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i
Emerging Trends and Challenges in the Use of ICTs for Better
Access to Agricultural Information in the Punjab, Pakistan
By
Muhammad Hammad Raza
M.Sc. (Hons.) Agri. Extension
Reg. No. 2010-ag-602
A thesis submitted in partial fulfillment of the requirements for the degree of
DOCTOR OF PHILOSOPHY
IN
AGRICULTURAL EXTENSION
INSTITUTE OF AGRI. EXTENSION AND RURAL DEVELOPMENT,
FACULTY OF SOCIAL SCIENCES,
UNIVERSITY OF AGRICULTURE,
FAISALABAD
2019
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DEDICATED
TO
MY MOTHER
A mother is a personality who shows you the light when you just see the dark
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ACKNOWLEDGEMENT
All praises and thanks are for Almighty Allah, the Merciful, the only Creator of
the universe and the source of all knowledge and wisdom, who blessed me with health,
thoughts, talented teachers and helping friends.
I offer my humblest thanks to the Holy Prophet Hazrat Muhammad (Peace Be
Upon Him), whose moral and spiritual teachings enlightened my heart, mind and
flourished my thoughts towards achieving high ideas of life.
I feel highly privileged to express my gratitude to my sincere and honorable
supervisor Dr. Ghazanfar Ali Khan, Assistant Professor, Institute of Agricultural
Extension and Rural Development for his keen interest, untiring guidance, creative
criticism and sympathetic attitude throughout the study.
With deep sense of honor, I wish to express my sincere gratitude to Dr. Babar
Shahbaz, Associate Professor, Institute of Agricultural Extension and Rural
Development for his inspiring help, proper guidance, keen interest and sympathetic
attitude during writing and completion of the thesis. Sincere and special thanks to Dr. M.
Farrukh Saleem, Associate Professor, Department of Agronomy, for his cooperation and
valuable suggestions in the completion of thesis.
I do not have words at command to express my gratitude and profound admiration
to Family for consistent encouragement and cordial cooperation, I also gratefully
acknowledge the company of my friend Saleem Ashraf who gave me not only his
excellent cooperation but also a lot of smiles and enjoyable moments throughout my
study period.
Muhammad Hammad Raza
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3.7.2 Pre-testing 36
3.7.3 Reliability 36
3.8 Data collection 37
3.8.1 Interviews of farmers 37
3.8.2 Interviews of extension field staff 37
3.9 Data analysis 37
3.10 Difficulties faced during data collection 37
CHAPTER 4 RESULTS AND DISCUSSION 39
4.1 Demographic characteristics of the respondents 39
4.1.1 Age 39
4.1.2 Education 40
4.1.3 Size of landholding 41
4.1.4 Tenancy status 42
4.1.5 Source of income 43
4.1.6 Area under cultivation 44
4.1.7 Major crops 45
4.1.8 Minor crops 45
4.1.9 Vegetables cultivation 46
4.1.10 Fruit orchards 47
4.1.11 Sources of information 47
4.2 Current use of different ICTs 49
4.2.1 Possession of ICTs 49
4.2.2 Extent of use of ICTs 50
4.2.3 Purpose of using ICTs 51
4.2.4 Use of ICTs for agricultural information 52
4.3 Emerging trends of ICTs regarding agricultural information
dissemination 54
4.3.1 Obtaining various kind of information from ICTs 59
4.3.2 Preferred ICTs of respondents 61
4.3.3 Preferred language for agricultural information 62
4.4 Assessment of effectiveness of ICTs as a source of agricultural
information 63
4.4.1 Effectiveness of ICTs as a source of agricultural information 63
4.4.2 Preference for getting agricultural information from ICTs 67
4.5 Challenges faced by the respondents regarding the use of ICT 69
4.6 Training needs of respondents regarding effective use of ICTs 73
4.7 Relationship between the independent (demographic
characteristics) and dependent (use of ICTs) variables 74
4.7.1 Relationship between demographic characteristics and using
ICTs for obtaining agricultural information 74
4.7.2
Relationship between demographic characteristics of
respondents and their future preference for ICTs for obtaining
agricultural information
77
CHAPTER 5 SUMMARY, CONLUSIONS AND RECOMMENDATIONS 79
5.1 Summary 79
5.2 Findings 80
5.2.1 Demographic characteristics 80
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5.2.2 Farming status among respondents 80
5.2.3 Information sources 81
5.2.4 Current use of different ICTs 81
5.2.5 Familiarity of ICTs regarding the agricultural information
dissemination 82
5.2.6 Preferred ICTs 83
5.2.7 Effectiveness of ICTs as information source 83
5.2.8 Challenges faced by respondents regarding use of ICTs 84
5.2.9 Training needs of farmers regarding ICTs 84
5.2.10 Correlation between demographic characteristics and use of
ICTs 85
5.3 Conclusions 85
5.4 Recommendations 86
5.4.1 Department of Agriculture (Extension & AR) Punjab 86
5.4.2 Educational institutions 87
5.4.3 Cellular companies 87
5.4.4 Media 87
5.4.5 For future research 87
REFERENCES 89
APPENDIX-1 (Data tables) 119
APPENDIX-2 (Data collection tools) 130
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LIST OF TABLES
Table No. Title Page No. 1.3 Use of ICTs by private companies for extension work 07
4.1 Age of respondents 40
4.2 Education of respondents 41
4.3 Landholding of respondents 42
4.4 Tenancy status of respondents 43
4.5 Income source of respondents 44
4.6 Area under cultivation of respondents 44
4.7 Major crops grown by respondents 45
4.8 Minor crops grown by respondents 46
4.9 Vegetable crops grown by respondents 46
4.10 Fruit orchards grown by respondents 47
4.11 Respondents’ distribution according to their major source for getting
agricultural information 48
4.12 Respondents’ distribution according to their possession of ICTs 49
4.13 Respondents’ distribution according to the extent of use of ICTs 50
4.14 Respondents’ distribution according to their purpose of using ICTs 51
4.15 Respondents’ distribution according to extent of ICTs use for obtaining
agricultural information 53
4.16 Respondents’ familiarity regarding radio/FM based agricultural
programmes 54
4.17 Respondents’ familiarity regarding TV based agricultural programmes 55
4.18 Respondents’ familiarity regarding internet based agricultural
information dissemination services 56
4.19 Respondents’ familiarity regarding mobile (apps & helpline) based
agricultural information dissemination services 57
4.20 Respondents’ familiarity about toll-free helpline services (public &
private) regarding agricultural information dissemination 58
4.21 Various kinds of information obtained from ICTs by respondents 59
4.22 Extent of future preference given by respondents to various ICTs for
getting agricultural information 61
4.23 Language preference of respondents for getting agricultural
information from various ICTs 62
4.24 Effectiveness of ICTs as sources of agricultural information for
respondents 64
4.25 Preferred areas of agriculture by respondents for getting information
from ICTs 68
4.26 Extent of challenges faced by respondents regarding the use of ICTs 70
4.27 Respondents’ skill level and training needs to use ICTs 73
4.28 Correlation between demographic characteristics and using ICTs for
obtaining agricultural information 75
4.29 Relationship between demographic characteristics and their future
preference for ICTs for obtaining agricultural information 77
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LIST OF FIGURES
Figure No. Title Page No.
3.1 Map of the Punjab province 32
3.2 Map of the study districts 33
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LIST OF ABBREVIATIONS
AD Assistant Director
AMIS Agriculture Marketing Information System
AOs Agriculture Officers
APPs Applications
AR Adaptive Research
BDS Basic Democracies System
DAI Directorate of Agriculture Information
DB Data Bank
Ext. Extension
f Frequency
FA Field Assistant
FFS Farmer Field School
FFC Fauji Fertilizer Company
GDP Gross Domestic Product
ICT Information Communication Technology
ICTs Information Communication Technologies
ID Identification
IRDP Intergraded Rural Development Programme
Km Kilometer
L&DD Livestock and Dairy Development
n Sample size
NGOs Non-Governmental Organizations
PTA Pakistan Telecommunication Authority
TV Television
PAH Punjab Agriculture Helpline
PTV Pakistan Television
PWP People Works Programme
RWP Rural Works Programme
SMS Short Message Service
Std. Dev. /SD Standard Deviation
T&V Training and Visit system
US United States
UN United Nations
V-AID Village Agricultural and Industrial Development Programme
xiv
ABSTRACT Being informed about agricultural innovations is imperative for farmers to cope with
complex challenges of farming. Information dissemination from research to farmers is an
integral phenomena to lead technological awareness among farmers. Therefore, access to
timely and accurate information is a need of farmers to become aware of the latest
agricultural information for agricultural development. There are different information
sources including traditional and modern media being utilized by farmers to nurture
themselves with updated information. Among traditional sources, fellow farmers,
extension field staff, radio and TV are more prominent as perceived by farmers. However,
information received through these sources is considered partially effective and
surrounded with constraints of cost, broadcasting, efficacy and relevancy. Inception of
Information Communication Technologies (ICTs) rendered a new horizon to the
information dissemination process bearing potential of sharing information among large
communities in no time. This esteemed technology reduces the cost and enhances the
access and efficacy ultimately. With the passing moments, users of these technologies are
uprising. integration of ICTs in extension services could uplift the standards of services
and access to information as compared to traditional sources. However, farmers may be
facing many challenges in the use of these ICTs because of illiteracy or other factors.
Therefore, it was considered essential to investigate the emerging trends and challenges in
the use of ICTs and training needs of the users. For this purpose, a total of 400
respondents were selected through simple random sampling technique from two districts
of the Punjab province. Data were collected through face to face interviews. Collected
data were analyzed using Statistical Package for Social Sciences (SPSS). According to
the findings regarding information sources, fellow farmers (71%) and mobile (60.3%)
were prominent while websites, helplines and newspapers were least choices. Possession
of ICTs appeared varied, however, mobile phones at highest possession and extensive
utilization (mean=4.61). Use of websites, helplines, internet and computers was
negligible. Awareness of ICT based services appeared average, however, information on
crop production, protection, marketing, weather updates and livestock management was
preferably accessed by farmers. Moreover preference of mobile phone was unveiled
dominating (mean=3.86) because of being more effective as better agricultural
information source (mean=4.17), source of improving farming skills (mean=4.12), source
of accurate information (mean=3.96), better communication (mean=4.05) and timely
information (mean=4.32,) as compared to all other ICT tools. Effectiveness of other tools
was restricted due to extensive cost (mean=3.75), inadequate education (mean=3.65) and
accessibility to internet (mean=3.23). Study further highlighted highest training needs of
farmers regarding use of helplines, internet, websites (mean=3.21) and computers
(mean=2.83). Study summarized that overall use of ICTs was below average except
mobile phone. It can be stated that ICTs have a great potential which has not been
achieved so far. There existed negative relationship between age of respondents and use
of internet, computer, social media, landline phone, agri. helpline and agri. website for
obtaining agricultural information. Furthermore, a significant positive relationship was
found between education of farming community and use of various ICTs. Pearson
correlation coefficient shows significant and negative relation between age of farmers and
their preference to TV and agri. helpline for obtaining agricultural information in future.
In addition, a significant positive relationship was found between education of farming
community and future use of various ICTs.
1
CHAPTER 1 INTRODUCTION
1.1 Status of agriculture in Pakistan
Agriculture is the largest and dominant sector for growth and development of Pakistan’s
economy. The country’s economy is profoundly dependent on agriculture sector with
18.9% contribution to Gross Domestic Product (GDP). About 42.3% of the labour force
comes from agriculture and livelihood for 60% of the population in Pakistan is heavily
dependent upon agriculture (Govt. of Pakistan, 2018). The agriculture sector has four
further sub-sectors: i) crops ii) livestock iii) fisheries and iv) forestry. The crops sub
sector contributes 23.85%, livestock 58.33%, fisheries 2.12% and forestry 2.33% in
agriculture (ibid). Unfortunately, the share of agriculture in GDP is down falling with
each passing year. Share of agriculture in GDP in 2005-06 was 24% while in 2016-17 it
has gone down to 19.5% (ibid). Average production of major crops i.e. rice, wheat,
cotton, maize and sugarcane is lower as compared to global nations (Ahmad, 2015).
About 53-82% yield gap in Pakistan as compared to other countries was unveiled by
Kamal et al. (2012). This poor production level is attributed to numerous constraints.
Across the country, subsistence farming is a leading constraint, as majority of the growers
are small landholders with poor financial position (Sattar, 2012).
Traditional farming practices adopted by small farmers (Ali, 2010), high cost of
production (Khan, 2012; Sattar, 2012), inadequate awareness of modern production
practices (Jehangir et al., 2007), imbalanced use of inputs (Iqbal and Ahmad, 2005),
intensive cultivation (Hussain et al., 2003), diseases (Khan, 2012), poor economic status
of growers and injudicious use of pesticides (Planning Commission, 2012), partial
success of latest technologies (Sattar, 2012), soil salinization (Qureshi et al., 2008), water
logging (Aslam et al., 2008) and climatic variations (Sattar, 2012) were the prominent
factors hampering agricultural productivity across Pakistan. Apart from these limiting
factors, poor educational level and inadequate training options to boost farmers’
knowledge were noteworthy factors suppressing productivity (Masood et al., 2012).
Despite these obstacles, agriculture is still a chief sector, holding tendency to feed ever
increasing population and uplift economic liabilities of the country. To achieve full
potential of agriculture, extension advisory services to mitigate limiting factors are
inevitable in the country.
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1.1.1 The role of extension services
Increase in production of crops is directly linked with the familiarity of farmers with
agricultural innovations developed by the research organizations. Agricultural extension
has prime role of creating awareness and fostering adoption of latest technologies
(Davidson et al., 2005). It refers to the knowledge enhancement among rural dwellers in a
non-formal way which is in practice across the nations to raise adoption of agricultural
innovations (Betz, 2009) and systematic approach and facilitation presented by extension
organizations to facilitate farmers (Farooq et al., 2010). The aim of extension revolves
around the identification of farmers’ problems and providing solutions in their best
interest (Havrland and Kapila, 2000).
Agriculture extension had responsibility of technology transfer in the past, but landscape
of extension is beyond training, learning, helping farmers, and informing farmer groups.
In wider working sphere, extension takes initiatives to address the marketing issues and
joins hands to enter into partnerships with the wide-range of service providers and other
related organizations. Agricultural extension builds partnership with all those
organizations which are working for the facilitation of farming communities via
providing various services and inputs (Birnor et al., 2006).
In Pakistan, fast population growth requires significant increase in production; so,
extension services have responsibility for the development of agriculture in Pakistan with
information that enables farmers to make better decision in farming (Subedi and Garforth,
1996). Extension education is fulfilling specific tasks within their set objectives and
principles (Moayedi and Azizi, 2011). For instance, improving livelihood of the end users
through positive modification in behavior has been one of the key roles (Rivera and Alex,
2004). Agriculture extension has been using variety of extension education methods for
training of farmers and dissemination of agricultural innovations (Bajwa et al., 2010).
Extension has been emphasizing the significance of natural resources for the long-term
utilization, which is key for the sustainable rural development (Ikram-ul-Haq et al., 2009).
Strengthening the linkage between research and extension has been a priority of the
extension department. Extension department is on stride for the dissemination of
research-oriented findings developed by research sector to the farmers for their wellbeing.
Eneyew (2013) regarded linkage between research and extension department as a major
pillar of development and technology. Technology sharing and improving adoption is
major core concern of extension (Qamar, 2005).
3
Both public and private sector extension are working in Pakistan to bridge the production
gap. Considering these facts, a number of extension programs were implemented defining
the role of extension sector. Each program was technically sound with diversified
methods of information sharing, though the success rate of the programmes appeared
partial (Abbas et al., 2009). Some of the major programs were Village Agricultural and
Industrial Development (Village-AID) Programme, Basic Democracies System (BDS),
Integrated Rural Development Programme (IRDP), Rural Works Programme (RWP),
Inputs at Farmers’ Doorsteps Approach and Training and Visit (T&V) System.
Unfortunately these programmes have partial success pertinent to different factors
(Ahmad, 1999; Ahmad et al., 2000).
In the world, some changes are occurring due to various demand and supply factors. The
increasing demand of food and fiber is due to the demand driven factors. There is dire
need of innovation to tackle these changes. Innovation mainly involves in the extraction
of economic, ecosystem and knowledge, it also aims to improve the performance by
putting ideas, knowledge and technology in a systematic manner of working.
Dissemination of information and knowledge will become easier due to the development
of Information and Communication Technologies (ICTs). The provision of information
regarding agricultural sector will be revolutionized due to ICTs (David and Talyarkhan,
2005; World Bank, 2002).
1.2 ICTs and agriculture in Pakistan
Like many other countries of the world, Pakistan also has proactive and fast-growing
sector of information communication technologies (ICTs) to facilitate farmers (Shahbaz
et al., 2013) In recent years, Pakistan documented a productive pace in building ICT
infrastructure, promoting the educational perspectives of ICTs and making the adoption
cost effective and affordable. The policies developed by governments were user friendly
and favorable to promote innovations among the users. For instance, introduction of
mobile internet and enhanced access for the poor to information was major achievement
that telecommunication policy exerted.
For the last two decades, the mobile telecommunication sector showed exponential
growth at global level. According to the Kenny and Keremane (2007) extensive growth in
IT sector has led to significant influence on human life and fortified the economic
development indicators. Though, potential of ICTs is partially explored in the country,
4
but still, Pakistan is third fastest arising telecom market around the globe. Pakistan
embarked triple digit growth performance till 2007-08; growth was bit slower after then,
but, growth enjoyed the heights again in 2010 (PTA, 2010). King et al. (1994) stated that
diffusion of any innovation or technology in market is primarily dependent upon three
reasons i.e. consumers pull, service providers push, and both the aspects are tempted by
rules set by regulators. The role of Pakistan Telecommunication Authority (PTA) as a
regulator has been seen remarkable in keeping the growth goes in better fashion.
1.3 Agricultural extension and ICTs
Agricultural Extension is a bridge linking farming masses and research sector. The
primary purpose of agricultural extension is dissemination of latest research-based
findings to the end users for their well-being. For the positive results, effective extension
work must have effective communication as a leading requirement (Memon et al., 2014).
Extension department and agents are using different teaching and training methodologies
to convey their messages in an appropriate way. The techniques used are not only
traditional, but addition of modern technologies equipped with media tools has raised the
effectiveness of extension work.
Spotlight on the past made visible that individual, group and mass contact methods were
the main techniques adopted by the extension agents for information delivery. The listed
methods had limited scope in modern era where science and technology have prevailed to
large extent. Consequently, traditional methods were not able to meet the information
needs of the growers. Realizing the need, modern media have stepped in for saving time
and providing information effectively in short time. The technology named as ICTs which
brought a new horizon in agricultural sector. Chhachar et al. (2013) denoted ICTs as one
of the leading tools for development in third world nations where adoption of ICTs was
increasing in education and agriculture sector with new hopes of improvement.
Knowledge produced and shared with the use of ICTs could itself be a tool and
technology for development of agriculture sector. Meera et al. (2004) described that with
the rapid transitions in the world, role of agricultural extension is characterized as
essential mechanism for information sharing regarding modern cropping system.
However, for higher recognition, extension is in desperate need to escape from traditional
approach for information delivery. With the integration of ICTs, extension sector can be
more diversified, focused, knowledge intensive, effective and demand driven according to
the needs of the end users (Meera et al., 2004). This innovative integration can empower
5
farmers by presenting greater control and access over shared information at minimal cost
and increased approach.
ICTs are very helpful for extension agents to adopt and share improved production
practices to the end users (Chavula, 2014). It can also facilitate farmers in improving their
livelihoods and the quality of life by making better decisions. Use of ICTs enables
farmers to receive updated, authentic, relevant and timely information. It can address
farmers’ information needs and provide an opportunity of information sharing within the
farmer groups. The experiences shared can bring improvement in production through
effective management and prevention of losses. ICTs also enable farmers to find suitable
and profitable markets and enquiry about the buyer. In addition, through ICTs online
marketing of products is possible and practically easier (Azeem and Ali, 2015).
Directorate of Agricultural Extension, Government of the Punjab is a separate dedicated
directorate for agricultural related information sharing among farmers. Directorate itself
is equipped with audio visual production section followed by publication section.
Directorate is also possessing high quality audio recording facilities to record agricultural
related messages. Directorate holds wide collection of agricultural contents in audio,
video and printed format which are distributed and disseminated among farmers with the
help of extension force working in field. Directorate offers following facilities:
1.3.1 Punjab agricultural helplines:
Toll free Punjab Agriculture Helplines 0800-15000 and 0800-29000 are working for
facilitation of farmers. Helplines are active from 08:00 am to 08:00 pm. The ability of
computerized call recording of farmers followed by display of callers’ ID with time and
date facilitates in locating caller for quick response by experts on the same day. Farmers
are effectively utilizing this service and about 12000 phone calls are received/recorded
annually to whom quick response is ensured by concerned staff on same day (Govt. of
Punjab, 2014).
Directorate has also initiated SMS helpline for farmers. Farmers may submit their queries
at 0304-4000172 from any mobile network for getting desired information and solution of
their problems (ibid).
Directorate has further established “Robo calls”/voice and text messaging service for
farmers. About one million farmers are the users of this service and receiving latest
information on multiple aspects of farming (ibid).
6
1.3.2 Radio agriculture programmes:
Agriculture based programs are daily broadcasted from eight radio stations (Islamabad,
Rawalpindi, Multan, Lahore, Faisalabad, Sargodha, Bahawalpur, Mianwali) in the Punjab
province. Approximately, 3000 talks of agricultural technical experts, 1500 agricultural
messages, jingles and 2000 agriculture news bulletins are broadcasted annually from
these stations with coordination and collaboration of Directorate of Agriculture
Information, Punjab. On radio stations, some of the notable agriculture programs are;
“Zarkhaiz Pakistan” from Islamabad, “Khait Khait Haryali”, “Jithey Terey Hul Wagey
from Lahore, “Utum Khaiti” from Multan “Thall Singhar” from Mianwali, “Wasde
Rehn Gran” from Rawalpindi, “Wasda Raye Kissan from Sargodha, “Dharti Bakht
Bahar” from Bahawalpur, “Sandhal Dharti” from Faisalabad (ibid).
1.3.3 Television:
To educate farming communities regarding technical aspects of the farming, different
agricultural programs are broadcasted on TV channels. Annually, about one thousand
agricultural messages are shared on different TV channels. Additionally, for public
awareness, a number of agriculture programs are broadcasted on different channels. For
instance, a part of exclusive agriculture channel “Sohni Dharti”, program named as
“Khaiti” is broadcast on Rohi TV, “Zamindar” on Waseeb TV, “Haryali” on PTV
Home, “Kissan Time” at Channel 5, “Khait Punjab Dey” at Punjab TV and “Zarat
Nama” at ATV for farmers’ awareness (ibid).
1.3.4 Internet:
Directorate of Information is also committed to facilitate farmers through internet at web-
based services. Farmers can get their desired information by sending an email at
(dainformation@gmail.com/ziratnama@gmail.com). Department of agriculture is also
maintaining website [www.agripunjab.gov.pk] to serve farmers. Latest literature
regarding, production technologies and plans of major as well as minor crops, messages
for farmers and feature consisting of information regarding latest farmers’ packages are
available at website in local language “urdu”. Availability of contents in local language is
enhancing readership.
1.3.5 Mobile applications (Apps.)
Department of agriculture is executing use of mobile based apps for information access.
For instance, latest project of Government of the Punjab, “Agriculture Marketing
Information Service (AMIS) is facilitating farmers regarding update pricing of major, as
well as minor, crops of particular area. This service is not only web-based but also can be
installed on android phones as App “AMIS Punjab”.
7
1.3.6 Cellular services:
Different cellular services working in the country are harnessing opportunities for
farming communities through helpline-based services. For instance, Zong is offering
“Zong Kissan Portal” Warid “Warid Kissan Live”, Telenor “Khushal Zameendar”, Ufon
is offering “Ukissan” and Jazz offering “Bakhabar Kissan” service for farmers. Farmers
can call on these helplines and chat with experts to resolve their problems.
Use of ICTs for farmers is not only in use of public sector, but the private sector is also in
transition to facilitate farmers using these technologies (Table 1.3).
Table 1.3 Use of ICTs by private companies for extension work
Private Companies Focus of the Call Centre/Tele Marketing
Syngenta Very focused on tracking information. Track franchisee
sales, Track field activities, maintain framer (bigger and
medium size customers) contact to track satisfaction with
field activities. Farmer relationship management, specified
number of contacts must be made with a farmer in year.
Customers can call back for solution to problems. Customer
data bank (DB) is maintained. Agriculture graduates work as
expert under Community Supported Agriculture (CSA)
model.
FMC No call center. Customer DB is maintained.
Auriga Separate tele-centers for seed and pesticide business. Farmer
relationship management. Advise customers on use of
products on per season and area basis. Advise on farming
technology. Customers can call back. Very good visual aids
available to the call center agents. Customer DB is
maintained.
Ali Akbar Group
of Companies
Tele marketing centers in the field to cater to weather and
crop advisory alerts to a contact DB of 1000 farmers.
8
1.4 Problem statement
Each farmer should have equal access to information sources for getting desired
information. This access to information should be timely, cost effective, comprehensive
and irrespective of socio-economic conditions of the respondents. Disseminated
information should sustain authenticity of coded message. Being a key sector, Extension
Field Staff (EFS) should be equipped with latest knowledge and tools to disseminate
information well in time to farmers. However, information delivery system in Pakistan is
partially effective. Farmers are still reliant on traditional sources which are unauthorized
and less authentic indeed. Discrimination in information dissemination persists across the
country as progressive farmers are generally preferred by extension workers for
communication. EFS to farmers’ ratio is higher and extension staff is not able to
disseminate information among all farmers. Due to that, farmers’ access to information is
scanty and preference is given to traditional information sources (i.e. fellow farmers)
because of easy access. Other means of information like mass media are partially
effective due to several constraints including educational level, poor broadcasting,
irrelevant programs and one-way flow of information. Findings of several researches are
in agreement to asserted constraints, poor access, heavy reliance of farmers on traditional
sources and partial effectiveness of mass media in Pakistan (Muhammad and Garforth,
1999; Nazam, 2000; Barkat, 2002; Abbas et al., 2003; Muhammad et al., 2004;
Chaudhary et al., 2008; Saleem et al., 2010; Rehman et al., 2013; Ashraf et al., 2015 and
Yaseen et al., 2016). As a result, these obstacles slow the information delivery process.
Use of modified system could bridge the debated information gap as proposed by
Zappacosta (2001) and Nkwocha et al. (2009) that ICTs consist of digital and electronic
modes of capturing, sharing, processing, retrieving and storing information for
broadcasting through different media including mobile phone, social media, websites,
helplines, SMS, email, TV and radio among farmers to fill information gap. ICTs share
accurate, validated, complete, concise and dynamic information to vast number of farmers
equally irrespective of gender, education and age disparities. This tremendous potential
can become prime source of quick access to information through different gadgets (Isiaka
et al., 2009). Furthermore, use of ICTs can improve extension work, save time & cost and
enhances availability of information. The debate sums up that modern ICTs integration in
agriculture can be more fruitful as compared to traditional sources.
9
Although, the significance of ICTs is well recognized to improve information delivery
system among farmers, yet Pakistan is still behind many countries regarding use of ICTs
in agriculture. It is clear from aforesaid discussion that farmers are still relying on
traditional sources of information. It is need of the time that the farmers should be made
aware of emerging trends of modern information sources. For this purpose, assessment of
farmers’ knowledge about the emerging trends and challenges there of regarding the
effective use of various ICTs is deemed necessary. So, the present study was conducted to
explore emerging trends and challenges of ICTs in agriculture. This study will provide a
pathway to various stakeholders and extension agencies to effectively utilize the various
ICTs in delivery of agricultural advisory services to farmers.
1.5 Theoretical framework
Theory of diffusion of innovations (Rogers,1995; 2003), technology acceptance model
(Davis, 1989) and use and gratification theory (Katz et al., 1973) are utilized in this study
as the study is mainly emphasized on emerging trends, challenges and use of ICTs for
agriculture related information acquisition. Rogers (1995) illustrated that the process by
which information is disseminated through definite channel over time within social
system is termed as diffusion. Theory of innovations diffusion clarifies how innovative
ideas, technologies or practice are shared via different channels in succession. (Rogers,
2003). Theory of attention on chances of adoption of new ideas was based on varying
factors like evaluation of innovative technology, economic advantage, compatibility and
complexity of presented ideas.
In this theoretical framework another theory utilized is technology acceptance model
presented by Davis (1989) based upon theory of reasoned action (Fishbein and Ajzen,
1975). This particular theory infers that how beliefs and attitudes of adopters towards
innovation and final decision regarding use of particular technology are affected (Davis,
1989). According to Davis (1993) numerous external obstacles influence the behavioral
decisions. This particular theory was used by Shaw (2013) in investigation of adoption of
technological advances like email, voicemail, word processing and internet (Lederer et
al., 2000). Usefulness of this theory in agricultural communications and internet was also
documented by Irani (2000).
Uses and gratifications theory presented by Katz et al. (1973) is third theory adopted for
this research investigation. This theory speaks that how people adopt particular channel to
meet definite needs (Joinson, 2008). This idea spreads to business, groups and society as
a whole. However, typically this idea encompasses traditional media (print, radio,
10
television). This theory spread to different types of electronic media and social media
recently. This theory can determine that how respondents and audiences are engrossed to
a particular media (Katz et al., 1973) and how targeted respondents could be encouraged
to adopt emerging channels.
1.6 Objectives
The objectives of the study are as follows:
1.6.1 General Objective
To analyze the emerging trends and challenges in the use of ICTs for better access to
agricultural information in the Punjab, Pakistan
1.6.2 Specific Objectives
1. To explore the current use of different ICTs by the respondents
2. To explore the emerging trends of ICTs regarding the agricultural information
dissemination among the respondents
3. To assess the effectiveness of ICTs as a source of agricultural information for the
respondents
4. To identify the challenges faced by the respondents in the use of ICTs
5. To assess training needs of respondents regarding the effective use of ICTs
6. To compile research-based recommendations to promote ICTs culture in the rural
areas
1.7 Limitations
1. In this study general farmers were considered for data collection.
2. Reliability of data was depending upon the respondents’ interest and
understanding of research questions.
3. Research was limited to two districts of the Punjab (Muzaffarghar and Rahim Yar
Khan)
4. The study was further limited to 400 respondents of the selected districts
1.8 Assumptions
1. Respondents would cooperate and provide accurate information.
2. Interview schedule would be considered the accurate method for data collection
in this study.
3. Collected data would highlight the current trends and challenges regarding the
usage of various ICTs in the farming sector.
4. Outcomes of the study would be helpful for all stakeholders including farmers,
extension workers, researchers, policy makers etc.
11
CHAPTER 2 REVIEW OF LITERATURE
Literature review infers to “look again” at literature in correlated field. Literature review
is valued as it offers contextual knowledge on the problem intended to be investigated.
Additionally, review of the literature enables scientists to bridge the research gaps
(Punch, 2006). Hek and Moule (2006) viewed that literature review connects researcher
with previous work done related to planned investigation and helps in generating ideas for
methodology setting, alleviating duplication and hypothesis construction. This
investigation is predominantly focused on emerging trends of ICTs, hence researcher
exerted utmost effort to review published literature relevant to this research. The detailed
debate through literature review is described in this chapter.
2.1 Effective communication; concepts and definitions
There are different definitions of the communication described by different scholars and
researchers. Leagan (1961:125) stated that “communication is the process in which at
least two or more individuals, share and exchange their facts, ideas and feelings in a way
that every participant gains considerate of meanings, use of messages and contents”. The
entire procedure by which one mind influences the other, is communication (Shannan and
Weaver, 1949). Communication process transmits message from one individual to
another (Brooker, 1949). Communication is determined process involving source,
message, medium and receiver (Karuhanga et al., 2012). Andersch et al. (1969) define
communication as sharing of that message which can change the behavior of receiver in
the particular aspect. They also stated that communication is control of behavior through
descriptive motivations.
The communication is said to be effective when all the parties (sender and receiver) in the
communication, assign similar meanings to the message and listen carefully to what all
have said and make the sender feel heard and understood. Leagans (1961) illustrated that
for effective communication, sender, message, medium, treatment, audience and feedback
are the significant elements. Effective communication is generally a two-way process
demanding skills and efforts from sender and receiver simultaneously (Tourish, 2010;
Cheney, 2011). Lunenburg (2010) explained that communication is the process of
exchanging information and general understanding from one individual to another. For
effective communication understanding on both ends is vital. Sender and receiver are two
leading elements contributing more in making communication effective. Capability to
12
listen mainly boosts the communication process. Effective listening turns communication
effective (Kneen, 2011). To achieve effective communication, actual sender should
encode the factual information to establish connection with receiver (Anene, 2006).
