How to Evaluate New Quality Productive Forces for Chinese Express Delivery Enterprises: A Hybrid DEMATEL-BBWM-CoCoSo Method

Junchi Ma; Zhenheng Hu; Qiaoyuan Zhang; Siyue Zhao

doi:10.31181/dmame8220251501

Authors

Junchi Ma School of Transportation Engineering, East China Jiaotong University, Nanchang 330013, China
Zhenheng Hu School of Transportation Engineering, East China Jiaotong University, Nanchang 330013, China
Qiaoyuan Zhang School of Transportation Engineering, East China Jiaotong University, Nanchang 330013, China
Siyue Zhao School of Transportation Engineering, East China Jiaotong University, Nanchang 330013, China

DOI:

https://doi.org/10.31181/dmame8220251501

Keywords:

Multi-Criteria Decision Making; New Quality Productive Forces; Bayesian Best-Worst Method; CoCoSo

Abstract

The integration of New Quality Productive Forces (NQPF), characterised by innovation, advanced technology, operational efficiency, and high-quality outputs, is transforming express delivery enterprises in China. Conventional performance evaluation systems are increasingly inadequate for assessing the evolving requirements associated with NQPF. To address this gap, this study proposes a comprehensive evaluation framework encompassing three principal dimensions: strategic leadership, technological innovation, and development support. A hybrid Multi-Criteria Decision Making (MCDM) approach, incorporating DEMATEL, Best–Worst Method (BBWM), and Combined Compromise Solution (CoCoSo), is employed to account for interdependencies among evaluation indicators, improve the precision of weighting, and maintain consistency in group decision-making, thereby enhancing the reliability of performance assessments. A case study of five major A-share listed Chinese express delivery firms illustrates the practical application of the proposed framework. The methodology provides a rigorous decision-support tool for evaluating NQPF and yields strategic insights to facilitate sustainable development within the express delivery sector. By aligning the advancement of NQPF with broader industry quality improvements, the study delivers actionable recommendations for modernising China’s logistics industry through innovation-driven productivity transformation.

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