




































 AMERICAN INTERNATIONAL JOURNAL OF AGRICULTURAL STUDIES 8(1) (2023), 1-9  

1 

 

      AGRICULTURAL STUDIES 

                                                               AIJAS VOL 8 NO 1 (2023) P-ISSN 2641-4155   E-ISSN 2641-418X 
                                                  

                                                                                                                      Available online at www.acseusa.org      

                                                                                                                                Journal homepage: https://www.acseusa.org/journal/index.php/aijas 
                Published by American Center of Science and Education, USA 

RICE FARMER'S USING MOBILE IN MARKETING OPERATIONS: 

AN ANALYTICAL STUDY IN THE SPECIFIC REGION OF 

BANGLADESH 
 

 Farjana Akter Shila (a)1    Sauda Afrin Anny (b)      Bisakha Dewan (c)      

 

(a) Msc in Agribusiness and Marketing, Department of Agribusiness and Marketing, Sher-e-Bangla Agricultural University, Dhaka, Bangladesh; E-Mail: 

farjanashila10dec@gmail.com 
(b) Assistant Professor, Department of Agribusiness and Marketing, Sher-e-Bangla Agricultural University, Dhaka, Bangladesh; E-Mail: 

anny3543@gmail.com 
(c) Assistant Professor, Department of Agribusiness and Marketing, Sher-e-Bangla Agricultural University, Dhaka, Bangladesh; E-Mail: 

d.bisakha@gmail.com 

 

 
A R T I C L E I N F O 
 

 

Article History: 
 

Received: 1st September 2023 

Revised: 20th October 2023 

Accepted: 27th October 2023   

Published: 4th November 2023   

 

Keywords: 

 

Rice Farmers, Price, Marketing Information,  

Mobile Phone, Rice Marketing. 

  

JEL Classification Codes:  

       

O13, O33, Q11, Q13 

 

 

 
 

 
A B S T R A C T 

 
Rice is a major staple crop in Bangladesh, and its production has a profound effect on the country's 
agricultural sector. Large distribution networks in Bangladesh may drive up rice prices. The scarcity of 

marketing information prevents farmers from making decisions when planning their output and sales. 

This study aimed to analyse the variables that influence mobile usage and the effects of mobile use in 

rice marketing. 100 farmers were selected by two steps sampling procedure from the rural area of 

Upazila Bangladesh. 100 farmers in all, mostly small-scale rice farmers with an average plot size of 

1.88 acres, were approached using a concise interview format & questionnaires. The data was evaluated 

using a variety of statistical methods, including correlation and regression analysis using a binary 

logistic regression model. The analysis was carried out utilizing the SPSS. Studies showed that 75% of 
mobile phone owners utilize it for paddy marketing. Income and education have a significant influence 

on cell phone usage, as shown in regression analysis. In the Likert scale study, there was a highly positive 

impact on having access to a broad variety of information, the accuracy of that information, negotiating 

power, and reducing market intermediaries' and transportation corporations' oppressiveness. Most 

farmers can save time and money by acquiring information themselves. It can be concluded that the 

adoption of mobile phones facilitates marketing activities and all potential consequences for rice 

farmers. Assuring mobile phone utilization could be essential in this area to improve the calibre of rice 
marketing. 

 
 

© 2023 by the authors. Licensee ACSE, USA. This open-access article is distributed under the terms 

and conditions of the Creative Commons Attribution (CC BY) license 

(http://creativecommons.org/licenses/by/4.0/).                           

 

INTRODUCTION 

Food security and social stability are two areas in which rice has historically played a significant influence over the world 

(Zeigler & Barclay, 2008). Farmed in over a hundred different countries, rice is the staple food for more than half of the 

world's population (Fukagawa & Ziska, 2019). Millions of people may attribute the success of their economies, cuisines, 

and cultures to rice (Gnanamanickam, 2009). Some farmers preferred rice production over other crops because of rice's high 

adaptability to many environments and minimal cultivation risk (Al Mamun et al., 2021). United Nation (2022) estimates 

that the world's population will reach 9.7 billion by 2050 and peak at roughly 10.4 billion in the 2080s. It is estimated that 

14,886 MMT of food will need to be produced to fulfil demand in 2050 (Islam & Karim, 2020). 

