Stochastic cognitive mapping to build common ground for selecting cases in research projects

Abstract

Creating common ground among research groups is a prerequisite for scientifically sound case study research, especially in multi-national and multi-disciplinary research projects. Therefore, this paper proposes a new procedure for case study selection: stochastic cognitive mapping (sCM). sCM complements the previously illustrated conceptual content cognitive mapping (3CM) with email enquiry on concepts and their interconnections, simple multi-attribute rating and stochastic estimation of priorities. The procedure was applied to select case studies in a study on the role of community-based initiatives (CBIs) in societal change towards sustainability. The procedure performed well, based on project members’ evaluations, and enabled them to consistently identify a map and ranked list of criteria for selecting case initiatives. Researchers of the project had two to some extent exclusive orientations towards case selection: sampling and searching strategies, i.e. emphasis on the representativeness of a case set or on the features that interesting and useful study cases should possess. Strategies were integrated and CBIs selected through the sequence of snowball, random, and purposive samplings. Moreover, the method and the criteria list are adaptable to support comparable studies across diverse contexts.