Bargaining is an important pricing mechanism, prevalent in both online and offline markets. However, there is little empirical work documenting the costs and benefits of bargaining, primarily because of the lack of real-world bargaining data. We leverage rich, transaction-level bargaining data from a major online platform and supplement it with primary data to quantify the costs and benefits of bargaining for sellers, buyers, and the platform. We do this by building a structural model of buyer demand and seller pricing decisions while allowing for the existence of bargaining initiation cost, loss-of-face cost, and price discrimination. Using our results, we perform three policy simulations to quantify the importance of not distinguishing between no-bargain and failed-bargain transactions, ignoring the loss-of-face cost, and not allowing for bargaining. These simulations provide rich details on how the various costs of bargaining impact our understanding of buyer and seller behavior and transaction outcomes. Banning bargaining, in particular, benefits the buyer and the platform greatly but only has a modest benefit for sellers. Finally, we show that our results are robust to our assumptions and replicate in another product category.
{"title":"\"Meet Me Halfway\": The Costs and Benefits of Bargaining","authors":"Xu Zhang, Puneet Manchanda, Junhong Chu","doi":"10.1287/mksc.2021.1296","DOIUrl":"https://doi.org/10.1287/mksc.2021.1296","url":null,"abstract":"Bargaining is an important pricing mechanism, prevalent in both online and offline markets. However, there is little empirical work documenting the costs and benefits of bargaining, primarily because of the lack of real-world bargaining data. We leverage rich, transaction-level bargaining data from a major online platform and supplement it with primary data to quantify the costs and benefits of bargaining for sellers, buyers, and the platform. We do this by building a structural model of buyer demand and seller pricing decisions while allowing for the existence of bargaining initiation cost, loss-of-face cost, and price discrimination. Using our results, we perform three policy simulations to quantify the importance of not distinguishing between no-bargain and failed-bargain transactions, ignoring the loss-of-face cost, and not allowing for bargaining. These simulations provide rich details on how the various costs of bargaining impact our understanding of buyer and seller behavior and transaction outcomes. Banning bargaining, in particular, benefits the buyer and the platform greatly but only has a modest benefit for sellers. Finally, we show that our results are robust to our assumptions and replicate in another product category.","PeriodicalId":423558,"journal":{"name":"Mark. Sci.","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132116982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We study the impact of an increase in minimum wages on consumer perceptions of service quality in the restaurant industry.
我们研究了最低工资的增加对消费者对餐饮业服务质量的看法的影响。
{"title":"The Impact of Increase in Minimum Wages on Consumer Perceptions of Service: A Transformer Model of Online Restaurant Reviews","authors":"Dinesh Puranam, Vrinda Kadiyali, V. Narayan","doi":"10.1287/mksc.2021.1294","DOIUrl":"https://doi.org/10.1287/mksc.2021.1294","url":null,"abstract":"We study the impact of an increase in minimum wages on consumer perceptions of service quality in the restaurant industry.","PeriodicalId":423558,"journal":{"name":"Mark. Sci.","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124903249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In 1956, a group of trade associations representing publishers and independent advertising agencies signed a consent decree aimed at ending a set of trade practices that for half a century effectively precluded advertisers from owning and operating in-house agencies. Since then, large firms have internalized more and more of the services formerly performed by external agencies, perhaps as many as half. We use this phenomenon to test a theory of the firm, thereby simultaneously offering an explanation for it. The theory suggests that firms should internalize activities for which their competitive position implies (1) that it is more important for human capital to be firm specific as opposed to function specific and (2) that frequent modifications are desirable. It also predicts (3) that these two effects reinforce each other. This is the first paper to report on a test of the specialization hypothesis, and we find that it is robustly significant in a cross-sectional data set covering nine different agency activities in 79 firms. In addition to the cross-sectional test, we informally present some time-series data suggesting that both specialization and frequency have grown over time along with the level of internalization.
