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Research Summary: We evaluate a pilot in an Inspections Department to explore the returns to a pair of algorithms that varied in their sophistication. We find that both algorithms provided substantial prediction gains, suggesting that even simple data may be helpful. However, these gains did not result in improved decisions. Inspectors often used their decision authority to override algorithmic recommendations, partly to consider other organizational objectives without improving outcomes. Interviews with 55 departments find that while some ran pilots seeking to prioritize inspections using data, all provided considerable decision authority to inspectors. These findings suggest that for algorithms to improve managerial decisions, organizations must consider both the returns to algorithms in the context and how decision authority is managed. Managerial Summary: We evaluate a pilot in an Inspections Department to explore the returns to algorithms on decisions. We find that the greatest gains in this context come from integrating data into the decision process in the form of simple heuristics, rather than from increasing algorithmic sophistication or additional data. We also find that these improvements in prediction do not fully translate into improved decisions. Decision‐makers were less likely to follow data‐driven recommendations, partly in consideration of other organizational objectives, but without substantially improving on them overall. These findings suggest that organizations should consider the returns to technical sophistication in each context, and that the design and management of decision authority can be a key choice that impacts the value organizations can capture from using predictive analytics. [ABSTRACT FROM AUTHOR]

This paper runs a large-scale field experiment on restaurants to understand which types of businesses gain more from digital advertising. Measuring the returns of advertising opportunities continues to be a challenge for many businesses. We design and run a field experiment on a large review platform across 18,294 firms in the restaurant industry to understand which types of businesses gain more from digital advertising. We randomly assign 7,209 restaurants to freely receive the platform's standard ads package for three months. The scale of the experiment gives us a unique opportunity to assess the heterogeneity in advertising effectiveness across a variety of business attributes. We find that restaurants that receive advertising observe on average a 7%–19% increase in a wide range of purchase intention outcomes, as well as a 5% increase in customer reviews. We find that gains are heterogeneous across firms, with independent and higher-rated businesses observing larger gains, as well as those with more reviews and higher pre-experiment organic traffic. History: Olivier Toubia served as the senior editor for this article. This paper was accepted through the Marketing Science: Frontiers review process. Supplemental Material: The data and e-companion are available at https://doi.org/10.1287/mksc.2023.1436. [ABSTRACT FROM AUTHOR]

The World Health Organization recently began developing a "pandemic treaty" in response to the perceived failures of the global COVID-19 response. The Framework Convention on Tobacco Control, which obligates members to certain global standards in tobacco control, is an example of a global public health agreement that may be used as a model for the pandemic treaty. Several challenges related to the convention, many from the tobacco industry itself, must be addressed if it is to be used as a prototype for a pandemic agreement. These include harm reduction policies, private-sector involvement, and its impact in low- and middle-income countries. A pandemic treaty may encounter similar challenges faced by the Framework Convention on Tobacco Control, particularly from industry groups with financial interests related to infectious disease control and prevention. Addressing challenges at the outset may facilitate the development and implementation of a more robust international instrument. [ABSTRACT FROM AUTHOR]

Public health organizations increasingly use social media advertising campaigns in pursuit of public health goals. In this paper, we evaluate the impact of about $40 million of social media advertisements that were run and experimentally tested on Facebook and Instagram, aimed at increasing COVID-19 vaccination rates in the first year of the vaccine roll-out. The 819 randomized experiments in our sample were run by 174 different public health organizations and collectively reached 2.1 billion individuals in 15 languages. We find that these campaigns are, on average, effective at influencing self-reported beliefs—shifting opinions close to 1% at baseline with a cost per influenced person of about $3.41. Combining this result with an estimate of the relationship between survey outcomes and vaccination rates derived from observational data yields an estimated cost per additional vaccination of about $5.68. There is further evidence that campaigns are especially effective at influencing users’ knowledge of how to get vaccines. Our results represent, to the best of our knowledge, the largest set of online public health interventions analyzed to date. [ABSTRACT FROM AUTHOR]

Introduction: The decision to discharge a patient from the hospital with confirmed or suspected coronavirus 2019 (COVID-19) is fraught with challenges. Patients who are discharged home must be both medically stable and able to safely isolate to prevent disease spread. Socioeconomically disadvantaged patient populations in particular may lack resources to safely quarantine and are at high risk for COVID-19 morbidity. Methods: We developed a telehealth follow-up program for emergency department (ED) patients who received testing for COVID-19 from April 24-June 29, 2020 and were discharged home. Patients who were discharged with a pending COVID-19 test received follow-up calls on Days 1, 4, and 8. The objective of our program was to screen and provide referrals for health-related social needs (HRSN), conduct clinical screening for worsening symptoms, and deliver risk-reduction strategies for vulnerable individuals. We conducted retrospective chart reviews on all patients in this cohort to collect demographic information, testing results, and outcomes of clinical symptom and HRSN screening. Our primary outcome measurement was the need for clinical reassessment and referral for an unmet HRSN. Results: From April 24-June 29, 2020, we made calls to 1,468 patients tested for COVID-19 and discharged home. On Day 4, we reached 67.0% of the 1,468 patients called. Of these, 15.9% were referred to a physician's assistant (PA) out of concern for clinical worsening and 12.4% were referred to an emergency department (ED) patient navigator for HRSNs. On Day 8, we reached 81.8% of the 122 patients called. Of these, 19.7% were referred to a PA for clinical reassessment and 14.0% were referred to an ED patient navigator for HRSNs. Our intervention reached 1,069 patients, of whom 12.6% required referral for HRSNs and 1.3% (n = 14) were referred to the ED or Respiratory Illness Clinic due to concern for worsening clinical symptoms. Conclusion: In this patient population, the demand for interventions to address social needs was as high as the need for clinical reassessment. Similar ED-based programs should be considered to help support patients' interdependent social and health needs beyond those related to COVID-19. [ABSTRACT FROM AUTHOR]

