COVID-19 and Digital Resilience: Evidence from Uber Eats*
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COVID-19 and Digital Resilience: Evidence from Uber Eats* Manav Raj,† Arun Sundararajan,‡ Calum You.§ This draft: June 12, 2020 Abstract We analyze how digital platforms can increase the survival rate of firms during a crisis by providing continuity in access to customers. Using order-level data from Uber Technologies, we study how the COVID-19 pandemic and the ensuing shutdown of businesses in the United States affected independent, small business restaurant supply and demand on the Uber Eats platform. We find evidence that small restaurants experience significant increases in total activity, orders per day, and orders per hour following the closure of the dine-in channel, and that these increases may be due to both demand-side and supply-side shocks. We document an increase in the intensity of competitive effects following the shock, showing that growth in the number of providers on a platform induces both market expansion and heightened inter-provider competition. Our findings underscore the critical role that digital will play in creating business resilience in the post-COVID economy, and provide new managerial insight into how supply-side and demand-side factors shape business performance on a platform. * The authors are listed alphabetically by last name. This study was conducted as an independent research collaboration between the authors. Manav Raj and Arun Sundararajan are not and have not been affiliated with Uber Technologies, and Calum You is not and has not been affiliated with NYU. No consulting fees, research grants or other payments have been made by Uber Technologies to the NYU authors, or by NYU to the Uber Technologies author. We thank Emilie Boman, Libby Mishkin, Sabrina Ross and Allison Wylie for thoughtful feedback, and Uber Technologies for access to data. All errors are our own. Author emails: [email protected]; [email protected]; [email protected]. † NYU Stern School of Business ‡ NYU Stern School of Business § Uber Technologies 1 1. INTRODUCTION The restaurant business is among the industries most acutely impacted by the COVID crisis. As cities and states initiated shelter-in-place orders and consumers pulled back their presence in public spaces, restaurants that rely exclusively or primarily on dine-in (serving consumers face- to-face) have been especially affected. Numbers from the Advance Monthly Retail Trade Survey by the U.S. Census Bureau indicate a 48.7% year-over-year decline for food services and drinking places (NAICS 722) in April 2020, reflecting revenue losses of over $30 billion that month alone, and of over $50 billion in March and April 2020 (US Census Bureau Monthly and Annual Retail Trade, 2020). According to the National Restaurant Association, the average establishment saw a 78% decline in its revenues in the first 10 days of April 2020 compared to the same period in April 2019, and revenue losses over the month are projected to exceed $50 billion (Grindy, 2020). Within the restaurant industry, small businesses have been especially vulnerable to this crisis. While larger restaurant chains may have the resources to weather a prolonged economic downturn, independent establishments and mom-and-pop restaurants may struggle to stay alive as revenues fall, and it is believed that up to 75% of independent restaurants closed during the pandemic may not survive the crisis (Severson and Yaffe-Bellany, 2020). Further, independent restaurants are more heavily impacted by recessions and economic shocks than the larger national chains as they have limited access to credit and alternative financing options during such crises (Dietrich, Schneider, and Stocks, 2020). The unfavorable economic environment will thus further exacerbate the credit constraints (Evans and Jovanovic, 1989) that typically disadvantage small businesses. Faced with the current crisis, restaurants have been forced to utilize alternative channels to reach customers, maintain revenue, and stay alive. A bright spot for some restaurants has been the growth of access to alternative digital channels over the last few years. For an independent restaurant, food delivery platforms like Uber Eats and Doordash can now make the difference between survival and shutdown. Our study takes a close look at the economic effects of access to this platform-enabled channel during the COVID-19 shutdown in March and April 2020. 