The importance of designing policy measures that government and other public bodies apply to different populations has been escalating in recent decades. This study seeks the best way to induce conservative minority groups to cooperate with healthcare policy. The case study focuses on the Bedouin population of Israel and its willingness to accept COVID-19 vaccination. The study is based on vaccination data from the Israel Ministry of Health for the country’s entire Bedouin population, twenty-four semi-structured in-depth interviews with relevant key stakeholders, and the use of game-theory tools to profile the players, the utility functions, and various equilibrium combinations. By comparing the groups and integrating game-theory tools into the process, we reveal variables that may affect healthcare processes among conservative minority communities. Finally, cross-tabulating the results with the interview findings strengthens the insights and allows a culturally adjusted policy to be adopted. The different starting points of different minority populations have implications for the design of requisite policies in both the short and the long terms. The analysis of the game allowed us to indicate the strategy that policymakers should adopt in consideration of variables that should be taken into account in order to improve cooperation and the ability to apply policy. To increase vaccination rates among conservative minority communities in general and the Bedouin population in particular, trust in the government must be increased in the long term. In the short term, trust in the medical profession must be increased, and also health literacy.

We study two-sided matching contests with two sets, A and B, each of which includes a finite number of heterogeneous agents with commonly known types. The agents in each set compete in a lottery (Tullock) contest, and then are assortatively matched, namely, the winner of set A is matched with the winner of set B and so on until all the agents in the set with the smaller number of agents are matched. Each agent has a match value that depends on their own type and the type of their match. We assume that the agents’ efforts do not affect their match values and that they have a positive effect on welfare. Therefore, an interior equilibrium in which at least some of the agents are active is welfare superior to a corner equilibrium in which the agents choose to be non-active. We analyze the conditions under which there exists a (partial) interior equilibrium where at least some of the agents compete against each other and exert positive efforts.

We consider two-stage parallel contests with a finite set of agents, as well as a finite set of heterogeneous contests with varying winning prizes. In the first stage, each agent simultaneously chooses in which contest he wants to compete, and in the second stage, the agents who chose the same contest compete against each other in a contest for a single prize. We first assume a general Tullock contest success function with nonlinear cost functions, and then we present an algorithm that converges to equilibrium, namely, the algorithm organizes the allocation of homogeneous or heterogeneous agents of two types, each with a different cost of effort, among the contests until no agent wishes to change his current contest. Later, we assume the Tullock contest success function with linear cost functions, and we show that for homogeneous agents, our model and a potential game are equivalent, allowing us to explicitly characterize the subgame perfect equilibrium with pure strategies.

We investigate two-stage parallel contests with a finite number of heterogeneous agents with various skills (cost of efforts) and reputations, as well as a finite number of heterogeneous contests. Each agent’s value of winning is a combination of a nominal value and the reputation of the competing agents. We demonstrate that reputation in contests may lead to an unstable environment. We present a sufficient condition for resolving this instability, which results in the existence of a subgame perfect equilibrium with pure strategies which cannot be explicitly calculated. However, we arrive at this equilibrium by introducing algorithms that describe dynamic processes in which the agents’ strategies approach the equilibrium point. We demonstrate that our equilibrium is far more likely to hold in an environment where the agents’ skills and reputations are correlated.