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298
THE USEFULNESS OF CELL PHONES FOR CROP FARMERS IN SELECTED
REGIONS OF BANGLADESH
Md. Mamun-ur-
Rashid a,
Md. Masud
Karim b,
Md. Muzahidul
Islam c
Md. Soad Bin
Mobarak d
a Professor; Department of Agricultural Extension & Rural
Development, Patuakhali Science and Technology University,
Dumki, Patuakhali -8602, Bangladesh
b Additional Director General; Institute of Mass Communication,
Ministry of Information, Darr-us-Salam, Dhaka-1216, Bangladesh
c Associate professor; Department of Management Studies, Patuakhali
Science and Technology University, Dumki, Patuakhali, Bangladesh
d Department of Agricultural Extension and Rural Development,
Patuakhali Science and Technology University, Dumki, Patuakhali,
Bangladesh
murashidpstu@gmail.com (Corresponding author)
Corresponding
author
ARTICLE HISTORY:
Received: 16-Sep-2019
Accepted: 26-Nov-2019
Online Available: 20-Dec-
2019
Keywords:
Usefulness,
Cell phone,
Crop farmers,
Bangladesh
ABSTRACT
This research endeavours the usefulness of cell phones for crop farmers
in selected region of Bangladesh. For adequate findings and to achieve
its purpose, structured interview schedule was adopted to collect data
from 281 randomly selected farmers and it was revealed that a little
over 60% of them found cell phones very useful, while only 5.3%
respondents found the cell phone as less useful. Based on average talk
time hours spend in the last six months, top three sources of agricultural
information were friends and relatives, distributors and middlemen, and
farmers in advanced categories. The results of the ordered logit model
showed that their usefulness was significantly determined by age, farm
size, per month call charges, and experience in using cell phones.
Higher call rates, lack of awareness and paucity of mobile-based
information sources were major bottlenecks in using cell phones for
agricultural information. The recommendations suggested therein lead
to connecting farmers with reliable and rich information sources, use of
MMS and SMS, voice call activities, providing subsidized SIM cards,
and ultimately undertake widespread campaigns for training of aged
farmers to persuade their interest towards the use of cell phones and
mobile-based information sources.
Contribution/ Originality
To the best of authors’ knowledge other researches did not consider the types of services provided to
farmers for receiving sufficient agricultural information. Moreover, this study is quite in contrast with
other researches undertaken earlier on the use of cell-phones in Bangladesh, since it considers the
concrete and appropriate usefulness, and also able to provide a holistic scenario of use of cell-phones
along with its extended and vast informative benefits to the farmers.
DOI: 10.18488/journal.1005/2019.9.2/1005.2.298.312
ISSN (P): 2304-1455/ISSN (E):2224-4433
How to cite: Md. Mamun-ur-Rashid, Md. Masud Karim, Md. Muzahidul Islam and Md. Soad Bin
Mobarak (2019). The usefulness of cell phones for crop farmers in selected regions of Bangladesh. Asian
Journal of Agriculture and Rural Development, 9(2), 298-312.
© 2019 Asian Economic and Social Society. All rights reserved.
Asian Journal of Agriculture and Rural Development
Volume 9, Issue 2 (2019): 298-312
http://www.aessweb.com/journals/5005
Asian Journal of Agriculture and Rural Development, 9(2)2019: 298-312
299
1. INTRODUCTION
Despite of apparent self-sufficiency in rice production, its yield is still considered to be very low in
Bangladesh (Shelley et al., 2016). For instance, being the fourth largest rice producer in the world,
productivity (4.42 ton/ ha) in Bangladesh is significantly lower than Vietnam (5.75 ton/ha)
although placed in the fifth position (GRiSP, 2013). Credit constraints, lack in insurance markets,
and poor infrastructure could be described as causes of some of this disparity, while a variety of
observers have pointed out the possibility that sub-optimal agricultural practices and poor
management may also be the contributors of these slackness (Jack, 2013).
There are mostly small and family operated farms amongst the more than 570 million farmers
worldwide, (Lowder et al., 2016). A similar trend is also characterized by the prevalence of small
and fragmented landholdings in the agricultural sector in Bangladesh (Haque and Jinan, 2017).
Unexpectedly, farming systems pertaining to small-holding farmers are remarkably less productive
and less profitable than their capacity for reasons encompassing the lack of access to credit and
input, and inability to withstand risks. Information and skill gaps regarding adoption of modern
technologies and management practices also contribute to productive growth and technical
efficiency (World Bank, 2007).
Since farming is gradually and progressively becoming time-critical and information-intense
business, and hence, improved information flows have positive effects on the agricultural sector
and individual producers, but gathering and distribution of information are quite difficult and
expensive activities (Milovanović, 2014). Similarly, agricultural extension system in Bangladesh is
historically suffering from many inherent problems and often unable to meet the information needs
of most farmers (Nippard, 2014; Rashid and Gao, 2016). The service is operating with limited
manpower in constraining resources. For instance, Department of Agricultural Extension (DAE) -
the largest crop extension organization - employs 14,092 field-level extension agents, where each
agent is liable and responsible to provide services to 900-2,000 farm families (Miah, 2015). In this
context, Information and Communication Technology (ICT), particularly mobile phones could be
effective medium to link farmers with necessary information. Mobile phone sector in Bangladesh
is experiencing a rapid growth from its inception since 1993. To be more precise, till March, 2019
the number of total mobile subscribers was 158.44 million, which includes almost 97.02% of the
total population standing at 163.288 million (BTRC, 2019). Not only had there been an increase in
the number of subscribers, the coverage of mobile network reached almost at its highest limits for
almost 99% residents (GlobalEconomy.com, 2019). However, successful application of cell phones
need to know the type of information, which is being sought by the farmers, various sources used
accordingly, and appropriate usefulness of mobile phones for the farmers.
