The Dark Side of Employee Collaboration with Robots: Exploring Its Impact on Self-Esteem Threat and Burnout

References

• Abraham, C., Sheeran, P., & Johnston, M. (1998). From health beliefs to self-regulation: Theoretical advances in the psychology of action control. Psychology & Health, 13(4), 569–591. https://doi.org/10.1080/08870449808407420
   Web of Science ®Google Scholar
• Ågnes, J. S. (2022). Gaining and training a digital colleague: Employee responses to robotization. The Journal of Applied Behavioral Science, 58(1), 29–64. https://doi.org/10.1177/00218863211043596
   Web of Science ®Google Scholar
• Ajoudani, A., Zanchettin, A. M., Ivaldi, S., Albu-Schäffer, A., Kosuge, K., & Khatib, O. (2018). Progress and prospects of the human-robot collaboration. Autonomous Robots, 42(5), 957–975. https://doi.org/10.1007/s10514-017-9677-2
   Web of Science ®Google Scholar
• Alarcon, G. M. (2011). A meta-analysis of burnout with job demands, resources, and attitudes. Journal of Vocational Behavior, 79(2), 549–562. https://doi.org/10.1016/j.jvb.2011.03.007
   Web of Science ®Google Scholar
• Anderson, C., & Kilduff, G. J. (2009). Why do dominant personalities attain influence in face-to-face groups? The competence-signaling effects of trait dominance. Journal of Personality and Social Psychology, 96(2), 491–503. https://doi.org/10.1037/a0014201
   PubMed Web of Science ®Google Scholar
• Atinc, G., Simmering, M. J., & Kroll, M. J. (2012). Control variable use and reporting in macro and micro management research. Organizational Research Methods, 15(1), 57–74. https://doi.org/10.1177/1094428110397773
   Web of Science ®Google Scholar
• Baltrusch, S. J., Krause, F., de Vries, A. W., van Dijk, W., & de Looze, M. P. (2021). What about the human in human robot collaboration? A literature review on HRC’s effects on aspects of job quality. Ergonomics, 65(5), 719–740. https://doi.org/10.1080/00140139.2021.1984585
   PubMed Web of Science ®Google Scholar
• Bandura, A. (1991). Social cognitive theory of self-regulation. Organizational Behavior and Human Decision Processes, 50(2), 248–287. https://doi.org/10.1016/0749-5978(91)90022-L
   Web of Science ®Google Scholar
• Bankins, S., & Formosa, P. (2020). When AI meets PC: Exploring the implications of workplace social robots and a human-robot psychological contract. European Journal of Work and Organizational Psychology, 29(2), 215–229. https://doi.org/10.1080/1359432X.2019.1620328
   Web of Science ®Google Scholar
• Baraglia, J., Cakmak, M., Nagai, Y., Rao, R. P. N., & Asada, M. (2017). Efficient human-robot collaboration: When should a robot take initiative? The International Journal of Robotics Research, 36(5–7), 563–579. https://doi.org/10.1177/0278364916688253
   Web of Science ®Google Scholar
• Bartneck, C., Kulić, D., Croft, E., & Zoghbi, S. (2009). Measurement instruments for the anthropomorphism, animacy, likeability, perceived intelligence, and perceived safety of robots. International Journal of Social Robotics, 1(1), 71–81. https://doi.org/10.1007/s12369-008-0001-3
   Web of Science ®Google Scholar
• Baumeister, R. F., Schmeichel, B. J., & Vohs, K. D. (2007). Self-regulation and the executive function: The self as controlling agent. In A. W. Kruglanski & E. T. Higgins (Eds.), Social psychology: Handbook of basic principles (2nd ed., pp. 516–539). Guilford Press.
   Google Scholar
• Becker, W. J., Belkin, L. Y., Tuskey, S. E., & Conroy, S. A. (2022). Surviving remotely: How job control and loneliness during a forced shift to remote work impacted employee work behaviors and well-being. Human Resource Management, 61(4), 449–464. https://doi.org/10.1002/hrm.22102
   Web of Science ®Google Scholar
• Bejar, A. H. C., Ray, S., & Huang, Y. H. (2023). Fighting for the status quo: Threat to tech self-esteem and opposition to competing smartphones. Information & Management, 60(2), 103748. https://doi.org/10.1016/j.im.2022.103748
   Web of Science ®Google Scholar
• Belanche, D., Casaló, L. V., Schepers, J., & Flavián, C. (2021). Examining the effects of robots’ physical appearance, warmth, and competence in frontline services: The Humanness‐Value‐Loyalty model. Psychology & Marketing, 38(12), 2357–2376. https://doi.org/10.1002/mar.21532
   Web of Science ®Google Scholar
• Benotsmane, R., Kovács, G., & Dudás, L. (2019). Economic, social impacts and operation of smart factories in Industry 4.0 focusing on simulation and artificial intelligence of collaborating robots. Social Sciences, 8(5), 143. https://doi.org/10.3390/socsci8050143
   Google Scholar
• Berkers, H. A., Rispens, S., & Le Blanc, P. M. (2022). The role of robotization in work design: A comparative case study among logistic warehouses. The International Journal of Human Resource Management, 34(9), 1852–1875. https://doi.org/10.1080/09585192.2022.2043925
   Web of Science ®Google Scholar
• Berx, N., Decré, W., Morag, I., Chemweno, P., & Pintelon, L. (2022). Identification and classification of risk factors for human-robot collaboration from a system-wide perspective. Computers & Industrial Engineering, 163, 107827. https://doi.org/10.1016/j.cie.2021.107827
   Web of Science ®Google Scholar
• Blanch, A., & Aluja, A. (2012). Social support (family and supervisor), work-family conflict, and burnout: Sex differences. Human Relations, 65(7), 811–833. https://doi.org/10.1177/0018726712440471
   Web of Science ®Google Scholar
• Blanton, H., Crocker, J., & Miller, D. T. (2000). The effects of in-group versus out-group social comparison on self-esteem in the context of a negative stereotype. Journal of Experimental Social Psychology, 36(5), 519–530. https://doi.org/10.1006/jesp.2000.1425
   Web of Science ®Google Scholar
• Bloss, R. (2016). Collaborative robots are rapidly providing major improvements in productivity, safety, programing ease, portability and cost while addressing many new applications. Industrial Robot, 43(5), 463–468. https://doi.org/10.1108/IR-05-2016-0148
   Web of Science ®Google Scholar
• Boekaerts, M., Zeidner, M., & Pintrich, P. R. (1999). Handbook of self-regulation. Elsevier.
