Using U.S. venture capital investment data from 1985 to 2008 and qualitative interviews, we examine how group dynamics influence the growth of interorganizational collaborations through the addition of new members.
North Carolina’s 100 counties have experienced an uneven pattern of growth and development over the past decade or so, even during the pandemic, when the state was a magnet for migration. At one end, metropolitan and amenity-rich counties captured most of the growth between April 1, 2020, and July 1, 2021; at the other, 21 counties experienced net out-migration. Given these disparities, the Urban Investment Strategies Center offers an approach using targeted economic development strategies.
Background: Influenza imposes heavy societal costs through healthcare expenditures, missed days of work, and numerous hospitalizations each year. Considering these costs, the healthcare and behavioral science literature offers suggestions on increasing demand for flu vaccinations. And yet, the adult flu vaccination rate fluctuated between 37% and 46% between 2010 and 2019.
Aim: Although a demand-side approach represents one viable strategy, an operations management approach would also highlight the need to consider a supply-side approach. In this paper, we investigate how to improve clinic vaccination rates by altering provider behavior.
Philanthropy by entrepreneurs remains an empirically underexplored topic. Combining datasets on U.S. based IPOs with individual philanthropic gifts, we empirically demonstrate that entrepreneurial harvests indeed trigger entrepreneurs’ philanthropic behavior. Furthermore, we distinguish how entrepreneurs’ approach to philanthropy differs from other individuals who experience the same wealth creating event. Entrepreneurs are able to transition more quickly to philanthropy compared to non-entrepreneurs, are more likely to invest in university science and technology, and also provide a greater number of gifts.
We use US Census administrative data to document important facts about wages at entrepreneurial firms. As in earlier studies, we confirm lower average wages at new firms. However, nearly two thirds of this decline can be attributed to differences in worker quality at new firms. Moreover, once we control for firm fixed effects, absorbing time invariant firm quality, the wage difference between new and established firms further declines.
This research utilizes data from the World Bank Investment Climate Survey to examine the use of external capital for almost 70,000 small and medium-sized firms in 103 developing and developed countries.
We empirically investigate the effect of uncertainty on corporate hiring. Using novel data from the labor market for MBA graduates, we show that uncertainty regarding how well job candidates fit with a firm’s industry hinders hiring and that firms value probationary work arrangements that provide the option to learn more about potential full-time employees.
In a recent paper, “Demystifying Illiquid Assets – Expected Returns for Private Equity,” Ilmanen, Chandra and McQuinn (of AQR) give a perspective on the past, present, and expected future performance of private equity. They conclude that “private equity does not seem to offer as attractive a net-of-fee return edge over public market counterparts as it did 15-20 years ago from either a historical or forward-looking perspective.” This analysis provides our perspective based on more recent and, we think, more reliable data and performance measures – the historical perspective is more positive than Ilmanen et al. portray.
Theoretically, wealthier people should buy less insurance, and should self-insure through saving instead, as insurance entails monitoring costs. Here, we use administrative data for 63,000 individuals and, contrary to theory, find that those with more wealth have better life and property insurance coverage, controlling for the value of the assets insured.
To encourage year-long engagement and invite more people into the conversation, the Kenan Institute of Private Enterprise and the Entrepreneurship Center at UNC have produced the first-ever Trends in Entrepreneurship Report. Combining data with expert analysis, the report gives timely insights into the topics that significantly affect entrepreneurs, funders, ecosystem partners, policymakers and others in the innovation economy.