1.1. Study objectives
The general objective of this research was to explore the usefulness of mobile telephony in
receiving agricultural information in the study area. However the specific objectives were:
1. To reveal the present situation of mobile use by the respondents.
2. To explore the usefulness of mobile phone for the crop farmers in the study area.
3. To identify the determinants of cell phone usefulness in the study area.
1.2. Conceptual framework
A cell phone is a portable telephone, which embraces cellular network technology to make and
receive calls. The names originated from the cell like structure of these networks (Ware, 2016). The
term cell phone is interchangeable with cellular phone or mobile phone. Usefulness, on the other
hand, is something (service or device) that represents its benefit. Usefulness is the quality of having
utility and especially practical worth or applicability. So, usefulness of mobile phone in agriculture
means the utility of mobile phone in enhancing benefit from crop production.
Asian Journal of Agriculture and Rural Development, 9(2)2019: 298-312
300
Mobile phone based information delivery assists smallholder farmers to address the economic
development challenges to deal with extreme poverty and increasing food security as well (Wyche
and Steinfield, 2016). Along with reduction of communication and information cost, cell phone
provide rural peasants with information on market, weather, transport, and agricultural techniques,
and helps to maintain contact with concerned agencies and departments (Aker, 2011). As stated by
McNamara (2009), the list of benefits of mobile phone use in extension and agricultural
development are numerous, which encompasses - increasing small-holder productivity and
incomes; turning agricultural markets more efficient and transparent; connecting poor farmers to
urban, regional, and global market; improving services and governance for the rural poor;
promoting and engaging smallholder in agricultural innovation; assisting farmers in managing a
range of risks; efficient management of land, natural resources, and environmental pressure;
enhancing participation of poor farmers in high-value agriculture; supporting the emergence of a
more diverse rural economy and assisting rural families decisions about their integration of
productive activities.. However, consulting several number of literatures (Aker, 2011; Baumüller,
2012; Bayes et al., 1999; Donner, 2006; Goggin and Clark, 2009; Goodman, 2005; Kyem et al.,
2006; Martin and Abbott, 2010; Mittal and Mehar, 2012, Singh and Issac, 2018; Qiang et al., 2011;
Vodafone Group and Accenture, 2011) around the globe a list of benefits of usefulness of cell-
phone in agriculture is displayed in Table 1.
Table 1: Usefulness of cell phone in agriculture
Area of information
Usefulness
Input related
Better input and equipment; optimum use of input; real price; less
chance of being cheated; better delivery; better environment
Financial
Quick payment; increased access to credit; better management of
bank account
Weather
Better management of climate change effect; reduction of risk;
better water management
Production
Better selection of crop varieties; efficient management of land,
irrigation, fertilizer, disease, pest, natural resources, etc.; better
harvest, processing, & storage
Market
Better market links and distribution networks; enhanced access to
markets and value chain; reduction of fraud; latest market rates
Training & Education
Better knowledge & skill; positive attitude; improved literacy
Social networking
Improved cohesion and better interpersonal relationship; enhanced
group efficiency; better mobility and security; more empowerment
Multiple social issues effect on the use of ICTs, such as literacy, socio-economic status,
willingness, as well as conditions to participate in ICT training (Manalo and Eligio, 2011).
Katengeza et al. (2011) identified literacy, distance to local market, land size, current value of
assets, crop income, and regional variations positively affect mobile use by smallholder farmers for
agricultural marketing. Demographic variables, such as age, sex, educational level, experience and
size of holdings were found influential determinants in the use of mobile phone among small-scale
poultry farmers in Ghana (Folitse et al., 2019). In Tanzania Urassa and Mvina (2016) identified
distance from home to the nearest cattle market; the variety of information demands; income earned
per year; level of local network coverage and access to mobile financial services in using cell
phones in access to beef cattle market information. Farmers’ decision to patronize mobile phone-
based weather and market information was found significantly influenced by contact with
agricultural extension agents and farmer-to-farmer extension services (Etwire et al., 2017). Factors,
such as, age and social participation was identified as influential in mobile phone use by the
farmers in receiving information on vegetable cultivation in Bangladesh (Asif et al., 2017).
Asian Journal of Agriculture and Rural Development, 9(2)2019: 298-312
301
Use of cell phone for agricultural information is often constrained by several factors. Primary
obstacle identified by most of the studies was high call charge (Asif et al., 2017; Stephane, 2017;
Warthi and Bhanotra, 2017). Several studies conducted in diversified locations also cited network
failure as a crucial constraint (Folitse et al., 2019; Navinkumar et al., 2018; Warthi and Bhanotra,
2017). Lack of electric power supply emerged as a conspicuous constrains in cell phone use in the
agriculture sector (Asif et al., 2017; Falola and Adewumi, 2012; Mukadasi, 2018; Navinkumar et
al., 2018; Warthi and Bhanotra, 2017). Other constraints limit the use of mobile phone in
agriculture identified in various studies were non-membership of agricultural society, inadequate
extension services, fluctuating telecommunication services, inadequate access to mobile services,
lack of mobile servicing centre, language barrier, lack of knowledge and confidence, complex
technology, incomplete messages, lack of locally relevant information, and high cost of mobile
phone set (Asif et al., 2017; Falola and Adewumi, 2012, Navinkumar et al., 2018; Warthi and
Bhanotra, 2017). There are also debates and issues on the mode of information delivery via mobile
phone. For instance, SMS is preferred over the voice message or vice-versa. For text SMS, there
are issues of language conversion, maintaining character constraints, compatibility of farmer’s
handset to local language, literacy of subscribers, etc. Voice message, on the other hand, have
constraints like more costly, efficiency of receiving the messages at pre-defined time is poor and
there is a cost of retrieving the information in the message (Aker, 2011; Mittal et al., 2010; Mittal,
2012).
