Service robots, which are system-based autonomous and adaptable interfaces that interact, communicate and deliver services to an organization’s customers (Wirtz et al., 2018), are increasingly adopted by service providers (Huang & Rust, 2018; Lu et al., 2020; Odekerken-Schröder et al., 2022; Wirtz et al., 2018). Consequently, there is a rapidly growing body of literature on the topic (Haenlein & Kaplan, 2021). While existing empirical studies have primarily focused on the technology’s adoption and acceptance (Mende et al., 2019), studies that investigate the post-purchase stage of robot-enabled services are scarce. For example, if a hotel service robot quickly and reliably brought Joyce an ordered coffee to her room, will this experience still influence her feelings about her stay when she is back home? Will it maybe even impact future purchase decisions? What if the robot had taken excessively long? With our study, we seek to understand how such different experiences shape customer attitudes and behaviors post-purchase (e.g., emotion, re-usage, repeat purchase).
To gain an initial understanding of how service robot-related post-purchase attitudes and behaviors are formed, we have analyzed 1107 reviews from online hotel booking websites and review platforms. All these reviews (partly) reflect on the customer’s experience with a hotel’s service robot. Based on these reviews, we see that customers’ primary and secondary appraisals play a crucial role in the formation of post-purchase attitudes and behaviors. For example, one customer writes “Wally the robot butler is pretty awesome, he frightened my husband at first, but after he got used to it, he ended up looking for reasons to have Wally deliver something to our room”. In this review, we can clearly observe a primary appraisal (i.e., fear), a secondary appraisal (i.e., accommodation), and ultimately post-purchase behavior (i.e., reuse).
Based on these reviews, we have built a model drawing on cognitive appraisal theory (Lazarus & Folkman, 1984) and coping strategies (Mick & Fournier, 1998) to better understand post-purchase attitudes and behaviors after robot-enabled services. We have planned field and lab experiments to validate and extend this model. In this way, we extend on from previous research and determine how real-life (rather than imagined) experiences with service robots shape actual post-purchase attitudes and behaviors as well as what role customers’ primary appraisals and coping strategies play in this process.

Appraisal theory posits that primary appraisals are driven by user perceptions (Fadel & Brown, 2010). That is, a primary appraisal is formed by assessing what is personally at stake in a given situation, resulting in irrelevant, pleasant/positive and stressful/negative outcomes (Lazarus & Folkman, 1984). The second appraisal is then concerned with identifying a suitable coping strategy (Lazarus, 1991). Applying appraisal theory to employee interactions with service robots, Paluch et al. (2022) demonstrate that these interactions can be modelled as multistage appraisal processes. We build on these findings and suggest that appraisals are also key in understanding the formation of customers’ service robot-related post-purchase attitudes and behaviors. More specifically, we suggest that customers deal with their service robot related appraisals through either avoidance (e.g., neglect, abandonment, distancing) or confrontation strategies (e.g., accommodation, partnering, mastering; Mick & Fournier, 1998).
Existing research has thus far predominantly focused on customer acceptance as a predictor of actual use of service robots (Wirtz et al., 2018). However, based on the analyzed reviews, we see that actual use of services robots is often not intentional. Instead, customers often merely order the service and are then surprised when a service robot is delivering it. For example, one customer writes “Our best experience at this hotel was ‘Wally’ [..]. We ordered some towels and to our surprise, this beautiful robot was at our doorstep bringing what we requested. This definitely is one notch up in customer’s satisfaction.” This observation highlights the need for analyzing customers’ appraisal and coping processes to understand how they feel and behave after a robot-enabled service. Applying appraisal and coping theory in a context of customer–service robot interactions is one core contribution of our study.

We started our investigation by analyzing 1107 reviews from online hotel booking websites. All reviews referred to the service robots employed by different hotels. These hotels used the same service robot which is characterized by a high level of autonomy, substituting the frontline employee in autonomously operating the elevator and delivering hotel amenities and missing items (e.g., toiletries, personal care, phone charger, coffee) to the guest’s hotel room. Following an inductive critical incident approach, we discovered the reoccurring theme of appraisal, coping and re-purchase (use) within the reviews. This led us to construct our initial model (see Figure 1).
In the next stages of our research, we validate and extend this model in multiple lab and especially field experiments. Here, we will especially focus on including robot-specific elements. We already collaborate with industry partners that are eager to support our research in hospitality contexts.

Preliminary Findings
Figure 1 shows the conceptual model. Table 1 provides an illustrative overview of reviews.
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Conclusion and outlook
Thus far, most studies investigating service robots are concerned with the pre-purchase (e.g., intention to use; Wirtz et al., 2018) and purchase stages (e.g., acceptance, customer satisfaction; Choi et al., 2020). However, as service robot interactions become more frequent, it is increasingly important to understand how these interactions impact customers’ attitudes and behaviors post-purchase. Consequently, our theoretical model suggests that a multistage process of appraisal and coping underlies customers’ service robot-related post-purchase attitudes and behaviors. Fitting in with the theme of this special issue, these post-purchase behaviors are often not only unanticipated, but also unintended (e.g., customers only ordering food to spend time with the robot).
In the next steps, we will validate and extend our model by using field and lab experiments. In this way, we seek to contribute to the service robot literature by furthering our understanding of the thus-far underexplored post-purchase stage. Additionally, by observing real behaviors and attitudes in the field rather than during hypothetical experiments (de Keyser & Kunz, 2022), we aim to understand the social complexity of the real world. By doing so, we complement current state-of-the-art literature by investigating the real-life impact of these robots (Lu et al., 2020).