Network hiring, firm performance and growth

Available on SSRN

(with Ines Black)

Network hiring—i.e. the preference for hiring workers who are referred by existing employees or have shared affiliations with them—is a prevalent practice across many industries. Considerable research shows hiring within a firm’s network provides soft information about potential hires as well as informal mechanisms of control once they join a company. While research shows that in-network hires perform better, little is known about the firm-level performance implications and the associated trade-offs of this practice. In this article, we study the impact of network hiring by using data on the universe of firms in Portugal between 1994 to 2017. We find that network hiring appears to increase firm performance but at the expense of growth. Furthermore, network hiring seems to provide firms with information on intrinsic motivation traits of the candidates, rather than information on skills. We conclude with a discussion on how this practice should affect the strategy of firms, particularly young ones.

Some data on the market for data

Available on SSRN

(with Morad Elsaify)

Firms are collecting more data—about their operations, customers, and markets—in order to improve performance. Some of this data has value beyond a firm’s boundary and thus can create value for other firms. Yet, we have relatively few facts about this market for data, its participants, and the types and value of data bought and sold by firms. We present preliminary descriptive evidence about the emerging data market using the information on over 1,600 data exchanges executed by 1,285 of the largest public and private firms. Our findings suggest that nearly 17% of these firms participate in the data market. Furthermore, 80% of the exchanges are for customer data, and over 50% of transactions are structured as mutual data sharing agreements rather than unidirectional sales. Among the firms in our sample, it is the largest firms in terms of valuation and those with significant data capabilities that buy and sell data. Moreover, we find that most exchanges appear to happen among firms in the same industry and with significant data science capabilities. These results suggest that the market for data may be consequential and call for further research.

The politics of experimentation

Available on SSRN

(with Todd Hall)

Many startups have embraced formal experimentation—i.e., A/B testing—to improve the performance of their products and services. Experimentation, some have argued, should democratize innovation inside organizations by creating a platform to rigorously test new ideas, regardless of origin. In this article, we argue that experimentation’s promise hinges on having the right organizational decision-making process—one that encourages innovation but without the added risk of unanticipated failures. We study this question by developing a model of experimentation inside organizations where decisions to implement are either centralized or decentralized—a tension identified by practitioners and scholars alike. We find that startups with centralized mechanisms that rely too much on the input of other teams benefit least from experimentation, as do ones with completely decentralized ones. In contrast, startups with mostly decentralized decisions, with a single authority that sets consistent thresholds for implementation, achieve growth but with less downside risk. Thus, without considering the politics that guide organizational decision-making, the benefits of experimentation may be limited.

Educational technology and the problem of inequality

Work in progress

(with Anuj Kumar)

Innovations in educational technology are proposed by many as a solution to the growing achievement gap in America and abroad. Recently, however, there is increasing concern over whether scarce resources should be allocated to these yet unproven technological interventions—or spent on more proven inputs to educational production (e.g., better-trained teachers). Moreover, recent reports advance the hypothesis that technology may further increase inequality. In this article, we synthesize the literature to develop a framework for understanding the conditions under which technology leads to less, rather than more, equity in educational outcomes. Our analysis indicates that given the uneven distribution of essential inputs to learning—teachers, administration, and family resources—across schools and students of different socioeconomic status, educational technology interventions that ignore these differences will exacerbate existing achievement gaps, not mitigate them.

Hunting for talent: Firm-driven labor market search in America

(with Ines Black and Rembrand Koning)

What impact has the digitization of the labor market had on firm-driven search for talent? We investigate this question with two novel data sets. First, we conduct a nationally representative survey of American workers. We find that today over 18 percent of all employed workers in the US were hired into their present company by the outbound recruiting effort their employer, either directly or through labor market intermediaries such as a headhunter. The share of hiring driven by active firm search behavior is greatest among higher-income workers, at 23 percent, and those with STEM and business degrees, at 22.5 percent. Moreover, there is considerable regional variation. Over a quarter of Silicon Valley workers are hired in this manner. We complement our worker-level results with an analysis of a large sample of job postings in the US economy over the past decade. We find that firms, especially those relying on high-skilled labor, are increasingly developing capabilities to better hunt for talent. Given the prevalence of this practice, we discuss how theories of labor markets and firm strategy may be refined to account for these facts.

Designing social networks: Joint tasks and the formation and endurance of network ties

Journal of Organization Design, (9)4, 2020

(with Rembrand Koning)

Can managers influence the formation of organizational networks? In this article, we evaluate the effect of joint tasks on the creation of network ties with data from a novel field experiment with 112 aspiring entrepreneurs. During the study, we randomized individuals to a set of 15 joint tasks varying in duration (week-long teams to 20-minute conversations). We then evaluated the impact of these interactions on the formation and structure of individuals’ social networks. We find strong evidence that these designed interactions led to the systematic creation of new friendship and advice relations as well as changes to the participants’ network centrality. Overall, network ties formed after a randomized interaction account for about one-third the individuals a participant knows, of their friendships, and their advice relations. Nevertheless, roughly 90% of randomized interactions never become social ties of friendship or advice. A key result from our research is that while joint tasks may serve to structure the social consideration set of possible connections, individual preferences strongly shape the structure of networks. As a consequence, there will likely remain a considerable unpredictability in the presence of specific ties even when they are designed.

Experimentation and startup performance: Evidence from A/B testing

Available on SSRN

(with Rembrand Koning and Aaron Chatterji)

Recent work argues that experimentation is the appropriate framework for entrepreneurial strategy. We investigate this proposition by exploiting the time-varying adoption of A/B testing technology, which has drastically reduced the cost of experimentally testing business ideas. This paper provides the first evidence of how digital experimentation affects the performance of a large sample of high-technology startups using data that tracks their growth, technology use, and product launches. We find that, despite its prominence in the business press, relatively few firms have adopted A/B testing. However, among those that do, we find increased performance on several critical dimensions, including page views and new product introductions. Furthermore, A/B testing is positively related to tail outcomes, with younger ventures failing faster and older firms being more likely to scale. Firms with experienced managers derive more benefits from A/B testing. Our results inform the emerging literature on entrepreneurial strategy and how digitization and data-driven decision-making are shaping strategy.