The service triad: an empirical study of service robots, customers and frontline employees
In hospitality services such as restaurants, service triads consisting of technology, customer, and frontline employees (FLEs) are becoming more common, with service robots supporting FLEs in performing advanced frontline tasks such as talking with customers or serving food. The Covid-19 pandemic has further amplified the importance of service robots due to the need to minimise human-to-human contact. Research indicates that service robots’ roles are dependent on their level of anthropomorphism, which refers to when the real or imagined behaviour of non-human agents are given human-like characteristics, motivations, intentions, or emotions. In some cases, service robots can not only augment but also substitute FLEs.
However, the literature about frontline service robots is fragmented, mostly conceptual in nature, and misses out on the social complexity that determines technology adoption. Moreover, previous studies in hospitality mainly focus on welcoming or greeting hotel customers, rather than customer frontline experience in restaurants.
Therefore, this study seeks to examine the relationships within the service triad of service robots, FLEs, and customers, and how these affect customer repatronage in hospitality. Specifically, it proposes a conceptual model through which service robots’ anthropomorphism impacts their social presence, utilitarian and hedonic values, and ultimately customer patronage.
Method and sample
This study comprised two studies. Study 1 collected field data from 108 customers who interacted with a humanoid service robot and FLE in a fast casual Asian-style dining restaurant in Europe. The sample consisted of relatively young customers such as students, young couples, and families with young kids. The constructs including customer repatronage intention, FLE interaction quality, the service robot’s utilitarian and hedonic value, social presence, and anthropomorphism were adapted from existing measurement scales. Partial least squares structural equation modeling (PLS-SEM) was used to test the hypotheses.
Study 2 complemented the field study by further scrutinizing the interplay between the service robot and FLEs within the service triad. Empirical data was collected from a scenario-based 2 (service robot utilitarian value: high, low) x 2 (service robot hedonic value: high, low) x 3 (FLE interaction quality: high, low, no interaction) between-subject experiment. 361 US MTurk participants were randomly assigned to one of the experimental conditions.
Key findings
- It was found that when customers perceive an anthropomorphized service robot, they are also likely to perceive being with another social entity in the restaurant. Both anthropomorphism and social presence have a strong positive effect on the service robot’s utilitarian and hedonic value. This supports the idea that humanoid service robots provide utitlity and gratification to customers in hospitality services.
- Moreover, anthropomorphism has a stronger influence on utilitarian value compared to hedonic value, as it affects the provision of the core service (serving drinks and food) more than entertaining guests in the service triad.
- Only utilitarian value demonstrates a strong, significant, positive effect on customer repatronage in both studies, while the effect of hedonic value on customer repatronage was only significant in the scenario-based experimental design, but insignificant in the field study. This may be attributed to the limited hedonic features of the service robot in the field experiment, as it communicates laterally and does not respond to customers.
- Moreover, the finding illustrates the delicate interplay of actors within the customer-FLE-technology triad. In situations where the utilitarian value of service robots is low, high FLE interaction quality leads to higher customer repatronage. However, the same level of customer repatronage can be achieved without FLE interaction if the utilitarian value of the service robot is high, suggesting that service robots with a high utilitarian value can make the interaction with FLEs redundant in a fast casual dining restaurant.
Recommendations
These findings have several managerial implications. First, for restaurants, particularly fast casual dining restaurants, implementing frontline service robots can reduce costs and increase productivity. With the robots’ high levels of functional performance, customers’ need to engage in high-quality interactions with FLEs can decrease, so FLEs no longer always need to take an active role in the service encounter. During the Covid-19 pandemic, service robots can facilitate social distancing requirements and ensure sufficient capacity to deliver consistent service during high staff shortages.
Second, for service settings in which robots are augmented by FLEs rather than substituting them, FLEs can compensate for service robots’ lower levels of functional performance by engaging in high-quality interaction with customers. This advocates joint service delivery by FLE – service robot teams in situations where service robot technology is not fully optimized, which can generate better service outcomes, such as customer repatronage.
Third, the field study results showed that the more service robots in restaurants evoke the perception of having thoughts and emotions, the higher customers evaluate the robots’ utilitarian and hedonic value. Robot engineers and designers should design service robots with the ability to have thoughts and convey emotions in order to display social presence, and in turn create customer value.
Finally, policy makers should recognise the importance of role readiness for employees to acclimate in the new service environment, as the tasks, jobs, and skills of FLEs in hospitality will be subject to change following the surge in digital technologies and automation. In some cases, FLEs will be substituted while in other cases augmented by service robots. Therefore, FLEs should be provided with the opportunity to reskill (in case of job substitution) or upskill (in case of job augmentation), with specific collaborative skills on how to work with a service robot in a team.
Researcher
More information
The research article is also available on eprints.