Decision Support System for Store Location Selection in Retailing

In the retail industry, many companies strive for excellence by increasing their productivity, aiming for more suitable target customers, etc. However, these are just a few of the examples that these companies need to consider while developing their business. Each decision must be well-analyzed and deeply investigated before execution, especially for the long-term decisions such as store location selection. For retailers, selecting an appropriate store location is rather complex due to occasion-specific micro and macro factors. Accordingly, this paper addresses this issue by, first, analyzing the literature about these factors. Then, appropriate methods are analyzed and chosen to form a structure for the suggested decision-making model. To apply these methods, which are Fuzzy AHP, TOPSIS, and set covering optimization model, a real bookstore is taken as an example with the appropriate data, and MS Excel and PYTHON are used to fully implement each method. Finally, all steps are combined to design the overall system, which acts as an information system, with its interface. Overall, this paper contains valuable insights about the retail environment, location selections and so forth. The decision support system designed in this paper should help retailers to make better location selection decisions, helping them also by reducing the amount of time and resources that they need to consume, ultimately benefiting the entire society by increasing the accessibility of goods and services.