   Google Scholar
• Bogue, R. (2011). Robots in healthcare. Industrial Robot, 38(3), 218–223. https://doi.org/10.1108/01439911111122699
   Google Scholar
• Brewer, E. W., & Shapard, L. (2004). Employee burnout: A meta-analysis of the relationship between age or years of experience. Human Resource Development Review, 3(2), 102–123. https://doi.org/10.1177/1534484304263335
   Google Scholar
• Brislin, R. W. (1986). The wording and translation of research instruments. In J. W. B. W. J. Lonner (Ed.), Field methods in cross-cultural research (pp. 137–164). Sage.
   Google Scholar
• Brougham, D., & Haar, J. (2018). Smart technology, artificial intelligence, robotics, and algorithms (STARA): Employees’ perceptions of our future workplace. Journal of Management & Organization, 24(2), 239–257. https://doi.org/10.1017/jmo.2016.55
   Web of Science ®Google Scholar
• Bruins, J., Ellemers, N., & De Gilder, D. (1999). Power use and differential competence as determinants of subordinates’ evaluative and behavioural responses in simulated organizations. European Journal of Social Psychology, 29(7), 843–870. https://doi.org/10.1002/(SICI)1099-0992(199911)29:7<843::AID-EJSP959>3.0.CO;2-5
   Web of Science ®Google Scholar
• Callea, A., Lo Presti, A., Mauno, S., & Urbini, F. (2019). The associations of quantitative/qualitative job insecurity and well-being: The role of self-esteem. International Journal of Stress Management, 26(1), 46–56. https://doi.org/10.1037/str0000091
   Web of Science ®Google Scholar
• Carver, C. S., & Scheier, M. F. (2001). On the self-regulation of behavior. Cambridge University Press.
   Google Scholar
• Cascio, W. F., & Montealegre, R. (2016). How technology is changing work and organizations. Annual Review of Organizational Psychology and Organizational Behavior, 3(1), 349–375. https://doi.org/10.1146/annurev-orgpsych-041015-062352
   Google Scholar
• Cha, Y. Y.-J., Baek, S., Ahn, G., Lee, H., Lee, B., Shin, J., & Jang, D. (2020). Compensating for the loss of human distinctiveness: The use of social creativity under human-machine comparisons. Computers in Human Behavior, 103, 80–90. https://doi.org/10.1016/j.chb.2019.08.027
   Web of Science ®Google Scholar
• Chandra, V., Nehra, D., Parent, R., Woo, R., Reyes, R., Hernandez-Boussard, T., & Dutta, S. (2010). A comparison of laparoscopic and robotic assisted suturing performance by experts and novices. Surgery, 147(6), 830–839. https://doi.org/10.1016/j.surg.2009.11.002
   PubMed Web of Science ®Google Scholar
• Chatzimichali, A., Harrison, R., & Chrysostomou, D. (2020). Toward privacy-sensitive human-robot interaction: Privacy terms and human-data interaction in the personal robot era. Paladyn, Journal of Behavioral Robotics, 12(1), 160–174. https://doi.org/10.1515/pjbr-2021-0013
   Google Scholar
• Chau, P. Y. (1996). An empirical assessment of a modified technology acceptance model. Journal of Management Information Systems, 13(2), 185–204. https://doi.org/10.1080/07421222.1996.11518128
   Google Scholar
• Cho, Y., & Fast, N. J. (2012). Power, defensive denigration, and the assuaging effect of gratitude expression. Journal of Experimental Social Psychology, 48(3), 778–782. https://doi.org/10.1016/j.jesp.2011.12.016
   Web of Science ®Google Scholar
• Choi, Y., Choi, M., Oh, M., & Kim, S. (. (2020). Service robots in hotels: Understanding the service quality perceptions of human-robot interaction. Journal of Hospitality Marketing & Management, 29(6), 613–635. https://doi.org/10.1080/19368623.2020.1703871
   Web of Science ®Google Scholar
• Chun, W. H., & Papanikolopoulos, N. (2016). Robot surveillance and security. In B. Siciliano & O. Khatib (Eds.), Springer handbook of robotics (pp. 1605–1626). Springer International Publishing.
