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Bilateral matching for collaborative remanufacturing services based on multi-attribute preferences and mutual interactions

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Abstract

The traditional partner selection in reverse logistics focuses on selecting recyclers for remanufacturers, but neglects the selection of remanufactures for recyclers and the mutual matching of the two parties. This is not conducive to forming a sustainable service chain and providing collaborative remanufacturing service solutions for users. In this work, a multi-attribute bilateral matching framework is proposed in accordance with the collaboration between recycling and remanufacturing services. Given the interdependence among service matching attributes and the psychological behavior of decision makers under vague matching surroundings, an integrated methodology is developed to determine service matching satisfaction, which incorporates grey theory, Best–Worst Method, Decision Making Trial and Evaluation Laboratory and an acronym in Portuguese of Interactive and Multi-Criteria Decision Making. On this basis, a collaboration-oriented bilateral matching model concerning recycling and remanufacturing services is constructed with the objectives of maximizing matching satisfaction of remanufacturers and recyclers, as well as achieving service synergy effect. Afterwards, linear weighting method is used to solve the model, and thus the optimal service matching scheme is obtained. The results of the present work provide some references for the optimal allocation of service resources and the transition from traditional remanufacturing into collaborative remanufacturing service.

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Acknowledgements

This work was supported by the National Key R&D Program of China (Grant No. 2018YFB1701400); Foshan Technological Innovation Project (1920001000041); and the National Natural Science Foundation of China (Grant No. 61973108).

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Correspondence to Liqun Zhang.

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The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Appendices

Appendix A

See Tables 9, 10, 11, 12.

Table 9 Matching criteria data on recyclers and remanufactures
Table 10 Information sharing times between recyclers and remanufacturers
Table 11 Transactions times and transactions volume between recyclers and remanufacturers
Table 12 Geographical distances between recyclers and remanufacturers

Appendix B

See Tables 13, 14, 15, 16, 17, 18.

Table 13 BO Vectors of recycling service attributes for 5 remanufacturers
Table14 OW Vectors of recycling service attributes for 5 remanufacturers
Table 15 BO Vectors of remanufacturing service attributes for 7 recyclers
Table 16 OW Vectors of remanufacturing service attributes for 7 recyclers
Table 17 BO Vectors of collaboration attributes given by five experts
Table 18 OW Vectors of collaboration attributes given by five experts

Appendix C

The corresponding software in the calculation is as follows: MATLAB R2020b (BWM, DEMATEL and TODIM), and CPLEX 12.9 (solving the bilateral matching optimization model).

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Liu, X., Zhang, L., Deng, Q. et al. Bilateral matching for collaborative remanufacturing services based on multi-attribute preferences and mutual interactions. J Intell Manuf 35, 1353–1372 (2024). https://doi.org/10.1007/s10845-023-02111-6

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  • DOI: https://doi.org/10.1007/s10845-023-02111-6

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