A quantum game decision-making analysis of parking sharing behavior considering fairness preferences

Abstract

Parking constraints are particularly acute in the urban city center, but the many negative impacts of sharing private parking make owners living in central areas reluctant to share private parking. Hence, we employ the quantum game to analyze the interactions among heterogeneous parking providers. This study explores quantum non-entanglement and entanglement strategies in the context of parking sharing and investigates the impact of heterogeneous and fairness preferences on gaming strategies. The findings indicate that in the absence of quantum entanglement, achieving a Pareto optimal strategy in which both parties share private parking is challenging. However, at the maximum quantum entanglement, the cost incurred by the unwilling side must be borne individually, whereas adopting mutual-sharing quantum strategy leads to a win–win situation. Furthermore, owners’ fairness preferences significantly motivate parties with higher sharing revenues. When the disparity in revenues is too high, leading to distinctly unfair aversion to the side with lower sharing revenues, owners’ willingness to engage in sharing is reduced.