We propose a two-step machine learning algorithm—the Supervised Adaptive Group LASSO (SAGLasso) method—that is suitable for constructing parsimonious return predictors from a large set of macro variables. We apply this method to government bonds and a set of 917 macro variables and construct a new, transparent, and easy-to-interpret macro variable with significant out-of-sample predictive power for excess bond returns. This new macro factor, termed the SAGLasso factor, is a linear combination of merely 30 selected macro variables out of 917. Furthermore, it can be decomposed into three sublevel factors: a novel housing factor, an employment factor, and an inflation factor. Importantly, the predictive power of the SAGLasso factor is robust to bond yields, namely, the SAGLasso factor is not spanned by bond yields. Moreover, we show that the unspanned variation of the SAGLasso factor cannot be attributed to yield measurement error or macro measurement error. The SAGLasso factor therefore provides a potential resolution to the spanning controversy in the macro-finance literature. This paper was accepted by Haoxiang Zhu, finance.
{"title":"Machine-Learning-Based Return Predictors and the Spanning Controversy in Macro-Finance","authors":"Jing-Zhi Huang, Zhan Shi","doi":"10.1287/mnsc.2022.4386","DOIUrl":"https://doi.org/10.1287/mnsc.2022.4386","url":null,"abstract":"We propose a two-step machine learning algorithm—the Supervised Adaptive Group LASSO (SAGLasso) method—that is suitable for constructing parsimonious return predictors from a large set of macro variables. We apply this method to government bonds and a set of 917 macro variables and construct a new, transparent, and easy-to-interpret macro variable with significant out-of-sample predictive power for excess bond returns. This new macro factor, termed the SAGLasso factor, is a linear combination of merely 30 selected macro variables out of 917. Furthermore, it can be decomposed into three sublevel factors: a novel housing factor, an employment factor, and an inflation factor. Importantly, the predictive power of the SAGLasso factor is robust to bond yields, namely, the SAGLasso factor is not spanned by bond yields. Moreover, we show that the unspanned variation of the SAGLasso factor cannot be attributed to yield measurement error or macro measurement error. The SAGLasso factor therefore provides a potential resolution to the spanning controversy in the macro-finance literature. This paper was accepted by Haoxiang Zhu, finance.","PeriodicalId":18208,"journal":{"name":"Manag. Sci.","volume":"71 1","pages":"1780-1804"},"PeriodicalIF":0.0,"publicationDate":"2022-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91395868","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}
When drawing inferences about a person’s personal characteristics from the person’s actions, “correspondence bias” is the tendency to overestimate the influence of those characteristics and underestimate the influence of situational factors, such as incentives the individual faces. We build a simple framework to formalize correspondence bias and test its predictions in an online experiment. Consistent with correspondence bias, subjects are, on average, willing to pay to receive the dictator-game givings of an individual with whom they are randomly assigned to play a game that encourages cooperation rather than one with whom they play a game that encourages selfish behavior. We show, further, that experiencing both games oneself, as opposed to playing one and observing the other, reduces the bias, and receiving information about how each of the players behaved in both games eliminates it. This paper was accepted by Yan Chen, behavioral economics and decision analysis.
{"title":"Confusing Context with Character: Correspondence Bias in Economic Interactions","authors":"Yi-Hsing Han, Yiming Liu, G. Loewenstein","doi":"10.1287/mnsc.2022.4384","DOIUrl":"https://doi.org/10.1287/mnsc.2022.4384","url":null,"abstract":"When drawing inferences about a person’s personal characteristics from the person’s actions, “correspondence bias” is the tendency to overestimate the influence of those characteristics and underestimate the influence of situational factors, such as incentives the individual faces. We build a simple framework to formalize correspondence bias and test its predictions in an online experiment. Consistent with correspondence bias, subjects are, on average, willing to pay to receive the dictator-game givings of an individual with whom they are randomly assigned to play a game that encourages cooperation rather than one with whom they play a game that encourages selfish behavior. We show, further, that experiencing both games oneself, as opposed to playing one and observing the other, reduces the bias, and receiving information about how each of the players behaved in both games eliminates it. This paper was accepted by Yan Chen, behavioral economics and decision analysis.","PeriodicalId":18208,"journal":{"name":"Manag. Sci.","volume":"27 1","pages":"1070-1091"},"PeriodicalIF":0.0,"publicationDate":"2022-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83739071","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}
A large experimental literature is devoted to studying discrimination. An important question for policymakers and firms is what drives the discrimination uncovered by those experiments. However, motivations are hard to determine when decision makers pay selective attention to information because their learning is private. We overcome this challenge by deriving conditions on average outcomes that reveal decision makers are prejudiced no matter what they learn about individuals in each demographic group before making their decisions. This provides a test of prejudice that is general, simple, and robust and that can potentially be used to identify prejudice in a wide range of important settings, such as hiring, consumer lending, and housing access. We demonstrate our test of prejudice using two influential labor market experiments. This paper was accepted by Yan Chen, decision science.
