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Previous research has studied interactive value formation (IVF) using resource- or practice-based approaches but has neglected the role of emotions. This article aims to show how emotions are correlated in problematic social media interactions and explore their role in IVF.

By combining a text mining algorithm, nonparametric Spearman's rho and thematic qualitative analysis in an explanatory sequential mixed-method design, the authors (1) categorize customers' comments as positive, neutral or negative; (2) pinpoint peaks of negative comments; (3) classify problematic interactions as detrimental, contradictory or conflictual; (4) identify customers' main positive (joy, trust and surprise) and negative emotions (anger, dissatisfaction, disgust, fear and sadness) and (5) correlate these emotions.

Despite several problematic social interactions, the same pattern of emotions appears but with different intensities. Additionally, value co-creation, value no-creation and value co-destruction co-occur in a context of problematic social interactions (peak of negative comments).

This study provides new insights into the effect of customers' emotions during IVF by studying the links between positive and negative emotions and their effects on different sorts of problematic social interactions.

Recent service studies suggest focusing on the service triad consisting of technology-customer-frontline employee (FLE). This study empirically investigates the role of service robots in this service triad, with the aim to understand the augmentation or substitution role of service robots in driving utilitarian and hedonic value and ultimately customer repatronage.

In study 1, field data are collected from customers (n = 108) who interacted with a service robot and FLE in a fast casual dining restaurant. Structural equation modeling (SEM) is used to test hypotheses about the impact of service robots' anthropomorphism, social presence, value perceptions and augmentation opportunities in the service triad. In study 2, empirical data from a scenario-based experimental design (n = 361) complement the field study by further scrutinizing the interplay between the service robot and FLEs within the service triad.

The study provides three important contributions. First, the authors provide empirical evidence for the interplay between different actors in the “customer-FLE-technology” service triad resulting in customer repatronage. Second, the empirical findings advance the service management literature by unraveling the relationship between anthropomorphism and social presence and their effect on perceived value in the service triad. And third, the study identifies utilitarian value of service robots as a driver of customer repatronage in fast casual dining restaurants.

The results help service managers, service robot engineers and designers, and policy makers to better understand the implications of anthropomorphism, and how the utilitarian value of service robots can offer the potential for augmentation or substitution roles in the service triad.

Building on existing conceptual and laboratory studies on service robots, this is one of the first field studies on the service triad consisting of service robots – customers – frontline employees. The empirical study on service triads provides evidence for the potential of FLEs to augment service robots that exhibit lower levels of functional performance to achieve customer repatronage. FLEs can do this by demonstrating a high willingness to help and having excellent interactions with customers. This finding advocates the joint service delivery by FLE – service robot teams in situations where service robot technology is not fully optimized.

The purpose of this paper is to analyse and evaluate the effect of customer experience management (virtual interaction, physical interaction and service interaction) on customer loyalty in the banking industry.

The study followed an explanatory research design to sample 384 respondents. Stepwise regression analysis was used to validate the relevance of the study model.

The results indicated that there is a positive association between customer experience management and customer loyalty. The dimensions of customer experience management, namely virtual interaction, physical interaction and service interaction, were also found to be statistically significant in explaining customer loyalty behaviour.

The study practically influences the way banks and other financial institutions gain competitive advantage through managing the experiences of customers in a volatile business environment. At a time when banks are no longer the only providers of financial services, the study offers a road map to reduce portfolio purchasing and switching behaviour through enhanced experience management at all customer touch points.

The study presents an augmented model of customer experience management which is linked to consumer loyalty.

The purpose of this study is to examine the role of interaction in supporting value co-creation during pre-purchase customer journey stages when selling professional B-to-B services. First, value co-creation in professional service firms (PSFs) is reviewed, and, second, the role of interaction in the different stages of a customer’s pre-purchase journey is explored, specifically in the context of B-to-B human resource management services.

Qualitative, semi-structured interview data was collected from potential B2B customers of a PSF in question, providing a broad coverage of prospective clients in architecture, engineering and IT sector.

