Combinatorial auctions have found widespread application for allocating multiple items in the presence of complex bidder preferences. The enumerative exclusive OR (XOR) bid language is the de facto standard bid language for spectrum auctions and other applications, despite the difficulties, in larger auctions, of enumerating all the relevant packages or solving the resulting NP-hard winner determination problem. We introduce the flexible use and efficient licensing (FUEL) bid language, which was proposed for radio spectrum auctions to ease both communications and computations compared with XOR-based auctions. We model the resulting allocation problem as an integer program, discuss computational complexity, and conduct an extensive set of computational experiments, showing that the winner determination problem of the FUEL bid language can be solved reliably for large realistic-sized problem instances in less than half an hour on average. In contrast, auctions with an XOR bid language quickly become intractable even for much smaller problem sizes. We compare a sealed-bid FUEL auction to a sealed-bid auction with an XOR bid language and to a simultaneous clock auction. The sealed-bid auction with an XOR bid language incurs significant welfare losses because of the missing bids problem and computational hardness, the simultaneous clock auction leads to a substantially lower efficiency than FUEL because of the exposure problem. This paper was accepted by Axel Ockenfels.
{"title":"Taming the Communication and Computation Complexity of Combinatorial Auctions: The FUEL Bid Language","authors":"M. Bichler, Paul R. Milgrom, G. Schwarz","doi":"10.1287/mnsc.2022.4465","DOIUrl":"https://doi.org/10.1287/mnsc.2022.4465","url":null,"abstract":"Combinatorial auctions have found widespread application for allocating multiple items in the presence of complex bidder preferences. The enumerative exclusive OR (XOR) bid language is the de facto standard bid language for spectrum auctions and other applications, despite the difficulties, in larger auctions, of enumerating all the relevant packages or solving the resulting NP-hard winner determination problem. We introduce the flexible use and efficient licensing (FUEL) bid language, which was proposed for radio spectrum auctions to ease both communications and computations compared with XOR-based auctions. We model the resulting allocation problem as an integer program, discuss computational complexity, and conduct an extensive set of computational experiments, showing that the winner determination problem of the FUEL bid language can be solved reliably for large realistic-sized problem instances in less than half an hour on average. In contrast, auctions with an XOR bid language quickly become intractable even for much smaller problem sizes. We compare a sealed-bid FUEL auction to a sealed-bid auction with an XOR bid language and to a simultaneous clock auction. The sealed-bid auction with an XOR bid language incurs significant welfare losses because of the missing bids problem and computational hardness, the simultaneous clock auction leads to a substantially lower efficiency than FUEL because of the exposure problem. This paper was accepted by Axel Ockenfels.","PeriodicalId":18208,"journal":{"name":"Manag. Sci.","volume":"25 1","pages":"2217-2238"},"PeriodicalIF":0.0,"publicationDate":"2022-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90440775","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}
To shed light on the factors that affect who speaks up in teams in the workplace, we study willingness to speak up after someone has raised an opinion. We call voicing disagreement overriding and study this behavior in a laboratory experiment where participants answer multiple choice questions in pairs. In a control treatment, participants interact anonymously. In a photo treatment, both participants see the photo of the person they are matched with at the beginning of the group task. Using a series of incentivized tasks, we elicit beliefs about the likelihood that each possible answer option to a question is correct. This allows us to measure disagreement and to tease apart the role of disagreement versus preferences in the decision to override ideas in teams. Results show that anonymity increases overriding. This treatment effect is driven by social image costs. Analysis of heterogeneity in behavior by gender reveals no differences between the likelihood that men and women override. However, we find some evidence that men and women are treated differently; when participants disagree with their partner, they are more likely to override a woman than a man. Preferences seem to in part explain the differential treatment of men and women. Studying group performance, we find that overriding helps groups on average, while the gender composition of teams does not affect team performance. This paper was accepted by Yan Chen, behavioral economics and decision analysis.
