Huiqiong Huang
College of Mechanical and Automotive Engineering, Guangxi University of Science and Technology, Liuzhou, China. & Faculty of Logistics and Digital Supply Chain, Naresuan University, Phitsanulok, Thailand.

Woramol Chaowarat Watanabe
Faculty of Logistics and Digital Supply Chain, Naresuan University, Phitsanulok, Thailand.

DOI https://doi.org/10.33889/IJMEMS.2026.11.1.003

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Abstract

Smart logistics parks (SLPs) drive economic growth but lack specialised maturity assessment frameworks. This study addresses this gap by developing a maturity assessment framework for SLPs, underscoring distinctions from the traditional logistics parks (TLPs) assessment model to guide the transformation toward smart logistics. The proposed framework comprises five main factors and twenty sub-factors: Smart Economy, Public Services and Smart Governance, Smart Infrastructure and Intelligent Technology Application, Skilled Human Capital, and Environmental Sustainability. These factors were identified through a literature review followed by expert consultations, while the TLPs model is based on China's national standard (2018). The Analytic Hierarchy Process (AHP) was applied to prioritize each factor in both TLPs and SLPs. The results indicate that for SLPs, Smart Infrastructure and Intelligent Technology Application (0.3229) is the most critical factor, followed by Public Services and Smart Governance (0.2447). At the sub-factor level, Smart Logistics Technology Coverage (0.1051) and Percentage of IT Investment (0.0796) are key factors for SLPs. In contrast, TLPs prioritise Service Capability (0.3317) and Operation Management (0.3317), with Customer Satisfaction (0.0639) and Logistics Operation Area (0.0475) as the most influential sub-factors. A comparative analysis reveals that while both models emphasize infrastructure, operational services, and environmental considerations, SLPs focus more on technological innovation and digital governance, whereas TLPs give priority to efficiency and service quality. The framework guides stakeholders, highlighting that SLPs' transformation requires integrating intelligent systems while maintaining efficiency and sustainability. Future research should validate the framework’s practical applicability through empirical case studies.

Keywords- Smart logistics parks, Maturity assessment model, Technology-driven supply chains, Digital transformation, Analytic hierarchy process (AHP).

Citation

Huang, H., & Watanabe, W. C (2026). A Comparative Analysis of Smart and Traditional Logistics Parks: A Maturity Model Perspective. International Journal of Mathematical, Engineering and Management Sciences, 11(1), 41-63. https://doi.org/10.33889/IJMEMS.2026.11.1.003.