Collecting large-scale comparative management data from multiple countries poses challenges in demonstrating methodological rigour, including the need for representativeness. We examine the rigour of sample representativeness, the counterbalancing effect of sample relevance, and explore sampling options, equivalence across countries, data collection procedures and response rates. We identify the challenges posed by cross-national survey data collection, and suggest that the ideal research designs presented in much of the literature might not be practical or desirable in large-scale, multi-time-point, cross-national comparative management studies because of the need to ensure relevance across such contexts. Using the example of Cranet – a large-scale, multi-time-point, cross-national survey of human resource management – we offer suggested solutions for balancing both rigour and relevance in research of this nature.
All Science Journal Classification (ASJC) codes
- General Business, Management and Accounting
- Strategy and Management
- Management of Technology and Innovation