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The aim of this study is twofold: (1) to gain insight into the different perspectives on the relationship between patient and person centeredness and (2) to learn more about the differences between non-academic and academic stakeholders in the healthcare system.

This mixed-methods study includes a scoping review on person and patient centeredness and in-depth interviews with patients, caregivers, staff and management of healthcare organizations. The data were analyzed by following the six phases of Braun and Clarke.

The analysis of the data showed four different perspectives on patient versus person centeredness: (1) they are synonyms; (2) one term is favorite; (3) they should be in balance; and (4) person centeredness is the surplus on top of patient centeredness.

There are different perspectives on patient versus person centeredness. Perspectives differ between people and can change over time. Some people feel like a patient all the time, other people feel like a person all the time, and some feel like a patient at one point in time and as a person at another point in time.

These different perspectives can have important implications for the so-called moments of truth. In their role as patients, people value functional encounters and in their identity as people they value meaningful encounters with caregivers.

By unraveling these different perspectives, novel insights were found in the different perspectives people can take.

Although consumers feel that the move toward service robots in the frontline so far was driven by firms' strive to replace human service agents and realize cost savings accordingly, the COVID-19 pandemic has led customers to appreciate frontline robots' ability to provide services in ways that keep them safe and protected from the virus. Still, research on this topic is scant. This article offers guidance by providing a theoretical backdrop for the safety perspective on service robots, as well as outlining a typology that researchers and practitioners can use to further advance this field.

A typology is developed based on a combination of a theory- and practice-driven approach. Departing from the type of behavior performed by the service robot, the typology synthesizes three different service robot roles from past literature and proposes three new safety-related role extensions. These safety-related roles are derived from a search for examples of how service robots are used in practice during the COVID-19 pandemic.

The typology's roles are corroborated by discussing relevant robot implementations around the globe. Jointly, the six roles give rise to several ideas that jointly constitute a future research agenda.

This manuscript is (one of) the first to provide in-depth attention to the phenomenon of service customers' physical safety needs in the age of service robots. In doing so, it discusses and ties together theories and concepts from different fields, such as hierarchy of needs theory, evolutionary human motives theory, perceived risk theory, regulatory focus theory, job demand–resources theory, and theory of artificial intelligence job replacement.

The purpose of this paper is to examine whether explicitly communicating the customer’s resource integrating role in value propositions improves or diminishes value proposition effectiveness.

Based on existing research on value propositions, three effectiveness criteria are used: role clarity, expected customer value, and purchase intention. Two experiments manipulating the presence of the customer’s resource integrating role in value propositions test the conceptual model in both an indirect interaction (Study 1, toothpaste, n=207) and a direct interaction context (Study 2, fitness program, n=228). Additionally, Study 2 includes the moderating role of resource availability.

Explicitly communicating the customer’s resource integrating role in value propositions increases customers’ role clarity, which in turn influences customer’s attitude toward the service and purchase intention through a service-related (i.e. expected benefits and expected efforts) and an ad-related (i.e. ad credibility and attitude toward the ad) route. However, these results only hold for customers high in resource availability.

This research provides initial empirical support for the often-stated claim that value propositions should include the (potential) value of the offering as well as the (resource integrating) role of the customer. Taking a broader perspective, this research provides initial empirical support for recent calls to develop marketing communication practices that facilitate value-in-use. This paper’s findings show that adopting service logic in marketing communications seems to improve value propositions’ effectiveness.

The purpose of this paper is to provide an illustrated step-by-step guideline of the partial least squares factorial structural equation modeling (PLS FAC-SEM) approach. This approach allows researchers to assess whether and how model relationships vary as a function of an underlying factorial design, both in terms of the design factors in isolation (i.e. main effects) as well as their joint impact (i.e. interaction effects).

After an introduction of its building blocks as well as a comparison with related methods (i.e. n-way analysis of variance (ANOVA) and multi-group analysis (MGA)), a step-by-step guideline of the PLS FAC-SEM approach is presented. Each of the steps involved in the PLS FAC-SEM approach is illustrated using data from a customer value study.

On a methodological level, the key result of this research is the presentation of a generally applicable step-by-step guideline of the PLS FAC-SEM approach. On a context-specific level, the findings demonstrate how the predictive ability of several key customer value measurement methods depends on the type of offering (feel-think), the level of customer involvement (low-high), and their interaction (feel-think offerings×low-high involvement).

This is a first attempt to apply the factorial structural equation models (FAC-SEM) approach in a PLS-SEM context. Consistent with the general differences between PLS-SEM and covariance-based structural equation modeling (CB-SEM), the FAC-SEM approach, which was originally developed for CB-SEM, therefore becomes available for a larger amount of and different types of research situations.

Following a contingency approach, this paper aims to understand when service automation can enhance or destroy value for customers in the frontline by (1) providing a comprehensive overview of factors that influence the value co-creation/co-destruction potential of service automation and (2) zooming in on the combination of service contexts and service tasks to develop research propositions.

This paper uses a grounded theory approach based on qualitative data from multiple methods (i.e. a diary study with follow-up interviews, a consultation of academic experts and a storyboard study) as well as a systematic literature review to develop (1) a Framework of Automated Service Interactions (FASI) and (2) a contingency model for service tasks/contexts.