{"title":"Overriding in Teams: The Role of Beliefs, Social Image, and Gender","authors":"Joy Guo, María P. Recalde","doi":"10.1287/mnsc.2022.4434","DOIUrl":"https://doi.org/10.1287/mnsc.2022.4434","url":null,"abstract":"To shed light on the factors that affect who speaks up in teams in the workplace, we study willingness to speak up after someone has raised an opinion. We call voicing disagreement overriding and study this behavior in a laboratory experiment where participants answer multiple choice questions in pairs. In a control treatment, participants interact anonymously. In a photo treatment, both participants see the photo of the person they are matched with at the beginning of the group task. Using a series of incentivized tasks, we elicit beliefs about the likelihood that each possible answer option to a question is correct. This allows us to measure disagreement and to tease apart the role of disagreement versus preferences in the decision to override ideas in teams. Results show that anonymity increases overriding. This treatment effect is driven by social image costs. Analysis of heterogeneity in behavior by gender reveals no differences between the likelihood that men and women override. However, we find some evidence that men and women are treated differently; when participants disagree with their partner, they are more likely to override a woman than a man. Preferences seem to in part explain the differential treatment of men and women. Studying group performance, we find that overriding helps groups on average, while the gender composition of teams does not affect team performance. This paper was accepted by Yan Chen, behavioral economics and decision analysis.","PeriodicalId":18208,"journal":{"name":"Manag. Sci.","volume":"38 1","pages":"2239-2262"},"PeriodicalIF":0.0,"publicationDate":"2022-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89244974","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}
Laura Alfaro, Ester Faia, Nora Lamersdorf, Farzad Saidi
Social preferences facilitate the internalization of health externalities, for example, by reducing mobility during a pandemic. We test this hypothesis using mobility data from 258 cities worldwide alongside experimentally validated measures of social preferences. Controlling for time-varying heterogeneity that could arise at the level at which mitigation policies are implemented, we find that they matter less in regions that are more altruistic, patient, or exhibit less negative reciprocity. In those regions, mobility falls ahead of lockdowns, and remains low after the lifting thereof. Our results elucidate the importance, independent of the cultural context, of social preferences in fostering cooperative behavior. This paper was accepted by Yan Chen, behavioral economics and decision analysis.
{"title":"Health Externalities and Policy: The Role of Social Preferences","authors":"Laura Alfaro, Ester Faia, Nora Lamersdorf, Farzad Saidi","doi":"10.1287/mnsc.2022.4461","DOIUrl":"https://doi.org/10.1287/mnsc.2022.4461","url":null,"abstract":"Social preferences facilitate the internalization of health externalities, for example, by reducing mobility during a pandemic. We test this hypothesis using mobility data from 258 cities worldwide alongside experimentally validated measures of social preferences. Controlling for time-varying heterogeneity that could arise at the level at which mitigation policies are implemented, we find that they matter less in regions that are more altruistic, patient, or exhibit less negative reciprocity. In those regions, mobility falls ahead of lockdowns, and remains low after the lifting thereof. Our results elucidate the importance, independent of the cultural context, of social preferences in fostering cooperative behavior. This paper was accepted by Yan Chen, behavioral economics and decision analysis.","PeriodicalId":18208,"journal":{"name":"Manag. Sci.","volume":"18 1","pages":"6751-6761"},"PeriodicalIF":0.0,"publicationDate":"2022-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81746000","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}
The growing adoption of virtual queues in the service and retail industries has been greatly accelerated in recent times. In collaboration with a major ride-sharing platform, we study how the wait time information (WTI), both its initial magnitude and its subsequent progress over time, impacts customers’ abandonment behavior in virtual queues. The study was conducted through a randomized field experiment that included 1,425,745 rides: one-third of the rides received a neutral WTI, one-third received an optimistic WTI shorter than the neutral WTI (hence less frequent updates), and one-third received a pessimistic WTI (hence more frequent updates). The underlying wait time did not vary across the three groups. We find that both the magnitude of the initial WTI and the update frequency of the WTI have a significant impact on customer abandonment. Specifically, when adjusting the initial WTI by one minute, it did not impact customer abandonment. This is because the magnitude effect of the initial WTI is cancelled out by the opposite update-frequency effect. However, when adjusting the WTI by more than one minute, the magnitude effect dominates: when comparing the pessimistic WTI of four minutes with the neutral initial WTI of two minutes, five minutes with three minutes, and eight minutes with five minutes, customers’ likelihood to abandon increases by 6.2%, 14.1%, and 19.6%, respectively. Similar but opposite effects are found when comparing the optimistic WTI with the neutral WTI. We discuss how firms can use our findings and insights to design and operate better virtual queues. This paper was accepted by Vishal Gaur, operations management.
