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Retailers are implementing technology-enabled mobile checkout processes in their stores to improve service quality, decrease labor costs and gain operational efficiency. These new checkout processes have increased customer convenience primarily by providing them autonomy in sales transactions in that store employee interventions play a reduced role. However, this autonomy has the unintended consequence of altering the checks and balances inherent in a traditional employee-assisted checkout process. Retailers, already grappling with shoplifting, with an estimated annual cost of billions of dollars, fear that the problem may be exacerbated by mobile checkout and concomitant customer autonomy. The purpose of this paper is to understand the effect of mobile checkout processes in retail stores on cybercrime in the form of shoplifting enabled by a technology transformed the retail environment.

The authors conducted an online survey of a US sample recruited from a crowdsourced platform. The authors test a research model that aims to understand the factors that influence the intention to shoplift in three different mobile checkout settings − namely, smartphone checkout settings, store-provided mobile device checkout settings, and employee-assisted mobile checkout settings − and compare it with a traditional fixed location checkout setting.

The authors found that, in a smartphone checkout setting, intention to shoplift was driven by experiential beliefs and peer influence, and experiential beliefs and peer influence had a stronger effect for prospective shoplifters when compared to experienced shoplifters; in a store-provided mobile devices checkout setting, experiential beliefs had a negative effect on shoplifters’ intention to shoplift and the effect was weaker for prospective shoplifters when compared to experienced shoplifters. The results also indicated that in an employee-assisted mobile checkout setting, intention to shoplift was driven by experiential beliefs and peer influence, and experiential beliefs had a stronger effect for prospective shoplifters when compared to experienced shoplifters.

This study is the among the first, if not first, to examine shoplifters’ intention to shoplift in mobile checkout settings. We provide insights into how those who may not have considered shoplifting in less favorable criminogenic settings may change their behavior due to the autonomy provided by mobile checkout settings and also provide an understanding of the shoplifting intention for both prospective and experienced shoplifters in different mobile checkout settings.

We review the implications of the mobile technology for different stages of the consumer path to purchase including awareness, search, evaluation, store visit, and product choice. Real-time and location-specific access to information and products are identified as distinguishing characteristics of mobile devices. While the literature on digital marketing is well developed, knowledge of the effects on the consumer path to purchase in the presence of dynamic and location-specific information is still scarce. Path to purchase models need to recognize the central and powerful role of user-generated content. Better management of marketing resources would require models that connect investments in mobile marketing to sales, and also model the synergies among different digital and offline media. We conclude with a framework that connects mobile media impressions to product choice, in the presence of other marketing media, and consumer and firm feedback loops.

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.

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.

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.

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.

Online retailing is continuing to grow at a time with many fashion brands are closing retail stores. Social media is now an essential component within the purchase journey of a fashion consumer. As social media networks continue to develop transactional capabilities, this has giving rise to the expansion of social shopping. Fashion brands need to consider how best to optimise social shopping opportunities as an extension of the retail shopping experience. Reviewing developments within retailing, a conceptual model of social shopping is proposed, which places mobile technologies as central to the social shopping experience both on social media and in store.

This study examines the dynamic relationships of visit behavior in the multiple channels [personal computer (PC) and mobile channels] on online store sales performance.

The empirical data were from an online store for the period between August 14, 2015 and May 15, 2016. The data consisted of consumer visit behavior and online store sales performance. Vector autoregression with an exogenous variables model was adopted to investigate the dynamic relationships.

The empirical results show significant relationships between visit behavior metrics (number of visitors, average number of visits per visitor and average length of each visit) in the two channels and online store sales performance. The number of visitors through the PC and mobile channels strongly and positively affects online store sales performance both in the short term and in the longer term. Moreover, the number of visitors in the PC channel has the strongest influence on sales performance metrics, followed by the number of visitors and the average number of visits in the mobile channel. The PC channel's visit behavior metrics explain a larger proportion of the sales performance variance than that in the mobile channel.

The previous literature on consumer behavior in multichannel marketing mainly focuses on channel selection or migration, and examines the different factors affecting channel choice behavior. Little is known about the impacts of visit behavior in the multiple channels. This study adopts the heuristic-systematic information processing theory to unveil the impacts of visit behavior metrics in the PC and mobile channels on online store sales performance.