Communication of agricultural information also improve the farm productivity
(Ahmadian et al., 2011). This effective communication is vital for dissemination of
information in agricultural sector (Anvari and Atiyaye, 2014).
2.2 Role of communication in agricultural development
Agriculture is the enterprise for the development of major chunk of population residing
on the globe. On one side, the population of the world is on rise, while on other side
improvement in growth of the agricultural sector has become inevitable. Agricultural
researchers and professionals identified the ways to alleviate problems prevailing in
agriculture and hampering the rural development. Since the inception of the “Green
Revolution” in 1960s, agricultural scientists have addressed global challenges like food
insecurity, poverty reduction, protection of environment, strengthening national
economies and most important in particular is the need of more food to achieve food
security. Recent emergence of devastating problems like climate change impacts and
energy concerns have raised the list of global challenges (FAO, 2008). To address these
ever-increasing problems, directly or indirectly relating to communication between the
researchers and stakeholders (extension service providers, farmers) is essential.
Moreover, in production process, communication mechanism in agriculture is of special
worth as well. Communication mechanism enables the stakeholders to connect with the
networks, knowledge and institutions essential to improve the food security and
employment opportunities for the development.
Ballantyne et al. (2010) highlighted the significant link between the scientific research,
communication and the development where dissemination of information, knowledge and
data were critical foundation for the sustainable agriculture and productive partnerships
within the global scientific community. Brierley (2009) and Holford et al. (2008)
regarded communication as primal to researchers’ professional life and the stakeholders
who are serving in benefiting manner. However, successful communication needs some
skills like professional recognitions and financial support. Both skills enable researchers
to gain some personal advantages to make communication successful (Yore et al., 2004).
Communication has dominating impacts on agriculture where the system is stratified into
different pillars i.e. highly qualified technology generation system (researchers),
13
comparatively well-educated and equipped technology dissemination system
(extensionists) and a bunch of technology utilization system (farmers) who are usually
less educated. Therefore, communication is generally assumed as the process of
information dissemination from a source to a receiver with the purpose to change the
attitude, knowledge and skill of the receiver (Adebayo, 1999). The FAO (2011)
documented the need of specific communication strategy to strengthen the research and
stakeholders’ association and participation in agricultural system. The report further
asked the field staff to cover all types of farmers, including “innovators”, “early
adopters”, “early majority”, “late majority” and “laggards” through different kind of
strategies to modify their attitude and to meet their needs.
The communication process between scientists and other stakeholders occurs in different
forms i.e. formally via research publications, informally through, face to face, group
meetings and via print media resulting in formulation of learning groups with common
interests (Garvey et al., 1971). Cruickshank (2002) was of the view that establishment of
formal groups exerted more benefits through encouraging professional communication
particularly in developing countries. He argued that communication and information
seeking are significantly influenced with the social process prevailing in community more
often spread over broader institutional distances. Barjak (2006) and Bjork (2005)
documented internet facility and email messaging as a pivotal informal communication
between local dwellers and global scientists seeking to serve widespread “knowledge
communities”. However, Bjork (2005) presented another view that informal and formal
communications were not mutually divided, resultantly; each can be applied at different
stages of single process i.e. publishing a scientific research journal article. Moemeka
(2000) conceptualized the communication by commenting that communication must be
interactive, sharing of ideas, focusing dialogues and mutual participation, developing the
opportunity of comprehension of numerous opinions and furnishing audience-oriented
response.
2.3 History of agricultural communication in Pakistan
Need of agricultural communication in Pakistan emerged with the foundation of country
in 1947. However, at that time extension department did not have separate identity. Due
to that, communications were made through different community development programs.
Numerous community development programs were implemented with the financial
assistance of US in India and Pakistan (Holdcraft, 1978). These programs were important
14
to build infrastructure and boost farm production to meet the requirements. Later, for
strengthening agricultural communications, the need of extension department was
recognized and the World Bank facilitated the inception of extension services (Gustafson,
1994). Conversely, efforts made to uplift rural income through improved farming and role
of communication in this regard were significant (Waseem, 1982). These extension-
oriented programs rendered necessary community services to rural peripherals. Among
these listed programs Village Agricultural and Industrial Development Programme (V-
AID), Basic Democracies System (BDS), Rural Works Programme (RWP), Integrated
Rural Development Programme (IRDP), People Works Programme (PWP) and Training
& Visit System (T&V) are prominent.
The foremost effort toward development was V-AID, implemented in 1952 (Mallah,
1997). The major objective of this initiative was community development in general and
solution of rural problems through community mobilization through local participation.
This initiative obliged as extension intervention of all nation building department at
village level. Within this approach, demonstration method was adopted to boost farmers’
confidence and to communicate need for adoption of updated practices to foster
production level (Chaudhry, 2002). During 1959, another modality named as BDS was
implemented for the community development. Attempt was made to engage agricultural
extension programs across the Punjab for economic, social and political development
through BD system, (Waseem, 1982, Chaudhry, 2002). Participation of local people in
community development efforts was the leading opportunity offered by BD system
(Mallah, 1997).
RWP was another effort to offer supreme participation of local people in planning and
implementation of development projects. This initiative further aimed to develop sense of
self help among participants (ibid). IRDP was a technocratic approach (Muhammad,
1994) to enhance living standards of rural people through collaboration of public sector
and intended beneficiaries (Govt. of Pakistan, 1983).
The government further implemented PWP in 1972 (Govt. of the Punjab, 1983). PWP
was much different from RWP in multiple ways as PWP included developmental schemes
in rural as well as urban areas through local people participation (Mallah, 1997 and
Cahudhry, 2002). This program communicated message of self-help and adjusting their
affairs, rather than depending on government (ibid). During 1961, a specifically
extension-oriented program, traditional agricultural extension system was introduced
which remained operational until 1978. Traditional extension system was generally a
15
technology transfer model for floating information from government to public. Thus, it
was referred as “Top-Down Extension System” (Govt. of Punjab, 1978; Malik, 1990).
Decisions were often made on top level and executed in field through front line workers
(Ali, 1991). Core responsibility of agricultural extension was to transfer related updated
and practical information to the public engaged in farming (Axinn, 1985).
T&V system was initially launched in 50 developing countries and was promoted and
monitored by the World Bank (Anderson et al., 2006). In Pakistan, this program was
initially launched in five districts of the Punjab in 1978, later it was introduced in Sindh
province in 1979. The focus was to develop strong coordination between framers,
research and extension workers by making a triangulation of the relationship. The
extension personnel under the T&V system were frequently trained and they were given a
fortnightly schedule to follow it strictly (Abbas et al., 2009). Regular farm visits were the
unique characteristic of this system. The major extension service providers under this
system were Field Assistants (FAs) that were supposed to deliver agricultural information
in their area. The EFS was bound to arrange exhibitions and field days for the farmers to
make them aware of the latest agricultural technologies. Initially the program achieved
success in some areas but could not give the desired results due to rigid schedule,
repetition of services, one-way flow of information, less technically trained staff, low
participation of farmers in meetings and lack of coordination among line departments
(ibid).
Farmer Field School (FFS) approach was highly participatory and capacity building
practice for farming masses (Khisa, 2003). FFS employed a number of practices for
communication including group discussions, lectures, demonstrations literature etc.
(Hussain, 2004). FFS was a paradigm shift in extension as participatory methodology,
which boosted farmers’ practical, critical skills and creativity (Kenmore, 2009).
In 2001, another modality known as decentralization was implemented in replacement of
T&V system. Ali et al. (2003) argued that this decentralized system is still a modified
form of T&V being top-down and autocratic with numerous limitations. This system
rendered supplementary feedback on farmers’ issues to EFS (Ashraf et al., 2009). But,
being autocratic, top down, large farmers oriented, less female participation and less
involvement of youth made decentralization inefficient (Farooq and Ishaq, 2005; Khushk
and Memon, 2004).
16
2.4 Challenges in agricultural communication
Regardless that communication in agriculture is inevitable, there are several constraints
hampering the process of efficient and cost-effective communication of scientific
information. Souter (2010) unveiled that sluggish infrastructure, inadequate human skills
to utilize networks and available services, high cost of communication tools, ineffective
policies and regulatory environments were the prominent constraints in the way of
agricultural communication. These prevailing factors were obstacles in the utilization of
communication technologies. According to Shrum and Campion (2000) researchers in
developing nations are “Isolated” with scanty contacts with the stakeholders to whom
they are intending to serve. In this context, researchers need to develop more and more
contact. Ward and Spennemann (2000) described that establishment of local information
systems and global economic forces affect the dissemination of agricultural information
between researchers and extension agents working for the development of end users.
Major factors in this regard appeared were insufficient support and funding for
developmental projects in developing countries.
Shrum and Campion (2000) viewed cultural and personal barriers as potential factors
hampering scientific information dissemination. Burnett and Tucker (2001) were of the
view that agriculture has become a complex enterprise, therefor communication pathways
are insufficient to fulfil the demand of information. Pawlick (1996) had unveiled that
communication channels poorly communicate controversial aspects including social and
economic issues which put threat of their weak relationship with agribusiness industry.
Financial and academic complications further suppress communication media to
communicate agricultural innovations (Fedler et al., 1998). Agbamu (2000) reported that
sluggish working association between communication agencies hampers communication
of innovations developed with the aim of improving productivities. Inter-department
collaboration was further identified as being weakened (Fedler et al., 1998).
2.5 Debates on effectiveness of various communication channels
2.5.1 Extension field staff
Dissemination of generated information to the end users is imperative and a number of
communication channels are used for this purpose. These communication channels could
be electronic media tools, print media and social media (Amudavi et al., 2009). EFS is
frequently serving farming communities at their door steps through various
communication channels. This flow of information is key aspect in fostering adoption of
17
innovations and improving farm production (Asaba et al., 2006). Face to face
communication carried out by extension staff was considered as most effective because of
disseminating improved practices to the farmers in effective manners (Pipy, 2006).
According to Weiss et al. (2000), extension activities like field days, demonstrations and
modern tools like ICTs effectively improved farmers’ access to information. Within the
sphere of extension work, farmers’ meetings organized in groups were found very
effective by Livondo et al. (2015). Group discussion technique for information sharing
among farmers adopted by extension staff enhanced their effectiveness (Bajwa et al.,
2010). Ali et al. (2011) indicated that group technique is frequently used method of
communication and this approach significantly enhanced the effectiveness of EFS as
communication medium.
Agriculture extension is a systematic communication channel aimed at transferring
innovations (Kidd et al., 2000) and relying on approach of related and useful information
sharing among farmers (Hedjazi et al., 2006). Extension is termed as effective medium
because it brings positivity in attitude of farmers and change their behavior towards
adoption of latest practices (Khan, 2005). Despite esteemed importance, effectiveness is
subject to level of access which is vital determinant for adoption of modern practices
(Ebrahim, 2006). According to Baloch and Thapa (2017) policy of extension work needs
restructuring according to the needs of the farming communities. Frequency of contacts
of extension staff to the farmers needs to be increased for effective transmission of newly
generated messages.
2.5.2 Fellow farmers
Fellow farmers are viewed as most viable and easily accessible information source for
farmers. Several researchers argued that interpersonal relations between farmers enhances
their understanding regarding farming and familiarity with agricultural innovations (Ota
and Shimayohol, 2011; Oladeji, 2012). Farmers can access fellow farmers for the
required information whenever they want. This quick and easy access ensures
effectiveness of fellow farmers. Farmers-based organizations tend to serve
communication channel to share relevant information among farmers (Pertev, 1994).
Bachhav (2012) was of the view that fellow farmers were widely preferred
communication channel of farmers to acquire their required information. Majority of the
respondents preferred fellow farmers for information acquiring because of easy access to
them (Opara, 2008). Farooq et al. (2007) unveiled that easy access and availability of
timely information were the reason that farmers rated fellow farmers as most effective
18
rather than other communication means. For instance, more preference was given to
fellow farmers over print media communication (Rehman et al., 2013). For effective use
of print media being literate is imperative but in case of communication with fellow
farmers literacy is not the barrier. Face to face communication appears more fruitful and
results positive (Muhammad, 2005). Experienced/progressive farmers become the best
discussion partners for other farmers (Place et al., 2005). During discussion with farmers
regarding their source of agricultural information, it was observed that most of them were
availing such information from neighbors (Minja et al., 2004). Since, fellow farmers are
traditional communication channels and bear some limitations as well, which some time
lower the credibility. The effectiveness of fellow farmers may however be partially due to
lack of trust among farmers. Irfan et al. (2006) declared fellow farmers unauthorized
information sources and tend to share incomplete information among farmers which may
result in contrast. Though fellow farmers are effective in impact, no efforts have been
rendered to ensure the effectiveness (Nalugooti and Semakula, 2006).
2.5.3 Electronic media
Electronic media are one of the emerging trends of modern days and have potential of
disseminating required information within shortest possible time. However, effectiveness
is dependent upon the nature and level of use of particular tool (Katz et al., 2013). For
instance, a study conducted by Menon et al. (2014) unveiled that majority (71%) of users
were satisfied from the information received through electronic media tools. They argued
crucial role of these media in their capacity building and uptake of modern production
practices. TV, radio, mobile phone, helplines, internet etc. are some prominent tools of
information receiving, though, accessibility of these media is not harmonized. As the
accessibility of mobile is higher now a days, respondents felt it much appreciated and
effective as reported by Aldosari et al. (2017). In this research, internet was also rated as
most effective by the respondents. Conversely, Otter and Thruvsen (2014) found that
mobile phone and email services were having positive influence of production of crops
particularly in control of small landholders. Chhachhar et al. (2014) found mobile phone
prominent in terms of effectiveness among farmers. They were of the view that mobile
facilitates the farmers to access information regarding marketing and alternate selling
options at easy access. With the presence of mobile phone farmers were able to bridge the
information gap regarding selling and getting profitable prices for their produce.
Additionally, mobile phone helped farmers in eliminating exploitations and monopolies
of middleman (Anoop et al., 2015). Lee and Bellemare (2013) reported significant
19
improvement in money, energy and time saving through effective marketing through
mobile phone as farmers were able to communicate directly with the vendors and traders.
TV is another electronic media tool possessing tremendous potential. According to Nazari
et al. (2011), TV embarked significant increase in knowledge of farmers through
educational interventions. Programs broadcasted on TV on various aspects render vast
opportunities of learning for farmers, hence, TV has been a preferred choice of farmers
(Ekoja, 2003). Positive impact of TV was further unveiled by Kim (2010) through
broadcasting of farming related messages. These broadcasts enhanced farmers’ awareness
on particular aspects (Nazari et al., 2009). Moreover, TV has been the prime source with
capability of sharing information among large audiences in effective manner (Movius et
al., 2007). Majority of the farmers own their TV sets which enables them to access
information all the time (Chhachar et al., 2012). On contrary, Khan et al. (2010) reported
poor broadcasting of TV programs which affected its effectiveness. Time disparities faced
by farmers kept them unable to watch programs on regular basis. Khan et al. (2010)
further reported that farmers were unaware regarding regular broadcasts of TV.
Inappropriate timing of broadcast was major hurdle in making TV more effective
communication tool (Jafri et al., 2014).
Likewise, radio has been the widely used information source of farmers. Radio was stated
as story teller by Fossard (2005) while Mirani et al. (2003) unveiled high level of
satisfaction of farmers with communication made through radio programs. Radio
successfully disseminated useful information on production and protection measures for
crops (Khan and Shabbir, 2000). Ekoja (2003) and Arokoyo (2003) mutually inferred that
Radio along with TV were the prominent and effective information sources because of
their easy access and dissemination of information to lager audiences. Nazari and
Hasbullah (2008) stated that radio and TV were highly effective tools in disseminating
innovations because of their broadcasts for every farmer regardless of their age, gender
and education.
Apart from traditional sources such as TV and Radio, some modern tools like internet are
potential sources to facilitate farmers. Computer and internet are getting more popular in
accessing agricultural information (Shetto, 2008). For example, internet kiosak in India,
were owned by women and they were motivated to establish credit groups (Narender and
Anandaraja, 2008). Mtega and Msungu (2013) unveiled the extensive use of internet for
accessing agricultural information in Tanzania. However, use of internet along with
modern tools like email is at low rate (Lwoga et al., 2011). Few more research studies
20
Adomi et al. (2003) and Chilimo (2009) unveiled use of internet as information source by
farmers, but at low pace.
Despite potential use and effectiveness of electronic media, there are many pertinent
obstacles. Power failure, poor connectivity and higher cost (Memon et al., 2014),
inadequate funds and trainings (Yaseen et al., 2015), small land holdings, (Khan and
Akram, 2012), poor socio-economic conditions (Muhammad et al., 2012), irrelevant
broadcasting and inappropriate timing of broadcasting (Jafri et al., 2014) were highlighted
obstacles to effectiveness of electronic media.
2.5.4 Print media
Print media are powerful communication tools of all time utilized to develop contact with
larger number of audiences and helping them in improving their productivities (Govt. of
Bangladesh, 1999). Chikwati (2009) reported that use of print media in agriculture could
be more effective if utilized along with electronic media tools. Print media are permanent
message senders and critical aspect of non-formal education (Oakley and Garforth, 1985).
Printed communication further entails posters, books, pamphlets, charts, notes etc.
(Hancock, 1976). Brochures, leaflets, magazines, technology guides, bulletins and news
sheets are additional features bearing function of information sharing (Flor, 2002;
Maningas et al., 2000). Agricultural publications including journals, periodicals, bulletins,
leaflets and folders are used by different stakeholders of agriculture for information
sharing and receiving (Ray, 1991).
Aina (2004) revealed that farmers require information in printed form for repeated use on
long term basis. Printed material was distributed free of cost among farming communities
for their welfare and motivation to adopt innovations (Malik, 1990). Singh and Dhillon
(2006) reported that concerns of farmers to get information on printed material were
higher than the broadcasted information. Hamid (2006) endorsed that majority of farmers’
perceived print media as an effective information source. Several more researchers Gloy
et al. (2000), Howell and Habron (2004), Ngathou et al. (2006), Parthaap and Ponnusamy
(2006), Farooq et al. (2007) and Clifford and William (2007) regarded print media as
effective communication tools. However, effectiveness of print media is limited to those
who are educated. Access to printed information is directly associated with educational
level (Rehman et al., 2013). Katungi (2006) endorsed that educated farmers had more
intentions to access printed media communications. Saadi et al. (2008) found significant
association between socio-economic attributes and access to printed information.
21
Generally, educated and socio-economically privileged farmers not only access printed
literature but also enjoy diversified patterns of information communicated.
2.5.5 Social media
Social media are the modern trends bearing tremendous potential of communication.
Hence, use of social media in agriculture sector as communication channels is imperative.
Advisory service providers can use social media to communicate over a large number of
audiences irrespective of their age, education, gender etc. (Barbassa, 2010). To construct
an association with media and stakeholders in agriculture it is essential to realize the way
how to use innovations for the benefit of farming communities. Insight access to
information is scanty (Tweeten, 2014) and emergence and prevalence of social media has
bridge the gap (Varner, 2012). Increased access to internet and cellular technology has
enabled the farmer to access available information easily in short time (Sutter, 2009).
Efforts to make farmers aware and educated regarding the importance of social media are
on right path. For instance, development of the Ag-Chat Foundation is leading example,
paving the ways to empower farmers to interconnect communities via social media (Ag-
Chat Foundation, 2014). This effort helped farmers in ensuring their active participation
on social media to share and diffuse agricultural innovative technologies. Social media
fulfils the requirement of information on agriculture i.e. marketing, news, branding,
publicity, policies, crisis and wide range solutions to persisting challenges (Eguoko et al.,
2015).
Knutson (2011) and Meyers et al. (2011) stated that through inception of social media,
farmers and information providers can reach large number of audiences that would not
have received messages in past. This modern invention has revolutionized
communication process and educating farmers through dissemination of valid information
(Eguoko et al., 2015)
Within social media groups, Facebook is one of the leading and popular social
networking sites being used by agricultural organizations for communication. Facebook is
well known to target audiences and has received scholarly attention (Tweeten, 2014).
Agricultural experts are using Facebook to communicate recent agricultural inventions
and to share success stories (White et al., 2014). Though Facebook has been impressive
and effective platform for information sharing in order to gain more success, it is essential
to build interconnectivity between different social media platforms (Meyers, 2011). As
number of users is increasing, it could be helpful for the extension professional for
22
information sharing, reaching the audiences and educating them regarding agricultural
innovations (Kinsey, 2010). Facebook focuses on relationship building (Waters et al.,
2009) hence; it could be easily used by extension scholars to develop relationship with
farming communities. For this purpose, groups can be created on Facebook and farmers
can be motivated to join the developed group to share their experiences and ideas (Pineda,
2010) related to farming.
2.6 ICTs as communication channels
ICTs are electronic technologies for creating, acquiring, processing, storing,
communicating and using information (Tiamiyu, 2002). According to Zappacosta
(2001), ICTs comprises electronic and digital modes of capturing, sharing, processing,
retrieving and storing information for broadcasting by using different tools like TV,
radio, transmission of speeches, images, data via faxes, email and web-based
connections and networks. ICTs provide beneficial strategies to disseminate agricultural
information among rural peripherals. The farmers of these peripherals need accurate,
authentic, complete, concise and dynamic agricultural information to boost agricultural
productivity (Nkwocha et al., 2009). Farmers having small land holding face a vast
information gap hindering the adoption of good agricultural practices (Syngenta
Foundation, 2011).
Application of updated and contemporary ICTs is the most viable source to quench the
thirst of getting updated information and narrowing the information gap existing among
the farmers. Miller et al. (2013) reported that connecting farmers with knowledge banks,
institutions and networks through updated information communication technologies has
uplifted the farm productivity, food security, profitability and employment opportunities
significantly. Moreover, the modern system can also interlink development practitioners
and global institutions to facilitate concerned stakeholders regarding relevant
agricultural information to build “community of practice” (Wenger et al., 2002). For
instance, several institutions have developed applications to facilitate farmers to increase
farm production, provide financial services and disseminate market price information.
Furthermore, agro-knowledge, ICT and data availability were assumed to be the major
driver of bringing developmental change in agro sector of Netherlands (Anil, 2008).
Aina (2004) and Kaniki (1995) revealed that agricultural information needs of the
farmers vary based upon their peculiarity. Increase in farm production and income is not
possible without appropriate tools that are in relevance of farmers’ needs.
23
Timely availability of information is critical for effective management of managerial
functions like planning, organizing, leading and controlling (Rodriguez, 2008). ICTs
tend to facilitate farmers on farm to uplift production and achieve higher levels of
production, income and sustainability. It is not possible without the effective agricultural
extension services and utilization of appropriate tools that are according to the needs of
farmers (Anil, 2008). Numerous extension strategies put in place over the years are
common examples (Akubuilo, 2009). Efforts exerted by extension sector were meant to
ensure dissemination of agricultural information among farmers in effective manner and
play critical role in enhancing agricultural production. For this purpose, ICT had several
potential applications in agricultural extension to bring new services to the front (Zijp,
1994). Bolarinwa and Oyeyinka (2011) were of the view that integration of ICT tools in
extension work will bring quick sharing of diversified information.
ICTs provide information in simple ways to the users (Michiels and Vancrowder, 2001).
Isiaka et al. (2009) reported that extension workers were utilizing ICTs potential to
foster extension services delivery and level of awareness was almost 88.5% about the
potential aspects of ICTs (Adebayo and Adesope, 2007). Salau and Saingbe (2008)
indicated that about more than half (56.22%) of the extension agents were using ICTs it
including TV, mobile, radio, internet etc. In Carribean, extension agents were using
ICTs for personal benefits and increased their professional productivity along with use
of traditional sources. While, Lasley et al. (2010) narrated that ICTs had potential to
replace traditional information sharing system and can be helpful in modifying the
extension agents’ role in agricultural system. Jensen (2007) was of the view that
penetration of mobile phone among farmers for information acquisition appeared helpful
in reducing price dispersion and sticking on fix price, further highlighted the
effectiveness of mobile phone in post-harvest management. Farmers were motivated by
extension staff to adopt ICTs and updated market related information was disseminated
on subscribers’ phones (Aker, 2008). Mtega and Msungu (2013) stated that in addition
mobile phone services and improvement in infrastructure helped extension agent to
disseminate learning opportunities among farmers with minimal cost.
Cost effective nature of mobile phones made communication cost effective and
successful (Churi et al., 2012). Levi (2015) revealed that an overwhelming majority of
farmers (88.3%) used radio for information followed by mobile phone users (51.7%)
while 17.1% farmers were users of TV. Abubakar et al. (2009) and Manyozo (2009)
agreed that in most of the developing nations information was disseminated through
24
radio because of very low cost. Olaleye et al. (2009) also found radio as a leading
agricultural information sources due to its affordability and quality of information.
Further studies conducted in Nigeria by Olaleye et al. (2009) and in Tanzania by Sife et
al. (2010) revealed that rural farmers were relying more on radio to access information
due to wide coverage, frequency and existence of multiple radio stations. Information
accessed through radio was perceived very helpful by the farmers in improving their
crop yields through extension education (Dodds, 1999). Mtega and Msungu (2013) also
illustrated that radio can be accessed easily on mobile phone in Tanzania which is
almost possessed by each and every farmer, further they ranked radio services on 1st due
to good radio waves and number of stations that are equally helpful for the farmers.
Olaleye et al. (2009) documented the benefits of radio that it is equally important for the
literate as well as illiterate farmers. Tanzanian Communication Regulatory Authority
(2012) reported the effectiveness of TV in dissemination of agricultural information and
enhancing adoption. The broadcasted programs were source of learning and helpful in
enhancing educational skills as well as the combination of sight and sound results in the
success of TV in broadcasting programs and bringing change in attitude of farmers and
make them active learner (Buren, 2000). Muhammad (2001) also narrated that TV
programs were broadcasted in local language which played significant role in farmers’
development.
2.7 Information sources of farmers in Pakistan
Farming in Pakistan is subsistence in nature as majority of growers are small farmers
possessing low level of education. Hence, they tend to receive information from
traditional sources. Muhammad and Garforth (1999) unveiled that farmers in Pakistan
usually tend to receive information from fellow farmers. Ashraf et al. (2015) unveiled that
farmers perceived fellow farmers as the most effective information source among other
sources like EFS, electronic media and print media. Different researchers like Cheema
(2000), Nazam (2000) and Barkat (2002) reported that fellow farmers and friends were
most preferred and utilized information source of farmers. Radio and TV were additional
sources being used, but effectiveness of fellow farmers appeared higher. Muahmmad and
Garfroth (1999) had also revealed that fellow farmers were a way ahead in terms of
effectiveness than radio. Furthermore, regarding preference of pesticide agencies, EFS
were perceived least by farmers in getting information when compared to fellow farmers
(Ashraf et al., 2015). Further studies conducted by Malik (2000), Abbas et al. (2003),
25
Chaudhary et al. (2008) and Saleem et al. (2010) endorsed fellow farmers as widely used
information source, further reported that farmers had received information from fellow
farmers, TV programs fertilizer dealers and seed dealers. Mirani et al. (2003) presented
the same thoughts that private agencies including seed and fertilizer often contacted
farmers to share information. Face to face communication and sharing information
through seminars were other effective approaches perceived by the farmers (Mirani,
2013).
Yaseen et al. (2016) found that fellow farmers/friends were perceived as information
source by majority of respondents while least proportion of farmers choose EFS as
information source. Fellow farmers and print media were reported preferred information
sources of farmers by Rehman et al. (2013). Fellow farmers/friends, printed media, TV
and private sector extension staff were the common information sources being used by
the farmers to fulfill their information requirement. Seed companies, group discussion
and brainstorming technique laid by EFS were the most popular information sources as
reported by Rehman et al. (2013). Group discussion technique, printed literature and TV
were assumed best information source by the farmers. TV is profound part of electronic
media possessing potential of sharing information among large audience in short time
(Farooq et al., 2007). Khan et al. (2010) affirmed that electronic media including TV,
internet, helplines, telephone and mobile phone were significant in information sharing
among farmers. Abbas et al. (2003) declared that TV had been powerful media of
communication and farmers’ choice to get agricultural information. Few researchers Butt
(2002), Bukhari (2000) and Muhammad et al. (2004) revealed that mass media showed
partial contribution and less information was obtained by farmers from these sources. The
reason behind this poor contribution was unveiled by Muhammad (2005) that mass media
tools offer one-way flow of communication and meager opportunity of feedback. In fact,
feedback is imperative for effective communication. Irfan (2008), Muhammad et al.
(2008) and Ashraf (2008) found TV as effective information source as compared to radio.
The possible reason behind effectiveness differences may be visual option which only TV
offers. However, Siddiqui (2006) didn’t find any difference in effectiveness of radio and
TV. Hussain (1997) affirmed that radio was most convenient and popular tool of
communication for extension agent to float agricultural information. Findings of Ghafoor
et al. (2008) unveiled some reservations on rely of TV as information source such as
improper and unrelated broadcast that lowered the effectiveness of TV as information
source. Within mass media tools, printed literature used as an information source was
26
ranked 3rd among other channels by Farooq et al. (2007). Nosheen et al. (2010) reported
low consideration to print media paid by farmers. The use of printed literature was limited
to those who were educated. The debate summarized that farmers were reliant on
traditional media for information acquisition.
2.8 Constraints to ICTs across worldwide
No wonder, effectiveness of ICTs is immense, but potential is yet not fully explored
pertinent to several constrains. According to Lederer et al. (2012) major challenges
regarding the use of ICTs is cost of access. Limited access and availability of
information disseminated via ICTs were also perceived major challenges by Babu et al.
(2012). Joseph and Andrew (2006) were of the view that rapid technological changes,
poor access to technology and high cost were the factors affecting the ICTs impact.
Akpabio et al. (2007) described that poor infrastructure, cost of equipment, electricity
problem and interconnectivity access were the constraints in the way of ICTs impact.
Munyua et al. (2009) revealed that inadequate infrastructure was major factor hindering
the effectiveness of ICTs and information disseminated. UN (2005) reported that
emerging tools like tele centers could be catalyst of information and knowledge
development opportunities but lack of infrastructure is the major constraint particularly
for the remote areas. Lack of access and ability to learn and share the knowledge from
ICTs was also reported by FAO (2011).
It has been seen that extension agents are using different ICTs for communication of
agricultural innovations with farmers. But, Isiaka et al. (2009) presented contradiction
that majority of the extension workers were not found conscious about the use of ICT
devices for information sharing, though these tools if used are of tremendous potential.
Wijekon and Newton (2000) found that with appropriate and effective usage of ICTs
among extension agents, potential can fully be utilized in benefiting manners. However,
Adebayo and Adesope (2007) supported the statement of Isiaka et al. (2009) that
majority of the extension agents was not having personal computers in their offices.
Findings clearly indicated that agricultural extension offices are not equipped with ICT
tools. As a result, farmers were compelled to go for traditional electronic tools to obtain
information.
Kameswhari et al. (2011) indicated that farmers were not aware about the ICTs and were
relying on radio for information acquisition and sharing. Churi et al. (2012) indicated
dissatisfaction of farmers with radio by revealing broadcasting of irrelevant messages
27
and poorly organized agricultural information. Studies conducted by International
Institute for Communication and Development (IICD) (2005) in Ghana, Zambia and
Tanzania revealed that farmers preferred mobile phone to obtain information due to its
cost effectiveness and availability. World Bank (2011) reported that prices of mobile
phone have become affordable for the poorest due to sharp decline and availability of
multiple models. However, internet connectivity was found very low despite increasing
population of subscribers particularly in developing nations (ITU, 2013).
Findings of Dia (2002) appeared in favor of Television because of visual nature, but
Kameswhari et al. (2011) contradicted and revealed that despite frequent broadcasting
users were only watching entertainment programs for the pleasure. It could be the result
of inadequate and inappropriate broadcasting of agriculture related programs or socio-
economic related issues of farmers. Khan et al. (2012) revealed that education had
significant association with use of TV as information source. Sife et al. (2010) narrated
that lack of electricity constrained the access of information broadcasted on TV.
Diyamett et al. (2010) reported limited number of TV stations in Tanzania as a major
challenge in information dissemination and access.