{"title":"Internalization of Advertising Services: Testing a Theory of the Firm","authors":"B. Wernerfelt, A. Silk, Shuyi Yu","doi":"10.1287/mksc.2021.1290","DOIUrl":"https://doi.org/10.1287/mksc.2021.1290","url":null,"abstract":"In 1956, a group of trade associations representing publishers and independent advertising agencies signed a consent decree aimed at ending a set of trade practices that for half a century effectively precluded advertisers from owning and operating in-house agencies. Since then, large firms have internalized more and more of the services formerly performed by external agencies, perhaps as many as half. We use this phenomenon to test a theory of the firm, thereby simultaneously offering an explanation for it. The theory suggests that firms should internalize activities for which their competitive position implies (1) that it is more important for human capital to be firm specific as opposed to function specific and (2) that frequent modifications are desirable. It also predicts (3) that these two effects reinforce each other. This is the first paper to report on a test of the specialization hypothesis, and we find that it is robustly significant in a cross-sectional data set covering nine different agency activities in 79 firms. In addition to the cross-sectional test, we informally present some time-series data suggesting that both specialization and frequency have grown over time along with the level of internalization.","PeriodicalId":423558,"journal":{"name":"Mark. Sci.","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129378926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Shunyuan Zhang, Nitin Mehta, P. Singh, K. Srinivasan
We study the effect of Airbnb’s smart-pricing algorithm on the racial disparity in the daily revenue earned by Airbnb hosts. Our empirical strategy exploits Airbnb’s introduction of the algorithm and its voluntary adoption by hosts as a quasinatural experiment. Among those who adopted the algorithm, the average nightly rate decreased by 5.7%, but average daily revenue increased by 8.6%. Before Airbnb introduced the algorithm, White hosts earned $12.16 more in daily revenue than Black hosts, controlling for observed characteristics of the hosts, properties, and locations. Conditional on its adoption, the revenue gap between White and Black hosts decreased by 71.3%. However, Black hosts were significantly less likely than White hosts to adopt the algorithm, so at the population level, the revenue gap increased after the introduction of the algorithm. We show that the algorithm’s price recommendations are not affected by the host’s race—but we argue that the algorithm’s race blindness may lead to pricing that is suboptimal and more so for Black hosts than for White hosts. We also show that the algorithm’s effectiveness at mitigating the Airbnb revenue gap is limited by the low rate of algorithm adoption among Black hosts. We offer recommendations with which policy makers and Airbnb may advance smart-pricing algorithms in mitigating racial economic disparities.
{"title":"Frontiers: Can an Artificial Intelligence Algorithm Mitigate Racial Economic Inequality? An Analysis in the Context of Airbnb","authors":"Shunyuan Zhang, Nitin Mehta, P. Singh, K. Srinivasan","doi":"10.1287/mksc.2021.1295","DOIUrl":"https://doi.org/10.1287/mksc.2021.1295","url":null,"abstract":"We study the effect of Airbnb’s smart-pricing algorithm on the racial disparity in the daily revenue earned by Airbnb hosts. Our empirical strategy exploits Airbnb’s introduction of the algorithm and its voluntary adoption by hosts as a quasinatural experiment. Among those who adopted the algorithm, the average nightly rate decreased by 5.7%, but average daily revenue increased by 8.6%. Before Airbnb introduced the algorithm, White hosts earned $12.16 more in daily revenue than Black hosts, controlling for observed characteristics of the hosts, properties, and locations. Conditional on its adoption, the revenue gap between White and Black hosts decreased by 71.3%. However, Black hosts were significantly less likely than White hosts to adopt the algorithm, so at the population level, the revenue gap increased after the introduction of the algorithm. We show that the algorithm’s price recommendations are not affected by the host’s race—but we argue that the algorithm’s race blindness may lead to pricing that is suboptimal and more so for Black hosts than for White hosts. We also show that the algorithm’s effectiveness at mitigating the Airbnb revenue gap is limited by the low rate of algorithm adoption among Black hosts. We offer recommendations with which policy makers and Airbnb may advance smart-pricing algorithms in mitigating racial economic disparities.","PeriodicalId":423558,"journal":{"name":"Mark. Sci.","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126766405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper develops a learning model to describe decision makers' exploration/exploitation trade-offs and their link to psychometric traits.