This study explores the importance of application search engine (ASE) technology in the omni-channel strategy. For this purpose, this chapter firstly explains the concepts of the omni-channel and the search engines and the importance of them. Then, omni-channel in the framework of ASEs is discussed. Finally, recommendations for further researches are presented.

Retailers have recently leveraged store-loyal customers’ store attachment to maintain customer relationships and motivate patronage intentions. However, the COVID-19 outbreak has driven customer migration from offline to mobile channels. Mobile retail applications (APPs) have been used by numerous retailers to reach their customers. Nonetheless, it has yet to be determined (1) whether store attachment can facilitate (or impede) the adoption of mobile retail APPs and (2) whether store-loyal customers will continue visiting offline stores in the post-pandemic era. To address these questions, we propose a theoretical account using integrated theories on trust transfer and store attachment.

We conducted multi-stage, longitudinal field surveys in two cities of mainland China: Beijing and Guangzhou. From two rounds of data collection, 237 and 103 responses were obtained in March 2022. Hypotheses were tested by partial least squares – structural equation modelling (PLS–SEM).

Results showed that customer trust in an offline retailer can be transferred to the retailer’s mobile APP at the pre-adoption stage, facilitating APP adoption. Notably, store-loyal customers who exhibited a strong attachment to the physical store of a retailer were more inclined to transfer their trust to the mobile APP of the retailer. This occurrence leads to an increased adoption rate, enhanced post-adoption satisfaction and increased inclination to continue (rather than discontinue) usage.

This study is the first to investigate the changes in store-loyal customers' shopping behaviour in the mobile retail era and in the post-COVID-19 pandemic recovery. Our findings elucidate the role of physical store attachment in the trust-transfer mechanism. Furthermore, store attachment may not prevent customers’ channel migration behaviour. Retailers may have to re-consider how to manage channel cannibalisation issues in the post-pandemic recovery.

Nowadays companies are constantly changing their retail settings and strategies to keep up with technological developments and consumer needs. Digital transformation enabled one’s shopping experience to be more efficient in terms of money, time, physical effort and other elements that determine the price a consumer has to pay. Channels of communication and distribution have evolved, increased in number and also became integrated. Mobile devices, mobile applications and location services help consumers in their shopping journey. These developments have led us to a new concept called omni-channel management. In theory, the omni-channel refers to a single and unified channel experience with multiple touchpoints, which include physical stores, online stores and direct marketing; mass communication channels (television, radio, print media, C2C, etc.), online channels (social media, search engines, comparison sites, e-mail, display etc.) and mobile channels (SMS, branded apps, etc.). Some examples of omni-channel practices are click-reserve, click-collect, tablets as in-store sales tools, in-store product order through mobile apps, etc.

In this chapter, the latest trends in marketing channels are discussed with enabling digital technologies and relevant success factors. Challenges and opportunities in implementing omni-channel strategies and several omni-channel initiatives from Turkey are reported.

A research was employed to present consumers’ preferences of touchpoints/channels for search, payment and delivery, and to find out the drivers that lead consumers to use more than one channel simultaneously and/or interchangeably in a buying process. The results will guide the readers to understand consumer behaviour in the new omni-channel world.

This study aims to explore the impact of channel integration on usage intention through mobile applications (apps) for customers in grocery retailers. Moreover, the study examines the moderating effect of customer commitment in the model.

Structural equation modeling was conducted on a sample of 536 consumers in Taiwan.

This study found that information integration, marketing integration and operational integration are three significant dimensions of channel integration in grocery retailers. Channel integration positively affects satisfaction and trust, which, in turn, increases usage intention. Moreover, customer commitment significantly moderates the relationships in the model.

Sample bias may exist because the sample was obtained from an online survey conducted on social media platforms.

This study suggested that practitioners should confidently implement channel integration through mobile apps in stores. They may develop more valuable services connected with different channels or devices to assist customers in buying in-store. To improve customer trust in the service, practitioners can enhance their confidence in using mobile apps in their stores. Moreover, practitioners segment customers based on high and low levels of customer commitment to provide different strategies to increase usage intention in the retailer.

This study advanced the extant knowledge of channel integration theory and relationship marketing theory in the context of omnichannel retailing.