In a department store, customers have the opportunity to reach a wide range of consumer goods from different product categories within a single store area. Store layouts generally show the size and location of each department, any permanent structures, fixture locations, and customer traffic patterns. Determining the area sizes to be allocated to each product category and the layout of these areas in the department store is a strategic planning decision problem. The layout problem has been studied in the literature with different approaches where the sizes of the areas are known. The first purpose of this paper is to determine the area sizes of each product category.
Customers decide to go to a department store for several reasons including the quality of products, services, location, etc. These reasons have been studied in the literature. However, “for which product categories do customers decide to go to a department store” is an open question. The second purpose of this paper is to find the frequency of product categories from the viewpoint of the customers. Therefore, our aim is to obtain the required results in a systematic way with multi-criteria decision making methodologies. For this purpose, we perform the Analytic Network Process (ANP) and the Analytic Hierarchy Process (AHP) from the viewpoints of department managers and customers, respectively.
In the ANP model, several tangible and intangible criteria such as product costs, the demands of customers, sales history, overall inventory, floor space and relationship with suppliers are chosen, and the intersections between them are specified. Pairwise comparisons are made by department store managers. The ANP outcome is the weight of each product category, and these weights are considered the percentage of the area size within the store from the viewpoint of the department stores. In the AHP model, a simple model is constructed to define the customers’ preference for each product category. Pairwise comparisons between product categories are made by the customers. Therefore, the outcome of the AHP model is the weight of each product category, and this is the preference of each product category from the viewpoint of the customers. The outcomes show that these weights may be different. This is an expected situation since even if a product category is preferred by some as the driver to visit a department store, the footprint of that category in the actual store may be small. The outcome from customers provides feedback to department store managers on which product category should be diversified as well as the area sizes of those categories.
A Multi-Criteria Decision-Making (MCDM) Approach Using Hybrid SCOR Metrics, AHP, and TOPSIS for Supplier Evaluation and Selection in the Gas and Oil Industry