   Google Scholar
• Coghlan, S. (2022). Robots and the possibility of humanistic care. International Journal of Social Robotics, 14(10), 2095–2108. https://doi.org/10.1007/s12369-021-00804-7
   PubMed Web of Science ®Google Scholar
• Collins, R. L. (1996). For better or worse: The impact of upward social comparison on self-evaluations. Psychological Bulletin, 119(1), 51–69. https://doi.org/10.1037/0033-2909.119.1.51
   Web of Science ®Google Scholar
• Crocker, J., & Park, L. E. (2004). The costly pursuit of self-esteem. Psychological Bulletin, 130(3), 392–414. https://doi.org/10.1037/0033-2909.130.3.392
   PubMed Web of Science ®Google Scholar
• Dang, J., & Liu, L. (2021). Robots are friends as well as foes: Ambivalent attitudes toward mindful and mindless AI robots in the United States and China. Computers in Human Behavior, 115(July 2020), 106612. https://doi.org/10.1016/j.chb.2020.106612
   Google Scholar
• de Assis Dornelles, J., Ayala, N. F., & Frank, A. G. (2022). Smart Working in Industry 4.0: How digital technologies enhance manufacturing workers’ activities. Computers & Industrial Engineering, 163, 107804. https://doi.org/10.1016/j.cie.2021.107804
   Web of Science ®Google Scholar
• De Cremer, D., Van Knippenberg, B., Van Knippenberg, D., Mullenders, D., & Stinglhamber, F. (2005). Rewarding leadership and fair procedures as determinants of self-esteem. The Journal of Applied Psychology, 90(1), 3–12. https://doi.org/10.1037/0021-9010.90.1.3
   PubMed Web of Science ®Google Scholar
• Dixon, J., Hong, B., & Wu, L. (2021). The robot revolution: Managerial and employment consequences for firms. Management Science, 67(9), 5586–5605. https://doi.org/10.2139/ssrn.3422581
   Web of Science ®Google Scholar
• Edwards, J. R., & Lambert, L. S. (2007). Methods for integrating moderation and mediation: A general analytical framework using moderated path analysis. Psychological Methods, 12(1), 1–22. https://doi.org/10.1037/1082-989X.12.1.1
   PubMed Web of Science ®Google Scholar
• Etemad-Sajadi, R., Soussan, A., & Schöpfer, T. (2022). How ethical issues raised by human-robot interaction can impact the intention to use the robot? International Journal of Social Robotics, 14(4), 1103–1115. https://doi.org/10.1007/s12369-021-00857-8
   PubMed Web of Science ®Google Scholar
• Faul, F., Erdfelder, E., Buchner, A., & Lang, A.-G. (2009). Statistical power analyses using G* Power 3.1: Tests for correlation and regression analyses. Behavior Research Methods, 41(4), 1149–1160. https://doi.org/10.3758/BRM.41.4.1149
   PubMed Web of Science ®Google Scholar
• Felten, E., Raj, M., & Seamans, R. (2021). Occupational, industry, and geographic exposure to artificial intelligence: A novel dataset and its potential uses. Strategic Management Journal, 42(12), 2195–2217. https://doi.org/10.1002/smj.3286
   Web of Science ®Google Scholar
• Ferrari, F., Paladino, M. P., & Jetten, J. (2016). Blurring human-machine distinctions: Anthropomorphic appearance in social Robots as a threat to human distinctiveness. International Journal of Social Robotics, 8(2), 287–302. https://doi.org/10.1007/s12369-016-0338-y
   Web of Science ®Google Scholar
• Galin, R. R., & Meshcheryakov, R. V. (2020). Human-robot interaction efficiency and human-robot collaboration. In A. G. Kravets (Ed.), Robotics: Industry 4.0 issues & new intelligent control paradigms (pp. 55–63). Springer International Publishing.
   Google Scholar
• Gasparetto, A., & Scalera, L. (2019). A brief history of industrial robotics in the 20th century. Advances in Historical Studies, 08(01), 24–35. https://doi.org/10.4236/ahs.2019.81002
   Google Scholar
• Gervasi, R., Mastrogiacomo, L., & Franceschini, F. (2020). A conceptual framework to evaluate human-robot collaboration. The International Journal of Advanced Manufacturing Technology, 108(3), 841–865. https://doi.org/10.1007/s00170-020-05363-1
   Web of Science ®Google Scholar
• Glikson, E., & Woolley, A. W. (2020). Human trust in artificial intelligence: Review of empirical research. Academy of Management Annals, 14(2), 627–660. https://doi.org/10.5465/annals.2018.0057
   Web of Science ®Google Scholar
• Goel, P., Kaushik, N., Sivathanu, B., Pillai, R., & Vikas, J. (2022). Consumers’ adoption of artificial intelligence and robotics in hospitality and tourism sector: Literature review and future research agenda. Tourism Review, 77(4), 1081–1096. https://doi.org/10.1108/TR-03-2021-0138
   Web of Science ®Google Scholar
• Gombolay, M., Bair, A., Huang, C., & Shah, J. (2017). Computational design of mixed-initiative human-robot teaming that considers human factors: Situational awareness, workload, and workflow preferences. The International Journal of Robotics Research, 36(5–7), 597–617. https://doi.org/10.1177/0278364916688255
   Web of Science ®Google Scholar
• Gombolay, M. C., Gutierrez, R. A., Clarke, S. G., Sturla, G. F., & Shah, J. A. (2015). Decision-making authority, team efficiency and human worker satisfaction in mixed human-robot teams. Autonomous Robots, 39(3), 293–312. https://doi.org/10.1007/s10514-015-9457-9
   Web of Science ®Google Scholar
• Hägele, M., Nilsson, K., Pires, J. N., & Bischoff, R. (2016). Industrial robotics. In B. Siciliano & O. Khatib (Eds.), Springer handbook of robotics (pp. 1385–1422). Springer International Publishing.
   Google Scholar
• Helmreich, R., Aronson, E., & LeFan, J. (1970). To err is humanizing sometimes: Effects of self-esteem, competence, and a pratfall on interpersonal attraction. Journal of Personality and Social Psychology, 16(2), 259–264. https://doi.org/10.1037/h0029848
   PubMed Web of Science ®Google Scholar
• Hentout, A., Aouache, M., Maoudj, A., & Akli, I. (2019). Human-robot interaction in industrial collaborative robotics: A literature review of the decade 2008–2017. Advanced Robotics, 33(15–16), 764–799. https://doi.org/10.1080/01691864.2019.1636714
   Web of Science ®Google Scholar
• Hesketh, I., & Cooper, C. (2023). Wellbeing at work: How to design, implement and evaluate an effective strategy. Kogan Page Publishers.
