaceutical concepts are

added. The reliability of the same is checked. This is explained in the third section of data

analysis.

7.3 Section 2

7.3.1 Consumer‟s data analysis

In the pharmaceutical scenario brands are not studied in detail as compare to FMCG brands.

This part of the study tries to understand the demographic details of the patients and the

overall opinion of the brand medicine.

Objective of this part of data collection from patients was to understand important factor for

patients while choosing medication. Initial demographic details were asked and are

summarized below,

Data cleaning was done by rejecting omissions, ambiguities and error in the responses, an

accurate sample point reach was found to be 442. Composition of male and female was 59%

and 41% respectively. 8% of the respondents had education up-to 12th

standard, 50% had

education up to graduation and 42% were post graduate.52% of them were in service 12% in

business 14% students 8 % were retired from the service and 14% were housewives .39% of

the respondents had income less than 5 lacks, 41% from 5 to 10 lacks and 19% were having

income above 10 lacks. 10% of the respondents had some medical educations. The minimum

age of the respondents 18 and maximum is 81. Respondents which are on daily medications

were 24%. Maximum number of pharmaceutical companies they could recall was 7, 61%

could recall less than 3 companies.

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TABLE 7: GENDER WISE DISTRIBUTION

Gender Percent

Valid Male 59.3

Female 40.7

Total 100.0

TABLE 8: OCCUPATION

Occupation Percent

Valid 1.4

Service 42.1

Business 11.8

Student 24.0

Retired 7.7

Housewife 13.1

Total 100.0

TABLE 9: EDUCATION

Education Percent

Valid 10th

standard 2.3

12th

standard 5.4

Diploma 3.6

Graduate 49.8

Post

graduate 35.3

Doctorates 1.8

Total 98.2

Missing System 1.8

Total 100.0

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TABLE 10: AGE WISE DISTRIBUTION OF RESPONDENTS

Age Category Frequency Percentage (%)

1 Below 18 2 0.45

2 18-30 81 18.33

3 31-40 70 15.84

4 41-50 214 48.42

5 51-60 60 13.57

6 61 and above 14 3.17

TABLE 11 : FAMILY INCOME

Frequency Percent

Valid 1lac to 5 lac 168 38.0

5 to 10 180 40.7

10 and above 78 17.6

Total 426 96.4

Missing System 16 3.6

Total 442 100.0

Inference: From the above tabular representation some prominent observations are,

Gender composition is almost equal. 50% of the respondents have education upto graduate

level and 35% post graduate level. 40% of the subjects have income in the bracket of 5 to 10

lacs. And around 50% of the age group is in the age bracket of 41- 50.

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TABLE 12 : DESCRIPTIVE STATISTICS FOR PATIENT‟S AWARENESS OF

MEDICINES

Parameters N Mean

Standard

Deviation

When the drug is prescribed to me I look for the company name 440 4.07 1.02

I ask the doctor to prescribe me medicines of the particular

company 438 3.71 0.91

I share the knowledge of the medicine with the physician 402 3.65 1.03

I ask a doctor about the side effects 420 3.59 1.03

I update myself with the new formulations 436 3.26 1.24

I am willing to pay 100% more for branded drug 440 3.22 0.99

Branded drugs are more effective than over the counter drugs 438 3.21 1.17

I purchase on Pharmacists' recommendation 434 3.18 1.06

I will purchase the same brand for the same symptoms 438 3.11 1.16

I feel branded drugs are more effective 436 3.06 1.18

After I read or see an advertisement I purchase it next time when

in need of a drug 432 2.97 1.11

I feel branded drugs are more expensive 440 2.95 1.30

Once in a day medicine is more convenient for me as compare to

twice or thrice a day 428 2.86 1.12

Colour of the medicine is an important factor 440 2.77 1.35

Size of the medicine is an important factor 440 2.66 1.11

105

Inference:

In this objective was to understand the awareness of patients for medicines. The mean is

calculated and standard deviation as a measure of dispersion of the data.

It was revealed from the data that company name is very important for them whose score is

4.07, another factor was demanding medicines from a reputed company got mean score of

3.71.

Another important factor is patients are interested in knowledge about the products, its side

effects and formulation or contents of the drug, which is reflected through high mean score

(3.65). Patients are willing to pay 100% more for prescription a drug, which indicates that

branded product from good company are preferred.

Another important factor is patients are interested in knowledge about the products, its side

effects and formulation or contents of the drug, which is reflected through high mean score

(3.65). Patients are willing to pay 100% more for prescription a drug, which indicates that

branded product from good company are preferred.

The basic thrust of marketing strategy depends on identifying a working value proposition

that is

"Packaging is what consumers see first in this marketing end game… this is why package

structure will be a key differentiator of products in the near future" (Arnold, 2003, p. 15). The

importance of packaging has been overlooked in the traditional marketing mix. The basic

thrust of marketing strategy depends on identifying a working value proposition that is

unique, and then trying to find a niche that will be attractive segment (Green, 2008).

There are several gaps that exist in the packaging of pharmaceutical products with reference

to Utility functions. The 4 P marketing mix classification can be viewed by suppliers as the

customers' four Cs, i.e. customer value, cost to satisfy, convenience and communication (the

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4C perspective) (Olsson & Gyorei 2002).The US Food and Drug Administration (FDA) has

started the regulatory process to require bar coding on packages of prescription and the

commonly used OTC drugs sold to hospitals and healthcare institutions (excluding physician

samples). This is done to cut the dispensing errors.

Branded drugs are more preferred and are more effective is the understanding of majority of

patients, mean score is 3.21.