In addition, rice accounts for 67.5% of daily calorie consumption in Bangladesh (Saha et al., 2021). The agriculture 

sector of the country's economy relies heavily on growing rice. Bangladesh's status as an agricultural giant would be further 

cemented by the country's projected rice output of 37 million tonnes for the 2023-24 season (Team, 2023). More than 165 

million people are being produced at this time, and the crop is responsible for around 78% of annual land use (gross 

cultivated area) (Kabir et al., 2021). Agriculture is the backbone of Bangladesh's economy. Approximately 76% of the 

                                                      
1Corresponding author: ORCID ID: 0009-0005-6625-1392 

© 2023 by the authors. Hosting by ACSE. Peer review under the responsibility of the American Center of Science and Education, USA.  

https://doi.org/10.46545/aijas.v8i1.271 

 
To cite this article: Shila, F. A., Anny, S. A., & Dewan, B. (2023). RICE FARMER'S USING MOBILE IN MARKETING OPERATIONS: AN 

ANALYTICAL STUDY IN THE SPECIFIC REGION OF BANGLADESH. American International Journal of Agricultural Studies, 8(1), 1–9. 

https://doi.org/10.46545/aijas.v8i1.271 

https://doi.org/10.46545/aijas.v8i1.271
http://creativecommons.org/licenses/by/4.0/)
http://creativecommons.org/licenses/by/4.0/)
https://orcid.org/0009-0005-6625-1392
https://orcid.org/0000-0002-4078-6429
https://orcid.org/0000-0003-1237-2218


Shila et al., American International Journal of Agricultural Studies 8(1) (2023), 1-9 

  

2 
 

population resides in rural regions, with 47.5% of the overall workforce being employed in agriculture (Shelley et al., 2016). 

Agriculture contributes 13.6% to Bangladesh's GDP. Seventy-five percent of the land is used to grow rice, and 85 percent 

of it is planted in varieties with excellent yields (International Rice Research Institute, 2023). Seventy of Bangladesh's 

harvested farmland is used for rice production, and of the 71 million people who work in agriculture there, 65 million are 

small-scale farmers (Ganesh-Kumar et al., 2012). 

Although selling rice on the official markets is crucial to many people's economic security, farmers often face 

barriers that prevent them from doing so. Smallholder market participation is both a cause and a consequence of a country's 

economic growth and development, crucial to the monetization of agriculture and the welfare of farmers (Hoq et al., 2021). 

Small-scale farmers, who account for almost all of the food producers in emerging nations, are often abandoned by the 

market (Barrett, 2008). Agricultural markets may be difficult for small-scale farmers because of a lack of knowledge or a 

systemic problem that results in discord between producers and buyers (Kydd & Dorward, 2004). Since the lengthy trek to 

distant, higher-paying markets is not worth it for an overwhelming number of small-scale farmers, they instead sell their 

rice in low-paying local marketplaces (Fafchamps & Hill, 2005).  

Efficient market information provided has been proven to help farmers, traders, and policymakers (Dagar, 2015). 

Farmers require regular, timely, and trustworthy market information for production and marketing planning, in addition to 

other market participants, to make the best trading decisions. Ideally, marketing information services should be available to 

anyone. Farmers can benefit from proper marketing information services to help them better realize pricing for marketed 

products (SASEC Village, 2013). A rising amount of farmers in smaller economies are using mobile phone technology to 

increase their access to markets for agriculture. This is because mobile phone communication is one of the most significant 

drivers encouraging economic development in emerging economies (Katengeza et al., 2011). The majority of a farmer's 

income and ability to feed their family is dependent on the selling price of rice. Farmers' ability to gain entry to new markets 

has a significant impact on rice prices (Hoq et al., 2021).  

Farmers' and businessmen's relationships are bolstered by the broad acceptance of mobile phone use (Kumar, 

2023). The current global population is estimated to be 7.33 billion, making up 91.04% of those with cell phones (Turner, 

2018). In developing nations, where computers and phones may not be readily accessible, almost 94% of farmers have their 

own mobile devices (AGRIVI, 2015). There are presently 186.10 million mobile phone users in Bangladesh (Bangladesh 

Telecommunication Regulatory Commission, 2023), and this number is expected to rise by 1% by 2022. In some parts of 

