4.8 Article

Modelling the adoption of electronic vehicle diagnostic technology for vehicle repairs: A structural equation modelling approach

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ELSEVIER SCIENCE INC
DOI: 10.1016/j.techfore.2023.122449

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Theory of planned behaviour; Decomposed Theory of Planned Behaviour; Technology Acceptance Model; Electronic vehicle diagnostic technology; Vehicle repairs

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The introduction of emission legislation has increased innovations in vehicle fault diagnosis, but the adoption of Electronic Vehicle Diagnostic Technology (EVDT) is low in Ghana. This study develops an EVDT Acceptance Model (EVDTAM) based on the Technology Acceptance Model (TAM) and Decomposed Theory of Planned Behaviour (DTPB) to assess mechanics' intention and actual use of EVDT. A sample of 384 auto mechanics in Ghana was selected using a convenient sampling technique. The results support the hypotheses and indicate that technology facilitating conditions strongly predict intention to use EVDT and resource facilitating conditions strongly predict the adoption of EVDT. This study fills a research gap and provides practical and theoretical implications.
The introduction of emission legislation around the world has led to an increasing number of innovations including the use of on-board diagnostic techniques for pin-pointing faults on vehicles. Generally, the adoption of Electronic Vehicle Diagnostic Technology (EVDT) for the repair of vehicles is low in Ghana. The objective of the study was to develop an Electronic Vehicle Diagnostic Technology Acceptance Model (EVDTAM) to assess the mechanics' intention to use and the actual use of EVDT for the repair of vehicles. The model developed was derived from the original Technology Acceptance Model (TAM) by considering the technological factors (perceived ease of use and perceived usefulness), and Decomposed Theory of Planned Behaviour (DTPB). In this research, a convenient sampling technique was used to select a population of 384 auto mechanic master craftsmen from the Volta and Greater Accra Regions in Ghana where automobile repair workshops especially local and corporate garages were dominant. The results indicated that the majority of the structural relationships supported the hypotheses with positive significant links. The technology facilitating condition emerged as the strongest predictor of intention to use EVDT. The adoption of EVDT was strongly predicted by the resource facilitating conditions. The empirical findings of the study are a step forward towards filling the research gap given the fact that testing and validation of the EVDTAM model has not been performed by any other study. The proposed model was found acceptable per the requirements of measurement and structural model testing. Practical and theoretical implications were also discussed.

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