ICTs adoption and usage for information acquisition is also associated with
socioeconomic position of the users. For instance, Anastasioset et al. (2011) indicated
that internet access was significantly influenced by income level of the farm-oriented
users in Greece. Mwombe et al. (2014) revealed that use of ICTs as information source
among banana growers was influenced by age, income, gender and area under banana
cultivation. Adegbidi et al. (2012) found that more the land farmers possess, more
intentions to use cell phone as information sources were found among them. On other
side, farmers with low land holding perceived the use of cell phone very low. In general
young farmers with enough education and land were more likely to use ICTs for
information sharing. Strong et al. (2014) pointed that technology acceptance and
adoption is directly associated with educational level of the users.
Doss and Morris (2014) endorsed the findings of Strong et al. (2014) by revealing
significant role of education in technology adoption. More the education level, more will
be the adoption of new technology. Lederer et al. (2012) highlighted the problem of
illiteracy affecting the usage of ICTs in Ethiopia. They were of the view that language
barrier i.e. poor English speaking was also hindering the capacity of ICTs usage among
users. Educational level brings significant change in attitude towards usage of ICTs
(Hassan et al., 2011). Khan et al. (2012) also endorsed significant and positive
28
association between educational level of the farmers and ICT tools like TV in particular.
Sekabira (2012) highlighted the importance of education that increase in educational
level increased the chance of ICT use by 0.0005 times through improving the reading
skills.
2.9 Constraints to ICTs in Pakistan
To achieve full potential of ICTs in Pakistan, harnessing management is urgent need of
time (Zakar and Zakar, 2007). Use of ICTs is hampered in Pakistan due to several
factors. In Pakistan, usage of ICTs in agricultural sector is poor as compared to other
countries due to weak infrastructure particularly in rural peripherals (Ali et al., 2011).
Rizvi (2003) opined that low tele-density and defective power supply are factors
affecting use of ICTs in Pakistan. According to Aldosari et al. (2017) socio-ecnomic
attributes of the respondents had significant impact on usage of ICTs as information
sources. The farmers having poor socio-economic attributes were undecided regarding
use of ICTs for information seeking. Significant influence of socio-economic attributes
like age, education and gender on use of ICTs was also unveiled by Yaseen et al. (2016)
Findings of Yaseen et al. (2015) revealed inadequate trainings to boost users’ capacities
discouraged the use of ICTs among farmers. Zakar and Zakar (2007) unveiled that poor
capacities of ICTs users are major factors hindering efficient use of ICTs. Physical
conditions of area do have significant impact on fostering use of ICTs. Improper
conditions hamper use of ICTs among users (Abdullah and Samah, 2013). Mubin et al.
(2015) stated that ICTs are usually inaccessible to farmers in Pakistan.
29
2.10 Synthesis of review
Effective communication holds significant function in improving farm production.
Interactive sharing of innovations attracts peoples’ participation for enhanced learning.
Historical extension programs in wake of community development are evident of
initiation of agricultural communication to raise awareness and mobilize capacities to
attain more benefits. Inter-department coordination strengthens the information flow
among farmers, however farmers utilize multiple information sources to meet their
information needs. With the passage of time, information needs are increasing with
increasing complexities of farming, hence, effectiveness of information sources varies
according to the situation. These varied needs tend farmers to alter their choices and
preferences of use of information sources. It is evident from literature that farmers used
to rely on traditional modes of information sharing. Fellow farmers/friends are the most
frequent and effective information sources as perceived by the farmers. Farmers
consider those sources effective which are cost effective and easily accessible. Fellow
farmers meet their exact concerns. Conversely, utilization and effectiveness of other
associated sources appeared nominal pertinent to several factors. For instance, poor
broadcasting, irrelevant programs and inappropriate timing followed by extensive cost
hindered the effectiveness of allied sources. One-way flow of information from
electronic media and accessibility restricted effectiveness of mass media. EFS is
considered foremost advisory source of farmers, however, reliance for information
receiving is found scanty. ICTs are the channels sharing information irrespective of age,
gender, education and bearing meager cost and wider coverage. ICTs are found equally
important to strengthen extension field services. Despite overwhelming benefits, use of
ICTs is below the mark in Pakistan due to poor infrastructure, high cost, poor
connectivity and inadequate knowledge on the part of uses. This literature indicated a
gap regarding emerging trends of ICTs in agriculture and challenges regarding use of
ICTs in particular situation.
30
CHAPTER 3 METHODOLOGY
The methodology section presents a structure and roadmap to investigate the problems
and generates binding generalization of phenomena (Thakur, 2003). Blaxter et al. (2001)
described that the collection and analysis of data are integral aspects of the research and
methodology section and highlight those procedural dimensions of data collection and
analysis (Ghafoor, 2008). Use of systematic and viable methods are prime aspects of
research (Flick, 2011). Dornyei (2007) unveiled that research design of qualitative or
quantitative study should be practiced systematically. Choosing viable methodology to
get reliable solution is vital (Farooq, 2011), hence, researcher followed a systematic
methodology for this study.
This section is illustration of area of study, research protocols, sample selection, research
instrument, pre-testing, reliability and validity checking, collection and analysis of
collected data. Hindrances faced by the researcher in whole data collection process are
also described in this section.
3.1 Pakistan: the study country
Pakistan is situated in South Asia and borders with India, China, Iran, Afghanistan and
Arabian Sea (Govt. of Pakistan, 2006). Pakistan is predominantly an agrarian economy
and is the 6th most populous country with approximate population of 200 million, and
reliance on agriculture industry is mounting. The country is blessed with tremendous
potential of natural resources, esteemed seasons, plains and mountain areas, fertile soil,
sandy deserts, groundwater and rivers. All these esteemed resources are favorable for
diversified farming across the country. Pakistan is graced with world’s largest canal
irrigation system, hence, pertinent to all these reason, agriculture is still dominant sector
with 18.9% contribution to GDP and 42.3% labor support (Govt. of Pakistan, 2018).
Since, inception of Pakistan in 1947, country is making progress to combat
developmental challenges. Telecommunication sector is rising across the country. Today,
accessibility to communication tools is higher. In result, user has an approach to multiple
means. Advancements in electronic media, print media and now social media have
bridged the information gap.
31
3.2 Punjab: the study province
There are four provinces in Pakistan, including Punjab, Sindh, Baluchistan and Khyber
Pakhtunkhwa (KP). Punjab is a significant and prominent province in terms of
development and agricultural productivity. It comprises 36 districts (Figure 3.1) with a
population of 110 million as per census of 2017. Literacy rate in the Punjab province is
61%, though literacy among urban areas is higher 77% followed by 55% in rural areas
(Govt. of Pakistan, 2017).
Agriculture is the major occupation and income generation source of people in the
Punjab. In addition, Punjab is the bread basket for the national GDP with a huge share of
60%. Livestock and crop farming are chief contributors in terms of revenue and
employment generation. The Punjab province holds 14.41 million hectares of irrigated
area which is favorable for extensive cultivation of major and minor crops.
Despite significance in agriculture and persistence of resources, farm productivity is
sluggish. Research has confirmed a wide production gap as compared to global
economies. Moreover, cost of production of major as well as minor crops in the Punjab is
higher which results in poor returns. In this regard, Directorate of Agricultural Extension
and Adaptive Research, Government of the Punjab is striving and utilizing all best
resources to combat the problem of high cost of production and reducing yields. The
Department is making progress in utilizing ICTs for timely dissemination of information
among farmers. Provision of androids phone and tablet sets to field officers and now
inception of drone technologies in agriculture is evidence of commitment of Agriculture
Department in digitalizing agriculture. Furthermore, effective utilization of electronic
media, mobile phone, web-based services and toll-free helplines are resulting at higher
situation.
32
Figure 3.1. Map of the Punjab province
33
3.3 Study districts
For the selection of study areas, lottery method was employed. All the 36 names of
districts were written on pieces of paper and two pieces were chosen blindfolded. Hence,
two districts, Muzaffargarh and Rahim Yar Khan appeared as study areas (Figure 3.2).
Both districts fall in southern part of the Punjab and hold tremendous potential of
agriculture. Further detail of these two districts is as under:
Figure 3.2. Map of the study districts
3.3.1 Muzaffargarh
Muzaffargarh lies in southwest of the Punjab province at the bank of Chenab River.
Muzaffargarh district consists of four tehsils named as; Muzaffargarh, Ali Pur, Kot Adu
and Jatoi. The northern side of this district is covered with the famous Thal desert. The
remaining part of the district is plains and favorable for agriculture. Two main canals,
Muzaffargarh and Rangpur emerge from Taunsa and Trimmu head works. These canals
irrigate major portion of the cultivable land (Govt. of Punjab, 2018)
The district is widespread over an area of 8249 KM2 with 93 union councils and 984
villages. Total population of the district is 4.3 million. Among total population 2.2
million are males while 2.1 million are females. The literacy rate of district is only 29%.
Agriculture is the mainstay of people residing in the district. Cotton, wheat and sugarcane
are extensively cultivated crops while among fruits mango is prominent for earning
foreign exchange and securing livelihoods of farmers.
For the facilitation of farming communities, Department of Agriculture (Extension) is
working under supervision of Deputy Director of Agriculture (Extension) to educate
farmers regarding agricultural innovations. The department is undertaking all potential
efforts and integrating use of ICTs for effective dissemination of information among
34
farmers. Use of mobile is more prominent followed by trends of electronic media like TV.
Some notable TV channels “Waseeb TV” and “Rohi TV” are rendering agricultural
programs for the benefits of farming communities.
3.3.2 Rahim Yar Khan
Rahim Yar Khan is destined by district Muzaffargarh on north side, Bahawalpur on east,
Jaisalmair (India) and district Ghotki of Sindh province on south, while District Rajanpur
in west. The district is mainly divided into three physical characteristics i.e. 1) Riverine
area, 2) Canal irrigated area 3) Cholistan (desert area). Rahim Yar Khan is spread over an
area of 11880 KM2. There are total four tehsils in the district including Sadiqabad, Rahim
Yar Khan, Khan Pur and Liaqat Pur. The district further comprises three municipal
committees and five town committees.
The Rahim Yar Khan district is an industrial hub and commercial center. Fertilizers, glass
manufacturing, production and processing of cotton, textile units, flour mills, and oil mills
are leading industries generating employment and revenue for people. This district is
foremost in cotton production, mango and citrus are prominent fruits.
Agriculture is main source of livelihood of farmers. Directorate of Agricultural Extension
and Adaptive Research are rendering advisory services to the farmers and strengthening
their livelihoods. EFS is fully utilizing potential of ICTs to facilitate farming
communities.
3.4 Research design
Clough and Nutbrown (2010) were of the view that for researcher it is inevitable to be
sure that which method would give him deep insight to desired information. Hence,
research design should be scientifically firm and reliable (Bassey, 2003; Churchil and
Lacobucci, 2005; Drew et al., 2008). Higson-Smith and Kagee (2006) said that research
design is an operation to be performed to test a particular hypothesis under a specific
condition. While, Welman et al. (2009) defined that research design is a plan to select
respondents for the study and collection of data. Babbie and Mouton (2008) reported that
research design is a blueprint for undertaking a research. Mouton (1996) stated that
research design enables researcher to finalize research decisions. Moreover, research
design enhances the validity of findings.
In this study, survey research design was used. Survey research design has been
employed by various researchers in relevant studies (Muhammad, 1994; Idrees, 2003;
Lodhi, 2003; Siddiqui, 2006 and Khan, 2010). Survey research design entails
35
interviewing respondents which provoke required information from the respondents and
offer deep insight to researchers for meaningful outcomes (Ashraf, 2008).
Considering the importance of survey research design, same was implemented for the
respondents’ selection and data collection for research study. Furthermore, cross sectional
survey was employed which imitates the collection of data at specific point of time, but
time span is not static; may surpass to months or more (Borg and Gall, 1989). For better
understanding it is essential to elaborate the population for the study (Babbie and Mouton,
2008).
3.5 Study population
All the farmers residing in study districts (Muzaffargarh and Rahim Yar Khan) were
considered as the population for the study.
3.6 Selection of sample
3.6.1 Farmers
The randomly selected two study districts comprised large areas and bulk of villages.
Hence, researcher decided to give an equal opportunity of selection to all villages. Entire
selection was made through multistage random sampling technique. On first stage, two
tehsils from each district Ali Pur & Muzaffargarh (Muzaffargarh) and Khan Pur &
Sadiqabad (Rahim Yar Khan) were selected at random. On next stage, five villages from
each selected tehsil were selected using random sampling technique. The complete list of
villages was obtained from revenue department of respective districts. This complete list
of villages enabled researcher to undertake random selection of five villages from each
selected tehsil. For selection of respondents, a brief benchmark survey from villages was
conducted with the help of local leaders, Field Assistants and some progressive farmers of
these areas. This survey resulted a list of 4012 farmers from selected villages of four
selected tehsils. This list of farmers served as sampling frame. Hence, 20 farmers were
selected from each selected village through random sampling technique. For viable
sample size, sample calculation formula developed by Yamane (1967) was used at 95%
confidence interval and 5% precision level. In the results of this sample size table 388
sample size was drawn while for the equal distribution, sample size of 400 respondents
was selected.
3.6.2 Extension field staff
EFS was also selected for the collection of qualitative data. In this regard from each
selected district Deputy Director Agri. Ext. (DD, Agri. Ext.), four (04) Assistant Director
36
Agri. Ext. (AD, Agri. Ext.) (One from each selected tehsil) and all the Agriculture
Officers (AOs) working in selected tehsils were interviewed for qualitative data.
3.7 Development of research instruments
Different types of research instruments like questionnaire and interview schedule are used
by researchers for the sake of data collection. However, the applicability of both
instruments is different. Collection of data through personal interview technique gives an
ample opportunity for the researcher to collect correct data and deep probing (Khan,
2007).
Hence, for this study, two different interview schedules were developed for data
collection. One interview schedule was developed for the collection of quantitative data
from farmers while another interview schedule/interview guide having open ended
questions was designed for the collection of qualitative data from extension staff. For the
purpose of agricultural experts, ICT experts, Directorate of Information, Lahore, Punjab
and senior researchers of the department were consulted, and their feedback and
suggestions helped a lot to improve the standards of instrument. Moreover, some related
research studies, Irfan (2005); Muhammad et al. (2008) and Khan (2010) were consulted
for the preparation of interview schedule. Five-point Likert scale was employed for
collection of data regarding perceptions and extent.
3.7.1 Validity
Validity of the research instruments was checked through face and content validity
technique. For this purpose, the instrument was presented to a panel of experts at Institute
of Agricultural Extension and Rural Development, University of Agriculture Faisalabad
and Department of Continuing Education, University of Agriculture Faisalabad. They all
guided and suggested a few improvements which were incorporated by the researcher to
give a final shape to the instruments.
3.7.2 Pre-testing
Prior to final data collection, the interview schedule was pre-tested for further
improvement. Instruments were pre-tested by interviewing 20 farmers. These 20
respondents were other than sampled respondents. Minor changes based on pre-testing
experience were incorporated by the researcher.
3.7.3 Reliability
One of the most important considerations for any research is to be sure that the
respondents had provided accurate information. Apart from the competence of
37
interviewer, the instrument itself plays an important role in obtaining reliable data.
Reliability is the level of internal consistency of the instrument (Borg and Gall, 2002).
Reliability indicates the degree to which a survey instrument is consistent with what it
measures. A number of methods can be used to measure the reliability of an instrument.
Cronbach’s alpha (coefficient of internal consistency) is commonly used to measure the
reliability of research instrument (Lodhi, 2003; idress, 2003). Cronbach's Alpha was
measured through Statistical Package for Social Sciences (SPSS). The average value of
internal consistency emerged was 0.821.
3.8 Data collection
3.8.1 Interview of farmers
Data were collected using survey technique (Mirani et al., 2003; Hassan et al., 2005).
Data collection was started in 2016 and ended in mid-2017. The researcher himself
conducted interviews of the farmers. The majority of the respondents was interviewed at
their farms while some at their homes. The researcher was accompanied by Field
Assistants sometimes, while on some occasions, local leaders facilitated the interview
process. Apart from interviews, informal discussions with respondents were also held for
in-depth probing.
3.8.2 Interviews of extension field staff
Extension field staff were interviewed at their offices by the researcher. The main purpose
of these interviews was to get deep insight of ICTs usage by farmers. The extension staff
reacted softly and unveiled many facts, which are mentioned in results and discussion
section.
3.9 Data analysis
Raw data are used for quantitative analysis. Hence, collected data were analyzed using
SPSS. Descriptive statistics including frequency, percentages, weighted scores and mean
values were computed for meaningful transition of results. Qualitative data obtained from
extension staff were analyzed through content analysis technique. This qualitative data
were used to validate the collected quantitative data from farmer respondents.
3.10 Difficulties faced during data collection
Data collection from a bulk of respondents is not an easy task. It was a gigantic task for a
researcher to collect this volume of data. Many challenges were faced;
Locating respondents was a major problem.
38
The researcher faced harsh environmental conditions as study area is dominantly
warm in summer season.
Availability of transport and approaching respondents in remote villages was
tough. Most of the time, the researcher managed his own conveyance which added
extra cost on his pocket.
It was difficult to convince and persuade farmers for revealing answers, because
most of the time they started complaining about inadequate availability of inputs,
poor marketing and poor government policies.
39
CHAPTER 4 RESULTS AND DISCUSSION
This chapter illustrates the information regarding demographic characteristics of the
respondents, their information sources, current use of different ICTs, emerging trends of
different ICTs, preferred ICTs by respondents, effectiveness of ICTs as agricultural
information sources, challenges faced by respondents regarding use of ICTs, and training
needs of respondents regarding ICTs use.
4.1 Demographic characteristics of respondents
Demographic characteristics of respondents include age of the respondent, education,
land holding, tenancy status, income level, cultivated area and crops cultivation.
Demographic characteristics have important role in awareness and adoption of modern
production practices. Demographic characteristics of respondents also have vital position
in the adoption of modern technologies (Hassan et al., 2005). Rehman et al. (2013)
reported that demographic characteristics of the farmers like age, education and land
holding had significant association with accessing agricultural information in wake of
technology uptake. Age, gender, income and land holding had an impact on the extent of
use of different ICTs to access information from these modern tools (Mwombe et al.,
2014). Similarly Jenkins et al. (2011), Thompson (2012), Just et al. (2006) and Ali and
Kumar (2010) reported that age, education and income were important determinants for
farmers to select information sources to access information. In this connection data on
demographic characteristics of the respondents are illustrated in the following:
4.1.1 Age
Age is a vital element in determining human behavior. Age influences the human
behavior and broadens the exposure through organized experiences (Siddiqui et al.,
2013). Mickeler and Staudinger (2008) argued that with the increasing age, individuals
become able to comprehend routine phenomena. With increasing age, the individual
happens to be more mature and mentally stronger for making decisions.
Considering the importance of age, respondents were asked to unveil their age. Age was
categorized into three classes i.e. up to 35 years, 36-50 years and more than 50 years of
age. Collected data in this regard are tabulated in Table 4.1.
40
Table 4.1: Age of respondents
Age (in years) f %
Up to 35 178 44.5
36-50 125 31.2
Above 50 97 24.3
Total 400 100.0
Data depicted in Table 4.1 illustrate that respondents falling in age category of up to 35
years appeared prominent (44.5%) followed by 31.2% respondents who were in age
category of 36-50 years. Furthermore, about one fourth (24.3%) respondents had more
than 50 years of age. Individuals bearing age of less than 35 years are more often denoted
as “young” and it is much appreciable that young individuals are engaged in farming.
This healthy participation of young ones is also a notion towards mainstreaming
agriculture in the country.
The above stated findings are similar to those of Muhammad et al. (2008) where they
found about 65% respondents of less than 50 years age. However, findings are in
contradiction to Siddiqui (2006) who unveiled dominancy of middle aged respondents.
Various research studies Fawole (2006); Demiryurek et al. (2008); Ofuoku et al. (2008);
Omobolanle (2008) reported that middle aged farmers were prominent. Thus, these
results are in disagreement of the findings of current study.
4.1.2 Education
Education refers to be a source of positivity in human behavior and a means of social
development. Education strengthens the abilities of human beings and enables them to
understand complexities of society and routine life. In case of farming communities,
education is imperative to cope emerging challenges in farming. Muro and Burchi (2007)
illustrated that educated farmers perform better than those who are illiterate or poorly
educated in managing farm for obtaining potential production. Adoption of improved and
site-specific technologies remain higher among those who are educated. Generally, it can
be stated that education is the major foundation of technological uptake and development
(Ali, 2005). Katungi (2006) stated that educated farmers had more access to information
and chances of adoption of technologies increase with the increasing information.
Educated farmers are projected to have favorable attitude towards agriculture knowledge,
skill and information as compared to illiterate farmers (Habib et al., 2007). Doss and
41
Morris (2001) reported that educational level was one of the prominent obstacles
hindering adoption of technology. This implies that with the lower educational level of
farmers, likelihood of adoption of technologies remains lower. Therefore, it was
considered necessary to know about educational status of respondents. Data in this regard
are given in Table 4.2.
Table 4.2: Education of respondents
Education level f %
Illiterate 180 45.0
Five years of schooling 48 12.0
Eight years of schooling 62 15.5
10 years of schooling 63 15.7
Above 10 years of schooling 47 11.8
Total 400 100.0
The data mentioned in Table 4.2 reveal that about 55% respondents were literate followed
by slightly less than half (45%) who were illiterate. Those who were illiterate, never
attended formal schooling. While, among literate respondents more or less, one in ten
respondents was educated above matriculation. Furthermore, 12% respondents had five
years of schooling, 15.5% had eight years of schooling and 15.7% respondents had ten
years of schooling. This situation implies that respondents may not be able to understand
complexities of farming and technology adoption may be meager.
Findings are more or less similar to those of Cheema (2004) as 30.8% illiterate
respondents were reported in his study. Aldosari et al. (2010) had reported 14.8%
illiterate respondents followed by 23, 23.5 and 20.2% respondents having educational
levels of primary, middle and secondary, respectively. Findings of this study are
dissimilar to those of Ogboma (2010) as majority of the respondents were graduates.
Results of the Ganeshagouda et al. (2013) and Singh et al. (2007) also negate with the
results of this study as 4.5 and 10% respondents were illiterate, respectively.
4.1.3 Size of landholding
Landholding is the unit for cultivation of crops, size of land holding refer to size of farm
being used by a farmer for cultivation of crops and rearing of livestock. Land holding is
directly associated with farmer’s information need to manage the farm (Khan et al.,
2012). Respondents were asked to unveil their land holding size. On this basis, they were
42
distributed into three categories including small land holding (up to 12.5 acres), medium
land holding (12.5-25 acres) and large land holding (more than 25 acres). Data in this
regard are given in Table 4.3.
Table 4.3: Landholding of respondents
Size of land holding (acres) f %
Small (up to 12.5) 361 90.2
Medium (> 12.5-25) 33 8.3
Large (>25) 6 1.5
Total 400 100.0
According to the data documented in Table 4.3, the overwhelming majority (90.2%) of
the respondents was small farmers bearing less than 12.5 acres of land. The respondents
with land possession of 12.5-25 acres were only 8.3%, while large farmers holding land
size of more than 25 acres were almost negligible (1.5%). Debated distribution of land
holding size is approximately in accordance with national division where small farmers
are in dominance (86%) across the country.
Above stated findings are similar to those of Khan (2010) where he reported 81.1% small
farmers. Findings are also in line with those of Hassan (2011) where he found majority
(78%) of respondents as small farmers having land of less than 12.5 acres. Findings of
Mahmood and Sheikh (2005) also support the findings of present study. However the
results of the study conducted by Ganeshagouda et al. (2013) revealed 48% small farmers
which are contradictory to those of with present results.
4.1.4 Tenancy status
Tenancy status of the farmers holds significant influence on their behavior toward seeking
information regarding modern technologies and operative utilization. Tenancy factor is
also vital in making decisions among farmers. Owner, tenants and owner cum tenants are
common categories of tenureship. According to Hossain and Bayes (2009) tenants are
those persons who do not own any cultivated land but operate entirely rented land from
others. As compared to other categories, owners remain confident and make innovative
decisions (USDA, 2007). According to the census report, 2000, in Pakistan total
percentage of owner cultivators is 78% followed by 8% Owner-cum-tenants and 14 %
tenants (Bhutta, 2007). Therefore, it was considered necessary to probe the tenancy status
of farmers in the study area. The data in this regard are given in Table 4.4.
43
Table 4.4: Tenancy status of respondents
Tenancy status f %
Owner 352 88.0
Tenant 12 3.0
Owner-cum tenant 36 9.0
Total 400 100.0
Data quoted in Table 4.4 reveal that an overwhelming majority (88.0%) of the
respondents was owners. Interestingly, the percentage of tenants and owner-cum-tenants
appeared meager. This implies that respondents in the study area had tendency to use
their own land resources. Above stated results are supported by the findings of Hassan
(2011), Muhammad et al. (2008), Ashraf (2008) and Khan (2010) where they reported
majority of respondents as owner cultivators.
4.1.5 Source of income
Income is a leading determinant of technology adoption. Various research studies agreed
that rise in income level fosters the technology adoption while technology adoption in
return escalates the income level (Lin, 1999; Tesfaye et al., 2016; Awotide et al., 2012).
Income sources of the farmers are not limited as farmers diversify their sources to earn
more income. Das and Ganesh-Kumar (2017) reported that on-farm and off farm income
sources are significantly associated with rise in income of farmers. Farm size affects the
on-farm income (Velandia et al. 2009) while various studies report that demographic
attributes of the farmers viz age, education, experience and marital status influence off-
farm work and income (Serra et al. 2005, Ahituv and Kimhi 2006, Lien et al. 2006).
Chaudhry (2003) had reported a positive association between size of land and income of
the households. Some researchers viewed farm diversification favorable to enhance
income. Farm diversification has a prominent role in income rise and alleviation of
poverty (Michler and Josephson, 2017; Birthal et al. 2015). Thus it was considered
necessary to explore the sources of income of farmers and the data in this regard are given
in Table 4.5.
44
Table 4.5: Income sources of respondents
Sources of income f %
Farming only 317 79.2
Farming + job 30 7.5
Farming + business 44 11.0
Multiple sources 9 2.3
Total 400 100.0
Data presented in the Table 4.5 indicated that farming was the prominent and most
reliable income source. A vast majority (79.2%) of the respondents reported income
generation from farming only. However, farming included crop farming and livestock
raising, as unveiled by the respondents during informal discussion. In Pakistan, 60% of
the rural people generate income from agriculture (GOP, 2008). Findings are further
supported by Birthal et al. (2014) who regarded agriculture as the biggest income source
for 91% farmers. De Janvry et al. (2005) reported that large farmers tend to focus on
agriculture to generate income while small farmers usually choose other options to
generate income. In this study, 7.5 and 11% respondents were earning income from job
and business along with farming. Whereas, 2.3% respondents were generating income
from multiple sources. Findings are supported with the results of Chang et al. (2011)
where they reported that if agriculture were to be the only income source for small
farmers, majority of them would have remained poor. Similarly, findings are supported
with those of Akram et al. (2011) where they reported that farmers were earning income
from on-farm and off farm sources.
4.1.6 Area under cultivation
Area under cultivation refers to the area used by a farmer for cultivation of crops.
Cultivated area may vary from farmer to farm depending upon his ability to afford
expenses and size of land holding. Respondents were inquired about their area on which
they have cultivated different crops and information in this regard is stated in Table 4.6.
Table 4.6: Area under cultivation of respondents
Area under cultivation (acres) f %
Up to 12.5 acres 381 95.2
>12.5-25 13 3.3
>25 6 1.5
Total 400 100.0
45
It has been unveiled that an overwhelming majority (90.2%) of the respondents was small
farmers in the study area. Similarly, cultivation area appeared alike as reported in Table
4.5. A huge majority (95.2%) of respondents had cultivation on less than 12.5 acres. Just
3.3 and 1.5% respondents reported cultivation on 12.5-25 and more than 25 acres,
respectively.
4.1.7 Major crops
Wheat, cotton and sugarcane are the major crops of the study area. Cotton is the cash crop
and farmers usually earn more income from cotton than other crops. Wheat is not only
consumed at household level, but also commercialized for earning income. Sugarcane is
an emerging crop as a replacement of cotton due to potential source of higher returns than
cotton as perceived by farmers. The respondents were asked to indicate crops they grow
and data in this regard are mentioned in Table 4.7.
Table 4.7: Major crops grown by respondents
Major crops f %
Cotton 389 97.3
Wheat 317 79.3
Sugarcane 113 28.3
Rice 59 14.8
n = 400 *Total frequency acceding from 400 due to multiple crops grown
Data presented in Table 4.7 reflect that wheat and cotton were the major crops of the
study area. However, cotton was the leading crop argued by 97.3% of the respondents.
The study area is typically cotton inductive and climatic conditions are optimum for
extensive production of cotton. A vast majority (79.3%) of respondents embarked
importance of wheat collateral to cotton. Sugarcane and rice crops were also in practice
but at small scale. Sugarcane was grown by 28.3% followed by 14.8% respondents who
were in favor of rice.
4.1.8 Minor crops
Minor crops are also cultivated along with major crops by the farmers for specific
purposes. These purposes may vary according to the domestic requirements or sometime
for profit making. Data in this regard are tabulated in Table 4.8.
46
Table 4.8: Minor crops grown by respondents
Minor crops f %
Fodder 379 94.7
Sorghum 79 19.8
Maize 32 8.0
n = 400 *Total frequency acceding from 400 due to multiple crops grown
There are a number of minor crops grown by farmers in study area to meet different
domestic liabilities. For instance, fodder for the animals as reported by 94.7%
respondents. Sorghum and Maize were practiced by 19.8 and 8.0% respondents,
respectively. During discussion, it was highlighted by the respondents that these minor
crops have additional significance in fulfilling domestic needs and generating income as
well.
4.1.9 Vegetables cultivation
Vegetables are important in daily life and hold significant position for income generation
by farmers. Though, the trend of cultivating vegetables on small scale is prominent,
cultivation of vegetables on large scale is dependent upon marketing situation.
Respondents were asked about vegetables grown by them. Information in this regard is
depicted in Table 4.9.
Table 4.9: Vegetables crops grown by respondents
Vegetables f %
Brinjal 40 10.0
Tomato 91 22.8
Okra 72 18.0
Potato 35 8.8
Cauliflower 16 4.0
Bitter guard 10 2.5
n = 400 *Total frequency acceding from 400 due to multiple vegetables grown
The data given in Table 4.9 reveal that tomato was cultivated by more than one fifth
(22.8%) of the respondents. Less than one fifth (18%) cultivated okra, one in ten
respondents grew brinjal, while cultivation of potato, cauliflower and bitter guard was
minimal.
47
4.1.10 Fruit orchards
Study area is favorable for cultivation of mango and other fruits. These fruit orchards are
additional income sources of the farmers managed at small, medium and large scale.
Respondents were asked to indicate the fruit orchard they had managed. Data in this
regard are mentioned in Table 4.10.
Table 4.10: Fruit orchards grown by respondents
Fruits f %
Mango 108 27.0
Banana 9 2.3
Pomegranate 6 1.5
n = 400 *Total frequency acceding from 400 due to multiple fruits grown
The data in Table 4.10 reveal that mango was the most popular fruit grown by more than
one fourth of the respondents (27%). Climatic conditions of the study area are not suitable
for cultivation of banana, hence negligible percentage (2.3%) of respondents cultivated
banana. Once there was an enormous trend of pomegranate cultivation in Muzaffargarh,
but sudden infestation of diseases couple of years back destroyed wide coverage of
orchards as reported by respondents. Cultivation by 1.5% respondents is clear notion of
their reduced interest in pomegranate at present.
4.1.11 Sources of information
Information regarding modern production practices is the utmost need of the farmers.
This information is received from different information sources. Therefore, respondents
were asked to indicate their information sources. Data in this regard are mentioned in
Table 4.11.
48
Table 4.11: Respondents’ distribution according to their major source for getting
agricultural information
Source of information f %
Radio/ FM 146 36.5
Television 165 41.3
Internet 52 13.0
Mobile phone 241 60.3
Agri. websites 32 8.0
Agri. help line 10 2.5
News paper 46 11.5
Written literature from public sector 22 5.5
Written literature from private sector 24 6.0
Extension worker of public sector 189 47.3
Extension worker of private sector 246 61.5
Fellow farmer/relatives/ neighbors 284 71.0
NGOs 23 5.8
The data presented in Table 4.11 highlight that fellow farmers/relatives/neighbors were
the leading information sources from which 71% respondents were acquiring farm related
information. Findings are similar to those of Malik (2000), Abbas et al. (2003),
Chaudhary et al. (2008), Squire (2000), Manohari (2002) and Adomi et al. (2003) where
fellow farmers and relatives were acting as leading information sources.
