Advertisement

International Journal of Social Robotics

, Volume 2, Issue 2, pp 175–186 | Cite as

A Cross-cultural Study: Effect of Robot Appearance and Task

  • Dingjun Li
  • P. L. Patrick RauEmail author
  • Ye Li
Article

Abstract

This study investigates the effects of culture, robot appearance and task on human-robot interaction. We propose a model with culture (Chinese, Korean and German), robot appearance (anthropomorphic, zoomorphic and machinelike) and task (teaching, guide, entertainment and security guard) as factors, and analyze these factors’ effects on the robot’s likeability, and people’s active response to, engagement with, trust in and satisfaction with the robot. We conducted a laboratory experiment with 108 participants to test the model and performed Repeated ANOVA and Kruskal Wallis Test on the data. The results show that cultural differences exist in participants’ perception of likeability, engagement, trust and satisfaction; a robot’s appearance affects its likeability, while the task affects participants’ active response and engagement. We found the participants expected the robot appearance to match its task only in the interview but not in the subjective ratings. Interaction between culture and task indicates that participants from low-context cultures may have significantly decreased engagement when the sociability of a task is lowered. We found strong and positive correlations between interaction performance (active response and engagement) and preference (likeability, trust and satisfaction) in the human-robot interaction.

Keywords

Human robot interaction Social robot Cultural differences Robot appearance Robot task 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    IFR Statistical Department (2009) Professional service robots are establishing themselves. In: World robotics 2009—service robots. IFR Statistical Department, Frankfurt Google Scholar
  2. 2.
    SuperDroid. Rp2w two way remote presence robot. Available from: http://www.robotshop.ca/superdroid-rp2w-remote-presence-robot.html
  3. 3.
    Sony. Aibo. Available from: http://support.sony-europe.com/aibo/index.asp
  4. 4.
  5. 5.
    Aldebaran-Robotics. Nao. Available from: http://www.aldebaran-robotics.com/en/
  6. 6.
    Powers A, Kiesler S (2006) The advisor robot: tracing people’s mental model from a robot’s physical attributes. In: HRI’06, 2006 Google Scholar
  7. 7.
    Kiesler S, Goetz J (2002) Mental models of robotic assistants. ACM, New York Google Scholar
  8. 8.
    Hofstede G (1980) Motivation, leadership, and organization: do american theories apply abroad? Organ Dyn 9(1):42–63 CrossRefGoogle Scholar
  9. 9.
    Hofstede G (1983) The cultural relativity of organizational practices and theories. J Int Bus Stud 14(2):75–89 CrossRefGoogle Scholar
  10. 10.
    Hofstede G, Hofstede G (2005) Cultures and organizations: software of the mind. McGraw-Hill, London Google Scholar
  11. 11.
    Hofstede G Cultural dimensions. Available from: http://www.geert-hofstede.com
  12. 12.
    Hall E (1977) Beyond culture. Anchor, Garden City Google Scholar
  13. 13.
    O’Neill-Brown P (1997) Setting the stage for the culturally adaptive agent. In: 1997 AAAI fall symposium. AAAI Press, Menlo Park Google Scholar
  14. 14.
    Reinecke K, Bernstein A (2007) Culturally adaptive software: moving beyond internationalization. Lect Not Comput Sci 4560:201 CrossRefGoogle Scholar
  15. 15.
    Bartneck C et al (2005) A cross-cultural study on attitudes towards robots. In: The 11th international conference on human-computer interaction (HCI ’05). Las Vegas, USA Google Scholar
  16. 16.
    Bartneck C et al (2007) The influence of people’s culture and prior experiences with Aibo on their attitude towards robots. Artif Intell Soc 21:217–230 Google Scholar
  17. 17.
    Bartneck C (2008) Who like androids more: japanese or U.S. americans? In: 17th IEEE international symposium on robot and human interactive communication (RO-MAN’08) Google Scholar
  18. 18.
    Rau P, Li Y, Li D (2009) Effects of communication style and culture on ability to accept recommendations from robots. Comput Hum Behav 25(2): 587–595 CrossRefGoogle Scholar
  19. 19.
    Wang L et al (2010) When in Rome: the role of culture and context in adherence to robot recommendations. In: Proceeding of the 5th ACM/IEEE international conference on human-robot interaction. ACM, Osaka Google Scholar
  20. 20.
    Evers V et al (2008) Relational vs. group self-construal: untangling the role of national culture in HRI. In: 3rd ACM/IEEE international conference: human-robot interaction. ACM, Amsterdam Google Scholar
  21. 21.
