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 50th 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.
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