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The purpose of this study is to identify the structural determinants of e-returns service interactions, examine their impact on online shoppers' loyalty and propose returns service interventions from an interactive marketing perspective to facilitate consumer interaction and repeat purchase intentions with e-retailers.

This study empirically tests the research hypotheses based on cross-sectional survey data collected from Chinese online consumers who experienced interactions during the product returns process.

E-return service interaction includes three determinants: access support, friendly interaction and communication support. These interactions positively impact ease of return, returns satisfaction and customer loyalty. Returns satisfaction is a key mediator in the relationship between return service interaction and loyalty. Access support and friendly interaction have both direct and indirect effects on loyalty, while communication support has only an indirect effect.

This study contributes to understanding e-returns service interaction by analyzing its structural determinants, providing a robust scale foundation and analytical framework for future empirical research. Additionally, this study explores the driving role of e-returns service interaction in forming e-customer loyalty, offering a theoretical basis for the service recovery function of e-returns service interaction. It enriches the application of service recovery theory and relationship marketing theory in the field of interactive marketing.

The study aims to propose a triadic interaction model to assess the effect of customer–customer (C2C), employee–customer and robot–customer interactions on customer voluntary performance in the context of smart dining.

An explanatory sequential mixed methods design was used. First, a quantitative study surveyed Foodom patrons to assess the impact of triadic interactions on customer voluntary performance. The mediating role of trust and social support and the moderating effect of the need to belong were also explored. A post hoc study (Study 2) analyzed online comments to validate and complement the survey findings.

While all interactions promote social support, the C2C interactions significantly correlate with customer trust. Moreover, customer voluntary performance is influenced by both customer trust and social support, while the need to belong remains as a moderator. Findings from Study 2 consolidate and enrich the relationships identified in Study 1.

This research reveals that patrons in smart dining still value interactions with employees and other diners. It enriches the stream of work on interaction quality by illuminating how different types of interactions could co-create value for customers, subsequently fostering voluntary behavior in smart dining contexts.

This research explores how patrons perceive interactions with robots in smart hospitality, highlighting their impact on trust and social support. It also sheds light on how interactions among robots, employees and customers influence customer voluntary performance, emphasizing the role of the need to belong in moderating relationships in this setting.

Customer-to-customer (C2C) interactions substantially affect the overall service experience. This study attempts to provide a better and deeper understanding of C2C interactions during the customer journey in the banking industry. The study aims to investigate the complexities of these interactions and to detect their outcomes and further implications in banking services.

This study used a sequential mixed-method approach. Firstly, semi-structured interviews were conducted to identify the components of C2C interactions during the customer journey. Subsequently, thematic analysis was performed to categorize the data and extract relevant components. Secondly, structural equation modeling was used to investigate the role of C2C interactions in behavioral outcomes.

The findings reveal that during the customer journey, C2C interactions plays a key role by providing information, managing queuing behavior, providing resources, and addressing issues related to other customers’ misbehavior. Additionally, C2C interactions have a positive direct effect on the customer experience, satisfaction, and loyalty. Customer experience, in turn, affects customer satisfaction and loyalty.

This study highlights the need for academic scholars to prioritize customers’ interaction during the customer journey in financial services, addressing a gap between industry directions and academic research in customer experience. Also, the findings help service providers develop effective strategies to enhance the customer experience by focusing on C2C interactions during the customer journey.

The e-services market is expected to reach nearly $500bn globally by 2028. As this marketplace grows, customer-to-customer interactions (CCIs) occurring through virtual channels will likely increase. Consequently, the purpose of this research is to examine how the context in which CCI’s occur (i.e. virtual vs in-person) and the frequency of their occurrence affects customer identification, leading to increased customer engagement and more favorable purchase behaviors.

Two studies were conducted to test the proposed models and hypotheses. The sample for Study 1 is comprised of college students taking in-person or online classes (n = 290). In Study 2, members of an online brand community (n = 125) were surveyed. Hypotheses were tested using structural equation modeling (SEM).

Overall, results support a mediation effect such that CCI context (virtual vs in-person) affects customer engagement and purchase behaviors via customer identification. Specifically, Study 1 finds that customer engagement behaviors (CEBs) are greater for in-person CCIs due to the frequency of interactions and heightened identification between customers. Study 2 further examines the CCI frequency-identification link and finds that customer-firm identification is the only form of identification that affects CEBs and purchase behaviors.

Limited customer engagement research has examined the effects of CCIs on CEBs, and research has rarely compared in-person to virtual CCI contexts. This paper addresses these shortcomings by testing the effects of in-person and virtual CCIs on CCI frequency, identification and CEBs. This research fills another important gap in the literature by considering the unique effects of specific dimensions of customer identification on CEBs and purchase behaviors.

This study builds on a conceptual model by integrating AI features – Perceived intelligence (PIN) and anthropomorphism (PAN) – while extending expectation confirmation theory (ECT) factors – interaction quality (IQU), confirmation (CON), and customer experience (CSE) – to evaluate the continued intention to use (CIU) of AI-enabled digital banking services.

Data were collected through an online questionnaire administered to 390 digital banking customers in India. The data were further analysed, and the presented hypotheses were evaluated using partial least squares structural equation modelling (PLS-SEM).

The research indicates that perceived intelligence and anthropomorphism predict interaction quality. Interaction quality significantly impacts expectation confirmation, consumer experience, and the continuous intention to use digital banking services powered by AI technology. AI design will become a fundamental factor; thus, all interactions should be user-friendly, efficient, and reliable, and the successful implementation of AI in digital banking will largely depend on AI features.