2. METHODOLOGY
2.1. Study area
The study was carried out in Barisal division under Bangladesh. This division is situated in the
southern part of the country and bears a land area equivalent to 13,295 km2. The total number of the
population resides in Barisal is 8,173,818 and the division is renowned for rice and pulse
production. In recent years some areas of the division become advanced in vegetable production
also. People (54.72%) of this division predominantly depend upon agriculture as a major source of
income (Banglapedia, 2015).
2.2. Study approach
This study adopted a quantitative method for reaching research objectives. As stated by Creswell
(1994), quantitative research is a type of research that is explaining a phenomenon by collecting
numerical data that are analyzed using mathematically based methods (in particular statistics).
2.3. Population and sampling
This study adopted a multistage random sampling method for the selection of sample. Barisal
division is composed of six districts of which three districts (Barisal, Patuakhali, and Jhalokathi)
were purposefully selected for the study. From each of the selected districts one sub-district was
randomly selected. One union from each of the selected sub-district (Babugonj, Dumki, and
Nalchity) was selected randomly followed by the selection of two villages randomly from each of
the selected unions (Chandpasa, Angaria, and Dopdobia). Hence, the total number of selected
villages was six namely Dumki Satani, Jhatra, Chandpasa, Bailakhali, Bhorotkathi, and Jurkathi.
The farmers of these selected villages, who use a cell phone for agricultural information at least
once in the last six months, constitute the population of the study. The total number of such farmers
in the study area was 1150. Based on the sample size calculator at 95% confidence level and 5%
margin of error the required sample size was 289. Hence, this research took face-to-face interview
of 289 farmers. Due to inconsistency of information 8 interviews were dropped and finally 281
respondents constituted the sample of the study.
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2.4. Data collecting instruments
This study used a structured interview schedule as data collecting instrument. The interview
schedule was pre-tested upon forty similar respondents as considered in the study for ensuring
validity and reliability and executing necessary correction and adjustments. Test-retest method was
applied to ensure the reliability of usefulness scale. The score of test and retest showed significant
correlation which represents the reliability of usefulness scale.
2.5. Measurement of variables
Usefulness of mobile phone is the dependent variable of the study which was measured based on a
single-item 5 point rating scale (Very useful=5, Useful = 4, Moderately useful = 3, Less useful = 2,
Very less useful = 1). Usefulness can be measured based on both single and multiple items. As
usefulness holistically represents one concept, and judged to be concrete, so single item
measurement can be considered as reasonable (Sackett and Larson, 1990; Rossiter, 2002).
Nonetheless, single-item measures are flexible, easy to administer (Pomeroy et al., 2001), less time
consuming and not monotonous (Gardner et al., 1998) thus reducing response biases (Drolet and
Morrison, 2001). However, measurement techniques of other variables of the study are provided in
Appendix 1.
2.6. Statistical tests
This study used descriptive statistics like mean, median, mode, standard deviation, frequency,
range, etc., for describing the variables. However, to identify the determinants of usefulness of
mobile phone, this study deployed order logistic regression. When a criterion variable has more
than two categories and the values of each category have a meaningful sequential order i.e. a value
is higher than the previous value then an ordinal logit model can be deployed (Torres-Reyna, 2012).
The model is based on the assumption that there is a latent continuous outcome variable and the
observed ordinal outcome arises from discretizing the underlying continuum into j-ordered groups.
The thresholds estimate these cut-off values. The basic form of the generalized linear model is
Where, γj is the cumulative probability for the jth category, θj is the threshold for the jth category,
β1…….βk are the regression coefficients, x1….xk are the predictor variables, and k is the number of
predictors.
The numerator on the right side determines the location of the model. The denominator of the
equation specifies the scale. The τ1…τm are coefficients for the scale component and z1…zm are m
predictor variables for the scale component (chosen from the same set of variables as the x’s).
3. RESULTS AND DISCUSSIONS
3.1. Personal characteristics of the respondents
Participants in this study were 214 males and 67 females. Mean age of the respondents were 42.69.
In terms of educational background, almost half (46.9%) of the respondents had Secondary School
Certificate (SSC) level education. More than one third (37.7%) of the respondents were placed in
marginal farmers category. In case of objectives of farming, 89.7 percent of the respondents had
both commercial and family consumption motive, while mean annual income of the respondents
was 129.94 thousand taka. However, a detail of personal characteristics of the respondents are
presented in Table 2.
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303
Table 2: Personal characteristics of the respondents (n = 281)
Variable
Scaling
Category
Freq.
%
Mean
Med.
SD
Age
Year
42.69
40
11.37
Gender
Nominal
Male
214
76.2
Female
67
23.8
Education
Category
Primary (1-5)
105
37.4
SSC(6-10)
132
46.9
Above SSC(<10)
44
15.7
Farm size
Category
Landless
35
12.5
Marginal
106
37.7
Small
66
23.5
Medium
68
24.2
Large
6
2.1
Objective of
farming
Nominal
Commercial
3
1.1
Family consumption
26
9.3
Both
252
89.7
Annual income
‘000’ Tk*
129.94
100
118.30
Note: *The short name of currency of Bangladesh called Taka (1 USD = 83 Tk)
Source: Field Data, 2016
3.2. A profile of cell phone use by the respondents
Data arranged in Table 3 shows that 80.15% of the respondents use only one operator for mobile
telephony. On an average, respondents spend 380 Taka per month as mobile toll and majority of
them were using mobile phone for almost six years.
Table 3: Status of cell phone use by the respondents (n = 281)
Variable
Scale
Category
Freq.
%
Mean
Med.
