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Previous studies have considered customers' psychological responses to intelligent retail technology adoption, but have not considered how technology integration systems could promote the relationship between retailers and consumers. Based on the Stimulus–Organism–Response framework, this paper proposes a customer engagement model in a fully intelligent retail environment. The concept of the quality of intelligent experience is constructed from the perspective of customer experience, and the effect of the mechanism of smart retail on the customer engagement relationship is discussed.

Using two surveys, this study analyzes 201 (in study 1) and 321 (in study 2) questionnaires by using structural equation model in partial least square software.

The analysis shows that the human–machine interaction, intelligent systems and the product content of the quality intelligent experience significantly impact customer engagement on smart retail.

This research was designed for general retail products, without distinguishing between different product types. Thus, it did not consider the moderating effect of product types.

The findings enrich the intelligent retail technology field and provide operable guidance to help smart retailers improve customer relations.

This paper proposes a customer engagement model to describe how technology integration systems promote the relationship between retailers and consumers.

With the advancement of digital transformation, it is important for e-retailers to use artificial intelligence (AI) for customer engagement (CE), as CE enables e-retail brands to succeed. Essentially, AI e-marketing (AIeMktg) is the use of AI technological approaches in e-marketing by blending customer data, and Retail 4.0 is the digitisation of the physical shopping experience. Therefore, in the era of Retail 4.0, this study investigates the factors influencing the use of AIeMktg for transforming CE.

The primary data were collected from 305 e-retailer customers, and the analysis was performed using a quantitative methodology.

The results reveal that AIeMktg has tremendous applications in Retail 4.0 for CE. First, it enables marketers to swiftly and responsibly use data to anticipate and predict customer demands and to provide relevant personalised messages and offers with location-based e-marketing. Second, through a continuous feedback loop, AIeMktg improves offerings by analysing and incorporating insights from a 360-degree view of CE.

The main contribution of this study is to provide theoretical underpinnings of CE, AIeMktg, factors influencing the use of AIeMktg, and customer commitment in the era of Retail 4.0. Subsequently, it builds and validates structural relationships among such theoretical underpinning variables in transforming CE with AIeMktg, which is important for customers to expect a different type of shopping experience across digital channels.

Recently, smart retail technology has emerged as an innovative technology that can improve consumer motivation and behavior in smart stores. Although prior studies have investigated factors influencing the adoption of smart retail technology, to the authors’ knowledge, no previous work has investigated the determinants of purchase intentions. The ultimate goal for retailers should be shopping, not technology adoption. However, traditional brick-and-mortar stores and theories focus on investing in utilitarian factors to attract customers. This study proposes that hedonic motivation should also play an important role, as new technologies may arouse customer curiosity and increase pleasant experiences. Therefore, the purpose of this study is to explore utilitarian and hedonic motivations that promote customers' purchase; intentions in smart stores. Specifically, the authors address the research questions: (1) What are the constituents of utilitarian motivation? (2) What are the constituents of hedonic motivation? (3) What are the factors that influence customers' purchase intentions? By answering the questions, the findings help retailers understand how to motivate customers to make purchases in smart stores.

To investigate consumer motivation and purchase intentions, the customers who made purchases in smart stores were invited to participate in the questionnaire survey. This study collected 307 data in smart retail settings. Partial least squares (PLS) software was used to assess the reliability, validity and the paths and significance of all hypotheses.

The results show that perceived ease of use directly and indirectly influences purchase intentions through utilitarian and hedonic motivations. Utilitarian motivation is a formative second-order construct comprised of merchandise price, merchandise quality, location convenience, speed of shopping and product recommendation. Hedonic motivation is a reflective second-order construct composed of control, curiosity, joy, focused immersion and temporal dissociation. The findings provide insights into the successful implementation of smart retail technology and offer retailers to better understand consumer motivation and purchase intentions in smart stores.

This study is the first to examine how consumer motivation influences purchase intentions in smart stores. This study posits and verifies the extended hedonic system acceptance model (HSAM) to explain consumer motivation for shopping in smart retail settings. This study also models the original first-order utilitarian and hedonic constructs as second-order formative and reflective constructs, respectively. Utilitarian motivation regarding functional benefits is developed based on the 5Ps of marketing and situational factors, while hedonic motivation regarding pleasant experiences is proposed based on cognitive absorption.

