Theory

The timing of talent acquisition is a central decision for new ventures. On one hand, hiring after demand is proven minimizes losses. On the other hand, hiring before demand is proven allows new ventures to start developing unique capabilities. We resolve this tension by proposing that the timing depends on human resource redeployability. We test our theory with the population of Finnish ventures, showing that portfolio entrepreneurs hire more employees early on because of higher redeployment potential and that they hire employees with more transferable skills in order to benefit from the redeployment option. To probe our mechanisms, we examine how talent acquisition strategies in portfolio and standalone ventures vary with external conditions that reduce or amplify the benefits of redeployment.

Paper · Forbes summary

Entrepreneurship research has traditionally emphasized the human capital of founders and founding teams. Yet as startups scale, their performance increasingly depends on how they attract, organize, develop, and retain talent. We argue that startup labor markets provide a unifying strategic lens for understanding how ventures build organizational capabilities under uncertainty. We organize this perspective around three structural features of startups: uncertainty about product-market fit, resource and reputational scarcity, and high failure risk. These structural features generate distinctive labor market frictions that shape hiring, compensation, job design, learning, and mobility for both startups and workers. We conclude by outlining a research agenda and showing how a labor market perspective advances strategic entrepreneurship by reframing venture scaling as the strategic organization of human capital under uncertainty.

Paper

We use census data on all Finnish firms during the period from 1996 to 2020 to study the impact of within-family CEO transitions on firm productivity. More specifically, we investigate how successions by the previous CEO’s children and other relatives affect productivity compared to successions by nonfamily CEOs. We further explore how top management team human capital (excluding the CEO) interacts with within-family CEO transitions to affect productivity. In line with prior research, we find a negative effect of family succession on productivity. Extending prior literature, we find the productivity penalty is only significant in the first two years after the transition. We further find that management team work experience is a critical ingredient in successful within-family CEO transitions. Meanwhile, we find no effect of the CEO’s education or experience, or the management team’s education, on productivity following within-family CEO succession. Finally, we explore the mechanisms, specifically management practice changes, behind the family CEO succession penalty.

Paper

Family ties may strengthen trust and coordination within entrepreneurial teams, but their consequences for external audiences remain less understood. We examine whether sibling cofounding affects startup hiring and whether this effect is moderated by lead-founder gender. We test these questions using a preregistered two-stage LinkedIn field experiment embedded in a real hiring process, complemented by a preregistered online experiment on Prolific. The field experiment provides causal evidence that sibling cofounding reduces applicant attraction, but only conditionally: the penalty is concentrated in male-leading sibling teams, whereas female-leading sibling teams in some comparisons are even weakly preferred to comparable non-family teams. Supplementary analyses further suggest that this pattern may extend to applicant sorting: among highly educated candidates, male-led sibling teams appear less attractive, whereas female-led sibling teams appear more attractive. The online experiment replicates the same asymmetric pattern and identifies startup attractiveness as the central moderated mediator: male-leading sibling teams are penalized because they are seen as less attractive employers, with this discount accompanied by stronger boundary-related concerns and weaker assessments of professionalism and fairness. An additional analysis of Finnish register data on the population of two-founder ventures shows the same asymmetry in realized employment: sibling ventures led by a brother employ fewer people in their first five years than comparable non-family ventures, whereas those led by a sister do not. Together, these findings show that sibling cofounding does not create a uniform hiring penalty. Instead, its labor-market consequences depend critically on who leads the venture.

Paper available upon request.

When a dominant employer collapses, it releases experienced workers into the labor market all at once. We ask how the thickness of the entrepreneurial labor market for a worker’s own occupation shapes where those workers land and how well they fare afterwards. Using the collapse of Nokia’s handset business and population-wide Finnish employer–employee registers, we compare displaced workers with otherwise similar job switchers in the same occupation, local labor market, year, and age band. Where young firms account for a larger share of hiring in a worker’s occupation, displaced workers are markedly more likely to enter a startup. Their earnings fall sharply in the first year after displacement and rise substantially from the third. But the gain accrues almost entirely to those who joined established firms, not startups. A thick entrepreneurial labor market benefits displaced workers by raising their outside options generally, through competition among all local employers, rather than through the young firms themselves.

Paper available upon request.

FUND I introduces the core logic of entrepreneurial judgment. Its premise is that entrepreneurial management is not only for founders: general managers, investors, joiners, and corporate leaders all have to evaluate uncertain opportunities and mobilize resources before the answer is obvious. The course opens the black box of entrepreneurship. Where do opportunities come from? How does one move from broad market change to a specific customer problem? What makes a business model credible? What does it mean to pivot, or to redeploy resources, when reality does not match the plan?

Students move through opportunity identification, value proposition, business model design, assumption testing, opportunity evaluation, product-market fit, pivoting, and corporate entrepreneurship, building a single opportunity analysis across six short assignments. A course AI agent supports the work with formative feedback before submission. The final assessment is deliberately different: an individual exam, completed without generative AI, in which students evaluate and commercialize a given opportunity. AI improves practice during the course; the exam tests independent judgment.

New Venture Creation is the integrative capstone course in entrepreneurship for the Master in Management. It rests on the insight that entrepreneurial management skills are now essential for general managers and entrepreneurs alike, and it asks students to synthesize what they have learned across the program and apply it to building a new business. The course has two objectives: to help students understand what a business opportunity is and how it fits their own personal and professional situation, and to help them turn an idea into a revenue-generating business, whether in a startup, a corporate setting, or a family firm.

The material follows the entrepreneurial process through cases: identifying opportunities, assembling the team, raising money, testing the business model, and scaling. Teams develop and present a venture concept of their own, and the course includes a startup event that puts students in front of practicing founders. By the end, students should be able to generate and evaluate ideas, design a value-creating business model, prioritize and test the assumptions behind it, anticipate resource constraints, stage the building of a business sensibly, and sell the idea to the people whose support it needs.

Analysis of Business Problems in the MBA and Critical Business Thinking in the Master in Management are the same course: the case-method course at the core of both programs, and for many students their introduction to the case method itself. Its premise is that in an era when AI can produce an instant answer to almost any question, the ability to think critically, exercise judgment, and decide has become more valuable, not less. Most business problems are unstructured: they mix economic, technical, and human issues, and they have no single correct solution. Working through them is the core of what managers actually do.

Each session is a different real problem in a different company and industry, worked through a structured methodology: diagnose the problem, establish the criteria that should govern the decision, generate the real alternatives, analyze, choose, and build an action plan naming the people who will carry it out. The course also trains three complementary perspectives on any situation, economic, organizational, and personal. The final assessment is an individual report on a case the student has never seen, written under time pressure in the last session, because that is the condition under which managers usually have to decide. An AI teaching assistant built around the methodology helps students prepare and improve their own notes without supplying answers.