SD
Number of
operator(s)
use
Score 1 for
each operator
One
229
80.15
Two
49
17.39
1.19
1
0.04
>2
3
1.06
Monthly
expenditure
‘00’ Taka
3.80
3
6.39
Tenure of mobile
use
Years
5.78
5.25
2.71
Source: Field Data, 2016
Mobile operators in Bangladesh cater different services for their clients. Grossly, these services
include voice call, text message, picture message, voice message, and internet service. However,
farmers’ use of these services varies abruptly. According to the data presented in Table 4, all the
respondents use the voice call service to a varying degree. Although a negligible section of the
farmers use the text message, but none of the farmers use the voice message service for receiving
agricultural information. Similar to voice message user group, a puny section of farmers uses the
internet service in the last six months. However, detail of farmer’s extent of used for different
service is presented in Table 4. Supporting to our findings, Wyche and Steinfield (2016) in their
study rural Kenya also found limited use of texting as SMS requires multiple sub-skills - in putting
letters, spaces, and symbols, and switching between upper and lower cases – which involve a
significant degree of learning, especially, when menus involve only English words. Martin and
Abbott (2010), in a study in Uganda on the use of mobile phones in agricultural development found
limited use of SMS what is supposed to be linked with a high illiteracy rate.
Asian Journal of Agriculture and Rural Development, 9(2)2019: 298-312
304
Table 4: Distribution of respondents based on extent of use of different types of services
S. No.
Type of service
Extent of use
Regular
Frequent
Occasionally
Rarely
Never
1
Voice call
166
41
56
18
0
2
Text message
0
2
1
4
274
3
Voice message
0
0
0
0
281
4
Internet
5
0
1
2
273
Note: Regular = every week; Frequent: every 15 days; occasionally = every month; rarely = every six months,
never = no use in last six months
Source: Field Data, 2016
Mobile phone operators in Bangladesh offer different kinds of service to their customers. These
services include voice call, text message, MMS, voice message, internet service, etc. Among these
services voice calls are more expensive and most transient in terms of future preservation. On the
other hand, text messages, MMS, voice message, etc. are long lasting and at the same time less
expensive. They can reach the receiver in case of his absence at the other end of the mobile phone.
Nonetheless, information received via text message, MMS, voice message, etc., can easily be
shared repeatedly with the peers at any time.
3.3. Usefulness of cell phone
As presented in Table 5 for little more than two third (35.2%) of the farmers found mobile phone
useful for receiving agricultural information, while 31.3% of the respondents found mobile phone
moderately useful. Among the rest of the respondents 28.1% found mobile phone very useful, while
rest 5.3% of the farmers identified mobile phone as less to very less useful.
Table 5: Distribution of the respondents based on the level of their mobile phone usefulness
S. No.
Level of usefulness
Frequency
Percentage
1
Very useful
79
28.1
2
Useful
99
35.2
3
Moderately useful
88
31.3
4
Less useful
11
3.9
5
Very less useful
04
1.4
Total
281
100
Source: Field Data, 2016
The following table shows the average minutes used in last six months, the top source for
agricultural information for respondents is peers and relatives. On average, farmers spent 135.85
minutes/six months with peers and relatives in agricultural information. The other dominated
source of information based on average minutes in the last six months via mobile was
distributer/middle man, advanced farmers, input dealers, NGO extension worker, public extension
worker, private company representative, and mobile company call centers. It is important to note
that a negligible proportion (2.8%) of farmers surfed website via mobile for agricultural
information. Fashina and Odefadehan (2014) also confirmed that the friends are the top ranked
agricultural information sources in the case of Ondo state of Nigeria.
Cell phone can be a very effective device for securing farm information, however, Bangladesh still
has significant room for improving the usefulness of the cell phone. If we have a critical
observation, majority of farmers mostly use less reliable sources like relatives and peers, advanced
farmers, middlemen, input dealers, etc. for getting information. Their use of reliable and rich
sources like public and private extension workers seemed to be very limited.
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305
Table 6: Use of different information sources for acquiring agricultural information (n = 281)
Information source
Use*
Freq. (%)
Mean
Med.
Std.
OR*
Rank*
Public extension officer
Yes
135(48)
18.71
0.00
40.27
0-240
6
No
146(52)
NGO extension worker
Yes
131(46.6)
25.36
0.00
58.78
0-360
5
No
150(53.4)
Seed/fertilizer/pesticide dealer
Yes
205(73)
35.61
15.0
53.73
0-240
4
No
76(27)
Private company representative
Yes
37(17.2)
6.50
0.00
42.33
0-480
7
No
244(86.8)
Advanced farmers
Yes
160(56.9)
37.26
6.0
63.69
0-480
3
No
121(43.1)
Mobile company call center
Yes
25(8.9)
2.46
0.00
18.98
0-280
8
No
256(91.1)
Distributer/middle man
Yes
137(48.8)
42.56
00
97.06
0-720
2
No
144(51.2)
Friends and relatives
Yes
217(77.2)
135.85
60.0
193.66
0-960
1
No
64(22.8)
Websites
Yes
8(2.8)
1.89
00
16.63
0-240
9
No
273(97.2)
Note: *Use in last six month; *Ranked based on mean (Minutes/6 month); *OR = Observed range
Source: Field Data, 2016
3.4. Type of information sought
Farmer sought varieties of information via mobile phone. Based on weighted mean, information
related to crop protection occupies the first position. The other crucial subjects of information
search according to rank order are fertilizer management, selection co crop varieties, marketing of
agricultural products, seed processing and treatment, etc. However, other aspects of information
search are presented in Table 7. Similar to the respondents of the study area, Kenyan farmers also
sought information about seed, fertilizers and pesticides for growing crops against bad weather
(Kashem, 2010). Studying the case of Morocco Ilahiane (2007) found that farmers exchange
marketing, weather, and business information among each other via cell phone.
