Investing in Data Quality for High-Impact Entrepreneurship Research
指出高影响力创业研究依赖数据质量，但研究设计常面临相关性、有效性和可复制性之间的权衡。作者提出5I框架（投资、整合、创新、激励、影响），为作者、审稿人和编辑提供指导，以构建独特的高质量数据集。
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.