This paper presents a framework which gives an overview of factors influencing the value co-creation/co-destruction potential of service automation. The framework discerns between three types of factors: service design (i.e. controllable and manageable by the organization), static contingency (i.e. uncontrollable and fixed) and dynamic contingency (i.e. uncontrollable and flexible). Furthermore, the paper presents a contingency model based on the combination of service contexts and service tasks which results in seven research propositions.

This paper brings structure in the fragmented field of service automation. It integrates and summarizes insights regarding service automation and sheds more light on when service automation has the potential to create or destroy value in the organizational frontline.

Service robots are now an integral part of people's living and working environment, making service robots one of the hot topics for service researchers today. Against that background, the paper reviews the recent service robot literature following a Theory-Context-Characteristics-Methodology (TCCM) approach to capture the state of art of the field. In addition, building on qualitative input from researchers who are active in this field, the authors highlight where opportunities for further development and growth lie.

The paper identifies and analyzes 88 manuscripts (featuring 173 individual studies) published in academic journals featured on the SERVSIG literature alert. In addition, qualitative input gathered from 79 researchers who are active in the service field and doing research on service robots is infused throughout the manuscript.

The key research foci of the service robot literature to date include comparing service robots with humans, the role of service robots' look and feel, consumer attitudes toward service robots and the role of service robot conversational skills and behaviors. From a TCCM view, the authors discern dominant theories (anthropomorphism theory), contexts (retail/healthcare, USA samples, Business-to-Consumer (B2C) settings and customer focused), study characteristics (robot types: chatbots, not embodied and text/voice-based; outcome focus: customer intentions) and methodologies (experimental, picture-based scenarios).

The current paper is the first to analyze the service robot literature from a TCCM perspective. Doing so, the study gives (1) a comprehensive picture of the field to date and (2) highlights key pathways to inspire future work.

The purpose of this paper is to provide insight into the decision process behind whether customers complain, and to identify the effects of the situational factor credence quality in this decision process.

A quasi-experimental design is used in which scenarios are applied in combination with a survey to test and to compare the model and its boundary conditions with existing consumer behavior models.

The mental-accounting process (theory of trying to complain (TTC)) seems to be a stronger predictor than mere attitude models (theory of planned behavior) when trying to explain intention to complain. Second, anticipated justice from complaint handling is a strong driver of intention to complain. Third, in both models, subjective norms are a strong predictor of intention to complain.

This study contributes to both theory and practice by extending existing theory and offering the TTC, and by providing practical insight for service managers.

To the best of the authors’ knowledge, the current study is the first to compare systematically two complaint approaches explaining complaint intention: the attitude model and the mental-accounting model.

Most transactions initiated online are completed by some form of offline fulfilment, i.e. the delivery of the goods to the customer's doorstep. In previous studies, web site performance or e‐service quality was found to be an important antecedent of customer satisfaction and loyalty. In traditional settings, physical fulfilment is considered an important driver of customers’ behavioral intentions. This study models and tests the combined effects of online and offline service components on customer responses.

This is an empirical, cross‐sectional study across four online industries.

In the surveyed industries offline fulfilment appears to be at least as important as web site performance.

Further research is needed on how value and joy are created as part of the total e‐experience. Furthermore, the importance of offline fulfilment in effecting customer satisfaction and loyalty levels for different online services needs further investigation.

Online retailers must ensure offline quality to at least the same level as online quality.

Important insights into the absolute and relative importance of online and offline fulfilment dimensions have been generated in a broader e‐commerce context.

This empirical study examines the impact of context‐team factors and team‐employee factors on perceived uncertainty in self‐managed service teams. The results of our study show that context‐team factors rather than team‐employee factors are critical to the extent of uncertainty employees perceive when providing customer service. Furthermore, perceived uncertainty has negative impact on self‐managed team outcomes in terms of job satisfaction and intention to leave the team. Besides this, our findings indicate that team commitment to customer service quality can serve as an effective tool to handle the negative consequences of perceived uncertainty in self‐managed service teams. Finally, in addition to the cross‐sectional analysis, a longitudinal exploration has been carried out, the outcomes of which suggest that the structural relationships are changing over time, underlining the need to take dynamic considerations into account in analyzing the effectiveness of self‐managed work teams.

The purpose of this paper is twofold. First, develop and test a conceptual model to understand customers’ intention to adopt online complaining. Second, to assess two competing perspectives regarding elaboration likelihood for the moderating impact of individual differences.

A scenario‐based survey was used to assess respondents’ beliefs, attitude, and usage intentions toward online complaining. Furthermore, individual and situational characteristics were assessed. The data were analyzed using partial least squares path modeling.

Attitude toward online complaining is a function of both process and outcome beliefs. It is also influenced by individual characteristics, but remains unaffected by situational characteristics. In contrast, usage intentions are influenced by situational characteristics, but by personal differences. For the moderating impact of affect‐based personality characteristics, the often used cognitive effort perspective to elaboration likelihood is not supported. Rather the consumption value perspective applies for these variables.

The use of a single setting, as well as the use of scenarios, may negatively impact external validity. Future research is needed to further explain the contradictory perspectives regarding information processing.

The results provide insight into determinants of customer online complaining. This opens up new possibilities to increase the number of complainants in case of service failures and for firms to take corrective action.

To the authors’ best knowledge, this is a first empirical study aimed at understanding what drives online customer complaining.