Determining the preferences of different functionality levels regarding dynamic pricing in combination with electronic shelf labels in the Dutch food retail industry - a Bayesian BWM approach

Abstract

For decades supermarkets have been seen as very conservative. However, it seems that food retailers are increasingly taking a proactive role in implementing new technologies in the food retail, shaping decision-making process from their own sales perspective. This research aims to identify the preferences of different technology implementation level scenarios in the Dutch food retail industry. This is done by applying a more qualitative approach, whereby less data is required to produce reliable results. As such, a Multi-Criteria Decision-Making method (MCDM) approach is used, wherein the Bayesian Best-Worst Method (BWM) is applied to determine the optimal experts preference of the identified technology implementation level scenarios. This is done within the context of selecting new adaptive technologies in the food retail industry and with the application of qualitative tools such as constructing the BWM and structured interviews with experts. The technology implementation level scenarios consists of obtained relevant scenarios with a combination of different functionality levels regarding dynamic pricing in combination with electronic shelf labels. This research contributes to the empirical application of the Bayesian BWM, in the specific field of implementing dynamic pricing in combination with electronic shelf labels in the food retail industry and proves that determining the preferences of these scenarios can be predictive by applying the aforementioned MCDM approach as well.