Table 7: Extent of information search by the respondents (n = 281)
S. No.
Subject of information
Extent of search
WM*
Rank
OF
OC
RA
NE
1
Pest and disease control information
107
109
41
24
2.06
1
2
Fertilizer management
66
112
44
59
1.65
2
3
Selection of crop and/or vegetables species
53
94
77
57
1.50
3
4
Marketing of crop/vegetables
73
58
34
116
1.31
4
5
Seed processing and treatment
24
54
58
145
0.84
5
6
Irrigation and water management
26
35
52
168
0.71
6
7
Purchase of equipment and their use
16
21
90
154
0.64
7
8
Land preparation
16
42
45
178
0.62
8
9
Weather information
27
18
38
198
0.55
9
10
Crop/vegetable processing
12
31
56
182
0.54
10
Note: Often (OF) = Search information at least once/month, Occasionally (OC) = At least once/three months,
Rarely (RA) = Once/six months, Never (NE) = Don’t search information in last six months, *Weighted mean=
oftenX3+ ocassionallyX2+ rarelyX1+ NeverX0/ Total respondents
Source: Field Data, 2016
Asian Journal of Agriculture and Rural Development, 9(2)2019: 298-312
306
3.5. Constraints of cell phone usefulness
Farmers encountered numerous problems in using cell phone for agricultural information (Table 8).
Among the confronted problems, high call charge is placed at the top of the list. Based on weighted
mean other major problems encompass lack of awareness about mobile based information sources,
scarcity of mobile based information sources, unavailability of skilled mobile mechanic, lack of
skill in operating cell-phone, etc. Similar to this study, a research conducted in Ethiopia, Ruanda,
and Bangladesh concluded that the cost of purchasing and using mobile devices can become a
momentous deterrent to the success of mobile device system for marketing (Cho and Tobias, 2012).
Reviewing several studies, Chhachhar and Hassan (2013) claimed that there is a lack of signal of
uses of mobile phone and infrastructure in many developing countries. The lack of knowledge is
also a profound problem among rural communities and families in use of ICT. A study in Malaysia
also claimed that use level of ICT among rural community especially farmers remain low as a result
of lack of knowledge and skill (Musa, 2008).
Table 8: Problem confrontation in using mobile phone for agricultural information (n = 281)
S. No.
Problem
Incidence of problem
WM*
Rank
VH
HI
MO
LO
VL
1
High call charge
62
126
72
15
6
3.79
1
2
Unaware about mobile based
information sources
95
83
47
35
21
3.77
2
3
Paucity of mobile based information
sources
65
91
73
29
23
3.52
3
4
Scarcity of skilled mobile mechanic
48
70
95
47
21
3.27
4
5
Lack of skill in operating cell phone
52
83
60
45
41
3.21
5
6
Weak network
54
56
78
60
33
3.13
6
7
Don’t find relevant information
61
48
72
59
41
3.10
7
8
Balance shortage during phone call
31
53
90
80
27
2.93
8
9
High price of mobile handset
6
36
151
72
16
2.80
9
10
Inadequacy of electricity for mobile
charging
49
38
57
61
76
2.72
10
*Weighted Mean = Very high (VH)X5 + High (HI)X4 + Moderate (MO)X3 + Low(LO)X2 + Very low
(VL)X1/ Total respondents
Source: Field Data, 2016
Bangladesh is one of the resource poor populous countries in south Asia. Contrasting other sectors,
cell phone sector is experiencing a rapid progress in last one and half decades. Cell phone can
improve proximity between service providers and clients which can enhance better farmer access to
quality information. Deplorably, mobile based information service for agricultural development in
Bangladesh is still minimal. Grossly, none of the important extension service provider either public
or private do not have well-structured sustainable communication with farmers via cell phone.
3.6. Ways to improve cell phone usefulness
Bangladesh is one of the top countries experiencing massive growth of the mobile network.
Common improvement of customer service may not be fully useful for improving farmer access to
agricultural information as most of the farmers in Bangladesh are subsistence farmers and don’t
have enough money to invest for cell phone based information collection. According to the
respondents reduction of call toll and strengthening cell phone network can certainly increase
farmers’ access to mobile based agricultural service. However, a detail of suggestions proposed by
the respondents for improving cell phone usefulness is displayed in Table 9.
Asian Journal of Agriculture and Rural Development, 9(2)2019: 298-312
307
Table 9: Suggestions for improving usefulness of mobile phone
S. No.
Suggestions
Frequency
1
Reduction of mobile call charge
189
2
Strengthening mobile network facilities
100
3
Toll free facilities for agricultural calls
33
4
Training for developing mobile operating skill
28
5
Inspiring farmers in using mobile based information sources
26
6
Ensuring accuracy of information
24
7
Ensuring regular supply of electricity
21
8
Increasing number of mobile based information sources
20
9
Reducing price of mobile phone set
20
10
Supplying need based easily understandable information
19
Note: Respondents enjoyed the opportunity of providing more than one suggestions
Source: Field Data, 2016
3.7. Determinants of mobile usefulness
This study used ordered logistic model to reveal the determinants of usefulness of mobile phone for
retrieving agricultural information. In the process of analysis, different models were run combining
explanatory variables to find out the most suitable combination. Model 1 can best explain the
usefulness of the cell phone with the highest number of explanatory variables at lower p value than
Model 2. OLM results presented in Table 10 show that among the selected variables age, farm size,
experience in mobile use, mobile expenditure per month, etc., have significant association with the
usefulness of the cell phone. It is important to note that age has a negative contribution on farmer
usefulness of mobile phone i.e. probability of usefulness of cell phone decreased with the increase
of farmers’ age. In line with our findings Nyamba and Mlozi (2012) also found age as a variable
significantly negatively associated with cell phone use in the case of Tanzania.
