African Journal of
Agricultural Research

  • Abbreviation: Afr. J. Agric. Res.
  • Language: English
  • ISSN: 1991-637X
  • DOI: 10.5897/AJAR
  • Start Year: 2006
  • Published Articles: 6429

Full Length Research Paper

Factors affecting the adoption of mobile applications by farmers: An empirical investigation

Victor Okoroji
  • Victor Okoroji
  • Depart Department of Agribusiness and Markets, Faculty of Agribusiness and Commerce, Lincoln University, P.O Box 85084, Lincoln 7647, Christchurch, New Zealand.
  • Google Scholar
Nic J Lees
  • Nic J Lees
  • Depart Department of Agribusiness and Markets, Faculty of Agribusiness and Commerce, Lincoln University, P.O Box 85084, Lincoln 7647, Christchurch, New Zealand.
  • Google Scholar
Xiaomeng Lucock
  • Xiaomeng Lucock
  • Depart Department of Agribusiness and Markets, Faculty of Agribusiness and Commerce, Lincoln University, P.O Box 85084, Lincoln 7647, Christchurch, New Zealand.
  • Google Scholar


  •  Received: 15 April 2020
  •  Accepted: 11 November 2020
  •  Published: 31 January 2021

Abstract

In developing countries such as Nigeria, agriculture is the main source of livelihood with over 70% of the population engaged in farming. They are mostly smallholders and subsistence farmers with minimal use of technology and low productivity. The use of mobile applications in agriculture can potentially help smallholders access agricultural information and financial services, improve access to markets and enhance visibility for supply chain efficiency. Unfortunately, due to a lack of uptake of these applications many farmers have not realized the benefits of this technology. This study seeks to explore and examine the factors that affect the uptake of this technology. A conceptual model which builds on the extended Technology Adoption Model (TAM2) was empirically estimated using Structural Equation Modelling (SEM) to examine the factors that influence the adoption of mobile applications. Primary data were collected from a sample of 261 farmers. Data were analyzed using SEM with the help of IBM SPSS and IBM AMOS software. The structural model showed that seven of the hypothesized relationships in the research model were supported. Social influence (SI), Perceived usefulness (PU), Information/awareness (IA) and Intention to use (ITU) affected the Actual Use (AU) of mobile applications positively, while Perceived risk (PR) and Perceived cost had a negative impact on their adoption. This study contributes to the literature on farmers’ technology adoption. It provides evidence that the extended TAM is a suitable model to explain the factors that influence mobile application adoption behavior. 

Key words: Mobile applications, smartphone, Information Communication Technologies (ICT) adoption, structural equation modelling, extended technology adoption model.