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To offer or not to offer? The optimal value-insured strategy for crowdsourced delivery platforms
Transportation Research Part E: Logistics and Transportation Review ( IF 10.6 ) Pub Date : 2023-03-17 , DOI: 10.1016/j.tre.2023.103091
Shan He , Ying Dai , Zu-Jun Ma

Value-insured services are widely used to reduce senders’ perceived risk in crowdsourced delivery. However, research has not examined whether and how the value-insured strategy provided by crowdsourced delivery platforms (CDPs) affects those platforms’ decisions and the participation behaviors of two-sided users (senders and couriers). In this study, we develop game-theoretic models for a CDP’s pricing and wage decisions when it offers value-insured services and when it does not. Moreover, we compare the CDP’s optimal decisions under three insurance scenarios, i.e., a revenue-sharing scheme, fixed-fee scheme, and reinsurance scheme, to explore the optimal insurance scheme for the CDP. We find that introducing a value-insured strategy will benefit the CDP only when the couriers’ sensitivity to the declared value of the delivered parcel is adequate. When the average declared value is below a certain threshold, the reinsurance scheme produces the highest CDP’s profit; otherwise, the fixed-fee scheme leads to the highest CDP’s profit. We also show that offering a value-insured service does not always increase consumer surplus, labor welfare, and social welfare, and although it increases the CDP’s price level, it is not necessarily beneficial to the CDP. Our findings provide strong support for CDPs’ decision-making.



中文翻译:

提供还是不提供?众包配送平台最优保值策略

价值保险服务被广泛用于降低发件人在众包交付中的感知风险。然而,研究尚未检验众包配送平台 (CDP) 提供的价值保险策略是否以及如何影响这些平台的决策和双边用户(发送者和快递员)的参与行为。在这项研究中,我们为 CDP 在提供保值服务和不提供保值服务时的定价和工资决策开发了博弈论模型。此外,我们比较了 CDP 在三种保险情景下的最优决策,即收益分享方案、固定费用方案和再保险方案,以探索 CDP 的最优保险方案。我们发现,只有当快递员对已交付包裹的申报价值足够敏感时,引入价值保险策略才会使 CDP 受益。当平均申报价值低于某个阈值时,再保险方案产生最高的 CDP 利润;否则,固定费用方案会导致 CDP 的利润最高。我们还表明,提供保值服务并不总能增加消费者剩余、劳动福利和社会福利,虽然它提高了 CDP 的价格水平,但不一定对 CDP 有利。我们的研究结果为 CDP 的决策提供了强有力的支持。它不一定对 CDP 有利。我们的研究结果为 CDP 的决策提供了强有力的支持。它不一定对 CDP 有利。我们的研究结果为 CDP 的决策提供了强有力的支持。

更新日期:2023-03-18
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