Reasoning With Case Studies: Issues Of An Aging Workforce

Case studies are an ideal research approach to generate in-depth and contextualized data. Many specific data collection approaches can be incorporated to gather data through a case study, but the information so gathered is interpreted in terms of a single case. When a set of case studies is conducted on a particular research theme, the question arises as to what kinds of inferences can be made with a small number of cases. Problems of inference are increased when the cases have been selected opportunistically or haphazardly and when the universe of all potential cases cannot readily be defined. Charles Ragin has distinguished between the logic of multivariate analysis and the logic of comparative case analysis. Drawing on this distinction, this article will describe the ways in which inferences can be drawn, and the nature of such inferences, from a multiple case study approach. Reasoning from multiple case studies is an inductive process that uses comparisons to generate hypotheses and to provide limited tests through the principle of falsification. This approach was used in developing a synthesizing report based on seven large case studies from the project, “Issues of an Aging Workforce.” Five Canadian and two American case studies were conducted in corporate settings in different economic sectors. The case studies used qualitative methods (focus groups and key informant interviews) and survey data from employees and managers. Thus, the logic of multivariate analysis was used, along with inductive reasoning with qualitative data, within cases, and a logic of comparative case analysis when seeking to make and test generalizations based on the set of seven cases.