Factors Influencing Smart Farming Technology Acceptance in Community-Based Farming Organizations

― Focusing on knowledge acquisition and attitude formation through prior conditions and information-seeking behavior ―

Abstract

This study empirically clarifies how prior conditions and information-seeking behavior influence knowledge acquisition and attitude formation in the pre-adoption stage of Smart Farming Technologies (SFT) within community-based farming organizations, using a comparative analysis of adopter and non-adopter groups. The results indicate that larger cultivated areas and greater external engagement increase opportunities to observe local SFT use cases and to hear favorable peer evaluations, thereby promoting knowledge acquisition. Moreover, adopters exhibit strong expectations for labor saving, workload reduction, and the engagement of unskilled or younger operators, whereas non-adopters demonstrate pronounced concerns about machinery size incompatible with their field conditions. High-cost burden emerged as a common concern across both groups. These findings suggest that effective diffusion policies should support machinery sharing through inter-village collaboration, expand subsidies for outsourcing core operations, provide field visits and trial deployments tailored to regional characteristics, and encourage the development of compact, labor-saving machinery designed for small-scale or disadvantaged areas.