Abstract
Innovation has considered organizations’ competitive advantage. The purpose of this study is to visualize the effects of the behavior of innovation level at innovation capability change. This work presents a fuzzy controller design using logic tables and a generalized ordered weighted averaging (GOWA) index to model the internal innovation phenomenon of manufacturing enterprises in Morelia, Michoacán, Mexico. The linguistic rules were programmed using a fuzzy design module in MATLAB software, and the controller was simulated using the Simulink tool. The results show that the values of at least two inputs have to change in order for the innovation value to change, and two static input values are enough to restrict the minimum innovation value. This paper presents an original methodology for visualizing the behavior of the internal innovation of companies based on control and fuzzy set theory that allows us to capture the dynamics of the phenomenon.
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References
Adams, R., Bessant, J., & Phelps, R. (2006). Innovation management measurement: a review. International Journal of Management Reviews, 8(1), 21–47.https://doi.org/10.1111/j.1468-2370.2006.00119.x
Alfaro-Garcia, V. G., Gil-lafuente, A. M., & Alfaro-Calderón, G. G. (2016). Quantification of the Incidence in Innovation Capacities by the Promotion of Specialized Economic Sectors. In ASME (Ed.), Lectures on Modelling and Simulation (pp. 1–10). Santiago, Chile: ASME
Alfaro-García, V. G., Gil-Lafuente, A. M., & Alfaro Calderón, G. G. (2017). A fuzzy methodology for innovation management measurement. Kybernetes, 46(1), 50–66.https://doi.org/10.1108/K-06-2016-0153
Calantone, R. J., Cavusgil, S. T., & Zhao, Y. (2002). Learning orientation, firm innovation capability, and firm performance. Industrial Marketing Management, 31(6), 515–524.
Chuen Chien, L. (1990). Fuzzy logic in control systems: Fuzzy logic controller. I. IEEE Transactions on Systems, Man, and Cybernetics, 20(2), 404–418. Retrieved from https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=52551&isnumber=1891%0A
Cornell University, INSEAD, & WIPO. (2018). The global innovation index 2018: Energizing the world with innovation. Global innovation index 2018: Energizing the world with innovation
Driankov, D., Hellendoorn, H., & Reinfrank, M. (1996). An introduction to fuzzy control. Berlin, Heidelberg: Springer. https://doi.org/10.1007/978-3-662-03284-8
Feng, G. (2006). A survey on analysis and design of model-based fuzzy control systems. IEEE Transactions on Fuzzy Systems, 14(5), 676–697. https://doi.org/10.1109/TFUZZ.2006.883415
Hooda, D. S., & Raich, V. (2017). Fuzzy logic models and fuzzy control: an introduction. Oxford, United Kingdom: Alpha Science International Ltd.
Knight, G. A., & Cavusgil, S. T. (2004). Innovation, organizational capabilities, and the born-global firm. Journal of International Business Studies, 35(2), 124–141. https://doi.org/10.1057/palgrave.jibs.8400071
Mamdani, E. H., Eng, M. S., Ph, D., & Mem, I. E. E. E. (1974). Control and science application of fuzzy algorithms for control of simple dynamic plant, 121(12), 1585–1588
OECD. (2005). Oslo manual: guidelines for collecting and interpreting innovation data, 3rd ed. The Measurement of Scientific and Technological Activities. Paris: OECD Publishing.
Schumpeter, J. A. (1934). The theory of economic development. Cambridge, MA: Harvard University Press
Valdivia-Miranda, C. (2012). Sistemas de control continuos y discretos. (M. J. López Raso, Ed.) (1a ed.). Madrid, España: Paraninfo
Venture Institute, CONACYT, & Secretaría de Economía. (2013). Índice Nacional De Innovación
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Alfaro-Calderón, G.G., Zaragoza-Ibarra, A., Alfaro-García, V.G. (2021). Fuzzy Control of Morelia’s Manufacturing Companies’ Innovation Capabilities. In: León-Castro, E., Blanco-Mesa, F., Gil-Lafuente, A.M., Merigó, J.M., Kacprzyk, J. (eds) Intelligent and Complex Systems in Economics and Business. Advances in Intelligent Systems and Computing, vol 1249. Springer, Cham. https://doi.org/10.1007/978-3-030-59191-5_6
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DOI: https://doi.org/10.1007/978-3-030-59191-5_6
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