Moreover 61.5% respondents reported information acquisition from private sector
extension staff, while 47.3% respondents were receiving information form public sector
extension. Ashraf et al. (2014) presented the same view that majority of respondents were
inclined towards private sector like pesticide companies rather than relying on public
sector. Further 60.3% respondents’ narrated information obtaining through mobile phone.
They argued that mobile based extension services are helping them at their door steps.
Furthermore, 41.3 and 36.5% respondents obtained information from TV and radio
respectively. Findings agree to those of Irfan (2005) and Muhammad et al. (2008) who
revealed that TV gained more interest of viewers as compared to radio. Radio still holds
unique position in disseminating agricultural information among rural dwellers in a
49
number of countries (George and Stylianou, 2018; Girma et al. 2018). Information
receiving from other sources like agri. websites, helplines, newspapers, literature and
NGOs was almost negligible.
Discussion with EFS also confirmed that getting information from fellow
farmers and friends was the preference of farmers. While, among ICTs,
mobile phone was the prominent source facilitating farmers in accessing
information.
4.2 Current use of different ICTs
4.2.1 Possession of ICTs
Possession of ICTs offers an opportunity of extensive use to meet information needs. It
also enable users to unveil deep insights regarding usage and effectiveness of various
ICTs. In this context, respondents were asked to express possession of ICTs. Data in this
regard are presented in Table 4.12.
Table 4.12: Respondents’ distribution according to their possession of ICTs
ICTs Possession
In possession since (years)
1-5 >5-10 > 10
f % f % f % f %
Radio/ FM 183 45.8 120 30.0 48 12.0 15 3.8
TV 319 79.8 176 44.0 99 24.8 44 11.0
Internet 71 17.8 71 17.8 0 0.0 0 0.0
Computer 37 9.3 31 7.8 6 1.5 0 0.0
Mobile phone 340 85.0 214 53.5 99 24.8 27 6.8
Fixed phone/ land line
phone 15 3.8 6 1.5 6 1.5 3 0.7
Data depicted in Table 4.12 illustrate the status of various ICT tools possessed by
respondents. Radio, TV, internet, computer, mobile phone and fixed phone were in
possession of respondents but with diversity. Mobile phone is one of the best innovations
of modern times, now a days its persistence is common. Hence, 85% of the respondents
were the owners of mobile phone of different specifications. Further 79.8% respondents
showed possession of TV. Radio/FM was owned by 45.8% respondents. Possession of
50
internet, computer and fixed phone was 17.8, 9.3 and 3.8% respectively. Almost one of
the ten respondents reported that he possessed TV since more than 10 years while 6.8%
respondents were possessing mobile phone since more than 10 years. Possession of rest of
the ICTs ranged between 1-5 years, and 6-10 years approximately.
4.2.2 Extent of use of ICTs
Respondents were asked about the extent of use of different ICTs. Their responses were
recorded on 05-point Likert scale (1=very low, 2=low, 3=medium, 4=high, 5=very high).
Data in this regard (Appendix-1, Table 1) are presented in Table 4.13.
Table 4.13: Respondents’ distribution according to the extent of use of ICTs
ICTs Weighted
score
Mean SD Rank
Mobile Phone 1042 4.61 1.714 1
TV 922 3.30 1.761 2
Radio/FM 521 2.61 1.688 3
Agri. websites 72 2.44 0.720 4
Internet 203 2.12 1.206 5
Agri. helplines 40 2.00 0.609 6
Social media 148 1.34 1.132 7
Computer 116 1.21 1.036 8
Fixed phone/ land line phone 25 1.00 0.484 9
According to the data in Table 4.13, mobile phone was the prominent and widely utilized
ICT. It fell under high usage category with mean value 4.61. TV appeared 2nd leading ICT
under use of respondents with mean value 3.30. Use of radio was dismal as well,
endorsed with the mean value of 2.61 which is hardly approaching towards medium level.
Findings are similar to those of Agwu et al. (2008) where they reported TV, radio and
mobile phone as highly utilized information sources by the farmers.
Use of agricultural websites, internet and helplines was gloomy as mean values were
barely of low level. Use of social media and computer was slight above very low level
with use of fixed phone was of very low level. Findings are supported by the results of
Kodagavallihatti et al. (2016) where they disclosed dismal use of internet and social
media for information receiving on farm operations. This implies that respondents in the
study area were far away from use of modern technologies except mobile phone. Time
51
saving and user friendly nature of mobile phone decreased the use of TV and radio which
have been strong information tools in the past.
EFS illustrated that “mobile phone is leading medium in meeting
information needs. On contrary, trend of using modern tools like internet,
social media and helplines is scanty”
4.2.3 Purpose of using ICTs
ICTs are diversified and embark multiple usage. Respondents were asked to unveil their
purposes of using various ICTs. The main purpose of this particular question was to
assess the importance of ICTs as sources of information. Data in this regard are presented
in Table 4.14.
Table 4.14: Respondents’ distribution according to their purpose of using ICTs
ICTs Entertainment Information Infotainment
f % f % f %
Radio/FM 82 20.5 69 17.3 32 8.0
TV 209 52.3 52 13.0 58 14.5
Internet 22 5.5 17 4.3 34 8.5
Computer 15 3.8 8 2.0 15 3.8
Mobile Phone 75 18.8 169 62.3 96 24.0
Social media 19 4.8 13 3.3 8 2.0
Fixed phone/ land
line phone 0 0.0 7 1.8 0 0.0
Agri. helplines 0 0.0 11 2.8 0 0.0
Agri. websites 0 0.0 28 7.0 0 0.0
Purposes of using ICTs by respondents are well documented in Table 4.14. TV was
revealed as prominent entertainment source by more than half (52.3%) of the respondents.
While only 20.5% respondents considered radio as entertainment source. Mobile phone
was narrated as entertainment source by less than one fifth (18.8%) of respondents. While
other ICTs were less preferred entertainment sources by the respondents. Regarding
information acquisition, mobile phone obtained agreement of 62.3% of respondents. They
were of the view that they can communicate with their peers, neighbors, friends, inputs
52
dealers, EFS and other experts without any limitations of timing through mobile phone.
Less than one fifth (17.3%) of the respondents used radio and 13% use TV for
information purpose. In the context of infotainment (obtaining information as well as
entertainment) about one fourth (24%) argued that they were using mobile phone. TV was
used by 14.5% respondents for infotainment. Infotainment from other media ranged
between 0-8.5%.
EFS argued that “prominent use of ICTs is information seeking by farmers
while as agriculture information source their usage is limited. However,
use of mobile phone in exchanging and accessing agricultural information
is higher”. They further argued that “they frequently receive calls from
farmers for the solution of their problems. On contrary, usage of modern
media is limited pertinent to number of constraints including inadequate
interest”.
In short mobile phone was the leading medium used by the respondents for information
and infotainment. While, computer, social media, internet, fixed phone, agri. helplines
and websites were the least used ICTs. Above stated results contradict with the findings
of Shaikh (2007) and Dinpanah and Lashgarara et al. (2011) where they reported radio
and TV as leading sources of infotainment. However, above results are similar to Singh
(2008) and Choi (2009) where they iterated mobile phone as leading source of
information and connectivity.
4.2.4 Use of ICTs for agricultural information
Agriculture information is imperative for tackling crop related challenges and obtaining
targeted production. Hence, respondents were asked to specify the use of various ICTs
specifically for getting agricultural information. Data were collected using Likert scale
(1=never, 2=rarely, 3=some time, 4=often, 5=always), are presented in Table 4.15.
53
Table 4.15: Respondents’ distribution according to extent of ICTs use for
obtaining agricultural information
ICTs Weighted score Mean SD Rank
Mobile Phone 1007 2.52 1.414 1
Radio/FM 721 1.87 1.287 2
TV 746 1.80 1.165 3
Internet 497 1.24 0.696 4
Computer 440 1.17 0.651 5
Social media 469 1.15 0.662 6
Fixed phone/ land line phone 419 1.10 0.403 7
Agri. helplines 460 1.10 0.475 8
Agri. websites 468 1.05 0.213 9
n = 400 *Total frequency acceding from 400 due to multiple use of various ICTs
Data in Table 4.15 illustrate the varied rate of obtaining agricultural information from
different ICTs. Among different ICTs, mobile phone was the only medium often used
(30.5%). Hence, mobile phone stood on 1st rank with mean value of 2.52. During
discussion respondents iterated that through mobile phone they feel more convenient in
sharing their problems with EFS and agricultural inputs dealers.
Radio stood on 2nd rank with mean value of 1.87. Though mean value is gloomy, but one
in ten respondents (9.8%) was using radio often for agricultural information. TV stood on
3rd rank with mean value of 1.80 followed by internet which stood on 4th rank with mean
value of 1.24. Nevertheless, mean value of internet is very low. Just like, computer, social
media, fixed phone, agri. helplines and websites showed the same trend. Overall, mobile
phone was the leading medium used for agricultural information by respondents.
54
4.3 Emerging trends of ICTs regarding agricultural information
dissemination
Use of ICTs is mounting in agriculture sector. ICTs are dully effective in farm operations
and dissemination of technologies. Therefore, with the passage of time to meet the future
needs ICTs are getting evolved and improved. According to Khosrowpour (2006)
emerging trends and challenges in ICTs reflect the latest issues adjoining management of
ICTs in organization and explains how these issues are addressed and used for the
benefits of practitioners and educators across the world. This study was meant for probing
the emerging trends of ICTs as perceived by the farmers. In this study the term “emerging
trends” refers to those modern technologies and services offered to farmers by the public
or private organizations. In addition to traditional sources of information farmers need to
know about emerging trends.
In this context, respondents were asked to unveil their familiarity with the emerging
trends of ICTs. The data in this regard are presented in Table 4.16.
Table 4.16: Respondents’ familiarity regarding radio/FM based agricultural
programmes
Agri. radio/FM broadcasts
Familiarity
Yes No
f % f %
Utam Kheti (Multan) 141 35.25 259 64.75
Dharti Bakht Bahar (Bahawalpur) 113 28.25 287 71.75
Khet Khet Haryali (Lahore) 11 2.75 389 97.25
Jithey Terey Hul Wagdey (Lahore) 06 1.5 394 98.5
Sandil Dharti (Faisalabad) 03 0.75 397 99.25
Wasda Raye Kissan (Sargodha) 00 0.0 400 100.0
Wasney Rehan Garan (Rawalpindi) 00 0.0 400 100.0
Thal Singhar (Mianwali) 00 0.0 400 100.0
Zarkhaiz Pakistan (Islamabad) 00 0.0 400 100.0
Data depicted in Table 4.16 are all about various agricultural programmes of Radio/FM
regarding dissemination of agricultural information. Radio Pakistan is broadcasting
various regional programs across the country. In this regard, Utam Kheti was the leading
programs known to approximately 35.3% of respondents. This program is broadcast of
radio Pakistan “Multan” station. Radio program “Dharti Bakht Bahar” broadcast of
Radio Pakistan Bahawalpur, was known to 28.3% of the respondents. During informal
55
discussion it was found that inclination of respondents was towards these programs.
There are number of other broadcasts of different radio stations, but their awareness was
negligible among respondents. The main cause of this unawareness was restricted
broadcast of these radio stations in other districts. Quite interestingly, radio programs
“Khet Khet Haryali”and “Jithey Terey Hal Wagday” broadcast of Lahore and “Sandhal
Dharti” from Faisalabad radio stations were known to negligible number of respondents.
Respondents claimed that their relatives and friends residing in these areas were the major
source of information in this context. However, awareness was mere a familiarity, they
have never listened to these programs. They further acclaimed that if these programs were
broadcasted in our region, they would have listened these programs.
Table 4.17: Respondents’ familiarity regarding TV based agricultural
programmes
Agri. TV telecasts
Familiarity
Yes No
f % f %
Zamindara (Waseb TV) 156 39.0 244 61.0
Khaiti (Rohi TV) 140 35.0 260 65.0
Haryali (PTV home) 124 31.0 276 69.0
Kissan Time (Channel 5) 71 17.75 329 82.25
Khait Punjab Day (Punjab TV) 9 2.25 391 97.75
Zarat Nama (ATV) 2 0.5 398 99.5
Dehat Sudhar (Sohni Dharti) 0 0.0 400 100.0
The data depicted in Table 4.17 show awareness of TV programs among respondents.
Only two programs “Zamindara” broadcasted on Waseb TV and “Khaiti” a broadcast of
Rohi TV were the prominent ones, as reported by 39 and 35% respondents. Respondents
perceived these programs informative because of being broadcasted in local language
“Saraiki”. During discussion it was also unveiled that low awareness may be attributed to
limited connections of cable network. More often these channels are aired on cable
network except PTV home which is national TV of the country and “Haryali” is the only
broadcast related to agriculture on national TV. Less than one fifth (17.7%) respondents
knew “Kissan Time” program on channel 5. The interesting fact unveiled was, that
majority of respondents was familiar with “Kissan Time” because it has been broadcasted
56
on different channels since recent past. Though respondents were unaware about the
current status of program. Similar trend was seen regarding broadcast of “Sohni Dharti”.
Hence, awareness about broadcasts of ATV, Punjab TV and Sohni Dharti were almost
negligible.
Table 4.18: Respondents’ familiarity regarding internet based agricultural
information dissemination services
Internet (web based)
Familiarity
Yes No
f % f %
Agri. websites 31 7.75 369 92.25
Fertilizer calculator 15 3.75 385 96.25
e-marketing 6 1.5 394 98.5
Social media 12 3.0 388 97
According to data mentioned in Table 4.18, only 16.1% of respondents were familiar with
the trends in available internet-based services. According to the data, agricultural
websites, fertilizer calculator, e-marketing services and social media were known to 7.8,
3.8, 1.5 and 3% of respondents, respectively.
57
Table 4.19: Respondents’ familiarity regarding mobile (apps & helpline) based
agricultural information dissemination services
Mobile (apps & helpline)
Familiarity
Yes No
f % f %
Bakhabar Kissan (Helpline 03030300000) 121 30.25 279 69.75
Khushal Zaminadr (Helpline 7272) 50 12.5 350 87.5
Warid Kissan Line (Helpline 2244) 45 11.25 355 88.75
Agricultural Business 34 8.5 366 91.5
Animal Clinic 31 7.75 369 92.25
Zong Kisan Portal (Helpline700) 30 7.5 370 92.5
Agriculture Corner 30 7.5 370 92.5
Facebook Pages 19 4.75 381 95.25
Plant Clinic 23 5.75 377 94.25
UKisaan (Helpline700) 23 5.75 377 94.25
Horticulture UAF 19 4.75 381 95.25
Cellular companies provide a number of mobile based services for the farmers. Among
these services, the majority is helplines based in the form of cellular apps, applicable on
smartphones. Data presented in Table 4.19 are illustrative of the familiarity of
respondents with available mobile-based services. It is evident that Bakhabar Kissan was
the leading helpline service known to 30.3% of respondents. Khushal Zamindar and
Warid Kissan Line were known to 12.5 and 11.3% of respondents, respectively.
Familiarity of rest of the helpline and mobile app services was less than 10%. This
implies that awareness of these services among respondents was almost negligible.
Familiarity of rest of the apps and services like plant clinic, facebook pages, agricultural
business, animal clinic, Ukissan and Horticulture UAF was almost negligible. There is no
doubt in the potential of mobile and mobile based services, but below average awareness
is questionable which further documents that farmers are not fully aware about the
potential of mobile phone for sharing and receiving agricultural information. Findings of
Kirui et al. (2010) negate the present results. Their findings iterated that mobile based
service like m-banking was widely known to farmers. Transactions made through m-
marketing were being invested on improving farm operations and production level.
58
Farmers were involved in sharing latest, site specific and market driven information
through mobile based social services (Ilahiane, 2007). Findings of Chhachhar and Hassan
(2013) endorsed that mobile services enabled farmers to communicate directly with
marketing agents and brokers and also with meteorological department for weather
related information (Duncombe, 2011). It can be concluded that mobile is one of the
effective media to bridge information gap enhanced access to information, but in
Pakistani settings farmers are yet underprivileged in this regard due to less education.
Table 4.20: Respondents’ familiarity about toll-free helpline services (public &
private) regarding agricultural information dissemination
Toll free helpline services
(public & private)
Familiarity
Yes No
f % f % Helpline Source
0800-15000 PAH (DAI)
46 11.5 354 88.5
0800-29000 42 10.5 358 89.5
0800-78686 L&DD
23 5.75 377 94.25
0800-78685 17 4.25 383 95.75
0800-54726 Kissan Dost 17 4.25 383 95.75
0800-00332 FFC 11 2.75 389 97.25
Note: (Punjab Agricultural Helpline) PAH, Directorate of Agricultural Information (DAI)
Livestock & Dairy Development (L&DD), Fauji Fertilizer Company (FFC)
Data depicted in Table 4.20 indicate trends of public and private helpline services and
their role in dissemination of agricultural information among farmers. There are different
helplines served by different public and private organizations. Helplines served by PAH
were known to 11.5 and 10.5% of respondents. While helplines of L&DD were known to
5.8 and 4.3% of respondents followed by the helpline of Kissan Dost which was familiar
to 4.1% of respondents. Helpline offered by FFC was known to only 2.8% of respondents.
This confirms that emerging trends of helplines are scanty in gaining interest of farming
community. Aldosari et al. (2017) stated that only 14.2% respondents were familiar and
59
in consensus with use of helpline for information acquisition. These findings are in line
with the present study that familiarity of helpline is meager among farming communities.
Discussion with EFS further confirmed that farmers were reluctant in using
helplines for information acquisition. It was also highlighted that farmers
perceived use of helplines as time consuming process.
4.3.1 Obtaining various kinds of information from ICTs
Farmers may use ICTs for obtaining various kinds of information depending upon the
situation. Therefore, respondents were asked about that what kind of information they had
obtained from ICTs. The data (Appendix-1, Table 2) were collected using Likert scale
(1=never, 2=rarely, 3=some time, 4=often, 5=always) which are presented in Table 4.21.
Table 4.21: Various kinds of information obtained from ICTs by respondents
Information regarding Weighted
score
Mean SD Rank
Production of major crops (wheat,
cotton, rice, sugarcane etc.) 1402 3.51 1.648 1
Plant protection measures (pest, insects
and dieses management) 1307 3.27 1.529 2
Weather updates 932 2.33 1.463 3
Livestock & poultry management 930 2.33 1.336 4
Harvesting and post harvesting
practices 838 2.10 1.245 5
Marketing of agricultural produce 752 1.88 1.168 6
Farm resource conservation 716 1.79 1.067 7
Access to credit 683 1.71 1.125 8
New cropping scheme 656 1.64 1.113 9
Data depicted in Table 4.21 show that respondents were utilizing agricultural helplines
for different ventures of agriculture. It is evident that respondents were more concerned
about information regarding production of different major crops. The study area was
typically cotton oriented; hence, more focus was on receiving agricultural information
regarding production and protection of standing crop. Information acquisition regarding
production technology of major crops stood at 1st rank with mean value of 3.51 followed
by plant protection measures obtaining 2nd rank and mean value of 3.27. Weather updates
60
and livestock management stood at 3rd and 4th rank with mean value of 2.33. Conversely,
Etwire et al. (2017) rated the information received related to weather as useful. Mital
(2012) illustrated that about 90% Indian farmers received weather related information
through phone and reported useful. Another study conducted in Tanzania by Angello
(2015) unveiled that 96.5% farmers reported weather related information acquisition
through mobile and rated useful in improving livestock. This implies that mobile is a vital
source from where diversified information could be harnessed. Unfortunately, in current
study, scope of receiving information through mobile is not up to the mark. This
inadequate information may lead farmers to increase their production cost and low farm
production (Mawazo, 2015) and poor returns (Courtois and Subervie, 2013). In actual,
farmers could choose and plan better to improve their farm production by seeking
information through mobile (Asenso-Okyere and Mekonnen, 2012).
It is also evident from the data that information obtained regarding harvesting of crop,
marketing of harvested produce, farm resources conservation, access to credit and
familiarity with new cropping schemes appeared ranging between low and very low
levels. This implies that farmers were unaware of this hidden potential of mobile phone or
they may have any other source to meet the information requirements on these aspects.
EFS said that “Farmers used to make calls to Agriculture Officers and
Field Assistants for acquiring information on multiple aspects including
production and protection aspects.” One Agriculture Officers stated that
“Currently farmers tend to be informed regarding subsidy schemes of
government. Despite availability of latest information on websites, farmers
rarely to visit those websites and prefer mobile phone.”
61
4.3.2 Preferred ICTs of respondents
After assessment of familiarity of the users with emerging trends of ICTs, respondents
were asked to unveil information tool they would like to prefer for effective information
acquisition in future. Their extent of preference was measured by using the Likert scale
(1=very low, 2=low, 3=medium, 4=high, 5=very high). Data in this regard (Appendix-1,
Table 3) are presented in Table 4.22.
Table 4.22: Extent of future preference of ICTs given by respondents to various
ICTs for getting agricultural information
ICTs
Extent of preference
Rank Weighted score Mean SD
Mobile 1216 3.86 1.156 1
TV 878 3.28 1.303 2
Radio/FM 537 3.12 1.141 3
Internet 277 3.04 1.357 4
Agri. websites 204 2.55 1.509 5
Agri. helplines 196 2.55 1.187 6
Computer 144 2.25 1.208 7
Land line phone 114 1.84 .891 8
According to data depicted in Table 4.22, mobile appeared most preferred ICT tool in
future for agricultural information. It was ranked 1st with mean value of 3.86. TV
appeared 2nd ranked ICT tool with mean value of 3.28 followed by radio obtaining mean
value of 3.12. While TV and radio were also preferred for future use by 67 and 43%
respondents, respectively. During informal discussion, farmers pointed out that in future,
use of ICTs will depend upon the quality of agricultural programs offered through various
ICTs.
Internet obtained mean value of 3.04 and 4th rank in terms of preference. Respondents
argued that utilization of internet is dependent upon them knowledge and skills which are
scanty at present. Ekundayo and Ekundayo (2009) revealed that limited experience of
computer use among respondents prevented e-Learning uptake. For effective utilization
62
of internet, it is imperative to enrich farming communities with extensive knowledge of
internet use. Similar concern was posed by respondent regarding use of agricultural
websites. Websites, helplines, computer and landlines phone were least preferred ICT
tools, as expressed by the respondents. It may be stated that inadequate computer literacy
among respondents could be the possible reason behind least preference of computer use.
Collaterally, majority of the respondents are in the phase of age, where learning
technicalities of computer is harder. Therefore, preference was given to traditional media
which are user friendly and cost effective. Adoption of e-Learning technologies are
associated with civilizing computer literacy (Ngamau, 2013).
EFS expressed that “optimizing use of websites, helplines and computers
for information exchange is full of potential. Hence, Government and
institutions should diversify their role and offer accessible services on
websites for farmers”
4.3.3 Preferred language for agricultural information
Language is important element in communication process. Inappropriate language may
obstacle information dissemination. The culture and language have effect on both the
information providers and the information users (Adetoun, 2006). Local language can be
considered more effective and understandable for the farmers in obtaining information
(Jumani, 2009).
Therefore respondents were asked to reflect their preferable language for receiving
agricultural information from different information sources. Data in this regard are
presented in Table 4.23.
Table 4.23: language preference of respondents for getting agricultural
information from various ICTs
Language f %
Local Language (Saraiki) 201 50.2
Urdu 120 30.0
Both (Urdu and local language) 79 19.8
Total 400 100.0
According to data depicted in Table 4.23, local language (Saraiki) was reported as most
preferred language of information sharing by 50.2% of respondents. Less than one third
(30%) of respondent preferred urdu. Almost one fifth (19.8%) respondents were in favor
63
of urdu and local language. They could understand either way. Results of the study are
similar to Khan, (2010) who reported that, respondents feel more comfortable with their
local language in acquiring agri. information than other language.
4.4 Assessment of effectiveness of ICTs as sources of agricultural
information
The potential of ICTs to contribute agriculture and rural development has been well
recognized (Singh 2006). ICTs can help farmers to access new knowledge and updated
information. According to Steinen et al. (2007) there are several ICTs viz, internet,
computer, mobile, electronic media and traditional sources being used to facilitate
farmers. Therefore, assessment of the effectiveness of these ICTs is imperative
considering different aspects and needs of the farmers. Rodriguez (2008) had stated that
timeliness of agricultural information is key for the farmers. Farmers often need
information on right time to apply on their farms for better production. Whereas, timely
availability of information is also crucial for farmers to manage farm operations
accordingly (ibid). Farmers would prefer to seek a source with timely and reliable
information. According to Fu and Akter (2010) due to ICTs use, extension service
delivery has become speedier, reliable and quality oriented for the farmers. EFS used
ICTs to collect and disseminate local as well as new knowledge among farmers (Stienen
et al, 2007).
4.4.1 Effectiveness of ICTs as sources of agricultural information
ICTs are bridging the information gap and providing an opportunity of better
communication between farmers and EFS. Thus, respondents were asked to report the
effectiveness of different ICTs as they perceived. Perceived effectiveness was recorded
on the Likert scale (1=very low, 2=low, 3=medium, 4=high, 5=very high). Data in this
regard (Appendix-1, Table 4-11) are presented in Table 4.24.
64
Table 4.24: Effectiveness of ICTs as sources of agricultural information for respondents
Effectiveness
Mobile TV Radio Internet Computer Landline Agri.
helpline
Agri.
websites
Mean± SD Mean ± SD Mean ± SD Mean ± SD Mean ± SD Mean ± SD Mean ± SD Mean ± SD
Better agricultural
information source 4.17+0.99 3.98±0.97 4.11±0.82 3.54±1.55 2.89±1.55 2.70±1.54 3.19±1.36 3.78±1.41
Improve farming skills 4.12±0.72 3.65±0.89 3.73±0.99 3.59±1.39 2.66±1.34 2.78±1.36 2.93±1.34 3.56±1.30
Provide accurate
information 3.96±0.74 3.88±0.80 4.12±0.91 3.96±1.24 2.66±1.73 3.08±1.15 3.22±1.28 3.49±1.31
Better communication 4.05±0.89 3.81±0.89 4.21±0.82 3.81±1.98 2.90±1.67 2.68±1.25 3.52±1.58 3.36±1.25
Provide timely
information 4.32±0.79 3.68±0.85 4.09±0.84 3.94±1.28 2.72±1.22 2.56±1.29 3.09±1.42 3.22±1.27
Cheaper source of
information 3.95±0.72 4.28±0.80 3.50±1.16 2.85±1.31 2.86±1.36 2.76±1.02 3.58±1.31 3.14±1.34
Easy to use 3.95±0.61 4.21±1.01 3.79±1.18 2.70±1.30 2.20±0.70 3.07±1.38 3.50±1.18 2.58±0.91
Easy access to
information 4.02±0.91 4.22±0.91 4.28±0.74 3.84±1.19 3.00±1.06 3.10±1.34 3.29±1.41 2.65±1.07
65
Data depicted in Table 4.24 highlight the effectiveness of various information sources as
perceived by respondents. Among various ICTs mobile was perceived more effective
information source by respondents. Mobile was perceived an important source of
providing timely information (mean=4.32). Respondents informally reported that mobile
phone enabled us to contact EFS to get information as and when needed. Moreover,
smartphones and internet allowed farmers to access information in no time (mean =4.02).
Otter and Thruvsen (2014) had reported that mobile, internet and email services had
positive contribution in farm and farmers development. Mobile was perceived better
agriculture information source (mean =4.17) as compared to other ICTs. Respondents
reported improvement in their farming skills due to use of mobile phone (mean =4.12).
Findings are supported with those of Otter and Thruvsen (2014) as mobile fostered the
development level of farmers and farm production ultimately. Mobile phone, being a
portable device was perceived as a source of better communication with fellow farmers
and EFS to meet their information needs (mean =4.05). This kind of effectiveness of
mobile phone among farmers was reported in the studies conducted by Aldosari et al.
(2017) and Chhachhar et al. (2014). These studies reported mobile phone as one of the
most effective ICTs.
TV appeared an effective tool of accessing information by the farmers. Farmers perceived
TV a cost effective medium to access agricultural information as compared to radio due
to both audio and video effect (mean=4.28). Respondents further arbitrated that accessing
information on TV (mean=4.22) and using TV is an easy (mean=4.21) for farmers. This
implies that TV is a user friendly medium for the farmers and accessing agricultural
information on TV is an easier for them. During informal discussion respondents viewed
that agriculture related programs broadcasted in local language significantly attracts the
attention of farmers. Various research studies have reported TV as one of the effective
tools helping farmers to access agricultural information (Ashraf et al., 2015; Muhammad
et al., 2008; Ashraf, 2008).
Effectiveness of the mobile and TV as agricultural information sources among farmers
was further endorsed by the EFS. They made a statement that;
“Mobile and TV are widely used and effective sources of agricultural
information among farmers. Mobile phone is equally important for
farmers and EFS for information dissemination and organizing farmers’
meetings. Inception of smart phones enabled both stakeholders to foster
66
communication and escalating learning process through audio and video
information.”
Radio is another source of information for the farmers. In time availability (mean=4.09),
easy access to information (mean=4.28), better communication (mean=4.21) because
respondents says that radio broadcast agricultural programmes in local language which
are easy to understand, accurate information (mean=4.12) and effective source of
information (mean=4.11) were the main features of radio as perceived by respondents and
termed this tool effective in meeting their information needs. The mean value in case of
all features indicate that effectiveness of radio was perceived higher. These results are
similar to those of Khan and Shabbir (2000), Ekoja (2003) and Arokoyo (2003) who
reported radio as an effective source of information for farmers due to its easy to use
nature and potential of disseminating information to larger audiences.
Findings further reflect that internet was perceived considerably less effective as
compared to radio, TV and mobile phone. The mean value more indicates that
effectiveness of internet stood at medium level. However, internet was perceived as
source of accurate information (mean=3.96), timely information (mean=3.94), better
communication (mean=3.81), improvement in farming skills (mean=3.59) and better
agricultural information source (mean=3.54). Findings are supported with the results of
Adomi et al. (2003) and Chilimo (2009) as they had reported a low pace and utilization of
internet as an agricultural information source among farmers. Shetto (2008) had reported
that accessing agricultural information on internet is rather difficult as compared to other
ICTs. Furthermore, accessing information on internet is mainly preference of literate
farmers. Results of this study show that educational level of the respondents in the study
area was not substantial as 45% respondents were illiterate. This illiteracy among
respondents pushed farmers to use traditional and user friendly tools like TV, radio and
mobile. Like internet, effectiveness of computer was perceived meager as well. Internet
and computer are modern tools having a great potential. However, contribution in
meeting information needs of the farmers was found poor. Easy access to information on
computer obtained mean value (3.00) reporting effectiveness of medium level. While in
case of better agricultural information source, improving farming skills, providing, better
communication accurate information, timely information, cheaper source of information
and easy to use computer reported mean values as 2.89, 2.66, 2.66, 2.90, 2.72, 2.86 and
2.20.
67
Landline was another medium used by farmers to access agricultural information.
Respondents perceived that landline was a source of an easy access to information
(mean=3.10), easy to use (mean=3.07), better agricultural information source
(mean=2.70), improving farming skills (mean=2.78), providing accurate information
(mean=3.08), better communication (mean=2.68), timely information (mean=2.56) and
cheaper source of information (mean=2.76).
Helpline was perceived considerably effective information source by the respondents.
They perceived it a better source of agricultural information (mean=3.19), helped in
improving farming skills of farmers (mean=2.93), served as accurate information
(mean=3.22), source of better communication (mean=3.52), provided in time information
(mean=3.09) and acted as cheaper source of information (mean=3.58). These results are
similar to those of Arfan et al. (2013) as they found helpline more effective source
information for farmers as compared to other sources. During informal discussion,
respondents expressed that making a call on helpline is quite easy and the expert on other
side respond to their questions promptly. They further arbitrated that this involves almost
a negligible cost. Another study conducted by Aldosari et al. (2017) reported that only
14.2% respondents strongly agreed that helpline could be an effective information source
while 14.2% strongly disagreed the statement. About one fifth (21.5%) respondents
agreed that helpline could be an effective information source. Subramanian et al. (2017)
had reported that agricultural extension helplines induced crops yield recovery by
augmenting awareness among farmers.