Convenience of the medicine, colour of the medicine and taste of the medicine are equally

important factors with the mean score of 2.77 and 2.66. Most of these older patients and

sometimes even some of the younger ones have trouble remembering what pills to take and

when. This is where packaging helps in the form of compliance packs. Also the dual-drug

pack introduced for the day-time only or night-time only user has been highly successful in

boosting the pharmaceutical products overall sale (Pierce2002).

Convenience of dosage has got a mean rating of 2.86, which again is a significant factor.

The National Pharmaceutical Council (NPC), an industry research organization, estimates

that Non compliance with medication added over US $100 million annually to the U.S. health

care system, 11 % of hospitalizations (over 1 million per year in the U.S.) are estimated to

result from poor compliance with prescribed medication (Wilson 2002). To overcome

problems of compliance in the elderly, healthcare providers are advised to prescribe a simple

dosage regimen for all medications to be taken (preferably 1 or 2 doses daily), to help the

patient select cues that assist them in remembering to take doses (time of day, meal time, or

other daily rituals), to provide devices to simplify remembering doses (medication boxes),

and to regularly monitor compliance (Cramer J.A. 1998). Single-unit doses, widely used in

hospitals, may be cumbersome for elderly patients who have difficulty opening the foil-

backed wrappers (Christensen, Christrup, Fabricius & Hansen; 2007).

107

Child resistant blisters are a lot more difficult to develop than a bottle with a child-resistant

cap because of the protocol tests. Some of the most effective designs in this category rely on

cognitive ability rather than brute force. Socially focused work on packaging also looks at

improving usability and ease of access for disabled customers and the elderly. Because of age

related infirmities, many seniors do not have the strength to overcome the child-resistant

features (Pierce 2002).

About OTC that is over the counter drug the mean is minimum which again supports the fact

that prescription drugs are preferred from the reputed company for the trust element, which

his depicted through a mean of 3.21.

From the above descriptive statistics it is analyzed that company name when medicine is

prescribed to them that is one of the important factor amongst all. The importance of recall is

well-established Aaker (1991) points out, that consumers understanding of Brand‘s image

derives initially from brand name and the association it elicits. From the above graph it is

clear that majority of the consumers could name less than 5 names and maximum that they

could recollect is 10 names. To increase the recall as has been researched by (Keller,

Heckler and Houston 1994) name suggestiveness increases recall in meaning with the brand

name, it impedes memory of unrelated brand claims.

7.3.2. Hypothesis testing for Consumer data.

H1: There is significant difference across different segments in their perception of

pharmaceutical industry.

-Education and age are independent variables when it comes to perception of the

pharmaceutical company.

H1a

: Awareness of the pharmaceutical companies is dependent on education.

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H1b: Awareness of the pharmaceutical company is dependent on age.

For this the recall variable is categorized into two one recall less than 5and second category

recall more than 5.

TABLE 13 : CHI-SQUARE TESTS- EDUCATION * COMPANY NAME CROSS

TABULATION

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 20.293(a) 5 .001

Inference:

From the above table it is inferred that name recall is dependent on education. The hypothesis

is significant at 0.05 and 0.001 significance level. Also count table suggests as the education

increases the recall also has increased.

H1b: Company name recall by patients is independent Family income.

Here the categorical variables are family income and company name recall.

TABLE 14 : CHI-SQUARE TEST- INCOME * COMPANY NAME CROSS

TABULATION

Value df

Asymp. Sig. (2-

sided)

Pearson Chi-Square 7.896 2 .019

The assumption here is to understand the dependency between companies patients could

recollect and their annual income. The above test of goodness of for is true at 0.05 and

109

0.01significance level, proving that there is a significant dependency between recall and

income.

This section of data analysis gave insight about important factors in consumers mind while

purchasing and consuming medicines. It also

7.4 Section 3

In this part of data analysis the sample unit is medical practitioners/ physicians. The objective

of this section is to understand major influencing factors for prescription. The second

objective is to find out how these major pharmaceutical companies are perceived. SPSS is

used to analyze the data. Univariate hypothesis testing, factor analysis and discriminant

analysis is used for the data sets.

7.4.1 Physicians perception study

Data analysis was done for each measure .This was done by tabulating the data. Tabulation

consists of simply counting the number of cases that fall into the various categories. The

primary use of tabulation was in calculating the descriptive (summary) statistics particularly

the mean or percentages.

7.4.1.1 Descriptive statistics for Physicians

Physicians sample consisted of all practicing doctors. All over Mumbai the data has been

collected .being a metro city and having major hospitals sample unit considered is Mumbai

city. One of the criterions was convenience of obtaining data. Data has been collected from

major hospitals, Clinics and dispensaries. The sample consisted of doctors of all age group

and all different specialties. The number of years of practice ranged from 1 to 40. The overall

final sample size after data cleaning used for analysis was 464 doctors.

110

The following section of data analysis is disuses the factor analysis and correlation with

hypothesis testing. Initially mean score of all the reasons for prescriptions are stated and

supported with standard deviations.

TABLE 15 : REASONS FOR PRESCRIPTION

Descriptive Statistics Mean Std. Deviation

Affordability 4.71 1.73

Better than competitor 4.44 1.25

Choice 4.83 1.42

Consider patients important 5.31 1.45

Convenience to obtain 5.08 1.50

Country of origin 3.63 1.85

Expensive 4.69 1.72

Extra benefit 4.98 1.30

Eye-catching visual aid 4.16 1.70

Familiarity 4.63 1.41

Good quality 5.36 1.37

High principle 5.01 1.33

Leaders in market 4.98 1.35

Reasonable price 5.39 1.45

Reliability 5.11 1.43

Assured results 5.27 1.64

Name of the product 5.24 1.22

Well known 5 1.42

Wide range 4.91 1.32

111

Trust worthy 5.33 1.52

Side effects 4.61 1.64

Medical representative 5.2 1.54

Interpretation:

From the above table it is understood that Patients convenience, price quality are some of the

important factors. Also reliable product from a good company is preferred by physicians.

