Over the last two decades, various “intelligent technologies” for database analyses have significantly impacted on the design and development of new decision support systems and expert systems in diverse disciplines such as engineering, science, medicine, economics, social sciences and management. So far, however, barring a few noteworthy retailing applications reported in the academic literature, the use of intelligent technologies in retailing management practice is still quite limited. This chapter’s objective is to acquaint the reader with the potential of these technologies to provide novel, effective solutions to a number of complex retail management decision problems, as well as stimulating more research and development of such solutions in practice.
The great opportunity and scope for productive use of intelligent technologies in the retailing industry today derives from the tremendous expansion in computing power and in data captured for decision-making in various domains of retailing, including inventory and supply chain management, category management, dynamic pricing, customer segmentation, market basket analysis, and retail sales forecasting. The universal adoption of barcode technologies over the last two decades has generated much of the data concerned (e.g., see chapter by Burke in this book). For example, as early as 1990, typical supermarket database sizes ranged from 1 million records for a store audit to 10 billion records for store-level scanner data (McCann and Gallagher 1990). Now, in the first decade of the 21st century, data availability is poised to explode further with the advent and adoption of RFID (radio frequency identification) technology in retailing management.