Websites are one of the emerging information sources. Visual features and contents
downloading options escalates the value of websites as information source. Thus,
websites were perceived as better agricultural information source (mean=3.78).
Respondents reported that use of websites to access agricultural information improved
their farming skills (mean=3.56), provided accurate information (mean=3.49), better
communication (mean=3.36) and provided timely information (mean=3.22). Websites
were cheaper sources of information (mean=3.58) as accessing information on website do
not involve a major cost except availability of internet connectivity and knowledge
regarding use of websites. Respondents perceived websites as easy to use (mean=2.58)
for information seeking. Accessing information on websites was also perceived as an easy
task by the respondents (mean=2.65), though effectiveness stood less than medium level.
4.4.2 Preference for getting agricultural information from ICTs
It is well documented that farmers had used ICTs for multiple avenues. Respondents were
further asked to indicate preference regarding receiving information about various aspects
of agriculture. Likert scale (1=low priority, 2=somewhat priority, 3=neutral, 4=high
68
priority, 5=very high priority) was used to get the preference of the respondents. Data are
(Appendix-1, Table 12) mentioned in Table 4.25.
Table 4.25: Preferred areas of agriculture by respondents for getting information
from ICTs
Various areas of Agri. information Weighted
score
Mean SD Rank
Agronomic practices (land preparation/seed,
fertilizer, irrigation etc.) 1411 4.23 1.133 1
Plant protection measures 1337 4.16 0.943 2
Marketing 1151 3.97 1.089 3
Harvesting/post-harvest technology 1062 3.92 1.075 4
Agri. loan schemes 1034 3.63 0.969 5
Storage techniques 1025 3.46 1.085 6
Farm mechanization 996 3.51 1.058 7
Farm management 776 2.88 1.638 8
Data quoted in Table 4.25 highlight those areas in which respondents were deficient and
would prefer to receive relevant information. Further agronomic practices including
different farm operations were the first (1st) preference of respondents on which they
would like to gather information through different information media. Receiving
information on plant protection measures will be 2nd priority (mean= 4.16). Respondents
disclosed that they faced significant yield reduction due to insect pests and diseases
infestation, especially in cotton. Hence, they agreed that enriching information on plant
protection was basic need of the farmers. On one side respondents highlighted yield
reduction due to diseases; on other hand they posed a stance that marketing system of the
country is collapsed. Sluggish marketing doubles the magnitude of loss. Therefore, they
intend to be in touch with media to get information about agricultural marketing and
secure their possible profits. Marketing obtained mean value of 3.97 and 3rd rank on the
scale. Information regarding harvesting of crop was fourth preference. Respondent urged
to be informed about agricultural loan schemes implemented by the government and
private sectors. Majority of the respondents was small farmers and their livelihoods were
feebler. Loan schemes bridge their financial gap. In this concern, farmers were more
concerned about letting them know about loan schemes (mean=3.63; rank; 5). Storage
69
techniques, mechanization and farm management related information was desired by the
respondent in future course of action as well.
4.5 Challenges faced by the respondents regarding the use of ICTs
Farmers are exposed to various ICTs to meet agricultural information needs in developing
countries because most of ICTs initiatives in such countries address only the information
needs of the farmers. As a result, farmers are not able to get additional information and
transform it into tangible benefits (Kameswari et al., 2011; Kaddu, 2011). Whereas
effectiveness and contribution of ICTs as agricultural input information is not acclaimed
at best (Kante et al., 2016). According to Churi et al. (2012), poor education of the
farmers’ hinder the utilization of ICTs. Whereas Voh (2002) had stated that new
technology uptake is associated with education of the farmers. Educated farmers can
effectively access and use ICTs for their desired purpose (Okwu and Ioorka, 2011). In
some studies, infrastructure is revealed as important factor for suppressing or persuading
the use of ICTs. Among other sources radio is a useful source of agricultural information
but it needs improvement in the areas of service delivery with a view to overcoming
language barrier, poor presentation of key points and improper interpretation of scientific
terms (Olaleye et al., 2009; Sife et al., 2010; Abubakar et al., 2009; Manyozo, (2009).
Similarly, mobile phone is perceived as preferable information source due to its wide
infrastructure, increased number of services and offers for users (Mtega and Msungu,
2013). Relevant, in time and reliable information is the need of farmers to increase farm
production (Rodriguez, 2008). Thus, it was presumed necessary to unveil whether or not
farmers are properly utilizing ICTs for their information needs and to identify the
obstacles they are facing in this regard. Respondents were asked to report the perceived
obstacles on 5 point Likert scale (1=very low, 2=low, 3=medium, 4=high, 5=very high).
The data in this regard (Appendix-1, Table 13 -20) are presented in Table 4.26.
70
Table 4.26: Extent of challenges faced by respondents regarding the use of ICTs
Challenges Radio TV Mobile Internet Computer Landline
Agri.
helpline
Agri.
website
Mean± SD Mean ± SD Mean ± SD Mean ± SD Mean ± SD Mean ± SD Mean ± SD Mean ± SD
High cost 3.15±1.16 2.72±1.25 3.86±0.80 3.75± 0.92 2.90±1.23 3.15±1.36 3.50±1.42 3.20±1.29
Lack of education 3.49±0.86 2.68±1.17 2.51±1.34 3.65±0.82 3.79±0.78 3.71±0.92 3.92±0.79 3.85±0.81
Lack of time (busy) 3.31±1.04 3.03±1.06 2.98±1.02 3.48±0.83 2.89±1.11 2.54±1.09 3.17±1.57 3.14±1.23
Language (difficult) 3.34±0.93 3.34±0.88 3.21±0.96 3.26±0.93 3.14±1.19 3.09±1.50 3.58±1.05 3.24±1.09
Inadequate
information 3.21±0.87 3.05±1.07 2.70±092 3.43±1.06 2.97±1.32 2.74±1.70 3.88±1.12 2.59±1.15
Lack of credibility of
medium 3.18±0.79 2.97±1.01 2.67±0.92 3.29±1.07 2.69±1.31 3.03±1.52 3.63±1.40 3.24±1.16
Lack of ownership 3.15±0.84 3.02±0.89 2.85±1.11 3.23±0.99 3.58±0.84 3.72±0.82 3.03±1.12 3.28±1.17
Odd transmission
time 3.36±0.91 2.79±1.08 2.64±1.16 3.03±1.04 2.48±1.21 2.26±0.98 3.60±1.35 3.12±1.33
Lack/poor feedback 2.85±1.21 3.38±0.97 3.44±0.94 2.63±1.26 2.41±1.22 3.14±1.56 3.37±1.49 3.30±1.15
Lack of visual impact 3.40±0.87 3.01±1.02 2.69±0.94 2.90±1.16 3.00±1.13 2.51±1.29 3.07±1.14 2.42±1.34
Poor quality
transmission 3.16±1.02 3.50±0.77 2.73±1.18 2.84±1.18 2.69±1.04 2.26±1.05 3.30±1.08 3.04±1.24
Lack of interest 2.74±1.24 3.23±0.99 2.63±1.26 2.89±1.12 2.86±1.30 2.26±1.17 2.87±1.35 3.32±1.18
Lack of awareness 2.56±1.13 2.95±1.07 2.37±1.18 2.67±1.30 2.59±0.90 2.44±1.15 3.17±0.98 3.38±1.04
71
Potential of ICTs as information sources is not fully achieved pertinent to a number of
obstacles. According to data depicted in Table 4.26 regarding use of radio, lack of
understanding of the listeners with respect to technical terms used by experts in different
agricultural programmes (mean=3.49) was the prominent obstacle as perceived by
respondents due to their literacy level. While poor awareness of radio broadcast (mean=2.56)
was the least obstacle affecting the use of radio as perceived by the respondents. Among
other constraints odd transmission time of programmes (mean=3.36), language barrier
(mean=3.34), lack of time and busy schedule of farmers (mean=3.31) and inadequate
information about the programs (mean=3.21) were constraints of more than medium level.
Farmers were of the view that their busy routine and irrelevant broadcasting were
discouraging their attitude towards tuning in radio.
Regarding TV, poor transmission and broadcast quality were the highly perceived constraint
among farmers (mean=3.50). During discussion respondents argued irrelevant broadcasting
of programs followed by an overwhelmed barrier of language (mean=3.34) as major
obstacles. Findings are similar to those of Jafri et al. (2014) where they reported irrelevant
broadcasting on TV (Jafri et al., 2014). Majority of the broadcast on TV is in Urdu language
while respondents preferred to watch agricultural broadcasts in local language to enhance
understanding of shared message. Overall level of hindrance of these factors ranged between
medium to high level.
Mobile is most powerful and effective medium and is widely preferred by farmers. However,
high cost of mobile phone (mean=3.86) and language (mean=3.21) were the leading factors
suppressing effectiveness of mobile phone. The level of hindrance appeared approaching
towards high level. It was found that purchasing of smart phone was bit tough for farmers
because of high rates. While, software installed in smart phones is in English which limits the
usage of mobile phone among illiterate farmers. Though, educated and technically skilled
farmers can fully enjoy mobile based services. High cost and affordability constraints were
highlighted by Babu et al. (2012). Joseph and Andrew (2006) and Akpabio et al. (2007)
regarding use of mobile phone, TV, Internet and computer technologies.
Internet and computer are two sides of coin and mutually harness vast opportunities to grab
required information. However, extensive cost (mean=3.75) of affording internet, inadequate
education to use internet (mean=3.65) and computer (mean=3.79) and ownership issues of
72
internet (mean=3.23) and computer (mean=3.58) were prominent barriers. Farmers critically
highlighted that they were poorly skilled to use computer and having less access to internet
for information acquisition.
Use of landline phone was highly hampered by lack of ownership of respondents
(mean=3.72) while poor interest in use of landline phone (mean=2.26) was the least factor of
hindrance. Inadequate information (mean=2.74) was also the major barrier in effective use of
helplines. Farmers were not fully aware to use helpline to address their problems and needs.
Similar difficulty was unveiled by the respondents regarding use of websites (mean=3.85). It
can be summarized that inadequate education of respondents was major obstacle in the use of
internet, computer, landline phone, helpline and website as an information source. Various
research studies show significance of education in acceptance of technologies. For example,
use of internet was significantly influenced by educational level of farmers (Anastasioa et al.,
2011); Mwombe et al., 2014). More the education of farmers, more are the chances of using
internet and mobile phone (Adegbidi et al., 2012). Strong et al. (2014) summarized that
technological acceptance and adoption of a particular ICT medium is dependent upon
educational level of the users.
During informal discussion, EFS viewed that “illiteracy among farmers
confronted them in disseminating information. Therefore, prospects of modern
tools like websites, helplines, internet and computer are limited except among
those who are literate and technically sound. Irrelevant broadcasts and non-
availability of specified TV or radio channels are some prominent
impediments acclaimed by farmers while conducting farmers’ meetings.”
73
4.6 Training needs of respondents regarding effective use of ICTs
Training needs assessment enables policy divisions to formulate planning to fulfill needs of
the end users i.e. farmers. This section describes skill level of farmers to use ICTs. The
calculated skills level on 5-point Likert scale (1=poor, 2=fair, 3=good, 4=very good,
5=excellent) lay foundation of training need calculation. Data (Appendix-1, Table 21)
reported in Table 4.27 are the illustration of skill level and training needs assessment.
Table 4.27: Respondents’ skill level and training needs to use ICTs
ICTs Possessed skill
level
Required skill level/
Training needs SD Rank
Agri. websites 1.79 3.21 1.200 1
Computer 2.17 2.83 1.342 2
Landline Phone 2.29 2.71 1.487 3
Agri. helplines 2.71 2.29 1.618 4
Mobile 3.28 1.72 1.338 5
Internet 3.37 1.63 1.086 6
Radio/FM 3.46 1.54 1.175 7
TV 3.59 1.41 1.187 8
* Total skill level – Possessed skill level = Required skill level/ Training needs (Appendix-1, Table 21)
Data in Table 4.27 highlighted respondents’ current ability to use ICTs and their training
needs for future management. Skill level appeared least in respect of use of agricultural
websites while high regarding use of TV. Agricultural websites embarked maximum training
need (mean=3.21) while TV exhibited minimum need of training (mean=1.41). This implies
that respondents are very good in the use of TV but poor in the use of agricultural websites.
Skill in use of computer stood at 2nd rank which show that the training need of a high level.
Landline phone was ahead to computer phone arbitrating 2.71 mean value at 3rd rank on
training needs ranking. Obtained mean value is the expression of medium level of training
need. Findings are similar to those of Angello (2015) who found that majority of respondents
was inadequately trained regarding use of computer. Akpabio et al. (2007) endorsed that
inadequate computer literacy and trainings imparted to users affected the efficacy of
computer use for receiving agricultural information. Agricultural helplines were on 4th rank
74
followed by mobile and internet standing on 5th and 6th. Furthermore, use of mobile phone
required less training among farmers because of its user friendly nature.
4.7 Relationship between the independent (demographic characteristics)
and dependent (use of ICTs) variables
This section focus on the relationship between the demographic characteristics and extent of
use of ICTs. The demographic characteristics (age, education, landholding and area under
cultivation) were considered as independent variables. While use of ICTs for obtaining
agricultural information and future preference of ICTs were considered as dependent
variables. Pearson correlation statistical test was used for checking the association between
the variables. This is applied to check the degree of association among various variables. The
correlation is denoted by “r” and calculated by application of the following formula:
b(Sx)
r = ––––––––––
(Sy)
In this formula “b” is taken as slope and “Sx” and “Sy” are standard deviation of the
independent and dependent variables. The value of correlation coefficient range from -1 to
+1, if all the points fall truly on a line with positive slope then the correlation coefficient
having value of +1; in contrast if all the points truly fall on a line with negative slope then
the value of correlation coefficient is -1. In both ways, if the value is highly positive up to +1
and highly negative up to -1, it shows that there is a strong linear relationship between the
two variables because the points are quite closer to the line, but if there is no linear
relationship being established between the two variables, than value of correlation coefficient
is nearly zero. It depicts that there exists no relationship between the two variables.
Possibility is always there that the value of correlation coefficient comes as zero (0) or near
to zero. It will be taken as nonlinear relationship or no relationship between the two variables
(Agesti and Finlay, 1997).
4.7.1 Relationship between demographic characteristics and using ICTs for
obtaining agricultural information
Data presented in Table 4.28 show the association between demographic characteristics and
specifically using of ICTs for obtaining agricultural information
75
Table 4.28: Correlation between demographic characteristics and using ICTs for obtaining agricultural information
Radio/FM TV Internet Computer Mobile
Phone
Social
media
Fixed
phone/
land line
phone
Agri.
helplines
Agri.
websites
Age
Pearson Correlation .227** -.086 -.131** -.129** .009 -.213** -.199** -.215** -.253**
Sig. (2-tailed) .000 .085 .009 .010 .857 .000 .000 .000 .000
N 400 400 400 400 400 400 400 400 400
Education
Pearson Correlation -.043 .172** .381** .145** .165** .252** .227** .206** .343**
Sig. (2-tailed) .386 .001 .000 .004 .001 .000 .000 .000 .000
N 400 400 400 400 400 400 400 400 400
Landholding
Pearson Correlation -.161** -.066 .168** -.089 .194** -.036 -.058 -.032 .051
Sig. (2-tailed) .001 .186 .001 .074 .000 .469 .247 .529 .305
N 400 400 400 400 400 400 400 400 400
Area under
cultivation
Pearson Correlation -.157** -.074 .151** -.103* .214** -.047 -.079 -.052 .037
Sig. (2-tailed) .002 .137 .002 .040 .000 .344 .115 .301 .456
N 400 400 400 400 400 400 400 400 400
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Table 4.28 represents the relationship among socio-economic characteristics and use of ICTs
for obtaining agricultural information:
Pearson correlation coefficient shows a highly significant and positive relationship
between and age and use of radio/FM for obtaining agricultural information. It means,
Aged farming community were having more use of radio for obtaining agricultural
information as compared to young farming community. Similarly, farmers’ age had
significant and negative relation between internet, computer, social media, landline
phone, agri. helpline and agri. Website. It means, young farming community were
having more use of Internet, computer, landline phone, agri. helpline and agri.
websites for obtaining agricultural information as compared to old age farmers. In
case of TV and mobile phone, there exited non-significant relationship with age
which shows that age group has no effect on the use mobile and TV for obtaining
agricultural information.
There was a significant and positive relationship found between education of farming
community and use of ICTs for obtaining agricultural information. It may be
concluded that farmers with high education, were more inclined towards use of TV,
Internet, computer, mobile phone, social media, landline phone, agri. helpline and
agri. websites for obtaining agricultural information as compared to illiterate farmers.
In case of radio, significant and negative relationship was found with size of land
holding. On the other side, mobile phone has positive relationship with landholding.
It means farmers having large landholding were using mobile phone for obtaining
agricultural information, while small farmers obtaining agricultural information from
radio. Similarly, a significant and negative relationship was found between area
under cultivation with radio, TV, computer, social media, landline phone and agri.
helplines while positive and significant relation was found between area under
cultivation with internet, agri. websites and mobile phone. It may be concluded from
data that, the farmers having more area under cultivation, make more use of internet
and mobile phone for obtaining agricultural information as compared to other ICTs.
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4.7.2 Relationship between demographic characteristics of respondents and their future preference for
ICTs for obtaining agricultural information
Relationship between demographic characteristics and future preference for ICTs for obtaining agricultural information presented
the future perspective regarding the usage of various ICTs. Data presented in Table 4.29 show the association.
Table 4.29: Correlation between demographic characteristics of respondents and their future preference for ICTs for
obtaining agricultural information
Radio/FM TV Mobile Internet Computer Land line
Phone
Agri.
helplines
Agri.
websites
Age
Pearson
Correlation -.106 -.318** .033 .177 -.039 -.152 -.378** .081
Sig. (2-tailed) .166 .000 .557 .093 .758 .240 .001 .473
N 172 268 315 ¤ 91 64 62 77 80
Education
Pearson
Correlation .401** .367** .332** .538** .457** .416** .422** .656**
Sig. (2-tailed) .000 .000 .000 .000 .000 .001 .000 .000
N 172 268 315 91 64 62 77 80
Landholding
Pearson
Correlation .383** .171** .324** .286** -.152 -.183 .163 .579**
Sig. (2-tailed) .000 .005 .000 .006 .232 .155 .157 .000
N 172 268 315 91 64 62 77 80
Area under
cultivation
Pearson
Correlation .378** .235** .340** .297** -.180 -.191 .171 .615**
Sig. (2-tailed) .000 .000 .000 .004 .154 .136 .137 .000
N 172 268 315 91 64 62 77 80
78
Above Table 4.29 represents the relation between socio-economic characteristics of
respondents and their future preference for ICTs for getting agricultural information
There exited a significant negative relationship between age and future preference of
TV for obtaining agricultural information. On the other side data show the significant
and positive relationship of education with use of ICTs (i.e. radio, TV, mobile,
internet, computer, landline phone, agri. helpline and agri. websites) for obtaining
agricultural information in future. It means, educated farmers were more likely to use
radio, TV, mobile, internet, computer, landline phone, agri. helpline and agri.
websites for obtaining agricultural information in future as compared to illiterate
farmers.
A significant and positive relationship of size of landholding was found with radio,
TV, mobile phone, internet and agri. websites. Similarly, significant positive
relationship exited between size of area under cultivation with radio, TV, mobile
phone, internet and agri. websites. It shows that farmers with more area under
cultivation were likely to use radio, TV, mobile phone, internet and agri. websites for
obtaining agricultural information in future than those farmers having relatively less
area under cultivation.
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CHAPTER 5 SUMMARY, CONLUSIONS AND RECOMMENDATIONS
5.1 Summary
With the passage of time, agricultural challenges are mounting at a rapid pace. Currently,
resource conservation and enhancing agricultural productivity are the major challenges for
the farming community. Tackling this challenge is not possible without effective extension
advisory services. There are enriching growers with facilitation and updated information.
Though the role of extension service providers is appreciable, however their efficiency is
under huge criticism. Inception of ICTs have opened new horizons bearing esteemed
potential to bridge the information gap among farmers. ICTs can strengthen working strategy
of extension service providers and assist in popularizing agricultural innovations among farm
families in less time. In addition, many ICTs offer an opportunity of visual communication
which reinforce farmers’ learning. ICTs entail digital and electronic form of capturing,
processing, retrieving, sharing and storing information for dissemination and broadcasting
through diversified media for information seekers. Having an authentic, validated, concise,
complete, dynamic and quick source, more and more individuals are accessing ICTs for
information acquisition. Saving cost and time are additional benefits to attract policy makers
and end users. Across Pakistan, various efforts are on board to utilize potential of ICTs in
agriculture sector and use these tools to assist EFS to bridge the information gap among
farmers. Emergence of radio and TV channels, mobile phone, websites, helplines, mobile
apps and internet paved multiple opportunities to gather required information. Mobile based
and web-based services offered by Agriculture Department in the Punjab, Pakistan are
helping in raising farmers’ awareness at their doorstep.
This study was entirely focused on assessing emerging trends of ICTs. The ICTs included
mobile, radio, TV, computer, helpline, internet, website and landline. Research was
conducted in two districts (Muzaffargarh and Rahim Yar Khan) of the Punjab. Total 400
farmer respondents were selected through multistage random sampling technique. In
addition, EFS was also selected for the collection of qualitative data. In this regard from each
selected district Deputy Director, Agri. Ext. (DD, Agri. Ext.), four (04) Assistant Directors
Agri. Ext. (AD, Agri. Ext.) (One from each selected tehsil) and all the Agriculture Officers
(AOs) working in selected tehsils were selected as study sample. Data were collected through
validated instruments from selected respondents. Qualitative data were analyzed through
80
content analysis technique while collected quantitative data were analyzed using SPSS.
Major findings of the study are presented here.
5.2 Findings
5.2.1 Demographic characteristics
Respondents falling in age bracket of up to 35 years appeared prominent (44.5%)
while respondents with age bracket of 36-50 years were 31.2%. Almost one fourth of
the respondents were more than 50 years old. This age difference is of clear notion
that respondents were engaged in farming regardless of their age. More than half
(55%) of the respondents were literate while 45% were illiterate. Among literate
respondents, about one in ten respondents passed matriculation, five years of
schooling was reflected by 12% while eight years of schooling by 15.5%.
An overwhelming majority (90.2%) of respondents was small farmers possessing
land up to 12.5 acres. Only 8.3% respondents were medium level farmers having land
of 12.5-25 acres. Moreover share of large land holders (more than 25 acres) appeared
negligible (1.5%). A large majority (88%) was owner cultivators. Tenancy and
owner-cum-tenancy system of cultivation was almost meager. A large majority
(95.3%) was having cultivation on small land holdings, 3.3% on 12.5-25 acres and
1.5% on more than 25 acres. Farming appeared leading income source of nearly 80%
farmers. Job and business were subsequent income sources along with farming as
revealed by 7.5 and 11% respondents, respectively.
5.2.2 Farming status among respondents
Among major crops cotton was the leading crop cultivated by 97.3% respondents.
However, 79.3% respondents were cultivating wheat collateral to cotton. Sugarcane
and rice were supplementary crops being cultivated on small scale as reported by 28.3
and 14.8% of respondents, respectively. Fodder for animals was leading choice as
minor crop among 94.7% respondents. Sorghum and maize embarked cultivation
among 19.8 and 8% respondents, respectively. Farmers in study area were also
practicing vegetables cultivation on small scale to meet domestic liabilities on
households’ level. Cultivation of tomato was reported by 22.8% respondents while
okra was cultivated by 18% respondents. One in ten respondents was grower of
brinjal, potato, cauliflower and bitter guard. As fruit orchards are concerned, about
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30.8% respondents were having fruit orchards, including mango (27%), banana
(2.3%) and pomegranate (1.5%).
5.2.3 Information sources
Farmers were acquiring agricultural information from multiple sources. Fellow
farmers/friends/neighbors were the prominent information sources of 71%
respondents. Easy access was the leading reason behind this extensive reliance.
Majority (61.5%) of respondents seeking information from private EFS. Mobile
phone appeared as information source of 60.3% respondents and they showed
satisfaction on mobile based extension services. TV and radio appeared information
sources of 41.3 and 36.5% respondents. However, information seeking from modern
tools including agricultural websites, helplines, newspapers and NGOs was almost
negligible.
5.2.4 Current use of different ICTs
A vast majority (85%) of respondents was having mobile phones of different
specifications. While 79.8 and 45.8% respondents possessed TV and radio/FM
respectively. Possession of internet, computer and fixed phone was than 17.8, 9.3 and
3.8% respectively. One in ten respondents possessed TV for more than 10 years.
While only 6.8% respondents possessed mobile phone for more than 10 years.
Possession of rest of the ICTs ranged between 1-5 years and 6-10 years
approximately.
Mobile phone was the prominent and widely utilized ICT tool (mean=4.61). TV
appeared 2nd leading used ICT tool (mean=3.30). Use of radio was dismal
(mean=2.61). Use of agricultural websites, internet and helplines was gloomy as
mean value was barely of low level. Use of social media, computer and fixed phone
was not more than very low level. The overall use of ICT tools was below average
except mobile phone.
TV was perceived as prominent entertainment source by 52.3% respondents. Mobile
phone was narrated as entertainment source by 18.8% respondents. Rest of the ICTs
were not used as entertainment sources. Regarding information acquisition, mobile
phone obtained agreement of 62.3% respondents. Less than one fifth (17.3%) of the
respondents used radio and 13% used TV for acquiring information. Use of other
82
associated tools for information was depressing. In context of infotainment, about one
fourth (24%) respondents used mobile phone for infotainment and 14.5% used TV.
Infotainment from allied media ranged between 0-8.5%. In short, Mobile phone was
the leading source of information and infotainment. While, computer, social media,
internet, fixed phone, agri. helplines and websites were the least despite these are
innovative and latest used technologies.
Regarding distribution of using ICT tools for obtaining agricultural information
mobile phone was ranked 1st (mean=2.52) Radio ranked 2nd (mean=1.87), TV ranked
3rd (mean=1.80), internet ranked 4th (mean=1.24). Overall, mobile phone remained
leading source for agricultural information among respondents.
5.2.5 Familiarity of ICTs regarding the agricultural information dissemination
Radio programs “Utam Kheti”, a broadcast of Multan Radio Station was known to
35.3% respondents. Another program “Dharti Bakht Bahar” broadcast of Radio
Pakistan Bahawalpur was familiar among 28.3% respondents.
Awareness of TV programs among respondents appeared ordinary. “Zamindara”
broadcasted on Waseb TV and “Khaiti” a broadcast of Rohi TV were the prominent
TV programs familiar among 39 and 35% of the respondents. On rank scale
“Zamindara” stood 1st followed by “Khaiti” obtaining 2nd rank. Respondents
perceived these programs informative being broadcasted in local language “Saraiki”.
Various internet based services like agricultural websites, fertilizer calculator, e-
marketing and social media were known to 7.8, 3.8, 1.5 and 3% respondents,
respectively.
Among available mobile based services “Bakhabar Kissan” was known to 30.3%
respondents. “Khushal Zamindar” and “Warid Kissan Line” were familiar among
12.5 and 11.3% respondents, respectively. Overall awareness of mobile based
services among respondents was poor.
Trends of public and private helpline services indicated that helplines served by
Punjab Agriculture Helpline (PAH) was known to 11.5 and 10.5% respondents.
While helplines of L&DD were known to 5.8 and 4.3% respondents, respectively
followed by the helpline of “Kissan dost” which was familiar among 4.1%
respondents. Helpline offered by FFC was negligibly known to 2.8% respondents.
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Results infer that accumulate familiarity of helplines was least among respondents.
Overall familiarity of hipline services was below average.
Information received through different ICTs on various agricultural avenues indicated
that information obtained regarding production of major crops was ranked 1st
(mean=3.51), plant protection measures was ranked 2nd (mean=3.27), weather updates
and livestock management were ranked 3rd (mean= 2.33.) Overall information
seeking level through ICTs persisted on average level.
5.2.6 Preferred ICTs
Mobile phone appeared most concerned ICT (mean=3.86). TV was 2nd ranked
preferred ICT (mean=3.28). Radio was ranked 3rd preferred ICT (mean=3.12).
Internet obtained mean value of 3.04 reflecting 4th ranked preference. Use of
websites, helplines, computer and landlines phone were least preferred because of
inadequate computer literacy.
Local language “Saraiki” was reported as most preferred language of information
sharing by half (50.2%) of the respondents. “Urdu” was preferred by 30% respondent
while one fifth (19.8%) respondents preferred information seeking in both urdu and
local language. They could understand either way.
5.2.7 Effectiveness of ICTs as information sources
Mobile phone was perceived more effective as better agricultural information source
(mean=4.17), source of improving farming skills (mean=4.12), source of accurate
information (mean=3.96), and timely information (mean=4.32,) as compared to all
other ICTs i.e. TV, radio, internet, computer, landline phone, helpline and websites.
Effectiveness of these features of mobile inclined towards effective. In case of
internet, computer, helpline and website appeared less effective.
Respondents showed their preference that they would like to receive information
regarding agronomic practices including different farm operations (mean=4.23), plant
protection measures (mean=4.16), marketing (mean=3.97), harvesting of crop
(mean=3.92), loan schemes (mean=3.63), storage techniques (mean=3.46), farm
mechanization (mean=3.51) and farm management (mean=2.88) through diversified
ICTs.
84
5.2.8 Challenges faced by respondents regarding use of ICTs
Regarding use of radio, inadequate education of the listeners (mean=3.49), poor
awareness of radio broadcasts (mean=2.56), odd transmission time of programs
(mean=3.36), language barrier (mean=3.34), lack of time and busy schedule of
farmers (mean=3.31) and inadequate information about the programs (mean=3.21)
were leading challenges.
Use of TV was confronted with challenges of poor transmission and broadcast quality
(mean=3.50), irrelevant broadcasting of programs and language barrier (mean=3.34)
and lack/poor feedback (mean=3.38).
High cost of mobile phone (mean=3.86), language barriers (mean=3.21) and
lack/poor feedback (mean=3.44) were the leading factors affecting usage of mobile
phone as perceived by respondents. Extensive cost (mean=3.75) of affording internet,
inadequate education to use internet (mean=3.65) and accessibility issues of internet
(mean=3.23) were prominent barriers affecting the effectiveness of internet as
information source.
Use of landline was hampered by lack of ownership of respondents (mean=3.72) and
poor interest in use of landline (mean=2.26). Inadequate education (mean=3.92) also
hampered effective use of helplines. It is summarized that inadequate education of
respondents was major obstacle in way of effectiveness of internet, computer,
landlines, helpline and website as information sources of farmers.
5.2.9 Training needs of farmers regarding ICTs
Agricultural websites embarked maximum training need (mean= 3.21) while TV
exhibited minimum training need (mean=1.41). This implies that respondents were
upright regarding use of TV but deprived regarding use of agricultural websites. Use
of computer stood in 2nd ranked arguing training need of almost medium level (2.83).
Landline (mean=2.71) arbitrated training need of medium level as well. Agricultural
helplines were on 4th rank followed by mobile and internet standing on 5th and 6th in
terms of training needs to enjoy full potential of these diversified tools.
85
5.2.10 Correlation between the demographic characteristics and use of ICTs
Pearson correlation coefficient shows a highly significant and positive relation
among and age and use of Radio/FM for obtaining agricultural information. However,
it show that farmers’ age had significant and negative relation among Internet,
Computer, social media, landline phone, agri. helpline and agri. website. While a
non-significant relation was found among age with TV and mobile phone. Pearson
correlation coefficients show that significant and positive relation was found between
education of farming community with use of ICT tools for obtaining agricultural
information i.e. TV, internet, computer, mobile phone, social media, landline phone,
agri. helpline and agri. websites.
