Customers’ tolerance for validation in omnichannel retail stores: Enabling logistics and supply chain analytics

Abstract

Purpose

Mobile technologies are increasingly used as a data source to enable big data analytics that enable inventory control and logistics planning for omnichannel businesses. The purpose of this paper is to focus on the use of mobile technologies to facilitate customers’ shopping in physical retail stores and associated implementation challenges.

Design/methodology/approach

First, the authors introduce three emerging mobile shopping checkout processes in the retail store. Second, the authors suggest that new validation procedures (i.e. exit inspections) necessary for implementation of mobile-technology-enabled checkout processes may disrupt traditional retail service processes. The authors propose a construct labeled “tolerance for validation” defined as customer reactions to checkout procedures. The authors define and discuss five dimensions – tolerance for: unfair process; changes in validation process; inconvenience; mistrust; and privacy intrusion. The authors develop a measurement scale for the proposed construct and conduct a study among 239 customers.

Findings

The results show that customers have higher tolerance for validation under scenarios in which mobile technologies are used in the checkout processes, as compared to the traditional self-service scenario in which no mobile technology is used. In particular, the customers do not show a clear preference for specific mobile shopping scenarios.

Originality/value

These findings contribute to our understanding of a challenge that omnichannel businesses may face as they leverage data from digital technologies to enhance collaborative planning, forecasting, and replenishment processes. The proposed construct and measurement scales can be used in future work on omnichannel retailing.

Citation

Hoehle, H., Aloysius, J.A., Chan, F. and Venkatesh, V. (2018), "Customers’ tolerance for validation in omnichannel retail stores: Enabling logistics and supply chain analytics", The International Journal of Logistics Management, Vol. 29 No. 2, pp. 704-722. https://doi.org/10.1108/IJLM-08-2017-0219