In general, the findings of this study indicate that interaction plays a crucial role in pre-purchasing stages of a customer journey. In particular, these findings form understanding of how various interaction channels and content support PSF’s ability to co-create value with its prospects.

The existing research tends to concentrate on how value is created for existing customers, and far less attention has been paid to the perspective of prospects. This study contributes theoretically by providing novel insights into the current literature on value co-creation in PSFs by providing an understanding of how interactions in pre-purchase phases affect the co-creation of value from the perspective of prospects, which is a less researched viewpoint. Empirically, this study offers managers much-needed, context-specific knowledge of PSFs by comparing differences and pulling together similarities from each customer journey stage of PSF prospects.

The purpose of this paper is to make a conceptual argument for considering interactive work – i.e. work made up of micro-level exchanges or social interactions with third parties such as customers, patients or citizens – as a distinct analytical category in employment-related research. The argument is underpinned by the core role played by interactive work in valorisation.

This is a conceptual paper, with its argument based on key findings from the debates on symbolic interactionism, service work and interaction work. These are merged and combined with a valorisation perspective.

“Social interactions” and “work” have mostly been considered separately by theoretical sociology and the sociology of work. The author contends however that the two concepts should be viewed together, as social interactions at work are a constitutive feature of many occupations, jobs and tasks. This implies studying both exchange and social relationships between the different parties and their embeddedness in specific (multi-level) contexts. Moreover, there are two reasons why interactive work relates to specific working conditions: first, it involves customers or similar groups as third parties; second, it is key to valorisation. To systematically study interactive work, context-sensitive approaches spanning multiple (analytical) levels are recommended.

The article contributes to advancing the understanding of interactive work as a distinct form of work as yet under-theorised but deserving to be considered as a separate analytical category.

Service research offering a view of both the dark and bright sides of smart technology remains scarce. This paper embraces a critical perspective and examines the conflicting outcomes of smart services on the customer experience (CX), with a specific focus on chatbots.

This study uses empirical research methods to examine a single case study where an online retail service provider implemented a chatbot for customer service. Using discourse analysis, we analysed 7,167 conversations between customers and the chatbot over a two-year period.

The analysis identifies seven general themes related to the effects of the chatbot on CX: interaction quality, information gathering, procedure literacy, task achievement, digital trust, shopping stress and shopping journey. We illuminate both positive (i.e. having a pleasant interaction, providing information, knowing procedures, improving tasks, increasing trust, reducing stress and completing the journey) and negative outcomes (i.e. having an unpleasant interaction, increasing confusion, ignoring procedures, worsening tasks, reducing trust, increasing stress and abandoning the journey).

The paper develops a comprehensive framework to offer a clearer view of chatbots as smart services in customer care. It delves into the conflicting effects of chatbots on CX by examining them through relational, cognitive, affective and behavioural dimensions.

This methodological paper demonstrates how service firms can use digital technologies to quantify and predict customer evaluations of their interactions with the firm using unstructured, qualitative data. To harness the power of unstructured data and enhance the customer-firm relationship, the use of computerized text analysis is proposed.

Three empirical studies were conducted to exemplify the use of the computerized text analysis tool. A secondary data analysis of online customer reviews (n = 2,878) in a service industry was used. LIWC was used to conduct the text analysis, and thereafter SPSS was used to examine the predictive capability of the model for the evaluation of customer-firm interactions.

A lexical analysis of online customer reviews was able to predict evaluations of customer-firm interactions across the three empirical studies. The authenticity and emotional tone present in the reviews served as the best predictors of customer evaluations of their service interactions with the firm.

Computerized text analysis is an inexpensive digital tool which, to date, has been sparsely used to analyze customer-firm interactions based on customers' online reviews. From a methodological perspective, the use of this tool to gain insights from unstructured data provides the ability to gain an understanding of customers' real-time evaluations of their service interactions with a firm without collecting primary data.