Bangladesh, 80.15 percent of farmers utilize a mobile phone service of some kind (Mamun-ur-Rashid et al., 2019). The 

potential for mobile phones to promote market transparency and efficiency in the agricultural sector has been at the forefront 

of discussions about the intersection of agriculture and information technology. Mobile phone usage in farming might 

influence market prices under certain conditions. Mobile phones could minimize the costs of farmers' households searching 

for private information, especially when compared to traditional mechanisms such as personal travel, periodicals, or 

landlines (Kusumaningsih, 2023). This research aims to identify the variables that contribute to mobile phone use and assess 

the results of mobile phone use among farmers seeking market data on rice.  Analytical outlines of this study are – (a) To 

characterize the unique socioeconomic features of the farmers, (b) to ascertain the elements influencing the utilization of 

mobile phones for gathering market data, (c) to assess the effects of farmers using their mobile phones to get market 

information. 

 

LITERATURE REVIEW 

The world's rice production has more than tripled. The majority of the production came from Asia. More than 80% of the 

world's rice is produced in seven Asian nations, including Bangladesh (Bin Rahman & Zhang, 2022) and Bangladesh ranks 

third globally in rice production (Sarkar et al., 2022). The production and trading of rice in Bangladesh have been the main 

issues (Bala et al., 2016). For farmers, a successful rice market is crucial. Sometimes it is impossible to develop a well-

designed rice market due to inaccurate market information (Rahman et al., 2020). In addition, high levels of market power 

among rice wholesalers and millers suggest that they have a monopolistic effect on the market. Consequently, farmers are 

receiving less money or profit than is paid for their products, which benefits the intermediaries (Khatun et al., 2020). Price 

increases are observed as a result of market manipulation by major merchants and millers (Rahman et al., 2021). Mobile 

devices improved the delivery of agricultural extension services (Fu & Akter, 2016). Information sharing in agriculture is 

essential for the widespread implementation of new farming techniques (Khan et al., 2019). An inefficient agricultural 

market has negative effects on market participants and, in the long run, has serious societal and economic ramifications 

when information is lacking. Improvements in market infrastructure, access to information and communication 

technologies, and potential development are all essential (Nugroho, 2021). Agricultural market information is crucial for 

small-scale farmers, hence they often turn to mobile devices as a reliable interaction route (Nyagango et al., 2023). 

Bangladeshi farmers utilize their cell phones largely for forecasts of the weather, market data, information on pests and 

diseases, and financial transactions (Rahman et al., 2020). Significant factors that influenced mobile phone usage included 

level of education, family size, income, and attitudes toward the use of mobile phones (Amir et al., 2016). By expanding 

farmers' access to information and services throughout the agricultural value chain, mobile phones boost farmers' influence 

and improve their quality of life (Anadozie et al., 2021). Farmers may increase their income, decrease their operational 

costs, and increase their crop yields by using mobile phones (Ogunniyi & Ojebuyi, 2016). Favorable effects of literacy, 

accessibility to local markets, size of the land, asset values at the time, crop revenue, and regional differences (Katengeza 

et al., 2013). The study found that using information systems, smallholder farmers' agricultural endeavors and agribusinesses 

improved agricultural output and boosted rural households' access to food (Mdoda et al., 2023). This study concentrates on 

the socio-demographic profile and correlation of different independent variables to find the results on different unique 

parameters that have strong driving power in agriculture marketing. Some of the studies have an analysis of factors and their 



Shila et al., American International Journal of Agricultural Studies 8(1) (2023), 1-9 

  

3 
 

impact on overall areas, but this study solely focuses on rice farmers to assess what factors are responsible. This study has 

some unique analyzing features that outline the impact of using mobile on rice marketing, like degree and reliability of 

information, intermediaries’ oppressiveness, information searching time and costs, bargaining power in all aspects, and 

rational decision-making. 

MATERIALS AND METHODS 

Population and Sampling Technique 

The population of the study was mostly made up of local rice farmers. A basic random sample approach was used to select 

100 farmers from 501 farmers (20% of the total population), with the decimal number adjusted accordingly. 

 

Method of Data Collection  

Face-to-face interviews were used to acquire data for the primary sources which was achieved with well-designed interview 

schedule that included both open and closed-ended queries. These were briefed to them and easy to answer with a view to 

collecting more precise opinions from the farmers over two months period.  

