









































Pa
ge

 
1



Pa
ge

 
80

American Journal of  Smart 
Technology and Solutions (AJSTS)

Adoption of  E-technology for Agricultural Advancement in Jamalpur, Bangladesh
Md. Yeakub Ali1*, Murad Ahmed Farukh1, Md Azharul Islam1, Yeasin Arafat1, Runa Laila2

Volume 4 Issue 2, Year 2025
ISSN: 2837-0295 (Online)

DOI: https://doi.org/10.54536/ajsts.v4i2.4541
https://journals.e-palli.com/home/index.php/ajsts

Article Information ABSTRACT

Received: February 12, 2025

Accepted: March 16, 2025

Published: October 25, 2025

Adopting e-technology is a transformative approach to enhancing agricultural productivity, 
optimizing resource utilization, and improving market access in Bangladesh. However, its 
adoption remains low among farmers in flood-prone areas like Jamalpur due to inadequate 
digital infrastructure, limited digital literacy, and financial constraints. This study examines 
the factors influencing e-technology adoption in Charpara Block, Laxirchar Union, 
Jamalpur District, through structured interviews with 50 farmers. The findings indicate 
that only 30% of  farmers use e-technology, primarily due to poor mobile network 
coverage, lack of  awareness, and affordability issues. Farmers with larger landholdings, 
higher education levels, and organizational involvement demonstrated a greater likelihood 
of  adoption. To address these barriers, this study proposes key policy interventions, 
including government-led subsidies for smartphones and internet services, expansion 
of  digital literacy programs, and investment in rural network infrastructure to enhance 
accessibility. Additionally, technological solutions such as mobile-based advisory platforms 
(e.g., Krishoker Janala), AI-driven decision-support systems, and precision agriculture 
tools can improve climate resilience and optimize farm management. By integrating these 
measures, policymakers can bridge the digital divide and enhance agricultural sustainability. 
Addressing these barriers and implementing targeted interventions can drive widespread 
e-technology adoption, leading to socio-economic empowerment and improved climate 
adaptation for smallholder farmers.

Keywords
Agricultural Empowerment, 
Farmer Adaptation, Rural 
Development, Socio-Economic 
Improvement, Technology Adopt

1 Department of  Environmental Science, Bangladesh Agricultural University, Mymensingh-2202, Bangladesh 

2  Department of  Anthropology, Jagannath University, Dhaka-1100, Bangladesh 
* Corresponding author’s e-mail: yeakub.sdf@gmail.com

INTRODUCTION 
The agricultural sector worldwide faces various intricate 
challenges consisting of  environmental changes, 
increasing populations, scarce resources, and the need 
for sustainable farming approaches (Ahmed, 2023; Hasan 
et al., 2023). Print-on-demand technology that merges 
Information and Communication Technologies (ICTs) 
including mobile applications and internet platforms and 
digital advisory tools, functions as a transformative method 
to increase agricultural productivity and operational 
efficiency and disaster resilience (Mumuni et al., 2023) 
demonstrates that e-technology supplies mobile extension 
information to farmers in developing countries through 
tools that manage resources to support crop development 
and pest control and market trend analysis. The worldwide 
increase in agricultural needs has revealed that digital 
solutions must become the standard because Bangladesh 
as an agricultural nation bases its GDP on farm output and 
labor distribution (Ali & Roknuzzaman, 2013).
Bangladesh farmers practice agriculture as both their life-
supporting activity and their basic sustenance system by 
conducting farming on a small scale. Bangladesh suffers 
from declining agricultural territory alongside growing 
pest outbreaks because irrigation methods need updated 
technologies and modern infrastructure and farmers 
experience limited access due to population growth and 
environmental changes (Sarker et al., 2021). E-technology 
introduces a breakthrough method which enables 
farmers to acquire time-sensitive valuable solutions 

