Museum and Visitor Interaction and Feedback Orchestration Enabled by Labor Economics

Abstract

In this article, we address the problem of modeling and orchestrating the interactions between a museum and its visitors, viewing the system as a cyber–physical–social system (CPSS). In particular, the museum operator provides monetary rewards to the visitors in exchange for their contributions, which are expressed as their total number of provided feedback evaluations of visited exhibits over their touring time. The interactions among the museum operator and visitors are captured in appropriately designed utility functions following the principles of labor economics, while the visitors’ behavioral characteristics are utilized to define their unique types. Under such a setting and formulation, the goal of the museum operator is to optimize their profit and benefits while jointly satisfying the visitors’ quality of experience prerequisites as reflected via their utility functions. The corresponding optimization problem is treated and solved under the general and realistic cases of incomplete information, wherein the museum operator estimates the visitors’ types probabilistically. The resulting outcome, referred to as the “optimal contract”, jointly determines the visitors’ optimal contributions, as well as the museum operator’s optimal amount of personalized rewards provided to each visitor. The performance of the proposed approach is evaluated through modeling and simulation, and detailed numerical results are presented to demonstrate the key benefits of the proposed optimization approach versus either type-agnostic or heuristic alternatives.