Although the phenomenon of hybrid entrepreneurs—individuals who work in paid and self-employment simultaneously—is prevalent, the psychological well-being of hybrid entrepreneurs has not been researched systematically to date. This is unlike research on paid employment and (assumed) full-time entrepreneurship, where psychological well-being has been researched as a key factor. Using data from the United Kingdom Household Longitudinal Survey, we address this void by studying whether hybrid entrepreneurs display distinct psychological well-being patterns (measured via mental strain, job satisfaction, and life satisfaction), utilizing a comparison with full-time paid employed, full-time self-employed and individuals working in two paid jobs. We further examine whether the specific work arrangements of hybrid entrepreneurs shape their well-being. To this end, we study the changes in well-being of hybrid entrepreneurs and other individuals in the comparison groups who switch to other jobs. For this purpose, we employed matching (entropy balancing approach) to account for self-selection effects. Our results suggest that the well-being of hybrid entrepreneurs is indeed distinct and can be explained by both self-selection effects and unique aspects of their work arrangements. Our study is thus the first to deliver evidence showing that hybrid entrepreneurs need to be studied as a separate group in entrepreneurship research concerned with well-being and psychological functioning. Our results have important implications not only for future research but also for practice.

Research and public interest on economic inequality have grown over the last years. Family firms and the concentration of wealth and power in the hands of a few wealthy entrepreneurial families have been discussed as both a cause and a consequence of economic inequality. Yet, so far, we lack knowledge about the relationship between economic inequality and the prevalence of family firms in an economy. Our study investigates how the share of family-controlled public firms correlates with various measures of income and wealth inequality. The results show that a higher share of public family-controlled firms leads to more income inequality in a country. This effect is particularly pronounced for the middle of the income distribution as opposed to the top quantiles. Redistribution only mitigates this effect to some extent, as the effect is significant for market income and disposable income. We also find that a higher share of family-controlled firms contributes to an increase in wealth inequality. Our results are of economic relevance as, for instance, a one standard deviation change in the share of family-controlled firms leads to an increase of around 1.3–1.5 percentage points in the Gini coefficients for market income, disposable income, and wealth.

We map the distribution of High-Growth Firms (HGFs, or “gazelles”) across the dimensions of firm size and firm age using contour plots, where firm size and growth are measured in terms of employees. The analysis is based on Swedish total population data for the period 1990–2016, covering approximately 11, 000, 000 firm-year observations. The results show that the majority of HGFs are small, which partly follows the high representation of small firms in the population. Yet when considering the proportions of HGFs across firm ages and sizes, a distinct feature emerges in that the territory of small, old firms appears to be almost completely deserted—despite their large overall numbers—where firms in this category have the (by far) lowest chances of becoming HGFs.

Honig and Samuelsson (2014) and Delmar (2015) recently had an exchange in this journal related to a replication-and-extension attempt of two papers which originally arrived at different conclusions based on the same data set. This commentary provides further clarification on the issues and links the debate to broader issues scholarly culture and practices in entrepreneurship research. 

Ramoglou & Tsang's (R&T) article “A realist perspective of entrepreneurship: Opportunities as propensities” is a recent, potentially influential addition to the literature on “entrepreneurial opportunities”. This short communication argues that R&T's intellectual exercise largely fails to move matters forward on the two most central problems with prior research on “entrepreneurial opportunities”, namely 1) lack of construct clarity and 2) slow progress regarding how characteristics of “entrepreneurial opportunities” give shape to entrepreneurial action and outcomes. I suggest that entrepreneurship researchers should avoid the detour of conceptually dichotomizing complex and empirically non-tractable sets of external circumstances into “opportunities” vs. “non-opportunities” and instead direct attention to multi-dimensional and continuous variation in “those [evolving] entities which entrepreneurs actually evaluate and [sometimes] act upon” (and which should not be mislabeled as “opportunities”). For this endeavor, the notion of “agency-intensity” is the primary take-away from R&T's study.

McBride and Wuebker's (2022) “Social Objectivity and Entrepreneurial Opportunities” – published in Academy of Management Review and hence potentially influential – provides an improved philosophical basis for ‘creation theory’ compared to earlier attempts in that direction, and it undoubtedly reflects a considerable amount of hard work and an honest intent to make a meaningful contribution. Regrettably, it is also characterized by questionable premises, claims, and conclusions. In this article I identify and discuss these issues and explain why McBride and Wuebker may mislead our field rather than guiding it toward more productive knowledge accumulation and dissemination. I argue that much more is known about new venture creation than their narrow lens allows us to see, and that going forward based on their suggestions would lead to lopsided entrepreneurship research and education.

In their review of venture creation process research, Davidsson and Gruenhagen (2021) identified two distinct types of process research: process as a journey through qualitative changes in content and process as a directional and temporal journey toward a goal. We revisit their findings with more robust methodology and find that these two are indeed distinct, ideal types that capture two centers of gravity in process-oriented research on venture creation. We enrich the picture of these two types of process research and develop ideas for how future research can address their respective weaknesses.