本文开发了一个学习模型来描述决策者的探索/利用权衡及其与心理测量特征的联系。
{"title":"Understanding Managers' Trade-Offs Between Exploration and Exploitation","authors":"Alina Ferecatu, A. D. Bruyn","doi":"10.2139/ssrn.3832662","DOIUrl":"https://doi.org/10.2139/ssrn.3832662","url":null,"abstract":"This paper develops a learning model to describe decision makers' exploration/exploitation trade-offs and their link to psychometric traits.","PeriodicalId":423558,"journal":{"name":"Mark. Sci.","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121909594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In a dual channel, the manufacturer's low-price guarantee facilitates price discrimination and channel coordination and the manufacturer may choose price-beating, price-matching, or no guarantee.
在双渠道中，制造商的低价保证有利于价格歧视和渠道协调，制造商可以选择打价、配价或不保证。
{"title":"Low-Price Guarantees in a Dual Channel of Distribution","authors":"Juncai Jiang, Chuan He","doi":"10.1287/MKSC.2020.1272","DOIUrl":"https://doi.org/10.1287/MKSC.2020.1272","url":null,"abstract":"In a dual channel, the manufacturer's low-price guarantee facilitates price discrimination and channel coordination and the manufacturer may choose price-beating, price-matching, or no guarantee.","PeriodicalId":423558,"journal":{"name":"Mark. Sci.","volume":"123 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127045653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Observational study and field experiments show that some consumers will pay more for products advertising themselves as American made but just a little.
观察性研究和实地实验表明，一些消费者愿意为标榜自己是美国制造的产品支付更多的钱，但只是支付一点点。
{"title":"Do \"Made in USA\" Claims Matter?","authors":"Xinyao Kong, A. Rao","doi":"10.1287/MKSC.2020.1274","DOIUrl":"https://doi.org/10.1287/MKSC.2020.1274","url":null,"abstract":"Observational study and field experiments show that some consumers will pay more for products advertising themselves as American made but just a little.","PeriodicalId":423558,"journal":{"name":"Mark. Sci.","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129357718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Dominic Coey, B. Larsen, Kane Sweeney, Caio Waisman
This paper provides a set of tools to compute and implement optimal reserve prices for online auctions.
本文提供了一套计算和实现在线拍卖最优保留价格的工具。
{"title":"Scalable Optimal Online Auctions","authors":"Dominic Coey, B. Larsen, Kane Sweeney, Caio Waisman","doi":"10.1287/MKSC.2021.1283","DOIUrl":"https://doi.org/10.1287/MKSC.2021.1283","url":null,"abstract":"This paper provides a set of tools to compute and implement optimal reserve prices for online auctions.","PeriodicalId":423558,"journal":{"name":"Mark. Sci.","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131314320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper analyzes the build-test-learn cycle of the lean start-up method (LSM) using an analytical model to understand its microfoundation and how best to implement it.
{"title":"A Theoretical Analysis of the Lean Start-up Method","authors":"Onesun Steve Yoo, Tingliang Huang, K. Arifoğlu","doi":"10.1287/MKSC.2020.1269","DOIUrl":"https://doi.org/10.1287/MKSC.2020.1269","url":null,"abstract":"This paper analyzes the build-test-learn cycle of the lean start-up method (LSM) using an analytical model to understand its microfoundation and how best to implement it.","PeriodicalId":423558,"journal":{"name":"Mark. Sci.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124413587","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jia et al. study the effects of the General Data Protection Regulation on technology venture investment in the European Union.
Jia等人研究了欧盟《通用数据保护条例》对技术风险投资的影响。
{"title":"The Short-Run Effects of the General Data Protection Regulation on Technology Venture Investment","authors":"Jian Jia, G. Jin, Liad Wagman","doi":"10.1287/MKSC.2020.1271","DOIUrl":"https://doi.org/10.1287/MKSC.2020.1271","url":null,"abstract":"Jia et al. study the effects of the General Data Protection Regulation on technology venture investment in the European Union.","PeriodicalId":423558,"journal":{"name":"Mark. Sci.","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126778689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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