Problems faced by farmers in application of e-Agriculture in Bangladesh

Problems faced by farmers in application of e-Agriculture in Bangladesh
JAERD
Problems faced by farmers in application of e-
Agriculture in Bangladesh
Sheikh Mohammed Mamur Rashid1*
and Md. Rezwan Islam2
1*
Department of Agricultural Extension and Information System, Sher-e-Bangla Agricultural University, Dhaka,
Bangladesh
2
Department of Finance, University of Dhaka, Bangladesh
The purpose of this research was to identify the obstacles that Bangladeshi farmers
encountered while using e-Agriculture services. Primary data were collected in Bhatbour
Block of Dhighi union under Sadar Upazila of Minikganj District where the local government
had been implementing the e-Agriculture pilot project since 2011. Data were collected from 1
September, 2015 to 30 September, 2015. Descriptive statistics, multiple regression (B)
method were used for analysis. Findings discovered that lack of knowledge on e-Agriculture
was the major problem that affected the farmers in the study area. In addition to that, the
study also revealed that education, participation in training, usages of e-Agriculture, attitude
towards e-Agriculture and availability of e-Agriculture had significant contribution towards
the problems faced by farmers’ in using e-Agriculture. These variables accounted for 65.8
percent of the problems faced by farmers’ in using e-Agriculture. Based on these findings,
the researchers suggest that government should implement integrated marketing
communication using the popular print and electronic media so that awareness about the
service will reach majority of the population more and more people get aware of this service.
In addition to that, the researchers recommend that the NGO’s and local government bodies
should create awareness to the farmers via organization of local seminars and training
programs on availability and usefulness of e-Agriculture service.
Key words: e-Agriculture, problem, usages of ICTs, farmers, agricultural development
INTRODUCTION
E-Agriculture as an emerging field in the intersection of
agricultural informatics, agricultural development and
entrepreneurship to agricultural services, technology
dissemination and information delivered or enhanced
through the Internet and related technologies (FAO,
2005). The application of e-Agriculture is still in its
elementary stage, evolving around the immense
multiplier impact capability that can significantly change
the farmer’s economic and social condition i.e.
empowerment. This ensures the effective and efficient
use of information and communication technologies for
analyzing, designing and implementing existing and
innovative applications to help the agricultural sector.
In 2008, Bangladesh Institute of ICT in Development
(BIID), in collaboration with Katalyst (Partner of Swiss
Contact and a local agro-based NGO) and
Grameenphone launched the e-krishok initiative (New
Agriculturist, 2015). The purpose of this project was to
lessen the information inadequacy in the agriculture
sector and keep farmers abreast with up-to-date
knowledge and advisory services which they often
required. After that, Bangladesh government came up
with the idea of “Digital Bangladesh” with a vision to
leverage the power of ICT in each and every public
sector and service Keeping that in mind, therefore, this
idea to measure the problems faced by the farmers in
using e-Agriculture was studied with the aim of
investigating whether to find out whether the initial
wave of e-Agriculture attempts made some productive
impacts or not.
*Corresponding Author: Sheikh Mohammed Mamur
Rashid, Department of Agricultural Extension and
Information System, Sher-e-Bangla Agricultural
University, Dhaka, Bangladesh. Email:
smm_rashid@hotmail.com
Journal of Agricultural Economics and Rural Development
Vol. 3(1), pp. 079-084, May, 2016. © www.premierpublishers.org, ISSN: 2167-0477
Research Article

