ETP at 50: The Past, Present and Future of Entrepreneurship Research

 

Journal:
Entrepreneurship Theory and Practice (forthcoming)


Summary:
Entrepreneurship research has over-invested in borrowed theories and under-invested in the evidence needed to test them, and the field’s future depends on rebalancing around the research question-design-data trio—a shift that AI makes both possible and urgent.


Research Questions:
1. How has the evolution of entrepreneurship research from relevance-driven cataloguing through theory-driven legitimacy-seeking shaped the field's current strengths and weaknesses?
2. What rebalancing of priorities—toward important questions, appropriate research designs, and high-quality data—is needed to advance the field’s next phase of development?
3. How does the rise of AI intensify the need for this rebalancing by automating the theoretical positioning that journals have historically rewarded?


What we know:
Entrepreneurship Theory and Practice turns fifty this year, having grown from one of only two English-language journals in the field to one of the most influential business journals worldwide. The field followed a path from early descriptive work documenting entrepreneurial phenomena, through a legitimacy era that elevated theoretical contribution as the primary criterion for publication, to its current standing. Along the way, the field developed a persistent over-investment in imported theory and under-investment in the evidence needed to test it. This matters because the reward structure—emphasizing theoretical novelty over evidentiary quality—shapes what scholars produce, what doctoral students learn, and ultimately what the field can credibly claim to know.


Novel Findings:
The editorial identifies a fundamental misalignment in entrepreneurship research’s reward structure: the field learned to reward the appearance of theoretical contribution—novelty of framing, density of citation, elaborate conceptual architecture—over the substance of genuine explanation. It shows that the field’s most enduring theoretical contributions (effectuation, bricolage, entrepreneurial action theory) emerged not from importing frameworks but from close engagement with entrepreneurial phenomena. A review of articles published in JBV and ETP in 2024–2025 reveals that over half of JBV articles and a quarter of ETP articles offered no explicit practical implications. Meanwhile, Overton data show that 74 of 194 ETP papers (2020–2022) were cited in policy documents, suggesting policy impact is a byproduct of getting the question-design-data combination right rather than a separate goal. The editorial argues that AI forces a reckoning: when machines can generate elaborate theoretical front ends, the distinctive value of scholarship must relocate to the question, design and evidence.


Novel Methodology:
This is a reflective editorial rather than an empirical study. It traces the field’s fifty-year intellectual trajectory through three phases—relevance-driven cataloguing, theory-driven legitimacy-seeking, and an emerging rebalancing around evidentiary quality—drawing on the author’s nine-year tenure as ETP Editor-in-Chief. It integrates arguments from two companion editorials on data quality (Maula et al.) and prescriptive theorizing (Shepherd & Wiklund) into a unified case for reordering the field’s priorities.


Implications for Practice:
When research credibly identifies mechanisms with practical stakes for identifiable actors, scholars can move from explanation to prescription. The editorial calls for prescriptive theorizing that identifies who has agency to act, specifies desired outcomes, grounds recommendations in demonstrated mechanisms, and formulates testable prescriptions—replacing the generic "entrepreneurs should consider..." language that currently pervades practical implications sections.


Implications for Policy:
Policy impact emerges as a byproduct of good science rather than a separate goal. ETP data show that papers combining important questions with credible evidence are cited in policy documents at rates that stand out compared to other business journals, without any deliberate policy strategy. Policymakers need to understand how things work; they do not need researchers to tell them what to do.


Implications for Society:
The field’s willingness to follow important questions rather than disciplinary boundaries remains its greatest strength. As entrepreneurship research matures, its ability to export ideas to other disciplines—rather than merely importing them—determines whether the scholarly community can address the societal phenomena that depend on entrepreneurship, from innovation and job creation to inclusion and wellbeing.


Implications for Research:
The editorial calls for a reordering of priorities: question first, design second, data third, theory as the product of getting those three right. AI makes this urgent—when elaborate theoretical front ends can be machine-generated, the distinctive value of scholarship must reside in the question, the design and the evidence. Doctoral education should privilege proximity to phenomena and skill in research design over theoretical positioning and literature mapping. The field should invest in indigenous theory-building, registered reports, replication studies and collaborative data infrastructure.


Full Citation:
Wiklund, J. (forthcoming). ETP at 50: The past, present, and future of entrepreneurship research. Entrepreneurship Theory and Practice.


Abstract:
Entrepreneurship scholars have over-invested in borrowed theories and under-invested in the evidence needed to test them–or to build something better. This editorial, written on the occasion of ETP’s fiftieth anniversary and my departure as Editor-in-Chief, argues for a rebalancing around the research question-design-data trio: important questions rooted in phenomena, designs matched to claims and serious investment in data quality. The field’s greatest strength has always been its willingness to ask important questions, and its most enduring theoretical contributions come from developing home-grown theories addressing these questions rather than importing frameworks from outside. AI makes this rebalancing urgent. When the front end of a paper can be generated by a machine, the distinctive value of scholarship must reside in the question, the design, and the evidence. The field’s future depends on producing work that reveals how entrepreneurship actually works, and on exporting those insights rather than merely importing ideas from other disciplines.