Consumer Acceptance and Resistance Factors Toward Smart Retail Stores

Introduction

The Internet of Things (IoT) and smart technologies considerably influence the retail industry and consumer shopping experiences (Inman & Nikolova, 2016; Manyika et al., 2013; Renko & Druzijanic, 2014). Strategies now extend product displays to fully immersive retail stores, like with the connected mirror that allows consumers to virtually try on clothes, create outfits from the inventory, request matching products, and connect to social networks. In France, managers and consumers are witnessing a timely metamorphosis of the point of sale with different technologies (i.e., smart mirror in the fitting room, application for smartphone, website dedicated). For example, Decathlon, a French store specialized in sports, digitized a store in Paris to improve consumer experience (e.g., real-time product information and inventory consultation, store transformed into a fitness room with coaches who are the salespeople at the same time). Moreover, the brand Bonobo insures its consumers to find their clothing size thanks to real-time stock information. Another example is with the brand Nike which launched digital stores with touch pads to pay for products, wall screens to consult the catalogue, emails or QR codes to memorize a product, and smartphones to test the Nike mobile app. Indeed, smart retail technologies give managers tools to enhance consumer experience and service personalization (Toch et al., 2012). Smart retail stores seem to be a valuable way to create greater benefits, customer loyalty and personalized interactions with consumers on the long term (Pantano & Timmermans, 2014; Wünderlich et al., 2013). Consequently, retailers are aware of the IoT potential and are interested to use smart technologies in retailing strategies (Foroudi et al., 2018).

As empirical studies on the topic are missing, there are many calls for research about these kinds of smart environments (Dennis et al., 2014; Foroudi et al., 2018; Garaus et al., 2016; Gao & Bai, 2014; Inman & Nikolova, 2017; Oh et al., 2007; Verhoef et al., 2009). Therefore, it becomes of high academic and managerial relevance to understand how the IoT is shaping the future of retailing (Kotler et al., 2017). Consequently, this research contributes to theory and practice by discussing theoretical and managerial highlights regarding consumers’ acceptance of smart retail stores and consumer buying intentions. To do this, few investigated factors of consumer acceptance and resistance are simultaneously taken into account, namely social influence, consumer well-being, and privacy concerns, as little research has investigated consumer acceptance and resistance of innovations (Talke & Heidenreich, 2014; Laukkanen, 2016). Moreover, this study extends existing theory on individual consumer differences with consumer traits like innovativeness, empowered and well-being personalities (e.g., Venkatesh & Bala, 2008; Gelderman et al., 2011).

This chapter is organized as follows: the next section describes the background of smart retailing; this is followed by a literature review about the acceptance and resistance factors of smart retail stores; then, solutions and recommendations are stated, followed by future research directions and a conclusion.