Attitudes toward service robots: analyses of explicit and implicit attitudes based on anthropomorphism and construal level theory

Purpose Building on both the uncanny valley and construal level theories, the analyses detailed in this paper aims to address customers' explicit and implicit attitudes toward various service robots, categorized by the degree of their human-like appearance, namely, mechanoids (low human-likeness), humanoids (medium human-likeness) and realistic robots (high human-likeness). Design/methodology/approach The analyses reflect a mixed-method approach, across three studies. A qualitative study uses focus groups to identify consensual attitudes. An experiment measures self-reported, explicit attitudes toward the three categories of robots. Another experiment explores customers' implicit attitudes (unconscious and unintentional) toward robots, using three implicit association tests. Findings Customers express both positive and negative attitudes toward service robots. The realistic robots lead to both explicit and implicit negative attitudes, suggesting that customers tend to reject these robots in frontline service settings. Robots with lower human-likeness levels generate relatively more positive attitudes and are accepted to nearly the same extent as human employees in hospitality and tourism contexts. Practical implications Because customers reject, both consciously and unconsciously, very human-like robots in service encounters, managers should leverage this key finding, along with the more detailed results, to inform their strategic introduction of robots into hospitality frontline service settings. Originality/value The combined qualitative and quantitative studies specify and clarify customers' implicit and explicit attitudes toward robots with different levels of human-likeness, in the real-world setting of hospitality and tourism services. Such insights can inform continued research into the effects of these service innovations.

Automated summary

This paper examines customers' explicit and implicit attitudes towards service robots with different levels of human-likeness. The findings reveal that highly realistic robots are met with negative attitudes, while robots with lower human-likeness generate more positive attitudes and are accepted similarly to human employees in hospitality settings. This key finding has important implications for the strategic introduction of robots in the hospitality industry.