Methoden vergleichen

	Principal-Agent-Modell	Shapley-Wert
Fachgebiet	Spieltheorie	Spieltheorie
Familie	Machine learning	Machine learning
Entstehungsjahr	1976	1953
Urheber	Michael Jensen, William Meckling, Bengt Holmstrom	Lloyd Shapley
Typ	algorithm	algorithm
Wegweisende Quelle	Jensen, M. C., & Meckling, W. H. (1976). Theory of the firm: Managerial behavior, agency costs and ownership structure. Journal of Financial Economics, 3(4), 305-360.	Shapley, L. S. (1953). A value for n-person games. In H. W. Kuhn & A. W. Tucker (Eds.), Contributions to the Theory of Games II (pp. 307-317). Princeton University Press.
Aliasnamen	Agency Theory, Hidden Action Problem, Moral Hazard	Fair Division, Cooperative Game Solution, Dividend Vector
Verwandt	4	4
Zusammenfassung	The Principal-Agent Model analyzes how a principal (e.g., owner, employer, policymaker) can incentivize an agent (e.g., manager, employee, firm) to act in the principal's interest when the agent has private information or can take hidden actions. Formalized by Jensen and Meckling in 1976, the model identifies agency costs arising from moral hazard (the agent exerts less effort than desired) and adverse selection (the agent hides unfavorable information). Optimal contracts balance incentives with risk allocation.	The Shapley Value is a solution concept for coalition games that distributes total payoff fairly among players based on their marginal contributions to coalitions. Introduced by Lloyd Shapley in 1953, the Shapley Value is the unique payoff distribution that satisfies four intuitive axioms: efficiency (total payoff is distributed), symmetry (identical players receive equal payoff), null player (players contributing nothing receive nothing), and additivity across games.