   Google Scholar
• Hinds, P. J., Carley, K. M., Krackhardt, D., & Wholey, D. (2000). Choosing work group members: Balancing similarity, competence, and familiarity. Organizational Behavior and Human Decision Processes, 81(2), 226–251. https://doi.org/10.1006/obhd.1999.2875
   PubMed Web of Science ®Google Scholar
• Ho, B. Q., Otsuki, M., Kishita, Y., Kobayakawa, M., & Watanabe, K. (2022). Human augmentation technologies for employee well-being: A research and development agenda. International Journal of Environmental Research and Public Health, 19(3), 1195. https://doi.org/10.3390/ijerph19031195
   PubMed Web of Science ®Google Scholar
• Hoegl, M., Weinkauf, K., & Gemuenden, H. G. (2004). Interteam coordination, project commitment, and teamwork in multiteam R&D projects: A longitudinal study. Organization Science, 15(1), 38–55. https://doi.org/10.1287/orsc.1030.0053
   Web of Science ®Google Scholar
• Hofer, J., Busch, H., & Kärtner, J. (2011). Self-regulation and well-being: The influence of identity and motives. European Journal of Personality, 25(3), 211–224. https://doi.org/10.1002/per.789
   Web of Science ®Google Scholar
• Holden, R. J., & Karsh, B.-T. (2010). The technology acceptance model: Its past and its future in health care. Journal of Biomedical Informatics, 43(1), 159–172. https://doi.org/10.1016/j.jbi.2009.07.002
   PubMed Web of Science ®Google Scholar
• Hompel, M., & Schmidt, T. (2006). Warehouse management: Automation and organisation of warehouse and order picking systems. Springer Science & Business Media.
   Google Scholar
• Hopko, S. K., Khurana, R., Mehta, R. K., & Pagilla, P. R. (2021). Effect of cognitive fatigue, operator sex, and robot assistance on task performance metrics, workload, and situation awareness in human-robot collaboration. IEEE Robotics and Automation Letters, 6(2), 3049–3056. https://doi.org/10.1109/LRA.2021.3062787
   Web of Science ®Google Scholar
• Howe, R. D., & Matsuoka, Y. (1999). Robotics for surgery. Annual Review of Biomedical Engineering, 1(1), 211–240. https://doi.org/10.1146/annurev.bioeng.1.1.211
   PubMedGoogle Scholar
• Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55. https://doi.org/10.1080/10705519909540118
   Web of Science ®Google Scholar
• Huang, H. L., Cheng, L. K., Sun, P. C., & Chou, S. J. (2021). The effects of perceived identity threat and realistic threat on the negative attitudes and usage intentions toward hotel service robots: The moderating effect of the robot’s anthropomorphism. International Journal of Social Robotics, 13(7), 1599–1611. https://doi.org/10.1007/s12369-021-00752-2
   Web of Science ®Google Scholar
• Javaid, M., Haleem, A., Singh, R. P., & Suman, R. (2021). Substantial capabilities of robotics in enhancing industry 4.0 implementation. Cognitive Robotics, 1, 58–75. https://doi.org/10.1016/j.cogr.2021.06.001
   Google Scholar
• Kahn, P. H., Jr, Ishiguro, H., Friedman, B., Kanda, T., Freier, N. G., Severson, R. L., & Miller, J. (2007). What is a human?: Toward psychological benchmarks in the field of human-robot interaction. Interaction Studies. Social Behaviour and Communication in Biological and Artificial Systems, 8(3), 363–390. https://doi.org/10.1075/is.8.3.04kah
   Web of Science ®Google Scholar
• Kangari, R., & Halpin, D. W. (1989). Potential robotics utilization in construction. Journal of Construction Engineering and Management, 115(1), 126–143. https://doi.org/10.1061/(ASCE)0733-9364(1989)115:1(126)
   Web of Science ®Google Scholar
• Khaliq, A., Waqas, A., Nisar, Q. A., Haider, S., & Asghar, Z. (2022). Application of AI and robotics in hospitality sector: A resource gain and resource loss perspective. Technology in Society, 68, 101807. https://doi.org/10.1016/j.techsoc.2021.101807
   Web of Science ®Google Scholar
• Kim, S. (2022). Working with robots: Human resource development considerations in human-robot interaction. Human Resource Development Review, 21(1), 48–74. https://doi.org/10.1177/15344843211068810
   Web of Science ®Google Scholar
• Kowalski, T. H. P., & Loretto, W. (2017). Well-being and HRM in the changing workplace. The International Journal of Human Resource Management, 28(16), 2229–2255. https://doi.org/10.1080/09585192.2017.1345205
   Web of Science ®Google Scholar
• Krakowski, S., Luger, J., & Raisch, S. (2022). Artificial intelligence and the changing sources of competitive advantage. Strategic Management Journal, 44(6), 1425–1452. https://doi.org/10.1002/smj.3387
   Web of Science ®Google Scholar
• Larson, L., & DeChurch, L. A. (2020). Leading teams in the digital age: Four perspectives on technology and what they mean for leading teams. The Leadership Quarterly, 31(1), 101377. https://doi.org/10.1016/j.leaqua.2019.101377
   PubMed Web of Science ®Google Scholar
• Law, T., Chita-Tegmark, M., & Scheutz, M. (2021). The interplay between emotional intelligence, trust, and gender in human-robot interaction: A vignette-based study. International Journal of Social Robotics, 13(2), 297–309. https://doi.org/10.1007/s12369-020-00624-1
   Web of Science ®Google Scholar
• Lee-Flynn, S. C., Pomaki, G., DeLongis, A., Biesanz, J. C., & Puterman, E. (2011). Daily cognitive appraisals, daily affect, and long-term depressive symptoms: The role of self-esteem and self-concept clarity in the stress process. Personality & Social Psychology Bulletin, 37(2), 255–268. https://doi.org/10.1177/0146167210394204
   PubMed Web of Science ®Google Scholar
