Development of the Socio-Technical System Framework for Hybrid Echelon Utilization of Power Batteries: A Fuzzy DEMATEL-IPA Hybrid Approach

Echelon utilization of power batteries serves as a crucial pathway to achieving resource recycling and reducing environmental impacts. However, its large-scale development is constrained by the cognitive disparities between formal enterprises and new energy vehicle (NEV) owners. Previous studies have largely proceeded from single technological, economic, or policy dimensions, relying on quantitative data or a single-stakeholder perspective, while neglecting the fuzziness and subjective uncertainty inherent in the qualitative judgments of corporate experts, and failing to effectively integrate the opinions of vehicle owners. To address these shortcomings, this study constructs a hybrid evaluation framework that integrates Fuzzy DEMATEL with Importance-Performance Analysis (IPA). Through content analysis and Exploratory Factor Analysis (EFA), we distill key criteria and underlying dimensions. We collect both importance ratings and performance scores from corporate experts and NEV owners respectively, and compare the IPA results of the two groups. This study contributes in the following aspects: (1) It establishes a multi-dimensional analytical framework covering both technical and social dimensions, thereby enriching the application of Socio-Technical Systems Theory in the field of echelon utilization; (2) A hybrid method integrating Fuzzy DEMATEL and IPA is proposed, in which the centrality of each criterion calculated by DEMATEL serves as the importance indicator in IPA. This approach effectively handles the fuzziness inherent in experts’ linguistic evaluations and the interdependencies among criteria, and reveals the cognitive differences between the two parties through comparative analysis; (3) Based on the dual-perspective comparison, the analytical results show that while both parties share consensus on certain technical capabilities, significant cognitive divergences exist regarding policy incentives and backend technology investment, providing a scientific basis for enterprises to optimize resource allocation.