without intermediaries from their agricultural landscapes. 
Mobile applications (Plantix, Krishoker Janala) as well 
as government programs (Krishi Batayon) offer two 
examples of  digital tools that enable farmers to improve 
their decision-making process in crop cultivation while 
decreasing production expenses (Mohammad & Dey, 
2024). E-technology serves as an important solution 
because it delivers information equality to farmers from 
disadvantaged locations so they can acquire high-yielding 
plant species together with fertilizer optimization and 
pest defense measures that create sustainable agricultural 
development (Niti, 2019; Sheela & Chakravarthi, 
2019). Implementing e-technology systems would act 
as a vital connection for farmers to retrieve extension 
services together with market information and disaster 
preparedness resources. The worldwide implementation 
of  e-technology produces real advantages because Sub-
Saharan African farmers see yield boosts of  20-30% 
through mobile platforms (Misaki, 2024) and Indian 
farmers gain market opportunities via e-Choupal 
(Kambar, 2023). The potential of  e-technology to 
transform agricultural progress has established that its 
adoption in Bangladesh is vital for achieving agricultural 
development.
Research investigations in the present time have shown 
increasing focus on how e-technology influences 
agricultural practices. E-technology represents an 
emerging technology discipline that pumps up rural 
development through better information management, 



Pa
ge

 
81

https://journals.e-palli.com/home/index.php/ajsts

Am. J. Smart. Technol. Solutions 4(2) 80-86, 2025

according to Mumuni et al. (2023). Research conducted 
by Misaki (2024) demonstrates how information 
and communication technology boosts agricultural 
productivity through mobile phone expansion that results 
in 1.5% yearly agricultural output increases across 62 
developing nations. ICTs have the potential to provide 
rural information in Bangladesh according to Ali and 
Roknuzzaman (2013) yet the adaptation rates remain 
inconsistent. Anandaraja et al. (2013) discuss how digital 
content for farmers needs validation as they reference 
the TNAU Agri Tech Portal platform which requires 
user centered design. Digital literacy and internet access 
limitations as well as economic restrictions continue to act 
as barriers for rural areas. Research evidence shows that 
e-technology brings opportunities but shows different 
system implementation challenges in diverse contexts 
(Kambar, 2023).
The evolution of  e-technology meets numerous 
challenges which restrict its adoption in Bangladesh. 
Farmers in Jamalpur must struggle because they lack 
smartphone and internet access while their education 
levels remain low and they do not know about digital 
tools. Local dealers provide traditional pest and fertilizer 
advisory services to farmers who practice conventional 
agriculture methods. Moreover, systemic issues—such 
as inadequate infrastructure, high device costs, and 
insufficient training—compound these challenges, 
leaving farmers ill-equipped to leverage e-Technology’s 
benefits (Mumuni et al., 2023). The government launched 
Krishoker Janala and Pesticide Prescriber apps while 
showing commendable initiative but they reach only a 
small number of  areas where Laxirchar Block falls.
Research about micro-level e-technology adoption in 
Jamalpur Bangladesh demonstrates necessary study 
by filling gaps that emerge from broad rural ICT 
adoption studies (Sarker et al., 2021) and urban-centric 
digital initiatives (Altarturi et al., 2023). Research about 
e-technology adoption lacks focus on socio-economic 
factors and environmental challenges which exist 
exclusively in flood-prone riverine areas while quantitative 
assessments linked to adoption variables are also rare. 
The existing research gap obstructs authorities from 
creating specific policies to promote basic agricultural 
development. The study investigates three essential 
questions which center around (1) Which factors prevent 
e-technology adoption among Jamalpur farmers? (2) 
What proportion of  farmers in Charpara village uses 
e-technology and are there any demographic differences 
alongside farm characteristics that influence adoption? 
(3) What policy actions should Bangladesh implement 
to boost the adoption of  e-technology among rural 
areas? This study investigates barriers to adoption and 
establishes adoption rates at Charpara while building 
recommendations for enhancing e-technology adoption 
in Bangladesh farming.
Research variables concerning farm size and e-technology 
perception together with organizational involvement 
make essential contributions to digital agriculture 