Availability is also considered a major factor. Though analysis is based on mean scores a

detailed inferences cannot be led. For that a factor analysis is performed. The scale is tested

for its Reliability the results are as follows,

7.4.1.2 Reliability of Scale for Physicians

The reliability of a measure is established by testing for both consistency and stability.

Consistency indicates how the items measuring a concept hang well together as a set.

Cronbach‘s alpha is a reliability coefficient that reflects how well the items in a set are

positively correlated to one another. Cronbach‘s alpha is computed in terms of the average

inter-correlations among the items measuring the concept. The closer Cronbach‘s alpha in to

1, the higher the internal consistency reliability (Kerlinger, 1986).

TABLE 16 : CRONBACH'S ALPHA PERCEPTION SCALE

Cronbach's Alpha Cronbach's Alpha

Based on

Standardized

Items

N of Items

.905 .916 27

112

Interpretation: For our study Cronbach‘s alpha is found out to be .905, which shows high

internal consistency in the scale.

TABLE 17 : KMO AND BARTLETT'S TEST

The Kaiser-Meyer Olkin test of Sphericity was used for measuring sampling adequacy

(KMO). After selecting ―Analyse‖ from the, SPSS menu bar, ―Dimension‖ and ―Factor

Reduction‖ and then Factor was carried out. After clicking on ―Descriptive‖, in the statistics

box initial solution was checked. In correlation matrix, KMO and Bartlett‘s test of Sphericity

was checked and reproduced. The KMO statistics varies between 0 and 1. A value close to 1

indicates that patterns of correlations are relatively compact and so factor analysis should

yield distinct and reliable factor. (Malhotra & Dash, 2009)

The results of Kaiser Mayor – Olkin measure of sampling adequacy indicates the value of

0.761 which is quite close to 0.8 , thus the test is sufficiently good (middling) to be conducted

on these factors. The Bartlett‘s test of Sphericity indicates that the variables that are studies

are independent of each other thus the variables chosen are good enough to conduct factor

analysis test on them. For the present study the null hypothesis of dependency between

variable is rejected.

KMO and Bartlett's

Kaiser-Meyer-Olkin Measure of Sampling Adequacy. 0.761

Bartlett's Test of Sphericity Sig. 0.000

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7.4.1.3 Hypothesis testing-Factors responsible for Prescription Generation

Objective of the thesis is to find out relevant and important factor for prescription. This part

of data analysis addresses significant factors which are tested with T test.

TABLE 18 : ONE-SAMPLE TEST- FACTORS RESPONSIBLE FOR

PRESCRIPTION

t Sig. (2-tailed)

Mean

Difference

95% Confidence

Interval of the

Difference

Lower Upper

affordability 5.816 .000 .710 .47 .95

better than comp 4.991 .000 .440 .27 .61

choice 8.277 .000 .830 .63 1.03

consider patient as imp 12.771 .000 1.310 1.11 1.51

convenience to obtain 10.240 .000 1.080 .87 1.29

country of origin -2.834 .005 -.370 -.63 -.11

expensive 5.702 .000 .690 .45 .93

extra benefit 10.667 .000 .980 .80 1.16

Eye catching visual aid 1.336 .183 .160 -.08 .40

Familiarity 6.327 .000 .630 .43 .83

good quality 14.104 .000 1.360 1.17 1.55

high principle 10.771 .000 1.010 .83 1.19

leaders in market 10.305 .000 .980 .79 1.17

reasonable price 13.603 .000 1.390 1.19 1.59

reliability 10.969 .000 1.110 .91 1.31

assured results 10.991 .000 1.270 1.04 1.50

name of the product 14.465 .000 1.240 1.07 1.41

well known 9.975 .000 1.000 .80 1.20

wide range 9.783 .000 .910 .73 1.09

Trust worthy 12.422 .000 1.330 1.12 1.54

side effects 5.258 .000 .610 .38 .84

Medical rep 11.066 .000 1.200 .99 1.41

Interpretation:

In the above table of hypothesis testing, most of the factors have come out significant, other

than few like eye catching visual aids with is insignificant factor. Confidence interval

indicates the difference will be in the lower and upper interval at 95% and 99% confidence

interval.

114

Research hypothesis is written in more formal statistical hypothesis structure and the

inferences are made according to the statistical tests used. Following are the results. Test

value considered here is 4 .

H2: Affordability is a significant factor in prescription of the product.

T test statistics is found out to be 5.816 and p value is 0.000, which can be inferred as it is a

significant factor at 0.05 and 0.01 significance level. Null hypothesis is rejected.

H3: Better than competitors is a relevant factor in the prescription of the product.


significant factor. It can be inferred as it is a significant factor at 0.05 and 0.01 significance

level. Null hypothesis is rejected

H4: Choice available is a relevant factor in the prescription of the product.


significant factor . This factor is significant at 0.05 and 0.01 significance level. Null

hypothesis is rejected

H5: Considers patient as important is a relevant factor in the prescription of the product.


significant factor. This factor is significant at 0.05 and 0.01 significance level. Null hypothesis

is rejected

H6: Convenience to obtain is a relevant factor in the prescription of the product.


115



H7:Country of origin is a relevant factor in the prescription of the product.

T test statistics is found out to be -2.834 and p value is 0.000, which can be inferred as it is a


is rejected.

H8: Being expensive is a relevant factor in the prescription of the product.




H9: Extra benefit offered is a relevant factor in the prescription of the product.




H10: Catching visual aid is a relevant factor in the prescription of the product.

T test statistics is found out to be 1.336 and p value is 0.1800, which can be inferred as it is

not a significant factor. This factor is significant at 0.05 and 0.01 significance level. Null

hypothesis is rejected.