{"title":"A Robust Test of Prejudice for Discrimination Experiments","authors":"Daniel Martín, P. Marx","doi":"10.1287/mnsc.2022.4396","DOIUrl":"https://doi.org/10.1287/mnsc.2022.4396","url":null,"abstract":"A large experimental literature is devoted to studying discrimination. An important question for policymakers and firms is what drives the discrimination uncovered by those experiments. However, motivations are hard to determine when decision makers pay selective attention to information because their learning is private. We overcome this challenge by deriving conditions on average outcomes that reveal decision makers are prejudiced no matter what they learn about individuals in each demographic group before making their decisions. This provides a test of prejudice that is general, simple, and robust and that can potentially be used to identify prejudice in a wide range of important settings, such as hiring, consumer lending, and housing access. We demonstrate our test of prejudice using two influential labor market experiments. This paper was accepted by Yan Chen, decision science.","PeriodicalId":18208,"journal":{"name":"Manag. Sci.","volume":"10 1 1","pages":"4527-4536"},"PeriodicalIF":0.0,"publicationDate":"2022-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78586851","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 strength of weak ties and brokerage theory both rely on the argument that weak bridging ties deliver novel information to create “vision advantages” for actors in brokerage positions. However, our conceptualization of novelty is itself fundamentally underdeveloped. We, therefore, develop a theory of how three distinct types of novelty—diversity, non-redundancy, and uniqueness—combine with network structure to create vision advantages in social networks. We test this theory using panel data on an evolving corporate email network. Three main results emerge from our analysis. First, we confirm the diversity-bandwidth tradeoff (DBT) at the heart of the vision advantage. As brokers’ networks become more diverse, their channel bandwidth contracts, creating countervailing effects on access to novel information. Second, we uncover a mechanism driving the DBT, which helps explain differences in vision advantages across strong and weak ties. Strong, cohesive ties deliver greater information diversity and non-redundancy, whereas weak bridging ties contribute the most unique information (the information that is most different from what other contacts deliver). Third, we find network diversity (in contrast to network constraint) to be positively associated with longitudinal entropy, a measure of the accumulation of novel information over time. This suggests that weak bridging ties, which provide the most unique information through low bandwidth, structurally diverse channels, contribute the most to one’s aggregation of novel information over time. Collectively, these results take a step toward resolving a long-standing debate in network theory about whether strong, cohesive networks or weak bridging networks contribute more to vision advantages. This work firmly establishes that it depends. This paper was accepted by Kartik Hosanagar, information systems.