Table 10: Contribution of different selected variables on the farmers’ usefulness of mobile
phone (n = 281)
Xi
Model 1
Model 2
β
SE
Z
p> |z|
β
SE
Z
p> |z|
Age
-0.0242
0.010
-2.422
0.015
-0.022
0.009
-2.296
0.021
Education
0.0360
0.042
-0.853
0.393
Annual income
-0.0008
0.001
0.782
0.433
Objectives of
farming
0.3346
0.354
0.943
0.345
Farm size
0.3701
0.122
3.017
0.002
0.324
0.112
2.881
0.004
Length of mobile use
0.1244
0.046
2.654
0.008
0.116
0.044
2.608
0.009
Mobile
expenditure/month
0.1066
0.052
2.037
0.041
0.111
0.051
2.143
0.032
Frequency of mobile
use
0.0003
0.0004
0.805
0.420
Extent of information
search
0.0316
0.0178
1.778
.0766
0.031
0.017
1.842
0.065
Yi= Usefulness of
mobile phone
(Ordered*)
LL=-334.37, LR static = 45.390,
p>LR= 0.000001, Pseudo R2= 0.0635
LL=-335.68, LR static = 42.77,
p>LR= 0.00000, Pseudo R2=
0.0598
*Ordered (5: Very useful, 4: useful, 3: moderate, 2: less useful, 1: very less useful)
Source: Field Data, 2016
Asian Journal of Agriculture and Rural Development, 9(2)2019: 298-312
308
In Bangladesh, most of the farm families are either marginal or small, possessed a very small piece
of land. Eventually, they are not well off to spend much money as mobile toll. Mobile operators in
Bangladesh have almost similar call rate. They also have different low call charge packages but
inured with so many rules and regulation that can’t easily be understood by an ordinary client like
farmer. In Bangladesh a major section of the farmers are aged and illiterate. Progress in agricultural
can’t be achieved without incorporating this section with modern information communication
technology like a cell phone. Negative association between age and usefulness can be explained
from a different angle. Firstly, aged farmers are normally less innovative and have less interest in
modern information communication media. Secondly, they are interested but don’t know how to
secure information via cell phone.
4. CONCLUSION & RECOMMENDATIONS
The findings of this research revealed that a large section of farmers in Bangladesh found mobile
phones from useful to very useful for the various crops farming. Deplorably, farmers predominantly
used less reliable and less efficient informal sources, such as friends, relatives, dealers, etc., for
accumulating various crop farming information. The respondents mostly sought information about
crop diseases and pest control followed by fertilizer management suggestions, selection of
appropriate crops and/or adequate vegetable species, and crop marketing related information.
Despite the availability of low-cost services, such as SMS, MMS, voice message, etc., the peasants
mostly used high costs in voice call service. Major deterrents of using a cell phone for crop related
information were high call rates, lack of awareness about mobile based information sources,
scarcity of mobile based information sources, and lack of skills among farmers in operating mobile
phones. However, in light of the findings of this research, recommendations are being proposed to
enhance the usefulness of mobile phones for crop farmers.
1. It is essential to link farmers with rich and reliable agricultural information sources, such as
public extension services, NGOs’ extension service, etc.
2. At present the respondents are predominantly using voice call service which is expensive and
short-lived. It is therefore essentially necessary to engage farmers with other comparatively
cheap services, such as SMS, MMS, and voice message, etc., so that they can store, share and
use information repeatedly.
3. To provide relief in mobile expenditure burden and assist in enhanced use of cell phones for
crops production, special kind of SIM with subsidized call rate should be supplied to them.
4. Aged farmers are less inclined to use mobile based agricultural information sources. It is
therefore necessary to launch widespread awareness campaigns for their training for keen
interest and to connect them with mobile phone based information sources.
Funding: This study received no specific financial support.
Competing Interests: The authors declared that they have no conflict of interests.
Contributors/Acknowledgement: All authors participated equally in designing and estimation of current
research.
Views and opinions expressed in this study are the views and opinions of the authors, Asian Journal of
Agriculture and Rural Development shall not be responsible or answerable for any loss, damage or liability
etc. caused in relation to/arising out of the use of the content.
References
Aker, J. C. (2011). Dial ‘A’ for agriculture: using information and communication technologies for
agricultural extension in developing countries. Washington D.C.: Center for Global
Development.
Asian Journal of Agriculture and Rural Development, 9(2)2019: 298-312
309
Asif, A. S., Uddin, M. N., Dev, D. S., & Miah, M. A. M. (2017). Factors affecting mobile phone
usage by the farmers in receiving information on vegetable cultivation in Bangladesh.
Journal of Agricultural Informatics, 8(2), 33-43.
Banglapedia (2015). Barisal division. Retrieved from
http://en.banglapedia.org/index.php?title=Barisal_Division
Baumüller, H. (2012). Facilitating agricultural technology adoption among the poor: The role of
service delivery through mobile phones. Working paper series 93. Center for Development
Research, University Bonn.
Bayes, A., von Braun, J., & Akhter, R. (1999). Village pay phones and poverty reduction: insights
from a Grameen Bank initiative in Bangladesh. ZEF discussion Papers on Development
Policy No. 8, Centre for development Research, Bonn.
BTRC. (2019). The total number of Mobile Phone subscribers has reached 159.780 Million at the
end of March, 2019. Retrieved from: http://www.btrc.gov.bd/content/mobile-phone-
subscribers-bangladesh-march-2019.
Chhachhar, A. R., & Hassan, M. S. (2013). The use of mobile phone among farmers for agriculture
development. International Journal of Scientific Research, 2(6), 95-98.
Cho, K. M., & Tobias, D. J. (2012). Importance of mobile technology in food and agribusiness
value chains: electronically linking farmers with markets. Conference on International
Research on Food Security, Natural Resource Management and Rural Development, 19-20
September 2012, Tropentag, Göttingen, Germany. Retrieved from:
http://www.tropentag.de/2012/abstracts/full/28.pdf.
Creswell, J. W. (1994). Research design: qualitative and quantitative approaches. SAGE
Publications, Thousand Oaks, CA.
Donner, J. (2006). The social and economic implications of mobile telephony in Rwanda: An
ownership/access typology. Knowledge, Technology & Policy, 19(2), 17-28.
