A Novel 2-Tuple SAW-MAIRCA Method for Partner Evaluation for Circular Economy


Büyüközkan G., UZTÜRK BARAN D.

International Conference on Intelligent and Fuzzy Systems, INFUS 2021, İstanbul, Turkey, 24 - 26 August 2021, vol.307, pp.113-120 identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 307
  • Doi Number: 10.1007/978-3-030-85626-7_14
  • City: İstanbul
  • Country: Turkey
  • Page Numbers: pp.113-120
  • Keywords: 2-tuple linguistic model, Circular economy, GDM, Innovation, MAIRCA, MCDM, Partner selection, SAW

Abstract

© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.The circular economy is based on deploying the sources over and over to attain sustainable development. Disruptive technologies such as 4.0 technologies and innovation are the main enablers for a circular economy. This paper presents a novel linguistic-based evaluation model for partner selection. Partner selection holds a crucial role for companies since cooperation and collaboration are significant drivers for a circular economy. Collaboration with an innovative and sustainable partner will sustain a strategic competitive advantage in the market. In this paper, the evaluation framework is threatened as a multi-criteria decision-making (MCDM) mechanism. The Multi-Attributive Ideal-Real Comparative Analysis (MAIRCA) is extended with the 2-tuple linguistic model for the first time to emphasize the utilization of semantic series in the evaluation and selection mechanism. The 2-tuple model enables the illustration of results closer to person’s reasoning. Also, it augments the precision of the calculations with semantic variables, and it provides the interpretability of the results. The Simple Additive Weighting (SAW) method is recommended for criteria weighting, and MAIRCA is suggested for the partner evaluation. An assessment model is generated with five fundamental dimensions and their related requirements. They are developed from academic literature and industrial reports. Finally, a case study from a Turkish food company is presented with the results and their analysis. Plus, the comparative analysis for the suggested 2-tuple MAIRCA framework is provided to test the method’s robustness.