{"title":"Delay Information in Virtual Queues: A Large-Scale Field Experiment on a Major Ride-Sharing Platform","authors":"Qiuping Yu, Yiming Zhang, Yong-Pin Zhou","doi":"10.1287/mnsc.2022.4448","DOIUrl":"https://doi.org/10.1287/mnsc.2022.4448","url":null,"abstract":"The growing adoption of virtual queues in the service and retail industries has been greatly accelerated in recent times. In collaboration with a major ride-sharing platform, we study how the wait time information (WTI), both its initial magnitude and its subsequent progress over time, impacts customers’ abandonment behavior in virtual queues. The study was conducted through a randomized field experiment that included 1,425,745 rides: one-third of the rides received a neutral WTI, one-third received an optimistic WTI shorter than the neutral WTI (hence less frequent updates), and one-third received a pessimistic WTI (hence more frequent updates). The underlying wait time did not vary across the three groups. We find that both the magnitude of the initial WTI and the update frequency of the WTI have a significant impact on customer abandonment. Specifically, when adjusting the initial WTI by one minute, it did not impact customer abandonment. This is because the magnitude effect of the initial WTI is cancelled out by the opposite update-frequency effect. However, when adjusting the WTI by more than one minute, the magnitude effect dominates: when comparing the pessimistic WTI of four minutes with the neutral initial WTI of two minutes, five minutes with three minutes, and eight minutes with five minutes, customers’ likelihood to abandon increases by 6.2%, 14.1%, and 19.6%, respectively. Similar but opposite effects are found when comparing the optimistic WTI with the neutral WTI. We discuss how firms can use our findings and insights to design and operate better virtual queues. This paper was accepted by Vishal Gaur, operations management.","PeriodicalId":18208,"journal":{"name":"Manag. Sci.","volume":"16 1","pages":"5745-5757"},"PeriodicalIF":0.0,"publicationDate":"2022-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72652998","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}
The rapid, widespread adoption of cloud computing over the last decade has sparked debates on its environmental impacts. Given that cloud computing alters the dynamics of energy consumption between service providers and users, a complete understanding of the environmental impacts of cloud computing requires an investigation of its impact on the user side, which can be weighed against its impact on the vendor side. Drawing on production theory and using a stochastic frontier analysis, this study examines the impact of cloud computing on users’ energy efficiency. To this end, we develop a novel industry-level measure of cloud computing based on cloud-based information technology (IT) services. Using U.S. economy-wide data from 57 industries during 1997–2017, our findings suggest that cloud-based IT services improve users’ energy efficiency. This effect is found to be significant only after 2006, when cloud computing started to be commercialized, and becomes even stronger after 2010. Moreover, we find heterogeneous impacts of cloud computing, depending on the cloud service models, energy types, and internal IT hardware intensity, which jointly assist in teasing out the underlying mechanisms. Although software-as-a-service (SaaS) is significantly associated with both electric and nonelectric energy efficiency improvement across all industries, infrastructure-as-a-service (IaaS) is positively associated only with electric energy efficiency for industries with high IT hardware intensity. To illuminate the mechanisms more clearly, we conduct a firm-level survey analysis, which demonstrates that SaaS confers operational benefits by facilitating energy-efficient production, whereas the primary role of IaaS is to mitigate the energy consumption of internal IT equipment and infrastructure. According to our industry-level analysis, the total user-side energy cost savings from cloud computing in the overall U.S. economy are estimated to be USD 2.8–12.6 billion in 2017 alone, equivalent to a reduction in electricity use by 31.8–143.8 billion kilowatt-hours. This estimate exceeds the total energy expenditure in the cloud service vendor industries and is comparable to the total electricity consumption in U.S. data centers. This paper was accepted by Chris Forman, information systems.