Bacteriophages infecting bacteria of the genus Gordonia have increasingly gained interest in the scientific community for their diverse applications in agriculture, biotechnology, and medicine, ranging from biocontrol agents in wastewater management to the treatment of opportunistic pathogens in pulmonary disease patients. However, due to the time and costs associated with experimental isolation and cultivation, host ranges for many bacteriophages remain poorly characterized, hindering a more efficient usage of bacteriophages in these areas. Here, we perform a series of computational genomic inferences to predict the putative host ranges of all Gordonia cluster DR bacteriophages known to date. Our analyses suggest that BiggityBass (as well as several of its close relatives) is likely able to infect host bacteria from a wide range of genera—from Gordonia to Nocardia to Rhodococcus, making it a suitable candidate for future phage therapy and wastewater treatment strategies. [ABSTRACT FROM AUTHOR]

We present evidence that unnecessarily complex disclosure can result from strategic incentives to shroud information. In our laboratory experiment, senders are required to report their private information truthfully but can choose how complex to make their reports. We find that senders use complex disclosure more than half the time. This obfuscation is profitable because receivers make systematic mistakes in assessing complex reports. Regression and structural analysis suggest that these mistakes could be driven by receivers who are naive about the strategic use of complexity or overconfident about their ability to process complex information. This paper was accepted by Yan Chen, behavioral economics and decision analysis. [ABSTRACT FROM AUTHOR]

The COVID‐19 pandemic led to dramatic economic disruptions, including government‐imposed restrictions that temporarily shuttered millions of American businesses. We use a nationwide survey of thousands of small business owners to establish three main facts about business owners' decisions to reopen at the end of the lockdowns. First, roughly 60 percent of firms planned to reopen within days of the end of legal restrictions, suggesting that the lockdowns were generally binding for businesses—although nearly 30 percent expected to delay their reopening by at least a month. Second, decisions to delay reopenings did not seem to be driven by concerns about employee or customer health; even businesses in high‐proximity sectors with the highest health risks generally reported intentions to reopen as soon as regulations allowed. Third, pessimistic demand projections primarily explain delays among firms that could legally reopen. Owners expected demand to be one‐third lower than before the crisis throughout the pandemic. Using experimentally induced shocks to perceived demand, we find that a 10 percent decline in expected demand results in a 1.5 percentage point (8 percent) increase in the likelihood that firms expected to remain closed for at least one month after being legally able to open. We use follow‐up surveys to cross‐validate expectations with realized outcomes. Overall, our results suggest that governments set more stringent guidelines for reopening than what many businesses would have selected, suggesting that governments may have internalized costs of contagion that businesses did not. [ABSTRACT FROM AUTHOR]

During the coronavirus disease 2019 (COVID‐19) pandemic, states issued and then rescinded stay‐at‐home orders that restricted mobility. We develop a model of learning by deregulation, which predicts that lifting stay‐at‐home orders can signal that going out has become safer. Using restaurant activity data, we find that the implementation of stay‐at‐home orders initially had a limited impact, but that activity rose quickly after states' reopenings. The results suggest that consumers inferred from reopening that it was safer to eat out. The rational, but mistaken inference that occurs in our model may explain why a sharp rise of COVID‐19 cases followed reopening in some states. [ABSTRACT FROM AUTHOR]

Although a business's reputation can affect its pricing, prices can also affect its reputation. To explore the effect of prices on reputation, we investigate daily data on menu prices and online ratings from a large rating and ordering platform. We find that a price increase of 1% leads to a decrease of 3%–5% in the average rating. Consistent with this, the overall distribution of ratings for cheaper restaurants is similar to that of more expensive restaurants. Finally, these effects do not seem to be driven by consumer retaliation against price changes but by changes in absolute price levels. This paper was accepted by Duncan Simester, marketing. [ABSTRACT FROM AUTHOR]

The article informs about rise of online marketplaces raises the potential for markets that are both more efficient and less biased, and research pointed to the arms-length nature and relative anonymity of online transactions as factors that lead to less discrimination in online transactions. Topics extent to which is realized depends on the design choices platforms; and growing share of markets and transactions have moved online, marketplaces have evolved and platform designers.

