5004. A Generalized Allocation Framework for Big Boss Games
Invited abstract in session MF-67: Selected Aspects of International Finance and OR 1, stream Selected Aspects of International Finance and OR.
Monday, 16:15-17:45Room: KOL – PC Raum 3
Authors (first author is the speaker)
| 1. | İsmail Özcan
|
| Department of Engineering for Industrial Systems and Technologies, University of Parma | |
| 2. | Gerhard-Wilhelm Weber
|
| Faculty of Engineering Management, Poznan University of Technology |
Abstract
This study introduces the k-proportional τ-value as a generalized allocation rule for big boss games by modifying the minimal right vector with a proportionality parameter, k. The model preserves core allocations while allowing flexible payoff distribution. An AI- and OR-focused case based on Amazon’s personalized recommendation system illustrates its use in analyzing hierarchical collaboration, incentive alignment, and fair reward sharing in complex, data-driven organizational settings. This approach offers a practical tool for evaluating cooperation and equity in modern firms.
Keywords
- Artificial Intelligence
- Game Theory
- Operations Management
Status: accepted
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