knowledge in developing areas. This research evaluates 
government apps like Krishoker Digital Thikana while 
comparing e-technology user groups with those who 
have resisted digital solutions to establish an uncommon 
research model across Bangladeshi academic papers. 
The study presents applicable policy recommendations, 
which include device subsidies and doorstep e-platform 
service provisions to support worldwide efforts to use 
technology for sustainable agriculture. E-Technology’s 
massive power for agricultural progress in Jamalpur 
rests on its ability to overcome existing obstacles while 
developing solutions for local farmers to match rural 
development and agricultural sustainability objectives.

MATERIALS AND METHODS
Study Area
This study was conducted in Charpara village, which is 
part of  Laxirchar Block and Sadar Upazila in Jamalpur 
District Bangladesh, situated near the Old Brahmaputra 
River along the rural area. Jamalpur District in northern 
Bangladesh consists of  seven upazilas with fertile flood-
prone soils, allowing researchers to study e-technology 
adoption. The 568,726 residents in Sadar Upazila earn 
57.48% of  its total income from agricultural activities that 
focus on cultivating paddy, jute, wheat, potato, vegetables 
and mango and banana fruits (BBS, 2022). Laxirchar 
Block obtained its segments from the Department of  
Agricultural Extension (DAE) because the entity received 
continuous e-technology support from government and 
foreign aid programs. The combination of  productive 
land with the problems of  seasonal waterlogging as well as 
the distribution of  small farm ownership (55.76% owners 
and 44.24% landless) and scarce infrastructure (28.70% 
electricity coverage) affects the region. The block offers 
communication infrastructure, which includes 110 km of  
pucca roads together with 185 km of  semi-pucca roads 
as well as 690 km of  mud roads while providing 48.5 km 
of  railway. 

Population and Sampling
Farm families permanently living in Charpara village of  
Laxirchar Block constituted the research population since 
they engaged in agricultural production. The researchers 
employed purposive sampling because surveying every 
household was impractical according to Goode & Hatt 
(1952). With the assistance of  the Assistant Agriculture 
Officer and local leaders (Matobbor), the sampling 
framework was constructed by obtaining e-technology 
user lists. Each household had one primary operator 
pickled as the survey participant. The target group 
consisted of  participants who utilized e-technology 
services like Krishoker Janala together with individuals 
who did not use these services from the same community. 
The research utilized random selection methods to 
obtain 50 participants from within their subject groups 
in Jamalpur Sadar Upazila, Laxirchar Block, Charpara 
village.



Pa
ge

 
82

https://journals.e-palli.com/home/index.php/ajsts

Am. J. Smart. Technol. Solutions 4(2) 80-86, 2025

Data Collection
Fifty face-to-face interviews were conducted with a pre-
tested, structured questionnaire capturing demographic 
information, including age, education, income, farm 
physical characteristics like farm land size and crops, and 
e Technology usage such as mobile phones and apps 
usage. The questionnaire was piloted with five farmers 
from a neighboring village and the language improved. 
The respondents were interviewed, in Bengali, by trained 
enumerators, lasting 30-45 minutes at the respondents’ 
homes or fields. Open ended questions were used to 
gather qualitative data on barriers and motivations. Data 
from secondary sources came from  DAE (2015).

Variables and Measurement
Independent Variables 
Age (years), education (schooling years), farm size 
(hectares), income (BDT/year), occupation (agriculture, 
business, service), attitude toward e-technology (1-5 scale), 
organizational participation (yes/no), and e-technology 
availability (frequent/occasional/rare).

Dependent Variable 
E-technology adaptation level (low, medium, high), 

based on usage frequency and services accessed. Age 
was self-reported, education scored by completed years 
(e.g., 1-5 = primary), farm size included owned/leased 
land, and annualized income. Mobile use was classified as 
traditional, smartphone, or none. 