To explore the impact of coronavirus disease 2019 (COVID-19) on small businesses, we conducted a survey of more than 5,800 small businesses between March 28 and April 4, 2020. Several themes emerged. First, mass layoffs and closures had already occurred—just a few weeks into the crisis. Second, the risk of closure was negatively associated with the expected length of the crisis. Moreover, businesses had widely varying beliefs about the likely duration of COVID-related disruptions. Third, many small businesses are financially fragile: The median business with more than $10,000 in monthly expenses had only about 2 wk of cash on hand at the time of the survey. Fourth, the majority of businesses planned to seek funding through the Coronavirus Aid, Relief, and Economic Security (CARES) Act. However, many anticipated problems with accessing the program, such as bureaucratic hassles and difficulties establishing eligibility. Using experimental variation, we also assess take-up rates and business resilience effects for loans relative to grants-based programs. [ABSTRACT FROM AUTHOR]

Dominant platform businesses often develop products in adjacent markets to complement their core business. One common approach used to gain traction in these adjacent markets has been to pursue a tying strategy. For example, Microsoft preinstalled Internet Explorer into Windows, and Apple set Apple Maps as the iOS default. Policymakers have raised concerns that dominant platforms may be leveraging their market power to gain traction for lower quality products when they use a tying strategy. In this paper, we empirically explore this question by examining Google's decision to tie its new reviews product to its search engine. We experimentally vary the reviews displayed above Google's organic search results to show either exclusively Google reviews (Google's current tying strategy) or reviews from multiple platforms determined to be the best-performing by Google's own organic search algorithm. We find that users prefer the version that does not exclude competitor reviews. Furthermore, looking at observational data on user traffic to Yelp from search engines, we find that Google's exclusion of downstream competitors may have been effective. The share of Yelp's traffic coming from Google has declined over this period, relative to traffic from Bing and Yahoo (which do not exclude other companies' reviews), and Google reviews has grown more quickly than Yelp and TripAdvisor during the period in which they excluded these (and other) reviews providers. Overall, these results suggest that tying has the potential to facilitate entry in complementary markets even when the tied product is of worse quality than competitors. The online appendix is available at https://doi.org/10.1287/mnsc.2018.3246. [ABSTRACT FROM AUTHOR]

As technology platforms have created new markets and new ways of acquiring information, economists have come to play an increasingly central role in tech companies—tackling problems such as platform design, strategy, pricing, and policy. Over the past five years, hundreds of PhD economists have accepted positions in the technology sector. In this paper, we explore the skills that PhD economists apply in tech companies, the companies that hire them, the types of problems that economists are currently working on, and the areas of academic research that have emerged in relation to these problems. [ABSTRACT FROM AUTHOR]

Because consumer reviews leverage the wisdom of the crowd, the way in which they are aggregated is a central decision faced by platforms. We explore this “rating aggregation problem” and offer a structural approach to solving it, allowing for (1) reviewers to vary in stringency and accuracy, (2) reviewers to be influenced by existing reviews, and (3) product quality to change over time. Applying this to restaurant reviews from Yelp.com, we construct an adjusted average rating and show that even a simple algorithm can lead to large information efficiency gains relative to the arithmetic average. [ABSTRACT FROM AUTHOR]

The article examines gentrification has emerged as a central policy issue in cities from New York to Edinburgh to Seoul and the role of data from agencies such as the Census Bureau. It notes that combining Yelp and American Community Survey (ACS) data helps explore the potential and find that entry of Starbucks into a neighborhood is in fact indicative of housing price growth across the U.S.

New, 'big data' sources allow measurement of city characteristics and outcome variables at higher collection frequencies and more granular geographic scales than ever before. However, big data will not solve large urban social science questions on its own. Big urban data has the most value for the study of cities when it allows measurement of the previously opaque, or when it can be coupled with exogenous shocks to people or place. We describe a number of new urban data sources and illustrate how they can be used to improve the study and function of cities. We first show how Google Street View images can be used to predict income in New York City, suggesting that similar imagery data can be used to map wealth and poverty in previously unmeasured areas of the developing world. We then discuss how survey techniques can be improved to better measure willingness to pay for urban amenities. Finally, we explain how Internet data is being used to improve the quality of city services. ( JEL R1, C8, C18) [ABSTRACT FROM AUTHOR]

Handgun waiting periods are laws that impose a delay between the initiation of a purchase and final acquisition of a firearm. We show that waiting periods, which create a "cooling off" period among buyers, significantly reduce the incidence of gun violence. We estimate the impact of waiting periods on gun deaths, exploiting all changes to state-level policies in the Unites States since 1970. We find that waiting periods reduce gun homicides by roughly 17%. We provide further support for the causal impact of waiting periods on homicides by exploiting a natural experiment resulting from a federal law in 1994 that imposed a temporary waiting period on a subset of states. [ABSTRACT FROM AUTHOR]