Drivers and challenges of internet of things diffusion in smart stores: A field exploration

Michael Roe, Konstantina Spanaki (), Athina Ioannou, Efpraxia Zamani and Mihalis Giannakis ()
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Michael Roe: Loughborough University
Konstantina Spanaki: Audencia Business School
Athina Ioannou: Surrey Business School [Guildford] - UNIS - University of Surrey
Efpraxia Zamani: University of Sheffield [Sheffield]
Mihalis Giannakis: Audencia Business School

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Abstract: The digitally disruptive environment has evolved rapidly due to the introduction of new advancements within the field of smart applications. Applications of one of the most prominent technologies, Internet of Things (IoT), often appear in the retail sector, where smart services have transformed the customer experience holistically. Presented in this paper are the findings from an exploratory field study in the retail service sector, which drew on the views of experienced practitioners about the smart store experience and the associated changes. The paper presents an overview of the drivers of smart retail service diffusion and the relevant challenges, such as the business expectations and the heterogeneity of devices. The arising themes indicate that IoT security is a major challenge for businesses installing IoT devices in their journey towards smart store transformation. The paper highlights the importance of a secure data-sharing IoT environment that respects customer privacy as the smart experience in-store offers data-driven insights and services. Implications for research and practice are discussed in terms of the customer experience relevant to the identified challenges.

Keywords: field study; Internet of Things; retail; smart store; security; privacy; diffusion of innovations (search for similar items in EconPapers)
Date: 2022-05
New Economics Papers: this item is included in nep-ict and nep-pay
Note: View the original document on HAL open archive server: https://audencia.hal.science/hal-03599486v1
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Citations: View citations in EconPapers (6)

Published in Technological Forecasting and Social Change, 2022, 178, pp.121593. ⟨10.1016/j.techfore.2022.121593⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-03599486

DOI: 10.1016/j.techfore.2022.121593

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