Data Analysis
Microsoft Excel was used to compile data and SPSS 
(Version 25) was used to analyze SPSS. Characteristics 
and adoption levels were summarized in the descriptive 
statistics (means, frequencies, and percentages) and 
shown in tables and figures. We evaluated the association 
of  independent variables with adaptation by using Chi-
square tests (p<0.05). 

RESULTS AND DISCUSSION
Socio-Demographic and Farm Characteristics
The adoption of  e-technology in Charpara village, 
Laxmichar Block, was studied through a survey of  50 
farmers who gave their socio-demographic background 
alongside their farm characteristics (Figure 1). The 
farmers selected in Charpara village mainly belonged to 
the following age groups: Under 20 years (12%) and 21–
30 years (18%), 31–40 years (32%), 41–50 years (26%), 

Figure 1: Socio-demographic and farm characteristics (a. Age, b. Education, c. Vegetation, d. Land owned, e. 
Occupations) of  Jamalpur



Pa
ge

 
83

https://journals.e-palli.com/home/index.php/ajsts

Am. J. Smart. Technol. Solutions 4(2) 80-86, 2025

and Above 50 years (12%) (Figure 1a). The participants’ 
educational levels largely consisted of  farmers who had 
1–5 years of  schooling (46%) while 13 participants (26%) 
completed 6–8 years of  education and 7 people (14%) 
finished 9–10 years of  schooling and 5 participants 
(10%) obtained 11–12 years of  schooling and two 
individuals (4%) finished university (Figure 1b). Figure 1c 
demonstrates that farm size differences existed between 
the farmers since 25 respondents (50%) maintained fields 
of  ≤0.5 hectares while 10 others (20%) possessed 0.6–1 
hc, 6 participants (12%) cultivated 1.1–1.5 hc and 5 (10%) 
controlled 1.6–2 hc and 4 subjects (8%) controlled >2 
hc. The survey revealed that rice cultivation occurred in 
20% of  farms, vegetables were grown in 70% of  farms, 
and wheat cultivation existed in 10% of  operated land. 
Farmers worked with annual incomes ranging from 
40,000–45,000 BDT (50%) and 60,000–100,000 BDT 
(26%) and 110,000–150,000 BDT (12%) while 160,000–
200,000 BDT (8%) was also present and >200,000 BDT 
(4%) (Figure 1d & e).
Statistics confirmed the existence of  meaningful 
relationships between social and demographic profiles 
and the adoption of  e-technology. Results indicated 
e-technology adoption strengthened as farmers became 
younger (χ² = 8.12, p < 0.05) obtained higher education 
levels (χ² = 10.34, p < 0.01) worked on larger farms (χ² 
= 6.78, p < 0.05) and earned higher income (χ² = 7.45, 
p < 0.05).
The age characteristics demonstrate how younger farmers 
between 21 to 40 years (50% of  those surveyed) show 
greater willingness to adopt digital technologies because 
they grew up using these tools and accept changes more 
readily. Youth populations act as the primary drivers 
of  ICT integration in agriculture across global regions 
because they actively pursue innovative approaches for 
enhancing flood-affected agricultural areas like Jamalpur 
(Kashem et al., 2013; Akter & Tan, 2023). The majority 
of  farmers above 40 years exhibited lower adoption 
rates since they depended on traditional practices and 
exhibited doubts about new strategies which is a typical 
resistance point in rural areas. Education and adoption 
show a robust relationship which demonstrates how 
literacy enables people to use digital platforms according 
to Mumuni et al. (2023). The app Krishoker Janala loses 
its impact because most farmers (72% of  the sample) 
possess less than eight years of  education and struggle to 
understand its functionalities (Akter & Tan, 2023).
The reduction of  Bangladesh’s fertile land area due to 
population growth explains why many farms measure 
less than one hectare. Most of  Charpara’s agricultural 
area (70%) consists of  vegetables because vegetable 
cultivation takes advantage of  the region’s excellent 
productive soil enriched by floods. These high-priced 
crops miss market performance improvement potential 
because they lack digital support methods (Chowhan 
& Ghosh, 2020). The adoption gaps worsen because 
farmers with incomes higher than the 100,000 BDT/
year threshold are more likely to use technology. In 

contrast, disadvantaged farmers have limited resources 
for agricultural development.