Recent breakthroughs make Artificial Intelligence (AI) technology a particularly potent enabler of entrepreneurship. Therefore, we use the External Enablement (EE) framework to examine AI's potentials as enabler of entrepreneurship. In doing so, we involve AI – specifically ChatGPT 4.0 – to enhance the analysis beyond our personal limitations. Through this exercise we provide insights into 1) AI technologies as enablers of entrepreneurship; 2) possible improvements of the EE framework, and 3) ChatGPT's and similar AI tools’ usefulness for entrepreneurship research more generally.

We longitudinally examine outcomes of entrepreneurial business planning to assess effectiveness. Both data replication and extension are used to examine previously published research. Our sample consists of 623 nascent ventures that we follow for more than ten years - from 1998 to 2010. Our findings highlight the importance of data replication, data extension, and sample selection bias. We not only add to the debate regarding the merits or liabilities of planning, but also contribute to evaluating normative research and publication standards by reexamining past research using more comprehensive data and an extended time frame.

This paper continues our debate examining pertinent issues related to scholarship, in particular, whether matters related to technical rigor eclipse the importance of causality, replicability, or that of underlying statistical and methodological assumptions. We report on specific data findings to further stimulate discussion of these important matters.

For many digital ventures, acquiring financial resources in multiple rounds beyond seed funding to grow has become an important part of their entrepreneurial journey. The success rate of raising equity capital beyond their seed investments is, however, very low. Existing entrepreneurship studies on financial resource acquisition have explored separately how entrepreneurs organize their networks, establish venture legitimacy, and decide on funding sources. However, despite being identified as an important subprocess in new venture creation, little is known about why, when, and how entrepreneurs engage potential investors to increase the likelihood of post-seed investments. Hence, this paper synthesizes the literature on financial resource acquisition, theoretical concepts in entrepreneurial financing, and practice knowledge to frame a set of design principles to create a prescriptive process model to increase the likelihood of success in post-seed financial resource acquisition.

In recent years, the notion of a unicorn, a startup exceeding a premarket valuation of one billion USD, has become one of the most prominent concepts in the practical discourse of entrepreneurship. Consequently, entrepreneurs aim to build unicorns, investors want to participate in their success, policymakers strive to support their emergence, and educators present them as an ideal-type entrepreneurial activity. We challenge this view with a provocative critique of the positive mainstream perception of unicorns. First, we characterize unicorns as an ambiguous analytical category with little value for research and evidence-based policy. Second, we point to the danger of neglecting the multifaceted nature of entrepreneurship by focusing solely on extreme outliers. Third, we highlight the potentially unethical consequences of entrepreneurship's obsession with unicorns. Finally, we conclude that focusing on unicorns contributes to a biased picture of entrepreneurship that favors valuation (i.e., the unicorn) over value creation (i.e., productive entrepreneurship).

This study aims to discern the duration of venture creation processes that end in successful venture emergence as well as those ending with abandonment. Discerning duration is essential to understand a process since every process unfolds over time. However, identifying correct venture creation duration is tricky because available panel data sets in entrepreneurship are length biased toward long duration due to left truncation. In order to adjust this problem, we applied Inverse Probability Weighting (IPW) and analyzed the venture creation duration of 1673 nascent ventures in the Harmonized PSED (Panel Study of Entrepreneurial Dynamics). The weighting analyses for the duration show that the emergence chance is maximized around three months after inception of the process, implying that venture creation in the typical case is faster and simpler than previously believed. Past three months the emergence chance decreases, whereas the abandonment hazard constantly increases over time and surpasses the emergence chance after seven months. The results show that weighing strongly influences duration time estimates and also can influence other estimates based on samples using the same type of sampling mechanism. Thus we conclude that IPW should be considered for all analyses using this type of data. Our study offers a possible interpretation of the different mechanisms of emergence and abandonment and provides guidance and insights for future studies.

The purpose of this study is to estimate country-level social network properties by reproducing plausible social network structures of each country. For this purpose, we suggest and utilize a novel simulation procedure using Agent-Based Modeling and Simulation (ABMS) method and the Global Entrepreneurship Monitor (GEM) data. Specifically, we estimate two types of country-level social network properties that can be related to entrepreneurial activities, i.e. social network density and supportive surroundings in each country. For the estimation, we use a social network-related question in the GEM questionnaire – “Do you know someone personally who started a business in the past 2 years?” As a result, this study provides estimated values of the social network properties for 69 countries. In doing so, this study suggests a simulation procedure for estimating the country-level social network properties, provides estimated values of the properties that can be utilized in future studies, and proposes potential roles of the country-level social network structure as a contextual factor that can affect individuals’ entrepreneurial activities.