    Fong T, Nourbakhsh I, Dautenhahn K (2003) A survey of socially interactive robots. Robot Auton Syst 42(3–4):143–166 zbMATHCrossRefGoogle Scholar
  22. 22.
    Syrdal D et al (2007) Looking good? Appearance preferences and robot personality inferences at zero acquaintance. In: AAAI—spring symposium 2007, multidisciplinary collaboration for socially assistive robotics. AAAI Press, Menlo Park Google Scholar
  23. 23.
    Goetz J, Kiesler S, Powers A (2003) Matching robot appearance and behavior to tasks to improve human-robot cooperation. In: IEEE international workshop on robot and human interactive communication (RO-MAN ’03) Google Scholar
  24. 24.
    Robins B et al (2004) Robots as assistive technology—does appearance matter? In: IEEE international workshop on robot and human communication (RO-MAN ’04) Google Scholar
  25. 25.
    Kiesler S, Goetz J (2002) Mental models of robotic assistants. In: CHI ’02 extended abstracts on human factors in computing systems. ACM, Minneapolis Google Scholar
  26. 26.
    Woods S (2006) Exploring the design space of robots: children’s perspectives. Interac Comput 18(6):1390–1418 CrossRefGoogle Scholar
  27. 27.
    Mori M (1970) The uncanny valley. Energy 7(4):33–35 Google Scholar
  28. 28.
    Gee F, Browne W, Kawamura K (2005) Uncanny valley revisited. In: 14th IEEE international workshop on robot and human interactive communication (RO-MAN ’05). Nashville, USA Google Scholar
  29. 29.
    Walters M et al (2008) Avoiding the uncanny valley: robot appearance, personality and consistency of behavior in an attention-seeking home scenario for a robot companion. Auton Robots 24(2):159–178 CrossRefGoogle Scholar
  30. 30.
    Walters ML et al (2009) Preferences and perceptions of robot appearance and embodiment in human-robot interaction trials. In: Artificial intelligence and simulation of behaviour (AISB’09) convention. Edinburgh, Scotland Google Scholar
  31. 31.
    Lohse M, Hegel F, Wrede B (2008) Domestic applications for social robots-an online survey on the influence of appearance and capabilities. J Phys Agents 2(2):21 Google Scholar
  32. 32.
    IFR Statistical Department (2009) Executive summary of world robotics 2009, IFR Statistical Department Google Scholar
  33. 33.
    Kumar V, Bekey G, Zheng Y (2006) Industrial, personal and service robots. In: Bekey G (ed) Assessment of international research and development in robotics. World Technology Evaluation Center, Lancaster Google Scholar
  34. 34.
    Onishi N In a wired South Korea, robots will feel right at home. In: The New York Times, April 2 (2006) Google Scholar
  35. 35.
    Lohse M et al (2007) What can I do for you? Appearance and application of robots. In: Artificial intelligence and simulation of behaviour (AISB ’07) Google Scholar
  36. 36.
    Montgomery D (1991) Design and analysis of experiments Google Scholar
  37. 37.
    Lombard M et al (2000) Measuring presence: a literature-based approach to the development of a standardized paper-and-pencil instrument. In: Third international workshop on presence. Citeseer, Delft Google Scholar
  38. 38.
    Reyen S (2005) Construction of a new scale: the Reysen likeability scale. Soc Behav Pers 33(2):201–208 CrossRefGoogle Scholar
  39. 39.
    Nicholson CY, Compeau LD, Sethi R (2001) The role of interpersonal liking in building trust in long-term channel relationships. Acad Mark Sci 29(1):3–15 CrossRefGoogle Scholar
  40. 40.
    Adams B et al (2003) Trust in automated systems. Ministry of National Defence Google Scholar
  41. 41.
    Chin J, Diehl V, Norman K (1988) Development of an instrument measuring user satisfaction of the human-computer interface. ACM, New York, pp 213–218 Google Scholar
  42. 42.
    Hofstede G (1984) Culture’s consequences: international differences in work-related values. Sage, Thousand Oaks Google Scholar
  43. 43.
    Britton C et al (2002) An empirical study of user preference and performance with UML diagrams. In: Proceedings of IEEE 2002 symposia on human centric computing languages and environments (HCC02). Arlington, Virginia Google Scholar
  44. 44.
    Bartneck C et al (2005) Cultural differences in attitudes towards robots. In: Robot companions: hard problems and open challenges in robot-human interaction (AISB ’05). University of Hertfordshire, Hatfield Google Scholar

Copyright information

© Springer Science & Business Media BV 2010

Authors and Affiliations

  1. 1.Institute of Human Factors and Ergonomics, Department of Industrial EngineeringTsinghua UniversityBeijingP.R. China
  2. 2.State Intellectual Property Office of P.R. ChinaBeijingP.R. China

Personalised recommendations