How technology and work environment drive agricultural extension performance in Indonesia
Bibliographic Data
| ID | 22422698 |
|---|---|
| Authors | Hepi Hapsari (0000-0002-8001-7800, Padjadjaran University, corresponding author), Ahmad Choibar Tridakusumah (0000-0002-9282-9574, Padjadjaran University), Eka Purna Yudha (0000-0003-0365-9735, Padjadjaran University), Indra Irjani Dewijanti (0000-0003-3046-6226, Universitas Pendidikan Muhammadiyah Sorong), Iwan Setiawan (0000-0002-6004-350X, Padjadjaran University), Muhammad Azizurrohman (0000-0002-8559-5685, Southern Taiwan University of Science and Technology) |
| Year | 2026 |
| Pages | 1-21 |
| Publication date | 2026-05-26 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | The Journal of Agricultural Education and Extension (JOURNAL) |
| Journal identifiers | ISSN: 1389-224X • E-ISSN: 1750-8622 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/1389224x.2026.2667787 |
| OpenAlex | W7162405306 |
| Language | EN |
| References cited | 51 |
Purpose This study examines the factors influencing smart technology adoption among agricultural extension workers in Indonesia and evaluates its effect on performance outcomes.Design/methodology/approach A quantitative survey was conducted with 286 extension workers in West Java. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to assess six direct relationships.Findings Smart technology traits and work environment were the strongest predictors of adoption, followed by competencies, communication channels, and agent characteristics. Technology adoption significantly improved extension worker performance, emphasizing that actual usage, not just access, drives service effectiveness.Practical implications Policymakers should invest in user-centered tool design, infrastructure, and digital training tailored to regional needs. Extension organizations are advised to adopt continuous learning strategies and performance-based incentives. Technology developers should co-design tools with users and localize features for greater adoption.Theoretical Implications This study extends TAM and DOI by integrating organizational and communication factors, demonstrating that technology adoption in agricultural extension is shaped not only by perceived traits but also by institutional and contextual conditions.Originality/value This study extends TAM and DOI by incorporating organizational and communication variables and provides empirical evidence from Indonesia, a context rarely explored in the digital extension literature.
Agricultural communication · Agricultural education · Agricultural machinery · Agricultural productivity · Agriculture · Work environment · Agricultural Development and Management · Agricultural Research and Practices · Fisheries and Aquaculture Studies
When to use and how to report the results of PLS-SEM
A Theoretical Extension of the Technology Acceptance Model
Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology
Peer effects in agricultural extension
Public sector innovation in context
How agricultural extension services affect farmers’ adoption of climate-smart technology? Evidence from rural China
Information and communication technologies (ICTs)
Factors Affecting the Competence Level of Agricultural Extension Agents
Promoting Healthcare Workers’ Adoption Intention of Artificial-Intelligence-Assisted Diagnosis and Treatment
Adoption of agricultural technology in the developing world
Adaptive policy implementation
Systems approaches to public service delivery
| Citation velocity | historical |
|---|---|
| Highly cited | No |