Rashid and Islam 079
LITERATURE REVIEW
The concept of e-Agriculture is still in the nascent stage
in Bangladesh context, so does it in the academic
arena. In 2003, under the “Support to ICT” taskforce
program the ministry of agriculture of Bangladesh did
set up an agricultural information system (MoA, 2003).
In 2005, a group of researchers of D.Net (Development
Research Network, Bangladesh) proposed the idea of
“Pallitathya Help Center” and conducted a project on it.
The idea centered on the use of relatively less
fashionable ICT, the mobile phone, as an effective 'last
mile solution' to improve access to livelihood
information for the rural people. They found it most
challenging to understand the problems (related to
health, agricultural, weather information) of rural people
and to provide the appropriate information (Raihan et.
al, 2005). Lwoga (2010) reported language barrier as a
constrain to better dissemination of agricultural
knowledge through community radio to the local
communities and thereby the improvement of
agricultural activities of the farmers was constrained by
language restriction. Chilimo (2008) revealed that a
number of problems in using ICT media like telecenters
and rural radio in dissemination of Information and
knowledge for sustainable agricultural practices in
Tanzania constrained the farmers from meeting their
information need which specially included high cost of
ICTs, illiteracy, distance to telecenter, language barrier,
lack of electricity, frequent power outage, sustainability
issues and lack of awareness of most of the telecenter
managers about the farmers’ information needs.
Mwakaje (2010) reported that the spread of ICT
technology among the farmers were hindered by a
number of factors namely cost, availability, knowledge
and reliability. Another problem namely lack of electric
power in many rural areas was a militating factor in the
spreading of ICT among Farmers. Hassan et al. (2009)
Identified five main problems in their study that less
affect entrepreneurs, who were more exposed to ICT
usage and courses. Wolf (2001) reported that extent of
using new ICT facilities were influenced by the cost and
availability of telecommunications. United Republic of
Tanzania (2005) stated that there were many factors,
namely high cost of ICT services in rural locations
compared to urban locations, low literacy rates, low
incomes and limited number of service providers,
inappropriate legal and regulatory framework for the
expanding market, inadequate telecom infrastructure
and ICT expertise which came to the low use of
Internet. Since this idea is brand new, this researcher
came across few literatures which made little
quantitative attempts in measuring the problems faced
by farmers’ in the use of e-agriculture. So, that literature
has provided indication to measure the problem faced
by the farmers in application of e-Agriculture at first of
its kind in Bangladeshi context.
MATERIALS AND METHODS
Data Collection and Sampling Methodology
The researcher applied purposive sampling technique
to determine the location form where the data were
collected. The study was conducted at the Bhatbour
block of Dighi union under Manikganj Sadar Upazila,
Manikganj (One of the major districts of Bangladesh)
where the government of Bangladesh has been
implementing a numbers of e-Agriculture related
development projects with the help of foreign aids
through Department of Agricultural Extension (DAE).
For the purpose of this study, the farmers (within this
block) those who used e-Agriculture were considered
as the study group and the farmers who did not use
such (within this block) were considered as the control
group. According to the DAE database, in this area,
approximately 1148 farmers used e-Agricultural
facilities. To determine the sample size out of these
1148 study group farmers, the researcher used
Yamane’s (1967) formula:
n=
Where, n = Sample size; N= Population size = 1148; e
= The level of precision = 8%; z = the value of the
standard normal variable given the chosen confidence
level (e.g., z = 1.96 with a confidence level of 95 %)
and P= The proportion or degree of variability = 50%.
According to the formula, the desired sample size (n)
was = 133.
A reserve list was maintained to fill in the gaps if any
respondent in the original list was found missing as the
same respondent in two interviews (in September,
2015). To ensure the same respondents for the two
phase interviews, 5% extra respondents were
interviewed during the interview period. The definitions
of the variables measured are shown in Table 1 and 2.
Measurement of Problems Faced by the Farmers in
Using e-Agriculture
Thirteen problems were selected by the researchers’
rough consultant with the experts. The respondents
were asked to show their responses as “not at all”, low,
medium, high, and very high against each problem
according to their extent of problem faced in using e-
Agriculture. The weighted score of the five responses
was assigned as 0, 1, 2, 3, and 4 respectively. The
definitions of the variables which were exercised to
measure the problems faced by the farmers in using e-
Agriculture are shown in Table 3.
Measurement of Problem Faced Index (PFI)
The Problem Faced Index (PFI) of each of the 10
problems was measured using the following formula:
PFI= 4×fv + 3×fh + 2×fm + 1×fl + 0×fn
Where,
fv= Number of respondents who faced very high
problem
fh= Number of respondents who faced high problem

J. Agricul. Econ. Rural Devel. 080
Table 1. Variable measurement techniques
Category Scoring system
Age 1 for each complete year of age of the respondent
Education 1 for each year of school education
Effective farm size 1 for each decimal area of land
Annual household
income
1 for each “thousand BDT” income in a year
Farming experience 1 for each year experience
Participation in
training
1 for each day training
Agricultural
Knowledge
1 for each question’s correct answer and “0” for wrong answer
Usages of
e-Agriculture
Extent of Uses
4 for
frequently
3 for
regularly
2 for occasionally 1 for rarely
O for
not at all
Attitude towards e-
Agriculture
Extent of Opinion
(+2) for
strongly
agree
(+1) for
agree
(0) for undecided (-1) for disagree
(-2) for strongly
disagree
Organizational
Participation
Nature of participation (years)
4 for
President/
3 for
secretary
2 for
executive
member
1 for ordinary
member
0 for
no participation
Cosmopoliteness
Places of visiting (years)
4 for
frequently
3 for
regularly
O for
not at all
Availability of
e-Agriculture
Availability score
4 for
frequently
3 for
regularly
O for
not at all
fm= Number of respondents who faced medium problem
fl= Number of respondents who faced low problem
fn= Number of respondents who faced no problem at all
In order to make comparison among the problems, a
rank order of problems were constructed in descending
order. PFI ranged from 0 to 532, where 0 indicated no
problem at all and 532 indicated very high problem
faced.
Statistical analysis
Data collected from the respondents were analyzed
and interpreted in accordance with the objectives of the
study. The analysis of data was performed using
statistical treatment with SPSS (Statistical Package for
Social Sciences) computer program, version 20.
Statistical measures as a number, range, mean,
standard deviation were used in describing the
variables whenever applicable. In order to estimate the
contribution of the selected characteristics of farmers in
empowering them through e-Agriculture, step-wise
multiple regression analysis (B) analysis was used.
Throughout the study, five percent (0.05) level of
significance was used as the basis for rejecting any null
hypothesis. If the computed value of (B) was equal to or
greater than the designated level of significance (p), the
null hypothesis was rejected and it was concluded that
there was a significant contribution between the
concerned variable. Whenever the computed value of
(B) was found to be smaller at the designated level of
significance (p), the null hypothesis could not be
rejected. The model used for this analysis can be rejected.
The model used for this analysis can be explained as
follows:
Y = a + b1x1 + b2x2 + b3x3 + b4x4 + b5x5 + b6x6 + b7x7 +
b8x8 + b9x9 + b10x10+ b11x11 + b12x12+e;

