Abstract
The determination of the strategic cognitive factors that intervene in the Second Order Change (SOC) are fundamental to achieve the transformation of organizational systems [6]. This work proposes a methodology based on the Fuzzy Cognitive Maps (FCM) model and the Forgotten Effects (FE) model, for the formalization and identification of these factors that intervene in the inference matrix. The inclusion of FE allows reducing inference errors in the matrix. The objective being to give certainty to the inference matrix in its state of reliability when applying FE, with the trade-off that this model only handles positive elements in the analysis matrix. This condition requires, first, to separate the elements into two matrices, one containing positive elements and the other, negative ones. The negative-element matrix is then temporarily transformed into a state of positive elements so that both matrices can operate the fuzzification-inferential-defuzzification process in the FE model [34, 16]. Once the matrices have been defuzzified, the matrix of temporarily positive elements returns to its original (negative) state and, finally, both matrices are added to obtain an adjusted inference matrix so it can be applied to the FCM model. A case study is presented where the main objective is to find the cognitive factors that intervene in the behavior of four companies’ staff, starting the procedure with two factors highly correlated: Stress Tolerance and Impulse Control. The main results represent the metrics of the absolute Hamming distances, laying the foundations for the formalization of the cognitive factors that hinder a SOC.
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Chávez, R., González, F., Alcaraz, V., Ramos, J.R. (2022). Strategic Diagnostics of Stress and Impulse Control for Second Order Change: Inclusion of Forgotten Effects in Diffuse Cognitive Maps. In: León-Castro, E., Blanco-Mesa, F., Alfaro-García, V., Gil-Lafuente, A.M., Merigó, J.M., Kacprzyk, J. (eds) Soft Computing and Fuzzy Methodologies in Innovation Management and Sustainability. Lecture Notes in Networks and Systems, vol 337. Springer, Cham. https://doi.org/10.1007/978-3-030-96150-3_5
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