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Sports Complex Location Selection for Traditional Games
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  • Bita Arabnarmi,
  • Fateme Khalilian,
  • Siamak Kheybari,
  • Alessio Ishizaka
Bita Arabnarmi
University of Neyshabur

Corresponding Author:[email protected]

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Fateme Khalilian
University of Tehran
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Siamak Kheybari
University of Cambridge Department of Engineering
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Alessio Ishizaka
NEOMA Business School
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Abstract

The simultaneous consideration of various economic, social, and environmental factors in determining the proper location for constructing a sports complex for traditional games is crucial to the continuation of such events. This research takes a two-stage approach when studying where to locate such infrastructure. In the first stage, namely, that of ranking the locations, the criteria influencing the evaluation are categorized based on the research literature and on interviews with experts well-versed in social, economic, and environmental questions. The criteria identified in this stage are divided into two broad categories: intra-city (selecting the most suitable city) and inter-city (identifying the most suitable geographic area). The best geographical area for constructing a sports complex is found using intra-city criteria based on expert opinions. These opinions were obtained using an online questionnaire prepared according to the Best Worst Method (BWM), giving the weights of both categories. In an effort to assess the desirability of the cities under consideration, we apply piecewise linear pereference functions (PLPFs) to determine the ranges in which each of the items achieve their best score. In the second stage, i.e., the geographical area selection stage, and according to the weighting of inter-city criteria and the ideal distance to each criterion (e.g., fire stations and hospitals), the best geographical area for constructing a sports complex is selected using geographical information system (GIS). The results of this research confirm that social factors are more important than economic and environmental ones in the evaluation phase of the candidates and PLPFs produce different results vis- à-vis the existing linear methods.