E-technology Adoption Patterns
Figure 2 reveals adoption patterns which show mobile 
phone structure among the farmers, as 30% used 
smartphones, 50% used traditional cell phones, and 
another 30% did not possess a phone (Figure 2a). 
Of  the study participants who used smartphones to 
access e-technology for agriculture purposes there 
were 15 farmers but 20 traditional phone users used 
their devices for personal communication (Figure 2b). 
Twelve farmers out of  the total 50 participants (24%) 
signed up for Krishoker Janala applications whereas 
only 3 farmers (6%) joined Krishi Batayon (Figure 2c). 
The primary influencers for using these e-technology 
apps were recommendations from extension officers at 
20% and friends or relatives at 6% and self-interests at 
4% (Figure 2d). Among 50 interviewed farmers only 15 
(30%) used e-technology services, while the rest (35 or 
70%) did not (Figure 2e). The services allowed access 
through text messages for 10 users (20%) and email for 2 
people (4%) and social media for 3 people (6%) (Figure 
2f). Figure 2g demonstrates the low, medium, and high 
adaptation categories corresponded to 70%, 30%, and 
0%, respectively. Non-adopters make up 70% of  the 
population and half  of  all phones remain traditional used 
for non-farm needs because of  limited awareness and 
unaffordability which increases due to low literacy and 
limited income. Thirty percent of  participants adopted 
app membership while it matched government initiatives 
Krishi Batayon (Mohammad & Dey, 2024) yet adoption 
remained restricted due to insufficient extension services 
and poor promotional efforts since most adopters came 
from extension officer influence. Text messaging appears 
preferred (20%) above email or social media because 
such user-friendly interfaces suit contexts where literacy 
is low  (Mumuni et al., 2023) which should guide future 
tool design. 
Systemic problems become visible when no respondents 
show high adaptation (0%) because they face costly 
devices alongside connectivity issues along with training 
deficiencies (FAO, 2005). The low rate of  technology 
adoption in Jamalpur’s flood-prone area presents a 
wasted chance to boost productivity and resilience despite 
successful examples like India’s e-Choupal (Chowhan & 
Ghosh, 2020; Sheela & Chakravarthi, 2019).

Impacts of  E-technology Adoption
Table 1 indicated that 30% of  50 farmers received 
e-technology services in their farming activities. A 
total of  40% of  farmers employed e-technology for 
production support service while 26.67% chose fertilizer 
services and 33.33% adopted HYV (High-Yield Variety) 
technology. The survey revealed that no farmers 
employed e-technology for marketing, price information, 
storage, transportation or disaster management services. 
These services showed complete adoption lack since 



Pa
ge

 
84

https://journals.e-palli.com/home/index.php/ajsts

Am. J. Smart. Technol. Solutions 4(2) 80-86, 2025

rates were 0%. Astaapuram region’s e-technology 
adopters saved money (66.67%) and achieved success 
rates of  80% for their satisfaction with the services. Non-
adopters constituted 70% of  the total who continued 
with traditional approaches which resulted in no digital 
advantages. The E-technology system demonstrated 
significant effects on its users because production 
advancement (40%) assisted pest regulation and weed 
suppression and fertilizer solutions (26.67%) enhanced 
nutrition management and cut costs while decreasing 
ecological impact (World Bank, 2011). A small proportion 
of  farmers (33.33%) reported using HYV technology to 
boost their production volumes which proves necessary 
for small-scale agricultural food security although this 
number points to limited awareness about its benefits. The 
66.67% of  money savings indicate global efficiency gains 
(Beguedou et al., 2023) yet Jamalpur’s flood-vulnerable 

