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Investing in Data Quality for High-Impact Entrepreneurship Research

Markku Maula¹; Tomasz Mickiewicz²; Silvio Vismara^3,4; Johan Wiklund⁵

¹ Department of Industrial Engineering and Management Aalto University Espoo Finland · ² Economics, Finance and Entrepreneurship Department, Aston University, Birmingham, West Midlands, UK · ³ Department of Management University of Bergamo Bergamo Italy · ⁴ IMT School for Advanced Studies Lucca, Lucca, Italy · ⁵ Whitman School of Management Syracuse University Syracuse New York USA

High-impact entrepreneurship research stands or falls with data quality. Yet research design and data collection choices often force researchers into trade-offs among relevance, validity, and replicability. Reliance on existing databases constrains the questions we can study, while primary data collection to address new questions often struggles to deliver high-quality, large, and representative samples. Increasingly, the most tangible contributions come from unique, high-quality data that answer novel, important questions. We present a 5I framework (Invest, Integrate, Innovate, Incentivize, Impact), offering guidance for authors, reviewers, and editors to navigate these trade-offs and build unique datasets that enable relevant, valid, and replicable research.

DOI

10.1177/10422587261435916

Volume

50 (5)

Pages

1295-1321

Language

en

Export

BibTeX

Sources

crossref