Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Internet of things platforms adoption in agriculture: comparative theoretical models

Internet of things platforms adoption in agriculture: comparative theoretical models The purpose of this study is to determine the farmers’ behavioural intention (BI) to adopt Internet of things platforms (IoT-P) in the agriculture context by comparing two well-known theories: the united theory of acceptance and use of technology (UTAUT), and the decomposed theory of planned behaviour (DTPB) with the integration of innovation resistance theory (IRT).Design/methodology/approachPurposive sampling was used to get responses from 267 potential farmers to examine their IoT-P adoption intention in Pakistan. The PLS-SEM, PLS model evaluation criterion and PLS model selection criterion were considered to determine the significance of path co-efficient, explanatory power, predictive power and more parsimonious model.FindingsThe findings demonstrate that DTPB is the best model with the extension of functional barriers (FBs) and psychological barriers (PBs). It has more predictive relevance and explanatory power. The results show that farmers’ attitude (ATT), based on the evaluation of three attributes (i.e. perceived usefulness (PU), perceived ease of use (PEOU) and compatibility (COMP)), is the strong predictor of farmers’ BI to adopt IoT-P. In addition, self-efficacy (SEF) and facilitating conditions (FC) peer influence (PI) and superiors’ influence (SPI) are required for adoption of IoT-P devices. Finally, FB and PB significantly and negatively influence the farmers’ BI to adopt IoT-P.Originality/valueThis research is the first to consider the two technology adoption models with the integration of IRT for explaining farmers’ BI in the context of agriculture. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Retail & Distribution Management Emerald Publishing

Internet of things platforms adoption in agriculture: comparative theoretical models

Download PDF
17 pages

Loading next page...
 
/lp/emerald-publishing/internet-of-things-platforms-adoption-in-agriculture-comparative-zi8Pwrhs8p

References (39)

Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
0959-0552
DOI
10.1108/ijrdm-10-2022-0420
Publisher site
See Article on Publisher Site

Abstract

The purpose of this study is to determine the farmers’ behavioural intention (BI) to adopt Internet of things platforms (IoT-P) in the agriculture context by comparing two well-known theories: the united theory of acceptance and use of technology (UTAUT), and the decomposed theory of planned behaviour (DTPB) with the integration of innovation resistance theory (IRT).Design/methodology/approachPurposive sampling was used to get responses from 267 potential farmers to examine their IoT-P adoption intention in Pakistan. The PLS-SEM, PLS model evaluation criterion and PLS model selection criterion were considered to determine the significance of path co-efficient, explanatory power, predictive power and more parsimonious model.FindingsThe findings demonstrate that DTPB is the best model with the extension of functional barriers (FBs) and psychological barriers (PBs). It has more predictive relevance and explanatory power. The results show that farmers’ attitude (ATT), based on the evaluation of three attributes (i.e. perceived usefulness (PU), perceived ease of use (PEOU) and compatibility (COMP)), is the strong predictor of farmers’ BI to adopt IoT-P. In addition, self-efficacy (SEF) and facilitating conditions (FC) peer influence (PI) and superiors’ influence (SPI) are required for adoption of IoT-P devices. Finally, FB and PB significantly and negatively influence the farmers’ BI to adopt IoT-P.Originality/valueThis research is the first to consider the two technology adoption models with the integration of IRT for explaining farmers’ BI in the context of agriculture.

Journal

International Journal of Retail & Distribution Management – Emerald Publishing

Published: Nov 11, 2024

Keywords: Competing models; Model selection criteria; Internet of things platforms (IoT-P) adoption; Psychological barriers (PBs); Functional barriers (FBs); Agriculture

There are no references for this article.