A TOE-Based Analysis of Modern Agricultural Technology Adoption in the Agri-Food Supply Chain

This study examines the key determinants influencing the adoption of modern agricultural technologies in the Agri-Food Supply Chain (AFSC) through the lens of the Technology-Organization-Environment (TOE) framework.By integrating scholarly literature and empirical evidence, the research explores how technological, organizational, and environmental factors such as cost, perception, access to extension services, credit availability, government support, and external pressures affect technology adoption.A sample of 145 respondents was selected using convenience sampling, and data were analyzed through descriptive analysis, correlation analysis, and multiple regression analysis using SPSS.The findings indicate that technological factors, particularly farmers' perceptions of cost-effectiveness and utility, play a crucial role in adoption.Additionally, organizational factors, including access to credit and extension services, serve as essential enablers, while environmental factors, such as government policies and market pressures, significantly impact adoption trends.Multiple linear regression results highlight perception as the most influential factor driving technology adoption.By offering empirical insights, this study contributes to enhancing agricultural productivity, strengthening food security, and promoting economic sustainability within the AFSC, ultimately fostering a more competitive and resilient agricultural sector.

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Publication Details

Journal
International Journal of Academic Research in Business and Social Sciences
Published
2025-09-04
DOI
https://doi.org/10.6007/ijarbss/v15-i9/26192
Primary Topic
Technology and Data Analysis
Type
article
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article

A TOE-Based Analysis of Modern Agricultural Technology Adoption in the Agri-Food Supply Chain

Nurudeen Abdul Rahman, Nur Fatin Munirah Aris, Nur Hazwani Muhammad Azam
International Journal of Academic Research in Business and Social Sciences
Technology and Data Analysis
article

A TOE-Based Analysis of Modern Agricultural Technology Adoption in the Agri-Food Supply Chain

Nurudeen Abdul Rahman, Nur Fatin Munirah Aris, Nur Hazwani Muhammad Azam
article en

Abstract

This study examines the key determinants influencing the adoption of modern agricultural technologies in the Agri-Food Supply Chain (AFSC) through the lens of the Technology-Organization-Environment (TOE) framework.By integrating scholarly literature and empirical evidence, the research explores how technological, organizational, and environmental factors such as cost, perception, access to extension services, credit availability, government support, and external pressures affect technology adoption.A sample of 145 respondents was selected using convenience sampling, and data were analyzed through descriptive analysis, correlation analysis, and multiple regression analysis using SPSS.The findings indicate that technological factors, particularly farmers' perceptions of cost-effectiveness and utility, play a crucial role in adoption.Additionally, organizational factors, including access to credit and extension services, serve as essential enablers, while environmental factors, such as government policies and market pressures, significantly impact adoption trends.Multiple linear regression results highlight perception as the most influential factor driving technology adoption.By offering empirical insights, this study contributes to enhancing agricultural productivity, strengthening food security, and promoting economic sustainability within the AFSC, ultimately fostering a more competitive and resilient agricultural sector.

International Journal of Academic Research in Business and Social SciencesVol. 15(9)
Openalex Percentile: Top 65%
Technology and Data Analysis
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A TOE-Based Analysis of Modern Agricultural Technology Adoption in the Agri-Food Supply Chain — Nurudeen Abdul Rahman, Nur Fatin Munirah Aris, et al. · International Journal of Academic Research in Business and Social Sciences (2025) | TGRS Research Map | TGRS