Pearson correlation coefficients show significant and negative relation among age and
preference TV and agri. helpline for getting agricultural information in future. While
it show that significant and positive relation was found between education of farming
community with use of ICT tools for getting agricultural information in future i.e.
radio, TV, mobile, internet, computer, landline phone, agri. helpline and agri.
websites
5.3 Conclusions
This research concludes that prospects of ICTs are full of potential but were utilized partially
by the farmers. Farmers have switched to mobile phone for infotainment, rather than towards
TV and radio. Among various ICTs, mobile phone is the only mediaS with vast possession
and utilization for information acquisition. After mobile, TV and radio appeared farmers’
choice. Possession and utilization of other latest interventions like internet, helpline,
computer, websites and landline were disconsolate. Overall usage of ICTs remained below
average level except mobile phone. Usage of ICTs was emphasized largely on plant
production, protection, weather updates and marketing. However, utilization was restricted
on average level pertinent to several associated constraints viz. poor awareness among
farmers regarding TV and radio broadcasts followed by inappropriate timing of broadcasts,
language barriers, lack of education and affordability issues. Converse to these hurdles,
farmers preferred to use mobile phone, TV and radio as subsequent. Latest ICTs didn’t gain
farmers’ interest and preference. This fractional attitude posed serious questions on
credibility and authenticity of modern tools. Better agricultural information sources,
86
improved farming skills and provide timely information compelled farmers to prefer mobile
phone to meet their information needs. On contrary, websites, helplines, computer and
landlines were least used in meeting information needs. It appeared from the findings of
correlation section that demographic characteristics had impact on the usage of ICTs.
5.4 Recommendations
5.4.1 Department of Agriculture (Extension & AR) Punjab
Mobile appeared prominent medium of information acquisition, hence, EFS should
use mobile phone extensively for communication among farmers. Additionally, EFS
should popularize mobile based services among farmers.
As mobile is prominent and accessible ICT tool among farmers, hence, Department of
Agriculture (Extension) Government of the Punjab, should diversify all services into
mobile-based. Mobile apps could be more convenient option. Moreover, contents
should be embarked in local language to alleviate language barrier.
TV and radio are still important choices for information after mobile. Hence,
Department of Agriculture (Extension) should initiate agriculture-based TV and radio
channel to attract rural people for information acquisition. These specific channels
will eliminate barriers of inappropriate timing and irrelevant broadcasts.
Awareness regarding TV and radio broadcasts agricultural programs appeared
meager. There is dire need to popularize these programs among farmers through
various extension activities like seminars, group meetings and media campaigns.
Use of helpline was almost negligible. Department of Agriculture (Extension) should
initiate free helpline centers at division level for the farmers. These call centers
should be organized by agricultural experts and farmers may be able to communicate
with experts according to their needs.
Internet applicability among farmers was also meager almost. Department of
Agriculture (Extension) should diversify mobile based internet services for farmers
with contents in local or national language. Government should coordinate with
cellular companies to harness opportunities for the farmers.
Department of Agriculture (Extension) should launch robbo calls system and punch
messages system. Registration of farmers should be ensured on district level and all
87
registered farmers should receive system generated calls and messages on specific
aspects of agriculture on regular basis.
5.4.2 Educational Institutions
Agricultural universities across the Punjab can play important role in digitalizing
information systems for farmers. Establishment of TV channels, radio programs,
interactive websites and toll-free helplines (preferably call centers) should be ensured
by the universities. Universities should initiate courses for undergraduate students to
familiarize with ICT services for farming and motivate them to serve as master trainer
for raising awareness among farmers.
There is need to develop holistic model of ICT and strong linkages between research
institutions, universities and extension service providers to bring transparency in
research findings for farmers.
In-Service Agricultural Training Institutes working across the Punjab should develop
curriculum and impart trainings to farmers regarding use of ICTs, i.e. internet,
helpline, web-based services. These trainings will advance knowledge and skills
among farmers. Further these trainings should be extended to EFS as well.
5.4.3 Cellular Companies
Cellular companies are providing enormous services and with the passage of time
subscribers are increasing. These companies could facilitate farming community
through voice and text messages and awareness campaigns. Cellular companies
should collaborate and develop partnership with Agriculture Department,
Government of the Punjab and educational institutions.
5.4.4 Media
Pakistan Electronic Media Regulatory Authority (PEMRA) should coordinate with
private TV channels and they should be advised to broadcast agricultural programs on
regular basis for farmers. They should be further advised to conduct talk shows with
agricultural experts and farmers, particularly who are progressive.
5.4.5 For Future Researchers
This research study was undertaken in two districts of the Punjab. Future researchers
are suggested to conduct similar research in other ecological zones for deep insights.
This research further can be undertaken in other provinces as well.
88
Similar kind of research may be conducted by engaging extension service providers
(both Public and private) bearing experience of using ICTs for technology sharing
among farmers.
89
REFERENCES
Abbas, M., A.D. Sheikh, S. Muhammad and M. Ashfaq, 2003. Role of print media in the
dissemination of recommended sugarcane production technologies among farmers in
the central Punjab, Pakistan. Int. J. Agri. Biol., 5:26-29.
Abbas, M., S. Muhammad, I. Nabi and A.D. Sheikh, 2003. Farmer- Extension interaction
and the dissemination of recommended sugarcane production techniques in the
central Punjab (Pakistan). Int. J. Agric. Biol., 5:134-137.
Abbas, M., S. Muhammad, I. Nabi and M. Kashif, 2003. Farmers' information sources, their
awareness and effectiveness of citrus extension services adoption of recommended
sugarcane production technologies in the central Punjab. Pak. J. Agri. Sci., 40:3-4.
Abbas, M., T.E. Lodhi., K.M. Aujla and S. Saadullah, 2009. Agricultural extension programs
in Punjab, Pak. J. Life Soc. Sci., 7: 1-10.
Abdullah, F.A., B.A. Samah, 2013. Factors impinging farmers’ use of agriculture technology.
Asian Soc. Sci., 9:120-124.
Abubakar, B.Z., A.K. Ango and U. Buhari, 2009. The roles of mass media in disseminating
agricultural information to farmers in Birnin Kebbi local government area of Kebbi
State: A case study of state Fadama II development project. J. Agri. Ext., 13: 115-
126.
Adebayo E.L. and O.M. Adesope, 2007. Awareness, access and usage of information and
communication technologies between female researchers and extensionists. Int. J.
Edu. Dev. Info. Commun. Tech., 3:85-93.
Adebayo, K. 1997. Communication in agriculture. Integrity prints, Nigeria: 1-60.
Adegbidi, A., R. Mensah, F. Vidogbena and D. Agossou, 2012. Determinants of ICT use by
rice farmers in Benin: from the perception of ICT characteristics to the adoption of
the technology. J. Res. Int. Bus. Mgt., 2:273-284.
Adomi, E.E., M.O. Ogbomo and D.E. Inoni, 2003. Gender factors in crop farmers access to
agricultural information in rural areas of Delta state, Nigeria. Library Rev. 52: 388-
393.
Adetoun, O. (2006). Cultural and linguistic barriers to information retrieval and
dissemination. World library and information congress: 72nd IFLA general
conference and council 20-24 august 2006, Seoul, Korea
90
Agbamu, J.U. 2000. Agricultural research, extension linkage systems: An international
perspective, agricultural research and extension network, Department for
International Development, U.K., Network Paper No. 106:1-7.
Agwu, A.E., U.C. Uchemba, and O.M. Akinnagbe, 2008. Use of information and
communication technologies (ICTs) among researchers, extension workers and
farmers in Abia and Enugu states: Implications for a national agricultural extension
policy on ICTs. J. Agri. Ext., 12:37-49.
Ag-Chat foundation. 2014. Retrieved from http://agchat.ord
Ahmad, M. 1999. A comparative analysis of the effectiveness of agricultural extension work
by public and private sectors in Punjab, Pakistan’. PhD Thesis. University of New
England, Armidale, Australia.
Ahmad, M., A.P. Davidson, and T. Ali, 2000. Effectiveness of public and private sectors
extension: Implications for Pakistani farmers’. Paper presented at 16th annual
conference held by association for international agricultural extension education,
Arlington, Texas.
Ahmad, S. 2015. Water availability and future water requirements. In: Project management
and policy implementation unit of the Ministry of Water and Power (MOWP) Water
conservation, Present Situation and future strategies. Proc. MOWP planning
commission and Asian Development Bank National Seminar. 21 May 2009. Project
management and policy. Implementation Unit MOWP Islamabad, Pakistan: 43-62.
Ahmadian, S., M. Rahmandoust, A.B. Abdul-Hamid, S. Chelliah, J. Munusamy and R.
Anvari, 2011. International opportunity recognition through international trade
intermediary networks in Malaysian SMEs. Aust. J. Bas. App. Sci., 5:635-648.
Ahituv, A. and A. Kimhi, 2006. Simultaneous estimation of work choices and the level of
farm activity using panel data. Euro. Rev. Agri. Eco., 33:49 -71.
Aina, L. 2004. Library and information science text for Africa. Ibadan publisher, Nigeria.
Aker, J. 2008. Can You Hear Me Now?’ How cell phones are transforming markets in Sub
Saharan Africa.” Center for Global Development.
Akpabio, I.A., D.P. Okon, E.B Inyang, 2007. Constraints affecting ICT utilization by
agricultural extension officers in the Niger Delta, Nigeria. J. Agric. Educ. Ext.,
13:263-272.
91
Akram, W., I. Naz and S. Ali, 2011. An empirical analysis of household income in rural
Pakistan: evidences from tehsil Samundri. Pak. Eco. Soc. Rev. 231-249.
Akubuilo, C.J.C. 2009. History of agricultural extension in Nigeria”. In: Akinyemiju.O.A
and Torimiro, D.O. (eds.) Agricultural extension a comprehensive treatise. Ikeja,
Lagos: ABC Agricultural Systems Ltd.:109-120.
Aldosari, F., M.S. Al Shunaifi, M.A. Ullah, M. Muddassir and M.A. Noor, 2017. Farmers’
perceptions regarding the use of Information and Communication Technology (ICT)
in Khyber Pakhtunkhwa, Northern Pakistan. J. Saudi Soci. Agri. Sci. 17: 411-419
Ali, M. 2010. Agriculture problems in Pakistan and their solutions. Pakistan Agriculture
Research (PAR). http://edu.par.com.pk/student/essay/agriculture-problems-pakistan-
theirsolutions/
Ali, S., M. Ahmad, T. Ali, S.W. Hassan and M. Luqman, 2011. Role of private extension
system in agricultural development through advisory services in the Punjab, Pakistan.
Pak. J. Sci., 63:70-73.
Ali, Jabir, and S. Kumar, 2010. Information and Communication Technology (ICTs) and
farmer’s decision-making across the agricultural supply Chain. Int. J. Info. Mgt., 31:
149-159.
Ali, T. 1991. An identification and validation of job performance competencies needed by
agricultural extension field assistants in Faisalabad District, Punjab, Pakistan.
Unpublished doctoral dissertation, University of Minnesota, United States of
America.
Ali, T., A. Munir and T.E. Lodhi, 2003. Proposed model of UAF extension. Enhancement of
agriculture extension system (AES) in Nepal. Enhancement of extension systems in
agriculture. Working paper presented in seminar organized by Asian Productivity
Organization 15-20 Dec. 2003. Faisalabad, Pakistan. 145-150.
Ali, H. 2005. Low farm productivity: A challenge. Daily Dawn. Economics and Business
Review.
Amudavi, D.M., Z.R. Khan, J.M. Wanyama, C.A.O. Midega, J. Pittchar, I.M. Nyangau, A.
Hassanali and J.A. Pickett, 2009. Assessment of technical efficiency of farmer
teachers in the uptake and dissemination of push–pull technology in western Kenya.
Crop prot., 28: 987-996.
92
Anastasioa, M.A., Koutsouris, M. Konstadinos, 2010. Information and communication
technologies as agricultural extension tools: A survey among farmers in West
Macedonia, Greece. J. Agric. Educ. Ext., 16:249-263.
Andersch, E.G., L.C. Staats, and R.N. Bostrom, 1969. Communication in everyday use.
Austin, Taxas: Holt, Rinehart and Winston publisher.
Anderson J.R., G. Feder and S. Ganguly. 2006. The rise and fall of Training and Visit
Extension: An Asian mini-drama with an African Epilogue. World Bank policy
research working paper 3928. Agriculture and Rural Development Department World
Bank.
Anene, M. 2006. Effectiveness of communication in administration. Abraka: Delta State
University.
Angello, C. 2015. Exploring the use of ICTs in learning and disseminating livestock
husbandry knowledge to urban and peri-urban communities in Tanzania. Int. J. Edu.
Dev. Using Info and Comm. Tech., 11:5-22.
Anil, N. 2008. ICT for agriculture and rural development. Accessed from:
http://en.wikieducator. Org/image/c/ce/information and communication (a-k-sahu)
ppt. pdf.
Anvari, R. and D.M. Atiyaye, 2014. Determinants of effective communication among
undergraduate students. Int. Edu. Stu., 7: 112-121.
Anoop, M., N. Ajjan, and K.R. Ashok, 2015. ICT based market information services in
Kerala determinants and barriers of adoption. Economic Affairs, 60:117.
Arfan, M., S. Ali, F.U. Khan, and G.A. Khan, 2013. Comparative analysis of punjab
agriculture helpline and other agricultural information sources for the farmers in
district Lahore. J. Agric. Res., 51:473-478.
Arokoyo, T. 2003. ICT’s for agriculture extension transformation. Proceeding of ICT's
transforming agriculture extension? CTA's observatory on ICT's”, 6th consultative
Expert Meeting. Wageningen, 23 – 25 September.
Asaba, J.F., R. Musebe, M. Kimani, R. Day, M. Nkonu, A. Mukhebi, A. Wesonga, R. Mbula,
P. Balaba and A. Nakagwa, 2006. Bridging the information and knowledge gap
between urban and rural communities through rural knowledge centers: case studies
from Kenya and Uganda. Quarterly Bulletin of IAALD, 51:143-151.
93
Asenso-Okyere, K, and D.A. Mekonnen, 2012.The importance of ICTs in the provision of
information for improving agricultural productivity and rural incomes in Africa.
United Nations Development Programme’s Regional Bureau for Africa working
paper.
Ashraf, I. 2008. Analysis of communication interventions of extension field staff with
farmers under decentralized extension in the Punjab, Pakistan. Ph.D. Thesis,
Department of Agricultural Extension, Univ. of Agri., Faisalabad.
Ashraf, I., S. Muhammad, K. Mahmood, M. Idrees, and N. Shah, 2009. Strengths and
weaknesses of extension system as perceived by extension field staff. Sarhad J.
Agric., 25:131-134
Ashraf, S., G.A. Khan, S. Ali, M. Iftikhar, 2014. Managing Insect Pests & Diseases of Citrus
on: Farm Analysis from Pakistan, Pak. J. Phytopathol, 26: 301-307.
Ashraf, S., G.A. Khan, S. Ali, S. Ahmed and M. Iftikhar, 2015. Perceived effectiveness of
information sources regarding improved practices among citrus growers in Punjab,
Pakistan. Pak. J. Agri. Sci., 52: 861-866.
Aslam, M., A.U. Haq and M. Javaid, 2008. Indus basin experiences on disposal of
agricultural drainage effluent. In: International Commission on Irrigation and
Drainage (ICID) 20th international congress on irrigation and drainage: Participatory
integrated water resources management from concepts to actions. Proc. 13-18
October 2008. Lahore, Pakistan: 143-145. Available at: http://asae.frymulti. com/
abstract.asp?aid=23403&t=2
Awotide, B., A. Diagne, and B. Omonona, 2012. Impact of improved agricultural technology
adoption on sustainable rice productivity and rural farmers’ welfare in Nigeria: A
local average treatment effect (late) technique. African Economic Conference. Kigali,
Rwanda.
Axinn, G.H. 1985.Systems of agricultural extension education for agriculture. Proc:
symposium on education for agriculture, 12-16 Nov. 1984. IRRI, Manila, Philippines.
Azeem, M. and S. Ali, 2015. ICT for sustainable agriculture. Published in Dawn, Economic
& Business.
Babbie, E. and J. Mouton, 2008. The practice of social research South African ed. Vasco,
Boulevard, Goodwood, Cape Town: Oxford University Press: 674.
94
Babu, S, C. Glendenning, K. Okyere and S. Govindarajan, 2012. Farmer information needs
and search behaviour. Case Study in Tamil Nadu India, IFPRI.: 1-51.
Bachhav, N.B. 2012. Information needs of the rural farmers: a study from Maharashtra,
India: a survey. Library Philosophy and Practice (e-journal) paper 866. Retrieved
from http://digitalcommons.unl.edu/libphilprac/866.
Bajwa, M.S., M. Ahmad and T. Ali, 2010. An analysis of effectiveness of extension methods
used in farmers field school approach for agricultural extension work in Punjab,
Pakistan. J. Agric. Res., 48: 259-265.
Ballantyne, P.A. Maru, and E.M. Poncari, 2010. Information and communication
technologies. Amer. Soc. Info. Sci. Tech.: 57:1350-1367.
Baloch, M.A. and G.B. Thapa, 2017. Review of the agricultural extension modes and
services with the focus to Balochistan, Pakistan. J. Saudi Soc. Agri. Sci.
Barbassa, J. 2010. Farmers defend way of life with Facebook, Twitter. ABC News, Retrieved
from http://abcnews.go.com/Business/wireStory?id=11070012
Barjak, F. 2006. The role of the internet in informal scholarly communication. J. Ass. Info.
Sci. Tech., 57:1350-1367
Barkat, A. 2002. An investigation into the performance of Crescent Sugar Mills extension
personnel in district Faisalabad. M.Sc. (Hons.) Thesis, Department of Agricultural
Extension. Univ. of Agri., Faisalabad, Pakistan.
Bassey, M. 2003. Educational Research. In: Swann, J. and J. Pratt, (Eds.), Educational
Research in Practice. Making sense of methodology. London: continuum
international publishing group: 111-123.
Betz, M. 2009. The effectiveness of agricultural extension with respect to farm size: The case
of Uganda. Paper prepared for presentation at the Agricultural & Applied Economics
Association 2009.
Bhutta, M.N. 2007. Land tenure and management: an analytical appraisal. Pak. Dev. Rev., :
957-968.
Bhutto, A.W. and A.A. Bazmi, 2007. Sustainable agriculture and eradication of rural poverty
in Pakistan. Natural Resources Forum, 31: 253–262.
95
Birthal, P.S., D.S. Negi, A.K. Jha and D. Singh, 2014. Income sources of farm households in
India: Determinants, distributional consequences and policy implications. Agri. Eco.
Res. Rev., 27: 37.
Birner, K.J., E. Davis, P. Pender, J. Nkonya, A. Anandajayasekeram, D. Ekboir, D. Mbabu,
D. Spielman., H. Benin, and M. Cohen, 2006. From "best practice" to "best fit": A
framework for designing and analyzing pluralistic agricultural advisory services
Worldwide, International Food Policy Research Institute, Washington, Discussion
Papers.
Bjork, B.C. 2005. A lifecycle model of the scientific communication process. Learned
Publishing, 18:165-176.
Blaxter, L., C. Hughes and M. Tight, 2001. How to Research (2nd Ed.). Open University
Press, McGraw- Hill Education, Bekshire, U.K.
Bolarinwa, K.K. and R.A. Oyeyinka, 2011. Use of cell phone by farmers and its implication
on farmers’ production capacity in Oyo State Nigeria. World academy of science,
engineering and technology. Int. J. Biol. Bio. Agri. Food Biot. Eng., 5: 170-175
Borg, W.R., and M. D. Gall, 1989. Educational research. An introduction (5th Ed.). White
Plains, NY: Longman.
Brierley, G. 2009. Communicating geomorphology. J. Geo. in High. Edu., 33: 3-17.
Brooker, F.E. 1949. Communication in the Modern World” in Audio-Visual Material of
Instruction, 48th Yearbook, Part 1 of the National Society for the Study of Education,
Chicago: The University of Chicago Press,:4-27.
Bukhari, S.M., 2000. A study of the communication gap between research recommendations
regarding cotton production and the information level of the farmers in tehsil Kot
Adu of district Muzzafargarh. M.Sc. (Hons.) Thesis, Department of Agricultural
Extension, Univ. of Agri., Faisalabad.
Buren, E.D. 2000. Cultural aspects of communication for development. Translator. IRIB
Press. Iran: 110-114.
Burnett, C. and M. Tucker, 2001. Writing for agriculture: A new approach using tested ideas.
Dubuque, IA: Kendall/Hunt Publishing Co.
96
Butt, S. 2002. Role of television in the dissemination of agricultural technologies among the
farmers of tehsil Faisalabad. M.Sc. (Hons.) Thesis, Department of Agricultural
Extension, Univ. of Agri., Faisalabad.
Chand, R., P.A.L. Prasanna and A. Singh, 2011. Farm size and productivity: Understanding
the strengths of smallholders and their livelihoods. Eco. Pol. Weekly., 54:5-11.
Chaudhry, I.S. 2003. An empirical analysis of the determinants of rural poverty in Pakistan: a
case study of Bahawalpur District with special reference to Cholistan. Pakistan
Research Repository.
Chaudhry, K.M. 2002. Community infrastructure services program (CISP): HRD manual.
Muzafarabad: Department of Local Government and Rural Development, Govt. of
AJK.
Chaudhry, K.M., S. Muhammad, A. Saghir and I. Ashraf, 2008. Rural women’s access to
various sources of information in tehsil Faisalabad. J. Anim. Pl. Sci., 18:2-3.
Chaudhry, K.M., S. Muhammad, A. Saghir and I. Ashraf, 2008. Rural women’s access to
various sources of information in tehsil Faisalabad. J. Anim. Pl. Sci., 18:99-101.
Chavula, H.K. 2014. The role of ICTs in agricultural production in Africa. J. Dev. Agri. Eco.,
6: 279-289.
Cheema, S.M. 2004. Socio-economic issue in the adoption of modern agricultural
technologies in rural Faisalabad. M.Sc. (Hons.) Thesis, Department of Agricultural
Extension, Univ. of Agri., Faisalabad.
Cheney, G. 2011. Organizational communication in an age of globalization: Issues,
reflections, practices. Long Grove, IL: Waveland Press.
Chhachhar, A.R., M.N. Osman and S.Z. Omar, 2012. Role of television in agriculture
development of Sindh, Pakistan. A publication of the pacific and Asian
communication association. 15:1-11.
Chhachhar, A.R., B. Qureshi, G.M. Khushk, and S. Ahmed, 2014. Impact of information and
communication technologies in agriculture development. J. Bas. App. Sci. Res., 4:
281-288.
Chhachhar, R. and S. Hassan, 2013. The use of mobile phone among farmers for agriculture
development. Int. J. Sci. Res., 2:95- 98.
97
Choi, J. 2009. Culture and characteristics of cellular phone communication in South Korea. J.
Media Commun. Stud., 1:1-10.
Chikwati, E. 2009. Zimbabwe: disseminate information to farmers, media urged. Available
at: http://allafrica.com/stories/200903301779.html
Chilimo, W.L. 2008. Information and communication technologies and sustainable
livelihoods: A case of selected rural areas of Tanzania. Ph.D. Thesis, University of
KwaZulu-Natal, Pietermaritzburg
Churchill, G.A. and D. Iacobucci, 2005. Marketing research: Methodological foundations (9th
Ed.). Mason, Ohio: Thomson South Western: 697.
Churi, A.J., M.R.S. Mlozi, S.D. Tumbo, R. Casmir, 2012. Understanding farmers’
information communication strategies for managing climate risks in rural Semi-Arid
Areas, Tanzania. Int. J. Info. Comm. Tech. Res., 2:838-842.
Clifford, W.R. and E.F. William, 2007. Strategies for disseminating assistive technology
information to farmers and ranchers. Published by American Society of Agricultural
and Biological Engineers
Clough, P. and C. Nutbrown, 2002. A Student’s Guide to Methodology: Justifying Enquiry,
Sage Publications.
Courtois P, J. Subervie, 2013. Farmer bargaining power and market information services.
The Centre for the Study of African Economies conference: Economic development
in Africa, 17th–19th March, St Catherine’s College, Oxford.
Cruickshank, J. 2002. The role of scientific literature in electronic scholarly communication.
Sci. Tech. Libr., 22:71-100.
Das, V.K. and A. Ganesh-Kumar, 2017. Drivers of farmers' income: The role of farm size
and diversification (No. 2017-013). Indira Gandhi Institute of Development Research,
Mumbai, India.
David J. and S. Talyarkhan, 2005. A best process approach for using ICTs in development.
IRFD World Forum on Information Society.
Davidson, A.P., M. Ahmad, and T. Ali, 2005. Dilemmas of Agricultural Extension in
Pakistan: Food for Thought, Agricultural Research and Extension Network (Agren),
Network paper No. 116, July, Overseas Development Institute (ODI), London.
98
De-Janvry, A., E. Sadoulet and N. Zhu, 2005. The Role of non-farm incomes in reducing
rural poverty and inequality in China. Department of Agriculture and Resource
Economics, University of California, Berkeley
Demiryurek, K., H. Erdem, V. Ceyhan, S. Atasever and O.U.O. Mayıs, 2008. Agricultural
information systems and communication networks: the case of dairy farmers in the
Samsun province of Turkey. Info. Res., 13: 38-47.
Dia, S. 2002. Radio broadcasting and New Information and Communication Technologies:
Uses, Challenges and Prospects. Information and Communications Technologies and
Social Development in Senegal: 4-32.
Dinpanah G. and F. Lashgarara, 2011. Factors influencing the information seeking
knowledge of wheat farmers in Iran: Afr. J. Agric. Res., 6:3419-3427.
Diyamett, B.D. and M. Materu, 2010. Tanzania ICT Sector Performance Review. Towards
evidence-based ICT policy and regulation. 2:1-47.
Dodds, T. 1999. Non-formal and adult basic education through open and distance learning in
Africa. University of Namibia, Center for external studies.
Dörnyei, Z. 2007. Research methods in applied linguistics: quantitative, qualitative, and
mixed methodologies. Oxford Uni. Press, USA.
Doss, C.R., M.L. Morris, 2001. How does gender affect the adoption of agricultural
innovations? The case of improved maize technology in Ghana. Agric. Econ. 25:27-
39.
Drew, C.J., M.L. Hardman, and J.L. Hosp, 2008. Designing and conducting research in
education. London: SAGE: 406.
Duncombe, R. 2011. Researching impact of mobile phones for development: concepts,
methods and lessons for practice. Info. tech. Dev., 17:268-288.
Ebrahim, J. 2006. Adoption dairy innovations: its income and gender implications in Adami
Tulu District. Masters’ Dissertation Haramaya University, Haramaya, Ethiopia.
Ekundayo, M.S. and J.M. Ekundayo, 2009. Capacity constraints in developing countries: A
need for more e-learning space? The case of Nigeria. Proceedings Ascilite Auckland:
243-255
Ekoja, I. 2003. Farmer's access to agricultural information in Nigeria. Bull. American Society
of Information and Science Technology, 29: 21-23.
99
Eneyew, A. 2013. Untied efforts: The challenges for improved research, extension and
education linkages. Edu. Res. and Rev., 8: 792-799.
Etwire, P.M., S.Buah, M. Ouédraogo, R. Zougmoré, S.T. Partey, E. Martey, S.D. Dayamba,
and J. Bayala, 2017. An assessment of mobile phone-based dissemination of weather
and market information in the Upper West Region of Ghana. Agri. Food Sec., 6:8-
16.
FAO, 2011. Women in Agriculture: Closing the gender gap for development. Rome: Food
and Agriculture Organization of the United Nations.
FAO, 2008. The State of Food and Agriculture, Rome, Italy: Food and Agriculture
Organization
Farooq, A, M. Ishaq, N.A. Shah and R. Karim, 2010. Agricultural extension agents and
challenges for sustainable development: A case study of Peshawar valley. Sarhad J.
Agric., 26: 419-426.
Farooq, A. and M. Ishaq. 2005. Devolving the Farm Extension System, Economic and
Business Review. Daily Dawn, Karachi.
Farooq, R.A. 2011. Understanding research in education. University Institute of Education
and Research, Univ. of Arid Agri., Rawalpindi, Pakistan.
Farooq, S., S. Muhammad, K.M. Chaudhary and I. Ashraf, 2007. Role of print media in the
dissemination of agricultural information among farmers. Pak. J. Agri. Sci., 44: 378-
380.
Fawole, O. P. 2006. Poultry farmers’ utilization of information in Lagelu local government
area, Oyo state of Nigeria. Int. J. Poultry Sci., 5: 499-501.
Fedler, A., A. Carey and T. Counts, 1998. Journalism’s status in academia: A candidate for
elimination. J. Mass Comm. Edu., 53: 31-39.
Flick, U. 2011. Introducing research methodology: A beginner’s guide to doing a research
project. Sage publications, London.
Flor, A.G. 2002. Information and communication opportunities for technology transfer and
linkages. Available at: http:/ /www.upou.org/downloads/out.html
FAO, 1987. The Archers, An everyday story of country folks, Rome FAO.
Fossard, E.D. 2005. Writing and producing radio dramas. Saga Publication. New Delhi.
100
Fu, X. and S. Akter, 2010. The impact of ICT on agricultural extension services
delivery: Evidence from the rural e-services project in India. TMD working paper
series. University of Oxford.
Ganeshagouda I., P.P. Kumar, A.V. Manjunatha, I. Somanagouda, P.V. Reddy and P.
Ramasundaram, 2013. Impact of KSAMBS’ free sms to farmers on agricultural
marketing prices: A case study in Karnataka, India. Science Discovery, 1:28-34.
Garvey, W.D., L. Nan and C.E. Nelson, 1971. A comparison of scientific communication
behavior of social and physical scientists. Int. Soc. Sci. J., 23:256-267
George, A. and Andreas Stylianou (2018) Evaluation of the radio as an agricultural
information source in rural areas, J. Agri. Food Info. 19:362-376
Ghafoor, A. 2008. Manual for synopsis and thesis preparation. Univ. of Agri, Faisalabad,
Pakistan.
Gloy, B., J. Akridge and L. Whipker, 2000. Sources of information for commercial farms:
usefulness of media and personal sources. Int. Food & Agribusiness Mgt. Rev., 3:
245-260.
Govt. of Pakistan. 2006. Economic Survey of Pakistan, Fedral Bureau of Statistics,
Islamabad.
Govt. of Pakistan. 2008. Economic Survey of Pakistan, Economic Advisory’s Wing, Finance
Division, Islamabad.
Govt. of Pakistan. 2018. Economic Survey of Pakistan, Federal Bureau of Statistics
Islamabad, Pakistan.
Govt. of Bangladesh. 1999. Mass media and audio-visual aids. Available at:
http://www.dae.gov.bd/Pdf%20forms/Extension%20mannual/AE_Manual_Web%20
Verion_Part5.pdf
Govt. of the Punjab. 1978. Punjab extension and agricultural development project. Lahore,
Pakistan: Policy and program farming cell, Agricultural department.
Govt. of the Punjab. 1983. Punjab extension and agricultural development project. PC-1
Form. Directorate General Agriculture (Extension & Adaptive Research) Punjab,
Lahore.
Govt. of Punjab. 2018. Distract Government Muzaffargar, Punjab, Pakistan.
Govt. of Punjab. 2018. Distract Government Rahim Yar Khan, Punjab, Pakistan.
101
Gustafson, D. 1994. Developing sustainable institutions: Lessons from cross-case analysis of
24 agricultural extension programs. Public Admin. Dev., 14: 121-134.
Girma, H. K. Zeyaur, O. Nathan and P. Jimmy. (2018). Perceived preference of radio as
agricultural information source among smallholder farmers in Uganda. Int. J. Agr.
Ext. 05: 119-130
Habib, M., Z. Khan, M. Iqbal, M. Nawab, S. Ali, 2007. Role of farmer field school on
sugarcane productivity in Malakand Pakistan. Afric. Crop Sci. Soc., 1443-1446.
Hamid, A. 2006. Role of private sector in introducing IPM technologies with special
reference to sugarcane crop in district Faisalabad. M.Sc. (Hons.) Thesis, Department
of Agricultural Extension, Univ. of Agri., Faisalabad.
Hancock, A. 1976. Producing for educational mass media. The Unesco Press, Paris.
Hassan, M. Z. Y., B.N. Siddiqui and M.N. Irshad, 2011. Effect of socio-economic aspects of
mango growers on the adoption of recommended horticultural practices. Pak. J. Agri.
Sci., 39: 20-21.
Hassan, M.Z.Y., H.A. Majeed and I.U. Rehman, 2005. Correlation of demographic
characteristics of the respondents with usefulness and effectiveness of technical
trainings as organized by PRSP in district Muzaffargarh. The Indus Cottons, 2: 219-
231.
Havrland B. and P. Kapila, 2000. Technological aspects of extension service in developing
countries. Agricultura Tropica et Subtropica, 33:3-39.
