Frédéric DELMAR

Understanding variability is a key focus in many areas of psychological research, with growing interest in modeling individual- and group-level variability. Although multilevel models such as heterogeneous variance models (HVMs) and Mixed-Effects Location-Scale models have been used to capture these dynamics, they typically rely on linear assumptions and restrict temporal changes in variability to a single level. Recent calls for nonlinear approaches in psychology highlight the need for more flexible models that can better account for complex, dynamic processes. This article introduces the use of Gaussian processes (GPs) within the framework of HVMs to address these limitations. By incorporating GPs in HVMs, we allow for the modeling of nonlinear variability across multiple levels, including temporal dynamics at both the individual and group levels. We demonstrate the benefits of this approach in two empirical applications. Our findings show that using GPs provides an improved model fit compared with traditional linear methods and highlight the utility of GPs in variance modeling, offering new possibilities for studying dynamic and emergent processes in psychological and social science research.

Management theories and models aim to predict future states and outcomes. Yet, as management scholars, we often tend to prioritise model fit metrics over prediction and forecasting, assuming that strong model fit inherently leads to accurate predictions. We challenge this assumption, arguing that an exclusive focus on model fit can yield theories that fail to generalise to new datasets, thereby limiting their forecasting accuracy and practical relevance. In a systematic review of 6,514 studies, we find a pronounced dominance of model fit approaches. Model fit metrics are susceptible to overfitting, where models capture noise rather than patterns, and underfitting, where key relationships are overlooked. Both problems undermine predictive performance. Drawing on insights from operations research, we apply newly developed forecasting metrics to address these limitations. Empirically examining the gender gap and motherhood penalty in returns from employment and entrepreneurship, we demonstrate how these metrics can complement traditional fit measures. By integrating multiple assessment metrics, we offer a comprehensive framework for improving both predictive accuracy and theoretical development in management research. We provide the Stata syntax that scholars can download and use to assess the forecasting ability of their models.

We introduce a new model to address three methodological biases in research on new venture growth and survival. The model offers entrepreneurship scholars numerous benefits. The biases are identified using a systematic review of 96 papers using longitudinal data published over a period of 20 years. They are: (1) distributional properties of new ventures; (2) selection bias; and (3) causal asymmetry. The biases make the popular use of normal distribution models problematic. As a potential solution, we introduce and test an event magnitude regression model approach (EMM). In this two-stage model, the first model explores the probability of four events: a firm staying the same size, expanding, contracting, or exiting. In the second stage, if the firm contracts or expands, we estimate the magnitude of the change. A suggested benefit is that researchers can better separate the likelihood of an event from its magnitude, thereby opening new avenues for research. We provide an overview of our model analyzing an example data set involving longitudinal venture level data. We provide a new package for the statistical software R. Our findings show that EMM outperforms the widely adopted normal distribution model. We discuss the benefits and consequences of our model, identify areas for future research, and offer recommendations for research practice.

We investigate how potential co-founders' perceptions of a founder's obsessive passion (OP) influence the decision to join a venture team. Using a conjoint experiment with a primary sample of 116 founder-entrepreneurs and validating it with an additional sample of 59 founder entrepreneurs, we found that potential co-founders were more likely to join if they perceived that the founder had OP for developing ventures. Potential co-founders were less likely to join if they perceived OP for founding ventures. Further, we found significant interactions between perceived OPs, as well as interactions between perceived OP and potential co-founders' own OP.

This chapter present a research project dedicated to better understand how new venture teams work together to achieve desired outcomes. Teams, as opposed to an individual, start a majority of all innovative new ventures. Yet, little research or theory exists in new venture settings about how members interact with each other over time—teamwork—to produce innovative technologies, products, and services. We believe a systematic study of social and psychological processes that underlie new venture teamwork and venture outcomes is timely and important. Unique features of our research project include: (1) a team level focus on social and psychological processes, to assess relations to proximal (e.g., innovation, first sales and team satisfaction), and distal value creation outcomes (e.g., sales growth, raised capital and profits); (2) Combined qualitative and quantitative research methodologies to provide both theory building and theory testing for the relations of interest; and (3) A time-sequential design with data collection every three months over one year to allow us to investigate the relations of interest for new ventures.

The 2019 Global Award for Entrepreneurship Research has been awarded to Professor Boyan Jovanovic at New York University in the USA. Boyan Jovanovic has developed pioneering research that advances our understanding of the competitive dynamics between incumbent firms and new entrants, entrepreneurial learning and selection processes, and the importance of entrepreneurship for the economy. Key perspectives in his research are that the entrepreneur makes employment choices based on the comparative advantage of his or her skills and that entrepreneurial firms are vehicles of technological change and knowledge diffusion that influence industry dynamics and, in turn, economic growth.

Denna artikel presenterar 2019 års pristagare av Global Award for Entrepreneurship Research – Boyan Jovanovic – och vilka bidrag han har gjort inom entreprenörskapsforskningen. Även om Jovanovic är en välkänd och välciterad ekonom inom akademin är måhända hans explicita bidrag inom entreprenörskapsforskningen inte lika välkända. Jovanovic har bidragit till en ökad förståelse av vem som egentligen blir entreprenör och entreprenörskapets betydelse för såväl företagsstruktur som innovationskraft och ekonomisk tillväxt.

Research Summary: To prevent loss of control post‐IPO, founder‐CEOs can implement control‐enhancing mechanisms disconnecting ownership from voting rights. However, this decision places them in a rich versus king dilemma. If they choose to implement such mechanisms and secure the king position, they risk losing money at IPO. If they choose not to implement control‐enhancing mechanisms and adopt the rich position they risk losing control over the firm. We investigate theoretically and empirically the outcomes of this dilemma in a multi‐period setting (at IPO and post‐IPO). We found that the majority of founder‐CEOs who choose the king option recover initial wealth loss, and hence, they can reconcile the rich and king paths in the long‐run post‐IPO., Managerial Summary: Founder‐CEOs often use control‐enhancing mechanisms (CEMs), such dual class shares, pyramid control structures, and pact agreements, to maintain control over their IPO firms. In this study, we investigate the effects of these CEMs on firm value at IPO and post‐IPO using a unique hand‐collected dataset comprising all founder‐CEO led firms that went public on French regulated markets between January 1992 and December 2010. We found that most founder‐CEOs who use multiple CEMs leave considerable amounts of money on the table at IPO date but they are able to recover their initial loss 5 years post‐IPO. This result suggests that an IPO may constitute a valuable financing alternative even for founder‐CEOs who value control.

This study examines how multiple blockholder structures affect family firm performance. Building on arguments from both principal–principal agency and familiness perspectives, we suggest that asymmetrical distribution of voting power among family and nonfamily blockholders hurts firm performance. Further, we suggest that the larger the number of blockholder types, the stronger the negative effect of voting-power asymmetry among family and nonfamily blockholders on firm performance. We provide empirical support for our hypotheses using a longitudinal sample of 413 French family firms over the 1992–2012 period.

Although training and development is recognized as an important means to nurture corporate entrepreneurs in organizations, extant research has focused primarily on efforts to develop entrepreneurial leaders and nurture business creation in a school or university setting. We report on the findings of an inductive case study of corporate entrepreneurship training in a large multinational corporation. We explore the learning outcomes which participants experienced, and outline how an action learning approach enabled these learning outcomes. Our emergent model of corporate entrepreneurship training is based on an episodic view of training, recognizing that individual, group and situational influences, need to be considered if a more complete understanding of what makes for effective training in this domain is to be developed.