116

H11: Familiarity is a relevant factor in the prescription of the product.




H12: Good quality is a relevant factor in the prescription of the product.




H13: High principle is a relevant factor in the prescription of the product.




H14: Leader in the market is a relevant factor in the prescription of the product.




H15: Reasonable price is a relevant factor in the prescription of the product.




117

H16: Reliability is a relevant factor in the prescription of the product.



is rejected.

H17: Assured result is a relevant factor in the prescription of the product.



is rejected

H18: Name of the product is a relevant factor in the prescription of the product.



is rejected

H19: Well known product is a relevant factor in the prescription of the product.



is rejected

H20: Wide range is a relevant factor in the prescription of the product.



is rejected

118

H21: Being trustworthy is a relevant factor in the prescription of the product.


significant factor .This factor is significant at 0.05 and 0.01 significance level. Null hypothesis

is rejected

H22: A Low side effect is a relevant factor in the prescription of the product.



is rejected.

H23 : Medical representative is a relevant factor in the prescription of the product.



is rejected.

TABLE 19:THE SUMMARY TABLE FOR HYPOTHESIS TESTING

S.no Alternative hypothesis Test p-

value

Result

1

Affordability is a relevant factor in

prescription of the product.

T- Test

.000

Null hypothesis

Rejected.

2

Better than competitors is a relevant factor

in the prescription of the product.

T- Test

.000

Null hypothesis

Rejected.

3

Choice available is a relevant factor in the


T- Test

Null hypothesis

119

.000

Rejected.

4

Considers patient as important is a relevant

factor in the prescription of the product.

T- Test

.000

Null hypothesis

Rejected.

5

Convenience to obtain is a relevant factor


T- Test

.000

Null hypothesis

Rejected.

6

Country of origin is a relevant factor in the


T- Test

0.005

Null hypothesis

Rejected.

7

Being expensive is a relevant factor in the


T- Test

.000

Null hypothesis

Rejected.

8

Extra benefit offered is a relevant factor in

the prescription of the product.

T- Test

.000

Null hypothesis

Rejected.

9

Catching visual aid is a relevant factor in


T- Test

.183

Null hypothesis

Accepted.

10

Familiarity is a relevant factor in the


T- Test

.000

Null hypothesis

Rejected.

11

Good quality is a relevant factor in the


T- Test

.000

Null hypothesis

Rejected.

120

12

High principle is a relevant factor in the


T- Test

.000

Null hypothesis

Rejected.

13

Leader in the market is a relevant factor in


T- Test

.000

Null hypothesis rejected.

14

Reasonable price is a relevant factor in the


T- Test

.000


15

Reliability is a relevant factor in the


T- Test

.000


16

Assured result is a relevant factor in the


T- Test

.000


17

Name of the product is a relevant factor in


T- Test

.000


18

Well known product is a relevant factor in


T- Test

.000


19

Wide range is a relevant factor in the


T- Test

.000


20

Being trustworthy is a relevant factor in the


T- Test


121

.000

21

A Low side effect is a relevant factor in


T- Test

.000


22

Medical representative is a relevant factor


T- Test

.000


23

There is a significant difference in factors

of relevancy like Company image, trust in

product, patient focus, price factor and

other stimulus.

One way

ANOVA

.000

Null hypothesis rejected

7.4.1.4 Grouping factors in Prescription Generation

Introduction

Initial factor analysis showed the grouping of factors according to the factor loading,

Affordability, Reasonable price, Choice are loaded together-factor 1, Consider patient as

important, Side effects and Easy to obtain are grouped together-factor 2 Good quality, High

principles, Reliability, Name of the product, Trustworthy, Well-known-factor 3, Country of

Origin, Medical Rep, Extra benefits, Assured results go hand in hand-factor 4 and Leaders in

market, Better than competitor-factor 5. Accordingly they are named as Company image,

Trust in product, Price factor, patients focus and other stimulus.

Factors such as Familiarity and Eye catching visual aid and Expensive had a loading less than

0.5, The correlation matrix is drawn to explain the relationship between them.

122

7.4.1.5 Correlation Matrix

The rule of thumb for interpreting correlation coefficients is to divide the range of possible

scores in five intervals: 0 to 0.20 corresponds to a very weak relationship; 0.21 to 0.40

corresponds to a weak relationship, 0.41 to o.60 corresponds to a moderate relationship, 0.61

to 0.80 corresponds to a strong relationship, and 0.81 to 1.00 corresponds to a very strong

relationship. The rules apply whether the sign of the correlation coefficient is positive or

negative

The correlation matrix obtained shows significant correlation between factors like company

image, trust in product, patient focus, price factor and other stimulus. The correlation is

significant at all levels of 0.05, 0.1 and 0.01.

TABLE 20 : CORRELATION MATRIX

Correlations

Company

image

Trust in

product

Patient

focus

Price

factor

Other

stimulus

Company

image

Pearson

Correlation 1.000 0.563 0.492 0.569 0.440

Sig. (2-

tailed) 0.000 0.000 0.000 0.000

Trust in

product

Pearson

Correlation 0.563 1.000 0.614 0.677 0.401

Sig. (2-

tailed) 0.000 0.000 0.000 0.000

123

Patient focus

Pearson

Correlation 0.492 0.614 1.000 0.667 0.405

Sig. (2-

tailed) 0.000 0.000 0.000 0.000

Price factor

Pearson

Correlation 0.569 0.677 0.667 1.000 0.358

Sig. (2-

tailed) 0.000 0.000 0.000 0.000

Other

Stimulus

Pearson

Correlation 0.440 0.401 0.405 0.358 1.000

Sig. (2-

tailed) 0.000 0.000 0.000 0.000

**Correlation is significant at the 0.01 level (2-tailed).

Interpretation:

From the above correlation matrix it is evident that there is a significant correlation between

company image, trust in product, price factor, patient focus and other stimulus. The

correlation coefficient is significant at both 0.05 and 0.01 significance level.