• Leitner, J. B., Hehman, E., Deegan, M. P., & Jones, J. M. (2014). Adaptive disengagement buffers self-esteem from negative social feedback. Personality & Social Psychology Bulletin, 40(11), 1435–1450. https://doi.org/10.1177/0146167214549319
   PubMed Web of Science ®Google Scholar
• Li, J. (Justin), Bonn M. A., & Ye, B. H.. (2019). Hotel employee’s artificial intelligence and robotics awareness and its impact on turnover intention: The moderating roles of perceived organizational support and competitive psychological climate. Tourism Management, 73, 172–181. https://doi.org/10.1016/j.tourman.2019.02.006
   Web of Science ®Google Scholar
• Lian, H., Yam, K. C., Ferris, D. L., & Brown, D. (2017). Self-control at work. Academy of Management Annals, 11(2), 703–732. https://doi.org/10.5465/annals.2015.0126
   Web of Science ®Google Scholar
• Liang, X., Guo, G., Shu, L., Gong, Q., & Luo, P. (2022). Investigating the double-edged sword effect of AI awareness on employee’s service innovative behavior. Tourism Management, 92, 104564. https://doi.org/10.1016/j.tourman.2022.104564
   Web of Science ®Google Scholar
• Lin, W., Shao, Y., Li, G., Guo, Y., & Zhan, X. (2021). The psychological implications of COVID-19 on employee job insecurity and its consequences: The mitigating role of organization adaptive practices. The Journal of Applied Psychology, 106(3), 317–329. https://doi.org/10.1037/apl0000896
   PubMed Web of Science ®Google Scholar
• Lu, L., Xie, Z., Wang, H., Li, L., & Xu, X. (2022). Mental stress and safety awareness during human-robot collaboration-Review. Applied Ergonomics, 105, 103832. https://doi.org/10.1016/j.apergo.2022.103832
   PubMed Web of Science ®Google Scholar
• Lu, V. N., Wirtz, J., Kunz, W. H., Paluch, S., Gruber, T., Martins, A., & Patterson, P. G. (2020). Service robots, customers and service employees: What can we learn from the academic literature and where are the gaps? Journal of Service Theory and Practice, 30(3), 361–391. https://doi.org/10.1108/JSTP-04-2019-0088
   Web of Science ®Google Scholar
• MacDonald, G., & Leary, M. R. (2012). Individual differences in self-esteem. In M. R. Leary & J. P. Tangney (Eds.), Handbook of self and identity (pp. 354–377). Guilford Press.
   Google Scholar
• Manyika, J., Chui, M., Miremadi, M., Bughin, J., George, K., Willmott, P., & Dewhurst, M. (2017). A future that works: AI, automation, employment, and productivity. McKinsey Global Institute Research.
   Google Scholar
• Maslach, C. (1982). Understanding burnout: Definitional issues in analyzing a complex phenomenon. In W. S. Paine (Ed.), Job stress and burnout: Research, theory and intervention perspectives (pp. 29–40). Sage Focus Editions.
   Google Scholar
• Maslach, C., Schaufeli, W. B., & Leiter, M. P. (2001). Job burnout. Annual Review of Psychology, 52(1), 397–422. https://doi.org/10.1146/annurev.psych.52.1.397
   PubMed Web of Science ®Google Scholar
• Masselink, M., Van Roekel, E., & Oldehinkel, A. J. (2018). Self-esteem in early adolescence as predictor of depressive symptoms in late adolescence and early adulthood: The mediating role of motivational and social factors. Journal of Youth and Adolescence, 47(5), 932–946. https://doi.org/10.1007/s10964-017-0727-z
   PubMed Web of Science ®Google Scholar
• McConnell, A. R. (2011). The multiple self-aspects framework: Self-concept representation and its implications. Personality and Social Psychology Review, 15(1), 3–27. https://doi.org/10.1177/1088868310371101
   PubMed Web of Science ®Google Scholar
• Meissner, A., Trübswetter, A., Conti-Kufner, A. S., & Schmidtler, J. (2020). Friend or foe understanding assembly workers’ acceptance of human-robot collaboration. ACM Transactions on Human-Robot Interaction, 10(1), 1–30. https://doi.org/10.1145/3399433
   Web of Science ®Google Scholar
• Mirbabaie, M., Brünker, F., Möllmann, N. R., & Stieglitz, S. (2022). The rise of artificial intelligence-understanding the AI identity threat at the workplace. Electronic Markets, 32(1), 73–99. https://doi.org/10.1007/s12525-021-00496-x
   Web of Science ®Google Scholar
• Muraven, M., & Baumeister, R. F. (2000). Self-regulation and depletion of limited resources: Does self-control resemble a muscle? Psychological Bulletin, 126(2), 247–259. https://doi.org/10.1037/0033-2909.126.2.247
   PubMed Web of Science ®Google Scholar
• Muraven, M., Tice, D. M., & Baumeister, R. F. (1998). Self-control as a limited resource: Regulatory depletion patterns. Journal of Personality and Social Psychology, 74(3), 774–789. https://doi.org/10.1037/0022-3514.74.3.774
   PubMed Web of Science ®Google Scholar
• Nash, K., Lea, J. M., Davies, T., & Yogeeswaran, K. (2018). The bionic blues: Robot rejection lowers self-esteem. Computers in Human Behavior, 78, 59–63. https://doi.org/10.1016/j.chb.2017.09.018
   Web of Science ®Google Scholar
• Nguyen, N., Besson, T., & Stinglhamber, F. (2022). Emotional labor: The role of organizational dehumanization. Journal of Occupational Health Psychology, 27(2), 179–194. https://doi.org/10.1037/ocp0000289
   PubMed Web of Science ®Google Scholar
• Oosthuizen, R. M. (2019). Smart technology, artificial intelligence, robotics and algorithms (STARA): Employees’ perceptions and wellbeing in future workplaces. In I. L. Potgieter, N. Ferreira, & M. Coetzee (Eds.), Theory, research and dynamics of career wellbeing (pp. 17–40). Springer International Publishing.
