Neutrosophic bipolar fuzzy decision-based approach for developing sustainable circular business model innovation tools - Zaidan A.A.; Deveci M.; Alsattar H.A.; Qahtan S.; Shang W.-L.; Delen D.; Mourad N.; Mohammed Z.K. (Elsevier Ltd, 2025)
The circular economy (CE) has been identified as a possible catalyst for sustainable development by business, academics, and policymakers. To aid company developers in creating and improving business models that incorporate circularity, a variety of tools for circular business model innovation (CBMI) have been proposed. Nevertheless, the existing tools failed to consider sustainability or CE in their advancements. Currently, there is no research that has presented a complete dataset including all potential tools that may be created based on the CE? sustainability performance attributes. Moreover, there has been a dearth of research conducted to assess and model these tools in order to determine the most efficient ones, which has resulted in a research gap. This paper constructs a decision matrix of CBMI tools by intersecting 100 CBMI tools with 10 CE? sustainability performance attributes. The modeling of CBMI tools falls under Multiple Attribute Decision Making (MADM) due to the presence of many attributes, varying importance levels of these attributes, and the and variation in data. Thus, the fuzzy weighted with zero inconsistency (FWZIC) method is reformulated under neutrosophic bipolar fuzzy sets (NBFS) to determine the weight of CE's sustainability performance attributes. The matrix that has been constructed and the resulting weight values are fed into the CODAS method in order to model CBMI tools and identify the most sustainable tool. The results indicate that the NBFS-FWZIC method gave a weight value of 0.1031 to A7, which is the greatest weight value. On the other hand, A3 had the lowest weight value of 0.0944. The CODAS method modeled the 100 CBMI tools, with Tool39 being identified as the most sustainable tool and Tool26 as the least sustainable tool. The robustness and durability of the proposed method are evaluated using a sensitivity analysis, Spearman's rank correlation test, and comparison analysis. ? 2024 Elsevier Ltd