 

Location of the Study 

The study was conducted in a rural area in a specific region of Bangladesh (Coordinates: 23°36′N 90°59.5′E  /  23.600°N 

90.9917°E  / 23.600; 90.9917).  

 

Analyzing Data 

The primary data that had been obtained were carefully scrutinized to look for flaws and omissions. The completed data 

was then entered into the SPSS program for additional analysis.  

 

Approaches for Analysis 

We utilized a binary logistic regression approach to analyze how various characteristics of participants influenced their 

likelihood to open marketing messages on their cell phones. A null hypothesis was created in accordance with the purpose 

to be used while running the regression model.  

Multiple variables in an analysis of multiple linear regression that are highly associated with each other and with 

the dependent variable are said to be multicollinearity. Due to multicollinearity, several previously significant variables 

become nonsignificant. Multiple collinearity between the independent variables was discovered via the use of a correlation 

analysis.  

The following describes the binary logistic regression model used in this study: 

 

Log [P/1-P] = β0 + β1X1 + β2X2 + β3X3 + β4X4 + β5X5 + β6X6 + β7X7 + e  

 

Where, P= Probability of outcome, β0 = Intercept, X1 = Age of the farmer’s (Year), X2= Farmers’ Gender (Male=0, 

Female=1), X3=Level of Education, X4=Duration of farming (Year), X5=Average Income/Year (BDT), X6=Terms of using 

mobile, X7= Plot Size (Acre), β1 – β7 = Regression Coefficient of the predictors, e = Random error 

 

The data was analyzed using SPSS. * signifies significance when applied to the 0.1 level, ** signify significance 

at the 0.05 level and ***signify importance when comparing groups at the 0.01 level. 

Lastly, descriptive statistics like percentage, mean, and standard deviation were utilized to examine the data from the likert 

scale and categories. 

RESULTS 

Farmers' Socioeconomic Profile 

The criteria were the farmer’s age, farmer’s gender, education level, plot size, farming duration, income, data of mobile use, 

and terms of mobile using mobile phones. Tables 1 and 2, demonstrate the category distribution of farmers' socioeconomic 

characteristics and descriptive statistics of farmers' socioeconomic characteristics, respectively. Approximately 90% of men 

and 10% of women work as farmers, according to Table 1. A third of farmers (34%), on average, have a secondary education. 

In the study area, there is a 73.0% literacy rate among respondents. As can be seen in Table 1, around 79% of people in the 

research region use mobile phones. The selected farmers' average age, according to Table 2, is 51.3 years, but the average 

length of time they have been farming is 23.50 years. 

 

Table 1. Categorical distribution of farmer’s socio-economic characteristics (N=100) 

 
Specification Frequency Percentage 

Gender 
  

Male 90 90% 

Female 10 10% 

Education Level 
  

Illiterate 27 27% 

Primary 17 17% 

Secondary 34 34% 

Higher Secondary 18 18% 

Graduation & Above 4 4% 

Mobile Phone 
  



Shila et al., American International Journal of Agricultural Studies 8(1) (2023), 1-9 

  

4 
 

Mobile Phone Users 79 79% 

Mobile Phone Non Users 21 21% 

 

The majority of farmers in the research areas are small farmers, with a mean plot size of 1.88 acres; there are no 

large farmers in the region.  The survey comprised small-holder farmers with small-category farms and annual incomes of 

roughly 2-3 lacs shown in Table 2.   

 

Table 2. Socioeconomic features of farmers  

 
Independent Variables Min. Max. Mean Std. Deviation 

Age of the Farmer's 28.0 75.0 51.32 12.71 

Grade of the Education 0 16.0 6.99 4.95 

Farming Duration  4.0 50.0 23.50 12.68 

Terms of using mobile (years) 4.0 17.0 8.71 2.87 

Household Income (BDT in lac) 0.50 12.00 2.72 1.52 

Plot size (acre) 0.20 5.50 1.88 1.08 

 

Analysis of the factors driving using mobile in paddy marketing:  

The characteristics affecting rice farmers' usage of mobile phones to learn about the market were identified using a binary 

logistic regression model. In this model, the independent factors included the farmer’s age, farmer’s gender, education level, 

household income, mobile phone usage duration, farm size, etc., whereas the dependent variable was the mobile phones 

used to get market information. Through SPSS software, the model was tested. Prior to performing the regression analysis, 

a correlation study was conducted to determine whether the independent variables were multicollinearity.  

