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This research aims (i) to assess the level of customer satisfaction and loyalty to self-service technologies and Auchan Retail Portugal, (ii) to identify the determinants of customer satisfaction and loyalty to these technologies and also, (iii) to identify their influence on customer loyalty to this modern distribution retailer operating in Portugal.

A conceptual model was defined to meet the research objectives and to carry out the quantitative analysis applied to the random sample (n = 483) of customers. The data used where gathered via an online questionnaire survey, which covered all dimensions of the conceptual model, applied in 2021 in Portugal. To validate the hypotheses, Cronbach’s alpha and multiple linear regression models were used.

The results reveal that customer satisfaction with self-service technologies has a direct and positive effect on customer loyalty to Auchan Retail Portugal. Furthermore, results reveal that the technology utility factors significantly influence the customer technology experience which has an impact on perceived service quality and perceived risk. The findings of this research provide data on how to improve customer adoption and satisfaction with self-service technology and highlight that these technologies should be part of firm’s competitive strategy.

This study presents itself as a novelty for science, while granting important contributions to the retailer. It presents an innovative conceptual model that delivers to Auchan the basis for it to move toward smart retail technologies, aiming at the market trend of personalization. For future research, this study can be used as an instrument to evaluate the customer experience with self-service technology and to examine the determinants and effects of self-service technology separately.

This article aims to develop a new theory that can better explain and predict how and when humans interact with commercial robots. To this end, utility maximization theory (UMT) along with four principles and propositions that may guide how human-to-commercial robot interactions are developed.

This article conceptualizes UMT by drawing from social exchange, conservation of resources, and technology-driven theories.

This article proposes UMT, which consists of four guiding principles and propositions. First, it is proposed that the human must invest sufficient resources to initiate a human-to-commercial robot interaction. Second, the human forms an expectation of utility gain maximization once a human-to-commercial robot interaction is initiated. Third, the human severs a human-to-commercial robot interaction if the human is unable to witness maximum utility gain upon the interaction. Finally, once the human severs a human-to-commercial robot interaction, the human seeks to reinvest sufficient resources in another human-to-commercial robot interaction with the same expectation of utility maximization.

This article is one of the few studies that offers a theoretical foundation for understanding the interactions between humans and commercial robots. Additionally, this article provides several managerial implications for managing effective human-to-commercial robot interactions.

Emerging economies are dominated by an unorganized retail landscape, with complex sociocultural norms dictating the behavior of retailers and customers. The purpose of this paper is to explore the phenomenon of consumer embarrassment in an emerging marketing, India.

This research adopts a grounded theory approach and undertakes 31 in-depth interviews with consumers in India. The data is analyzed inductively and iteratively simultaneously with data collection.

The study uncovers that sociocultural normative influences, the retail environment’s structural constraints, interaction-based buying processes and customers’ perceptions play a role in eliciting embarrassment in traditional stores. The traditional format retailers play a significant role in evoking embarrassment and, surprisingly, also in facilitating coping. Contrary to the extant findings, purchasing embarrassing products online may not ensure anonymity and elicit embarrassment. The findings contribute to understanding the phenomenon of embarrassment in emerging markets.

There is a dearth of research examining consumer embarrassment in emerging markets, with extant studies investigating the phenomenon in the modern retail setup of developed economies. The retail landscape of India is predominantly unorganized, with distinct transactional processes and physical characteristics that are starkly different from modern retail stores. Moreover, sociocultural normative forces have distinct influences on the informal setup of unorganized retail.

This study focuses on memorable customer shopping experience design in the sporting goods retail setting. It aims to identify the phygital customers' needs and expectations that are satisfied through in-store technologies and to detect the in-store strategies that use these technologies to make the store attractive and experiential.

This exploratory study adopted a qualitative research methodology, specifically a multiple-case study, by performing semi-structured interviews with sporting goods store managers.

Sporting goods retailers use various in-store technologies to create a phygital customer shopping experience, including devices, mobile apps, wireless communication technologies, in-store activations, support devices, intelligent stations, and sensors. To improve the phygital customer journey and the phygital shopping experience, retailers meet customers' needs for utilitarian, hedonic, social, and playfulness experiences. Purely physical or digital strategies, as well as phygital strategies, are identified. This research also proposes a model of in-store phygital customer shopping experience design for sporting goods retailers.

Sporting goods managers can invest in multiple technologies by designing a physical environment according to the customers' needs for utilitarian, hedonic, social, and playful experiences. In addition, they can improve the phygital customer shopping experience with specific push strategies that increase customer engagement and, in turn, brand and store loyalty.

This study highlights how the phygital customer experiential journey can be created through new technologies and improved with specific reference to the sporting goods stores.

Self-service technologies (SST) have become more and more pervasive in retail to facilitate autonomous checkout. In this context, customers play an active role and, as such, can be considered as “partial employees.” Partial employees have to perform a wide range of tasks, get rewarded for their work and need to understand the terms of the exchange, all without being subject to a formalized contract. In this research, the authors suggest that partial employees go through a process of organizational socialization that allows them to define the psychological contract they hold with the organization.

In order to investigate the psychological contracts of partial employees, 324 Canadian customers using SST completed an online questionnaire, in which their SST use, psychological contract fulfillment and organizational socialization were measured.