This also indicates that positioning of the product can be done based on above criterions to

have more success for the brand. The coefficient is high for price, trust and patient focus.

124

7.4.2 Corporate Personality Perception- Physician‟s study

From the section 1, data analysis on secondary data ims India about eight major players, the

data on personality scale is asked from physicians. The scale is adapted for measuring Brand

personality from Aaker (1997). Some important traits related to pharmaceutical concepts are

added. The reliability of the same is checked. This is explained in this section of data

analysis.

TABLE 21: RELIABILITY STATISTICS FOR PERSONALITY SCALE

Cronbach's Alpha

Cronbach's Alpha Based on

Standardized Items N of Items

.933 .933 27

Reliability analysis allows you to study the properties of measurement scales and the items

that compose the scales. The reliability analysis procedure calculates a number of commonly

used measures of scale reliability and also provides information about the relationship

between individual items in the scale. Interclass correlation coefficient can be used to

compute inter-rater reliability estimates. Using reliability analysis, the extent to which the

items in questionnaire are related to each other, an overall index of the repeatability or

internal consistency of the scale as a whole can be found out. Problem items can be identified

by this method. Cronbach's Alpha for the sample is .933 which is considered ―superb ―and

one can consider that it is appropriate to conduct factor analysis on this sample, which will

yield distinct and reliable factors.

125

7.4.2.1 Exploratory Factor analysis

Using SPSS 17 factor analysis is performed, the initial tables generated are explained. The

factors with high factor loading are combined and are named after grouping together.

TABLE 22 : TOTAL VARIANCE EXPLAINED

Component Initial Eigen values Rotation Sums of Squared Loadings

Total

% of

Variance

Cumulative

% Total

% of

Variance

Cumulative

%

1 9.365 34.685 34.685 3.524 13.053 13.053

2 1.706 6.319 41.005 3.218 11.918 24.971

3 1.251 4.633 45.637 2.870 10.628 35.600

4 1.101 4.079 49.716 2.430 9.002 44.601

5 1.011 3.745 53.462 2.392 8.860 53.462

6 .898 3.327 56.789

7 .854 3.163 59.952

8 .754 2.794 62.745

9 .737 2.730 65.476

10 .699 2.590 68.065

11 .670 2.483 70.548

12 .661 2.448 72.997

13 .622 2.303 75.300

14 .603 2.234 77.533

15 .586 2.171 79.704

16 .576 2.132 81.836

17 .536 1.986 83.822

18 .526 1.947 85.769

19 .517 1.916 87.685

20 .479 1.776 89.461

21 .456 1.689 91.150

22 .438 1.622 92.772

23 .422 1.562 94.334

24 .411 1.523 95.857

25 .397 1.472 97.328

26 .376 1.393 98.721

27 .345 1.279 100.000

126

Interpretation

From the above table factors are estimated based on common variance. There are 27 items in

the scale. The first variance is 3.524, which is (3.524/27) or 13.053 % variance explained of

the total variance. Likewise second one accounts for 11.918 % of variance. In addition, the

first 5 accounts for cumulative 53% of total variance explained. Several considerations are

involved in determining the number of factors that are considered for further explanation.

They are a priori determination; determination based on Eigen value, determination based on

Scree plot, percentage variance explained, determination based on split half reliability and

significance test.

TABLE 23 : FACTOR LOADING

Components

F 1 F2 F3 F4 F5

Dynamic 0.787421

Creative 0.724674

Optimistic 0.608829

Prudent

0.50558

Hard 0.555567

Cold 0.470714

Caring 0.483388 0.432263

Rational 0.579305

Generous 0.623894

Empathetic 0.741987

Close 0.456301

Elegant

Class 0.619215

Serene 0.570611

Calm 0.54621

Product image 0.633578

Efficient 0.648899

Rapid 0.496024 0.562492

Low cost

Prevents

recurrence 0.69499

No side effects 0.633154

127

Brand status 0.609617

It is a reference

point 0.59077

High reputation 0.501606

Superior quality 0.724168

Major product 0.740344

Prescription

0.635913

Interpretation

Interpretation is facilitated by identifying the variables that have large loadings on the same

factor. The factors are interpreted in terms of variables that load high on it. The other method

available is to plot variables using the factor loadings as coordinates. The first method is

followed to define factor.

Five personality dimensions are named as

1. Sincere

2. Professional

3. Innovative

4. Eminent

5. Competent

Ries and trout (1969) stressed the importance of positioning in order solidify the branding

process in the mind of one‘s consumer, marketers focused on specific ―character‖ traits when

promoting their products. Whether perceived or developed, brand personality (BP) has been

studied regarding its use and effectiveness for decades (e.g., de chernatony, 2001; Keller,

2003). With its academic exploration stemming from Aaker‘s (1997) original five dimensions

of brand personality (Sincerity, Excitement, Competence, Sophistication, Ruggedness) .This

phenomenon has provided marketers with the ability to examine marketing practices , finding

128

that matching the characteristics of the brand with those of its endorsers and consumers tend

to be more effective (e.g. Kamins 1990, Lynch & Schuler, 1994) .

In the present data the five factors identified is sincerity, professional, Innovative, eminent

and competent. Before we position these four with respect to company names, the

significance of difference among them is studied.

The purpose of a t test is to assess the likelihood that the means for two groups are sampled

from the same sampling distribution of means. The purpose of an ANOVA is to test whether

the means for two or more groups are taken from the same sampling distribution. Purpose of

MANOVA is to test whether the vectors of means for the two or more groups are sampled

from the same sampling distribution. There are two major situations in which MANOVA is

used. The first is when there are several correlated dependent variables, and the researcher

desires a single, overall statistical test on this set of variables instead of performing multiple

individual tests. The second, and in some cases, the more important purpose is to explore

how independent

Variables influence some patterning of response on the dependent variables.