Hedjazi, Y., R. Rezaee, and N. Zamani, 2006. Factors affecting the use of ICTs by Iranian
agriculture extension specialists. J. Ext. Syst., 22: 1-15.
Hek, G. and P. Moule, 2006. Making sense of research: An introduction for health and social
care practitioners. 3rd edition. London, UK: Sage.
Higson-Smith and A. Kagee, 2006. Fundamentals of social statistics: An African perspective.
Cape Town: Juta: 190-193.
Hossain, M and A. Bayes, 2009. Rural economy and livelihoods insights from Bangladesh.
Dhaka: AH Development Publishing House, Dhaka.
Holdcraft, R.C. 1978.The rise and fall of community devolvement in developing counties,
1950- 65: A critical analysis and an innovated bibliography. MSU rural development
paper No. 2. Michigan State University, Michigan.
102
Holford, P., J. Malfroy, P. Parker, P. Robinson, W. Ward and P. Kailoa, 2008.
Communicating Science. Canberra, ACT: Australian Centre for International
Agricultural Research. 3:1-47.
Howell, J. L. and G.B. Hebron, 2004. Agricultural landowners' lack of preference for internet
extension. J. Ext., 42: 45-54.
Hussain, I., R. Sakthivadivel, U. Amarasinghe, M. Mudasser and D. Molden, 2003. Land and
water productivity of wheat in the western Indo-Gangetic plains of India and
Pakistan: A comparative analysis. International Water Management Institute
Research Report 65. Colombo, Sri Lanka: International Water Management Institute.
Hussain, M., 1997. Mass media. In: Memon, R.A. and E. Basir (Eds.), Extension Methods:
208–61. National Book Foundation, Islamabad, Pakistan.
Hussain, N. 2004. Analysis of the competency level of extension administration in the
Punjab. Unpolished Ph.D. Thesis, Department of Agricultural Extension, Univ. of
Agri. Faisalabad.
Idrees, M. 2003. Developing a strategy for mobilizing rural youth for the development of
agriculture in NWFP-Pakistan. Ph.D. Thesis, Department of Agricultural Extension,
Univ. of Agri., Faisalabad.
IICD (International Institute for Communication and Development). 2006. “ICTs for
agricultural livelihoods: Impact and lessons learned from IICD supported activities.”
The Hague: IICD.
Ikram-ul-Haq., M. Ahmad, T. Ali and M.I. Zafar, 2009. An analysis of farm services center
(FSC) approach launched for agricultural extension in NWFP, Pakistan. Pak. J. Agri.
Sci., 46: 69-72.
Ilahiane, H. 2007. Impacts of information and communication technologies in agriculture:
Farmers and mobile phones in Morocco. Paper presented at the annual meetings of
the American Anthropological Association, Washington, DC.
Iqbal, M., and M. Ahmad, 2005. Science & technology-based agriculture vision of Pakistan
and prospect of growth in: Pakistan Society of Development Economics (PSDE) 20
Annual General Meeting (AGM) on Regional Co-operation and Economic Growth
2005, Marriot Hotel Islamabad, Pakistan, 10th -12th January 2005.
103
Irfan, M. 2005. Comparative effectiveness of mass media in the dissemination of agricultural
technologies among farmers of Lahore district. M.Sc. (Hons.) Thesis, Department of
Agricultural Extension, Univ. of Agri., Faisalabad.
Irfan, M. S. Muhammad, G.A. Khan and M. Asif, 2006. Role of mass media in the
dissemination of agricultural technologies among farmers. Int. J. Agri. Bio., 8: 417-
419.
Isiaka, B.T., O. A. Lawal-Adebowale and O. Oyekunle, 2009. Agricultural extension agents’
awareness of ICT potentials and training needs on usage for improved extension
service delivery in selected southwest States. Nig. J. Hum. Soc. Sci. Creative Arts
4:18-30.
ITU. 2013. The world in 2013: ICT facts and Figures. Retrieved September 13, 2017 from
http:/www.itu.im/en/ITU-D/Statitics/pages/facts/default.aspx.
Jafri, M.N., G.A. Khan, S. Muhammad, H. Munir, M. Iftikhar, S. Ashraf. 2014. TV as
diversified agricultural information source perceived by farmers: Issues and concerns,
Int. J. Agri. Ext., 02:235-241.
Jehangir, W.A., I. Masih, S. Ahmed, M.A. Gill, M. Ahmad, R.A. Mann, M.R. Chaudhary,
A.S. Qureshi and H. Turral, 2007. Sustaining crop water productivity in rice-wheat
systems of South Asia: A case study from the Punjab, Pakistan. Working paper 115
Colombo Sri Lanka International Water Management Institute: 45-48.
Jenkins, A., M. Velandia, D. M. Lambert, R. K. Roberts, J. A. Larson, B. C. English, and S.
W. Martin, 2011. Factors influencing the selection of precision farming information
sources by cotton producers. Agri. Res. Eco. Rev., 40: 307-320.
Jensen, R. T. 2007. The digital provides: Information technology, market performance and
welfare in the South Indian fisheries sector. Qua. J. Eco., 122: 879-924.
Joseph M.K. and T.N. Andrew, 2007. Convergence opportunities and factors influencing the
use of internet and telephony by the rural women in South Africa and India towards
empowerment. J. Comput. Sci., 241: 1-20.
Just, D., S.A. Wolf, S. Wu, and D. Zilberman. 2006. Effect of information formats on
information services: analysis of four selected agricultural commodities in the United
States. Agri. Eco., 35: 289-301.
104
Jumani, N.B. 2009. Study on role of radio for rural education in Pakistan. The Turk. Online
J. Dist. Educ., 10(4): 176-187
Kaddu, S.B. 2011. Information and Communication Technologies’ (ICTs) contribution to the
access and utilization of agricultural information by the rural women in Ugand
Makerere University.
Kameswari, V.L.V., D. Kishore, V. Gupta, 2011. ICTs for agricultural extension: a study in
the Indian Himalayan region. Elec. J. Info. Sys. Dev. Ctries. 48: 1-12
Kamal, S., P. Amir and K. Mohtadullah, 2012. Development of integrated river basin
management for Indus Basin: Challenges and Opportunities. WWF-Pakistan, Lahore,
Pakistan: 123.
Kameshwari, V.L.V., D. Kishore, V. Gupta, 2011. ICTs for agricultural extension. The Elec.
J. Info. Sys. Dev. Cou., 48:1-12.
Kante, M., R. Oboko, and C. Chepken, 2016. Factors affecting the use of ICTs on
agricultural input information by farmers in developing countries.
Kaniki, A. M. 1995. Agricultural information user populations and critical tasks. In: Aina,
L.O, Kaniki, I.O and Ojiambo, J.B (eds) Agricultural information in Africa, Third
World Information Services Ltd., Ibadan. 4:56-70.
Karuhanga, M., E. Kiptot, and S. Franzel, 2012. The effectiveness of the farmer trainers
approach in technology dissemination in the East Africa DAIRY DEVELOPMENT
project in Uganda: A study of volunteer farmer trainers. Nairobi, Kenya: East Africa
Dairy Development Project (EADD).
Katungi, E. 2006. Gender, social capital and information exchange in rural Uganda. IFPRI
and Melinda Smale, IFPRI (International Food Policy Research Institute) CAPRI
Working Paper No.59, University of Pretoria, Uganda. Available at:
http://www.capri. cgiar.org/pdf/capriwp59.pdf
Katz, E., J.G. Blumler and M. Gurevitch, 2013. Uses and gratifications research. The public
opinion quarterly, 37:509-523.
Kenmore, P. 2002. Integrated pest management. Int. J. Occup. Environ. Health, 8:173-174
Kenny, C. and R. Keremane, 2007. Towards universal telephone access: Market progress and
progress beyond the market. Telecommunications Policy, 31: 155-163.
Khan, A. 2012. Major problems of agricultural sector of Pakistan. Economics and Education.
105
Khan, J.A. 2007. Research Methodology. APH Publishing Corporation, New Delhi.
Khan, S.A. 2005. Introduction to extension education. In: Memon, R.A. and E. Bashir (Eds.).
Extension Methods (3rd Ed.). National Book Found, Islamabad, Pakistan. : 3-32.
Khan, G.A., S. Muhammad, K.M. Chaudhry and M.A. Khan, 2010. Present status and future
preferences of electronic media as agricultural information sources by the farmers.
Pak. J. Agri. Sci., 47:166-172.
Khan. G.A., S. Muhammad. K.M. Chaudhry and M.A. Khan, 2012. Demographic
characteristics of farmers and general use of electronic media in the Punjab, Pakistan.
Sarhad. J. Agric., 28: 89-94.
Khan. G.A. 2010. Present and prospective role of electronic media in the dissemination of
agricultural technologies among farmers of the Punjab, Pakistan Ph.D. Thesis,
Department of Agricultural Extension, Univ. of Agri., Faisalabad.
Khan, A and M. Akram. 2012. Farmers’ perception of extension methods used by Extension
Personnel for dissemination of new agricultural technologies in Khyber
Pakhtunkhwa, Pakistan, Sarhad J. Agric., 28:511-520
Khan, A.M. and M. Shabbir. 2000. A study on the effectiveness of agriculture programme
“Sandal dharti” of radio Faisalabad in rural areas of Faisalabad. Pak. J. Agri. Sci. 37:
96-98
Khosrow-Pour, M. 2006. Emerging trends and challenges in information technology
management. Idea Group.
Khisa, S. G. 2003. Overview of farmer field schools approach in Kenya. In: K. R. Sones, D.
Duveskog, and B. Minjauw (Eds.), Farmer Field Schools: the Kenyan experience.
Report of the farmer field school’s stakeholders’ Forum. ILRI, Nairobi, Kenya. :3-10.
Khushk, A. M. and A. Memon, 2004. Increasing wheat yield. The Daily Dawn. 5 April.
Kidd, A.D., J.P.A. Lamers, P.P. Ficarelli, and V. Hoffmann, 2000. Privatizing agricultural
extension: caveat emptor. J. Rural Stu., 16: 95-102.
Kim L, K.L. Niewolny and P.T. Lillard, 2010. Expanding the boundaries of beginning farmer
training and program development: A review of contemporary initiatives to cultivate
a new generation of American farmers. J. Agric. Food Syst. Commun. Dev., 1: 1-65.
106
King, J, V. Gurbaxani, K. Kraemer, W. McFarlan, K. Raman and C. Yap, 1994. Institutional
factors in information technology innovation, Information Systems Research, 5:139-
169.
Kinsey, J. 2010. Five social media tools for the extension toolbox. J. Ext., 48:1-3.
Kirui, O.K., J.J. Okello, and R.A. Nyikal, 2010. Awareness and use of m-banking services in
agriculture: The case of smallholder farmers in Kenya. Contributed paper presented at
the Joint 3rd African Association of Agricultural Economists (AAAE) and 48th
Agricultural Economists Association of South Africa (AEASA) conference, Cape
Town, South Africa, September 19-23, 2010.
Kneen, J. 2011. Essential skills: Essential speaking and listening skills. Oxford University
Press. New York.
Knutson, J. 2011. Ag turns to social media to make its case. AGWEEK. Retrieved from
http://www.agweek.com/event/article/id/17797/. Koch Smith, C. (10, August 2017).
Kodagavallihatti, P.M., B.S. Mahanthesh and S. Dechamma, 2016. Attitude of farmers about
use of ICT tools in farm communication. J. Agric. Food Syst. Commun. Dev., 1: 1-
65.
Lasley, P., S. Pasgitt, and M. Hanson, 2001. Telecommunication technology and its
implications for farmers and Extension Services. Tech. in Soc., 23: 109-120.
Lederer, A.L., D.J. Maupin, M.P. Sena and Y. Zhuang, 2012. The technology acceptance
model and the World Wide Web. Decision Support Systems, 29:269-282.
Leagans, J.P. 1961. Extension programme building. In: extension education in community
development. Ministry of Food and Agriculture. New Delhi.
Lee, K.H. and M.F. Bellemare. 2013. Look who's talking: the impacts of the intra house hold
allocation of mobile phones on agricultural prices, J. Devel Stud., 49:624-640.
Levi, C. 2015. Effectiveness of information communication technologies in dissemination of
agricultural information to smallholder farmers in Kilosa District, Tanzania, master’s
dissertation, Department of Agriculture Extension Education, University of Makerere
Tanzania.
Lien, G. 2006. Management and risk characteristics of part-time and full-time farmers’ in
Norway. Rev. Agri. Eco., 28:111-131.
107
Livondo, J., A. Kipkoech, E. Macharia and P. Odwori, 2015. Factors affecting
communication channels reference information on adoption of agricultural
technology for Striga control: A case of Bungoma County, Kenya. Int. J. Curr. Res.,
7: 23057-23062.
Lodhi, T.E. 2003. Need for paradigm shift from top down to participatory extension in the
Punjab, Pakistan: perceptions of farmers, change agents and their supervisory staff.
Ph.D. Thesis, Department of Agricultural Extension, Univ. of Agri., Faisalabad.
Luneneburg, F.C. 2010. Communication: The process, barriers and improving effectiveness.
Schooling, 1:1-11.
Lwoga, E.T., C. Stilwell and P. Ngulube, 2011. Access and use of agricultural information
and knowledge in Tanzania. Library Review, 60:383-395.
Mahmood, M.A. and A.D. Sheikh, 2005. Crop yields from new technologies. P: III. “Daily
Dawn” March 28: April 3, 2005
Malik, S. 2000. The role of mass media in diffusing modern agricultural techniques to district
Sheikupura. M.Sc. (Hons.), Thesis, Department of Agricultural Extension, Univ. of
Agri., Faisalabad.
Malik, W.A. 1990. Systems paradigm: A study of agricultural knowledge system in Pakistan.
Islamabad, Pakistan: Leo Books publishers Islamabad.
Mallah, U. 1997. Extension programs in Pakistan. In: E. Basir (Ed.) Extension Methods (35-
60). Islamabad, Pakistan: National Book Foundation.
Manyozo, L. 2009. Mobilizing rural and community radio in Africa. Afric. J. Stu. 30:1-23.
Maningas, R.V., V.O.G. Perez, A.J.T. Macaraig, W.T. Alesna, and S.O. Villagonzalo, 2000.
Electronic information dissemination through the Farmers’ Information and
Technology Services (FITS)/ Techno Pinoy program: bringing information and
technology within the reach of the farmers. Available at: http://zoushoku.narc.affrc.
go.jp/ADR/AFITA-/afita/afita conf/2000/part08/p231.pdf.
Manohari, P.L. 2002. Key communicator networks used in dissemination of agricultural
information: A case study in Kenya sub tribe setting. Manage extension research
review III: 39-41. National Institute of Agricultural Extension Management,
Rajendranagar, Hyderabad, India.
108
Manyozo, L. 2009. Mobilizing rural and community radio in Africa. Ecquid Novi: African J.
Stu., 30:1-23.
Masood, A., N. Ellahi and Z. Batool, 2012. Causes of low agricultural output and impact on
socio-economic status of farmers: A case study of rural Potohar in Pakistan. Int. J.
Bas. Appl. Sci. 1:343-351.
Mawazo M.M. 2015. Linking rural farmers to markets using ICTs. The Technical Centre for
Agricultural and Rural Cooperation (CTA) working paper 15/12. Wageningen,
Netherlands.
Meera, S.N., A. Jhamtani, and D. Rao, 2004. Information and communication technology in
agricultural development: A comparative analysis of three projects from India. Agren.
Network Paper: 1-14.
Memon, I., K.N. Panhwar, R.A. Chandio, A.L.Bhutto and A.A. Khooharo, 2014. Role of
mass media in dissemination of agricultural technology among the farmers of
Jaffarabad District of Balochistan. J. Bas. Appl. Sci., 10: 525-531.
Meyers, C., E. Irlbeck, M. Graybill and D. Doerfert, 2011. Advocacy in agricultural social
movements: Exploring Facebook as a public relations communications tool. J. Appl.
Comm., 95:68-81.
Michailidis, A., M. Partalidou, S.A. Nastis, A. Papadaki-Klavdianou, C. Charatsari, 2011.
Who goes online? Evidence of internet use patterns from rural Greece.
Telecommunication Policy, 35:333–343.
Michiels, S.L. and I. Vancrowder, 2001. Discovering the magic box, local appropriation of
information and communication technologies (ICTs). FAO, Rome.
Mickler, C. and U.M. Staudinger. 2008. Personal wisdom: Validation and age-related
differences of a performance measures. Psychology and Aging. 23: 787-799.
Michler, J. D. and L. Anna Josephson, 2017. To specialize or diversify: Agricultural diversity
and poverty dynamics in Ethiopia. World Dev., 89: 78-85.
Miller, T.R., A. Wiek, D. Sarewitz, J. Robinson, L. Olsson, D. Kriebel and D. Loorbach,
2014. The future of sustainability science: A solutions-oriented research agenda. Sust.
Sci., 9: 239-246.
Minja E., E. Ulicky, M. Mfoi, M. Marawiti and H. Mziray H. 2004. Farmer group activity
reports for DFID crop protection programme (CPP). Bean IPM Promotion Project in
109
Eastern and Southern Africa. Retrieved on January 24, 2012 from: http//:www.ciat.
org/ Africa/pdf/ffd_sanjajjuu_Tan_Uun04.pdf.
Mirani, Z., G. Leske, Z.H. Bhatti and S.A. Khan, 2003. Impact assessment of the on-farm
water management projects in Hyderabad district of Sindh Province, Pakistan.
Association for International Agricultural and Extension Education. Proceedings of
the 19th annual conference, Raleigh, North Carolina, USA: 461-468.
Mirani, Z.U., G.W. Leske, and A.H. Laba, 2013. Farmers’ adoption of recommended
technology for rice in Larkana district of Sindh province of Pakistan. FAO, Rome,
Italy.
Mittal S. 2012. Modern ICT for agricultural development and risk management in
smallholder agriculture in India. Socio-economics Working Paper 3. Mexico, DF:
International Maize and Wheat Improvement Center (CIMMYT).
Moayedi, A.A. and M. Azizi, 2011. Participatory management opportunity for optimizing in
agricultural extension education. Proce. Soc. Beha. Sci., 15:1531-1534.
Moemeka, A. 2000. Development Communication in action: Building understanding and
creating participation. University Press of America.
Moemeka, A. 2000. Reporter' Handbook: An introduction to effective journalism. USA:
Morris Publishing.
Mouton, J. 1996. Understanding Social Research. Pretoria: Van Schaik Publishers South
Africa.
Movius L, M. Cody, G. Huang, M. Berkowitz and S. Morgan, 2007. Motivating television
viewers to become organ donors. Cases in public health communication and
marketing.
Available at: http://www.gwumc.edu/sphhs/departments/pch/phcm/casesjournal/vo
lume1/peer-reviewed/cases_1_08.pdf.
Mtega, W.P and A.C. Msungu, 2013. Using information and communication technologies for
enhancing the accessibility of agricultural information for improved agricultural
production in Tanzania. The Elec. J. Info. Sys. Dev. Cou., 56 (1):1-14.
Mubin, O., J. Tubb, M. Novoa, M. Naseem and S. Razaq, 2015. Understanding the needs of
Pakistani farmers and the prospects of an ICT intervention. Proceedings of the 33rd
110
annual ACM conference extended abstracts on human factors in computing systems.
Seoul, Republic of Korea: 1109-1114.
Muhammad, S. 2005. Agricultural Extension: Strategies and Skills. Unitech Communication,
Faisalabad, Pakistan.
Muhammad, S. 1994. An effective communication model for the acceptance of new
agricultural technology by farmers in the Punjab, Pakistan. Ph.D. Thesis, Department
of Agricultural Extension and Rural Development, University of Reading. England.
Muhammad, S. and C. Garforth, 1999. Farmers’ information exposure and its impact on their
adoption behavior. Pak. J. Agri. Sci., 32:262-265.
Muhammad, S., S.A. Butt and I. Ashraf, 2004. Role of television in agricultural technology
transfer. Pak. J. Agri. Sci., 41:158-161.
Muhammad, S., T.E. Lodhi and G.A. Khan, 2008. An in-depth analysis of the electronic
media for the development of a strategy to enhance their role in agricultural
technology transfer in the Punjab, Pakistan. Final report of research project submitted
to Higher Education Commission, Islamabad.
Muhammad, S. T.E. Lodhi, G.A. Khan. 2012. In-depth analysis of electronic media to
enhance their role in agricultural technology transfer in the Punjab, Pakistan, Pak. J.
Agric. Sci., 49: 221-227.
Munyua, H., E. Adera, M. Jensen, 2009. Emerging ICTs and their potential in revitalizing
small-scale agriculture in Africa. Agric. Inf. Worldwide. 2:3-9.
Muro, P.D. and F. Burchi. 2007. Education of rural people and food security. A cross country
analysis. Roma department of economics food and agriculture organization of the
United Nations. Rome.
Mwombe, S.O.L. F.I. Mugivane, I.S. Adolwa, J.H. Nderitu, 2014. Evaluation of information
and communication technology utilization by small holder Banana farmers in
Gatanga District, Kenya.J. Agric. Educ. Ext.20:247-261.
Narender, K. and N. Anandaraja, 2008. Information and communications technology for
women experience of women managed internet kiosks at Melur, Tamil Nadu. In:
Extension of technologies from lab to farm. (Eds.) Anandaraja, N., K. Chandrakandan
and M. Ramasubramaniam. New India Publishing Agency.
111
Nalugooti, A. and E. Semakula, 2006. Limitations and opportunities of farmer and privately
serviced extension system in Nakisunga sub county, Mukono District Ugandan.
Available at: http://hdl.handle.net/10570/1382.
Nazam, M. 2000. A sociological study of the factors affecting the adoption rate of modern
agricultural technologies in tehsil Chishtian. M.Sc. Thesis, Department of Rural
Sociology, Univ. Agri., Faisalabad, Pakistan.
Nazari, M.R. and M.S.B.H. Hassan, 2011. The role of television in the enhancement of
farmers’ agricultural knowledge. African J. Agri. Res., 6: 931-936.
Nazari M.R., A.H. Hasbullah, S. Parhizkar, A. Shiraz and R. Marioriad, 2009. The impact of
visuals: Using television program to transform environmental health concepts to
people. J. Appl. Sci., 8: 2619-2624.
Ngamau, K., 2013. Factors affecting effective adoption of e-learning in Kenyan Universities:
The case of Jomo Kenyatta University of Agriculture and Technology. Doctoral
Dissertation, United States International University, Africa.
Ngathou, I.N., J.O. Bukenya and D.M. Chembezi, 2006. Managing agricultural risk:
Examining information sources preferred by limited resource farmers. J. Ext. 44:44-
53.
Nkwocha, V.I., I.I. Ibeawuchi, N.O. Chukwueke, N.O. Azubuike and G.A. Nwkwoch, 2009.
Overview of the impact of information and communication technology on agricultural
development in Imo State, Nigeria. Proceeding of the 43rd annual conference of the
agricultural society of Nigeria held in Abuja, from 15-20 August 2009, Nigeria.714.
Nosheen, F., T. Ali and M. Ahmad, 2010. Analysis of gender specific sources of information
regarding home and farm practices in Potohar region: a case study. The J. Anim.
Plant Sci., 20:56-59.
Oakley, P and C. Garforth, 1985. Guide to Extension Training, FAO, Rome Italy.
Ogboma, M. U. 2010. Access to agricultural information by fish farmers in Niger Delta
region of Nigeria. Available at: http:// digitalcommons.unl.edu /cgi/ viewcontent. cgi.
Ofuoku, A.U., G.N. Emah and B.E. Itedjere, 2008. Information utilization among rural fish
farmers in Central Agricultural Zone of Delta state, Nigeria. World J. Agric. Sci.,
4:558-564.
112
Oladeji, J.O. 2011. Farmers’ perception of agricultural advertisements in Nigerian
newspapers in Ibadan municipality, Oyo State, Nigeria. J. Media and Commu. Stud.,
3:97-101.
Olaleye, R.S., F.S. Gana, I.S. Umar, M.A. Ndanisa and E.W. Peter, 2009. Effectiveness of
radio in the dissemination of agricultural information among farmers in local
government area of Kwara State, Nigeria. Conti. J. Agri. Sci., 3:1-6.
Omobolanle, O. L. 2008. Analysis of extension activities on farmers’ productivity in
Southwest, Nigeria. Afr. J. Agric. Res., 3: 469-476.
Opara, U.N. 2008. Agricultural information sources used by farmers in Imo State, Nigeria.
Info. Dev., 24:289-292.
Oto J.O. and D. Shimayohol, 2011. Extension communication channels’ usage and
preference by farmers in Benue State Nigeria. J. Agri. Ext. Rural Dev. 3:88-94.
Otter, V. and L. Theuvsen, 2013. ICT and Farm Productivity: Evidence from the Chilean
Agri-cultural Export Sector. In: Clasen, M., M. Hamer, S. Lehnert, B. Petersen, B.
Theuvsen, (Eds.), IT- Standards in der Agrar- und Ernährungswirtschaft; Fokus:
Risiko- und Krisenmanagement. Bonner Köllen Verlag: Bonn: 113-116.
Parthaap, D.P. and K.A. Ponnusamy, 2006. Effectiveness of four mass media channels on
the knowledge gain of rural women. J. Int. Agric. Ext. Edu., 13:73-81.
Pawlick, T.F. 1996. The invisible farm: The worldwide decline of farm news and agricultural
journalism training. Master's thesis, Carleton University, Ottawa, Canada.
Eguoko, E.V., T. Dwarha, T.M. Olu, 2015. Extension communication channels’ usage and
preference by farmers in Benue State Nigeria. J. Agri. Ext. and Rural Dev., 3101-107.
Pertev R. 1994. The role of farmers and farmers' organizations. : 152. In: Plaza P.
(Ed.). Extension, component of agricultural and rural development: proceedings of
the Granada seminar. 24-26 Nov. 1994, Granada, Spain.
Pineda, N. 2010. Facebook tips: What's the difference between a Facebook page and group?
Retrieved from: http://www.facebook.com/blog.php?post=324706977130
Pipy F. O, 2006. Poultry farmers’ utilization of information in Lagelu local government area,
Oyo State of Nigeria. Int. J. Poultry Sci. 5: 499-501.
113
Place, F., M. Adato, P. Hebinck, M. Omosa, 2005. The impact of agroforestry-based soil
fertility replenishment practices on the poor in western Kenya. IFPRI, research report
No. 142.
Planning Commission. 2012. Agriculture and food security in annual plan 2013-14. In:
planning commission, ministry of planning, development and reform. Annual plan
2013-14. Planning commission, ministry of planning development and reform,
government of Pakistan Islamabad, Pakistan: 77-93.
PTA. 2010. Pakistan Telecommunication Authority.
Punch, K. 2006. Developing effective research proposals (second edition). Thousand Oaks,
CA. Sage.
Qamar, M.K. 2005. Modernizing national agricultural extension systems: A practical guide
for policy-makers of developing countries. FAO, Rome, Italy.
Qureshi, A.S., P.G. McCornick, M. Qadir and Z. Aslam, 2008. Managing salinity and water
logging in the Indus Basin of Pakistan. J. Agric. Water Manage. 95: 1-10.
Ray, G. L. 1991. Extension communication and management (1st Ed.). Kalyani Publishers,
New Delhi, India.
Rehman, F., S. Muhammad, I. Ashraf, K. Mahmood, T. Ruby and I. Bibi, 2013. Effect of
farmers’ socioeconomic characteristics on access to agricultural information:
empirical evidence from Pakistan, The J. Ani. Plan. Sci., 23: 324-329.
Rivera,W and G. Alex, 2004. Privatization of extension systems: Case studies of
international initiatives. Agriculture and rural development discussion paper 9.
Extension reform for rural development. The World Bank.
Rizvi, H. 2003. National consultation in Pakistan: workshop held at Islamabad from
November 17–19 2003 [Online]. Available: http://www.wsis.sdnpk.org.
Rodriguez, A.B. 2008. A framework for align strategy, improvement performance and
customer satisfaction using an integration of Six Sigma and Balanced Scorecard,
Ph.D. Thesis, College of Engineering and Computer Science, University of Central
Florida, CA.
Saadi, H., K.N. Mahdei and R. Movahedi, 2008. Surveying on wheat farmers’ access and
confidence to information and communication channels (ICCs) about controlling
114
Eurygaster integriceps in Hamedan province, Iran. Amer. J. Agri. and Biol. Sci., 3:
497-501.
Saleem, M., T. Ali and M. Ahmad, 2010. Identification and prioritization of competencies
possessed by mango growers in district Faisalabad, Pakistan. Pak., J. Agri. Scie., 47:
421-424.
Salau, E.S. and N.D. Saingbe. 2008. Access and utilization of information and
communication technologies (ICTs) among agricultural researchers and extension
workers in selected institutions in Nasarawa State of Nigeria. 4: 1-11.
Sattar, T. 2012. A sociological analysis of constraining Factors of development in agriculture
sector of Pakistan. J. Econ. Sustain. Dev., 3:8-24.
Sekabira, H., J. Bonabana and N. Asingwire, 2012. Determinants for adoption of information
and communications technology (ICT)-based market information services by
smallholder farmers and traders in Mayuge District, Uganda. J. Dev. Agri.
Eco., 4:404-415.
Serra, T., B.K. Goodwin, and A.M. Featherstone, 2005. Agricultural policy reform and off-
farm labour decisions. J. Agri. Eco., 56:271-285.
Shahbaz, M., S. Abosedra, R. Sbia, 2013. Energy consumption, financial development and
growth: evidence from cointegration with unknown structural breaks in Lebanon.
Online at http://mpra.ub.uni-muenchen.de/46580/MPRA Paper No. 46580, posted 29.
April 2013 08:25 UTC.
Shaikh, M.A. 2007. Satellite television and social change in Pakistan: A case study of rural
Sindh. Orient Books Public. House, Karachi, Pakistan.
Shannan and Weaver, 1949. The mathematics of communication. Scientific
American, 181:11-15.
Shrum, W. and P. Campion, 2000. Are scientists in developing countries isolated? Sci. Tech.
Soc., 5:1-34.
Shetto, M.C. 2008. Assessment of agricultural information needs In African, Caribbean and
Pacific (ACP) States Eastern Africa Country Study: Tanzania. Ministry of
Agriculture, Food Security and Cooperatives on behalf of the Technical Centre for
Agricultural and Rural Cooperation (CTA). http://icmpolicy.cta.int/filesstk/Tanzania_
Final-report-081209. pdf.
115
Siddiqui, B.N. 2006. Analysis of communication interventions of extension field staff in
apple growing areas of Baluchistan, Pakistan. Ph.D. Thesis, Department of
Agricultural Extension, Univ. of Agri., Faisalabad.
Siddiqui, B., M. Hassan, F. Asif, S. Iqbal, M. Bajwa and N. Malik. 2013. Awareness
adoption and reasons for non-adoption of apple growers with regards to
recommended horticulture practices. Pak. J. App. Sci., 3: 182-184.
Sife, A, E. Kiondo and J.G. Lyimo-Macha, 2010. Contribution of mobile phones to rural
livelihoods and poverty reduction in Morogoro region, Tanzania. The Elec. J. Info.
Sys. Dev. Coun., 42:1-15.
Singh, A.K. 1986. Tests Measurements and Research Methods in Behavioral Sciences. Tata
MacGraw-Hill Publishing Company Limited, New Delhi.
Singh, D. and D.S. Dhillon, 2006. Communication behavior of agricultural development
officers of Punjab. Annals of Biol., 22: 66-74.
Singh, S. 2008. Selected success stories in agricultural information systems Asian pacific
association of agriculture and research, Bangkok, Thailand: 40.
Singh, H., C. Kvyon and S. Kin, 2007. IPTV over wireless LAN: promises and challenges,
process dings of the 5th IEEE conference communication and networking conference,
Las Vegas, 626-631
Singh, S. 2006. Selected success stories on agricultural information systems. Asia-pacific
association of agricultural research institutions. Bankok, Thailand.
Souter, D. 2010. ICTs and development in Zambia: challenges and opportunities. Policy
Brief, Information society programme, Panos London.
Squire, P.J. 2000. Factors influencing traditional farmers to adopt improved food production
technologies in Bo district of Southern Sierra Leon. J. Ext. Syst., 16: 107-116.
Strong, R., W. Ganpat, A. Harder, T.L. Irby and J.R. Lindner, 2014. Exploring the use of
information communication technologies by selected Caribbean extension officers. J.
Agric. Educ. Ext. 20:485–495.
