A Comparative Analysis of Smart and Traditional Logistics Parks: A Maturity Model Perspective

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Authors: Huiqiong Huang, Woramol Chaowarat Watanabe
Cited by: 1
References: 64

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.

Fields of Study & Subjects

Urban and Freight Transport Logistics Outsourcing and Supply Chain Management Sustainable Supply Chain Management

Publication details

Journal / source
International Journal of Mathematical Engineering and Management Sciences
Publisher
Ram Arti Publishers
Volume
11
Issue
1
Pages
41–41
Publication date
4 January 2026
Language
EN