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How do firms respond to entry in multi-sided markets? We address this question by studying the impact of Craigslist, a website providing classified-advertising services, on local U.S. newspapers. We exploit temporal and geographical variation in Craigslist's entry to show that newspapers with greater reliance on classified-ad revenue experience a larger drop in classified-ad rates after Craigslist's entry. The impact of Craigslist's entry on the classified-ad side appears to propagate to other sides of the newspapers' market. On the subscriber side, these newspapers experience an increase in subscription prices, a decrease in circulation, and an increase in differentiation from each other. On the display-ad side, affected newspapers experience a decrease in display-ad rates. We also find evidence that affected newspapers are less likely to make their content available online. Finally, we estimate that Craigslist's entry leads to $5.0 billion (year 2000 dollars) in savings to classified-ad buyers during 2000-2007. This paper was accepted by Sandra Slaughter, information systems.

Firms’ innovative activities can be sensitive to public policies that affect the availability of capital. In this paper, we investigate the effects of regional and temporal variation in U.S. personal bankruptcy laws on firms’ innovative activities. We find that bankruptcy laws that provide stronger debtor protection decrease the number of patents produced by small firms. Stronger debtor protection also decreases the average quality, and variance in quality, of firms’ patents. We find evidence that the negative effect of stronger debtor protection on experimentation and innovation may be due to the decreased availability of external financing in response to stronger debtor rights, an effect amplified in industries with a high dependence on external financing. Hence, while it is typically assumed that stronger debtor protection encourages innovation by reducing the cost of failure for innovators, we show that it can instead dampen innovative activities by tightening the availability of external financing to innovative firms. This paper was accepted by David Hsu, entrepreneurship and innovation .

We assess the role of race in loans made through the Paycheck Protection Program (PPP). The PPP program, created by the U.S. government as a response to the Covid-19 pandemic, provides loans to small businesses so they can keep employees on their payroll. We argue that the historical record and PPP program design choices made it likely that many Black-owned businesses received smaller PPP loans than White-owned businesses. Using newly released data on the PPP program, we find that Black-owned businesses received loans that were approximately 50% lower than observationally similar White-owned businesses. The effect is marginally smaller in areas with more bank competition and disappeared over time as changes to the PPP program were implemented allowing for entry by fintechs and other nontraditional lenders. We find that Black-owned businesses received loans through the Paycheck Protection Program that were approximately 50 percent lower than White-owned businesses with similar characteristics. However, this difference in loan size shrank over time as more non-bank lenders such as fintechs were allowed to participate in the program and began approving PPP loans. Loan size differences were also slightly smaller in zip codes containing a larger number of bank branches. These results are consistent with prior research which shows lending discrimination by commercial banks against Black borrowers. It is also consistent with studies showing that greater access to and competition among banks and other lenders can reduce discrimination. In light of these results we recommend that policy makers account for existing racial inequalities within banking or other systems in their program design to produce more equitable outcomes.

This article investigates how private firms respond to potential entry from public firms. This paper uses a data set of over 3,000 U.S. cable TV systems to present evidence consistent with entry deterrence. Incumbent cable TV firms upgrade faster when located in markets with a potential municipal entrant. However, the same systems are then slower to offer new products enabled by the upgrade, suggesting upgrades in these markets occur for strategic reasons. Incumbent cable systems also upgrade faster in response to municipal entry threats than to private entry threats. Understanding how private firms respond to potential entry from public firms is especially important in light of recent U.S. government entry into several industries. This paper was accepted by Bruno Cassiman, business strategy.

This paper examines the impact of asymmetric information on incumbent firms' propensity to engage in limit pricing when faced with threat of entry. I draw from information economics to argue that incumbents will use price to respond ex ante to entry in situations characterized by asymmetric information. I suggest two situations in which asymmetric information can arise: when potential entrants are from outside the primary industry and when incumbent firms are members of R&D consortia. I then study pricing in the U.S. cable TV industry to show that pricing patterns of incumbent cable TV systems are consistent with limit pricing when the relationship between the incumbent and potential entrant is characterized by asymmetric information.

Prior episodes of automation have led to economic growth and also to many changes in the workplace. We expect the same from artificial intelligence (AI). The link between AI and labor is complex, however. To assist researcher and policymakers, we provide a method that links advances in AI to occupational abilities, and then aggregates from these abilities to the occupation level. We demonstrate the method by estimating which occupational descriptions have changed the most due to advances in AI between 2010 and 2015, and check our estimates using the Bureau of Labor Statistics scheduled update to occupational descriptions in 2016.

This article provides an introduction to artificial intelligence, robotics, and research streams that examine the economic and organizational consequences of these and related technologies. We describe the nascent research on artificial intelligence and robotics in the economics and management literature and summarize the dominant approaches taken by scholars in this area. We discuss the implications of artificial intelligence, robotics, and automation for organizational design and firm strategy, argue for greater engagement with these topics by organizational and strategy researchers, and outline directions for future research.

Research Summary: With the recent growth of the sharing economy, regulators must frequently strike the right balance between private and public interests to maximize value creation. In this article, we argue that political competition is a critical ingredient that explains whether cities accommodate or ban ridesharing platforms and that this relationship is moderated in more populous cities and in cities with higher unemployment rates. We test our arguments using archival data covering ridesharing bans in various U.S. cities during the 2011–2015 period. We supplement these data with semistructured interviews. We find broad support for our arguments while mitigating potential endogeneity concerns. Our study has important implications for nonmarket strategy, entrepreneurship and innovation, and public‐private partnership literatures. In addition, our findings inform policy debates on the sharing economy. Managerial Summary: Entrepreneurs and businesses oftentimes face severe regulatory barriers when commercializing innovative products and services even if the innovations are generally beneficial for consumers and the broader society. This research focuses on the political determinants of regulation to provide a better understanding of why some markets are more receptive to innovative products while other markets are more hostile to them. Using the banning of ridesharing companies (e.g., Uber and Lyft) in various U.S. cities during the 2011–2015 period, we find that elected politicians facing less political competition (i.e., not easily replaceable, serving multiple terms, longer tenure in office) were more likely to ban ridesharing companies and favor, potentially displaceable, local taxicab companies. Our research has implications for navigating the political barriers to entry.

This research note reports on an empirical investigation of the effect of the Internet on racial hate crimes in the United States from the period 2001–2008. We find evidence that, on average, broadband availability increases racial hate crimes. We also document that the Internet’s impact on these hate crimes is not uniform in that the positive effect is stronger in areas with higher levels of racism, which we identify as those with more segregation and a higher proportion of racially charged search terms, but not significant in areas with lower levels of racism. We analyze in depth whether Internet access will enhance hate group operations but find no support for the idea that this mechanism is driving the result. In contrast, we find that online access is increasing the incidence of racial hate crimes executed by lone wolf perpetrators. Several other mechanisms that could be driving the results are described. Overall, our results shed light on one of the many offline societal challenges from increased online access.

We review the evidence that artificial intelligence (AI) is having a large effect on the economy. Across a variety of statistics—including robotics shipments, AI start-ups, and patent counts—there is evidence of a large increase in AI-related activity. We also review recent research in this area that suggests that AI and robotics have the potential to increase productivity growth but may have mixed effects on labor, particularly in the short run. In particular, some occupations and industries may do well while others experience labor market upheaval. We then consider current and potential policies around AI that may help to boost productivity growth while also mitigating any labor market downsides, including evaluating the pros and cons of an AI specific regulator, expanded antitrust enforcement, and alternative strategies for dealing with the labor market impacts of AI, including universal basic income and guaranteed employment.