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Generation Z consumers’ expectations of interactions in smart retailing: A future agenda

Research output: Contribution to journalArticle

Original languageEnglish
Number of pages8
JournalComputers in Human Behavior
Early online date31 Jan 2017
DOIs
DateAccepted/In press - 29 Jan 2017
DateE-pub ahead of print (current) - 31 Jan 2017

Abstract

Retailing is witnessing a transformation due to rapid technological developments. Retailers are using smart technologies to improve consumer shopping experiences and to stay competitive. The biggest future challenge for marketing and consequently for retailing seems to be generation Z, since members of this generation seem to behave differently as consumers and are more focused on innovation. The aim of this paper is to explore Generation Z consumers’ current perceptions, expectations and recommendations in terms of their future interactions in smart retailing contexts. To do so, we used a qualitative approach by conducting a series of semi-structured in depth interviews with 38 university students-consumers in the UK market. The findings showed that smart technologies have a significant influence on generation Z consumers’ experiences. Moreover, this particular group of consumers expects various new devices and electronic processes to be widely available, thus offering consumers more autonomy and faster transactions. In addition, they expect the technology to enable them to make more informed shopping decisions. Interviewees also stressed the importance of training consumers how to use new smart retailing applications. In addition, some of the participants were sceptical about the effects of further advancing smart retailing on part of the job market. Relevant theoretical and practical implications are also provided.

    Research areas

  • Smart retailing, Generation Z, Consumer expectations, Consumer interactions

    Structured keywords

  • Smart Networks for Sustainable Futures

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    Rights statement: This is the final published version of the article (version of record). It first appeared online via Computers in Human Behavior at http://www.sciencedirect.com/science/article/pii/S0747563217300729 . Please refer to any applicable terms of use of the publisher.

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