{"title":"What (Exactly) Is Novelty in Networks? Unpacking the Vision Advantages of Brokers, Bridges, and Weak Ties","authors":"Sinan Aral, Paramveer S. Dhillon","doi":"10.1287/mnsc.2022.4377","DOIUrl":"https://doi.org/10.1287/mnsc.2022.4377","url":null,"abstract":"The strength of weak ties and brokerage theory both rely on the argument that weak bridging ties deliver novel information to create “vision advantages” for actors in brokerage positions. However, our conceptualization of novelty is itself fundamentally underdeveloped. We, therefore, develop a theory of how three distinct types of novelty—diversity, non-redundancy, and uniqueness—combine with network structure to create vision advantages in social networks. We test this theory using panel data on an evolving corporate email network. Three main results emerge from our analysis. First, we confirm the diversity-bandwidth tradeoff (DBT) at the heart of the vision advantage. As brokers’ networks become more diverse, their channel bandwidth contracts, creating countervailing effects on access to novel information. Second, we uncover a mechanism driving the DBT, which helps explain differences in vision advantages across strong and weak ties. Strong, cohesive ties deliver greater information diversity and non-redundancy, whereas weak bridging ties contribute the most unique information (the information that is most different from what other contacts deliver). Third, we find network diversity (in contrast to network constraint) to be positively associated with longitudinal entropy, a measure of the accumulation of novel information over time. This suggests that weak bridging ties, which provide the most unique information through low bandwidth, structurally diverse channels, contribute the most to one’s aggregation of novel information over time. Collectively, these results take a step toward resolving a long-standing debate in network theory about whether strong, cohesive networks or weak bridging networks contribute more to vision advantages. This work firmly establishes that it depends. This paper was accepted by Kartik Hosanagar, information systems.","PeriodicalId":18208,"journal":{"name":"Manag. Sci.","volume":"98 1","pages":"1092-1115"},"PeriodicalIF":0.0,"publicationDate":"2022-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79479556","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 examines the effect of the expiry of recording copyright on the supply of music—in the form of rereleases, availability on streaming platforms, and concert performances—by artists popular in the United Kingdom in the 1960s. We find that recording copyright expiry has different effects on a song’s availability in different distribution channels. The lapsing of copyright leads to a large increase in the number of rereleases in physical formats, holding constant artist, age, and year fixed effects. However, when a song’s original recording copyright expires, it becomes less likely to be performed in concert. Moreover, copyright status is not associated with differences in availability on the digital streaming platform Spotify. These results show that copyright expiry has nuanced effects on availability and can lead to different and even opposite effects on availability of a product across different distribution channels. They also show that within the context of digital distribution, the impact of copyright on availability differs based on the business model of a platform. This paper was accepted by Chris Forman, information systems.
{"title":"It Was 50 Years Ago Today: Recording Copyright Term and the Supply of Music","authors":"J. Watson, Megan J. MacGarvie, J. McKeon","doi":"10.1287/mnsc.2022.4343","DOIUrl":"https://doi.org/10.1287/mnsc.2022.4343","url":null,"abstract":"This paper examines the effect of the expiry of recording copyright on the supply of music—in the form of rereleases, availability on streaming platforms, and concert performances—by artists popular in the United Kingdom in the 1960s. We find that recording copyright expiry has different effects on a song’s availability in different distribution channels. The lapsing of copyright leads to a large increase in the number of rereleases in physical formats, holding constant artist, age, and year fixed effects. However, when a song’s original recording copyright expires, it becomes less likely to be performed in concert. Moreover, copyright status is not associated with differences in availability on the digital streaming platform Spotify. These results show that copyright expiry has nuanced effects on availability and can lead to different and even opposite effects on availability of a product across different distribution channels. They also show that within the context of digital distribution, the impact of copyright on availability differs based on the business model of a platform. This paper was accepted by Chris Forman, information systems.","PeriodicalId":18208,"journal":{"name":"Manag. Sci.","volume":"5 1","pages":"351-376"},"PeriodicalIF":0.0,"publicationDate":"2022-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82466667","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 this paper, we study how an on-demand service platform could improve its performance through managing user conduct. In such a platform, service providers may reject certain platform-proposed service requests, and their responses, in turn, incentivize users to adjust their conduct. We develop an evolutionary game theory model of user conduct and provider responses that shows that the platform could improve user conduct through either setting a low wage for service providers or implementing priority matching. Building upon these results, we further model providers and users joining and leaving the platform by once again utilizing the evolutionary game theory approach. We find that wage setting alone is a blunt instrument to improve platform performance via managing user conduct, whereas supplementing the wage decision with priority matching could overcome its limitations and serve as an effective strategy to further improve platform performance in terms of growth and profitability. This finding suggests that matching prioritization could be an important strategy for managing platforms with user and provider heterogeneities. In addition, our analysis and results also demonstrate the potential of the evolutionary game theory approach for analyzing the impact of pricing and matching decisions on the performance of large markets. This paper was accepted by Gabriel Weintraub, revenue management and market analytics.
