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Neighborhood selection for a newcomer via a novel BWM-based revised MAIRCA integrated model: a case from the Coquimbo-La Serena conurbation, Chile

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Date
2020
Author
Hashemkhani Zolfani, Sarfaraz
Ecer, Fatih
Pamučar, Dragan
Raslanas, Saulius
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Abstract
Nowadays, cities are developing differently according to their needs, limitations and certain strategic plans. Moreover, conurbation areas will be more common in so many countries like Chile when there are two or more cities developing one next to another, leaning on each other. In this atmosphere, typical residents live in a region or a neighborhood based on certain criteria, so they know how and where they are going to live. From another point of view, a newcomer is usually faced with a city full of contrasts which make things completely and surprisingly complicated. In order to illustrate this, a real case was selected based on the research field, qualitative and quantitative (real) data. The Coquimbo-La Serena conurbation and it’s regions as “Comuna (in Chile)” is a really suitable case to show the complexity of the study. In order to face the challenge, a new hybrid Multiple-Attribute Decision-Making (MADM) method is introduced based on the Best-Worst Method (BWM) and Multi-Attributive Ideal-Real Comparative Analysis (MAIRCA). The five best different neighborhoods as Comunas of the conurbation were analyzed based on the two main scenarios: having a private car or using only public transportation. To obtain more reliable results, a sensitivity analysis was made so as to determine the behavior of the proposed model against weight changes. Besides, the final results were compared with the other MADM methods, for example: Multi-Attributive Border Approximation Area Comparison (MABAC), VIsekriterijumsko KOmpromisno Rangiranje (VIKOR) and COmbinative Distance-based ASsessment (CODAS).
Issue date (year)
2020
URI
https://etalpykla.vilniustech.lt/handle/123456789/148661
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  • Straipsniai Web of Science ir/ar Scopus referuojamuose leidiniuose / Articles in Web of Science and/or Scopus indexed sources [7946]

 

 

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