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Research Article

Perceived Fairness of Human Managers Compared with Artificial Intelligence in Employee Performance Evaluation

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References

  • Agrawal, A.; Gans, J.; and Goldfarb, A. Managing the Machines - AI is Making Prediction Cheap, Posing New Challenges for Managers | Data Science Association. Working Paper, (December 2016).
  • Agrawal, A.; Gans, J.; and Goldfarb, A. Prediction Machines: The Simple Economics of Artificial Intelligence by Ajay Agrawal. Boston: Harvard Business Press, 2018.
  • Agrawal, A.; Gans, J.; and Goldfarb, A. Human judgment and AI pricing. AEA Papers and Proceedings, 108, (May 2018), 58–63.
  • Argote, L. Organizational Learning: Creating, Retaining and Transferring Knowledge. Boston: Springer Science & Business Media, 1999.
  • Bai, B.; Dai, H.; Zhang, D.; Zhang, F.; and Hu, H. The impacts of algorithmic work assignment on fairness perceptions and productivity: Evidence from field experiments. SSRN Electronic Journal, (March 2020).
  • Bajari, P.; Chernozhukov, V.; Hortaçsu, A.; and Suzuki, J. The impact of big data on firm performance: An empirical investigation. AEA Papers and Proceedings, 109, (May 2019), 33–37.
  • Balasubramanian, N.; Ye, Y.; and Xu, M. Substituting human decision-making with machine learning: Implications for organizational learning. Academy of Management Review, 47, 3 (July 2022), 448–465.
  • Brynjolfsson, E.; Hui, X.; and Liu, M. Does machine translation affect international trade? Evidence from a large digital platform. Management Science, 65, 12 (December 2019), 5449–5460.
  • Brynjolfsson, E.; Liu, M.; and Westerman, G. Do computers reduce the value of worker persistence? Journal of Management Information Systems, 39, 1 (2022), 41–67.
  • Burton, J.W.; Stein, M.K.; and Jensen, T.B. A systematic review of algorithm aversion in augmented decision making. Journal of Behavioral Decision Making, 33, 2 (April 2020), 220–239.
  • Carver, C.S.; and Scheier, M.F. On the Self-Regulation of Behavior. Cambrdige, UK: Cambridge University Press, 1998.
  • Carver, C.S.; Sutton, S.K.; and Scheier, M.F. Action, emotion, and personality: Emerging conceptual integration. Personality and Social Psychology Bulletin, 26, 6 (August 2000), 741–751.
  • Casciaro, T.; and Lobo, M.S. When competence is irrelevant: The role of interpersonal affect in task-related ties. Administrative Science Quarterly, 53, 4 (December 2008), 655–684.
  • Castelo, N.; Bos, M.W.; and Lehmann, D.R. Task-dependent algorithm aversion. Journal of Marketing Research, 56, 5 (October 2019), 809–825.
  • Choudhury, P.; Starr, E.; and Agarwal, R. Machine learning and human capital complementarities: Experimental evidence on bias mitigation. Strategic Management Journal, 41, 8 (August 2020), 1381–1411.
  • Cowgill, B.; and Tucker, C.E. Economics, fairness and algorithmic bias. The Journal of Economic Perspectives, (April 2020).
  • Csaszar, F.A.; and Steinberger, T. Organizations as artificial intelligences: The use of artificial intelligence analogies in organization theory. Academy of Management Annals, 16, 1 (January 2022), 1–37.
  • Cyert, R.M.; and March, J.G. A Behavioral Theory of the Firm. Englewood Cliffs, NJ: Prentice-Hall, 1963.
  • Dawes, R.M. The robust beauty of improper linear models in decision making. American Psychologist, 34, 7 (July 1979), 571–582.
  • Deming, D.J. The growing importance of social skills in the labor market. Quarterly Journal of Economics, 132, 4 (November 2017), 1593–1640.
  • Dennis, A.R.; Lakhiwal, A.; and Sachdeva, A. AI agents as team members: Effects on satisfaction, conflict, trustworthiness, and willingness to work with. Journal of Management Information Systems, 40, 2 (April 2023), 307–337.
  • Dietvorst, B.J.; Simmons, J.P.; and Massey, C. Algorithm aversion: People erroneously avoid algorithms after seeing them err. Journal of Experimental Psychology: General, 144, 1 (2015), 114–126.
  • Dietvorst, B.J.; Simmons, J.P.; and Massey, C. Overcoming algorithm aversion: People will use imperfect algorithms if they can (even slightly) modify them. Management Science, 64, 3 (March 2018), 1155–1170.
  • Dorsey, D.; and Mueller-Hanson, R. Performance Management that Makes a Difference: An Evidence-Based Approach. 2017.
  • Fountaine, T.; McCarthy, B., and Saleh, T. Building the AI-Powered Organization, 97, 4 (2019), 62–73.
  • Gal, U., Jensen, T.B., and Stein, M.K. Breaking the vicious cycle of algorithmic management: A virtue ethics approach to people analytics. Information and Organization, 30, 2 (June 2020), 100301.