 

Table 3. The independent variables' coefficient of correlation 

 
  Age of the 

Farmer's 

Level of 

Education 

Farming 

Duration 

Average 

income/Year  

(BDT In lac) 

Mobile phone use 

duration (years) 

Plot Size in 

Acre 

Age of the Farmer's 1 -0.475** 0.847** -0.038 0.088 0.140 

Level of Education -0.475** 1 -0.424** 0.529** 0.220* 0.394** 

Farming Duration 0.847** -0.424** 1 -0.061 0.003 0.071 

Average income/Year  

(BDT In lac) 

-0.038 0.529** -0.061 1 0.352** 0.596** 

Mobile phone use 

duration (years) 

0.088 0.220* 0.003 0.352** 1 0.429** 

Plot Size in Acre 0.140 0.394** 0.071 0.596** 0.429** 1 

** Significant at the 5% level 

 

A correlation analysis in SPSS revealed a correlation coefficient of 0.847 between the age of the farmers and their 

terms of farming, which is significant at the 5% level of significance. This information is displayed in Table 3. It suggests 

that the age of the farmer and the number of years they have been farming have a significant positive link. A variable should 

be removed in order to prevent multicollinearity. Years of agricultural experience have been eliminated as an independent 

variable in the ensuing binary logistic regression analysis. The remaining six independent variables were utilized in 

regression analysis. The dependent variable was the use of mobile phones to get market information. Table 4 presents the 

results of the regression. 

Table 4 examines the null hypothesis and implies that the significant contributing factors (at the 1% and 5% levels 

of significance) are education and income and the other 4 parameters are unrelated to farmer’s use of mobile phones to 

receive market information.  

Model validity:  It was checked through Cox and Snell R2, Nagelkerke R2, and Chi-square test where Cox & Snell 

R2 and Nagelkerke R2 values were 0.556 & 0.815 respectively.  

According to the Cox and Snell R2 value of 0.556, the explanatory variable may account for around 56% of the 

variance in the response. Unknowns are responsible for the remaining 44.4%. The farmers' usage of mobile phones to receive 

market information varies significantly among respondents, although each predictor might be able to account for some of 

the variation by pure chance. Adjusting the Cox and Snell R2 is done via Nagelkerke R2. According to the Nagelkerke R2 

value of 0.815, the explanatory factors can account for 82% (roughly) of the variance in the response. Additionally, 93.5% 

of predictions were accurate overall. The omnibus test value for the model coefficient is about 62.46, which is greater than 

the tabular value (18.48) of chi-square (χ2) test at the 1% level of significance with 60 of freedom. This indicates that this 

model passes the omnibus test of model coefficient value. These findings collectively show that the model is valid and best 

fitted.  

 

Table 4. Binary logistic regression coefficients of the influencing variables: the farmers' usage of mobile phones to receive 

market information was the dependent variable 

 
Independent variable ß SE Wald Sig. Exp (ß) 

Age of the farmers  -0.036 0.116 0.097 0.755 0.965 

Gender 1.839 2.057 0.799 0.371 6.288 

Education 0.640 0.195 10.767 0.001*** 1.896 



Shila et al., American International Journal of Agricultural Studies 8(1) (2023), 1-9 

  

5 
 

Household income 1.946 0.844 5.309 0.021** 6.998 

Length of using mobile phone -0.058 0.255 0.052 0.819 0.943 

Plot size -0.725 0.727 0.995 0.318 0.484 

*** Significant at 1%; ** Significant at 5%. 

 

Impact of using mobile phone- description with null hypothesis 

Farmers' propensity to utilize mobile phones to get market information is hypothesized to be positively correlated with their 

level of education and family income. 

 

H1: There is no educational value in trying to convince farmers to use cell phones to get access to market information. 

H2: The likelihood that farmers will utilize their mobile phones to receive market information is unaffected by household 

income. 

 

Education's Impact on the Likelihood of Mobile Phone Use  
The variable 'education' has a p-value of 0.001 (Table 4). Based on the results of the relevant study's variables, the following 

conclusions were drawn: (a) Education significantly affects farmers' propensity to use mobile phones to get market 

information at the 1% level. The null hypothesis can thus be disproved. (b) Mobile phone use and education are positively 

correlated, which implies that a farmer had a better likelihood of acquiring market information via mobile phone if they had 

more education. Farmers who have greater education have an 89% more chance of utilizing a cell phone than those with 

less education, according to the Exp (ß) value of 1.896. Through education, farmers can improve their capacity to use mobile 

phones to get market information in a short amount of time. 