Table 2. Problems faced by farmers in using e-Agriculture measurement technique
Problems Extent of problem
Not at
all(0)
Low(1) Medium
(2)
High (3) Very
High (4)
Apathy towards new technology
Expensive to use
Lack of knowledge on e-Agriculture
Inadequate government digital service
centers & facilities
Inadequate ICT Experts
Inadequate number of e-agriculture
related programs in electronic media
Lack of awareness towards benefits of
ICT in Agriculture
Lack of relevant customized content
Lack of Training
Lower Internet Speed
Miserable electricity connections
Quality of Information
User-friendliness of the technology
Where, Y= Problems faced by farmers in using e-
Agriculture,
Of the independent variables, x1 is the respondent’s
age, x2 is education, x3 is farm size, x4 is annual
household income, x5 is farming experience, x6 is
participation in training, x7 is agricultural knowledge, x8
usages of e-Agriculture, x9 is the attitude towards e-
Agriculture, x10 is organizational participation, x11 is
cosmopoliteness, x12 is the availability of e-Agriculture.
b1, b2, b3, b4, b5, b6, b7, b8, b9, b10, b11 and b12 are
regression coefficients of the corresponding
independent variables, and e is random error, which is
normally and independently distributed with zero mean
and constant variance.
RESULTS AND DISCUSSION
Problem Faced Index (PFI)
On the basis of PFI it was observed that Lack of
knowledge on e-Agriculture ranked first followed by
Inadequate government digital service centers and
facilities, Lower Internet Speed, Quality of Information,
Inadequate ICT Experts, Lack of awareness towards
benefits of ICT in Agriculture, User-friendliness of the
technology, Expensive to use, Apathy towards new
technology, Lack of Training, Inadequate number of e-
agriculture related programs in electronic media,
Miserable electricity connections and Lack of relevant
customized content respectively.
So far, the study discovered two aspects of problems:1)
to measure the problems faced by the farmers in using
e-Agriculture 2) the factors which changed significantly
due to the problems faced by the farmers in using e-
Agriculture of the study group. In the next segment of
the study, analysis was carried forward to identify the
significantly contributing factors regarding the problems
faced by the farmers in using e-Agriculture
Variables related for the problem faced by farmers’
in using e-Agriculture
In order to estimate the problems faced by the farmers
in using e-Agriculture from the independent variables,
multiple regression analysis was used which is shown
in the table 4.
Results in Table 4 indicate these variables (age, farm
size, annual household income, farming experience,
agricultural knowledge, organizational participation,
cosmopoliteness,) do not influence problems faced by
farmers’ in the use of e-Agriculture.
However, factors such as education, participation in
training program, usages of e-Agriculture, attitude
towards e-Agriculture and availability of e-Agriculture

