Wieczynski, JonataLucca, GiancarloBorges, Eduardo N.Pereira Dimuro, GraçalizLourenzutti, RodolfoBustince Sola, Humberto2023-09-282023-09-282022Wieczynski, J., Lucca, G., Borges, E., Dimuro, G., Lourenzutti, R., & Bustince, H. (2022). Application and comparison of cc-integrals in business group decision making. En J. Filipe, M. Śmiałek, A. Brodsky, & S. Hammoudi (Eds.), Enterprise Information Systems (Vol. 455, pp. 129-148). Springer International Publishing. https://doi.org/10.1007/978-3-031-08965-7_7978-3-031-08964-010.1007/978-3-031-08965-7_7https://academica-e.unavarra.es/handle/2454/46427Optimized decisions is required by businesses (analysts) if they want to stay open. Even thought some of these are from the knowhow of the managers/executives, most of them can be described mathematically and solved (semi)-optimally by computers. The Group Modular Choquet Random Technique for Order of Preference by Similarity to Ideal Solution (GMC-RTOPSIS) is a Multi-Criteria Decision Making (MCDM) that was developed as a method to optimize the later types of problems, by being able to work with multiple heterogeneous data types and interaction among different criteria. On the other hand the Choquet integral is widely used in various fields, such as brain-computer interfaces and classification problems. With the introduction of the CC-integrals, this study presents the GMC-RTOPSIS method with CC-integrals. We applied 30 different CC-integrals in the method and analyzed its results using 3 different methods. We found that by modifying the decisionmaking method we allow for more flexibility and certainty in the choosing process.application/pdfeng© 2022 Springer Nature Switzerland AG.CC-integralDecision makingGeneralized choquet integralGMC-RTOPSISinfo:eu-repo/semantics/conferenceObject2023-09-26info:eu-repo/semantics/openAccess