Modelling the adoption of agro-advisory mobile applications: a theoretical extension and analysis using result demonstrability, trust, self-efficacy and mobile usage proficiency

Abstract

Purpose: This paper aims to explore the determinants of intention towards the use of agro-advisory mobile applications by extending the technology acceptance model (TAM) with addition of the following constructs: result demonstrability (RD), trust, self-efficacy (SE) and mobile usage proficiency (MUP). Design/methodology/approach: The study employed a survey on farmers (n = 446), which was analysed through structural equation modelling using Analysis of Moment Structures (AMOS). Findings: The results show that RD and farmer's trust on agro-advisory mobile apps (AAMA) positively impact their perceptions of usefulness. Also, farmer's SE and MUP positively affect their perceptions of ease of using AAMA. Further, interestingly, farmer's attitude towards the AAMA fully mediates the relationship between perceived usefulness and perceived ease of use on intention to use them. Research limitations/implications: Understanding the antecedents of agro-advisory mobile application offers a unique contribution to policymakers, private firms, and non-government organizations by proving key insights on the acceptance of agriculture based mobile technologies in context of developing nations. Originality/value: To the best of author's knowledge, this is one of the first research enquiries on the adoption of agro-advisory mobile applications. The new theoretical framework adds to the original TAM and offers novel insights that are helpful in augmenting the current understanding on AAMA and their acceptance by the beneficiaries.