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The Effects of Robot Managers’ Reward-Punishment Behaviours on Human–Robot Trust and Job Performance

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Abstract

In a human–robot team, robots may play a manager, helping to maintain the behavioural norms of its team. Robots as managers have the power to reward and punish. Currently, a small number of previous relevant studies have mainly focused on the impact of robot punishment behaviour on human beings, but managers without reward behaviour have difficulty gaining the trust of members. Therefore, this study investigates the effects of robot managers' reward and punishment behaviours on human–robot trust and job performance and explores the mediating effect of emotion and the moderating effect of group relations. The study recruited 76 participants using a 2 (independent variable robot managers' reward and punishment behaviours: reward behaviour, punishment behaviour) × 2 (moderator variable human–robot group relations: ingroup and outgroup) experimental design, and each participant and a robot manager worked together to complete the task of sorting items. It was found that the robot managers' reward-punishment behaviours have an impact on human emotions. Emotions play a mediating role in the effect of robot managers' reward-punishment behaviours on human trust but do not play a mediating role in the effect on job performance. The human–robot group relation plays a moderating role in the effects of emotions on human–robot trust. The research results help more preferably understand the interaction mechanism of the human–robot team and more preferably serve the management and cooperation of the human–robot team by appropriately adjusting the robot managers' reward and punishment behaviours in the human–robot team and the human–robot group relation.

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The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

References

  1. Fox J, Gambino A (2021) Relationship development with humanoid social robots: applying interpersonal theories to human–robot interaction. Cyberpsychol Behav Soc Netw 24(5):294–299

    Article  Google Scholar 

  2. Lopes SL, Rocha JB, Ferreira AI, Prada R (2021) Social robots as leaders: leadership styles in human-robot teams. In: 2021 30th IEEE international conference on robot & human interactive communication (RO-MAN). IEEE, pp 258–263

  3. Tsai CY, Marshall JD, Choudhury A, Serban A, Hou YT, Jung MF, Dionne SD, Yammarino FJ (2022) Human-robot collaboration: a multilevel and integrated leadership framework. Leadersh Q 33(1):101594

    Article  Google Scholar 

  4. Samani HA, Koh JTKV, Saadatian E, Polydorou D (2012) Towards robotics leadership: an analysis of leadership characteristics and the roles robots will inherit in future human society. Asian conference on intelligent information and database systems. Springer, Berlin, pp 158–165

    Chapter  Google Scholar 

  5. Riedl R, Mohr PN, Kenning PH, Davis FD, Heekeren HR (2014) Trusting humans and avatars: a brain imaging study based on evolution theory. J Manag Inf Syst 30(4):83–114

    Article  Google Scholar 

  6. Bartneck C, Bleeker T, Bun J, Fens P, Riet L (2010) The influence of robot anthropomorphism on the feelings of embarrassment when interacting with robots. Paladyn 1(2):109–115

    Google Scholar 

  7. Xu J, Broekens J, Hindriks K, Neerincx MA (2014). Effects of bodily mood expression of a robotic teacher on students. In: 2014 IEEE/RSJ international conference on intelligent robots and systems. IEEE, pp 2614–2620

  8. Agrawal S, Williams MA (2018) Would you obey an aggressive robot: a human-robot interaction field study. In 2018 27th IEEE international symposium on robot and human interactive communication (RO-MAN). IEEE, pp 240–246

  9. Braverman H (1998) Labor and monopoly capital: the degradation of work in the twentieth century. NYU Press, New York

    Google Scholar 

  10. Fousiani K (2020) Power asymmetry, negotiations and conflict management in organizations. Organizational conflict. IntechOpen, London

    Google Scholar 

  11. Ge JJ, Zhang P, Dong D (2022) Can extrinsic motivational state hinder good behavior? The mediating role of ambition and competition in relationships of contingent rewards and punishments with work performance. Curr Psychol 41(4):2162–2183

    Article  Google Scholar 

  12. Zhu N, Liu Y, Zhang J, Wang N (2023) Contingent reward versus punishment and compliance behavior: the mediating role of affective attitude and the moderating role of operational capabilities of artificial intelligence. Humanit Soc Sci Commun 10(1):1–11

