Tanzanian Farmers’ Intention to Adopt Improved Maize Technology: Analyzing Influencing Factors Using SEM and fsQCA Methods

Abstract

The China–Tanzania Village-based Learning Center for Poverty Reduction project aims to demonstrate China’s experience in poverty reduction through developing smallholder agriculture at the village level, and through the promotion of improved technologies with the purpose of increasing agricultural productivity and improving village-level agricultural production. However, to promote technology application effectively, a better understanding of farmers’ behavioral intention toward improved maize technology is needed. This study uses microdata from 282 Tanzanian maize farmers. Compared with previous research, the innovation of our study is that the methods of structural equation model (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) are applied to study the influencing factors of farmers’ intention to adopt improved maize technology and the combination paths that affect farmers’ intention. The analysis results show that farmers’ behavior perceptions and compatibility perceptions positively impact their intention to choose agricultural technology. Three modes can trigger farmers’ intention to adopt technology: “behavior perception, compatibility perception, non-self-efficacy, facilitation conditions,” “behavior perception, social impact, non-self-efficacy, facilitation conditions,” and “compatibility perception, social impact, self-efficacy, facilitation conditions.” To increase maize yield and promote the extension of improved agricultural technology through the China–Tanzania Village-based Learning Center for Poverty Reduction project, it is necessary to choose an effective combination path to influence farmers’ intention to adopt the proposed changes. If farmers’ intention to adopt improved maize technology can be increased to a greater extent, it can accelerate the improvement of agricultural technology in Tanzania, thereby increasing agricultural productivity, improving agricultural production at the village level, and reducing poverty.