A HITS-based model for facility location decision

Document Type

Article

Abstract

This paper presents a model to the facility location problem which incorporates both location characteristics and rival effects within a business cluster. Location characteristics in the model are predefined selection criteria such as rent, distance, safety and size. Rival effects represent the competition and collaboration relationship among close facility locations in the business cluster where candidate locations are located. The model presented uses data envelopment analysis (DEA) and weighted hyperlink-induced topic search (HITS) algorithm. DEA determines the efficient and inefficient locations as well as benchmarking relationship. The weighted HITS algorithm with the distance parameter considers the rival effects among locations to identify hubs and authorities. The applicability of our proposed model is demonstrated with a case study that rank apartments in the University area.

Publication Title

Expert Systems with Applications

Publication Date

11-30-2020

Volume

159

ISSN

0957-4174

DOI

10.1016/j.eswa.2020.113616

Keywords

benchmarking, data envelopment analysis, facility location decision, HITS, ranking

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