   Google Scholar
• Palan, S., & Schitter, C. (2018). Prolific. ac—A subject pool for online experiments. Journal of Behavioral and Experimental Finance, 17, 22–27. https://doi.org/10.1016/j.jbef.2017.12.004
   Web of Science ®Google Scholar
• Paluch, S., Tuzovic, S., Holz, H. F., Kies, A., & Jörling, M. (2022). “My colleague is a robot”–exploring frontline employees’ willingness to work with collaborative service robots. Journal of Service Management, 33(2), 363–388. https://doi.org/10.1108/JOSM-11-2020-0406
   Web of Science ®Google Scholar
• Pollak, A., Paliga, M., Pulopulos, M. M., Kozusznik, B., & Kozusznik, M. W. (2020). Stress in manual and autonomous modes of collaboration with a cobot. Computers in Human Behavior, 112, 106469. https://doi.org/10.1016/j.chb.2020.106469
   Web of Science ®Google Scholar
• Prakash, A., & Rogers, W. A. (2015). Why some humanoid faces are perceived more positively than others: Effects of human-likeness and task. International Journal of Social Robotics, 7(2), 309–331. https://doi.org/10.1007/s12369-014-0269-4
   PubMed Web of Science ®Google Scholar
• Preacher, K. J., Rucker, D. D., & Hayes, A. F. (2007). Addressing moderated mediation hypotheses: Theory, methods, and prescriptions. Multivariate Behavioral Research, 42(1), 185–227. https://doi.org/10.1080/00273170701341316
   PubMed Web of Science ®Google Scholar
• Prewett, M. S., Johnson, R. C., Saboe, K. N., Elliott, L. R., & Coovert, M. D. (2010). Managing workload in human-robot interaction: A review of empirical studies. Computers in Human Behavior, 26(5), 840–856. https://doi.org/10.1016/j.chb.2010.03.010
   Web of Science ®Google Scholar
• Purvanova, R. K., & Muros, J. P. (2010). Gender differences in burnout: A meta-analysis. Journal of Vocational Behavior, 77(2), 168–185. https://doi.org/10.1016/j.jvb.2010.04.006
   Web of Science ®Google Scholar
• Pyszczynski, T., Greenberg, J., Solomon, S., Arndt, J., & Schimel, J. (2004). Why do people need self-esteem? A theoretical and empirical review. Psychological Bulletin, 130(3), 435–468. https://doi.org/10.1037/0033-2909.130.3.435
   PubMed Web of Science ®Google Scholar
• Qin, X., Huang, M., Johnson, R. E., Hu, Q., & Ju, D. (2018). The short-lived benefits of abusive supervisory behavior for actors: An investigation of recovery and work engagement. Academy of Management Journal, 61(5), 1951–1975. https://doi.org/10.5465/amj.2016.1325
   Web of Science ®Google Scholar
• Reichl, C., Leiter, M. P., & Spinath, F. M. (2014). Work-nonwork conflict and burnout: A meta-analysis. Human Relations, 67(8), 979–1005. https://doi.org/10.1177/0018726713509857
   Web of Science ®Google Scholar
• Reis, J., Melão, N., Salvadorinho, J., Soares, B., & Rosete, A. (2020). Service robots in the hospitality industry: The case of Henn-na hotel, Japan. Technology in Society, 63, 101423. https://doi.org/10.1016/j.techsoc.2020.101423
   Web of Science ®Google Scholar
• Rhodewalt, F., & Tragakis, M. W. (2003). Self-esteem and self-regulation: Toward optimal studies of self-esteem. Psychological Inquiry, 14(1), 66–70. https://doi.org/10.1207/s15327965pli1401_02
   Web of Science ®Google Scholar
• Robinson, H., MacDonald, B., & Broadbent, E. (2014). The role of healthcare robots for older people at home: A review. International Journal of Social Robotics, 6(4), 575–591. https://doi.org/10.1007/s12369-014-0242-2
   Web of Science ®Google Scholar
• International Federation of Robotics. (2017). The impact of robots on productivity, employment and jobs. https://ifr.org/downloads/papers/IFR_The_Impact_of_Robots_on_ Employment_Positioning_Paper_updated_version_2018.pdf.