The Trends in Entrepreneurship Report brings together expertise and data from academia, industry and policy to highlight relevant topics facing entrepreneurs and investors today. For the 2022 annual report, we invited researchers to submit trends based on their own emerging research. We welcomed submissions related to current topics in entrepreneurship, with a particular interest on trends related to funding; ecosystems; teams and talent; emerging technologies; and addressing diversity, equity and inclusion in entrepreneurship and small business. Each trend was reviewed for quality and relevance by our editorial board
There has been renewed advocacy for restrictions on international financial flows in the wake of the recent financial crisis. Motivated by this trend, we explore the extent to which cross-border flows affect real economic activity. Unlike previous research efforts that focus on aggregated capital flows, we exploit novel data on forced trading by global mutual funds as a plausible source of exogenous flow shocks. Such forced trading is known to generate large liquidity and price effects, but its real impacts have not been studied extensively. We find that both country- and firm-level investment growth rates are significantly affected by these exogenous capital shocks, and that their effect is more pronounced for firms whose marginal investment decisions are more equity-reliant.
We use panel data on ISO 9000 quality certification in 85 countries between 1993 and 1998 to better understand the cross-national diffusion of an organizational practice. Following neoinstitutional theory, we focus on the coercive, normative, and mimetic effects that result from the exposure of firms in a given country to a powerful source of critical resources, a common pool of relevant technical knowledge, and the experiences of firms located in other countries. We use social network theory to develop a systematic conceptual understanding of how firms located in different countries influence each other's rates of adoption as a result of cohesive and equivalent network relationships.
Research on resource dependence typically takes a static view in which actions and outcomes are determined structurally, but not as responses to the actions of the counterparty in an exchange relation. By contrast, this study addresses a question of power dynamics by examining whether mergers of organizations trigger responses from their common exchange partners. We predict that common exchange partners respond by withdrawing from the relationship and that their responses vary with the availability of alternatives, the value of the relationship, and the relationship history. Using data on advertising agencies, we show that mergers of agencies do trigger reactions from their common clients, and the reactions differ with agency and client characteristics. Extending existing theory and evidence, our results suggest that firms respond to the dynamics of exchange relationships and not only to their structure.
Work scheduling research typically prescribes task sequences implemented by managers. Yet employees often have discretion to deviate from their prescribed sequence. Using data from 2.4 million radiological diagnoses, we find that doctors prioritize similar tasks (batching) and those tasks they expect to complete faster (shortest expected processing time).
Past research has shown that founders bring important capabilities and resources from their prior employment into their new firms and that these intergenerational transfers influence the performance of these ventures. However, we know little about whether organizational practices also transfer from parents to spawns, and if so, what types of practices are transferred? Using a combination of survey and registrar data and through a detailed identification strategy, we examine these two previously unaddressed questions.
During the 2000s, over a dozen U.S. states passed laws that prohibit healthcare employers from mandating overtime for nurses. Using a nationwide panel data set from 2004 to 2012, we find that these mandatory overtime laws reduced the service quality of nursing homes, as measured by an increase in deficiency citations. This outcome can be explained by two undesirable changes in the staffing hours of registered nurses: decreased hours of permanent nurses and increased hours of contract nurses per resident day. We observe that the increase in deficiency citations concentrates in the domains of administration and quality of care rather than quality of life, and the severity levels of the increased citations tend to be minor rather than major.
We introduce a new framework that facilitates term structure modeling with both positive interest rates and flexible time-series dynamics but that is also tractable, meaning amenable to quick and robust estimation. Using both simulations and U.S. historical data, we compare our approach with benchmark Gaussian, stochastic volatility, and shadow rate models, where the latter enforces positive interest rates.
Application Programming Interface (APIs) have increasingly become crucial to digital ecosystems, facilitating interconnectivity and data exchange essential for digital transformation and open innovation in today's business landscape. In this article, we introduce a perspective on how APIs can be viewed as a means of achieving a dynamic equilibrium between centralization and decentralization for value creation in business ecosystems.
We examine the relationship between MIDAS regressions and the estimation of state space models applied to mixed frequency data. While in some cases the binding function is known, in general it is not, and therefore indirect inference is called for. The approach is appealing when we consider state space models which feature stochastic volatility, or other non-Gaussian and nonlinear settings where maximum likelihood methods require computationally demanding approximate filters.