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Investing in Data Quality for High-Impact Entrepreneurship Research

  • Markku Maula*
  • , Tomasz Mickiewicz
  • , Silvio Vismara
  • , Johan Wiklund
  • *Corresponding author for this work
  • Aalto-universitetet
  • Università degli studi di Bergamo
  • Syracuse University

Research output: Contribution to journalEditorialpeer-review

Abstract

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.
Original languageEnglish
Pages (from-to)1-27
JournalEntrepreneurship Theory and Practice
DOIs
Publication statusE-pub ahead of print - 6 Apr 2026

Keywords

  • Entrepreneurship
  • Research methods
  • Data
  • Identification
  • Transparency
  • Reproducibility

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