    Article  Google Scholar 

  13. Canbek M (2020) Artificial intelligence leadership: imitating Mintzberg’s managerial roles. Business management and communication perspectives in Industry 4.0. IGI Global, pp 173–187

    Chapter  Google Scholar 

  14. Breslin S (2017) Meet the Terrifying New Robot Cop that’s Patrolling Dubai. Forbes. https://www.forbes. com/sites/susannahbreslin/2017/06/03/whistleblower-christopher-wylie-faceook-nix-bannon-trump

  15. Metz R (2014) Rise of the Robot Security Guards. Retrieved 26 Jan 2021 from https://www.technologyreview.com/2014/11/13/170454/rise-of-the-robot-security-guards

  16. Akker VDL, Heres L, Lasthuizen K, Six FE (2009) Ethical leadership and trust: It’s all about meeting expectations. Int J Leadersh Stud 5(2):102–122

    Google Scholar 

  17. Hancock PA, Billings DR, Oleson KE, Chen JY, De Visser E, Parasuraman R (2011) A meta-analysis of factors influencing the development of human–robot trust. Hum Factors 53(5):517–527

    Article  Google Scholar 

  18. De Jong BA, Dirks KT, Gillespie N (2016) Trust and team performance: a meta-analysis of main effects, moderators, and covariates. J Appl Psychol 101(8):1134–1150

    Article  Google Scholar 

  19. Malle BF, Ullman D (2021) A multi-dimensional conception and measure of human-robot trust. In: Nam CS, Lyons JB (eds) Trust in human–robot interaction: research and applications. Academic Press, Cambridge, pp 3–25

    Chapter  Google Scholar 

  20. Ullman D, Malle BF (2018) What does it mean to trust a robot? Steps toward a multidimensional measure of trust. In: Companion of the 2018 ACM/IEEE international conference on human-robot interaction, pp 263–264

  21. Lee JJ, Knox B, Baumann J, Breazeal C, DeSteno D (2013) Computationally modeling interpersonal trust. Front Psychol 4:893

    Article  Google Scholar 

  22. Aliasghari P, Ghafurian M, Nehaniv CL, Dautenhahn K (2021) Effect of domestic trainee robots’ errors on human teachers’ trust. In: 2021 30th IEEE international conference on robot & human interactive communication (RO-MAN). IEEE, pp 81–88

  23. Flook R, Shrinah A, Wijnen L, Eder K, Melhuish C, Lemaignan S (2019) On the impact of different types of errors on trust in human-robot interaction: are laboratory-based HRI experiments trustworthy? Interact Stud 20(3):455–486

    Article  Google Scholar 

  24. Wang FJ (2016) The effect of growth demand intensity on employee job performance: a status Competition perspective. Master's Thesis, Huazhong University of Science and Technology

  25. Judge TA, Thoresen CJ, Bono JE, Patton GK (2001) The job satisfaction–job performance relationship: a qualitative and quantitative review. Psychol Bull 127(3):376

    Article  Google Scholar 

  26. Podsakoff NP, Podsakoff PM, Kuskova VV (2010) Dispelling misconceptions and providing guidelines for leader reward and punishment behavior. Bus Horiz 53(3):291–303

    Article  Google Scholar 

  27. Walumbwa FO, Wu C, Orwa B (2008) Contingent reward transactional leadership, work attitudes, and organizational citizenship behavior: the role of procedural justice climate perceptions and strength. Leadersh Q 19:251–265

    Article  Google Scholar 

  28. Tremblay M, Vandenberghe C, Doucet O (2013) Relationships between leader-contingent and non-contingent reward and punishment behaviors and subordinates’ perceptions of justice and satisfaction, and evaluation of the moderating influence of trust propensity, pay level, and role ambiguity. J Bus Psychol 28:233–249

    Article  Google Scholar 

  29. Whitney D, Rosen E, MacGlashan J, Wong LL, Tellex S (2017) Reducing errors in object-fetching interactions through social feedback. In: 2017 IEEE international conference on robotics and automation (ICRA). IEEE, pp 1006–1013

  30. Austermann A, Yamada S (2008) “Good robot”, “bad robot”—Analyzing users’ feedback in a human-robot teaching task. In: RO-MAN 2008-The 17th IEEE international symposium on robot and human interactive communication. IEEE, pp 41–46