Drolet, A. L., & Donald, G. M. (2001). Do we really need multiple-item measures in service
research?. Journal of Service Research, 3(February), 196–204.
Etwire, P. M., Buah, S., Ouédraogo, M., Zougmoré, R., Patey, S. T., Martey, E., & Bayala, J.
(2017). An assessment of mobile phone-based dissemination of weather and market
information in the Upper West Region of Ghana. Agric & Food Secur., 6(8).
doi:10.1186/s40066-016-0088-y.
Falola, A., & Adewumi, M. O. (2012). Constraints to use of mobile telephony for agricultural
production in Ondo State, Nigeria. Journal of Research in Forestry Wildlife and
Environment, 4(2), 52-63.
Fashina, O. O., & Odefadehan, O. O. (2014). An enquiry into the prospects of mobile telephone for
agricultural information delivery in Ondo state, Nigeria. South African Journal of
Agricultural Extension, 42, 1-14.
Folitse, B. Y., Manteaw, S. A., Dzandu, L. P., Obeng-Koranteng, G., & Bekoe, S. (2019). The
determinants of mobile-phone usage among small-scale poultry farmers in Ghana.
Information Development, 35(4), 564-574. doi:
https://doi.org/10.1177/0266666918772005.
Gardner, D. G., Cummings, L. L., Dunham, R. B., & Pierce, J. L. (1998). Single-item versus
multiple-item measurement scales: an empirical comparison. Educational and
Psychological Measurement, 58(6), 898-915.
GlobalEconomy.com. (2019). Bangladesh: Mobile network coverage (measure: percent; Source:
International Telecommunication Union). Retrieved from :
https://www.theglobaleconomy.com/Bangladesh/Mobile_network_coverage/.
Goggin, G., & Clark, J. (2009). Mobile phones and community development: A contact zone
between media and citizenship. Development in Practice, 19(4-5), 585-597. doi:
10.1080/09614520902866371.
Goodman, J. (2005). Linking mobile phone ownership and use to social capital in rural South
Africa and Tanzania. Vodafone Policy Paper Series, Number 2.
Asian Journal of Agriculture and Rural Development, 9(2)2019: 298-312
310
GRiSP (Global Rice Science Partnership). (2013). Rice almanac. 4th edition. Los Baños
(Philippines): International Rice Research Institute. Retrieved from:
http://ricepedia.org/rice-around-the-world/asia.
Haque, Z., & Jinan, T. (2017). Impact of land tenure system on socio-economic characteristics in
selected areas of mymensingh. J. Environ. Sci. & Natural Resources, 10(2), 133–142.
Ilahiane, H. (2007). Impacts of information and communication technologies in agriculture:
farmers and cell phones in Morocco. Presented at the American Anthropological
Association Conference, Washington, D.C. Retrieved from http://www.fao.org/e-
agriculture/forumtopics/impacts-icts-agriculture-farmers-and-mobile-phones-morocco.
Jack, B. K. (2013). Constraints on the adoption of agricultural technologies in developing
countries. Literature review, Agricultural Technology Adoption Initiative, J-PAL (MIT)
and CEGA (UC Berkeley).
Kashem, M. (2010). Farmers’ use of mobile phones in receiving agricultural information towards
agricultural development. In Proceedings of the 2nd International Conference on M4D
Mobile Communication Technology for Development, Kampala, Uganda.
Katengeza, S. P., Okello, J. J., & Jambo, N. (2011). Use of mobile phone technology in agricultural
marketing: the case of smallholder farmers in Malawi. International Journal of ICT
Research and Development in Africa, 2(2), 14-25.
Kyem, K., Kweku, P. A., & Le Maire, P. (2006). Transforming recent gains in the digital divide
into digital opportunities: Africa and the boom in mobile phone. Electronic Journal of
Information Systems in Developing Countries, 28(5), 1-16. Retrieved from
https://onlinelibrary.wiley.com/doi/epdf/10.1002/j.1681-4835.2006.tb00189.x
Lowder, S. K., Skoet, J., & Raney, T. (2016). The number, size, and distribution of farms,
smallholder farms, and family farms worldwide. World Development, 87, 16-29.
Manalo, J., & Eligio, A. (2011). Making ICT initiatives more relevant: creating spaces for farmers’
participation in ICT policies in the Philippines. In the proceedings of the CPR South 6th
Conference in Bangkok, Thailand.
Martin, B., & Abbott, E. (2010). Development calling: the use of mobile phones in agriculture
development in Uganda. Greenlee School of Journalism and Communication, Iowa State
University.
McNamara, K. (2009). Mobile applications in agriculture and rural development framing the
Topic, and learning from experience. World Bank Workshop on Mobile Innovations for
Social and Economic Transformation. Retrieved from
http://siteresources.worldbank.org/EXTEDEVELOPMENT/Resources/Slides_McNamara
_revised.pptx.
Miah, H. (2015). Agriculture sector development strategy: background paper for preparation of the
7th five year plan. Bangladesh: Food and Agriculture Organization.
Milovanović, S. (2014). The role and potential of information technology in agricultural
improvement. Economics of Agriculture, 61(2), 471-485.
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).
Mittal, S., Gandhi, S., & Tripathi. G. (2010). Socio-economic impact of mobile phones on Indian
agriculture. Working paper 246. Indian Council for Research on International Economic
Relations. Retrieved from http://www.icrier.org/pdf/WorkingPaper246.pdf.
Mittal, S., & Mehar, M. (2012). How mobile phones contribute to growth of small farmers?
evidence from India. Quarterly Journal of International Agriculture, 51(3), 1-18.
Mukadasi, B. (2018). Mixed cropping systems for sustainable domestic food supply of the
smallholder farming communities in Nakasongola District, Central Uganda. Canadian
Journal of Agriculture and Crops, 3(1), 42-54.