region shows a surprising absence of  monetary-saving 
uses for disaster management or marketing. The high 
satisfaction rate shows user approval of  e-technology 
yet the moderate success rate indicates profit limitations 
because the system provides only limited range of  services 
(Akter & Tan, 2023). Traditional farming practices used 
by non-adopters created higher production expenses 
and reduced outputs but demonstrated the potential 
advantages of  e-technology to close economic divisions 
between groups. Astonishing usage gap between farmers 
demonstrates the requirement to increase the adoption of  
e-technology to optimize agricultural development in the 
high-value vegetable systems characteristic of  Charpara 
(Kambar, 2023).

Environmental Implications
Adopters of  technology applied compound fertilizers 

Figure 2: E-technology adoption pattern



Pa
ge

 
85

https://journals.e-palli.com/home/index.php/ajsts

Am. J. Smart. Technol. Solutions 4(2) 80-86, 2025

accurately (26.67%) and better pest control practices 
(40%), thus reducing chemical pollution. Yet HYV 
technology (33.33%) improved their crop production 
yields. The group of  unadopters, who totaled 70%, failed 
to realize any positive effects on their methods and kept 
using their outdated procedures (Table 1).
Educational scientific data show that e-technology 
provides precise fertilizer application and pest control, 
which reduces flood-caused water contamination in 
Jamalpur’s river basin and prevents soil destruction 
(Chowhan & Ghosh, 2020). HYV use optimizes 
soil productivity by improving land productivity and 

addressing land shortages and changing climate conditions. 
Operation non-adoption increases environmental strain 
in this flood-prone area with a mounting population 
because it wastes resources (Ali & Roknuzzaman, 2013). 
The application of  e-technology shows potential as a 
sustainability framework to support development goals 
through conservation measures, which have worked in 
global ICT implementations (Rahman et al., 2020). This 
achievement demands successful barrier removal since 
the ecological advantages of  this technology need to be 
maximized for this susceptible agricultural system.

Table 1: Environmental implications
Support type Farmers using e-tech (%) Farmers not using e-tech (%)
Production Technology Support 40 60
Fertilizer Services Support 26.67 73.33
Saving Money by Adopting E-Tech 66.67 33.33
HYV Adoption Support 33.33 66.67
Other Problems Support 0 100
Irrigation Support 13.33 86.67
Marketing Support 0 100
Price Information Support 0 100
Storage Support 0 100
Transportation Support 0 100
Disaster Issue Support 0 100
Success of  E-Tech Services 66.67 33.33
Satisfaction of  E-Tech Users 80 20

Implications for Adoption of  E-Technology for 
Agriculture
This investigation within Charpara village in Laxirchar 
Block, Jamalpur District provides extensive insights 
regarding how e-technology can develop farming 
practices in Bangladesh by utilizing research frameworks 
and methodologies, demonstrating results, and 
suggesting strategies. Rural communities experience 
dual disadvantages of  low smartphone availability and 
inadequate education alongside weak infrastructure but 
achieve better yields and cost reductions when using 
digital tools, thus creating multiple theoretical and policy 
effects and economic and environmental implications 
that limit scalability. Theoretical analysis indicates it is 
essential for current adoption models to consider distinct 
rural contingencies, which include minimal farming 
operations coupled with low reading skills and weather 
threats, including floods. Younger farmers who possess 
updated knowledge combined with better access to 
resources currently implement such practices, indicating 
their potential to guide larger-scale changes in the future. 
Stronger policy intervention calls for better electricity and 
mobile infrastructure, affordable technology, and digital 
centers in rural areas to make digital tools accessible to 
farmers. The adoption rate would increase when designers 
create basic programs that match local requirements 
(Kashem et al., 2013; Misaki, 2024).

