Brands are increasingly incorporating humanoid robots into frontline services (Brengman et al., 2021; Choi et al., 2021; Song & Kim, 2022). Due to their high level of human-likeness, humanoid robots induce a higher degree of anthropomorphism and hence engender more automated social presence among consumers than nonhumanoid robots (van Doorn et al., 2017). Yet, successfully integrating humanoid robots into customer service is a major challenge for most brands because they can trigger negative feelings and compensatory behaviours from consumers (Mende et al., 2019). While previous empirical research has identified contextual factors (Holthöwer & van Doorn, 2022; Pitardi, Wirtz, et al., 2022) and robotic design features (Belanche et al., 2021; Pitardi, Bartikowski, et al., 2022) that may attenuate such negative effects, literature on how brands can strategically frame the social relationship between a humanoid service robot and consumer to mitigate these effects remains scant (Chang & Kim, 2022). Moreover, like all technologies, humanoid robots are not error free (Choi et al., 2021), causing service failures that precipitate unfavourable consumer responses. Hence, it is imperative to examine how brands can proactively mitigate negative effects of a humanoid service robot failure. In this paper, we examine how framing the social relationship between consumers and humanoid robots can reduce attribution of globality (the extent to which consumers generalize robot-led failure to the brand as a whole) and negative word-of-mouth. Our second objective is to examine the variations of this effect in different cultures by drawing on the cultural dimension of power distance belief (Hofstede, 2001).
Previous research suggests that consumers perceive robots as social agents and during interactions experience their automated social presence (van Doorn et al., 2017). Novak and Hoffman (2019) conceptualize that consumers can form master-servant and partner-partner relationships with smart objects. Meanwhile, Schweitzer et al. (2019) provide empirical evidence that consumers form various relationships with smart devices, including servant, friend, or master. Building on this body of work, we conceptualize two types of consumer-humanoid relationship in frontline services: robot as servant to consumer and robot as partner with consumer. We posit that the two relationship types activate different states of power in consumers.
As a psychological state, power is defined as a sense of discretion to asymmetrically enforce one’s will over other others (Sembada et al., 2016; Sturm & Antonakis, 2015). A high power state triggers an agentic orientation whereas a low power state triggers a communal orientation. One consequence is that high power consumers develop a greater psychological distance to others and are more prone to use stereotypical beliefs in evaluations than low power consumers (Galinsky et al., 2006). Moreover, previous research suggests that consumers make inferences about a brand from a service employee’s negative behaviours (Folkes & Patrick, 2003) and this attribution of globality leads to dissatisfaction with the brand (Hess et al., 2007). Thus, we hypothesize that priming consumers to perceive a robot as partner leads to less attribution of globality than priming consumers to perceive a robot as servant, and this relationship is mediated by power. Furthermore, high power consumers are more action oriented than low power consumers (Galinsky et al., 2003). In a service failure, consumers can experience negative emotions like anger and frustration, prompting them to form coping responses (Gelbrich, 2010). We argue that high power consumers are more likely than low power consumers to express and act on their negative emotions. Therefore, we hypothesize that priming consumers with robot as partner leads to less negative WOM than robot as servant, mediated by power.
Distinct from power, power distance belief (PDB) is the degree to which individuals embrace and expect inequalities in power; eastern societies like Japan and China have higher PDB than western countries (Hofstede, 2001; Xu et al., 2021). We posit that consumers high on PDB will perceive a greater power differential between servants and partners, because they are more cognizant of social hierarchy and receptive of power disparity between social classes. In other words, the difference between consumer power states activated by the two relationship types is greater for high PDB consumers. Hence, we hypothesize that the mitigating effects of robot as partner (versus robot as servant) on attribution of globality and negative WOM are greater for high PDB than for low PDB consumers.
A pre-test with 60 administrative staff and students in Norway (female = 48%, average age = 32) enabled us to establish a baseline for our conceptualization that without any cues, robot as servant and partner relationship types are prevalent amongst consumers, and that consumers perceive a spectrum of power disparity between service robots and themselves. We have planned three experiments onward. To test the main and mediation effects, we will conduct an online experiment using Prolific in late August 2022. In line with previous studies (Choi et al 2021), we are currently developing a 3D animation as stimuli, which is more effective than pictorial stimuli. To enhance externality validity, we have planned a quasi-field experiment in early November, where a humanoid service robot will provide students with information on a fictional student travel insurance scheme. The quasi experiment will happen at a pop-up campus event. To test the mediated moderation, we will conduct an additional online experiment with one sample from US/Europe on Prolific and one sample from China on Wenjuanxing (wjx.cn) in October 2022.
Our research contributes to literature by showing that framing consumer-robot relationship as a partnership in frontline services can allow brands to attenuate negative effects of robot-led failures. We use a dynamic triadic framework that combines the micro-level of consumer traits and the meso-level of brands and markets (Wirtz et al., 2018). We also answer the call for more cross-cultural analyses in studying consumer frontline encounters with service robots (Belanche et al., 2020; Chang & Kim, 2022). Our finding will shed light on the role of a fundamental cultural factor and help firms market their service robots appropriately in different consumer markets.
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