7.4.2.2 Hypothesis for difference in Personality Dimensions.

The personality dimensions found out, that is, Sincere Professional Innovative Eminent

Competent are checked on analysis of variance, the hypothesis formulated as below,

H1: There is a difference in the dimensions Sincere, Professional, Innovative, Eminent and

Competent

129

TABLE 24 : ANOVA TABLE FOR PERSONALITY TRAIT SINCERE

Sum of

Squares Mean Square F Sig.

Between Groups 289.080 41.297 1.091 .0367

Within Groups 31942.648 37.847

Total 32231.728

Sincerity differs across all the eight companies. And the difference is found out significant at

0.05.

TABLE 25 : ANOVA TABLE FOR PERSONALITY TRAIT PROFESSIONAL

Sum of


Between Groups 580.523 82.932 4.824 .000


Total 15245.951

Trait ‗professional‘ differs across all the eight companies. And the difference is found out

significant at 0.05.

TABLE 26: ANOVA TABLE FOR PERSONALITY TRAIT INNOVATIVE

Sum of


Between Groups 110.413 15.773 1.866 .0414

130


Total 8690.026

Trait ‗Innovative‘ differs across all the eight companies. And the difference is found out


TABLE 27: ANOVA TABLE FOR PERSONALITY TRAIT EMINENT

Sum of


Between Groups 365.709 52.244 5.554 .000


Total 8671.666

Trait ‗Eminent‘ differs across all the eight companies. And the difference is found out


TABLE 28: ANOVA TABLE FOR PERSONALITY TRAITS

Sum of


Between Groups 97.614 13.945 1.875 .0403


Total 7963.304

Interpretation: F test statistics is used to find out difference in the groups and to check for

variances. Sincere, Professional, Innovative, Eminent and Competent are found to

significantly different from each other. All other dimensions are significant 0.05.

131

An ANOVA gives one overall test of the equality of means for several groups for a single

variable. The ANOVA will not tell you which groups differ from which other groups. The

MANOVA gives one overall test of the equality of mean vectors for several groups.

However, it cannot tell you which groups differ from which other groups on their mean

vectors. In addition, MANOVA will not tell you which variables are responsible for the

differences in mean vectors. (Gregory Carey, 1998)

By observing the following table, it is very clear that there is a significant difference in the

groups with respect to various variables.

7.4.2.3 Positioning Map of Pharmaceutical companies among physicians

This study measured the brand positioning of the banks by conducting discriminant analysis.

Eight brands are compared on five brand dimensions. The categorical data is used as a

dependent variable here in this situations eight pharma companies are nothing but nominal

data points (Categories),and the individual dimensions are used as a independent variables. A

perceptual map is drawn based on the output of this variable. The two axis X and Y are

nothing but Function 1 and function 2 obtained after grouping of independent variable.

TABLE 29: MULTIVARIATE TESTS

Effect Value F Sig.

Company

name

Wilks' Lambda

.028 98.293 .000

a The statistic is an upper bound on F that yields a lower bound on the significance level.

b Design : Company name

132

Inference: The significance of the discriminant model is provided by the value of Wilk‘s

Lamda Value nearing zero indicates better fit of the study.

TABLE 30: WILKS' LAMBDA

Test of

Function(s)

Wilks'

Lambda

Chi-

square df Sig.

1 through 5 .864 104.897 35 .000

2 through 5 .956 32.414 24 .117

3 through 5 .978 16.121 15 .374

4 through 5 .993 5.122 8 .744

5 .999 .523 3 .914

From the above table it is clear that Wilks‘ lambda is significant at function one and five .

these functions are selected while making a positioning map.

TABLE 31: CANONICAL DISCRIMINANT FUNCTION COEFFICIENTS

Function

1 2 3 4 5

Sincere -.089 -.057 .010 .212 .100

Professional .169 -.264 .174 -.111 -.081

Innovative .090 .281 -.018 .097 -.369

Eminent .282 .199 -.143 .001 .260

Competent -.280 .164 .213 -.259 .077

(Constant) -2.033 -1.520 -4.368 -1.801 -1.138

Inference: Significance of discriminant function

133

To test the null hypothesis of equal group centroids, both the functions are considered

simultaneously .It is possible to test the means of the functions successively by testing all

means simultaneously. Out of seven functions first and fifth were significantly discriminating

the groups and are therefore considered for mapping. Wilks‘ Lamda is found significant at

0.05 level of significance.

TABLE 32: CANONICAL DISCRIMINANT FUNCTION COEFFICIENTS

Dimensions Function 1 Function2

Sincere -0.0890 0.1001

Professional 0.1688 -0.0806

Innovative 0.0899 -0.3691

Eminent 0.2822 0.2603

Competent -0.2795 0.0773

In the above mentioned table the functions which are significant are considered while plotting

it for scatter gram. The Scatter gram plot which is drawn with the help of SPSS output has

two axis X and Y which is function 1 and function 2. Similar interpretation can be obtained

by territorial map.

TABLE 33 : FUNCTIONS AT GROUP CENTROIDS

Company Name

1 2

Ranbaxy 0.583 0.151

134

Cipla

0.604 -0.243

Glaxosk

0.467 0.122

Sun

0.233 -0.002

Dr.Reddy

-0.444 0.039

Lupin

-0.46 0.087

Cadila healthcare

-0.529 -0.011

Aventis

Pharma

-0.358 -0.141

Interpretation:

The table above provides values of each company on two axes which are plotted with

functions selected that is first and fifth. Cannonical discriminant function coefficients and

functions at group centroids given n the table were used in prepare the perceptual map, which

also is called combined plot in SPSS.

