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Masayo Kodama, President, Reborn Kyoto NPO, believed foreign-aid food saved her and other Japanese from starvation after World War II. Kodama was determined to help others suffering in third world countries. After distributing emergency supplies in Cambodia, Kodama developed a new vision: teach impoverished people how to “fish” and they would feed themselves and their children for life. She decided to teach dressmaking skills to people in third-world countries. Kodama recruited volunteers in Japan and these women, in turn, collected and prepared silk from kimonos. Japanese volunteer seamstresses took the silk and supplies, traveled to such places as Vietnam and Yemen, and taught people how to create clothes suitable for sale in western markets of Japan and the US. Although the sale of products, along with small grants and private donations, yielded subsistent revenues for the nonprofit organization, Kodama wondered how to build her organization and to find a replacement for herself with so few resources.

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).

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.

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.

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.

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.