Descriptive analyses highlight that customers as partial employees build a psychological contract with their most frequent retailer, as they perceive not only retailer inducements but also their own contributions. Multiple linear regressions suggest that organizational socialization favors psychological contract fulfillment, but that specific dimensions of organizational socialization are important for employer inducements vs. employee contributions. Moreover, results suggest that the frequency of use of SST as well as the patronage positively predicts psychological contract fulfillment.

This research investigates a specific situation of unconventional employment – that of customers as partial employees with organizations. It contributes to the literature on the psychological contract by broadening its application to new relations and to the literature on customer management by reemphasizing the relevance of the psychological contract in this domain.

The growth of self-service technologies (SST) in the retail sector has led to an increased prevalence of SST failures, and spurred academic debate on customer self-recovery of the failed services. This study sets out to explore why customers prefer or decline to engage in self-recovery. A framework integrating elements from self-determination theory and theory of planned behavior is developed to explore the impact of motivational factors, attitudes and self-efficacy on self-recovery intention.

Structural equation modeling (SEM) was used to analyze the sample consisting of 297 users of retail kiosks in convenience stores.

The results revealed that intrinsic motivation and identified regulation directly affect customers' attitude and intention to engage in self-recovery. Despite an insignificant direct relationship, external regulation impacted self-recovery intention through attitude. Further, the association between intrinsic motivation and self-recovery intention is moderated by self-efficacy.

Much of the extant SST recovery literature has focused on company-rendered service recovery, providing little guidance to firms on how to promote self-recovery among customers. The integrated motivational-cognitive theoretical base in this study allows for a more differentiated inquiry into the factors shaping self-recovery intention, resulting in a deeper understanding of this topic. The novel insights will help retailers develop effective strategies for promoting self-recovery among users of retail kiosks.

The study’s objective is to measure the importance consumers attach to AI-based attributes, namely, chatbots, face recognition, virtual fitting room, smart parking and cashier-free station in retail stores. The study also examines the specific purpose of using these attributes for shopping.

A conjoint experiment was conducted using fractional factorial design. Consumers were given 14 profiles (AI attributes and its levels) to rank according to their visiting preferences.

The results revealed that the retail chatbot was considered the most important attribute, followed by face recognition, virtual fitting room, smart parking system and cashier-free station. Moreover, consumers prefer to use chatbots for in-store shopping assistance over alerts and updates, customer support and feedback. Similarly, consumers wish a face recognition facility for greetings while entering the store over other services. In addition, cluster analyses revealed that customer groups significantly differ in their preferences for AI-based attributes.

The study guides retail managers to invest in AI technologies to provide consumers with a technology-oriented shopping experience.

Our results provide an insight into the receptivity of AI technologies that consumers would like to experience in their favorite retail stores. The present study contributes to the literature by investigating consumer preferences for various AI technologies and their specific uses for shopping.

In today's world, retailers must embrace technological devices to provide fluid, convenient and complete customer experiences. Therefore, combining the offline and online spaces into a single strategy becomes essential, representing a significant opportunity for retailers to improve customer experience. Therefore, this study aims to explore and compare the importance of digital elements in an omnichannel experience by companies in the luxury and non-luxury segments.

The research offers a model to explore and compare the omnichannel strategies that brands use, considering six dimensions that cover recent technological advances, thus offering a complete experience to their customers. A multiple case study was selected based on a sample of six international companies from two different price segments (luxury and non-luxury).

The data collected allowed the authors to verify the presence of some dimensions, even though some had little evidence. Nevertheless, the dimensions connectivity, innovativeness and flexibility (only in luxury segment companies) were not present. Overall, and even though they present just little evidence, the results showed that retailers for the luxury segment invest more in delivering digital experiences within omnichannel strategies than the non-luxury ones.

This study improves the existing knowledge of omnichannel retailing. By analysing and comparing the omnichannel experiences, companies can identify areas for improvement and enhance the overall customer journey. Additionally, the model allows managers to compare and re-evaluate their omnichannel strategies with other competitors to gain competitiveness in an ever-evolving market.

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, first, propose a valid and reliable scale to document the COVID-19 Pandemic Shopping Experience (CPSE) and, second, determine the impact of its variables on the postpurchase shopping experience (PPSE).

For scale development, published studies were scanned and the variables were shortlisted. These shortlisted variables were validated by 52 faculties from four universities in Saudi Arabia. Data were collected from 318 respondents to purify the CPSE Scale. In Study 2, a path analysis was performed on a sample of 354 respondents to determine the individual impact of each variable on PPSE.

A total of 14 items were found to be aligned under four variables, social distance (SD), shop hygiene, operational time and entertainment venues. SD was found to have the greatest influence on PPSE, followed by operational time and shop hygiene.

This research has important implications for retailers to initiate changes in store layout so that they can implement social distancing by physically marking stickers on the floors and by placing barricading on billing counters. Store hygiene can be ensured by making sanitizers and hand gloves available at the entry points, periodically cleaning the floor and sanitizing the premises. Rationing the operating time proved to be an effective tool to minimize the exposure time, thereby limiting consumers' time inside the store.

To the best of the authors’ knowledge, this is the first study to propose a full-scale measure of the customer shopping experience (SE) during a pandemic. This scale can be generalized to measure SE in similar situations.