The Rise of Service Robots in the Hospitality Industry

 The Rise of Service Robots in the Hospitality Industry

The current wave of service technologies is service robots, “system-based autonomous and adaptable interfaces that interact, communicate and deliver service to an organization’s customers” (Wirtz et al., 2018, p. 4). The spread of Covid-19 has boosted implementation of service robots in the hospitality industry as more consumers become more sensitive to risk of infectious disease from interpersonal interactions. Adoption of service robots could signal low interpersonal contacts, reduce perceived risk of virus transmission, which might in turn increase visit intention (Wan, Chan, & Luo, 2020). As a result, consumers show a stronger preference for robot-staffed (vs. human-staffed) hotels due to safety concerns . The market size for service robots in the healthcare and hospitality sectors is projected to grow by 942 million USD during 2020-2024 (Technavio, 2020).To get more news about GRS, you can visit glprobotics.com official website.

In this article, we will first discuss different roles that can be played by service robots based on different levels of intelligence. Then, we will further discuss important factors influencing consumer adoption of service robots, followed by introducing cross-cultural aspects in service robot adoptions.
What Roles Can Service Robots Play?
Service robots can be equipped with different levels of artificial intelligence: mechanical, analytical, intuitive, and empathetic (Huang & Rust, 2018). Mechanical intelligence relates to standardized and transactional tasks, which require a minimal level of learning (e.g., YO2D2, a room service robot, at Yotel Boston). Analytical intelligence is based on systematic and rule-based learning from big data and enables logical thinking in decision-making. For example, chatbots find an appropriate answer to customer enquiry, retrieving it from big data collected from customer FAQ. Service robots with these two levels of intelligence can basically handle functional tasks such as delivering food and answering a customer’s question. They free human staff from the high volume of trivial customer requests rather than taking higher-value roles.

Intuitive intelligence relates to the capability to process holistic and contextual thinking and thus provide personalized services. Empathetic intelligence refers to the ability to recognize and appropriately respond to people’s emotions. This “highest” level of intelligence enables service robots to deliver socially and emotionally interactive services, which is the ultimate goal of service robotics (Rafaeli et al., 2017). These two levels of intelligence focus on emotional and social capabilities of technology to enhance consumers’ service experience (Huang & Rust, 2018). Current service robot technologies have been developing a higher level of intelligence to make customer engagement with frontline robots more intuitive and natural. Alternatively, to overcome the limited social and emotional capacity of robots, human staff and service robots can collaborate so that service robots do the mechanical and analytical work, and human staff deal with emotional tasks. For instance, during the check-in process, a service robot can deliver luggage to the assigned room, while the human staff provides the guest with a warm reception.
What Makes Consumers Adopt Robots?
When implementing service robots, particularly customer-contact robots, companies should first consider the key factors that influence consumers’ adoption/acceptance of the new technology.

Building on the classic technology acceptance model (Davis, 1989), the service robot acceptance model suggests that consumers’ acceptance of service robots is determined not only by its functionality (e.g., perceived usefulness and ease of use), but also by social-emotional and relational elements that robots can provide (Wirtz et al., 2018). For the social-emotional dimension, the model shows that perceived humanness of service robots through their appearance and social actions (e.g., smiling) can influence consumers’ attitudes and willingness to interact with them (Breazeal, 2003; Tinwell et al., 2011). Moreover, for the relational dimension, consumers can trust and thus accept service robots when they feel secure and comfortable with the technology (Wirtz et al., 2018). The trust building can also be achieved by its human-like attributes including service robots’ appearance and emotional displays (Tinwell et al., 2011).

Together, as service robots are able to engage consumers on a social level like human employees (Wirtz et al., 2018), their capability to meet consumers’ social-emotional and relational needs is critical in consumer acceptance and perception of service robots. Service robot acceptance can be influenced by the extent to which they can provide enjoyable interactions – a feeling of care and friendliness, and personal connection to consumers (i.e., rapport). Supporting this notion, Tung and Au (2018) examined guest experiences with robots analyzing online reviews from hotels and found that a considerable number of reviewers commented on service robots’ physical embodiment and social interactivity.

For this reason, a large body of previous research on service robotics explains consumer perceptions of service robots based on the extent to which consumers treat robots as human beings (i.e., anthropomorphism, the psychological tendency to attribute human characteristics, intentions, and emotions to nonhuman objects; Epley, Waytz, & Cacioppo, 2007). Robots with a greater number of human-like features, such as face, voice, and movement (e.g., Sophia by Hanson Robotics or Pepper by Softbank Robotics), are perceived to be more human-like than those with fewer of these features.