 

Income’s impact on the Likelihood of Mobile Phone Use 
In Table 4, the variable household income's p-value was 0.021. Based on this value, under examination in the study, the 

following discussions were made: (a) at a 5% level, household wealth significantly affects farmers' propensity to use mobile 

devices to get market data. So, the null hypothesis is disproved. (b) Mobile phone usage and household income are positively 

correlated which defines that farmer who have higher income has a greater likelihood of acquiring market information via 

mobile phone. Farmers with higher household income might increase the possibility of using a mobile phone about 600%, 

as indicated by the exp (β) value (7). 

 

Outcomes of Mobile Phone use in rice marketing 

According to the discussion above, 79% of the farmers in the research region own mobile phones. The remaining 21% do 

not own mobile phones but do occasionally use those provided by their family, relatives, or other service providers. Farmers 

were further categorized based on whether they explicitly used mobile phones for paddy marketing in order to study the 

effects of their use in gathering market data. 

 

 
 

Figure 1. Landscape of farmer’s mobile phone use in paddy market 

 

 
 

Figure 2. Response of the farmers who use mobile phone in paddy marketing. The detailed impact results is displayed here 

which is explained in Table 8.  

 

5%

75%
95%

25%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Mobile Phone Not Owner

Mobile Phone Owner

Don’t Use Phone in Paddy Marketing Use Phone in Paddy Marketing

12%

88%

10%

90%

8%

92%

53%

12% 5%

29%

2%
19%

81%

14%

86%

53%

14%
2%

32%

N
o

Y
es N
o

Y
es N
o

Y
es

A
g
re

e

D
is

ag
re

e

N
eu

tr
al

S
tr

o
n

g
ly

 a
g
re

e

S
tr

o
n

g
ly

 d
is

ag
re

e

N
o

Y
es N
o

Y
es

A
g
re

e

D
is

ag
re

e

N
eu

tr
al

S
tr

o
n

g
ly

 a
g
re

e

Scale of

Information

Reliable

Information

Taking

Decision

Oppressiveness Bargaining

power

Search cost Searching time

R
es

p
o
n
se

 (
%

)



Shila et al., American International Journal of Agricultural Studies 8(1) (2023), 1-9 

  

6 
 

Table 5. Response from the farmers who don’t use mobile phone in paddy marketing   

 

Individual visit expenses and expenses with mobile are calculated to understand the cost ratio during data 

collection. The mean cost of individual visit expenses and expenses with mobile was about 41.33 & 13.65 (BDT) 

respectively (Table 6).  

 

Table 6. A scenario of the relative costs of collecting information 

 
Categories Sample (N) Min. (BDT) Max. (BDT) Mean (BDT) Std. Deviation 

Individual visit Expense (Tk) 42 30.00 60.00 41.33 9.70 

Mobile phone expense (Tk) 58 5.00 30.00 13.65 5.07 

  

Table 7. Impacts result summary and findings  

 
Impacts  Description Results Findings  

Scale of Information various levels of data were 

collected for paddy 
marketing and solicited for 

this study from 60 mobile 

users in rice marketing  

88% of people think it's 

important to learn more, 
compared to 12% who don't 

(Figure 2). In contrast, 60% 

of non-user shared 

unfavorable opinions (Table 

5) 

In paddy marketing, the majority of people are 

positive about utilizing mobile phones to obtain 
extensive information.  

Information reliability Information reliability was 
asked to the both mobile 

users and non-users 

90% of farmers who used 
mobile phones said they 

trusted the data more than 

other sources (Figure 2). 
Most farmers who don't use 

it, however, (60%) said they 

didn't get it. The other 40% 
of the population strongly 

disagreed with the comment 

(Table 5). 

Comprehensive market information is available 
to rice farmers from a variety of vendors, 

allowing them to choose whether reports are 

reliable. 

Rice Marketing in 
Decision 

Decision parameters were 
evaluated with well-

designed questions  

Nearly all mobile users 
(92%) agree that having 

instantaneous access to a 

variety of factors facilitates 

better decision-making 

(Figure 2). 

