Capturing Managerial Cognition in Chilean Wineries: Hardening a New Method to Elicit and Code Mental Models of Dynamic Systems

This paper contributes to research on mental models of dynamic systems (MMDS). MMDS research works with qualitative data that has to be elicited and analyzed to represent the MMDS as qualitative models which can be analyzed and compared by analysis tools like the “distance-ratio” method. We have revised the SD literature on collecting and analyzing qualitative data and devised an interview-based method which minimizes influence on interviewees and applies a coding process which yields a qualitative model according to the current definition of MMDS. We use exemplary data from a case study which is currently in process to show how the method is applied. We extract some observations concerning the particularity of coding for MMDS and the double competence which researchers should have. We also raise two questions for future research, dealing with the proper aggregation level of MMDS and with the unknown amount of researcher influence that a MMDS can resist without bias