Journal of Business Venturing Insights最新文献

Scholars have long called for moving beyond a narrow focus on average performance toward a more direct investigation of the variance in performance. While a few studies have evaluated star entrepreneurs, most empirical research continues to focus on average performers. This lacuna has constrained not only the development of theories but also the accumulation of data on the distribution of performance. In response, this study uses simulations and heuristics to extract distributional information from descriptive statistics commonly reported in published research (i.e., mean, standard deviation, and sample size). Applying this approach to studies recently published in high-impact entrepreneurship journals shows that (a) the suggested methodology can provide rough estimates of the skew and shape of performance distributions, and (b) right-skewed, heavy-tailed distributions featuring star performers are ubiquitous in entrepreneurship, thus reinforcing calls for more direct studies of performance distributions in entrepreneurship.

Extant literature has typically drawn from the behavioral theory of the firm (BTOF) to examine new product introductions in the context of well-established companies. This paper extends the behavioral theory of the firm to entrepreneurial firms and argues that jointly considering founders' dispositional optimism together with the performance feedback promises to yield a better understanding of new product introductions in new ventures. We analyze a longitudinal dataset on the activities of 344 newly founded high technology ventures in the United States. The key insight of our study is that when BTOF is applied to the context of nascent, entrepreneurial ventures, the personality and dispositional characteristics of the entrepreneur must be considered. Specifically, we find that performance attainment discrepancy leads to new product introductions, but only when the entrepreneur's dispositional optimism level is high.

While emerging evidence suggests that bricolage may contribute to new venture internationalization by helping overcome situations of resource scarcity, the limitations or “dark side” of bricolage have been overlooked. We present a competitive mediation framework, in which bricolage is hypothesized to have both (1) a positive effect on new venture internationalization through innovativeness and international aspirations, as well as (2) a negative effect through operating costs and international aspirations. Using a sample of 344 Australian new ventures from the four-year longitudinal CAUSEE study, the results support our hypotheses. Over time, however, the negative effect dissipates and only the positive mediated effect remains. Our work contributes quantitative evidence of competing mediation mechanisms to largely exploratory research on bricolage and internationalization and answers calls for longitudinal examinations of new venture internationalization. In doing so, we join a broader conversation on the complex relationship between bricolage and new venture outcomes and point out opportunities for further research on new venture internationalization.

As the demand for seed accelerators grows, so does the complexity of their evaluations of numerous startup applications. This paper introduces a novel two-phase data-driven framework for startup performance prediction. Phase 1 extracts founding team-level and venture-level features applicable to early-stage startups for success prediction. Phase 2 further engineers cohort-level features to predict the success of accelerator-admitted startups. We demonstrate the utility of our framework by leveraging machine learning methods coupled with real-world data of 35,647 startups (accelerator intakes: 763). We achieve high predictive accuracy and produce explainable results. We make methodological contributions to startup competitor detection and industry categorization. The key insight of our study is that member success largely depends on cohort-level features such as shared industries with different members and industry similarity to the accelerator's past portfolio.

In this paper, we study the spatial implications of digital entrepreneurship. Leveraging detailed micro-data on the universe of new venture formations in Germany between 2011 and 2018, we illustrate regional determinants of digital entrepreneurship. Unlike conventional entrepreneurship, digital entrepreneurship demonstrates sustained growth rates throughout this time period, highlighting the policy importance of understanding the drivers of digital ventures’ location choices. The key insight of our study is that digital entrepreneurship requires both digital infrastructure and highly-skilled human capital. If both are present, digital entrepreneurship can flourish in rural areas, even if digital venture formations generally concentrate in urban centers.

Accelerators are gaining popularity in the entrepreneurship ecosystem for accelerating new ventures by providing benefits such as learning, sorting, and signaling. However, theoretical tension exists about whether these benefits are contingent on quality of institutions. The institutional-void view suggests that accelerator benefits are more pronounced in countries with weak institutions, while the institutional-support view posits the importance of strong institutions for realizing the benefits of accelerators. In this study, we theorize and test the moderating role of institutions in assessing the impact of accelerators on new venture performance using a generalized difference-indifferences technique on a worldwide accelerator database. At the baseline, the findings are consistent with previous literature, which shows a positive impact of accelerators on new ventures performance. More importantly, the key insight of our study is that the positive impact of accelerators is higher in countries with stronger institutions, thus favoring the institutional-support view. These findings contribute to emerging empirical research that assesses the impact of business accelerators on new venture performance.