{"title":"Green Cloud? An Empirical Analysis of Cloud Computing and Energy Efficiency","authors":"Jiyong Park, Kunsoo Han, Byungtae Lee","doi":"10.1287/mnsc.2022.4442","DOIUrl":"https://doi.org/10.1287/mnsc.2022.4442","url":null,"abstract":"The rapid, widespread adoption of cloud computing over the last decade has sparked debates on its environmental impacts. Given that cloud computing alters the dynamics of energy consumption between service providers and users, a complete understanding of the environmental impacts of cloud computing requires an investigation of its impact on the user side, which can be weighed against its impact on the vendor side. Drawing on production theory and using a stochastic frontier analysis, this study examines the impact of cloud computing on users’ energy efficiency. To this end, we develop a novel industry-level measure of cloud computing based on cloud-based information technology (IT) services. Using U.S. economy-wide data from 57 industries during 1997–2017, our findings suggest that cloud-based IT services improve users’ energy efficiency. This effect is found to be significant only after 2006, when cloud computing started to be commercialized, and becomes even stronger after 2010. Moreover, we find heterogeneous impacts of cloud computing, depending on the cloud service models, energy types, and internal IT hardware intensity, which jointly assist in teasing out the underlying mechanisms. Although software-as-a-service (SaaS) is significantly associated with both electric and nonelectric energy efficiency improvement across all industries, infrastructure-as-a-service (IaaS) is positively associated only with electric energy efficiency for industries with high IT hardware intensity. To illuminate the mechanisms more clearly, we conduct a firm-level survey analysis, which demonstrates that SaaS confers operational benefits by facilitating energy-efficient production, whereas the primary role of IaaS is to mitigate the energy consumption of internal IT equipment and infrastructure. According to our industry-level analysis, the total user-side energy cost savings from cloud computing in the overall U.S. economy are estimated to be USD 2.8–12.6 billion in 2017 alone, equivalent to a reduction in electricity use by 31.8–143.8 billion kilowatt-hours. This estimate exceeds the total energy expenditure in the cloud service vendor industries and is comparable to the total electricity consumption in U.S. data centers. This paper was accepted by Chris Forman, information systems.","PeriodicalId":18208,"journal":{"name":"Manag. Sci.","volume":"19 1","pages":"1639-1664"},"PeriodicalIF":0.0,"publicationDate":"2022-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74559585","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}
H. Bleichrodt, Rogier J. D. Potter van Loon, D. Prelec
This paper introduces the index [Formula: see text] as a measure of time inconsistency and vulnerability to self-control problems in the quasi-hyperbolic, beta-delta ([Formula: see text] discounting model. We provide a preference foundation for [Formula: see text] and, consequently, a revealed preference definition of failed self-control. The [Formula: see text] index is independent of utility and has an intuitive interpretation as the maximum number of future selves who can disagree with the current self with respect to uniform deviations from an intertemporal plan. The index is also computable for continuous discount functions after an appropriate mapping of functions onto the ([Formula: see text] family. The [Formula: see text] index thus provides a common yardstick for comparing temporal inconsistency across different functional forms. This paper was accepted by Manel Baucells, behavioral economics and decision analysis.
