A Multi-Criteria Decision-Making Approach for Ideal Business Location Identification

Salman Ahmed Shaikh,Kyoung-Sook Kim,Mohsin Memon

doi:10.3390/app11114983

Abstract

Location has always been a primary concern for business startups to be successful. Therefore, much research has focused on the problem of identification of an ideal business site for a new business. The process of ideal business site selection is complex and depends on a number of criteria or factors. Since the ultimate goal of all businesses is to increase customer footprints and to thus increase sales, criteria including traffic accessibility, visibility, ease of access, vehicle parking, customers availability, etc. play important roles. In other words, we can say that optimal business site selection is a multi-criteria decision-making (MCDM) problem. MCDM is used to identify an optimal solution or decision out of many alternatives by utilizing a number of criteria. In mathematics, there exist a number of structured techniques for organizing and analyzing complex decisions, for instance, AHP, ANP, TOPSIS, etc. In this work, we present a hybrid of two such techniques to solve the MCDM problem for an optimal business site selection given a set of candidate sites. The proposed approach is based on the AHP (Analytic Hierarchy Process) and TOPSIS (The Technique for Order of Preference by Similarity to Ideal Solution) approaches. The reason for using the proposed hybrid approach is multi-fold. The hybrid approach reduces the computational complexity and require less manual effort, thus improving the efficiency and accuracy of the proposed approach. Given a set of candidate locations for a new business, the proposed approach ranks the candidates. Thus, the candidate locations with higher ranks are identified as suitable or ideal. The approach comes up with the ranking of all of the candidate locations, thus giving business managers room to make calculated decisions. To show the effectiveness of the proposed approach, a detailed step-by-step case study is given to identify an ideal location in New York City for a new gas station. Furthermore, an experimental evaluation is also presented using a number of real New York City datasets.

Highlights

IntroductionThe location of a brick and mortar business plays a vital role in its success or failure
The location of a brick and mortar business plays a vital role in its success or failure.In order to keep investors happy and to avoid any financial losses, it is necessary to select an optimal site for a new business
The proposed work presented in this paper provides a hybrid Analytic Hierarchy Process (AHP)/TOPSIS approach for pointing out an optimal site to open a commercial store

Summary

Introduction

The location of a brick and mortar business plays a vital role in its success or failure. In order to keep investors happy and to avoid any financial losses, it is necessary to select an optimal site for a new business. The term “optimal” refers to a location that may be suitable for a new business and that yields paybacks. The identification of optimal sites does not depend on any one factor. There are several aspects that require consideration, such as competition in the area, the target customers’ convenience in terms of accessibility, the convenience of suppliers, traffic congestion in the area, etc. The selection of an optimal business site is a multi-criteria decision-making (MCDM) [1,2] problem

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