Knowledge that Transforms

Acquisitions by corporate entities have fueled the growth of chain organizations in healthcare. A chain is a multiunit firm under the same ownership and management providing similar services in different locations. Chain ownership has been credited with boosting firm performance in the retail and service sectors but has been criticized for prioritizing profits over the well-being of patients in the healthcare sector. This paper finds that chain ownership improves healthcare outcomes in the market for in vitro fertilization (IVF). Using novel data on U.S. fertility clinics and difference-in-differences methods, we find that IVF cycles increase by 27.2%, and IVF success rates increase by 13.6% after acquisition by a fertility chain. We provide evidence that fertility chains facilitate resource and knowledge transfers needed to enhance quality and expand the IVF market. For example, acquired clinics change IVF processes and procedures to achieve the IVF gold standard of simultaneously reducing higher-risk multiple births and increasing singleton births. We discuss how the fertility sector’s relatively minimal market frictions and information asymmetries may incentivize chain owners to invest in quality. This paper was accepted by Stefan Scholtes, healthcare management. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.02793 .

Although investor attention is fundamental to the efficient functioning of capital markets, it is also an elusive construct that researchers struggle to measure. In recent years, the search volume index (SVI) of ticker searches on Google has become a ubiquitous measure of investor attention, but the amount and effects of measurement error in ticker SVI are unknown. We investigate measurement error in ticker SVI using a data set of 2.7 billion website visits following Standard and Poor’s 500 firms’ ticker searches. We find that 69% of searches are unrelated to investing, that this measurement error is highly correlated with firm characteristics, and that this measurement error can easily generate false-positive or false-negative results in common settings. We go on to show that a modified version of SVI using both a firm’s ticker and the word “stock” (e.g., searches for “CAT stock,” which we label “ticker-stock SVI”) not only better captures the search terms that investors typically use, but also has considerably less measurement error that is largely uncorrelated with observable firm characteristics. Ticker-stock SVI produces better specified tests, and although researchers must still carefully consider the effects of measurement error, we recommend that ticker-stock SVI is used in place of ticker SVI in most settings. We provide a data set of ticker-stock SVI to facilitate future work. This paper was accepted by Suraj Srinivisan, accounting. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.02174 . TS-SVI for the Russell 3000 is available for download at: github.com/robinlitjens/GoogleTickerStock-SVI and will be updated annually.

We use disaggregated U.S. data and a border discontinuity design to show that more generous unemployment insurance (UI) policies lower bank deposits. We test several channels that could explain this decline and find evidence consistent with households lowering their deposit holdings due to reduced precautionary savings. Because deposits are the largest and most stable source of funding for banks, the decrease in deposits affects bank lending. Banks that raise deposits in states with generous UI policies reduce their loan supply to small businesses. Furthermore, counties that are served by these banks experience a higher unemployment rate and lower wage growth. This paper was accepted by Lukas Schmid, finance. Funding: G. Kabas acknowledges financial support from the European Research Council [ERC ADG 2016-GA 740272 lending]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.03217 .

We explore how information ambiguity and traders’ attitudes toward such ambiguity affect expectations and asset prices under three different market institutions. Specifically, we test a theoretical prediction that information ambiguity will lead market prices to overreact to bad news and underreact to good news. We find that such an asymmetric reaction exists and is strongest in individual prediction markets. It occurs to a lesser extent in single price call markets. It is weakest of all in double auction markets, in which buyers’ asymmetric reaction to good/bad news is cancelled out by the opposite asymmetric reaction of sellers. This paper was accepted by Camelia Kuhnen, finance. Funding: Financial support from a Tier 1 Grant from MOE of Singapore [Grant RG 69/19], NTU-WeBank JRC [Grant NWJ-2020-003], the National Natural Science Foundation of China [Grants 72303170, 72141304], and the National Key Research and Development Program of China [Grant 2022YFC3303304] is gratefully acknowledged. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.01223 .

In the last two decades, last-mile delivery (LMD) firms have seen immense growth fueled by the success of e-commerce, leading to faster and cheaper deliveries. Operating on thin margins, LMD firms strive for successful first-time deliveries to avoid the financial and reputational costs of reattempts. Delivery agents (DAs) are integral to LMD efficiency, influencing customer experience, delivery success, and productivity. However, most LMD performance enhancement research focuses on process, technology, and incentives, which presume workers will conform to procedures and monitoring tools will function flawlessly. Nevertheless, in practice, DAs deviate from expected behaviors, that is, indulge in misconduct, negatively affecting delivery efficiency, often resulting in returned parcels. One of the major forms of misconduct is entering fake remarks about deliveries, wherein DAs intentionally do not deliver the parcels and provide fake reasons for it. For instance, even without reaching a delivery address, a DA remarks “customer unavailable” and records a delivery failure. In this study, we collaborated with a leading Indian LMD firm and, using instrumental variable regression, found that such misconduct leads to a spillover productivity loss. This effect reduces the next day’s successful deliveries by 1.60% and first-time-right deliveries by 1.86%. We discuss misconduct’s correlation with factors such as task complexity and offer novel insights into how opportunistic circumstances can influence worker behavior. This paper was accepted by Elena Katok, operations management. Funding: V. Choudhary acknowledges the support received from Ministry of Education, Singapore [Grant RS12/20]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.01829 .