{"title":"Beta-Delta or Delta-Tau? A Reformulation of Quasi-Hyperbolic Discounting","authors":"H. Bleichrodt, Rogier J. D. Potter van Loon, D. Prelec","doi":"10.1287/mnsc.2022.4453","DOIUrl":"https://doi.org/10.1287/mnsc.2022.4453","url":null,"abstract":"This paper introduces the index [Formula: see text] as a measure of time inconsistency and vulnerability to self-control problems in the quasi-hyperbolic, beta-delta ([Formula: see text] discounting model. We provide a preference foundation for [Formula: see text] and, consequently, a revealed preference definition of failed self-control. The [Formula: see text] index is independent of utility and has an intuitive interpretation as the maximum number of future selves who can disagree with the current self with respect to uniform deviations from an intertemporal plan. The index is also computable for continuous discount functions after an appropriate mapping of functions onto the ([Formula: see text] family. The [Formula: see text] index thus provides a common yardstick for comparing temporal inconsistency across different functional forms. This paper was accepted by Manel Baucells, behavioral economics and decision analysis.","PeriodicalId":18208,"journal":{"name":"Manag. Sci.","volume":"106 1","pages":"6326-6335"},"PeriodicalIF":0.0,"publicationDate":"2022-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80679434","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 optimal contracting problem with subjective evaluation when the principal can ask the agent to revise his work. The possibility of revision benefits the principal by providing the option value of making another attempt at the work. However, it also introduces a new type of incentive problem for the principal: she may ask for revision even if it is inefficient to do so. This new incentive issue for the principal also affects the incentive of the agent: he may procrastinate his effort in anticipation of excessive revision. This results in a trilemma: The optimal contract cannot simultaneously provide for efficient revision, efficient effort, and minimal ex post surplus destruction. The optimal contract will of necessity contain at least one of the following problems: revision, the principal asks for excessive revision; procrastination, the agent shirks in the early stage; or punishment, excessive surplus destruction at low-quality final output. This paper was accepted by Joshua Gans, business strategy.
{"title":"Optimal Subjective Contracting with Revision","authors":"Xinhao He, Jin Li, Zhaoneng Yuan","doi":"10.1287/mnsc.2022.4418","DOIUrl":"https://doi.org/10.1287/mnsc.2022.4418","url":null,"abstract":"We study the optimal contracting problem with subjective evaluation when the principal can ask the agent to revise his work. The possibility of revision benefits the principal by providing the option value of making another attempt at the work. However, it also introduces a new type of incentive problem for the principal: she may ask for revision even if it is inefficient to do so. This new incentive issue for the principal also affects the incentive of the agent: he may procrastinate his effort in anticipation of excessive revision. This results in a trilemma: The optimal contract cannot simultaneously provide for efficient revision, efficient effort, and minimal ex post surplus destruction. The optimal contract will of necessity contain at least one of the following problems: revision, the principal asks for excessive revision; procrastination, the agent shirks in the early stage; or punishment, excessive surplus destruction at low-quality final output. This paper was accepted by Joshua Gans, business strategy.","PeriodicalId":18208,"journal":{"name":"Manag. Sci.","volume":"1 1","pages":"6346-6354"},"PeriodicalIF":0.0,"publicationDate":"2022-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89164088","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 studies outcomes of the deferred acceptance algorithm in large random matching markets where priorities are generated either by a single lottery or by independent lotteries. In contrast to prior work, my model permits students to submit lists of varying lengths and schools to vary in their popularity and number of seats. In a limiting regime where the number of students and schools grow while the length of student lists and number of seats at each school remain bounded, I provide exact expressions for the number of students who list l schools and match to one of their top k choices, for each [Formula: see text]. These expressions provide three main insights. First, there is a persistent tradeoff between using a single lottery and independent lotteries. For students who submit short lists, the rank distribution under a single lottery stochastically dominates the corresponding distribution under independent lotteries. However, the students who submit the longest lists are always more likely to match when schools use independent lotteries. Second, I compare the total number of matches in the two lottery systems, and find that the shape of the list length distribution plays a key role. If this distribution has an increasing hazard rate, then independent lotteries match more students. If it has a decreasing hazard rate, the comparison reverses. To my knowledge, this is the first analytical result comparing the size of stable matchings under different priority rules. Finally, I study the fraction of assigned students who receive their first choice. Under independent lotteries, this fraction may be arbitrarily small, even if schools are equally popular. Under a single lottery, we provide a tight lower bound on this fraction which depends on the ratio r of the popularity of the most to least popular school. When each school has a single seat, the fraction of assigned students who receive their first choice is at least [Formula: see text]. This guarantee increases to [Formula: see text] as the number of seats at each school increases. This paper was accepted by Gabriel Weintraub, revenue management and market analytics.