The marketing of rice requires several decisions 
from the farmer, including where to sell the crop, 

who to sell to, how to transport the crop, and what 

roads to take. It can be achieved easily with 

mobile phone ownership which simplifies their 

daily works 

Intermediaries' 
oppressiveness  

Influence and market power 
were assessed  

29% strongly agree and 53% 
agree that mobile phones can 

lessen oppressiveness 

(Figure 2), in the contrary 
65% of non-users showed a 

negative response (Table 5). 

Using mobile phones in rice marketing can able 
to reduce the stiffness of the middlemen where 

producers can communicate directly and get 

optimum outcomes with faster communication. 

Bargaining power of the 
farmer 

Crosschecking and 
validation of prices and 

costs by the farmers were 

also evaluated  

81% of cell phone users are 
farmers, giving them 

instantaneous access to 

numerous data on regional 
and international market 

trends and prices (Figure 2).  

Communication with mobile phones in rice 
marketing broadens increases their reach and 

sales potential. This gives them greater sway in 

negotiations with potential buyers. 

Information searching 

time 

Can information be 

collected faster or not 

53% of farmers agreed and 

32% of farmers strongly 

agreed compared to 

conventional (Figure 2) and 

60%had ambivalent opinions 
regarding cutting down on 

the amount of time needed 

(Table 5) 

Utilizing their phones will speed up information 

gathering and paddy marketing. 

Search cost with mobile 

phone 

Cost effectiveness were 

examined compare to 

individual visit cost   

When asked how often they 

seek information, 86% of 

farmers said it was less often 
than before they started using 

their mobile phones. (Figure 

2) 

Mobile phone use actively in rice marketing can 

save money to assist in getting the desired 

outcome.   

 

Impacts Neutral  

N (%) 

No  

N (%) 

Yes  

N (%) 

Agree  

N (%) 

Disagree  

N (%) 

Scale of Information 12 (60) 7 (35) 1 (5) 
  

Reliable Information 12 (60) 8 (40) 
   

Taking Decision 12 (60) 8 (40) 
   

Oppressiveness  7 (35) 13 (65) 
   

Bargaining Power  13 (65) 7 (35) 
   

Search Cost 12 (60) 8 (40) 
   

Searching Time 12 (60) 
  

1 (5) 7 (35) 



Shila et al., American International Journal of Agricultural Studies 8(1) (2023), 1-9 

  

7 
 

DISCUSSIONS 

Agriculture frequently provides the primary source of income for rural farmers in developing countries. There are so many 

factors that influence the income of farmers. It is assessed and evaluated in some studies regarding the influential parameters 

that contribute to household income. Numerous studies on mobile usage and its related economic and social effects have 

been conducted recently. Numerous studies examine the impact of mobile devices on market efficiency and agricultural 

pricing trends. An in-depth evaluation of the variables influencing paddy farmers' use of mobile phones to access market 

information was done in this study. Education and household income are among the socioeconomic factors of the 

respondents, who are farmers that have the greatest beneficial impact on the use of mobile phones to get market information. 

Rajkhowa and Qaim (2022) found that using mobile phones is linked to higher household earnings. 

The likelihood of using a mobile phone to get market information improves by 89% with education. The simplest 

practical explanation for this is that more educated farmers are more aware of their profit margins and subsequently aim to 

cut costs. They therefore look for farming and product marketing methods that are comparably less expensive. In addition, 

education raises farmers' marketing and agriculture understanding of the advantages of mobile. They get insight into 

potential applications of mobile technologies to improve their agricultural and marketing operations, which will lower their 

costs and boost their profit margin.  

The likely outcome of using mobile devices for acquiring market data is significantly positively correlated with 

household income. The likelihood of using a mobile phone to receive market information grows by 600% with income. 

More amenities are guaranteed with higher income. In our nation, a cell phone still costs a lot to buy and maintain, especially 

for those with lower incomes. Higher earners would rather make a phone call than visit someone in person. They are not 

particularly bothered by the cost of phone calls. But it might be a burden for the underprivileged. So, using a cell phone to 

gather market data depends significantly on money.  

