How customers ‘learn’ to work for retailers

Cassidy (aka Harris), Kim; Harris, K; Baron, Steve; Lu, Xiaoming

Abstract

The purpose of this paper is to investigate how learning style affects the performance of the ‘working’ customer in one self-service context – retail Self Check-Out Tills (SCOT). For the purposes of this paper, we have adopted the UK term Self Check-Out Tills (SCOT), also known as ‘self-service registers’ in other countries, to describe this form of self-service in retail stores). The study uses qualitative and quantitative data collected from users of retail SCOT. Initial exploratory factor analysis of 232 SCOT users revealed significant differences in learning styles. Three categories emerged: ‘regular reassurance’, ‘motivated practice’ and ‘cautious discovery’. Customers adopting different learning styles varied in their perceptions of ability and enjoyment with SCOT, and in their capability of helping other customers with SCOT. The demographic make-up of customers adopting the different learning styles was also shown to vary. Previously, little has been done to identify the specific training needs of working customers. This research begins to address this knowledge gap.

Citation

Cassidy (aka Harris), K., Harris, K., Baron, S., & Lu, X. (2015). How customers ‘learn’ to work for retailers. Journal of Marketing Management, 31(17-18), 1747-1772. https://doi.org/10.1080/0267257x.2015.1020329

• Journal Article Type: Article
• Acceptance Date: Dec 1, 2014
• Online Publication Date: Mar 18, 2015
• Publication Date: Nov 22, 2015
• Deposit Date: Jun 4, 2018
• Publicly Available Date: Jun 6, 2018
• Journal: Journal of marketing Management
• Print ISSN: 0267-257X
• Electronic ISSN: 1472-1376
• Publisher: Routledge
• Peer Reviewed: Peer Reviewed
• Volume: 31
• Issue: 17-18
• Pages: 1747-1772
• DOI: https://doi.org/10.1080/0267257x.2015.1020329
• Keywords: customer participation, self-service, technology, factor analysis, co-creation, learning style
• Public URL: http://researchrepository.napier.ac.uk/Output/1195590
• Contract Date: Jun 6, 2018