Examining the key influences on farmers' intentions to adopt Smart Farming Technology

Dilleen, Gráinne (2023) Examining the key influences on farmers' intentions to adopt Smart Farming Technology. Doctoral thesis, SETU Waterford.

Text Grainne Dilleen - Final Doctoral Study 2024.pdf Download (6MB)

Abstract

Smart Farming Technology (SFT) has been recognised as a potential solution to the many challenges facing the agricultural sector. SFT is information and communication technologies, and smart devices deployed on-farm to help optimise operations. However, the adoption rate of SFT has been slower than expected. The overarching objective of this study was to identify and examine the factors influencing the farmer’s behavioural intention (BI) to adopt SFT. The research sought to develop and empirically test a model to advance substantive theory. The Technology Acceptance Model (TAM) served as the guiding framework. A series of hypotheses were developed, based on the extant literature. A deductive approach was undertaken, using a cross-sectional study to test the validity of the hypotheses. An online survey was used for data collection, yielding two hundred and seventeen valid responses from farmers. Confirmatory factor analysis and structural equation modelling were used to test the hypothesised relationships between variables. Overall, the findings confirm that the farmer’s BI to adopt SFT is directly influenced by the perceived usefulness (PU) of the technology and the personal innovativeness (PIIT) of the farmer. PU had the strongest relationship with BI, thus demonstrating the importance of highlighting the increased efficiency and productivity delivered by SFT. PIIT also directly influenced the PU and perceived ease of use of SFT, indicating the need to develop innovativeness as a personality trait in farmers. Social influence directly affected PU, determining the importance of the farmer’s network in shaping perceptions of SFT. Finally, PU had a positive, direct influence on trust in the SFT vendor. The major theoretical contribution is the development of a novel, integrated model which empirically verifies the key influences on the farmer’s BI to adopt SFT. Furthermore, the research advances TAM by including additional antecedent variables to increase its explanatory and predictive power.

Item Type:	Thesis (Doctoral)
Uncontrolled Keywords:	Agriculture, smart farming technology
Departments or Groups:	*NONE OF THESE*
Divisions:	School of Business > Department of Management and Organization
Depositing User:	Derek Langford
Date Deposited:	21 Oct 2024 12:47
Last Modified:	21 Oct 2024 12:47
URI:	https://repository.wit.ie/id/eprint/7841

Actions (login required)

View Item