Investigating farmers’ adoption of mobile Agri-Tech: A TAM-Based study of KaseChar in Eastern Thailand

IF 3.1 Q1 Social Sciences
Eain Dray Aung , Nophea Sasaki , Takuji W. Tsusaka , Chaklam Silpasuwanchai
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Abstract

Addressing agricultural waste through digital innovation is vital for mitigating environmental harm and supporting sustainable farming. This study examines the adoption of KaseChar, a mobile application designed to reduce open-field burning and promote agriwaste management among Participatory Guarantee System (PGS) farmers in Chachoengsao Province, Eastern Thailand. Using the Technology Acceptance Model (TAM), we evaluated perceived usefulness (PU), perceived ease of use (PEOU), and behavioral intention (BI) through a structured survey of 150 farmers. Results show high ratings for PU (mean = 4.11), PEOU (mean = 4.08), and BI (mean = 4.03), with key adoption drivers including productivity, efficiency, digital proficiency, and social influence. Exploratory Factor Analysis identified efficiency, usability, and public support as core factors. Waste management cost significantly influenced PU (β = 0.126, p = 0.009), while internet usage was positively correlated with PEOU (β = 0.252, p = 0.002). Despite high smartphone access, barriers such as digital literacy, labor intensity, and infrastructure gaps—particularly among older farmers—limit adoption. The study recommends targeted training, subsidies, and digital infrastructure improvements to scale adoption. It also contributes to TAM literature by integrating contextual variables like digital readiness and financial capacity. Future research should explore long-term behavioral impacts and conduct multi-regional comparisons to enhance scalability and generalizability of findings.
调查农民对移动农业技术的采用:基于tam的泰国东部KaseChar研究
通过数字创新解决农业废弃物问题对于减轻环境危害和支持可持续农业至关重要。本研究考察了KaseChar的采用情况。KaseChar是一款旨在减少泰国东部chachengsao省参与性担保制度(PGS)农民露天焚烧和促进农业废弃物管理的移动应用程序。通过对150名农民的结构化调查,我们使用技术接受模型(TAM)评估了感知有用性(PU)、感知易用性(PEOU)和行为意图(BI)。结果显示,PU(平均= 4.11)、PEOU(平均= 4.08)和BI(平均= 4.03)的评分很高,主要采用驱动因素包括生产力、效率、数字熟练程度和社会影响力。探索性因素分析确定了效率、可用性和公众支持作为核心因素。垃圾管理成本显著影响PU (β = 0.126, p = 0.009),互联网使用与PEOU正相关(β = 0.252, p = 0.002)。尽管智能手机普及率很高,但数字素养、劳动强度和基础设施差距等障碍——尤其是在老年农民中——限制了智能手机的采用。该研究建议有针对性的培训、补贴和数字基础设施改善,以促进大规模采用。它还通过整合诸如数字化准备和财务能力等上下文变量,为TAM文献做出贡献。未来的研究应探索长期的行为影响,并进行多区域比较,以增强研究结果的可扩展性和普遍性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Global Transitions
Global Transitions Social Sciences-Development
CiteScore
18.90
自引率
0.00%
发文量
1
审稿时长
20 weeks
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