International Journal of Strategic Property Management (May 2024)

Extracting and prioritizing the attractiveness parameters of shopping centers under intuitionistic fuzzy numbers

  • Alireza Bakhshizadeh,
  • Abdolreza Yazdani-Chamzini,
  • Masoumeh Latifi Benmaran,
  • Jonas Šaparauskas,
  • Zenonas Turskis

DOI
https://doi.org/10.3846/ijspm.2024.21376
Journal volume & issue
Vol. 28, no. 2

Abstract

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Shopping center plays an important role in distribution system and marketing. These canters provide an appropriate atmosphere for customers; so that, the customers achieve the best service within a short time. However, there is an intense competition among shopping centers to attract more customers for increasing the profit. Therefore, a powerful model assists authorities in identifying the critical competitive aspects and directing their efforts toward performance improvement. However, a number of strategies have been developed to identify the most relevant components. The Delphi technique under intuitionistic fuzzy environment, called intuitionistic fuzzy Delphi method (IFDM) study, is a group-based technique that can simply formulate the uncertainty imposed by decision making circle. On the other hand, multi criteria decision making (MCDM) method such as analytical network process (ANP) is a mathematical tool for taking into account mutual relationships in order to rank a number of criteria. Nonetheless, the ANP is unable to account for the uncertainty involved in the decision-making process. Similarly, the intuitionistic fuzzy set (IFS) can express ambiguity and vagueness by utilizing the given scale. Because the IFS is robust in dealing with complexity and ambiguity, the IFS-GANP (an integrated model of the IFS and ANP methods under group decision) can result in a more specific description of the situation. As a result, the IFS-GANP approach outperforms both conventional ANP and fuzzy ANP. To demonstrate the model’s feasibility, a case study rating the essential aspects impacting the attractiveness of retail centers is shown. The result demonstrates factor C31 (Location) with value of 0.202 plays the greatest role in attracting customers.

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