International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 186 - Number 38 |
Year of Publication: 2024 |
Authors: George Essah Yaw Okai, William Akotam Agangiba, Millicent Agangiba |
10.5120/ijca2024923953 |
George Essah Yaw Okai, William Akotam Agangiba, Millicent Agangiba . Assessment of Farmers’ Acceptance of Intelligent Agriculture System using Technology Acceptance Model. International Journal of Computer Applications. 186, 38 ( Sep 2024), 16-22. DOI=10.5120/ijca2024923953
Several known factors are hampering the acceptance of technology-enhanced farming practices such as precision agriculture and smart farming in developing countries. These factors include high initial cost, low access to technology infrastructure, unawareness of efficient technology use in farming and socio-cultural issues. As a result, farmers in many developing countries rely purely on traditional farm management methods. Unfortunately, these traditional practices are faced with several challenges such as the inability to predict adverse conditions before they occur. Besides such methods are suitable for small-scale farms. Technology-enhanced farming practices have been proven by research and reported as a means of improving farm management and agriculture yield in many advanced economies. This study presents the use of the Technology Acceptance Model (TAM) to assess farmers’ acceptance level of technology-enhanced farming practices in Tarkwa Nsuaem Municipality; an important mining district in Ghana. The proposed model was empirically tested using data collected from a survey of three hundred and forty (340) farmers in mining communities within the municipality. Structural equation modelling was used as the statistical technique to analyze the data to explain the acceptance. The general structural equation model, which includes perceived usefulness, perceived ease of use, attitude, and behavioural intention to use an intelligent agricultural system by farmers was developed based on TAM. The result proved that farmers’ perception of the ease of use of technology significantly impacts their perception of its usefulness in farming. It further showed that farmers’ intention to use technology for farm management would depend on their attitude towards its use. The model would provide the major stakeholders of agriculture with implications for the effective implementation of an intelligent agriculture system.