A new multi-method decision framework for anchor selection and tenant mix allocation optimisation in shopping malls

Abstract

The increasing urbanization and fast-paced lifestyle have heightened the importance of shopping malls in retail industry, altering traditional shopping patterns by designing efficient space and optimise time of shoppers. Due to this newly-acquired importance, these malls have become critical players in the retail industry sector. Despite their significance, current research lacks comprehensive scientific methods in two critical aspects: the classification of anchors (or magnet shops) and regular tenants, and the detailed analysis of interrelations among anchors and tenants within the shopping malls. Both aspects are heavily related to the strategic allocation of shops position within malls. For addressing these gaps, this paper introduces a multi-method framework expert system to classify anchors and tenants and to optimise their positions in the shopping mall, considering their categories and existing product relationships. This framework comprises a new sorting method, a modified ranking method, a product correlation technique based on implementing ecological dynamics, an ecological interrelation index, and a metaheuristic allocation algorithm. The practical application of this framework are demonstrated through a real-world case study, highlighting its potential to significantly improve shopping mall management and retail efficiency. The effect of the proposed framework is subject to empirical tests and comparison between layout modifications.