The Impacts of Green Supply Chain Management and Product Innovation on Marketing Performance in Thailand’s Processed Food Industry

Abstract

This research investigates the synergistic relationships between Green Supply Chain Management (GSCM) practices and product innovation in marketing performance and organizational sustainability within Thailand’s processed food industry. Building upon Resource-Based View theory and Stakeholder Theory, this study addresses a critical gap in understanding how environmental practices interact with innovation strategies to create sustainable competitive advantages in emerging markets. The research employs a comprehensive mixed-methods approach, integrating qualitative insights from industry expert interviews with quantitative analysis through Structural Equation Modeling (SEM). Primary data were systematically collected from 300 strategically selected enterprises representing small (≤50 employees), medium (51–200 employees), and large-scale (>200 employees) operations across diverse product categories within Thailand’s processed food sector. The analytical framework examines three core GSCM dimensions—green purchasing, green production, and green distribution—alongside three innovation aspects—quality innovation, safety innovation, and sustainability innovation. Eleven hypothesized relationships were rigorously tested to examine direct and indirect effects on marketing performance indicators (sales growth, market share expansion, brand enhancement, customer satisfaction, and cost optimization) and organizational sustainability metrics (environmental impact reduction, regulatory compliance, competitive positioning, and resource efficiency). SEM results revealed that Green Production practices significantly enhance marketing performance (β = 0.16, p < 0.01), demonstrating the strategic value of environmentally responsible production processes in achieving market success. Conversely, Green Distribution exhibited negative effects on both marketing performance (β = −0.106, p < 0.10) and organizational sustainability (β = −0.152, p < 0.05), indicating potential operational trade-offs and infrastructure limitations that require strategic optimization. The model demonstrated excellent fit indices (GFI = 0.929, CFI = 1.000, TLI = 1.000, RMSEA = 0.000, RMR = 0.034), validating the theoretical framework’s robustness. However, modest explanatory power (R2 MP = 0.050, R2 OS = 0.029) suggests that additional contextual factors, firm-specific capabilities, and market dynamics significantly influence these outcomes, warranting future investigation of mediating and moderating variables.