Dog Eat Dog: Measuring Network Effects Using a Digital Platform Merger

Farronato, Chiara; Fong, Jessica; Fradkin, Andrey

doi:10.2139/ssrn.3727123

Cited by 5 publications

(5 citation statements)

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“…Pet owners are randomly assigned different increases in the size of the network of pet sitters with which they may interact, with assignment depending on what city the pet owner lives in. Farronato, Fong, and Fradkin (2020) find that in markets where the acquiring platform was dominant, there is little change after the merger. Network effects are apparent in markets where the two platforms were similar in size, although pet sitters of the acquired platform often did not participate after the merger.…”

Section: Exclusions In Two-sided Marketsmentioning

confidence: 92%

“…They quantify the importance of network effects and the extent of multiple equilibria. Farronato, Fong, and Fradkin (2020) study digital platforms that match pet owners to pet sitters. From the perspective of a pet owner, a merger between two platforms creates a larger set of potential pet sitters to interact with on the remaining platform than either platform provided before the merger.…”

Section: Exclusions In Two-sided Marketsmentioning

confidence: 99%

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Two-sided markets, pricing, and network effects

Pavan

Rysman

2021

Handbook of Industrial Organization

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Section: Exclusions In Two-sided Marketsmentioning

confidence: 92%

Section: Exclusions In Two-sided Marketsmentioning

confidence: 99%

Two-sided markets, pricing, and network effects

Pavan

Rysman

2021

Handbook of Industrial Organization

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“…Based on these data and exploiting the COVID-19 shock, Amstad et al (2020 [24]) build a new index capturing investors' attitudes toward pandemic-related risks. In the same spirit, Eichenauer et al (2020 [25]) propose a novel method for using Google Trends data to construct daily sentiment indicators for a set of German-speaking countries.…”

Section: Box 2 Google Trends As a Measure Of Socioeconomic Outcomesmentioning

confidence: 99%

The role of online platforms in weathering the COVID-19 shock

2021

OECD Policy Responses to Coronavirus (COVID-19)

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This policy brief reports on the activity of online platforms during the COVID-19 crisis. Google Trends data for OECD and other G20 countries indicate that in some areas (such as retail sales, restaurant delivery, and mobile payments) online-platform use increased markedly during the first half of 2020, when most countries imposed lockdown and physical distancing measures. Thus, in this period, some economic transactions may have shifted to online marketplaces as people and businesses increasingly turned to online platforms to pursue economic and social activities. The rise in platform use was however highly heterogeneous across areas of activity and countries. Countries with higher levels of economic and technological development, easier access to infrastructure and connectivity, better digital skills, and wider Internet use tended to experience a larger increase in the use of online marketplaces, possibly mitigating the negative effects on output and jobs of the COVID-19 shock. This highlights the role of policies in strengthening countries' digital preparedness and their resilience to future shocks. This is an updated version of the Policy Brief dated 16 Dec 2020. The only changes concern the labels of Figure 2.The role of online platforms in weathering the COVID-19 shock 2 The closest historic parallel in terms of mortality to the current crisis was the Spanish Flu pandemic from 1918 to 1920, which took place in a markedly different economic, social, and demographic context.

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“…2 Although Amazon previously allowed sellers to import their reputational data from eBay, once eBay threatened to sue Amazon for intellectual property infringement, it halted this practice, which likely relaxed the competition for sellers (Resnick et al, 2000;Ba and Pavlou, 2002;Dellarocas et al, 2006). We also recognize that it is technically feasible to transfer reputational data, such that when Rover merged with DogVacay, it gave DogVacay's users an easy path to transfer their ratings, reviews, and transaction history to its platform (Farronato et al, 2020). However, dominant platforms such as Airbnb, Amazon, eBay, and Uber appear to prefer limiting such transfers of reputational data, likely because the switching costs created by user lock-in can mitigate competition, even if they harm users' overall welfare (Shapiro et al, 1998).…”

Section: Introductionmentioning

confidence: 99%

Lock-in Effects in Online Labor Markets

Stenzhorn¹,

Hornuf²,

Ciotti³

2021

AEA Randomized Controlled Trials

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This article reports on an investigation of the role of lock-in exploitation and the impact of reputation portability on workers' switching behaviors in online labor markets. Online platforms using reputation mechanisms typically prevent users from transferring their ratings to other platforms, inducing lock-in effects and high switching costs and leaving users vulnerable to platform exploitation. With a theoretical model, in which workers in online labor markets are locked-in by their reputational data, we test the effects using an online lab-in-the-field decision experiment. In addition to comparing a policy regime with and without reputation portability, we vary lock-in exploitation using platform fees to consider how switching behavior might differ according to monetary motives and fairness preferences. Theoretically, this study reveals how reputational investments can produce switching costs that platforms can exploit. Experimentally, the results suggest that reputation portability mitigates lock-in effects, making users less susceptible to lock-in exploitation. The data further show that switching is driven primarily by monetary motives, but perceiving the fee as unfair also has a significant role.

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Dog Eat Dog: Measuring Network Effects Using a Digital Platform Merger

Cited by 5 publications

References 0 publications

Two-sided markets, pricing, and network effects

Two-sided markets, pricing, and network effects

The role of online platforms in weathering the COVID-19 shock

Lock-in Effects in Online Labor Markets

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