Table 3. Rank order of the problems faced by farmers in using e-Agriculture
Problems Extent of problem PFI Rank
Order
Not at
all(0)
Low (1) Medium
(2)
High
(3)
Very High
(4)
Lack of knowledge on e-Agriculture 0 17 25 19 72 412 1
Inadequate government digital
service centers & facilities
0 15 16 48 54 407 2
Lower Internet Speed 0 13 19 52 49 403 3
Quality of Information 0 27 20 41 45 370 4
Inadequate ICT Experts 8 36 35 32 30 322 5
Lack of awareness towards benefits
of ICT in Agriculture
11 34 29 26 33 302 6
User-friendliness of the technology 13 38 26 24 32 290 7
Expensive to use 14 33 29 30 27 289 8
Apathy towards new technology 10 39 27 35 22 286 9
Lack of Training 18 48 32 17 18 235 10
Inadequate number of e-agriculture
related programs in electronic media
21 42 36 21 13 229 11
Miserable electricity connections 19 47 34 22 11 225 12
Lack of relevant customized content 26 43 39 16 9 205 13
significantly influenced the problems faced by farmers
in the use of e-agriculture as evident by the significance
of the estimated coefficient at probability level ranging
from 5 percent to 1 percent levels.
The R
2
value of 67.1 percent implies that the variation
in the problems faced by the farmers’ in the use of e-
Agriculture was accounted for by the variables included
in the model, while the remaining percentage was
attributed to error term. The F value indicates that the
model is significant (p<0.017). However, each
predictor may explain some of the variance for the
problem faced by farmers’ in using e-Agriculture simply
by chance. The adjusted R-square value penalizes the
addition of extraneous predictors in the model, but
values of 0.658 still show that the variance for the
problem faced by farmers’ in using e-Agriculture can be
attributed to the predictor variables rather than by
chance, and that both are suitable models (Table
4.). In summary, the models suggest that the
respective authority should consider the respondents’
education, participation in training, usages of e-
Agriculture, attitude towards e-Agriculture and
availability of e-Agriculture.
RECOMMENDATION
The study identified several critical problems that
Bangladeshi farmers faced while using the newly
introduced e-agriculture services. These problems
revealed several scopes to improve the e-agriculture
service both at government and NGO level. The
researchers suggested that government should
implement integrated marketing communication using
the popular print and electronic media so awareness
about the service will reach majority of the farmers,
especially those at rural area. In addition to that, the
researchers recommend that the NGO’s and local
government bodies should create mass awareness on
availability and usefulness of e-Agriculture through
organization of local seminars and training programs for
the farmers.
ACKNOWLEDGEMENTS
The researchers would like to express their boundless
gratitude and heartfelt thanks to Dr. Mohummed Shofi
Ullah Mazumder, Assoc. Prof. and Chairman,
Department of Agricultural Extension and Information
System, Sher-e-Bangla Agricultural University, for his
cognitive suggestions, unprecedented co-operation and
inspiration throughout the course of this research work.
Finally, the researchers would like to extend their
gratitude to the government of the people’ republic of
Bangladesh for providing the financial support under
the National Science and Technology Fellowship to
conduct this research work.

Table 4. Multiple regression coefficients of contributing factors related for the problems faced by farmers’ in using e-
Agriculture
Dependent
variable
Independent variables B p R
2
Adj. R
2
F p
Age 0.214 0.473
0.671 0.658 79.267 0.017
**
Education -0.134 0.000
***
Problems faced
by farmers in
using e-
Agriculture
Farm size 0.276 0.132
Annual household
income
0.365 0.114
Farming experience 0.129 0.168
Participation
in training
-0.264 0.017
**
Agricultural knowledge 0.417 0.324
Usages of
e-Agriculture services
-1.097 0.000
***
Attitude towards
e-Agriculture
-0.158 0.037
**
Organizational
Participation
0.329 0.127
Cosmopoliteness 0.536 0.173
Availability of
e-Agriculture
-0.405 0.029
**
*** Significant at p<0.01. ** Significant at p<0.05. * Significant at p<0.1.
AUTHORS’ CONTRIBUTION
All authors were involved in the conception of the idea
of the study. All authors helped for collecting the data
and interpreted the data and drafted, read, and
approved the final manuscript.
COMPETING INTERESTS
The authors of this manuscript have no competing
interests as defined by the journal; they don’t have any
other interests that influence the results and discussion
of this paper.
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New Agriculturist (2015). e-Krishok: promoting ICTs to
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http://www.new-
ag.info/en/focus/focusItem.php?a=2779
Raihan A, Hasan M, Chowdhury M, Uddin F (2005).
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Center. A D.Net Publication, November 2005.
United Republic of Tanzania 2005 National stategy for
Growth and Reduction of Poverty. Government
Printer, Dar es Salaam retrieved from:
http://www.tanzania.go.tz./pdf/nsgrptext.pdf
Wolf S (2010). Determinants and Impact of ICT use for
African USE for African SMEs: Implications for Rural
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Policy Strategies (TIPS) 2001 Annual Forum, South
Africa. Retrieved from:
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nd_Impact_of_ICT_use_for_African_ SMEs.pdf
Yamane T (1967). Elementary Sampling Theory,
Prentice-Hall: Englewood Cliffs, NJ.
Accepted 25 May, 2016
Citation: Rashid SMM and Islam MR (2016). Problems
faced by farmers in application of e-Agriculture in
Bangladesh. Journal of Agricultural Economics and
Rural Development, 3(1): 079-084.
Copyright: © 2016 Rashid and Islam. This is an open-
access article distributed under the terms of the
Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any
medium, provided the original author and source are
cited.

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