   Google Scholar
• Rosse, J. G., Boss, R. W., Johnson, A. E., & Crown, D. F. (1991). Conceptualizing the role of self-esteem in the burnout process. Group & Organization Studies, 16(4), 428–451. https://doi.org/10.1177/105960119101600406
   Google Scholar
• Salvini, P., Laschi, C., & Dario, P. (2010). Design for acceptability: Improving robots’ coexistence in human society. International Journal of Social Robotics, 2(4), 451–460. https://doi.org/10.1007/s12369-010-0079-2
   Web of Science ®Google Scholar
• Sarker, S., Jamal, L., Ahmed, S. F., & Irtisam, N. (2021). Robotics and artificial intelligence in healthcare during COVID-19 pandemic: A systematic review. Robotics and Autonomous Systems, 146, 103902. https://doi.org/10.1016/j.robot.2021.103902
   PubMed Web of Science ®Google Scholar
• 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. Computers in Human Behavior, 115(May 2020), 106585. https://doi.org/10.1016/j.chb.2020.106585
   Google Scholar
• Schaufeli, W. B., Leiter, M. P., & Maslach, C. (2009). Burnout: 35 Years of research and practice. Career Development International, 14(3), 204–220. https://doi.org/10.1108/13620430910966406
   Web of Science ®Google Scholar
• Shirom, A., Westman, M., Shamai, O., & Carel, R. S. (1997). Effects of work overload and burnout on cholesterol and triglycerides levels: The moderating effects of emotional reactivity among male and female employees. Journal of Occupational Health Psychology, 2(4), 275–288. https://doi.org/10.1037/1076-8998.2.4.275
   PubMedGoogle Scholar
• Short, M. M., Mazmanian, D., Oinonen, K., & Mushquash, C. J. (2016). Executive function and self-regulation mediate dispositional mindfulness and well-being. Personality and Individual Differences, 93, 97–103. https://doi.org/10.1016/j.paid.2015.08.007
   Web of Science ®Google Scholar
• Simões, A. C., Pinto, A., Santos, J., Pinheiro, S., & Romero, D. (2022). Designing human-robot collaboration (HRC) workspaces in industrial settings: A systematic literature review. Journal of Manufacturing Systems, 62, 28–43. https://doi.org/10.1016/j.jmsy.2021.11.007
   Web of Science ®Google Scholar
• Smids, J., Nyholm, S., & Berkers, H. (2020). Robots in the workplace: A threat to—or opportunity for—meaningful work? Philosophy & Technology, 33(3), 503–522. https://doi.org/10.1007/s13347-019-00377-4
   Google Scholar
• Song, C. S., & Kim, Y.-K. (2022). The role of the human-robot interaction in consumers’ acceptance of humanoid retail service robots. Journal of Business Research, 146, 489–503. https://doi.org/10.1016/j.jbusres.2022.03.087
   Web of Science ®Google Scholar
• Song, Y., Zhang, M., Hu, J., & Cao, X. (2022). Dancing with service robots: The impacts of employee-robot collaboration on hotel employees’ job crafting. International Journal of Hospitality Management, 103, 103220. https://doi.org/10.1016/j.ijhm.2022.103220
   Web of Science ®Google Scholar
• Sorell, T. (2022). Cobots, “co-operation” and the replacement of human skill. Ethics and Information Technology, 24(4), 44. https://doi.org/10.1007/s10676-022-09667-6
   Web of Science ®Google Scholar
• Spatola, N., & Normand, A. (2021). Human vs. machine: The psychological and behavioral consequences of being compared to an outperforming artificial agent. Psychological Research, 85(3), 915–925. https://doi.org/10.1007/s00426-020-01317-0
   PubMed Web of Science ®Google Scholar
• Spears, R., Ellemers, N., & Doosje, B. (2005). Let me count the ways in which I respect thee: Does competence compensate or compromise lack of liking from the group? European Journal of Social Psychology, 35(2), 263–279. https://doi.org/10.1002/ejsp.248
   Web of Science ®Google Scholar
• Stecke, K. E., & Mokhtarzadeh, M. (2022). Balancing collaborative human-robot assembly lines to optimise cycle time and ergonomic risk. International Journal of Production Research, 60(1), 25–47. https://doi.org/10.1080/00207543.2021.1989077
   Web of Science ®Google Scholar
• Stock-Homburg, R. (2022). Survey of emotions in human-robot interactions: Perspectives from robotic psychology on 20 years of research. International Journal of Social Robotics, 14(2), 389–411. https://doi.org/10.1007/s12369-021-00778-6
   Web of Science ®Google Scholar
• Tang, P. M., Koopman, J., Mai, K. M., De Cremer, D., Zhang, J., Reynders, P., Ng, C. T. S., & Chen, I.-H. (2023). No person is an island: Unpacking the work and after-work consequences of interacting with artificial intelligence. The Journal of Applied Psychology, 108(11), 1766–1789. https://doi.org/10.1037/apl0001103
   PubMedGoogle Scholar
• Tang, P. M., Koopman, J., McClean, S. T., Zhang, J. H., Li, C. H., De Cremer, D., Lu, Y., & Ng, C. T. S. (2021). When conscientious employees meet intelligent machines: An integrative approach inspired by complementarity theory and role theory. Academy of Management Journal, 65(3), 1019–1054. https://doi.org/10.5465/amj.2020.1516
   Web of Science ®Google Scholar
• Tang, P. M., Koopman, J., Yam, K. C., De Cremer, D., Zhang, J. H., & Reynders, P. (2023). The self‐regulatory consequences of dependence on intelligent machines at work: Evidence from field and experimental studies. Human Resource Management, 62(5), 721–744. https://doi.org/10.1002/hrm.22154
   Web of Science ®Google Scholar
• Tangney, J. P., Baumeister, R. F., & Boone, A. L. (2004). High self-control predicts good adjustment, less pathology, better grades, and interpersonal success. Journal of Personality, 72(2), 271–324. https://doi.org/10.1111/j.0022-3506.2004.00263.x
   PubMed Web of Science ®Google Scholar
• Taris, T. W., Kompier, M. A., De Lange, A. H., Schaufeli, W. B., & Schreurs, P. J. (2003). Learning new behaviour patterns: A longitudinal test of Karasek’s active learning hypothesis among Dutch teachers. Work & Stress, 17(1), 1–20. https://doi.org/10.1080/0267837031000108149
