产品质量信息不对称时基于信号博弈的期权预售策略
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作者单位:

1. 莆田学院 商学院,福建 莆田 351100;2. 厦门大学 管理学院,福建 厦门 361005;3. 诺丁汉大学 商学院,诺丁汉 NG81BB

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E-mail: laowu-50@163.com.

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F272.3

基金项目:

国家自然科学基金项目(71571151,71871197,71872158);莆田学院引进人才科研启动项目(2021080).


Option pricing in advance selling to signal quality
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Affiliation:

1. School of Business,Putian University,Putian 351100,China;2. School of Management,Xiamen University,Xiamen 361005,China;3. School of Business,Nottingham University,Nottingham NG8 1BB,UK

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    摘要:

    预售期到达的策略消费者与制造商之间产品质量信息不对称,制造商可以通过不同的预售策略和预售价格设置,影响消费者对产品质量的判断和购买时机的选择.基于信号传递博弈理论,构建产品质量信息对称和不对称时的博弈模型,给出质量信息不对称时制造商实现分离均衡和混同均衡的边界条件.结果表明:制造商产能较大时,期权预售本身可以作为高产品质量制造商的信号传递工具;消费者判断产品质量为高质量的先验概率足够大时,高产品质量制造商倾向于实现混同均衡隐藏质量信息,反之倾向于实现分离均衡,通过较高的行权价格传递质量信息.最后进一步探讨预售期时长对消费者等待成本的影响,结果表明等待成本相对较低时上述结论依然成立.

    Abstract:

    We consider a manufacturer who has private information about product quality but the strategic customers who arrive in the advance period are unknown the quality information, the manufacturer could influence consumers' judgment of product quality and chosen of purchasing time through different advance selling strategies and prices. Based on the signaling game theory, we construct the game models when quality information is symmetric and asymmetric, and get the existence conditions of separating equilibrium and pooling equilibrium. We find that the option advance selling strategy is an effective tool to signal product quality when manufacturer's capacity is larger, and the high product quality manufacturer tries to hide its quality information by pooling equilibrium when the prior probability about high product quality of customers is high enough, otherwise the manufacturer will reveal its quality information though higher option execution price and separating equilibrium. Finally, we further discuss the influence of the waiting cost of customers who purchase in the advance selling period, and it is found that preceding conclusions still hold when the waiting cost is relatively low.

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孙忠锋,计国君,Kim Hua Tan,等.产品质量信息不对称时基于信号博弈的期权预售策略[J].控制与决策,2023,38(7):2009-2018

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  • 在线发布日期: 2023-06-27
  • 出版日期: 2023-07-20
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