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Mobile self-checkout refers to scanning products using a mobile device inside a brick-and-mortar store and completing the checkout process on mobile devices. Even though mobile self-checkout has been used in other industries for several years, it is a new application in the fashion industry and only limited numbers of retailers have implemented mobile self-checkout in their stores. The purpose of this study is to understand consumers' acceptance of mobile self-checkout in fashion retail stores by analyzing determinants of using a new system.

Part of the Unified Theory of Acceptance and Use of Technology (UTAUT) was used as a theoretical framework. Openness to experience, variety seeking and adventure shopping were added to the model. Empirical data (with 229 valid responses) were collected from the top 20 metropolitan areas in the US via Qualtrics Panel services. Exploratory factor analysis, confirmatory factor analysis, structural equation modeling and multi-group moderation were used to estimate construct validity and test the proposed hypotheses and theoretical framework.

The results indicated that consumers' intentions toward using mobile self-checkout in fashion retail stores were predicted by facilitating conditions, social influence and openness to experience. Moreover, consumers' previous experience of using mobile self-checkout in fashion retail stores moderated the path from facilitating conditions to behavioral intention and the path from social influence to behavioral intention. In addition, different genders and smartphone usage frequency did not vary significantly on the model paths.

The findings show how fashion retailers can understand consumers' preference and their willingness to use mobile self-checkout in fashion retail stores. Moreover, the authors addressed ways for fashion retailers to promote mobile self-checkout in the future.

As a new technology in the fashion industry, literature is deficient concerning consumers' intention to adopt mobile self-checkout. This research provided suggestions for fashion retailers about adopting and improving acceptance of mobile self-checkout. Results will lead to theoretical and managerial implications for future technology development.

Retailers are increasingly using self-service technologies to improve customer experience and reduce costs. The purpose of this study is to identify factors that could explain the level of continuance intention of mobile self-scanning applications in retail. Based on previous theoretical streams, the present study integrates technology readiness (TR) and service quality into the technology acceptance model.

Using data collected through an online survey of 217 users of a mobile self-scanning application of a large supermarket chain operating in Portugal, the study uses partial least squares structural equation modeling to test the proposed hypotheses.

The results indicate that the continuance usage of the self-scanning apps is directly driven by users' satisfaction and perceived usefulness. Findings also show that TR has a positive and significant impact on ease of use and perceived usefulness. Ease of use has a positive impact on users' satisfaction and perceived usefulness but has no direct effect on the continuance intention to use the application. Perceived quality has a positive direct effect on satisfaction and a positive indirect effect on continuance intention. Finally, need for interaction has a negative effect on TR.

This work contributes to a better understanding of the emerging market for mobile self-scanning applications in retail applications, particularly relevant in a digital transition context.

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.

Self-service check-out technologies (SSTs) are becoming a trend across different retail settings, allowing companies to gain efficiency and reduce costs. Nevertheless, the success of SSTs implementation is still subject to challenges and uncertainties. This study aims to provide insights for theory and managers on the necessary conditions for the successful implementation of retail SSTs.

Based on an online survey, data from 251 participants were collected to understand the factors predicting SSTs adoption and realise what conditions are mandatory for the adoption. partial Least Squares Structural Equation Modelling (PLS-SEM) and necessary condition analysis (NCA) were used to analyse the data.

According to the NCA analysis results, 12 latent variables were relevant for predicting SSTs adoption, but only seven were necessary conditions for user adoption.

The complementarity of perspectives for understanding the adoption of SSTs based on the two data analysis techniques provides novel insights into theory and support for retailers' decision-making on self-service technologies (STTs) implementation.

Continuous change has long been recognized as a core characteristic of retailing, its recent acceleration unprecedented, yet innovation in retailing remains under-researched, especially within fashion retailing. Therefore, the aim of this paper is to generate a deeper understanding of if, and to what extent, fashion retailers across different market segments are innovating in terms of in-store technology diffusion over time by taking a long-term perspective over five years.

Drawing on retail change and innovation diffusion theory, the study takes a qualitative approach, using direct observation of 71 fashion stores in London (UK) in 2014 and 2019. In total, 142 stores were tabulated in Excel and qualitatively analysed manually and with NVivo.

The findings identify the innovation adoption strategies implemented, the types of in-store technologies adopted over time and the fashion retail innovation adopters.

The research offers new knowledge in terms of retail innovation and retail change, specifically on retail diffusion of innovation and the importance of in-store technology integration. Several practical implications for improving technology innovation management are also identified.

Mobile apps represent an emergent self-service technology that has greatly contributed to the rise of mobile shopping. However, the existing services and marketing literature offer little insight on consumer app usage. Further, little is known about how this app usage might affect important outcomes such as consumers’ intentions to use and recommend an app, their channel preferences (in-store vs app), or their purchasing behavior with the app. Thus, the purpose of this research is to examine if, and how, consumers’ actual experiences using retailers’ apps affected these outcomes.

Data were collected from a series of online surveys of adult consumers based on their prior experiences with retailers’ apps. The hypothesized relationships were tested using regression analyses.

