{"title":"基于社会互动的定价决策:一个博弈论模型","authors":"Xiaofang Wang, Yaoyao Yang, Jun Zhuang","doi":"10.1287/deca.2022.0463","DOIUrl":null,"url":null,"abstract":"For media or digital products with quality uncertainty like online games, movies, theater plays, software, and smartphone applications, online customers may strategically delay their purchase waiting for online reviews and their peers’ purchase decisions. Thus, a firm needs to consider both social learning and positive network externality to anticipate the customers’ purchasing decisions and set a good pricing strategy over time. This paper investigates how these dual concerns affect the strategic interaction between a firm using preannounced pricing or responsive pricing and strategic customers in a two-period game-theoretic model. Deviating from conventional wisdom suggesting that social learning and externality work in a similar way, our results highlight their differences and provide valuable managerial insights. Although social learning and externality play a similar role in expanding the increasing-price-optimal region, they are different in other aspects: The firm will be worse off with learning if the externality gets stronger, whereas it will be worse off or better off with learning if learning gets stronger. In addition, we characterize the condition under which responsive pricing may outperform preannounced pricing. We further find that the firm’s discount factor has an influence on the firm’s pricing strategy selection. Funding: X. Wang and Y. Yang acknowledge financial support from the National Natural Science Foundation of China [Grant 72071204]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/deca.2022.0463 .","PeriodicalId":46460,"journal":{"name":"Decision Analysis","volume":null,"pages":null},"PeriodicalIF":2.5000,"publicationDate":"2022-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Pricing Decisions with Social Interactions: A Game-Theoretic Model\",\"authors\":\"Xiaofang Wang, Yaoyao Yang, Jun Zhuang\",\"doi\":\"10.1287/deca.2022.0463\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"For media or digital products with quality uncertainty like online games, movies, theater plays, software, and smartphone applications, online customers may strategically delay their purchase waiting for online reviews and their peers’ purchase decisions. Thus, a firm needs to consider both social learning and positive network externality to anticipate the customers’ purchasing decisions and set a good pricing strategy over time. This paper investigates how these dual concerns affect the strategic interaction between a firm using preannounced pricing or responsive pricing and strategic customers in a two-period game-theoretic model. Deviating from conventional wisdom suggesting that social learning and externality work in a similar way, our results highlight their differences and provide valuable managerial insights. Although social learning and externality play a similar role in expanding the increasing-price-optimal region, they are different in other aspects: The firm will be worse off with learning if the externality gets stronger, whereas it will be worse off or better off with learning if learning gets stronger. In addition, we characterize the condition under which responsive pricing may outperform preannounced pricing. We further find that the firm’s discount factor has an influence on the firm’s pricing strategy selection. Funding: X. Wang and Y. Yang acknowledge financial support from the National Natural Science Foundation of China [Grant 72071204]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/deca.2022.0463 .\",\"PeriodicalId\":46460,\"journal\":{\"name\":\"Decision Analysis\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2022-11-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Decision Analysis\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://doi.org/10.1287/deca.2022.0463\",\"RegionNum\":4,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MANAGEMENT\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Decision Analysis","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1287/deca.2022.0463","RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MANAGEMENT","Score":null,"Total":0}
Pricing Decisions with Social Interactions: A Game-Theoretic Model
For media or digital products with quality uncertainty like online games, movies, theater plays, software, and smartphone applications, online customers may strategically delay their purchase waiting for online reviews and their peers’ purchase decisions. Thus, a firm needs to consider both social learning and positive network externality to anticipate the customers’ purchasing decisions and set a good pricing strategy over time. This paper investigates how these dual concerns affect the strategic interaction between a firm using preannounced pricing or responsive pricing and strategic customers in a two-period game-theoretic model. Deviating from conventional wisdom suggesting that social learning and externality work in a similar way, our results highlight their differences and provide valuable managerial insights. Although social learning and externality play a similar role in expanding the increasing-price-optimal region, they are different in other aspects: The firm will be worse off with learning if the externality gets stronger, whereas it will be worse off or better off with learning if learning gets stronger. In addition, we characterize the condition under which responsive pricing may outperform preannounced pricing. We further find that the firm’s discount factor has an influence on the firm’s pricing strategy selection. Funding: X. Wang and Y. Yang acknowledge financial support from the National Natural Science Foundation of China [Grant 72071204]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/deca.2022.0463 .