Abstract
Survey methodology remains a widely used data collection method in creativity and innovation management studies. However, evolving technological advancements and methodological challenges necessitate a reassessment of best practices to benefit the most from it. In this study, we conduct a comprehensive review of 311 articles that rely on survey-based research to identify critical aspects that influence data quality, including sampling strategies, response rates, construct validity and data integration. We synthesize existing recommendations and propose a structured framework that connects specific methodological challenges to best practices and examples from the literature. By distinguishing between survey research design (predata collection decisions) and survey data management (postdata collection activities), we provide guidance for scholars on ensuring methodological rigour, enhancing data reliability and improving the representativeness of findings. Finally, we offer practical examples tailored to the unique demands of creativity and innovation management research. By implementing the identified best practices, future studies can ensure the quality and impact of survey-based research in this and related fields.