Learning innovation management to elevate labor competitiveness within the Thai food industrial sector - Chinbutr, Petch; Vuttisophon, Sujira; Saengnoree, Amnuay; Chamsuk, Wawmayura (Edelweiss Applied Science and Technology, 2026)
This research examines learning innovation management as a systemic framework for enhancing labor competitiveness in the Thai food industry. Amid increasingly volatile competition driven by automation, digital supply chains, and sustainability standards, this study develops a conceptual model linking key determinants, including learning innovation management, organizational factors, human capital investment, and upskilling and reskilling initiatives. A quantitative research design was employed, and data were collected from 340 professionals working in the Thai food sector. Structural Equation Modeling (SEM) was utilized to test the hypothesized relationships among variables. The findings reveal that learning innovation management has a significant direct influence on both upskilling and reskilling development, as well as on organizational readiness. However, its direct impact on competitiveness enhancement was not statistically significant. Instead, learning innovation management contributes indirectly to competitiveness through mediating variables, particularly human capital development and organizational capability. The overall model explains 49.7% of the variance in competitiveness enhancement (R² = 0.497). These results provide important implications for policymakers and industry leaders in designing effective learning systems that bridge skill gaps, strengthen workforce adaptability, and enhance long-term industrial competitiveness in the digital economy.