Positioning map: For selected 8 companies group centroids are plotted on x and y axis.

After this personality dimensions found are plotted considering fuctions1 and 2 as axis

X and Y.

On the next page of data analysis positioning map is placed.

135

GRAPH 6: BRAND POSITIONING OF PHARMACEUTICAL COMPANIES AMONG PHYSICIANS

Sincerity

Professional

Innovative

Eminant

Competent

Ranbaxy

Cipla

Glaxosk

sun

Dr.Reddy

Lupin

cadila healthcareAventis pharma

-0.5

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

-0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1 1.2

136

Interpretation: Ranbaxy and Glaxosk are perceived higher on two dimensions of sincerity

and eminence. As they are closely located in the X-Y plot it also can be inferred that

physicians perceive them similar to each other.

Dr. reddys , cedilla health care and Aventis are loading together which indicates that thse

very strong and competent brands. Also physicians perceive them similar. Lupin is away

from y axis which means that it is not perceived Eminent and sincere by the physicians.

Sun , Cipla have scores near to axis suggests that they are they are perceived competent . The

same is applicable to Dr. reddys.

7.4.3 Understanding “Trust dimension” of Pharmaceutical Companies

The trust scale composed of 11 items over three dimensions. The three-factor model,

representing reliability, honesty and altruism dimensions showed an adequate fit via

confirmatory factor analysis .Hess in 1995 has formulated three factor models, representing

the reliability, honesty and altruism dimensions via confirmatory factor analysis.

TABLE 34: RELIABILITY STATISTICS FOR PERCEIVED TRUST CONCEPT

Cronbach's Alpha

Cronbach's Alpha Based on

Standardized Items N of Items

0.775 .779 11

Cronbach‘s alpha estimate of internal consistency is 0.775 for the entire data set. This

indicates a good consistency in the scale. The scale basically consists of Reliability, Honesty,

Altruism which measures trust.

137

7.4.3.1 Descriptive and graphical representation of trust

11 statements that studied trust for companies are placed below. The descriptive and visual

statistics is placed in the form of tables and graphs.

Statement1 - Interested more than just manufacturing product and making a profit.

TABLE 35: ALTRUISM-1

Company Name Frequency Percent

1 Ranbaxy 185 39.9

2 Cipla 67 14.4

3 Glaxo 57 12.3

4 Sun 40 8.6

5 Dr. Reddy 36 7.8

6 Lupin 21 4.5

7 Cadila 6 1.3

8 Aventis 45 9.7

Total 457 98.5

Trust plays a vital role for developing and maintaining brand loyalty. Trustworthiness and

kindness of the object are areas of trust. From the above table it is clear that physicians find

more trust in terms of confidence and selflessness in Ranbaxy.

138

Statement2-There are no limits to how Far company will go to solve a problem I might

have

TABLE 36 : ALTRUISM-2


1 Ranbaxy 157 33.8

2 Cipla 90 19.4

3 Glaxo 83 17.9

4 Sun 74 15.9

5 Dr. Reddy 6 1.3

6 Lupin 22 4.7

7 Cadila 3 0.6

8 Aventis 22 4.7

Total 457 98.5

Trust is also built on competency of the brand to solve the problem to meet the need. Ranbxy

again has got maximum count on this altruism parameter.

Statement3-Company is genuinely committed to my satisfaction.

TABLE 37: ALTRUISM-3


1 Ranbaxy 152 32.8

2 Cipla 83 17.9

139

3 Glaxo 58 12.5

4 Sun 80 17.2

5 Dr. Reddy 30 6.5

6 Lupin 20 4.3

7 Cadila 6 1.3

8 Aventis 28 6

Total 457 98.5

Ongoing satisfaction, which is required for trust to develop, results from consistent

satisfaction with individual transactions over time. Satisfaction from the company‘s product

is important factor in generating trust.

Statement4-Company will do whatever it takes to make me happy

TABLE 38 : ALTRUISM-4


1 Ranbaxy 86 18.5

2 Cipla 93 20

3 Glaxo 49 10.6

4 Sun 158 34.1

5 Dr. Reddy 38 8.2

6 Lupin 18 3.9

7 Cadila 6 1.3

8 Aventis 9 1.9

Total 457 98.5

140

Physicians found SUN companies initiatives better than others to make them happy.

Statement5-Company product Brochure, I believe the information in it is accurate.

TABLE 39: HONESTY-1


1 Ranbaxy 98 21.1

2 Cipla 79 17

3 Glaxo 172 37.1

4 Sun 12 2.6

5 Dr. Reddy 36 7.8

6 Lupin 7 1.5

7 Cadila 7 1.5

8 Aventis 46 9.9

Total 457 98.5

Reputation of the company is nothing but trustworthiness, integrity and honesty. According

to the study it is found that product brochure of Glaxo is found more accurate by

respondents.

Statement6- Most of what company says about its product is true

TABLE 40: HONESTY-2


1 Ranbaxy 82 17.7

2 Cipla 141 30.4

3 Glaxo 102 22

141

4 Sun 47 10.1

5 Dr. Reddy 24 5.2

6 Lupin 9 1.9

7 Cadila 10 2.2

8 Aventis 42 9.1

Total 457 98.5

Product performance is the primary indicator of trust and the functional or exchange aspects

of the relationship. For Ciplas and Glaxos products claims are found true.