{"title":"Lottery Design for School Choice","authors":"N. Arnosti","doi":"10.1287/mnsc.2022.4338","DOIUrl":"https://doi.org/10.1287/mnsc.2022.4338","url":null,"abstract":"This paper studies outcomes of the deferred acceptance algorithm in large random matching markets where priorities are generated either by a single lottery or by independent lotteries. In contrast to prior work, my model permits students to submit lists of varying lengths and schools to vary in their popularity and number of seats. In a limiting regime where the number of students and schools grow while the length of student lists and number of seats at each school remain bounded, I provide exact expressions for the number of students who list l schools and match to one of their top k choices, for each [Formula: see text]. These expressions provide three main insights. First, there is a persistent tradeoff between using a single lottery and independent lotteries. For students who submit short lists, the rank distribution under a single lottery stochastically dominates the corresponding distribution under independent lotteries. However, the students who submit the longest lists are always more likely to match when schools use independent lotteries. Second, I compare the total number of matches in the two lottery systems, and find that the shape of the list length distribution plays a key role. If this distribution has an increasing hazard rate, then independent lotteries match more students. If it has a decreasing hazard rate, the comparison reverses. To my knowledge, this is the first analytical result comparing the size of stable matchings under different priority rules. Finally, I study the fraction of assigned students who receive their first choice. Under independent lotteries, this fraction may be arbitrarily small, even if schools are equally popular. Under a single lottery, we provide a tight lower bound on this fraction which depends on the ratio r of the popularity of the most to least popular school. When each school has a single seat, the fraction of assigned students who receive their first choice is at least [Formula: see text]. This guarantee increases to [Formula: see text] as the number of seats at each school increases. This paper was accepted by Gabriel Weintraub, revenue management and market analytics.","PeriodicalId":18208,"journal":{"name":"Manag. Sci.","volume":"9 1","pages":"244-259"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87639325","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 investigate the causal effect of performance pay and conversations about performance in 224 stores of a retail chain implementing a field experiment with a 2x2 factorial design. In the performance pay treatments, managers receive a bonus, which is a simple linear function of the profits achieved above a threshold value. In the performance review treatments, managers have to report their activities undertaken to increase profits in regular meetings. We find that whereas performance pay did not yield significant profit increases, performance review conversations increased profits by about 7%. However, when additionally receiving performance pay, the positive effect of performance reviews vanished. We provide evidence from surveys and meeting protocols that performance pay changes the nature of conversations, leading to a stronger self-reliance of store managers, which undermines the value of the performance reviews. This paper was accepted by Yan Chen, behavioral economics and decision analysis.