{"title":"Courteous or Crude? Managing User Conduct to Improve On-Demand Service Platform Performance","authors":"Yunke Mai, Bin Hu, S. Pekec","doi":"10.1287/mnsc.2022.4391","DOIUrl":"https://doi.org/10.1287/mnsc.2022.4391","url":null,"abstract":"In this paper, we study how an on-demand service platform could improve its performance through managing user conduct. In such a platform, service providers may reject certain platform-proposed service requests, and their responses, in turn, incentivize users to adjust their conduct. We develop an evolutionary game theory model of user conduct and provider responses that shows that the platform could improve user conduct through either setting a low wage for service providers or implementing priority matching. Building upon these results, we further model providers and users joining and leaving the platform by once again utilizing the evolutionary game theory approach. We find that wage setting alone is a blunt instrument to improve platform performance via managing user conduct, whereas supplementing the wage decision with priority matching could overcome its limitations and serve as an effective strategy to further improve platform performance in terms of growth and profitability. This finding suggests that matching prioritization could be an important strategy for managing platforms with user and provider heterogeneities. In addition, our analysis and results also demonstrate the potential of the evolutionary game theory approach for analyzing the impact of pricing and matching decisions on the performance of large markets. This paper was accepted by Gabriel Weintraub, revenue management and market analytics.","PeriodicalId":18208,"journal":{"name":"Manag. Sci.","volume":"101 1","pages":"996-1016"},"PeriodicalIF":0.0,"publicationDate":"2022-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90667178","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}
Clinical practice guidelines do not sufficiently address the needs of patients with chronic conditions as these guidelines focus on single disease management and ignore unique patient-specific conditions. As a result, a nonpersonalized approach to the management of the patients with chronic conditions leads to adverse events and increases the financial burden on the healthcare system as over 150 million Americans experience chronic conditions. To this end, we develop a stochastic modeling framework to personalize the disease screening decisions for patients with or at risk for developing a chronic condition and provide an exact solution algorithm. We consider the optimal management of the screening decisions for an index disease (e.g., breast cancer, colorectal cancer, human immunodeficiency virus, etc.) while accounting for the existence of a chronic condition (e.g., hypertension, diabetes, Alzheimer’s disease, etc.). Our modeling framework is particularly useful for the cases where the chronic condition affects the risk of the index disease. In a case study using real breast cancer epidemiology data, we demonstrate how our modeling framework can be used to personalize breast cancer screening for women with type 2 diabetes. In addition to providing a personalized breast cancer screening schedule for women with diabetes, we find some important policy insights that were not previously recognized by the medical community. More specifically, we find that compared with women without diabetes, women with diabetes should be screened less aggressively, but screening should end at similar ages. We also find that adherence to the optimal screening policy is more crucial for women with diabetes compared with nondiabetic women. Our main insight on screening recommendations also has important resource implications as it leads to fewer screening mammograms. That is, compared with the current national breast cancer screening guidelines, the optimal breast cancer screening policy for women with diabetes could save the healthcare system approximately 2.6 million mammograms annually. This paper was accepted by Stefan Scholtes, healthcare management.