  • Gibbons, R. Incentives between firms (and within). Management Science, 51, 1 (January 2005), 2–17.
  • Glikson, E.; and Woolley, A.W. Human trust in artificial intelligence: Review of empirical research. Academy of Management Annals, 14, 2 (July 2020), 627–660.
  • Granulo, A.; Fuchs, C.; and Puntoni, S. Psychological reactions to human versus robotic job replacement. Nature Human Behaviour 2019 3:10, 3, 10 (August 2019), 1062–1069.
  • Gunaratne, J.; Zalmanson, L.; and Nov, O. The persuasive power of algorithmic and crowdsourced advice. Journal of Management Information Systems, 35, 4 (October 2018), 1092–1120.
  • Haack, P.; Pfarrer, M.D.; and Scherer, A.G. Legitimacy-as-feeling: How affect leads to vertical legitimacy spillovers in transnational governance. Journal of Management Studies, 51, 4 (June 2014), 634–666.
  • Hansen, M.T. The search-transfer problem: The role of weak ties in sharing knowledge across organization subunits. Administrative Science Quarterly, 44, 1 (March 1999), 82–111.
  • Hayes, A. PROCESS: A Versatile Computational Tool for Observed Variable Mediation, Moderation, and Conditional Process Modeling 1. Psychology, (2012), 4–6.
  • Hayes, A.F. Introduction to mediation, moderation, and conditional process analysis, Second Edition: A regression-based approach. The Guilford Press, 46, 3 (2018), 1–692.
  • Iansiti, M.; and Lakhani, K.R. Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World. Cambridge, MA: Harvard Business Review Press, 2020.
  • Jensen, R.J.; and Szulanski, G. Template use and the effectiveness of knowledge transfer. Management Science, 53, 11 (November 2007), 1716–1730.
  • Jia, N. The “Make and/or buy” decisions of corporate political lobbying: Integrating the economic efficiency and legitimacy perspectives. Academy of Management Review, 43, 2 (April 2018), 307–326.
  • Jia, N.; Luo, X.; Chen, H.; and Fang, Z. AI Assistance, Employee Creativity, and Job Performance: Evidence from a Field Experiment. Working Paper, (2021).
  • Joshi, A.; Lavanchy, M.; Srinivasan, S.; and You, Y. A Meta-Analysis of Algorithm Aversion. Working Paper.
  • Kahneman, D.; and Frederick, S. Representativeness revisited: Attribute substitution in intuitive judgment. Heuristics and Biases, (June 2002), 49–81.
  • Kesavan, S.; and Kushwaha, T. Field experiment on the profit implications of merchants’ discretionary power to override data-driven decision-making tools. Management Science, 66, 11 (August 2020), 5182–5190.
  • Kleinberg, J.; Ludwig, J.; Mullainathan, S.; and Sunstein, C.R. Discrimination in the age of algorithms. Journal of Legal Analysis, 10, (December 2018), 113–174.
  • Köchling, A.; and Wehner, M.C. Discriminated by an algorithm: A systematic review of discrimination and fairness by algorithmic decision-making in the context of HR recruitment and HR development. Business Research, 13, 3 (November 2020), 795–848.
  • Kolbjørnsrud, V.; Amico, R.; and Thomas, R.J. Partnering with Al: How organizations can win over skeptical managers. Strategy and Leadership, 45, 1 (2017), 37–43.
  • Lee, K. AI superpowers: China, Silicon Valley, and the New World Order. New York: Houghton Mifflin Harcourt, 2018.
  • Lee, M.K. Understanding perception of algorithmic decisions: Fairness, trust, and emotion in response to algorithmic management. Big Data & Society, 5, 1 (January 2018), 205395171875668.
  • Logg, J.M.; Minson, J.A.; and Moore, D.A. Algorithm appreciation: People prefer algorithmic to human judgment. Organizational Behavior and Human Decision Processes, 151, (March 2019), 90–103.
  • Ludwig, J.; and Mullainathan, S. Fragile algorithms and fallible decision-makers: Lessons from the justice system. Journal of Economic Perspectives, 35, 4 (September 2021), 71–96.
  • Luo, X.; Qin, M.S.; Fang, Z.; and Qu, Z. Artificial intelligence coaches for sales agents: Caveats and solutions. Journal of Marketing, 85, 2 (March 2021), 14–32.
  • Mahmud, H.; Islam, A.K.M.N.; Ahmed, S.I.; and Smolander, K. What influences algorithmic decision-making? A systematic literature review on algorithm aversion. Technological Forecasting and Social Change, 175, (February 2022), 121390.
  • Mayer, R.C.; Davis, J.H.; and Schoorman, F.D. An integrative model of organizational trust. The Academy of Management Review, 20, 3 (July 1995), 709.
  • McKnight, D.H.; Liu, P.; and Pentland, B.T. Trust change in information technology products. Journal of Management Information Systems, 37, 4 (2020), 1015–1046.
  • Meehl, P.E. (Paul E. Clinical versus Statistical Prediction: A Theoretical Analysis and a Review of the Evidence. Minneapolis, MN: University of Minnesota Press, 1954.
