Person:

Zhu, Feng

The diffusion of the Internet and digital technologies has enabled many organizations to use the open-content production model to produce and disseminate knowledge. While several prior studies have shown that the open-content production model can lead to high-quality output in the context of uncontroversial and verifiable information, it is unclear whether this production model will produce any desirable outcome when information is controversial, subjective, and unverifiable. We examine whether the open-content production model helps achieve a neutral point of view (NPOV) using data from Wikipedia's articles on U.S. politics. Our null hypothesis builds on Linus' Law, often expressed as "Given enough eyeballs, all bugs are shallow." Our findings are consistent with a narrow interpretation of Linus' Law, namely, a greater number of contributors to an article makes an article more neutral. No evidence supports a broad interpretation of Linus' Law. Moreover, several empirical facts suggest the law does not shape many articles. The majority of articles receive little attention, and most articles change only mildly from their initial slant. Our study provides the first empirical evidence on the limit of Linus' Law. While many organizations believe that they could improve their knowledge production by leveraging communities, we show that in the case of Wikipedia, there are aspects, such as NPOV, that the community does not always achieve successfully.

Problem definition: We study the disproportionate impact of the lockdown as a result of the COVID-19 outbreak on female and male academic research productivity in social science. Academic/practical relevance: The lockdown has caused substantial disruptions to academic activities, requiring people to work from home. How this disruption affects productivity and the related gender equity is an important operations and societal question. Methodology: We collect data from the largest open-access preprint repository for social science on 41,858 research preprints in 18 disciplines produced by 76,832 authors across 25 countries over a span of two years. We use a difference-in-differences approach leveraging the exogenous pandemic shock. Results: Our results indicate that, in the 10 weeks after the lockdown in the United States, although total research productivity increased by 35%, female academics’ productivity dropped by 13.2% relative to that of male academics. We also show that this intensified productivity gap is more pronounced for assistant professors and for academics in top-ranked universities and is found in six other countries. Managerial implications: Our work points out the fairness issue in productivity caused by the lockdown, a finding that universities will find helpful when evaluating faculty productivity. It also helps organizations realize the potential unintended consequences that can arise from telecommuting.

We study compatibility decisions of two competing platform owners that generate profits through both hardware sales and royalties from content sales. We consider a game-theoretic model in which two platforms offer different standalone utilities to users. We find that incentives to establish one-way compatibility—the platform owner with smaller standalone value grants access to its proprietary content application to users of the competing platform—can arise from the difference in their profit foci. As the difference in the standalone utilities increases, royalties from content sales become less important to the platform owner with greater standalone value, but more important to the other platform owner. One-way compatibility can thus increase asymmetry between the platform owners’ profit foci and, given a sufficiently large difference in the standalone utilities, yields greater profits for both platform owners. We further show that social welfare is greater under one-way compatibility than under incompatibility. We also investigate how factors such as exclusive content and hardware-only adopters affect compatibility incentives.

Research Summary: Platform owners sometimes enter complementors' product spaces and compete against them. Using data from Amazon.com to study Amazon's entry pattern into third‐party sellers' product spaces, we find that Amazon is more likely to target successful product spaces. We also find that Amazon is less likely to enter product spaces that require greater seller efforts to grow, suggesting that complementors' platform‐specific investments influence platform owners' entry decisions. While Amazon's entry discourages affected third‐party sellers from subsequently pursuing growth on the platform, it increases product demand and reduces shipping costs for consumers. We consider the implications of these findings for complementors in platform‐based markets. Managerial Summary: Platform owners can exert considerable influence over their complementors' welfare. Many complementors with successful products are pushed out of markets because platform owners enter their product spaces and compete directly with them. To mitigate such risks, complementors could build their businesses by aggregating nonblockbuster products or focusing on products requiring significant platform‐specific investments to grow. They should also develop capabilities in new product discovery so that they could continually bring innovative products to their platforms.

Static models of two-sided markets often lead to multiple equilibria as a result of increasing return to demand. Typically the market can be monopolistic or oligopolistic in equilibrium. We provide a simple dynamic model to address the equilibrium selection problem. Our results indicate that the final market structure depends critically on the overall strength of the indirect network effects of the two sides. Interestingly, we find under weak network effects the market share advantage of the leader diminishes over time. Simulating our model under the monopoly conditions also suggests that time until dominance follows a power law distribution, and as a result the probability that monopoly does not occur for an extended period is not trivial. We then discuss the implications of our results for intermediaries.

