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Multi-stakeholder decision theory

Author

Listed:
  • Danny Samson

    (University of Melbourne)

  • Pat Foley

    (University of Melbourne)

  • Heng Soon Gan

    (University of Melbourne)

  • Marianne Gloet

    (University of Melbourne)

Abstract

Decisions made by people at work often have outcomes for their employer (sales, costs, profits) and for themselves personally (career progression, bonus), which are not perfectly aligned across the choice options. When such misalignment exists, decision-makers at all levels in organizations must evaluate choices in terms of conflicting outcomes across stakeholders. Existing theories of agency and stewardship provide very different answers to this question, and utility theory does not address this question at all: it assumes that the decision maker will act so as to maximize the expected utility of the firm, essentially a pure steward position. Yet we see commonplace practices of incentives and monitoring of people’s work and decisions aiming to overcome agency problems, with mixed success in practice. We also sometimes see ‘super-agent’ choices, of managers lining their own pockets while their organizations lose out. In this study, we propose, develop, mathematically model and illustrate a new theory of decision-making, based on a multiple stakeholder utility function approach, where the argument of that function explicitly includes both the employer’s and the employee’s utilities as stakeholders. This new approach is shown to be more generalizable than both pure agency and stewardship approaches, within a broad continuum of tradeoff-based decisions.

Suggested Citation

  • Danny Samson & Pat Foley & Heng Soon Gan & Marianne Gloet, 2018. "Multi-stakeholder decision theory," Annals of Operations Research, Springer, vol. 268(1), pages 357-386, September.
  • Handle: RePEc:spr:annopr:v:268:y:2018:i:1:d:10.1007_s10479-017-2433-3
    DOI: 10.1007/s10479-017-2433-3
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    References listed on IDEAS

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    3. Anna Trunk & Hendrik Birkel & Evi Hartmann, 2020. "On the current state of combining human and artificial intelligence for strategic organizational decision making," Business Research, Springer;German Academic Association for Business Research, vol. 13(3), pages 875-919, November.

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