Through improved e-technology implementation, 
society has an opportunity to bridge gaps by providing 
economic well-being to poor farmers, thus giving them 
competitive advantages above traditional practices. When 
farmers combine their knowledge and resources through 
group sharing, their development accelerates while 
strengthening community bonds. The study identifies 
potential ecological benefits for the flood-prone Jamalpur 
region through smarter land management methods 
yet non-adopters limit the potential advantages from 
reaching scale. The likelihood of  e-technology expansion 
grows strong since devoted farming tools for vegetables 
need development alongside research to monitor its 
long-term outcomes in various Bangladeshi regions. 
E-technology can transform agriculture in Jamalpur by 
directing policy decisions while empowering farmers and 
protecting the environment if  officials eliminate existing 
implementation challenges. The study provides the 
necessary foundations to achieve the potential of  digital 
transformation in agriculture.

CONCLUSION
This study investigates the adoption of  e-technology 
for agricultural advancement in Jamalpur, Bangladesh, 
focusing on Charpara village, Laxirchar Block. Through a 
three-month study involving 50 farmers, the findings reveal 
that most farmers rely on traditional practices. At the same 



Pa
ge

 
86

https://journals.e-palli.com/home/index.php/ajsts

Am. J. Smart. Technol. Solutions 4(2) 80-86, 2025

time, e-technology adoption remains low due to limited 
digital infrastructure, financial constraints, and a lack of  
digital literacy. Farmers who adopt e-technology experience 
improved productivity, cost reductions, and better resource 
management, particularly in fertilizer application and pest 
control. However, a significant gap exists between adopters 
and non-adopters, perpetuating inefficient farming 
practices and exacerbating environmental stress. Non-
adopters continue using excessive agrochemicals, outdated 
irrigation methods, and inadequate land management, 
contributing to soil degradation, water contamination, 
and increased vulnerability to climate change impacts. 
To bridge this gap, targeted interventions are necessary, 
including government subsidies for smartphones and 
internet services, expansion of  digital literacy programs, 
and the development of  localized mobile advisory 
services. Additionally, integrating AI-driven decision-
support systems and precision agriculture tools can 
enhance resource efficiency and climate resilience. By 
addressing these challenges, policymakers can promote 
widespread adoption of  e-technology, fostering agricultural 
sustainability and reducing environmental degradation in 
vulnerable farming communities. The study underscores 
the urgency of  adopting digital agricultural solutions to 
enhance farming efficiency, minimize ecological risks, 
and empower rural farmers socio-economically. Future 
research should focus on the long-term impacts of  
e-technology adoption, scalability of  digital tools, and 
policy frameworks that facilitate a more inclusive digital 
transformation in agriculture.

REFERENCES 
Ahmed, M. (2023). ICTs in Smart Agriculture: Paths to 

Build SDGs of  Bangladesh. Asian Journal of  Advanced 
Research and Reports, 17(8), 10–19. https://doi.
org/10.9734/ajarr/2023/v17i8500

Akter, A., & Tan, K. H. (2023). Agro-Based Mobile 
Apps Adoption among Bangladeshi Farmers at the 
‘Hamlet’ of  Bangladesh – A Case Study of  Chandpura 
Village of  Barisal. Jurnal Komunikasi: Malaysian Journal 
of  Communication, 39(4), 324–339. https://doi.
org/10.17576/JKMJC-2023-3904-17

Ali,  a K. M. E., & Roknuzzaman, A. (2013). Rural 
Information Provision in Bangladesh : A Study on 
Development Research Network. Information and 
Knowledge Management, 3(10), 64–74.

Altarturi, H. H. M., Nor, A. R. M., Jaafar, N. I., & Anuar, 
N. B. (2023). A bibliometric and content analysis of  
technological advancement applications in agricultural 
e-commerce. In Electronic Commerce Research (Issue 
0123456789). Springer US. https://doi.org/10.1007/
s10660-023-09670-z

Anandaraja, N., Sankri, S. K., Sriram, N., & Venkatachalam, 
R. (2013). TNAU Agri Tech Portal : Content Design 
and Validation. CSI Communications, 20–24.