Stienen, J., W. Bruinsma and F. Neuman, 2007. How ICT can make a difference in
agricultural livelihoods .The commonwealth ministers reference book.
Subedi, A. and C. Garforth, 1996 Gender, information and communication networks:
implications for extension. Eur. J. Agri. Edu. Ext., 3: 63-74.
116
Subramanian, A., P. Purohit, R. Echavarri. 2017. Information provision and learning
outcomes: Helpline intervention in agriculture under risk, Adam Smith Business
School, University of Glasgow.
Sutter, J. D. 2009. Twittering from the tractor: Smartphones sprout on the farm. CNN.com.
Syngenta Foundation. 2012. Syngenta Foundation for Sustainable Agriculture Review 2012-
2013.file:///C:/Users/Saleem/Downloads/syngenta_review_2012-13_onlineversion.
pdf.
Tanzania communication regulatory authority, 2012. Quarterly Telecom Statistics. 5:1-34.
http://www.tcra.go.tz/publications/telecom
Thakur, D. 2003. Research Methodology in Social Science. Deep and Deep Publications
(Pvt.) LTD. Rajouri Garden, New Dehli: 475.
Tesfaye, S., B. Bedada, and Y. Mesay, 2016. Impact of improved wheat technology adoption
on productivity and income in Ethiopia. Afri. Cro. Sci. J., 24:127-135.
Tiamiyu, M.A. 2002. Information and communication technology (ICTs) for social
development issues: Options and strategies. African J. Libr. Info. Sci., 12:12-40.
Thompson, N.M. 2012. Two studies evaluating input use in soybean and cotton production.
Master’s Thesis, University of Tennessee. http://trace.tennessee.edu/utk_
gradthes/1215.
Tourish, D. 2010. Auditing organizational communication: A handbook of research, theory,
and practice. New York, NY: Routledge.
Tweeten, J.F. 2014. Perceptions regarding importance and frequency of use of selected
communication tools by Iowa cattle producers. Retrieved from digital depository.
Iowa State University. 13749.
United Nations. 2005. Global E-government readiness report: from E-government to
Inclusion. UNPAN/2005/14, United Nations, New York.
USDA. 2007. Off farm work and the adoptions of agriculture innovation. Available at
http://www.ers.usda.gov/publications
Varner, J. 2012. Agriculture and social media. Mississippi State University. Retrieved from
http://msucares.com/pubs/infosheets/is1946.pdf
117
Velandia, M., R.M. Rejesus, T.O. Knight and B.J. Sherrick, 2009. Factors affecting farmers'
utilization of agricultural risk management tools: the case of crop insurance, forward
contracting, and spreading sales. J. Agri. App. Eco., 41:107-123.
Voh, J.P. 2002. Information sources and awareness of selected recommended farm practices:
A case study of Kaduna State, Nigeria. Afri. J. Agri. Sci. 8:80-87.
Ward, W. and D. Spennemann, 2000. Getting wired: A Pacific Islands study. Aust. J.
Comm., 27:91-104.
Waseem, M. 1982. Local power structure and the relevance of rural development strategies:
A case study of Pakistan. Commu. Dev. J., 17: 225-233.
Waters, R.D., E. Burnett, A. Lamm and J. Lucas, 2009. Engaging stakeholders through social
networking: How nonprofit organizations are using Facebook. Public relations
review. 35:102-106.
Welman, C., F. Kruger and B. Mitchell, 2009. Research Methodology (3rd Ed.). Cape Town:
Oxford University Press: 342.
Wenger, E., R.A. McDermott and W. Snyder, 2002. Cultivating communities of practice: A
guide to managing knowledge. Boston: Harvard Business School Press.
White, D., M. Courtney, D. David; and I. Erica. 2014. Exploring Agriculturalists' Use of
social media for agricultural marketing. J. App. Comm. 98: 1051-1094
Wiese, M., Y. Jordaan and C.H. Heerden, 2010. Differences in the usefulness of
communication channels, as experienced by gender and ethnic groups during their
university selection process, Communication: South African J. Commu. Theo. Res.,
36:112-129.
Wijekon R. and B. Newton, 2000. Multimedia training support for extension trainers in
developing countries. CESO Report. Netherlands.
World Bank, 2002. Information and Communication Technologies. World Bank group
support for the development of information infrastructure water manage. 95:1-10.
World Bank. 2011. Food Price Watch. http://siteresources.worldbank.org/INTPREMNET/
Resources/Food_Price_Watch_Feb_2011_Final_Version.pdf, accessed September 4,
2011.
Yamane, T. 1967. Statistics, an Introductory Analysis (2nd Ed.). New York: Harper and Row.
118
Yaseen, M., S.W. Xu, W. Yu and S. Hassan, 2016. Farmers’ access to agricultural
information sources: Evidences from rural Pakistan. J. Agric. Chem. Environ., 5: 12-
19.
Yaseen, M., X. Shiwei, Y. Wen and S. Hassan, 2015. Policy challenges to agricultural
extension system in Pakistan: A review. Int. J. Agric. Appl. Sci., 7:111-115.
Yifu, J., 1999. Technological change and agricultural household income distribution: theory
and evidence from China. Aus. J. Agri. Res. Eco., 43:179-194.
Yore, L. D., B.M. Hand and M.K. Florence, 2004. Scientists' view of science, models of
writing and science writing practices. J. Res. Sci. Teac., 41:338-369.
Zakar, M.Z. and R. Zakar, 2009. Diffusion of information technology for agricultural
development in rural Punjab: Challenges and opportunities. J. Pak. Visi., 9:136-174.
Zappacosta, M. 2001. Information technologies for rural development: between promises and
mirages. Info., 3:521-534.
Zijp, W. 1994. Improving the transfer and use of agricultural information: A guide to
information technology. World Bank.
119
APPENDIX # 1
Table 1: Respondents’ distribution according to the extent of use of ICTs
ICTs 1 2 3 4 5
No
Response
f % f % f % f % f % f %
Radio/FM 53 13.25 10 2.50 45 11.25 62 15.50 13 3.25 217 54.25
TV 97 24.25 31 7.75 47 11.75 98 24.50 46 11.50 81 20.25
Internet 15 3.75 10 2.50 18 4.50 26 6.50 2 0.50 329 82.25
Computer 13 3.25 3 0.75 2 0.50 9 2.25 11 2.75 362 90.50
Mobile Phone 86 21.50 27 6.75 57 14.25 119 29.75 51 12.75 60 15.00
Social media 1 0.25 2 0.50 5 1.25 32 8.00 0 0.00 360 90.00
Fixed phone/
land line phone 0 0.00 0 0.00 5 1.25 0 0.00 2 0.50 393 98.25
Agri. helplines 0 0.00 2 0.50 0 0.00 9 2.25 0 0.00 389 97.25
Agri. websites 8 2.00 2 0.50 12 3.00 6 1.50 0 0.00 372 93.00
Table 2: Various kinds of information obtained from ICTs by respondents
Information regarding 1 2 3 4 5
f % f % f % f % f %
Production of major crops
(wheat, cotton, rice,
sugarcane etc.)
96 24.00 29 7.25 27 6.75 73 18.25 175 43.75
Plant protection measures
(pest, insects and dieses
management)
102 25.50 16 4.00 60 15.00 117 29.25 105 26.25
Weather updates 160 40.00 70 17.50 90 22.50 38 9.50 42 10.50
120
Livestock & Poultry
management 160 40.00 70 17.50 90 22.50 40 10.00 40 10.00
Harvesting and post
harvesting practices 202 50.50 39 9.75 87 21.75 63 15.75 9 2.25
Marketing of agricultural
produce 224 56.00 62 15.50 65 16.25 36 9.00 13 3.25
Farm resource conservation 236 59.00 52 13.00 74 18.50 36 9.00 2 0.50
Access to credit 261 65.25 58 14.50 22 5.50 55 13.75 4 1.00
New cropping scheme 289 72.25 21 5.25 40 10.00 45 11.25 5 1.25
Table 3: Future preference of ICTs for getting agricultural information by respondents
ICTs 1 2 3 4 5
f % f % f % f % f %
Radio/FM 21 5.25 27 6.75 46 11.50 66 16.50 12 3.00
TV 39 9.75 33 8.25 61 15.25 85 21.25 50 12.50
Mobile 27 6.75 4 1.00 61 15.25 117 29.25 106 26.50
Internet 21 5.25 4 1.00 30 7.50 22 5.50 14 3.50
Computer 28 7.00 4 1.00 20 5.00 12 3.00 0 0.00
Land line Phone 30 7.50 12 3.00 20 5.00 0 0.00 0 0.00
Agri. helplines 25 6.25 4 1.00 29 7.25 19 4.75 0 0.00
Agri. websites 30 7.50 14 3.50 10 2.50 14 3.50 12 3.00
121
Table 4: Effectiveness of radio as a source of agricultural information for respondents
Radio Weighted score Mean SD Rank
Easy access of information 675 4.28 0.741 1
Timely information 622 4.09 0.842 2
Accurate information 606 4.12 0.914 3
Improve farming skills 596 3.73 0.993 4
Better agricultural information source 593 4.21 0.826 5
Cheaper source of information 589 3.50 1.161 6
Better communication 588 4.21 0.823 7
Easy to use 466 3.79 1.180 8
Table 5: Effectiveness of TV as a source of agricultural information for respondents
TV Weighted score Mean SD Rank
Easy to use 864 4.21 1.016 1
Easy access of information 856 4.22 0.919 2
Cheaper source of information 843 4.28 0.801 3
Accurate information 741 3.88 0.809 4
Timely information 718 3.68 0.850 5
Better agricultural information
source 649 3.98 0.972 6
Better communication 648 3.81 0.897 7
Improve farming skills 621 3.65 0.899 8
122
Table 6: Effectiveness of mobile as a source of agricultural information for respondents
Mobile Phone Weighted score Mean SD Rank
Easy access of information 1054 4.02 0.914 1
Timely information 1046 4.32 0.790 2
Better communication 1035 4.05 0.894 3
Accurate information 981 3.96 0.742 4
Easy to use 951 3.95 0.613 5
Better agricultural information
source 936 4.17 0.998 6
Improve farming skills 859 4.12 0.720 7
Cheaper source of information 826 3.95 0.729 8
Table 7: Effectiveness of internet as a source of agricultural information for
respondents
Internet Weighted score Mean SD Rank
Timely information 315 3.94 1.286 1
Easy access of information 288 3.84 1.193 2
Accurate information 285 3.96 1.249 3
Better communication 240 3.81 1.980 4
Improve farming skills 226 3.59 1.399 5
Better agricultural information
source 216 3.54 1.555 6
Cheaper source of information 202 2.85 1.316 7
Easy to use 154 2.70 1.302 8
123
Table 8: Effectiveness of computer as a source of agricultural information for
respondents
Computer Weighted score Mean SD Rank
Easy access of information 87 3.00 1.069 1
Better communication 84 2.90 1.676 2
Cheaper source of information 83 2.86 1.356 3
Timely information 79 2.72 1.222 4
Better agricultural information
source 78 2.89 1.553 5
Accurate information 77 2.66 1.173 6
Improve farming skills 77 2.66 1.344 7
Easy to use 55 2.20 0.707 8
Table 9: Effectiveness of land line phone as a source of agricultural information for
respondents
Land line Phone Weighted score Mean SD Rank
Easy access of information 90 3.10 1.345 1
Easy to use 83 3.07 1.385 2
Accurate information 77 3.08 1.115 3
Improve farming skills 75 2.78 1.368 4
Better agricultural information
source 73 2.70 1.540 5
Cheaper source of information 69 2.76 1.021 6
Timely information 64 2.56 1.294 7
Better communication 51 2.68 1.250 8
124
Table 10: Effectiveness of agri. helpline as a source of agricultural information for
respondents
Agri. helpline Weighted score Mean SD Rank
Cheaper source of information 172 3.58 1.318 1
Better communication 169 3.52 1.584 2
Easy access of information 158 3.29 1.414 3
Better agricultural information
source 153 3.19 1.363 4
Accurate information 148 3.22 1.284 5
Timely information 142 3.09 1.427 6
Improve farming skills 135 2.93 1.340 7
Easy to use 126 3.50 1.183 8
Table 11: Effectiveness of agri. websites as a source of agricultural information for
respondents
Agri. websites Weighted score Mean SD Rank
Better agricultural information
source 170 3.78 1.412 1
Improve farming skills 160 3.56 1.307 2
Accurate information 157 3.49 1.313 3
Better communication 151 3.36 1.250 4
Timely information 145 3.22 1.277 5
Cheaper source of information 135 3.14 1.342 6
Easy to use 116 2.58 0.917 7
Easy access of information 106 2.65 1.027 8
125
Table 12: Preferred area of agriculture by respondents for getting information from
ICTs
Various areas of
Agri.
Information
1 2 3 4 5 No
Response
f % f % f % f % f % f %
Farm management 31 7.75 23 5.75 52 13.00 87 21.75 39 9.75 168 42.00
Agronomic
practices (land
preparation/seed,
fertilizer,
irrigation etc.)
16 4.00 11 2.75 65 16.25 57 14.25 190 47.50 61 15.25
Plant protection
measures 6 1.50 14 3.50 34 8.50 109 27.25 153 38.25 84 21.00
Harvesting/post-
harvest technology 14 3.50 12 3.00 48 12.00 105 26.25 92 23.00 129 32.25
Storage techniques 23 5.75 29 7.25 71 17.75 134 33.50 39 9.75 104 26.00
Marketing 16 4.00 15 3.75 35 8.75 120 30.00 104 26.00 110 27.50
Farm
mechanization 12 3.00 31 7.75 98 24.50 87 21.75 56 14.00 116 29.00
Agri. loan
schemes 9 2.25 23 5.75 83 20.75 120 30.00 50 12.50 115 28.75
Table 13: Challenges faced by respondents in the use of radio/FM
Radio/FM Weighted score Mean SD Rank
Lack of awareness 680 3.15 1.160 1
Lack/poor feedback 569 3.49 .863 2
Lack of interest 486 3.31 1.004 3
Inadequate information 447 3.34 .933 4
Poor quality transmission 436 3.21 .870 5
Lack of ownership 429 3.18 .790 6
Odd transmission time 428 3.15 .848 7
Lack of credibility of medium 427 3.36 .914 8
Lack of education 425 2.85 1.210 9
Language (difficult) 425 3.40 .871 10
Lack of visual impact 407 3.16 1.027 11
Lack of time (busy) 392 2.74 1.249 12
High cost 379 2.56 1.132 13
126
Table 14: Challenges faced by respondents in the use of TV
TV Weighted score Mean SD Rank
Poor quality transmission 697 3.50 0.778 1
Lack/poor feedback 680 3.38 0.979 2
Language (difficult) 615 3.34 0.885 3
Lack of interest 581 3.23 0.991 4
Lack of time (busy) 506 3.03 1.061 5
Inadequate information 504 3.05 1.072 6
Lack of credibility of medium 490 2.97 1.015 7
Lack of visual impact 482 3.01 1.028 8
Lack of awareness 460 2.95 1.076 9
Lack of ownership 441 3.02 0.890 10
Odd transmission time 391 2.79 1.089 11
Lack of education 349 2.68 1.175 12
High cost 346 2.72 1.258 13
Table 15: Challenges faced by respondents in the use of mobile
Mobile Phone Weighted score Mean SD Rank
Language (difficult) 778 3.21 0.962 1
High cost 699 3.86 0.801 2
Lack/poor feedback 698 3.44 0.944 3
Lack of time (busy) 634 2.98 1.007 4
Lack of visual impact 449 2.69 0.963 5
Inadequate information 449 2.70 0.929 6
Lack of credibility of medium 430 2.67 0.927 7
Lack of ownership 416 2.85 1.116 8
Odd transmission time 414 2.64 1.161 9
Lack of interest 408 2.63 1.264 10
Poor quality transmission 398 2.73 1.189 11
Lack of education 372 2.51 1.343 12
Lack of awareness 368 2.37 1.185 13
127
Table 16: Challenges faced by respondents in the use of internet
Internet Weighted score Mean SD Rank
High cost 397 3.75 0.926 1
Lack of education 332 3.65 0.822 2
Lack of time (busy) 285 3.48 0.835 3
Language (difficult) 176 3.26 0.935 4
Inadequate information 120 3.43 1.065 5
Lack of credibility of medium 102 3.29 1.071 6
Lack of ownership 100 3.23 0.990 7
Odd transmission time 94 3.03 1.048 8
Lack/poor feedback 92 2.63 1.262 9
Lack of visual impact 90 2.90 1.165 10
Poor quality transmission 88 2.84 1.186 11
Lack of interest 78 2.89 1.121 12
Lack of awareness 72 2.67 1.301 13
Table 17: Challenges faced by respondents in the use of computer
Computer
Weighted score
Mean
SD
Rank
Lack of education 496 3.79 0.785 1
Lack of ownership 186 3.58 0.848 2
Language (difficult) 138 3.14 1.193 3
Lack of time (busy) 104 2.89 1.116 4
Lack of visual impact 87 3.00 1.134 5
Inadequate information 86 2.97 1.322 6
High cost 84 2.90 1.263 7
Lack of interest 83 2.86 1.302 8
Poor quality transmission 78 2.69 1.004 9
Lack of credibility of medium 78 2.69 1.312 10
Lack of awareness 75 2.59 0.907 11
Odd transmission time 72 2.48 1.214 12
Lack/poor feedback 70 2.41 1.211 13
128
Table 18: Challenges faced by respondents in the use of landline
Landline phone Weighted
score Mean SD Rank
Lack of ownership 927 3.72 0.824 1
Lack of education 427 3.71 0.925 2
Lack/poor feedback 110 3.14 1.556 3
Language (difficult) 108 3.09 1.502 4
High cost 107 3.15 1.306 5
Lack of credibility of medium 106 3.03 1.524 6
Inadequate information 96 2.74 1.704 7
Lack of time (busy) 89 2.54 1.094 8
Lack of visual impact 88 2.51 1.292 9
Lack of awareness 66 2.44 1.155 10
Poor quality transmission 61 2.26 1.059 11
Odd transmission time 61 2.26 0.984 12
Lack of interest 52 2.26 1.137 13
Table 19: Challenges faced by respondents in the use of agri. helpline
Agri. Helpline Weighted
score Mean SD Rank
Lack of education 537 3.92 0.796 1
Language (difficult) 136 3.58 1.056 2
Lack of awareness 133 3.17 0.986 3
Inadequate information 124 3.88 1.129 4
Lack of credibility of medium 109 3.63 1.402 5
Odd transmission time 108 3.60 1.354 6
High cost 105 3.50 1.432 7
Lack/poor feedback 101 3.37 1.497 8
Poor quality transmission 99 3.30 1.088 9
Lack of time (busy) 95 3.17 1.577 10
Lack of visual impact 92 3.07 1.143 11
Lack of ownership 91 3.03 1.129 12
Lack of interest 86 2.87 1.358 13
129
Table 20: Challenges faced by respondents in the use of agri. website
Agri. website Weighted
score
Mean SD Rank
Lack of education 420 3.85 0.815 1
Lack of awareness 115 3.38 1.045 2
Lack/poor feedback 109 3.30 1.159 3
Language (difficult) 107 3.24 1.091 4
Lack of interest 83 3.32 1.180 5
Lack of ownership 82 3.28 1.173 6
Lack of credibility of medium 81 3.24 1.165 7
Lack of visual impact 80 2.42 1.347 8
High cost 80 3.20 1.291 9
Odd transmission time 78 3.12 1.333 10
Poor quality transmission 76 3.04 1.241 11
Inadequate information 70 2.59 1.152 12
Lack of time (busy) 66 3.14 1.236 13
Table 21: Respondents’ skill level and training needs to use ICTs
ICT tools/
Devices
1 2 3 4 5 No
Response
f % f % f % f % f % f %
Radio/FM 19 4.75 6 1.50 72 18.00 47 11.75 41 10.25 215 53.75
TV 19 4.75 21 5.25 83 20.75 65 16.25 74 18.50 138 34.50
Mobil 25 6.25 66 16.50 55 13.75 51 12.75 70 17.50 133 33.25
Internet 14 3.50 4 1.00 45 11.25 51 12.75 14 3.50 272 68.00
Landline
Phone 23 5.75 6 1.50 7 1.75 6 1.50 6 1.50 352 88.00
Computer 21 5.25 2 0.50 12 3.00 5 1.25 2 0.50 358 89.50
Agri.
helplines 23 5.75 2 0.50 4 1.00 20 5.00 6 1.50 345 86.25
Agri.
websites 21 5.25 9 2.25 5 1.25 4 1.00 0 0.00 361 90.25
* Total skill level on scale – Possessed skill level = Required skill level/ Training needs
Example: Total skill level on scale (05) – Possessed skill level (03) = Required skill level/ Training needs (02)
130
APPENDIX # 2
Interview Schedule
Emerging Trends and Challenges in the Use of ICTs for Better Access to Agricultural Information in the
Punjab, Pakistan
Demographic characteristics of the respondents
1. District _______________
2. Tehsil _______________
3. Village name _______________
4. Name of the respondent (Optional) _______________
5. Mobile number of respondent (Optional) _______________
6. Age (years) _______________
7. Education of the respondent (years of schooling) _______________
8. Landholding capacity of the respondent (acres) _______________
I. Small (< 12.5)
II. Medium (above 12.5-25)
III. Large (>25)
9. Tenureship status
I. Owner
II. Tenant
III Owner cum Tenant
10. Sources of income
I. Farming only
II. Farming + Job
III. Farming + Business
IV. Multiple sources
11. Area under cultivation (Acres) _______________
12. Which crops you are growing, please specify?
I. Major Crops
____________________________________________________________________
____________________________________________________________________
II. Minor Crops
____________________________________________________________________
____________________________________________________________________
III. Fruits & Vegetables
131
____________________________________________________________________
____________________________________________________________________
IV. Any other
____________________________________________________________________
____________________________________________________________________
13. Which are the sources of getting agricultural information?
I. Radio/ FM
II. Television
III. Internet
IV. Mobile phone
V. Agri. websites
VI. Agri. help line
VII. News paper
VIII. Written literature from public sector
IX. literature from private sector
X. Extension worker of public sector
XI. Extension worker of private sector
XII. Fellow farmer/relatives/neighbors
Any other please specify
_____________________________________________________________________
_____________________________________________________________________
Objective 1. To explore the current use of different ICTs by the respondents
14: Which ICTs tools do you have in your possession?
ICTs Possession In possession since
Yes No
a. Radio/ FM
b. TV
c. Internet
d. Computer
e. Mobile phone
f. Fixed phone/land line phone
132
15: To what extent do you use following ICT tools and for what purpose?
Scale: 1= V. Low 2= Low 3=Medium 4=High 5= V. High X= Not using/Not applicable
ICTs Extent of use Purpose
a. Radio/FM 1 2 3 4 5 X Entertainment Information Infotainment Any
other
b. TV
c. Internet
d. Computer
e. Mobile Phone
f. Social media
g. Fixed phone/ land line
phone
h. Agri. helplines
i. Agri. websites
16: Which ICTs you are using for obtaining agricultural information and to what extent?
Scale: 1 = Never, 2 = Rarely, 3 = Sometimes, 4 = Often, 5 = Always
ICTs 1 2 3 4 5
a. Radio/FM
b. TV
c. Internet
d. Computer
e. Mobile Phone
f. Social media
g. Fixed phone/ land line phone
h. Agri. helplines
i. Agri. websites
133
Objective 2: To explore the emerging trends of ICTs regarding agricultural
information dissemination among respondents
17: Are you familiar with following ICTs services regarding agricultural information?
ICTs Familiarity
Yes No
1. Radio/FM
Khait khait haryali
Jithey terey hul wagdey
Sandhil Dharti
Wasde rain Kissan
Utum khaiti
Dharti bakhat bahar
Wasnay rehan garan
Thal Singhar
Zarkhiz Pakistan
Packages/ Short messages
Advertisements
Any other
2. TV
Haryali (PTV Home)
Zamindara (Waseeb TV)
Khaiti (Rohi TV)
Kissan time (Channel 5)
Khait Punjab day (Punjab TV)
Zarat Nama (ATV)
Dehat sudhar (Sohni Dharti)
Packages/Short messages
Advertisements
Any other
3. Internet (web based)
Agri. Web sites:
Fertilizer Calculator
e-marketing
Any other
4. Mobile (apps & helpline)
Horticulture UAF
Plant Clinic
Animal Clinic
Agricultural Business
Agriculture Corner
134
UKisaan (Helpline700)
Zong Kisan Portal (Helpline700)
Warid Kissan Line (Helpline 2244)
Bakhabar Kissan (Helpline 03030300000)
Khushal Zaminadr 7272
Facebook Pages
Any other
5. Toll free helpline
Services (public & private)
0800-15000
0800-29000
0800-78686
0800-78685
0800-54726
0800-00332
Any other
18: What kind of information you are obtaining from various ICTs and to what extent?
Scale: 1= Never, 2= Rarely, 3=Sometimes, 4=Often, 5= Always
Information 1 2 3 4 5
a. Production of major crops (wheat, cotton, rice
sugarcane etc)
b. Farm resource management
c. Plant protection measures (pest, insects and dieses
management)
d. Harvesting and post harvesting practices
e. Storage
f. Marketing of agricultural
g. New cropping scheme
h. Weather updates
i. Access to credit
j. Livestock & Poultry management
k. Any other
135
19: To what extent will you prefer to use the following ICTs in future for getting agricultural
information?
Scale: 1 = Very Low, 2 = Low, 3 = Medium, 4 = High, 5 = Very High
ICTs 1 2 3 4 5
a. Radio/FM
b. TV
c. Mobile
d. Internet
e. Computer
f. Land line Phone
g. Agri. helplines
h. Agri. websites
20: Which language will you prefer for getting agricultural information from various ICTs?
I. National language (Urdu) ________
II. Local language (______) ________
Objective 3: To assess the effectiveness of ICTs as a source of agricultural information
for the respondents
21: How would you rate the effectiveness of following ICTs and their various applications on
the basis of following aspects in providing agricultural information? Please rate on given
scale
Scale: 1 = Very low, 2 = Low, 3 = Medium, 4 = High, 5 =Very high
Aspects Extent of effectiveness
1 2 3 4 5
1. Radio/ FM
Easy to use
Easy access of information
Provide timely information
Cheaper source of information
Provide accurate information
Better communication
Improve farming skills
Better agricultural information source
Any other
2. TV
Easy to use
Easy access of information
136
Provide timely information
Cheaper source of information
Provide accurate information
Better communication
Improve farming skills
Better agricultural information source
Any other
3. Mobile phone
Easy to use
Easy access of information
Provide timely information
Cheaper source of information
Provide accurate information
Better communication
Improve farming skills
Better agricultural information source
Any other
4. Internet
Easy to use
Easy access of information
Provide timely information
Cheaper source of information
Provide accurate information
Better communication
Improve farming skills
Better agricultural information source
Any other
5. Computer
Easy to use
Easy access of information
Provide timely information
Cheaper source of information
Provide accurate information
Better communication
Improve farming skills
Better agricultural information source
Any other
6. Land line Phone
Easy to use
Easy access of information
Provide timely information
Cheaper source of information
137
Provide accurate information
Better communication
Improve farming skills
Better agricultural information source
Any other
7. Agri. helpline
Easy to use
Easy access of information
Provide timely information
Cheaper source of information
Provide accurate information
Better communication
Improve farming skills
Better agricultural information source
Any other
8. Agri. websites
Easy to use
Easy access of information
Provide timely information
Cheaper source of information
Provide accurate information
Better communication
Improve farming skills
Better agricultural information source
Any other
22: How will you rank the areas of agriculture on the basis of getting information from ICTs?
Scale: 1 = Low priority, 2 = Somewhat priority, 3 = Neutral, 4 = High priority, 5 = Very high priority X=No Response
Various areas of Agri. Information Level
1 2 3 4 5 X
Farm management
Agronomic practices (land preparation/seed,
fertilizer, irrigation etc. related practices)
Plant protection measures
Harvesting/Post harvest technology
Storage techniques
Marketing
Farm mechanization
Agri. loan schemes
Any other (please specify)
138
Objective 4. To identify the challenges faced by the respondents in the use of ICTs
23: What are the challenges you are face in the use of ICTs and to what extent?
Scale: 1 = Very low, 2= Low, 3 = Medium, 4 = High, 5= Very High
ICT Challenges Responses Extent
Radio/
FM
Yes No 1 2 3 4 5
Lack of education
Lack of awareness
Lack of interest
Lack of time (busy)
Lack of ownership
Poor quality transmission
Odd transmission time
Lack of visual impact
Lack of credibility of medium
Inadequate information
Language (difficult)
Lack/poor feedback
High Cost
Any other
TV
Lack of education
Lack of awareness
Lack of interest
Lack of time (busy)
Lack of ownership
Poor quality transmission
Odd transmission time
Lack of visual impact
Lack of credibility of medium
Inadequate information
Language (difficult)
Lack/poor feedback
High Cost
Any other
Mobile
phone
Lack of education
Lack of awareness
Lack of interest
Lack of time (busy)
Lack of ownership
Poor quality transmission
Odd transmission time
Lack of visual impact
Lack of credibility of medium
Inadequate information
Language (difficult)
139
Lack/poor feedback
High Cost
Any other
Internet
Lack of education
Lack of awareness
Lack of interest
Lack of time (busy)
Lack of ownership
Poor quality transmission
Odd transmission time
Lack of visual impact
Lack of credibility of medium
Inadequate information
Language (difficult)
Lack/poor feedback
High Cost
Any other
Computer
Lack of education
Lack of awareness
Lack of interest
Lack of time (busy)
Lack of ownership
Poor quality transmission
Odd transmission time
Lack of visual impact
Lack of credibility of medium
Inadequate information
Language (difficult)
140
Lack/poor feedback
High Cost
Any other
Landline
Phone
Lack of education
Lack of awareness
Lack of interest
Lack of time (busy)
Lack of ownership
Poor quality transmission
Odd transmission time
Lack of visual impact
Lack of credibility of medium
Inadequate information
Language (difficult)
Lack/poor feedback
High Cost
Any other
Agri.
helplines
Lack of education
Lack of awareness
Lack of interest
Lack of time (busy)
Lack of ownership
Poor quality transmission
Odd transmission time
Lack of visual impact
Lack of credibility of medium
Inadequate information
Language (difficult)
Lack/poor feedback
High Cost
Any other
Agri.
websites
Lack of education
Lack of awareness
Lack of interest
Lack of time (busy)
Lack of ownership
Poor quality transmission
Odd transmission time
Lack of visual impact
141
Lack of credibility of medium
Inadequate information
Language (difficult)
Lack/poor feedback
High Cost
Any other
Objective 5. To assess training needs of respondents regarding effective use of ICTs
24. What is your skill level in use of ICTs tools/devices? Please rate it on given scale
Scale: 1 = Poor, 2 = Fair, 3= Good, 4 = Very good, 5 = Excellent
ICT tools/ Devices Skill Level
1 2 3 4 5
Radio/FM
TV
Mobil
Internet
Computer
Landline Phone
Agri. helplines
Agri. Websites
Objective 6. To compile research-based recommendations to promote ICTs culture in
the rural areas
___________________________________________________________________________
___________________________________________________________________________
___________________________________________________________________________
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Interview Guide for Extension Field Staff Emerging Trends and Challenges in the Use of ICTs for Better Access to Agricultural Information in the
Punjab, Pakistan
Questions
1. In your view, which information sources farmers usually prefer to meet their
information needs?
_____________________________________________________________________
_____________________________________________________________________
2. Being an extension services provider, which ICT tools you are currently using to
communicate agricultural technologies among farmers of your jurisdiction?
_____________________________________________________________________
_____________________________________________________________________
3. Would you please describe the purpose of integration of ICTs that you have made in
extension services?
_____________________________________________________________________
_____________________________________________________________________
4. How do you perceive that to what extent farmers are aware of recent trends and
potential of ICTs to meet their information needs?
_____________________________________________________________________
_____________________________________________________________________
5. In your view, which ICT tool is more effective in dissemination of agricultural
information?
_____________________________________________________________________
_____________________________________________________________________
6. What is your stance on the role of government in integrating ICTs in the Department
of Agriculture (Extension)?
_____________________________________________________________________
_____________________________________________________________________
7. In your view, are ICTs impacting farmers positively?
_____________________________________________________________________
_____________________________________________________________________
Name of the respondent: ______________________________________
Designation: ______________________________________
Area of working: ______________________________________
Cell No.: ______________________________________
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