Antecedents to Thai Automotive Manufacturing Competitive Advantage: A Structural Equation Model Analysis

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Vithit Leenutaphong, Puris Sornsaruht, Samart Deebhijan, PhayatWutthirong

Abstract

The research was undertaken to develop a structural equation model (SEM) of how technological capabilities (TC),
knowledge management (KM), quality management (QM), and the supply chain (SC) affected the competitive advantage (CA)
of Thailand’s automotive and auto-parts manufacturing businesses. The research instrument was a questionnaire from which
data were collected from 515 automotive industry entrepreneurs and managers in Thailand. Subsequently, a confirmatory
factor analysis (CFA) was done using LISREL 9.1 to determine the model’s fit, followed by an SEM of the variables. The
results revealed that all causal variables in the model had a positive influence on CAwhich could jointly be explained by the
variance of factors influencing CA (R2) at 78%. The factors affecting CA (ranked from highest to lowest) were QM, the SC,
KM, and TC, with total effect(TE) values of 0.72, 0.68, 0.45, and 0.44, respectively. Therefore, to maintain Thailand’s
automotive leadership within ASEAN and maintain a CA on a global scale, this study’s entrepreneurs and managers felt the
key factor was their firm’s ability at QM. Specifically, QM should be focused on the quality management process and strategic
planning, as well as continual improvement and the focus on quality. These factors were closely followed by the SC and each
firm’s ability to provide good customer service, having a supply chain emergency plan and crisis management system, and
finally, an ongoing supply chain development process. The research also suggests that strategic partnerships with larger,
international SC vendors enable a more secure CA. Government policymakers also need to structure their support in a way that
addresses the needs of each type of firm’s TC. Moreover, research & development incubators need to be established, especially
in light of the Thai government's direction into EVs and the stated goal of 30% EV production by 2030. Universities and
vocational education institutions must also be given the means to prepare their next generat ion of knowledge workers for these
new technologies. Policy and direction also need to be focused, clear, and funded as well, if Thailand wants to retain its current
leadership grasp within the ASEAN automotive manufacturing and auto-parts community.

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How to Cite
Vithit Leenutaphong, Puris Sornsaruht, Samart Deebhijan, PhayatWutthirong. (2021). Antecedents to Thai Automotive Manufacturing Competitive Advantage: A Structural Equation Model Analysis. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12(14), 2279–2290. https://doi.org/10.17762/turcomat.v12i14.10645
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