Statement 7- I think some of company claims about its products are puffed up to make

them seem better than they really are

TABLE 41: HONESTY-3


1 Ranbaxy 151 32.5

2 Cipla 40 8.6

3 Glaxo 55 11.9

4 Sun 52 11.2

5 Dr. Reddy 28 6

6 Lupin 58 12.5

7 Cadila 40 8.6

8 Aventis 33 7.1

Total

142

Statement 8-If company makes claim or promise about its products, it is probably true

TABLE 42: HONESTY-4


1 Ranbaxy 74 15.9

2 Cipla 74 15.9

3 Glaxo 161 34.7

4 Sun 26 5.6

5 Dr. Reddy 40 8.6

6 Lupin 12 2.6

7 Cadila 10 2.2

8 Aventis 60 12.9

Total 457 98.5

Statement 9-Company is very reliable.

TABLE 43: RELIABILITY-1


1 Ranbaxy 147 31.7

2 Cipla 76 16.4

3 Glaxo 75 16.2

4 Sun 45 9.7

5 Dr. Reddy 34 7.3

6 Lupin 36 7.8

7 Cadila 6 1.3

8 Aventis 38 8.2

143

Total 457 98.5

Statement 10-I feel I know what to expect from company.



1 Ranbaxy 149 32.1

2 Cipla 88 19

3 Glaxo 22 4.7

4 Sun 89 19.2

5 Dr. Reddy 41 8.8

6 Lupin 35 7.5

7 Cadila 6 1.3

8 Aventis 27 5.8

Total 457 98.5

Physicians are confident about the Ranbaxy‘s products and know what to expect when they

prescribe anew product from the same company. The assurance reflects trust in the product

and they find the company reliable.

Statement11- If I prescribe another medicine from company, I feel I know what to

expect.



1 Ranbaxy 73 15.7

2 Cipla 74 15.9

3 Glaxo 41 8.8

144

4 Sun 120 25.9

5 Dr. Reddy 30 6.5

6 Lupin 78 16.8

7 Cadila 10 2.2

8 Aventis 31 6.7

Total 457 98.5

GRAPH 7: ALTRUISM 1

After going through the secondary data on companies and the successful brands the major

brands were from Ranbaxy, which were contributing to sales. The reason for enjoying good

sale is the trust that physicians experience while prescribing it. Altruism as explained by Hess

in 1995 , in the scale developed for measuring trust the interest of the company in not only

the product of interest but also in other activities.

Ranbaxy Cipla Glaxo Sun Dr. Reddy Lupin Cadila Aventis 0

50

100

150

200

Frequency

185

67 57

40 36 21

6

45

Interested more than just manufacturing product and making a Profit. (Altruism)

145

GRAPH 8: ALTRUISM 2

From the above chart, it is clear that these companies have philanthropically approach and

they don‘t just function for making profit. This is the result of how these companies are

positioned in the physicians mind. 88% of the respondents have found altruism a very

prominent reason for trust for the company.


50

100

150

Frequency

157

90 83

74

6 22

3 22

Graph No.: There are no limits to how Far company will go to solve a Problem I might have (Altruism)

146

GRAPH 9: ALTRUISM 3

From the above bar chart, it is clear that respondents here are satisfied, and that is the result

of the commitment the company is showing for the physicians. Again, the commitment part is

reflected more from Ranbaxy, Cipla, Glaxo and Sun.


50

100

150

Frequency

152

83

58

80

30 20

6

28

Graph No.: Company is genuinely committed to my satisfaction (Altruism)

147

GRAPH 10: ALTRUSM 4

Around 35% of the respondents feel that Sun pharmaceutical, Ranbaxy and Cipla will

practice whatever pleases physicians.


50

100

150

Frequency

86 93

49

158

38

18 6 9

Company will do whatever it takes to make me Happy (Altruism)

148

GRAPH 11: HONESTY 1

The message transformation in medical marketing happens through brochure. According to

32 % of the respondents the information provided by Glaxo is accurate.

Ranbaxy Cipla Glaxo Sun Dr. Reddy Lupin Cadilla Aventis 0

50

100

150

200

Frequency

98 79

172

12

36

7 7

46

Company product Brochure, I believe the information in it is Accurate

149

GRAPH 12: HONESTY 2

What company says about its product is true, for this statement Cipla followed by Glaxo and

Ranbaxy got maximum responses. From all these visual statistics the inferences for trust

generates satisfaction through sales can be formed.


30

60

90

120

150

Frequency

82

141

102

47

24 9 10

42

Most of what company says about its product is true (Honesty)

150

GRAPH 13: HONESTY 3

The above statement was reverse coded to understand the actual responses. Whereas Ranbaxy

scored more than others, rest of the companies scored almost same score from the responses.


50

100

150

Frequency

151

40 55 52

28

58

40 33

I think some of company claims about its products are puffed

up to make them seem better than they really are(Honesty)

151

GRAPH 14: HONESTY 4

The above statement was reverse coded to understand the actual responses. Whereas Ranbaxy

scored more than others, rest of the companies scored almost same score from the responses.


50

100

150

200

Frequency

74 74

161

26 40

12 10

60

If company makes claim or promise about its products, it is

Probably true (Honesty)

152

GRAPH 15: RELIABILITY 1

Here for the dimension Reliability physicians found Ranbaxy more reliable as compare to

other companies. This suggests that the performance of the products is consistent over the

time.


30

60

90

120

150

Frequency

147

76 75

45 34 36

6

38

Company is very reliable (Reliability)

153


Repeat prescription will generate the same result and Physicians are confident about result

and expectations by prescribing products from these majors.


30

60

90

120

150

Frequency

149

88

22

89

41 35

6

27

I feel I know what to expect from company. (Reliability)

154


According to the physicians, when they prescribe the new product of the same company they

know what to expect from them.

This section on data analysis of the thesis elaborated about measuring Brand awareness,

hypothesis testing, and Brand positioning and Brand trust. The finding of the study which has

emerged from this chapter is discussed in the next chapter.


20

40

60

80

100

120

Frequency

73 74

41

120

30

78

10

31

If I prescribe another medicine from company, I feel I know

what to expect(Reliability)

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