  • Mende, M.; Scott, M.L.; van Doorn, J.; Grewal, D.; and Shanks, I. Service robots rising: How humanoid robots influence service experiences and elicit compensatory consumer responses. Journal of Marketing Research, 56, 4 (August 2019), 535–556.
  • Mintzberg, H. The Manager’s Job: Folklore and Fact. Harvard business review, 53, 4 (1975), 1–14.
  • Moss, S.E.; and Sanchez, J.I. Are your employees avoiding you? Managerial strategies for closing the feedback gap. Academy of Management Perspectives, 18, 1 (February 2004), 32–44.
  • Murray, A.; Rhymer, J.; and Sirmon, D.G. Humans and technology: Forms of conjoined agency in organizations. Academy of Management Review, 46, 3 (July 2021), 552–571.
  • Newman, D.T.; Fast, N.J.; and Harmon, D.J. When eliminating bias isn’t fair: Algorithmic reductionism and procedural justice in human resource decisions. Organizational Behavior and Human Decision Processes, 160, (September 2020), 149–167.
  • Park, E.H.; Werder, K.; Cao, L.; and Ramesh, B. Why do family members reject AI in health care? Competing effects of emotions. Journal of Management Information Systems, 39, 3 (2022), 765–792.
  • Purvis, R.L.; Sambamurthy, V.; and Zmud, R.W. The assimilation of knowledge platforms in organizations: An empirical investigation. Organization Science, 12, 2 (April 2001), 117–135.
  • Qiu, L.; and Benbasat, I. Evaluating anthropomorphic product recommendation agents: A social relationship perspective to designing information systems. Journal of Management Information Systems, 25, 4 (April 2008), 145–182.
  • Raisch, S.; and Krakowski, S. Artificial intelligence and management: The automation-augmentation paradox. Academy of Management Review, 46, 1 (January 2021), 192–210.
  • Rambachan, A.; Kleinberg, J.; Ludwig, J.; and Mullainathan, S. An economic perspective on algorithmic fairness. AEA Papers and Proceedings, 110, (May 2020), 91–95.
  • Riedl, R.; Mohr, P.; Kenning, P.; Davis, F.; and Heekeren, H. Trusting humans and avatars: A brain imaging study based on evolution theory. Journal of Management Information Systems, 30, 4 (April 2014), 83–114.
  • Rust, R.T., and Huang, M.-H. The Feeling Economy: How Artificial Intelligence is Creating the Era of Empathy. New York, NY: Palgrave Macmillan, 2021.
  • Schilke, O.; Reimann, M.; and Cook, K.S. Trust in social relations. Annual Review of Sociology, 47, 1 (July 2021), 239–259.
  • Srinivasan, R.; and Sarial-Abi, G. When algorithms fail: Consumers’ responses to brand harm crises caused by algorithm errors. Journal of Marketing, 85, 5 (September 2021), 74–91.
  • Tan, H.T.; and Jamal, K. Do auditors objectively evaluate their subordinates’ work? The Accounting Review, 76, 1 (January 2001), 99–110.
  • Teodorescu, M.H.M.; Morse, L.; Awwad, Y.; and Kane, G.C. Failures of fairness in automation require a deeper understanding of human–ML augmentation. MIS Quarterly: Management Information Systems, 45, 3 (September 2021), 1483–1499.
  • Tong, S.; Jia, N.; Luo, X.; and Fang, Z. The Janus face of artificial intelligence feedback: Deployment versus disclosure effects on employee performance. Strategic Management Journal, 42, 9 (September 2021), 1600–1631.
  • Tost, L.P. An integrative model of legitimacy judgments. Academy of Management Review, 36, 4 (October 2011), 686–710.
  • Wang, W.; and Benbasat, I. Recommendation agents for electronic commerce: Effects of explanation facilities on trusting beliefs. Journal of Management Information Systems, 23, 4 (March 2007), 217–246.
  • Wang, W.; and Benbasat, I. Empirical assessment of alternative designs for enhancing different types of trusting beliefs in online recommendation agents. Journal of Management Information Systems, 33, 3 (July 2016), 744–775.
  • Wilson, J., and Daugherty, P.R. Collaborative intelligence: Humans and AI are joining forces. Harvard Business Review, 96, 4 (2018), 114–123.
  • Xue, M.; Cao, X.; Feng, X.; Gu, B.; and Zhang, Y. Is college education less necessary with AI? Evidence from firm-level labor structure changes. Journal of Management Information Systems, 39, 3 (2022), 865–905.
  • You, S.; Yang, C.L.; and Li, X. Algorithmic versus human advice: Does presenting prediction performance matter for algorithm appreciation? Journal of Management Information Systems, 39, 2 (2022), 336–365.
  • Zhang, S.; Mehta, N.; Singh, P.V.; and Srinivasan, K. Frontiers: Can an artificial intelligence algorithm mitigate racial economic inequality? An analysis in the context of Airbnb. Marketing Science, 40, 5 (September 2021), 813–820.

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