Abstract
This work presents a preservation model of production engineers’ tacit knowledge of Data Envelopment Analysis (DEA). Their expertise was explicitly coded into a computer system, and the model was developed by applying techniques and procedures from the fields of engineering and knowledge management. Technology transfer enables to solve the problem of selecting criteria and interpreting results with DEA techniques, when the efficiency of similar organizations is compared using an efficient frontier derived from non-parametric approximations of such techniques. Misunderstanding the techniques leads to misinterpretations of DEA results. This model was created by applying Knowledge Engineering, which enables to preserve and extend specific experiences and expertise in time by means of computer solutions. The model had an efficient and positive impact on strategic self-learning processes for the community interested in production engineering, knowledge transfer and management.
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Montoya-Quintero, D.M., Larrea-Serna, O.L., Jiménez-Builes, J.A. (2021). Technology Transfer from a Tacit Knowledge Conservation Model into Explicit Knowledge in the Field of Data Envelopment Analysis. In: Zapata-Cortes, J.A., Alor-Hernández, G., Sánchez-Ramírez, C., García-Alcaraz, J.L. (eds) New Perspectives on Enterprise Decision-Making Applying Artificial Intelligence Techniques. Studies in Computational Intelligence, vol 966. Springer, Cham. https://doi.org/10.1007/978-3-030-71115-3_9
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