{"title":"Personalized Disease Screening Decisions Considering a Chronic Condition","authors":"Ali Hajjar, Oğuzhan Alagöz","doi":"10.1287/mnsc.2022.4336","DOIUrl":"https://doi.org/10.1287/mnsc.2022.4336","url":null,"abstract":"Clinical practice guidelines do not sufficiently address the needs of patients with chronic conditions as these guidelines focus on single disease management and ignore unique patient-specific conditions. As a result, a nonpersonalized approach to the management of the patients with chronic conditions leads to adverse events and increases the financial burden on the healthcare system as over 150 million Americans experience chronic conditions. To this end, we develop a stochastic modeling framework to personalize the disease screening decisions for patients with or at risk for developing a chronic condition and provide an exact solution algorithm. We consider the optimal management of the screening decisions for an index disease (e.g., breast cancer, colorectal cancer, human immunodeficiency virus, etc.) while accounting for the existence of a chronic condition (e.g., hypertension, diabetes, Alzheimer’s disease, etc.). Our modeling framework is particularly useful for the cases where the chronic condition affects the risk of the index disease. In a case study using real breast cancer epidemiology data, we demonstrate how our modeling framework can be used to personalize breast cancer screening for women with type 2 diabetes. In addition to providing a personalized breast cancer screening schedule for women with diabetes, we find some important policy insights that were not previously recognized by the medical community. More specifically, we find that compared with women without diabetes, women with diabetes should be screened less aggressively, but screening should end at similar ages. We also find that adherence to the optimal screening policy is more crucial for women with diabetes compared with nondiabetic women. Our main insight on screening recommendations also has important resource implications as it leads to fewer screening mammograms. That is, compared with the current national breast cancer screening guidelines, the optimal breast cancer screening policy for women with diabetes could save the healthcare system approximately 2.6 million mammograms annually. This paper was accepted by Stefan Scholtes, healthcare management.","PeriodicalId":18208,"journal":{"name":"Manag. Sci.","volume":"38 1","pages":"260-282"},"PeriodicalIF":0.0,"publicationDate":"2022-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79110984","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 cross-sectional variation in corporate profitability has occupied research across fields as diverse as strategic management, industrial organization, finance, and accounting. Prior work suggests that corporate idiosyncrasies are important determinants of profitability, but it disagrees on the quantitative importance of particular effects. This paper shows that corporate specificities become irrelevant in the long run because profitability is ergodic conditional on survival, leading to a uniform, time-invariant regularity in profitability that applies across firms. Conditional on survival, we cannot reject the hypothesis that corporations are on average equally profitable and also experience equally volatile fluctuations in their profitability, irrespective of their individual characteristics. Because the same is not true for shorter-lived firms, even for more than 20 years after entry, we can reconcile our findings with an extensive literature that studies profitability in heterogeneous samples of surviving and shorter-lived firms. Our findings provide a new benchmark for long-term performance in competitive environments and offer a novel perspective by highlighting a robust commonality instead of specificities. This paper was accepted by Alfonso Gambardella, business strategy.
{"title":"Survival and the Ergodicity of Corporate Profitability","authors":"Philipp Mundt, S. Alfarano, M. Milakovic","doi":"10.1287/mnsc.2022.4395","DOIUrl":"https://doi.org/10.1287/mnsc.2022.4395","url":null,"abstract":"The cross-sectional variation in corporate profitability has occupied research across fields as diverse as strategic management, industrial organization, finance, and accounting. Prior work suggests that corporate idiosyncrasies are important determinants of profitability, but it disagrees on the quantitative importance of particular effects. This paper shows that corporate specificities become irrelevant in the long run because profitability is ergodic conditional on survival, leading to a uniform, time-invariant regularity in profitability that applies across firms. Conditional on survival, we cannot reject the hypothesis that corporations are on average equally profitable and also experience equally volatile fluctuations in their profitability, irrespective of their individual characteristics. Because the same is not true for shorter-lived firms, even for more than 20 years after entry, we can reconcile our findings with an extensive literature that studies profitability in heterogeneous samples of surviving and shorter-lived firms. Our findings provide a new benchmark for long-term performance in competitive environments and offer a novel perspective by highlighting a robust commonality instead of specificities. This paper was accepted by Alfonso Gambardella, business strategy.","PeriodicalId":18208,"journal":{"name":"Manag. Sci.","volume":"10 1","pages":"3726-3734"},"PeriodicalIF":0.0,"publicationDate":"2022-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82215952","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}
Elizabeth Blankespoor, Bradley E. Hendricks, Gregory S. Miller, Douglas R. Stockbridge
Firms’ use of special purpose acquisition companies (SPACs) to go public has increased dramatically, leading to market and regulatory debate about their use of projections. Examining SPAC mergers from 2004 through 2021, we find that 80% of firms provide projections for four years ahead on average, with approximately one-quarter of recent projections extending more than five years. For the sample of SPAC mergers with observable postmerger revenue, we find that only 35% of firms meet or beat their projections. This proportion declines for forecasts that are longer horizon, and nonserial SPAC sponsors miss forecasts by greater percentages. When we compare SPAC projected revenue growth with benchmark samples of firms completing an initial public offering (IPO) and matched firms, the SPAC projections are approximately three times larger on average than benchmark firms’ actual revenue growth, with even greater differences for long-term projections. After the merger, firms reduce their use of projections, providing them at statistically similar rates as benchmark firms. Overall, the evidence supports concerns that the SPAC merger includes highly optimistic projections. This paper was accepted by Suraj Srinivasan, accounting.