  31. Podsakoff PM, Bommer WH, Podsakoff NP, MacKenzie SB (2006) Relationships between leader reward and punishment behavior and subordinate attitudes, perceptions, and behaviors: a meta-analytic review of existing and new research. Organ Behav Hum Decis Process 99(2):113–142

    Article  Google Scholar 

  32. Judge TA, Bono JE (2000) Five-factor model of humanality and transformational leadership. J Appl Psychol 85:751–765

    Article  Google Scholar 

  33. Tjosvold D (1995) Effects of power to reward and punish in cooperative and competitive contexts. J Soc Psychol 135(6):723–736

    Article  Google Scholar 

  34. Mizumaru K, Satake S, Kanda T, Ono T (2019) Stop doing it! Approaching strategy for a robot to admonish pedestrians. In: 2019 14th ACM/IEEE international conference on human–robot interaction (HRI). IEEE, pp 449–457

  35. Lee SL, Lau IYM (2011) Hitting a robot vs. hitting a human: is it the same?. In Proceedings of the 6th international conference on Human-robot interaction, pp 187–188

  36. Jois H, Wagner AR (2019) Should robots be allowed to punish us?. In: 2019 conference of the international association for computing and philosophy (IACAP 2019)

  37. Jois H, Wagner AR (2021) What happens when robots punish? Evaluating human task performance during robot-initiated punishment. ACM Trans Hum Robot Interact (THRI) 10(4):1–18

    Article  Google Scholar 

  38. Jois H (2021) Evaluating human response to robot-administered punishment

  39. Saunderson SP, Nejat G (2021) Persuasive robots should avoid authority: the effects of formal and real authority on persuasion in human-robot interaction. Sci Robot 6(58):eabd5186

    Article  Google Scholar 

  40. You S, Nie J, Suh K, Sundar SS (2011) When the robot criticizes you... Self-serving bias in human-robot interaction. In Proceedings of the 6th international conference on human-robot interaction, pp 295–296

  41. Keltner D, Lerner JS (2010) Emotion. John Wiley & Sons Inc., Hoboken

    Google Scholar 

  42. Stock RM, Hoyer WD (2005) An attitude-behavior model of saleshuman’s customer orientation. J Acad Mark Sci 33(4):536–552

    Article  Google Scholar 

  43. Burke MJ, Brief AP, George JM (1993) The role of negative affectivity in understanding relations between self-reports of stressors and strains: a comment on the applied psychology literature. J Appl Psychol 78(3):402

    Article  Google Scholar 

  44. Stock-Homburg R (2022) Survey of emotions in human–robot interactions: perspectives from robotic psychology on 20 years of research. Int J Soc Robot 14(2):389–411

    Article  Google Scholar 

  45. Robert D, John R (1982) Store atmosphere: an environmental psychology approach. J Retail 58(1):34–57

    Google Scholar 

  46. Weiss HM, Suckow K, Cropanzano R (1999) Effects of justice conditions on discrete emotions. J Appl Psychol 84(5):786

    Article  Google Scholar 

  47. Stock-Homburg R (2021) Survey of emotions in human–robot interactions: perspectives from robotic psychology on 20 years of research. Int J Soc Robot 1–23

  48. You S, Robert L (2018) Teaming up with robots: an IMOI (inputs-mediators-outputs-inputs) framework of human-robot teamwork. You S, Robert LP (2017) Teaming up with robots: an IMOI (inputs-mediators-outputs-inputs) framework of human–robot teamwork. International Journal of Robotic Engineering (IJRE) 2(3)

  49. Kozlowski SW, Bell BS (2003) Work groups and teams in organizations

  50. Carpenter J (2013) Just doesn’t look right: exploring the impact of humanoid robot integration into explosive ordnance disposal teams. In: Handbook of research on technoself: identity in a technological society. IGI Global, pp 609–636

  51. Robert Jr LP, You S (2015) Subgroup formation in teams working with robots. In: Proceedings of the 33rd annual ACM conference extended abstracts on human factors in computing systems, pp 2097–2102

