Transformations  in
Business & Economics

PARTNER SELECTION FOR AUTOMOBILE MANUFACTURING ENTERPRISES WITH A Q-RUNG ORTHOPAIR FUZZY DOUBLE NORMALIZAION-BASED MULTI-AGGREGATION METHOD¹
Huchang Liao, Junfeng Xue, Mehrbakhsh Nilashi, Xingli Wu, Jurgita Antucheviciene

ABSTRACT. Practical multi-criterion decision-making problems about partner selection are usually composed of both quantitative and qualitative criteria. To solve such problems, this paper develops a ranking method, named the q-ROF-DNMA method, based on the double normalization-based multi-aggregation (DNMA) method and a distance measure of q-rung orthopair fuzzy numbers (q-ROFNs). The values of quantitative criteria are expressed as numerical numbers, while the information on qualitative criteria is described by the q-rung orthopair fuzzy set (q-ROFS) which can describe inaccurate and uncertain information effectively. A distance measure is proposed to process the q-ROF information such that both quantitative and qualitative data can be integrated in a collective decision matrix. In addition, we combine three aggregation techniques with two target-based normalization methods to develop three subordinate utility functions under the q-rung orthopair environment. Next, an integration method is introduced to aggregate the utility values and subordinate ranks of alternatives to measure their comprehensive performances. Finally, the superiority of the proposed method is illustrated by comparative analysis based on a case study concerning the partner selection in an automobile manufacturing enterprise.

KEYWORDS:  multiple criteria decision making, partner selection, automobile manufacturing enterprise, double normalization-based multi-aggregation method; q-rung orthopair fuzzy set, distance measure.

¹Acknowledgments: The work was supported by the National Natural Science Foundation of China (71771156, 71971145).