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Predictors of behavioral intention to adopt e-AgriFinance app among the farmers in Sarawak, Malaysia
British Food Journal ( IF 3.3 ) Pub Date : 2021-06-25 , DOI: 10.1108/bfj-04-2021-0449
Quistina Omar , Ching Seng Yap , Poh Ling Ho , William Keling

Purpose

This study examines the predictors of behavioral intention of farmers to adopt a mobile agricultural finance application called e-AgriFinance using the Unified Theory of Acceptance and Use of Technology (UTAUT) and perceived cost as an additional predictor.

Design/methodology/approach

Using a questionnaire survey, data are collected from 337 farmers in Sarawak, Malaysia. The collected data are analyzed using partial least squares structural equation modelling (PLS-SEM).

Findings

The research finds that performance expectancy, effort expectancy, social influence and facilitating conditions are positively related to behavioral intention to adopt the e-AgriFinance app, with social influence being the strongest predictor. Perceived cost is also found to be positively related to behavioral intention which contradicts the prediction of the model.

Research limitations/implications

This study contributes to the use of UTAUT in predicting the adoption of mobile agricultural finance applications among farmers.

Practical implications

For practice, this study provides implications for the Sarawak government to promote digital and financial inclusivity for all communities. This study also provides insights into important features of the e-AgriFinance app for digital finance providers to develop the apps that will be well accepted by farmers in the future.

Originality/value

This research is one of the few studies that focused on farmers' mobile technology adoption in agribusiness from the perspective of an emerging economy.



中文翻译:

马来西亚沙捞越农民采用 e-AgriFinance 应用程序的行为意向预测因素

目的

本研究使用技术接受和使用统一理论 (UTAUT) 和感知成本作为额外的预测因素,研究了农民采用名为e-AgriFinance的移动农业金融应用程序的行为意图预测因素。

设计/方法/方法

使用问卷调查,从马来西亚沙捞越的 337 名农民收集数据。使用偏最小二乘结构方程模型 (PLS-SEM) 分析收集到的数据。

发现

研究发现,绩效预期、努力预期、社会影响和便利条件与采用e-AgriFinance应用程序的行为意向呈正相关,其中社会影响是最强的预测因素。还发现感知成本与行为意图正相关,这与模型的预测相矛盾。

研究限制/影响

本研究有助于使用 UTAUT 预测农民对移动农业金融应用程序的采用。

实际影响

在实践中,这项研究为砂拉越政府促进所有社区的数字和金融包容性提供了启示。这项研究还为数字金融提供商提供了有关e-AgriFinance应用程序重要功能的见解,以开发未来农民会广泛接受的应用程序。

原创性/价值

这项研究是为数不多的从新兴经济体的角度关注农民在农业综合企业中采用移动技术的研究之一。

更新日期:2021-06-25
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