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

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.

Application of topsis, mairca and EAMR methods for multi-criteria decision making in cubic boron nitride grinding

“…The MCDM problem is solved by the TOPSIS method in the following order: The normalized values of k ij are calculated according to formula (2). The l ij normalized weighted values are determined using formula (3). Table 4 describes the converted and normalized matrix values in the TOPSIS method using the Entropy and MEREC methods for calculating the weights of criteria.…”

“…Multi-criteria decision making (MCDM) problem is used to find the best alternative among many different alter-natives. It is widely applied in medicine [1,2], business [3,4], rescue operations [5], weather forecasting [6,7], etc. Recently, this problem has been used for mechanical machining processes.…”

Intelligent Mobility in Smart Cities

“…Another contribution to the topic of city logistics is in the paper "A Multi-Criteria Decision-Making Approach for Ideal Business Location Identification" [8]. It searches for optimal placement of business within a city.…”

Evaluation of Occupational Health Risk Management and Performance in China: A Case Study of Gas Station Workers

“…Among the various multi-criteria approaches available, the Analytical Hierarchy Process (AHP) and Importance Performance Analysis (IPA) are the most recognized and reliable risk management tools [26]. That's why studies related to gas stations employ these methods frequently [27,28]. The AHP method was proposed by Saaty in 1977.…”