{"title":"Talking About Performance or Paying for It? A Field Experiment on Performance Reviews and Incentives","authors":"Kathrin Manthei, Dirk Sliwka, Tim Vogelsang","doi":"10.1287/mnsc.2022.4431","DOIUrl":"https://doi.org/10.1287/mnsc.2022.4431","url":null,"abstract":"We investigate the causal effect of performance pay and conversations about performance in 224 stores of a retail chain implementing a field experiment with a 2x2 factorial design. In the performance pay treatments, managers receive a bonus, which is a simple linear function of the profits achieved above a threshold value. In the performance review treatments, managers have to report their activities undertaken to increase profits in regular meetings. We find that whereas performance pay did not yield significant profit increases, performance review conversations increased profits by about 7%. However, when additionally receiving performance pay, the positive effect of performance reviews vanished. We provide evidence from surveys and meeting protocols that performance pay changes the nature of conversations, leading to a stronger self-reliance of store managers, which undermines the value of the performance reviews. This paper was accepted by Yan Chen, behavioral economics and decision analysis.","PeriodicalId":18208,"journal":{"name":"Manag. Sci.","volume":"57 1","pages":"2198-2216"},"PeriodicalIF":0.0,"publicationDate":"2022-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81018514","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}
Zelin Zhang, Kejia Yang, Jonathan Z. Zhang, Robert W. Palmatier
Massive online text reviews can be a powerful market research tool for understanding consumer experiences and helping firms improve and innovate. This research exploits the rich semantic properties of text reviews and proposes a novel machine learning modeling framework that can reliably and efficiently extract consumer opinions and uncover potential interaction effects across these opinions, thereby identifying hidden and nuanced areas for product and service improvement beyond existing modeling approaches in this domain. In particular, we develop an opinion extraction and effect estimation framework that allows for uncovering customer opinions’ average effects and their interaction effects. Interactions among opinions can be synergistic when the co-occurrence of two opinions yields an effect greater than the sum of two parts, or as what we call dysergistic, when the co-occurrence of two opinions results in dampened effect. We apply the model in the context of large-scale customer ratings and text reviews for hotels and demonstrate our framework’s ability to screen synergy and dysergy effects among opinions. Our model also flexibly and efficiently accommodates a large number of opinions, which provides insights into rare yet potentially important opinions. The model can guide managers to prioritize joint areas of product and service improvement and innovation by uncovering the most prominent synergistic pairs. Model comparison with extant machine learning approaches demonstrates our improved predictive ability and managerial insights. This paper was accepted by Gui Liberali, marketing.
{"title":"Uncovering Synergy and Dysergy in Consumer Reviews: A Machine Learning Approach","authors":"Zelin Zhang, Kejia Yang, Jonathan Z. Zhang, Robert W. Palmatier","doi":"10.1287/mnsc.2022.4443","DOIUrl":"https://doi.org/10.1287/mnsc.2022.4443","url":null,"abstract":"Massive online text reviews can be a powerful market research tool for understanding consumer experiences and helping firms improve and innovate. This research exploits the rich semantic properties of text reviews and proposes a novel machine learning modeling framework that can reliably and efficiently extract consumer opinions and uncover potential interaction effects across these opinions, thereby identifying hidden and nuanced areas for product and service improvement beyond existing modeling approaches in this domain. In particular, we develop an opinion extraction and effect estimation framework that allows for uncovering customer opinions’ average effects and their interaction effects. Interactions among opinions can be synergistic when the co-occurrence of two opinions yields an effect greater than the sum of two parts, or as what we call dysergistic, when the co-occurrence of two opinions results in dampened effect. We apply the model in the context of large-scale customer ratings and text reviews for hotels and demonstrate our framework’s ability to screen synergy and dysergy effects among opinions. Our model also flexibly and efficiently accommodates a large number of opinions, which provides insights into rare yet potentially important opinions. The model can guide managers to prioritize joint areas of product and service improvement and innovation by uncovering the most prominent synergistic pairs. Model comparison with extant machine learning approaches demonstrates our improved predictive ability and managerial insights. This paper was accepted by Gui Liberali, marketing.","PeriodicalId":18208,"journal":{"name":"Manag. Sci.","volume":"98 1","pages":"2339-2360"},"PeriodicalIF":0.0,"publicationDate":"2022-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76124222","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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