Labor cost management approaches in the industrial sector for sustainable success

Thailand has consistently raised the minimum wage rate, which has affected the manufacturing industry that still relies heavily on labor. This ‎research aims to identify ways to manage labor costs and reduce their impacts in line with existing problems. It examines labor cost management approaches in the industrial sector for sustainable success and develops them into a structural equation model. The research was ‎conducted using both quantitative and qualitative methods. The quantitative research involved surveying executives from medium, small, ‎and large industrial businesses, using a questionnaire with 500 respondents. Descriptive statistics, reference statistics, and multivariate statistics were used for analysis. The qualitative research involved focus group discussions with 11 experts. The research findings revealed the ‎following key strategies for Labor Cost Management Approaches in the Industrial Sector for Sustainable Success, ranked in order of im-‎portance, composed of 4 aspects, with the most important item in each aspect: 1) Labor Management (X̅ = 4.33) creating a labor operations ‎manual, 2) Skill Labor Development (X̅ = 4.31), developing labor skills by offering opportunities to learn new skills, 3) Work process Im-‎provement (X̅ = 4.30), encouraging a positive attitude toward organizational change through effective, and 4) Innovation and Technology ‎‎(X̅ = 4.23), implementing technology systems to assist in monitoring work hours. Regarding the hypothesis testing results, it was found ‎that the strategies for managing labor costs towards sustainable success in the medium, small, and large industrial sectors did not differ significantly at the 0.05 statistical level. The results of the structural equation model analysis showed that the developed model met the evalua-‎tion criteria and was consistent with the empirical data, with a chi-square probability value of 0.076, a relative chi-square value of 1.138, a ‎goodness-of-fit index of 0.958, and a root mean square error of approximation value of 0.017‎.