Shared parking firms offer a double-sided platform for parking space sharing. Many of these firms provide differentiated service levels to both suppliers and buyers. This new phenomenon in the parking industry materialized thanks to recent innovations in IoT-enabled automation and electric vehicle charging technologies. We study shared parking firms. Specifically, we formulate the firm's location and quality decision problem by using a multiplicative interaction model with competition. A non-cooperative game renders the optimized quality levels and location selections at Nash equilibrium in the presence of competition. We illustrate managerial insights with a small-sized problem. For industry practitioners, we propose a tailored branch and bound based exact algorithm and a problem-specific genetic algorithm for large-sized problems. Simulated computational results confirm the effectiveness and efficiency of the proposed shared-parking decision support model.

共享停车公司提供了一个共享停车位的双面平台。这些公司中有许多都为供应商和购买者提供了不同的服务水平。停车行业中的这一新现象的出现，得益于基于IoT的自动化和电动汽车充电技术的最新创新。我们研究共享停车公司。具体来说，我们通过使用竞争的乘法互动模型来制定公司的选址和质量决策问题。在存在竞争的情况下，非合作游戏会在Nash均衡状态下提供优化的质量级别和位置选择。我们以一个小型问题来说明管理洞察力。对于行业从业者，我们提出了一种基于分支定界的量身定制的精确算法和针对大型问题的特定于问题的遗传算法。