Results highlight perceived ease of use as a critical app attribute that fosters consumers’ personal connections to apps. These connections in turn influence their purchase channel preferences (app vs in-store) and actual purchasing behavior with the app, as well as their future intentions to purchase with the app and recommend it to others. App usage frequency is shown to moderate these effects.

The findings provide needed managerial insight into consumer usage of brick-and-click retailers’ apps. Specifically, the results inform service providers’ mobile commerce strategies – particularly with respect to app design, channel management and customer segmentation. Future opportunities exist to explore and compare consumer usage of other types of service providers’ apps, such as “pure play” providers that do not have physical stores.

This research moves beyond initial app adoption to instead focus on consumers’ actual app usage experiences and their implications. Of note, the findings suggest that firms may be paradoxically driving consumers away from their physical stores as they continue to devote considerable resources to creating and providing customers with easy-to-use mobile apps.

Blockchain can track the material from the manufacturer to the end customers. Therefore, it can ensure the product's authenticity, transparency and trust in the retail supply chain (SC). There is a need to trace and track the retail products before it reaches the customers to check the quality of the products so that expired products can be recycled and reused, which in turn will help gain customers' trust. This research aims to investigate retail employees' behavioural intention to adopt blockchain in the retail SC.

To examine the behavioural intention of employees in the retail SC, the research uses three theories – the technology acceptance model; the unified theory of acceptance and use of technology; and the theory of planned behaviour. The technology acceptance model measures the employee's acceptance of blockchain in the retail SC. The unified theory of acceptance is used in this research to measure how blockchain adoption will improve the performance of the employees. The theory of planned behaviour is used in this research to measure whether the employees intend to adopt blockchain. A survey was carried out in the retail stores of India. Exploratory factor analysis and structural equation modelling were used for data analysis.

This study found that the employees of the retail stores have a positive intention and attitude to adopt blockchain technology. Further, it was found that perceived behavioural control and effort expectancy was not promoting blockchain adoption in the retail sector.

This study will help the retail stores' employees understand the blockchain in their operations and will motivate the top management of the retail companies to adopt this technology. The study is limited to the retail SC in India only.

This study uses three theories technology acceptance model; the unified theory of acceptance and use of technology; and the theory of planned behaviour, which were not used in earlier studies of blockchain adoption in the retail SC.

This study aims to investigate the intention of adopting a technological service innovation that is a mix-mode consumer shopping service in the retailing context.

A modified extended Unified Theory of Acceptance and Use of Technology (UTAUT2) model is tested by using data on a real example named “Mkolay” which is a new mix-mode consumer shopping service. Data are collected from 217 participants and analyzed by using Partial Least Squares Structural Equation Modeling (PLS-SEM).

Research findings show that the customers' intention to use the new mix-mode consumer shopping service is particularly influenced by performance expectations, effort expectations, social influence and personal innovativeness.

In designing a mix-mode consumer shopping service, keeping the design as simple and easy to use as possible seems to increase the intention of adoption. Additionally, collaborating with reference figures or influencers could be instrumental to spread the new service to a wider audience hence increase the likelihood of adoption. Practitioners should also use new technologies in different ways to attract and surprise customers, especially taking into account the technological profile of potential users.

This study contributes to the literature of technological service innovation adoption by revealing the factors affecting the intention of adoption of mix-mode consumer shopping service in the retailing context with a modified UTAUT2 model.

“Contactless service” refers to the use of technology in providing products or services without a salesperson. This study explores the mechanism underlying Millennial and Generation Z (M/Z generations) consumers' preference for contactless service over salespersons in retail stores. In addition, this study tests differences between the M/Z generations.

The researchers predict characteristics to be antecedents of young consumer's preference for contactless service over salespersons and that the effects are mediated by technology self-efficacy. Next, a moderating variable (perceived consumer conformity) is added in the path between technology self-efficacy and the preference for contactless service. The hypotheses are tested among 142 Gen Z and 137 Millennial respondents.

The results show that M/Z generations’ characteristics significantly influence the preference for contactless service, except for security seeking. Also, interests in new technology and safety seeking are perceived higher by M/Z generations. The influence of technology self-efficacy on the preference for contactless service is moderated by social conformity.

As retail technology rapidly develops, the service industry is expected to change from the past, where salespersons played an important role, to contactless services. This study has academic and practical values, for the authors clarify the underlying psychological mechanisms of why young consumers prefer retail technology rather than communication with salespersons.

This study aims to examine the factors influencing consumers’ intentions to use QR code menus in the post-COVID-19 pandemic using the unified theory of acceptance and use of technology and rational choice theory as the theoretical foundations.

Using a survey method, 200 data are collected from consumers who had used QR code menus in the past. Partial least squares structural equation modelling is used to analyse the data.

Our findings show that performance expectancy, effort expectancy, social influence, habit and perceived privacy protection have a significant positive influence on intentions. However, facilitating conditions, hedonic motivation and perceived privacy risk do not have a significant influence on intentions.

This study further extends the work of previous studies by using the unified theory of acceptance and use of technology model, with additional two new predictors, namely perceived privacy protection and perceived privacy risk, to understand consumers’ intentions to use QR code menus.