Market information systems have the ability to deliver exact and reliable data on costs & agriculture product prices, 

arrivals & availability of the products, trends, analysis, etc. An effective and accessible marketing information system may 

control prompt product delivery, cut marketing expenses, and boost output and productivity. For farmers to achieve their 

targeted outcomes, real-time market knowledge and trustworthy data are essential. In this study, results showed that the 

majority of farmers who use mobile devices, using a mobile phone suggests a favorable impact on their marketing 

operations, such as information search time, search cost, decision making, and so forth. Varieties of agriculture marketing 

information can be collected easily from different trustworthy sources which assist the farmers to make appropriate and 

rational decisions. Mittal and Tripathi (2009) stated that mobile devices can be a catalyst for raising rural incomes and 

agricultural output while associated with three most crucial elements: quality, timeliness, and trustworthiness of the 

information. According to this study, the majority of farmers agreed that using a mobile phone implies a favorable impact 

on their marketing operations, such as providing a reliable, timely, and large volume of information.  

As there remains a long chain that is dominated by many intermediaries can be mitigated by access to market 

information. Study findings indicated that most of the farmers can overcome these challenges and lessen the stiffness of 

intermediaries. Ilahiane (2023) asserted that farmers' use of mobile phones leads to increased farmers’ market involvement 

and the gradual elimination of middlemen in the agricultural value chain.  However, the opposite opinion was shared by 

non-users which forwarded the necessity of the use of mobile phones in rice marketing. Most importantly, rice marketing 

information can be managed with high speed, and the search cost with mobile is reduced by 68% compared to personal visit 

cost. As a result, bargaining ability and scope are increased. A study by Aker (2008), observed that using cell phones in the 

agriculture market reduces information searching costs. The non-user group, meanwhile, tended to give unfavorable 

feedback or remained silent. When comparing the two groups' comments, it can be concluded that the employment of mobile 

phones in the paddy marketing system has enormous potential. 

 

CONCLUSIONS  

The use of mobile devices is rapidly increasing worldwide. Farmers are finding mobile phones a fantastic tool to maintain 

and extend communication to all relevant stakeholders they need in agriculture marketing. Mobile Phone Adoption in 

emerging nations and its effects on the economy and Society In this study, most of the farmers are using mobile phones for 

rice marketing. The research region found that using a cell phone to get information on rice marketing worked satisfactorily. 

The use of mobile phones by farmers is significantly influenced by household income and educational attainment. Study 

results based on farmers’ reactions found that mobile offers large-scale, fast, trustworthy information at a relatively cheaper 

cost, giving farmers more negotiating leverage in the market and lessening the power of the middlemen. Following the 

conversation, it is clear that using a mobile phone has enormous potential for expanding the agricultural marketing industry. 

Mobile phone usage among farmers has the potential to boost both the distribution and manufacturing sectors. The potential 

afforded by mobile phone technology can be used by the government and policymakers to boost production and create a 

productive and successful marketing system for farmers. Since rice is the primary staple food in the nation, the government 

ought to place more attention on supplying farmers with more facilities. If not, farmers will face difficulties in growing rice, 

which will cause the entire country to suffer in the near future.  

 

 
Author Contributions: Conceptualization, F.A.S.; Methodology, F.A.S.; Software, F.A.S.; Validation, F.A.S, S.A.A. and B.D.; Formal Analysis, F.A.S.; 
Investigation, F.A.S.; Resources, F.A.S, S.A.A. and B.D.; Data Curation, F.A.S.; Writing – Original Draft Preparation, F.A.S.; Writing – Review & Editing, 

F.A.S, S.A.A. and B.D.; Visualization, F.A.S. and S.A.A.; Supervision, S.A.A. and B.D.; Project Administration, S.A.A. and B.D.; Funding Acquisition, 

F.A.S, S.A.A. and B.D. Authors have read and agreed to the published version of the manuscript.  
Institutional Review Board Statement: Ethical review and approval were waived for this study, due to that the research does not deal with vulnerable 

groups or sensitive issues. 



Shila et al., American International Journal of Agricultural Studies 8(1) (2023), 1-9 

  

8 
 

Funding: The authors received no direct funding for this research. 

Acknowledgments: Not Applicable  

Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. 

Data Availability Statement: The data presented in this study are available on request from the corresponding author. The data are not publicly available 
due to restrictions. 

Conflicts of Interest: The authors declare no conflict of interest.                                                                                                                                                                                                                                   

 

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