The purpose of this paper is to analyse the factors which influence value co-creation intention through customer engagement during the COVID-19 pandemic. This paper studies the online modest fashion small- and medium-sized enterprises (SMEs) in Egypt as a Muslim country.

This paper is based on the social cognitive theory (SCT) and the literature to develop a theoretical framework of the factors influencing customers’ value co-creation intention on social media. The framework is then tested quantitatively through structural equation modelling based on partial least squares method (SEM-PLS) approach using the SmartPLS software.

The empirical analysis supported the SCT through the following conclusions: first, regarding the subject factors, self-efficacy has a positive significant effect on all dimensions of customer engagement and outcome expectation has a positive significant effect on cognitive customer engagement. Concerning the environmental factors, community experience has a positive significant effect on affective and behavioural customer engagement, whereas content quality has a positive significant effect on affective customer engagement. Second, customer engagement is a significant mediator through the dimensions of affective and behavioural customer engagement.

The findings of this study can help online modest fashion SMEs better comprehend the factors which influence the customers’ engagement for value co-creation intention whether it is subject factors or environmental factors. Therefore, they can better operate online and encourage customers to contribute to the development of new products and services and hence achieve a competitive advantage and survive in times of COVID-19.

Most of the existing studies focused on the value co-creation behaviour and output. However, there is limited research focusing on what contributes to the customers’ engagement for value co-creation intention, especially for online modest fashion and Muslim countries. Therefore, this study attempts to examine and bridge this research gap.

Financial technology (FinTech) is undergoing a transformation as a result of robotics and artificial intelligence. FinTech service providers are embracing contactless technology, including the development and widespread adoption of innovative payment service. Among the many types of contactless payment services, facial recognition payment (FRP) has gained in popularity. To capitalize on this rising popularity, comprehending the mechanisms underlying continuous usage intention toward FRP is essential. Drawing from the stimulus–organism–response (S-O-R) model, this study investigates how FRP attributes facilitate continuous usage intention.

In total, 321 Chinese FRP users completed an online survey. Partial least squares structural equation modeling analyzed the results of the survey.

The results reveal that relative advantage and compatibility, user-interface attractiveness and perceived security (stimuli) promote performance expectancy, effort expectancy and positive emotion (organism), which in turn foster FRP continuous usage intention (response).

This research presents an S-O-R model that incorporates several attributes from DOI theory, the UTAUT model and the AIDUA framework to elucidate the antecedents of consumers' continuous usage intention toward FRP. The findings corroborate the significance of the S-O-R mechanism in FRP, setting the groundwork for the acceptance and development of biometric authentication technologies in service contacts and banks. In addition, the study highlights opportunities and essential aspects for FinTech service developers and providers to consider in terms of their practical significance.

Contemporary firms are increasingly focusing on enhancing the customer experience (CX) to gain a sustainable competitive advantage. However, despite the rapid growth of CX research from both the customer's and the firm's perspectives, the intellectual structure of CX research remains tenuous, thus requiring further investigation. Addressing this gap, the authors review and map the existing corpus of CX literature, from which important implications are drawn.

After inventorizing the CX literature (1997–2021), the authors apply bibliometric (e.g. co-citation) analysis to identify key CX articles and pertinent CX-publishing journals, followed by the identification of key CX research themes through network analysis.

The authors first document chief CX-publishing journals and articles and identify their respective contributions. The authors, then, derive five core CX themes, including CX through the customer journey, S-D Logic-informed CX, interactive service–based CX, CX in the servicescape and CX and consumption. The authors conclude by developing an agenda for future CX research based on the study findings.

By offering a pioneering analysis of the corpus of CX research (1997–2021), these analyses offer a pertinent theoretical contribution.

Despite the growing number of cashierless stores, few studies have examined the factors that influence the success of such stores. This paper aims to identify the influence of store attributes in customers’ affective attitudes regarding cashierless stores and to understand how customers’ need for interaction and risk reduction affect the relationship between customer experiences and evaluation.