As platform owners continue to expand their ecosystems, many of them have started to provide consumers with their own complementary applications. These moves position the platform owners as direct competitors to their complementors. This paper surveys empirical studies that examine the direct entry of platform owners into complementors’ product spaces. It finds that both the motivation and impact of such entries on complementors are multifaceted. The motivation behind platform owners’ direct entry goes beyond value capture, and the impact of platform entry on complementors varies across empirical settings. It identifies several future research directions that can help advance our understanding of the relationships between platform owners and complementors.

Organizations today can use both crowds and experts to produce knowledge. While prior work compares the accuracy of crowd-produced and expert-produced knowledge, we compare bias in these two models in the context of contested knowledge, which involves subjective, unverifiable, or controversial information. Using data from Encyclopædia Britannica, authored by experts, and Wikipedia, an encyclopedia produced by an online community, we compare the slant and bias of pairs of articles on identical topics of U.S. politics. Our slant measure is less (more) than zero when an article leans towards Democratic (Republican) viewpoints, while bias is the absolute value of the slant. We find that Wikipedia articles are more slanted towards Democratic views than are Britannica articles, as well as more biased. The difference in bias between a pair of articles decreases with more revisions. The bias on a per word basis hardly differs between the sources because Wikipedia articles tend to be longer than Britannica articles. These results highlight the pros and cons of each knowledge production model, help identify the scope of the empirical generalization of prior studies comparing the information quality of the two production models, and offer implications for organizations managing crowd-based knowledge production.

Digital technologies have led to the emergence of many platforms in our economy today. In certain platform networks, buyers in one market purchase services from providers in many other markets, whereas in others, buyers primarily purchase services from providers within the same market. Accordingly, network interconnectivity—which measures the degree to which consumers in one market purchase services from service providers in a different market—varies across different industries. We examine how network interconnectivity affects interactions between an incumbent platform serving multiple markets and an entrant platform seeking to enter one of these markets. Our model yields several interesting results. First, even if the entrant can advertise at no cost, it still may not want to make every user in a local market aware of its service, as doing so may trigger a competitive response from the incumbent. Second, having more mobile buyers, which increases interconnectivity between markets, can reduce the incumbent’s incentive to fight and, thus, increase the entrant’s incentive to expand. Third, stronger interconnectivity between markets may or may not make the incumbent more defensible: when advertising is not costly and mobile buyers consume in both their local markets and the markets they visit, a large number of mobile buyers will increase the entrant’s profitability, thereby making it difficult for the incumbent to deter entry. However, when advertising is costly or mobile buyers only consume in the markets they travel to, a large number of mobile buyers will help the incumbent deter entry. When advertising cost is at an intermediate level, the entrant prefers a market with moderate interconnectivity between markets. Fourth, we find that even if advanced targeting technologies can enable the entrant to also advertise to mobile buyers, the entrant may choose not to do so in order to avoid triggering the incumbent’s competitive response. Finally, we find that the presence of network effects is likely to decrease the entrant’s profit. Our results offer managerial implications for platform firms and help understand their performance heterogeneity.

In this essay, we identify several themes of the digital business transformation, with a particular focus on the economy-wide impacts of artificial intelligence and digital platforms. In doing so, we highlight specific industries, beyond just the high-profile “Big Tech” firms, where the digital business revolution is having, or promises to have, significant impact. The papers in this special issue (flagged with bold font below) provide a deeper analysis of the themes and applications we touch on here.

This paper provides the first formal model of business model innovation. Our analysis focuses on sponsor-based business model innovations where a firm monetizes its product through sponsors rather than setting prices to its customer base. We analyze strategic interactions between an innovative entrant and an incumbent where the incumbent may imitate the entrant's business model innovation once it is revealed. The results suggest that an entrant needs to strategically choose whether to reveal its innovation by competing through the new business model or conceal it by adopting a traditional business model. We also show that the value of business model innovation may be so substantial that an incumbent may prefer to compete in a duopoly rather than to remain a monopolist.