  52. Lewis M, Phd JMH-J, Barrett LF (2009) Handbook of affective sciences. Oxford University Press, Oxford

    Google Scholar 

  53. Stokes CK, Lyons JB, Littlejohn K, Natarian J, Case E, Speranza N (2010) Accounting for the human in cyberspace: Effects of mood on trust in automation. In: 2010 international symposium on collaborative technologies and systems. IEEE, pp 180–187

  54. Myers CD, Tingley D (2016) The influence of emotion on trust. Polit Anal 24(4):492–500

    Article  Google Scholar 

  55. Wang L, Rau PLP, Evers V, Robinson B, Hinds P (2009) Responsiveness to robots: effects of ingroup orientation & communication style on HRI in China. In: Proceedings of the 4th ACM/IEEE international conference on human robot interaction, pp 247–248

  56. Brewer MB, Chen YR (2007) Where (who) are collectives in collectivism? Toward conceptual clarification of individualism and collectivism. Psychol Rev 114(1):133

    Article  Google Scholar 

  57. Fraune MR, Šabanović S, Smith ER (2017) Teammates first: favoring ingroup robots over outgroup humans. In: 2017 26th IEEE international symposium on robot and human interactive communication (RO-MAN). IEEE, pp 1432–1437

  58. Nauts S, Langner O, Huijsmans I, Vonk R, Wigboldus DH (2014) Forming impressions of humanality. Soc Psych. https://doi.org/10.1027/1864-9335/a000179

    Article  Google Scholar 

  59. Eyssel F, Kuchenbrandt D (2012) Social categorization of social robots: anthropomorphism as a function of robot group membership. Br J Soc Psychol 51(4):724–731

    Article  Google Scholar 

  60. Sembroski CE, Fraune MR, Šabanović S (2017) He said, she said, it said: Effects of robot group membership and human authority on human’s willingness to follow their instructions. In: 2017 26th IEEE international symposium on robot and human interactive communication (RO-MAN). IEEE, pp 56–61

  61. Wang L, Rau PLP, Evers V, Robinson B, Hinds P (2009) Responsiveness to robots: Effects of ingroup orientation & communication style on HRI in China. In: 2009 4th ACM/IEEE international conference on human–robot interaction (HRI). IEEE, pp 247–248

  62. Fraune MR, Šabanović S, Smith ER (2020) Some are more equal than others: ingroup robots gain some but not all benefits of team membership. Interact Stud 21(3):303–328

    Article  Google Scholar 

  63. Savela N, Kaakinen M, Ellonen N, Oksanen A (2021) Sharing a work team with robots: the negative effect of robot co-workers on in-group identification with the work team. Comput Hum Behav 115:106585

    Article  Google Scholar 

  64. Thompson ER (2007) Development and validation of an internationally reliable short-form of the positive and negative affect schedule (PANAS). J Cross Cult Psychol 38(2):227–242

    Article  Google Scholar 

  65. Bialystok E, Martin MM (2004) Attention and inhibition in bilingual children: evidence from the dimensional change card sort task. Dev Sci 7(3):325–339

    Article  Google Scholar 

  66. Wegge J, Roth C, Neubach B, Schmidt KH, Kanfer R (2008) Age and gender diversity as determinants of performance and health in a public organization: the role of task complexity and group size. J Appl Psychol 93(6):1301

    Article  Google Scholar 

  67. Garbers Y, Konradt U (2014) The effect of financial incentives on performance: a quantitative review of individual and team based financial incentives. J Occup Organ Psychol 87(1):102–137

    Article  Google Scholar 

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Acknowledgements

The authors would like to acknowledge the support of Ministry of Education of Humanities and Social Science project, National Natural Science Foundation of China, Beijing Social Science Fund and Major Research plan of the National Natural Science Foundation of China. Additionally, we wish to thank the other members in the college of Economics and Management for their useful advice and good ideas.

Funding

This study was funded by the National Natural Science Foundation of China 72201023.

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Correspondence to Na Chen.

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Chen, N., Cao, J. & Hu, X. The Effects of Robot Managers’ Reward-Punishment Behaviours on Human–Robot Trust and Job Performance. Int J of Soc Robotics 16, 529–545 (2024). https://doi.org/10.1007/s12369-023-01091-0

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