Musa, A. H. (2008). Benefiting ICT for all. Inaugural Lecture Series. Serdang: UPM Publisher.
Asian Journal of Agriculture and Rural Development, 9(2)2019: 298-312
311
Navinkumar, B., Dhananjaya, H. M., & Ranjeeth, T. H. (2018). Constraints faced by the farmers in
using mobile agro-advisory services. International Journal of Current Microbiology and
Applied Sciences, Special Issue-6, 2885-2890.
Nippard, D. (2014). Improving public agricultural extension services in Bangladesh using the M4P
approach. The KATALYST Case Study no.7. Retrieved from:
http://katalyst.com.bd/docs/case_studies/Katalyst_case_study-7.pdf.
Nyamba, S. Y., & Mlozi, M. R. S. (2012). Factors influencing the use of mobile phones in
communicating agricultural information: A case of Kilolo District, Iringa, Tanzania.
International Journal of Information and Communication Technology Research, 2(7),
558-563.
Torres-Reyna, O. (2012). Getting Started in logit and ordered logit regression. Princeton
University. Retrieved from https://www.princeton.edu/~otorres/Logit.pdf.
Pomeroy, I. M., Clark, C. R. & Ian, P. (2001). The effectiveness of very short scales for depressions
screening in elderly medical patients. International Journal of Geriatric Psychiatry, 16(3),
321–326.
Qiang, C. Z., Kuek, S. C., Dymond, A., & Esselaar, S. (2011). Mobile applications for agriculture
and rural development. ICT Sector Unit, World Bank. Retrieved from
http://siteresources.worldbank.org/INFORMATIONANDCOMMUNICATIONANDTEC
HNOLOGIES/Resources/MobileApplications_for_ARD.pdf.
Rashid, M. M., & Gao, Q. (2016). An assessment of public and private crop extension services in
Bangladesh, IOSR Journal of Agriculture and Veterinary Science, 9(1), 7-16. doi:
10.9790/2380-09120716.
Rossiter, J. R. (2002). The C-OAR-SE procedure for scale development in marketing. International
Journal of Research in Marketing, 19(4), 305–335.
Sackett, P. R., & Larson, J. R. (1990). Research strategies and tactics in industrial and
organizational psychology. In M. D. Dunnette & L. M. Hough (Eds.), Hand-book of
industrial and organizational psychology (pp.419-489). Palo Alto, CA: Consulting
Psychologists Press.
Shelley, I. J., Takahashi-Nosaka, M., Kano-Nakata, M., Haque Mohammad S., & Inukai, Y. (2016).
Rice Cultivation in Bangladesh: Present Scenario, Problems, and Prospects. Journal of
International Cooperation for Agricultural Development, 14, 20-29.
Singh, A. K., & Issac, J. (2018). Impact of climatic and non-climatic factors on sustainable
livelihood security in Gujarat state of India: A statistical exploration. Agriculture and
Food Sciences Research, 5(1), 30-46.
Stephane, N. Y. (2017). Use of mobile phone in rural area for agriculture development. Retrieved
from http://www.fao.org/e-agriculture/blog/use-mobile-phone-rural-area-agriculture-
development.
Urassa, N. S., & Mvena, Z. S. K. (2016). Determinants of the use of cell phones in access to beef
cattle market information for smallholders in Mpwapwa District, Tanzania. Huria:
Journal of the Open University of Tanzania, 22(1), 116-131.
Vodafone Group & Accenture (2011). Mobile communications to transform smallholding farmers’
livelihoods in emerging markets. London: Vodafone Group and Accenture.
Ware, R. (2016). What is cell phone? Retrieved from https://www.lifewire.com/what-is-a-cell-
phone-577492.
Warthi, M., & Bhanotra, A. (2017). Benefits and constraints of mobile phone use as an ict tool by
dairy entrepreneurs. Journal of Animal Research, 7(6), 1089-1092. doi: 10.5958/2277-
940X.2017.00162.0.
World Bank (2007). Agriculture for development. World Development Report 2008.The
International Bank for Reconstruction and Development/World Bank, Washington, DC.
Wyche, S., & Steinfield, C. (2016). Why don't farmers use cell phones to access market prices?
technology affordances and barriers to market information services adoption in rural
Kenya. Information Technology for Development, 22(2), 320-333, doi:
10.1080/02681102.2015.1048184.
Asian Journal of Agriculture and Rural Development, 9(2)2019: 298-312
312
Appendix
Appendix 1: Measurement and coding of the variables of the study
Var.
no.
Variable Name
Coding system
Level of
Measurement
1
Age
Score 1 for each year
Scale
2
Gender
1= Male, 0= Female
Nominal
3
Education
Score 1 for each year of schooling
Scale
4
Annual income
Score 1 for each thousand Taka*
Scale
5
Objective of farming
1= Commercial, 2= Family
consumption, 3= Both
Nominal
6
Farm size
1= Landless farmer, 2= Marginal
farmer, 3= Small farmer, 4=
Medium farmer, 5= Large farmer
Ordinal
7
Length of mobile use
Total number of months/12
scale
8
Mobile expenditure per month
Score 1 for each 100 Taka
scale
9
Number of mobile operators used
Score 1 for each operator
scale
10
Frequency of mobile use for
agricultural purposes
Minutes/ six months
( Against 8 selected sources of
information)
Scale
11
Extent of information search
Scoring against 13 selected
information subject (3= Very
often, 2= often, 1= seldom,
0=never )
Scale
12
Problem confrontation in using
mobile for information
Scoring against 11 selected
problems ( 5= very high, 4= high,
3=moderate, 2=low, 1=very low
Scale
13
Usefulness of mobile phone
5= Very useful, 4= useful,
3=moderately useful, 2= less
useful, 1= very less useful
Ordinal
Note: *Taka is the national currency of Bangladesh (1$ = 83 Taka