This research contributes to the growing body of knowledge regarding the use of computerized lexical analysis to assess unstructured, online customer reviews to predict customers' evaluations of a service interaction. The results offer service firms an inexpensive and user-friendly methodology to assess real-time, readily available reviews, complementing traditional customer research. A tool has been used to transform unstructured data into a numerical format, quantifying customer evaluations of service interactions.

Service robotics, a branch of robotics that entails the development of robots able to assist humans in their environment, is of growing interest in the hospitality industry. Designing effective autonomous service robots, however, requires an understanding of Human–Robot Interaction (HRI), a relatively young discipline dedicated to understanding, designing, and evaluating robotic systems for use by or with humans. HRI has not yet received sufficient attention in hospitality robotic design, much like Human–Computer Interaction (HCI) in property management system design in the 1980s. This article proposes a set of introductory HRI guidelines with implementation standards for autonomous hospitality service robots.

A set of key user-centered HRI guidelines for hospitality service robots were extracted from 52 research articles. These are organized into service performance categories to provide more context for their application in hospitality settings.

Based on an extensive literature review, this article presents some HRI guidelines that may drive higher levels of acceptance of service robots in customer-facing situations. Deriving meaningful HRI guidelines requires an understanding of how customers evaluate service interactions with humans in hospitality settings and to what degree those will differ with service robots.

Robots are challenging assumptions on how hospitality businesses operate. They are being increasingly deployed by hotels and restaurants to boost productivity and maintain service levels. Effective HRI guidelines incorporate user requirements and expectations in the design specifications. Compilation of such information for designers of hospitality service robots will offer a clearer roadmap for them to follow.

The impact of frontline robots (FLRs) on customer orientation perceptions remains unclear. This is remarkable because customers may associate FLRs with standardization and cost-cutting, such that they may not fit firms that aim to be customer oriented.

In four experiments, data are collected from customers interacting with frontline employees (FLEs) and FLRs in different settings.

FLEs are perceived as more customer-oriented than FLRs due to higher competence and warmth evaluations. A relational interaction style attenuates the difference in perceived competence between FLRs and FLEs. These agents are also perceived as more similar in competence and warmth when FLRs participate in the customer journey's information and negotiation stages. Switching from FLE to FLR in the journey harms FLR evaluations.

The authors recommend firms to place FLRs only in the negotiation stage or in both the information and negotiation stages of the customer journey. Still then customers should not transition from employees to robots (vice versa does no harm). Firms should ensure that FLRs utilize a relational style when interacting with customers for optimal effects.

The authors bridge the FLR and sales/marketing literature by drawing on social cognition theory. The authors also identify the product categories for which customers are willing to negotiate with an FLR. Broadly speaking, this study’s findings underline that customers perceive robots as having agency (i.e. the mental capacity for acting with intentionality) and, just as humans, can be customer-oriented.

Using retail banking as a setting and focusing specifically on elderly customers (i.e. individuals aged 60 or more), this study aims to deepen the current understanding of how the physical context and the need for human interaction influence elderly customers' attitudes toward self-service technologies (SSTs) and their behavior.

Using face-to-face questionnaires, a sample of 505 elderly bank customers was collected. Data were analyzed using a multi-method approach, combining a moderated mediation analysis with a fuzzy-set qualitative comparative analysis.

The findings suggest that a pleasant retail space may result in a positive attitude toward SSTs, which increases their co-creation intention. It also highlights that need for interaction of elderly customers with employees has detrimental effects on their attitude toward SSTs.

The current analysis was carried out among Italian elderly banks' customers. Thus, the results are highly dependent on the context of the analysis. In addition, it does not consider the different degrees of knowledge and experience the elderly may have with technology.

This study suggests that providing access and support for using technology may be essential for banks to facilitate SSTs adoption in elderly customers.

To the best of the authors' knowledge, this study represents the first attempt to examine the influence of the physical context on elderly customers' attitudes toward SSTs and their consequent behavioral intentions. Furthermore, it highlights the importance of the human touch for these particular customers.