We study the asset pricing implications of being able to optimally early exercise plain vanilla puts, contrasting expected raw and delta-hedged returns across equivalent American and European puts. Our theory suggests that American puts yield less negative raw but more negative delta-hedged expected returns than equivalent European puts. The raw (delta-hedged) spread widens with a higher early exercise probability as induced through, for example, moneyness, time to maturity, and underlying asset volatility (variance and jump risk premiums). An empirical comparison of single-stock American puts with equivalent synthetic European puts formed from put–call parity supports our theory if and only if we allow for optimal early exercises in our return calculations. More strikingly, allowing for optimal early exercises significantly alters the profitability of 14 out of 15 well-known option anomalies with the average absolute change equal to 33% and five anomalies becoming insignificant. This paper was accepted by Lukas Schmid, finance. Supplemental Material: The internet appendix and data files are available at https://doi.org/10.1287/mnsc.2023.00440 .

Many professional and educational settings require individuals to be willing and able to perform under time pressure. We use a laboratory experiment and survey data to study preferences for working under time pressure. We make three main contributions. First, we develop an incentivized method to measure preferences for working under time pressure and document that participants in our laboratory experiment are averse to working under time pressure on average. Second, we show that there is substantial heterogeneity in the degree of time pressure aversion across individuals and that these individual preferences can be partially captured by simple survey questions. Third, we include these questions in a survey of bachelor’s degree students and a nationally representative survey panel and show that time pressure preferences predict career choices and income. Our results indicate that individual differences in time pressure aversion could be an influential factor in determining labor market outcomes. This paper was accepted by Yan Chen, behavioral economics and decision analysis. Funding: This work was supported by the Jan Wallander and Tom Hedelius Foundation, European Research Council under the European Union’s Horizon 2020 Research and Innovation Programme [Grant 850590]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.02078 .

We study the blocking effect of patents on follow-on innovation by others. We posit that follow-on innovation requires freedom to operate (FTO), which firms typically obtain through a license from the patentee holding the original innovation. Where licensing fails, follow-on innovation is blocked unless firms gain FTO through patent invalidation. Using large-scale data from post-grant oppositions at the European Patent Office, we find that patent invalidation increases follow-on innovation, measured in citations, by 16% on average. This effect exhibits a U-shape in the value of the original innovation. For patents on low-value original innovations, invalidation predominantly increases low-value follow-on innovation outside the patentee’s product market. Here, transaction costs likely exceed the joint surplus of licensing, causing licensing failure. In contrast, for patents on high-value original innovations, invalidation mainly increases high-value follow-on innovation in the patentee’s product market. We attribute this latter result to rent dissipation, which renders patentees unwilling to license out valuable technologies to (potential) competitors. This paper was accepted by Ashish Arora, entrepreneurship and innovation. Funding: This work was supported by the Deutsche Forschungsgemeinschaft [Collaborative Research Center TRR 190]. F. Gaessler acknowledges financial support from the Spanish Agencia Estatal de Investigación through the Severo Ochoa Programme for Centres of Excellence in R&D [Barcelona School of Economics CEX2019-000915-S]. Supplemental Material: The online appendices and data files are available at https://doi.org/10.1287/mnsc.2019.02294 .

Using data on 10,776 firms across 22 emerging markets, we show that both credit constraints and weak green management hold back corporate investment in green technologies embodied in new machinery, equipment, and vehicles. In contrast, investment in measures to explicitly reduce emissions and other pollution is mainly determined by the quality of a firm’s green management and less so by binding credit constraints. Data from the European Pollutant Release and Transfer Register reveal the environmental impact of these organizational constraints. In areas where more firms are credit constrained and weakly managed, industrial facilities systematically emit more CO 2 and pollutants. A counterfactual analysis shows that credit constraints and weak management have respectively kept CO 2 emissions 4.5% and 2.3% above the levels that would have prevailed without such constraints. This is further corroborated by our finding that in localities where banks had to deleverage more due to the global financial crisis, carbon emissions by industrial facilities remained 5.6% higher a decade later. This paper was accepted by Lukas Schmid, finance. Supplemental Material: The online appendices and data files are available at https://doi.org/10.1287/mnsc.2023.00772 .

Descriptive norms, the behavior of other individuals in one’s reference group, play a key role in shaping individual decisions in managerial contexts and beyond. Organizations are increasingly using information about descriptive norms to nudge positive behavior change. When characterizing peer decisions, a standard approach in the literature is to focus on average behavior. In this paper, we argue both theoretically and empirically that not only averages but also the shape of the whole distribution of behavior can play a crucial role in how people react to descriptive norms. Using a representative sample of the U.S. population, we experimentally investigate how individuals react to strategic environments that are characterized by different distributions of behavior, focusing on the distinction between tight (i.e., characterized by low behavioral variance), loose (i.e., characterized by high behavioral variance), and polarized (i.e., characterized by u-shaped behavior) environments. We find that individuals indeed strongly respond to differences in the variance and shape of the descriptive norm they are facing: Loose norms generate greater behavioral variance and polarization generates polarized responses. In polarized environments, most individuals prefer extreme actions, which expose them to considerable strategic risk, to intermediate actions that minimize such risk. Furthermore, in polarized and loose environments, personal traits and values play a larger role in determining actual behavior. These nuances of how individuals react to different types of descriptive norms have important implications for company culture, productivity, and organizational effectiveness alike. This paper was accepted by Dorothea Kübler, behavioral economics and decision analysis. Funding: This work was supported by the German Research Foundation under Germany’s Excellence Strategy [EXC 2126/1–390838866]. Supplemental Material: The online appendices and data files are available at https://doi.org/10.1287/mnsc.2023.01022 .