Quantitative research is conducted using a partial least squares structural equation model. Data was collected from 174 customers with cashierless store experience.

The results identify the influence of hedonic and utilitarian characteristics on affective attitudes and the impact of attitudes on behavioral intentions. Also, multigroup analysis reveals that hedonic features are stronger indicators of customer attitudes among those with a low need for interaction, whereas utilitarian attributes are more important among customers with a low need for risk reduction. Customers’ affective attitudes are stronger influences on behavioral intentions among members of customer groups with a low need for both interaction and risk reduction.

To add to the limited research in customers’ experience with unstaffed stores, this study provides useful insights to achieve sustainable growth in the retailing context. Managerial considerations suggest that operators of cashierless stores should design store environments to guarantee customers’ purchasing and recommendation intentions.

The study examines the extrinsic variables, namely store environment, promotional activities (PA), product features and stimulation factors that encourage compulsive purchasing in emerging markets.

The data were collected from customers with recent compulsive shopping experiences at an online retail store. This study collected 469 original survey responses employing purposive sampling and data analyzed with covariance-based structural equation modeling and used segmentation analysis.

The study results indicated that extrinsic (stimulus) factors, such as shop environment, PA and stimulation factors positively impacted shoppers’ impulsive buying tendency (IBT), whereas product characteristics did not affect shoppers’ IBT. Similarly, IBT (organism) influenced compulsive purchase, as did a favorable mediating relationship between extrinsic factors (stimulus factors) and shoppers’ compulsive purchase (response factor). Moreover, segmentation results showed that female consumers had more IBT and compulsive buying behavior than male respondents.

This research adds to the corpus of information concerning impulsive and compulsive buying behavior. As this study incorporates the Stimulus-Organism-Response paradigm, new findings emerge; using this paradigm allows for the testing of new linkages to better understand consumers’ impulsive and compulsive behavior.

The paper aims to explore the relationship between customer mindsets and customer citizenship behavior. This study used the cognitive-affective-behavioral model to examine how customer mindsets relate to customer citizenship behavior. In addition, it investigated the mediating effect of customer brand engagement and moderating role of brand trust.

The study used a self-administered online survey from 412 respondents using cellular mobile operating brands. Partial least square structural equation modeling was used to analyze the collected data.

The results revealed that growth-mindset customers directly and significantly influence customer citizenship behavior. The impact of a fixed mindset on customer citizenship behavior is indirect through customer brand engagement. The moderating findings revealed that the effect of brand trust on the relationship between customer brand engagement and customer citizenship behavior is higher than that between the fixed mindset and customer brand engagement.

The findings provide valuable insights for marketing and brand managers to design marketing campaigns considering different mindsets to generate customer citizenship behavior among customers.

This study provides new avenues in consumer psychology and behavior by unfolding the underlying mechanism through which mindsets lead to customer citizenship behavior, contributing to existing knowledge by extending the cognitive-affective-behavioral model.

This paper aims to introduce the Schmid–Leiman solution (SLS) as a useful tool to interpret the results of higher-order factor analyses in marketing research irrespective of the type of higher-order factor structure used (formative or reflective).

Two studies, one with retail shoppers in India and another with undergraduate students in Hong Kong, are used to compare different types of higher-order factor structures to test the utility of SLS.

The authors show that whether a reflective or a formative model is used to operationalize a higher-order construct, using SLS as an additional analysis gives useful insights into the factor structure at different levels and helps isolate their unique contributions to the explained variance.

The authors test higher-order models for store environment and consumer impulsiveness with data from retail shoppers and undergraduate students in two Asian countries, which may restrict the generalizability of the study findings. Future research may try to replicate our findings with other higher-order constructs and consumers in other countries.

The authors offer a checklist that can be used by future researchers to evaluate alternate higher-order factor structures and choose the appropriate one for their research context.

The authors show that using SLS is especially useful when there is a lack of clarity on the nature of relationships between the factors at different levels or about the independent contribution of the factors at different levels, in a higher-order factor structure.