Annamaria Conti

Multisided platforms crucially rely on indirect network effects. When trying to strengthen these effects, platform owners face a fundamental challenge, namely, designing incentives to enhance developer effort and simultaneously ensuring the release of high-quality products on the platform. This paper highlights the costs associated with lowering royalty rates to boost developer effort, as such reductions increase the relative supply of lower-quality offerings, worsening information congestion problems and amplifying the importance of visibility-enhancing investments. We leverage the quasi random announcements made by Apple and Google, declaring their intention to reduce the royalty rate applied to small app developers from 30% to 15%. We analyze the implications of these reforms using a difference-in-differences approach, finding a substantial increase in small developers’ likelihood of releasing lower-quality and less original apps on iOS and Android after the announcements. These effects are neither paralleled by a comparable increase in high-quality app releases nor by an increase in small developers’ likelihood of launching venture-backed apps. Consistent with worsening information congestion problems because of an influx of low-quality apps, our findings show an increase in the marginal value of experienced user certifications and developers’ app store optimization efforts post announcement. Additionally, we observe that venture capitalists are increasingly concentrating their investments in ventures with higher (observable) quality. This paper was accepted by Anita McGahan, business strategy. Funding: This work was supported by the Spanish Ministry of Education [Project PID2022-138710NB-I00 funded by MCIU/AEI/10.13039/501100011033/FEDER, UE]. A. Conti acknowledges financial support from the Swiss National Science Foundation [Grant 100013_197807]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2024.0586 .

A central challenge in venture scaling is that growing external output typically demands a corresponding increase in human and financial resources. This study investigates how the adoption of generative artificial intelligence (GenAI) reshapes this relationship. Using a panel of U.S. software startups in 2018-2024 and a difference-in-differences design centered on ChatGPT’s release, we find that GenAI adoption does not significantly affect overall hiring or venture funding. Instead, GenAI-adopting startups experience greater adoption of complementary technologies and significant output growth, as reflected in increased website traffic and faster commercialization outcomes. While total headcount remains unchanged, GenAI adoption induces a compositional shift away from junior roles toward senior-level positions. This organizational change is reflected in an increase in internal promotions, suggesting that GenAI enhances the value of labor by accelerating upskilling and internal career advancement. Collectively, our findings demonstrate that GenAI allows nascent firms to accelerate scaling without a proportional expansion in headcount.

We study the engagement of nascent firms with open source communities and its implications for innovation and attracting funding. To do so, we link data on 160,065 U.S. startups from Crunchbase to their activities on the open source software development platform GitHub. In a matched sample of firms with and without GitHub activities, difference-in-differences models reveal a substantial increase in the likelihood of being funded after early stage startups engage with open source communities on GitHub. This relationship is weaker for firms that employ GitHub for internal development only. Startups developing novel technologies tend to benefit more from engaging with open source communities, unlike those in highly competitive environments. This heterogeneity highlights a potential trade-off between engaging with open source communities and appropriability. To provide insight regarding mechanisms, we classify startups’ technology use-cases on GitHub using machine learning and exploit data on product launches. Our results from these additional analyses support the notion that one important channel potentially driving our findings is the access to external knowledge for technology development provided by open source communities. Engaging with these communities may thereby aid startups in innovating and creating a (minimum) viable product. Funding: A. Conti and C. Peukert received financial support from the Swiss National Science Foundation [Project IDs 100013_188998 and 100013_197807]. M. Roche received financial support from the Harvard Business School Division of Research and Faculty Development. Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2023.18348 .

While patents have been shown to play a role as barriers to entry, they also reveal information about incumbent strategies and risk being invalidated. We examine the trade-off incumbents face between using their patents ex ante as entry deterrents or ex post once competitors have revealed their moves. Leveraging the unique characteristics of the pharmaceutical sector, in which it is possible to observe exactly when a competitor entry threat materializes, and exploiting exogenous variation in that timing, we show that incumbents intentionally fragment and delay the full disclosure of their intellectual property rights through continuation patents. They disproportionately reveal continuation patents after a competitor entry threat becomes concrete, tailoring their response to the threat they have received and successfully delaying competitor entry through litigation. The detected incumbents’ reaction is stronger when their attacked drugs are valuable and when the patents listed at the Food and Drug Administration approval of a drug are relatively narrow in scope. This paper was accepted by Alfonso Gambardella, business strategy. Funding: A. Conti acknowledges funding from E4S. E. Sung acknowledges funding from the HEC Foundation [Grant 9B82F1905+] and the U.S. National Science Foundation [Grant 1759991]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.00900 .

In November 2020, Apple announced a reduction in the royalty rate applied to small app developers from 30% to 15%. In March 2021, Google followed suit committing to a similar reform. We analyze the implications of these reforms for the distribution of app quality with a stylized model that assumes heterogeneity in the ability to develop apps. After Apple’s announcement, we empirically find a substantial increase in the number of new apps released on the iOS and Android platforms by solo developers, who supposedly are more likely to conform to the definition of “small app developers.” The launched apps are in the lowest quartile for the number of upvotes and ratings received, indicating a surge in low-quality apps. Consistently, we find that -as a result of the reforms- the likelihood of solo developers launching apps that turn into new ventures declines. We finally show that post-reform, the marginal value of quality certification by external, experienced users increases, suggesting that there are potential costs associated with the increased supply of low-quality apps. We discuss the implications for platform governance and regulation.

Given its spectacular growth in recent years, venture capital is gaining significant attention among strategy scholars. In this paper, we shed light on a novel and unexplored phenomenon, namely the...

Using a large dataset of US investors and their portfolio startups, we analyze the phenomenon of micro VC investors, that is, VC firms managing funds smaller than $50 million. We show that investments by micro VCs have increased at a much steeper rate than those by traditional VCs during 2010-2020. We find significant differences between micro and traditional VCs beyond fund size. Micro VCs invest in early-stage startups more than traditional VCs do. Despite the greater risk of such investments, micro VCs use staged financing less frequently than traditional VCs. Additionally, micro VCs invest in geographically closer startups but their investments span a larger set of industries than traditional VCs. Examining the implications for portfolio startups, we find that startups financed by micro VCs raise less capital than those funded by traditional VCs and are less likely to exit via IPO or acquisition. These results are more pronounced when micro VCs are led by former entrepreneurs and are, at least in part, ascribed to the more founder-friendly management style of micro VCs.

We study the participation of nascent firms in open-source communities and its implications for attracting VC funding. To do so, we exploit unique data on 160,065 US startups linking information from Crunchbase to firms’ GitHub accounts. Estimating a within-startup model saturated with a host of relevant fixed effects, we show that startups accelerate their activities on the platform in the twelve months prior to raising their first financing round. The intensity of their involvement on GitHub declines in the twelve months after. Remarkably, startups intensify those activities that rely on external technology sources above and beyond the technologies they themselves control. Applying machine learning to classify GitHub projects, we find that the most prevalent among these external activities are related to software development, data analytics, and integration. Our results indicate that VCs and renowned investors are the most responsive to these activities.