Academic conferences are popular platforms for academicians to share their research with colleagues, get feedback, and stay up to date on recent academic studies. Conferences also provide opportunities for the participants to express themselves, expand their network, and become socialized. However, academicians are forced to choose a limited number of conferences to participate due to several different factors such as time required for preparing a research, traveling and lodging expenses, and conference fees. At this multi-criteria decision problem, relevant factors can be used to evaluate the alternatives (i.e., academic conferences to participate) and prioritization of these factors would be necessary in advance. To address this issue, this study suggests an improved fuzzy cognitive mapping (FCM) approach to analyze factors affecting the choice of academic conferences to participate. The classical FCM allows to observe the dynamic behavior of complex systems during time. While the approach is widely used in different areas, it has considerable drawbacks: (i) producing same steady state values under different initial conditions and (ii) yielding completely different steady state values when different threshold functions are used. The new approach provides a mathematical formulation that produces steady state values sensitive to initial conditions. Since the selection of the threshold function in classical FCM is a highly subjective choice, the proposed approach offers an alternative way to obtain comparable values.