Come join the Strategy PhD program at the Fuqua School of Business at Duke University. We’re looking for talented, driven, and curious students who want to become the next generation of scholars and thinkers about the role of innovation, entrepreneurship and strategy in the economy. Below in the attached PDF you will find lots of detail about our program! If you have any questions, feel free to reach out to me.
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 the growing data exchange between firms, 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 1600 data exchanges reported in the news between 2017 and 2018 executed by 1285 of the largest public and private firms. Our findings suggest that nearly 17% of these firms in our sample 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 data exchanges and the market for data may be consequential and call for further research.
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.
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.
Research suggests that increased digitization of the labor market combined with the changing demand for skill has altered the job-search process. In this article, we argue that these changes have led to increased investments in firm-driven search for talent (or `outbound recruiting’). We investigate this question using two data sets, one new. First, we conduct a nationally representative survey of over 13,000 American workers. We find that nearly 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 firm-driven search is greatest among higher-income workers, at 20.3 percent, and those with STEM and business degrees, at 20 percent. Moreover, considerable regional variation exists. For example, over a quarter of Silicon Valley workers are hired in this manner, whereas only 14.5% of those in Rochester are. Second, we complement our worker-level results by analyzing 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—hiring more recruiters with skill in online search. Given the growth of this practice, we discuss implications for research on firm strategy and labor markets.
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.
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.
We conduct a field experiment at an entrepreneurship bootcamp to investigate whether interaction with proximate peers shapes a nascent startup team’s performance. We find that teams whose members lack prior ties to others at the bootcamp experience peer effects that influence the quality of their product prototypes. A one-standard-deviation increase in the performance of proximate teams is related to a two-thirds standard-deviation improvement for a focal team. In contrast, we find that teams whose members have many prior ties interact less frequently with proximate peers, and thus their performance is unaffected by nearby teams. Our findings highlight how prior social connections, which are often a source of knowledge and influence, can limit new interactions and thus the ability of organizations to leverage peer effects to improve the performance of their members.
We analyze whether widespread online access to school quality information affected economic and social segregation in America. We leverage the staged roll-out of GreatSchools.org school ratings across America from 2006-2015 to answer this question. Across a range of outcomes and specifications, we find that the mass availability of school ratings has accelerated divergence in housing values, income distributions, education levels, as well as the racial and ethnic composition across communities. Affluent and more educated families were better positioned to leverage this new information to capture educational opportunities in communities with the best schools. An unintended consequence of better information was less, rather than more, equity in education.