2 Figure 1: Year-over-Year Percent Change in Seated Diners in Response to the COVID-19 Pandemic Note: Illustrates the year-over-year percent change in seated diners at restaurants on the OpenTable network in the United States The dashed line represents March 16. Prior research has explored the challenges and opportunities that such alternative distribution channels pose to incumbent firms that have traditionally operated in different markets (e.g., Chen, Hu, and Smith, 2019a; Danaher et al., 2010; Smith and Telang, 2009). For example, Airbnb is now an increasingly important channel, not just for sharing one’s spare bedroom or apartment, but also for bed-and-breakfasts and full-time vacation rental properties (Guttentag, 2015). Similarly, e-commerce platforms such as eBay and Amazon.com are increasingly important for small businesses and individual sellers (Bailey et al., 2008). These digital distribution channels that have ended up being a source of small business resilience exhibit different characteristics than traditional markets, altering the nature of competition in markets (Farronato and Fradkin, 2018; Hall and Krueger, 2018; Zervas, Proserpio, and Byers, 2017). Such changes provide opportunities for businesses that may struggle in other market settings. On the supply side, platforms and digital distribution channels lower the costs of entry for small providers, enabling smaller providers to reach buyers more easily and providing them with flexibility (Chen et al., 2019b; Einav, Farronato, and Levin, 2016). Digital markets greatly reduce the costs of consumer search and discovery using recommendation tools that leverage large data on consumer behavior with a wide inventory of products (Brynjolfsson, Hu, and Simester, 2011; Oestreicher-Singer and Sundararajan, 2012). In conjunction with the decreased 3 costs of maintaining inventory and the ability to aggregate demand across a wider consumer base, such recommendation and search tools create a market in which “niche” offerings can find an audience and thrive (e.g., Brynjolfsson et al., 2006, 2011; Oestreicher-Singer and Sundararajan, 2012; Zhang, 2018). Building on such work, we analyze and document the stabilizing and sustaining effects of food delivery platforms in the weeks following the shutdown in the United States due to the COVID- 19 pandemic in mid-March 2020. We use order-level data from the Uber Eats food delivery platform for five major US cities (New York City, San Francisco, Atlanta, Miami, and Dallas) from February 1st 2020 through May 1st 2020 to examine changes in restaurant demand and performance on the Uber Eats platform following the shutdown. We find evidence that small restaurants take advantage of the online on-demand channel to partially offset the revenue losses from shuttering their dine-in channel. Across our five sample cities, we see a sharp increase in the rate at which new restaurants join the Uber Eats platform. In addition, we see that restaurants that remain open for delivery appear to experience significant and economically meaningful increases in the count of orders that they receive. This increase in orders exists despite the fact that many restaurants have cut the number of hours that they supply on the platform. Probing deeper, our analysis reveals that the impact of the COVID-induced economic shock has many facets which collectively influence observed changes in restaurant demand and performance. There is a demand-side shock comprised of many parts with countervailing effects: the absence of dine-in options may shift demand towards the online channel; variability in the availability of groceries and fears of going to a grocery store may induce consumers to order in rather than cook themselves; an increase in the hours people have been spending at home coupled with health concerns associated with food prepared and delivered by people outside their homes could induce an increased propensity and ability to prepare one’s own meals. More saliently, there is also a supply-side shock induced by the shuttering of many restaurants, the cutting back of operating hours for those that remain open, and the greater availability of resources to dedicate to the delivery side of operations as dine-in dries up. Our analysis of the competitive effects of this supply-side shock reveals that the intensity of competitive effects (as measured by the percent of restaurants within a cuisine categorization that 4 remain open on a given day) have grown following the shock. As one might expect, the performance of an individual restaurant on the Uber Eats platform is better when a larger fraction of its competitors (defined as those in the same city offering the same cuisine) are closed. However, overall demand on the platform is larger when more restaurants are open. These dual effects of market expansion and substitution suggest an interesting tension between what is optimal for the platform and what is optimal for the complementors hosted on the platform. Our work contributes to multiple streams of literature. Over the last decade, the emergence of platforms has spawned a growing body of literature that focuses on the strategy and performance of the firms that create and organize the platforms (e.g., Boudreau, 2010; Cennamo and Santalo, 2013; Eisenmann, Parker, and Alstyne, 2011; Tucker and Zhang, 2010; Zhu and Iansiti, 2012). However, much less attention has been paid to understanding the performance and strategy of providers on digital markets, despite the fact that such providers are critical to value creation and represent the vast majority of firms within a platform ecosystem (Kapoor and Agarwal, 2017). Our work aims to fill that gap by showing how digital channels can stabilize firm performance when other distribution channels are limited.