{"title":"A Hard Look at SPAC Projections","authors":"Elizabeth Blankespoor, Bradley E. Hendricks, Gregory S. Miller, Douglas R. Stockbridge","doi":"10.1287/mnsc.2022.4385","DOIUrl":"https://doi.org/10.1287/mnsc.2022.4385","url":null,"abstract":"Firms’ use of special purpose acquisition companies (SPACs) to go public has increased dramatically, leading to market and regulatory debate about their use of projections. Examining SPAC mergers from 2004 through 2021, we find that 80% of firms provide projections for four years ahead on average, with approximately one-quarter of recent projections extending more than five years. For the sample of SPAC mergers with observable postmerger revenue, we find that only 35% of firms meet or beat their projections. This proportion declines for forecasts that are longer horizon, and nonserial SPAC sponsors miss forecasts by greater percentages. When we compare SPAC projected revenue growth with benchmark samples of firms completing an initial public offering (IPO) and matched firms, the SPAC projections are approximately three times larger on average than benchmark firms’ actual revenue growth, with even greater differences for long-term projections. After the merger, firms reduce their use of projections, providing them at statistically similar rates as benchmark firms. Overall, the evidence supports concerns that the SPAC merger includes highly optimistic projections. This paper was accepted by Suraj Srinivasan, accounting.","PeriodicalId":18208,"journal":{"name":"Manag. Sci.","volume":"82 1","pages":"4742-4753"},"PeriodicalIF":0.0,"publicationDate":"2022-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73388441","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}
Morals constrain self-serving behavior. Yet, self-regulation failures in the face of monetary temptation are common at the workplace. To limit such failures, organizations can design environments that limit the temptation to behave self-servingly, nudging workers to uphold their morals. In a series of experiments where participants may be tempted to take excessive pay after exerting effort, we study whether a simple intervention—asking individuals to state the wage they believe should be paid ex ante, before facing the temptation to take excessive compensation—prevents self-serving behavior. In contrast to lay beliefs and the predictions from prior work, we find that such an intervention is not effective, leading to self-serving behavior. However, a more realistic elicitation procedure of the appropriate wage mitigates this effect. These findings contribute to work on the malleability of moral behavior showing that simple interventions thought to effectively mitigate self-serving behavior can prompt individuals to stretch their moral boundaries. They also stress the importance of properly testing interventions that might seem intuitive. This paper was accepted by Yan Chen, behavioral economics and decision analysis.
{"title":"Mis-Nudging Morality","authors":"Coby Morvinski, Silvia Saccardo, On Amir","doi":"10.1287/mnsc.2022.4344","DOIUrl":"https://doi.org/10.1287/mnsc.2022.4344","url":null,"abstract":"Morals constrain self-serving behavior. Yet, self-regulation failures in the face of monetary temptation are common at the workplace. To limit such failures, organizations can design environments that limit the temptation to behave self-servingly, nudging workers to uphold their morals. In a series of experiments where participants may be tempted to take excessive pay after exerting effort, we study whether a simple intervention—asking individuals to state the wage they believe should be paid ex ante, before facing the temptation to take excessive compensation—prevents self-serving behavior. In contrast to lay beliefs and the predictions from prior work, we find that such an intervention is not effective, leading to self-serving behavior. However, a more realistic elicitation procedure of the appropriate wage mitigates this effect. These findings contribute to work on the malleability of moral behavior showing that simple interventions thought to effectively mitigate self-serving behavior can prompt individuals to stretch their moral boundaries. They also stress the importance of properly testing interventions that might seem intuitive. This paper was accepted by Yan Chen, behavioral economics and decision analysis.","PeriodicalId":18208,"journal":{"name":"Manag. Sci.","volume":"31 2","pages":"464-474"},"PeriodicalIF":0.0,"publicationDate":"2022-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91507156","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：