This study is the first to demonstrate the effectiveness of an AI-ECT model for AI-enabled Indian digital banks. The user continuance intention to use digital banking in the context of AI has not yet been studied. These findings further enrich the literature on AI, digital banking, and information systems by focusing on the AI's Intelligence and Anthropomorphism variables in digital banks.

Inspired by the concept of the moment of truth, this study aims to examine how service interactions between hotel front-desk staff and a first-time check-in guest affect the guest’s brand satisfaction and brand attitudes, considering the moderating effect of welcome hospitality.

This study employs a between-subjects 2 (check-in service with high-service interaction vs low-service interaction) × 2 (with welcome hospitality vs without welcome hospitality) experimental method to investigate the mechanism of building brand attitudes towards a hotel during the check-in process.

The results of Study 1 showed that participants in the high-service interaction group reported higher brand satisfaction and brand attitudes than the low-service interaction group. It also confirmed that brand satisfaction fully mediates the relationship between service interactions and brand attributes. The results of Study 2 demonstrated the moderating effect of welcome hospitality. When service interaction is low, welcome hospitality can effectively improve brand satisfaction, but when service interaction is high, the improvement in brand satisfaction is smaller.

This research contributes to the literature on service interactions by potentially first experimentally examining the impact of first-time employee-customer interactions within a hotel setting. Recommendations were provided to hotel operators on how hotel staff can improve their service interactions.

This study aims to examine the interaction effects of chatbots’ language style and customers’ decision-making journey stage on customer’s service encounter satisfaction and the mediating role of customer perception of emotional support and informational support using the construal level theory and social support theory as conceptual frameworks.

This study used a scenario-based experiment with a 2 (chatbot’s language style: abstract language vs concrete language) × 2 (decision-making journey stage: informational stage vs transactional stage) between-subjects design.

Findings show that during the informational stage, chatbots that use abstract language style exert a strong influence on service encounter satisfaction through emotional support. During the transactional stage, chatbots that use concrete language style exert a strong impact on service encounter satisfaction through informational support.

Findings provide some suggestions for improving customer–chatbot interaction quality during online service encounters.

This study offers a novel perspective on customer interaction experience with chatbots by investigating the chatbot’s language styles at different decision-making journey stages.

This study aims to identify the groups of value cocreators in the context of social media in the retail banking industry and resources that predict customer membership among different groups of value cocreators.

This study reviewed the literature and developed measurement instruments for the constructs of interest. Data were collected from 406 customers in an emerging market in 2019 and analyzed using latent profile analysis.

This study identified three profiles of value cocreators on social media based on the actual practices of resource integration that enliven value cocreation. Second, this study explains the differences in the performance of resource integration practices to cocreate by the types of resources that customers integrate into social media. Third, this study fills the need for knowledge of value cocreation in different contexts and industries (e.g. banks).

This study analytically relates a set of resources to the variety and intensity of the value cocreation practices adopted by bank customers in interactive environments. The emphasis on how value cocreation practices in online environments combined with customer resources (e.g., a person-centered approach) allows to identify unique profiles of value cocreators on social media. The findings inform managers of the profiles of cocreators, which customers are more attractive as value cocreators on social media, and which resources managers should help customers develop to increase cocreation on social media.

Drawing on social identity theory (SIT), the current research highlights the sequential mediation effects of customer interaction, functional value and hedonic value in linking customer-brand identification and self-representation with online brand advocacy (OBA).

Data were gathered from 483 Egyptian and 595 non-Egyptian Aliexpress shopping platform customers, then analyzed using SmartPLS 4.

The multigroup analysis findings revealed that customer interaction and functional/hedonic values sequentially mediated the linkages of customer-brand identification and self-presentation with OBA for Egyptian and non-Egyptian user groups.

The novelty of this study is that it tested and validated customer interaction with the Aliexpress service scale, allowing for reflection on the interactive nature of this platform between Egyptian and non-Egyptian customers. SIT also lends credence to the idea that self-presentation mediates the effect of customer-brand identification on Aliexpress’s OBA, potentially shedding new light on this understudied dimension using a theoretical framework.

Underpinning social identity theory (SIT) and service-dominant logic (SDL), the current paper seeks to explore the effect of self-presentation on online brand advocacy (OBA). Furthermore, this paper investigates the mediating role of hedonic value and the moderating role of customer interaction with e-commerce websites (i.e. Amazon, Walmart and eBay).

Data were collected from customers of three e-commerce platforms (i.e. Walmart, Amazon and eBay) using a structured questionnaire – multi-group analysis applied on SmartPLS 4.4.

Self-presentation has a positive role in increasing hedonic value and its impact on OBA. The moderating effect of customer interaction on these relationships is also investigated and found to be significant.

Our findings underscore the significance of fostering inclusive online communities and favorable online settings. Existing findings are consistent with overarching objectives of digital empowerment and enhanced online interaction quality. This paper contributes to harmonious and collaborative digital societies by encouraging personalized experiences that foster a sense of belonging among diverse customers.

This paper adds to the existing body of knowledge by comparing customer behavior on three major e-commerce platforms, going beyond the traditional focus on a single platform. Drawing on SIT and SDL, this paper provides a distinct nomological framework for OBA that unifies disparate constructs, filling theoretical gaps in our understanding of online customer behavior.