Investigation of a three-sided stable matching model for shared manufacturing green innovation ecosystem and its implementation perspectives

Driven by advancements in Industry 5.0, the shared manufacturing green innovation ecosystem (SharedMfg-GIE) has emerged as a novel paradigm that involves multi-platforms to provide customized matching. Concurrently, to avoid resource waste and monopolies, three-sided stable matching has become essential for ensuring precise matches. While previous literature focuses on supply–demand matching in isolated SharedMfg platforms that prioritize profitability, it often ignores sustainability and human well-being. This study proposed a novel three-sided stable matching model for SharedMfg-GIE. Firstly, owing to cognitive imprecision and reference dependence, hesitant fuzzy (HF) multiple reference points based on weak and strong composite indicators (MRP-WSCI) are presented for effective satisfaction evaluation. It creatively combines HF sets, achievement scalarizing function (ASF), and Kano, which offer greater advantages in expressing psychological disparity and attribute compensation relationship. On this basis, the matching model that consists of coupling coordination degree and matching state is established, which supports balanced synergy among matching parties. The proposed model is applied to the three-sided stable matching in Haier Sino-German Ecological Park. The results indicated that the average value of three-sided matching was 0.404, indicating relative adequacy of matching supply with demand. This study assists policymakers in formulating targeted strategies to optimize the ultra-flexible matching process.