   Web of Science ®Google Scholar
• Tsai, C. Y., Marshall, J. D., Choudhury, A., Serban, A., Tsung-Yu Hou, Y. Y., Jung, M. F., Dionne, S. D., & Yammarino, F. J. (2022). Human-robot collaboration: A multilevel and integrated leadership framework. The Leadership Quarterly, 33(1), 101594. https://doi.org/10.1016/j.leaqua.2021.101594
   Web of Science ®Google Scholar
• Turja, T., Särkikoski, T., Koistinen, P., Krutova, O., & Melin, H. (2022). Job well robotized!–Maintaining task diversity and well-being in managing technological changes. European Management Journal. Advance online publication. https://doi.org/10.1016/j.emj.2022.08.002
   Google Scholar
• Valkenburg, P., Beyens, I., Pouwels, J. L., van Driel, I. I., & Keijsers, L. (2021). Social media use and adolescents’ self-esteem: Heading for a person-specific media effects paradigm. Journal of Communication, 71(1), 56–78. https://doi.org/10.1093/joc/jqaa039
   Web of Science ®Google Scholar
• vanDellen, M. R., Campbell, W. K., Hoyle, R. H., & Bradfield, E. K. (2011). Compensating, resisting, and breaking: A meta-analytic examination of reactions to self-esteem threat. Personality and Social Psychology Review, 15(1), 51–74. https://doi.org/10.1177/1088868310372950
   PubMed Web of Science ®Google Scholar
• Vohs, K. D., Baumeister, R. F., Schmeichel, B. J., Twenge, J. M., Nelson, N. M., & Tice, D. M. (2008). Making choices impairs subsequent self-control: A limited-resource account of decision making, self-regulation, and active initiative. Journal of Personality and Social Psychology, 94(5), 883–898. https://doi.org/10.1037/0022-3514.94.5.883
   PubMed Web of Science ®Google Scholar
• Vohs, K. D., & Heatherton, T. F. (2004). Ego threat elicits different social comparison processes among high and low self-esteem people: Implications for interpersonal perceptions. Social Cognition, 22(1), 168–191. https://doi.org/10.1521/soco.22.1.168.30983
   Web of Science ®Google Scholar
• Waheed, A., & Zhang, Q. (2022). Effect of CSR and ethical practices on sustainable competitive performance: A case of emerging markets from stakeholder theory perspective. Journal of Business Ethics, 175(4), 837–855. https://doi.org/10.1007/s10551-020-04679-y
   Web of Science ®Google Scholar
• Wang, H., Zhang, Y., & Wan, M. (. (2022). Linking high‐performance work systems and employee well‐being: A multilevel examination of the roles of organisation‐based self‐esteem and departmental formalisation. Human Resource Management Journal, 32(1), 92–116. https://doi.org/10.1111/1748-8583.12391
   Web of Science ®Google Scholar
• Watson, J., & Nesdale, D. (2012). Rejection sensitivity, social withdrawal, and loneliness in young adults. Journal of Applied Social Psychology, 42(8), 1984–2005. https://doi.org/10.1111/j.1559-1816.2012.00927.x
   Web of Science ®Google Scholar
• Weis, P. P., & Herbert, C. (2022). Do I still like myself? Human-robo collaboration entails emotional consequences. Computers in Human Behavior, 127, 107060. https://doi.org/10.1016/j.chb.2021.107060
   Web of Science ®Google Scholar
• West, D. M. (2018). The future of work: Robots, AI, and automation. Brookings Institution Press.
   Google Scholar
• Wilson, H. J., & Daugherty, P. R. (2018). Collaborative intelligence: Humans and AI are joining forces. Harvard Business Review, 96(4), 114–123. https://hometownhealthonline.com/wp-content/uploads/2019/02/ai2-R1804J-PDF-ENG.pdf.
   Web of Science ®Google Scholar
• Wilson, J. R., Lee, N. Y., Saechao, A., Tickle-Degnen, L., & Scheutz, M. (2018). Supporting human autonomy in a robot-assisted medication sorting task. International Journal of Social Robotics, 10(5), 621–641. https://doi.org/10.1007/s12369-017-0456-1
   Web of Science ®Google Scholar
• Wolf, F. D., & Stock-Homburg, R. M. (2022). How and when can robots be team members? Three decades of research on human-robot teams. Group & Organization Management, 48(6), 1666–1744. https://doi.org/10.1177/10596011221076636
   Google Scholar
• Wrosch, C., Scheier, M. F., Miller, G. E., Schulz, R., & Carver, C. S. (2003). Adaptive self-regulation of unattainable goals: Goal disengagement, goal reengagement, and subjective well-being. Personality & Social Psychology Bulletin, 29(12), 1494–1508. https://doi.org/10.1177/0146167203256921
   PubMed Web of Science ®Google Scholar
• Wu, M., Lin, J.-R., & Zhang, X.-H. (2022). How human-robot collaboration impacts construction productivity: An agent-based multi-fidelity modeling approach. Advanced Engineering Informatics, 52, 101589. https://doi.org/10.1016/j.aei.2022.101589
   Web of Science ®Google Scholar
• Yam, K. C., Tang, P. M., Jackson, J. C., Su, R., & Gray, K. (2023). The rise of robots increases job insecurity and maladaptive workplace behaviors: Multimethod evidence. The Journal of Applied Psychology, 108(5), 850–870. https://doi.org/10.1037/apl0001045
   PubMed Web of Science ®Google Scholar
• Yogeeswaran, K., Złotowski, J., Livingstone, M., Bartneck, C., Sumioka, H., & Ishiguro, H. (2016). The interactive effects of robot anthropomorphism and robot ability on perceived threat and support for robotics research. Journal of Human-Robot Interaction, 5(2), 29–47. https://doi.org/10.5898/JHRI.5.2.Yogeeswaran
   Web of Science ®Google Scholar
• Zhang, L.-X., Li, J.-M., Wang, L.-L., Mao, M.-Y., & Zhang, R.-X. (2023). How does the usage of robots in hotels affect employees’ turnover intention? A double-edged sword study. Journal of Hospitality and Tourism Management, 57, 74–83. https://doi.org/10.1016/j.jhtm.2023.09.004
   Web of Science ®Google Scholar
• Złotowski, J., Yogeeswaran, K., & Bartneck, C. (2017). Can we control it? Autonomous robots threaten human identity, uniqueness, safety, and resources. International Journal of Human-Computer Studies, 100, 48–54. https://doi.org/10.1016/j.ijhcs.2016.12.008
   Web of Science ®Google Scholar