Issues with data collection methods in construction management research

The effectiveness of data collection is vital to the overall quality of research. A review of data collection methods was carried out on construction management research to establish trends. A survey was administered to a sample of 650 housing associations using two data collection tools, the traditional postal survey and a web-based survey. Response rates, and the dimensions of time and cost were compared to measure the effectiveness of each method. The web is a relatively untapped resource for construction management research. Literature on web surveys argues the advantages in terms of reduced time and cost and potentially higher response rates. It is suggested that it could assist in making data available quicker, cheaper and in greater quantities. This can only be a benefit to research. A review of ARCOM proceedings, Refereed Journals and Postgraduate research shows limited utilisation of the web as a research tool. The range of data collection methods commonly adopted in both quantitative and qualitative research was identified. There is a common theme of low response rates which may lead to less than rigorous analysis. The results of the survey comparison illustrate the differences between a traditional approach to data collection and the use of modern technology. There are concerns in the use of the web in research. Sample selection and traceability become less controllable. Access to the web is traditionally seen as a limitation to participation. These factors are being addressed by the new web technology and obstacles to the use of the web are slowly being removed. The approach to data collection is fundamental to the conclusions that may be drawn from a piece of research. In understanding the mechanisms associated with data collection researchers are able to use modern technology to take the drudgery out of the process. Potentially more time can be spent in designing research and analysing the results than is typically spent in collecting data.