BBS. (2022). Population and Housing Census 2022, 
Preliminary report. Bangladesh Bureau of  Statistics, 
Government of  Bangladesh, 11. 

Beguedou, E., Narra, S., Afrakoma Armoo, E., Agboka, 

K., & Kongnine Damgou, M. (2023). E-Technology 
Enabled Sourcing of  Alternative Fuels to Create 
a Fair-Trade Circular Economy for Sustainable 
Energy in Togo. Energies, 16(9), 3679. https://doi.
org/10.3390/en16093679

Chowhan, S., & Ghosh, S. R. (2020). Role of  ICT on 
Agriculture and Its Future Scope in Bangladesh. 
Journal of  Scientific Research and Reports, June, 20–35. 
https://doi.org/10.9734/jsrr/2020/v26i530257

DAE. (2015). Agricultural Statistics.
Goode, W. J., & Hatt, P. k. (1952). Methods In Social Research. 

Tosho Printing Co. Limited, Tokyo, Japan.
Hasan, M. A., Mimi, M. B., Voumik, L. C., Esquivias, M. 

A., & Rashid, M. (2023). Investigating the Interplay 
of  ICT and Agricultural Inputs on Sustainable 
Agricultural Production: An ARDL Approach. Journal 
of  Human, Earth, and Future, 4(4), 375–390. https://
doi.org/10.28991/HEF-2023-04-04-01

Kambar, P. S. (2023). A Study on The Role of  
E-Technology to Tackle The Agricultural Distress 
In India. Aayushi International Interdisciplinary Research 
Journal (AIIRJ), 10(4), 53–57.

Kashem, M., Faroque, M., Ahmed, G., & Bilkas, S. 
(2013). The Complementary Roles of  Information 
and Communication Technology in Bangladesh 
Agriculture. Journal of  Science Foundation, 8(1–2), 161–
169. https://doi.org/10.3329/jsf.v8i1-2.14639

Misaki, E. (2024). Consolidation of  human factors 
limiting the success and sustainability of  e-Agriculture 
projects in sub-Saharan Africa. African Journal of  Science, 
Technology, Innovation and Development, 16(1), 64–78. 
https://doi.org/10.1080/20421338.2023.2259880

Mohammad, I., & Dey, N. C. (2024). Digital Agriculture 
Innovations in Bangladesh: A Situational Analysis 
and Pathways for Future Development. Thunderbird 
International Business Review, 49–60. https://doi.
org/10.1002/tie.22421

Mumuni, E., Alhassan, A., & Sulemana, N. (2023). Success 
Factors of  Electronic (E) Agriculture in Ghana: 
Lessons from MoFA and Cowtribe. Ghana Journal of  
Science, Technology and Development, 9(1), 2343–6727.

Niti, D. P. (2019). E-technology as an Aid for Agriculture: 
An Analytical View. Indian Journals, 8(1), 33–37.

Rahman, T., Ara, S., & Khan, N. A. (2020). Agro-
information Service and Information-seeking 
Behaviour of  Small-scale Farmers in Rural Bangladesh. 
Asia-Pacific Journal of  Rural Development, 30(1–2), 175–
194. https://doi.org/10.1177/1018529120977259

Sarker, M. R., Galdos, M. V., Challinor, A. J., & Hossain, A. 
(2021). A farming system typology for the adoption of  
new technology in Bangladesh. Food and Energy Security, 
10(3), 1–18. https://doi.org/10.1002/fes3.287

Sheela, K. S., & Chakravarthi, A. D. (2019). Smart 
farming with e: Technology. International Journal of  
Engineering in Computer Science, 1(1), 32–35. https://doi.
org/10.33545/26633582.2019.v1.i1a.8

World Bank. (2011). Connecting Smallholders to ICT In 
Agriculture Connecting Smallholders to Knowledge , 
and Institutions (Issue 64605).


