SimulLinova: Uma Ferramenta de Simulação para Avaliação da Evolução de Ganhos com Inovação
Keywords:
Inovação, Simulação, Algoritmos Evolutivos.Abstract
Este artigo apresenta os detalhes de um sistema computacional, SimuLInova, desenvolvido para ser um ambiente de testes e simulação, que representa de forma detalhada o processo de co-evolução inovativa em rede. Os modelos utilizados para a elaboração do sistema foram os grafos assimétricos, os algoritmos evolutivos e os modelos de agentes. Mostra-se aqui como o sistema reproduz um cenário de interação de empresas, a partir da definição de métricas de absorção, que estabelecem claramente a forma como um indivíduo aprende em rede. Foi adaptado um método evolutivo similar ao algoritmo genético, para preencher os requisitos de evolução de um ambiente de inovação.Downloads
References
AHUJA, Gautam. Collaboration networks, structural holes, and innovation: A longitudinal study. Admin-istrative science quarterly, v. 45, n. 3, p. 425-455, 2000.
ALLEN, Robert C. Collective invention. Journal of Economic Behavior & Organization, v. 4, n. 1, p. 1-24, 1983.
ARIFOVIC, Jasmina "Genetic Drift in a Model With Strategic Complementarities," Computing in Eco-nomics and Finance 2000 370, Society for Computational Economics 2000.
ARIFOVIC, Jasmina; KARAIVANOV, Alexander. "Evolutionary Learning in a Principal-Agent Model," Meeting Papers 505, Society for Economic Dynamics, 2006.
BACK, T. Evolutionary Algorithms in Theory and Practice, Oxford University Press, 1996
BANZHAF, W., NORDIN, P., KELLER, R. E., FRANCONE, F. D. Genetic Programming: An Introduction. Morgan Kaufmann, Inc., San Francisco, USA, 1998.
BIRCHENHALL, Chris. Modular Technical Change and Genetic Algorithms, Computational Economics, vol. 8, issue 3, pages 233-253, 1995
BOAVENTURA NETTO, P.O., Grafos: teoria, modelos, algoritmos. Editora Edgard Blücher, 4ª ED. 2006.
BURT, Ronald S. Structural holes and good ideas1. American journal of sociology, v. 110, n. 2, p. 349-399, 2004.
BURT, Ronald S. Social contagion and innovation: Cohesion versus structural equivalence. American Journal of Sociology, p. 1287-1335, 1987.
COHEN, Wesley M.; LEVINTHAL, Daniel A. Innovation and learning: the two faces of R & D. The eco-nomic journal, p. 569-596, 1989.
COLEMAN, James Samuel et al (INCLUIR OS DEMAIS). Medical innovation: A diffusion study. Indianap-olis: Bobbs-Merrill Company, 1966.
DAWID, Herbert; REIMANN, Marc; BULLNHEIMER, Bernd. To innovate or not to innovate? IEEE Trans. Evolutionary Computation, pp 471-481 - 2001
DOSI, Giovanni. Sources, procedures, and microeconomic effects of innovation. Journal of economic literature, p. 1120-1171, 1988.
EDQUIST, Charles (Ed.). Systems of innovation: technologies, institutions and organizations. Psychol-ogy Press, 1997.
EIBEN, A.E. Multiparent recombination, In T. Back, D.B. Fogel, and Z. Michalewicz, editors, Evolutionary Computation 1: Basic Algorithms and Operators, pages 289-307, Institute of Physics Publishing, 2000.
FOGEL, L. J., OWENS AJ, and WALSH, MJ "Artificial Intelligence Through a Simulation of Evolution," Chap-ter 14 of Biophysics and Cybernetic Sciences Symposium, edited by M. Maxfield, A. Callahan, and L. J. Fogel, Spartan Book Co., Washington, D.C., pages 131-155.
FOGEL, David B. Evolutionary Computation: The Fossil Record. New York: IEEE Press. 1998.
FLEMING, Lee; MARX, Matt. Managing Creativity in Small Worlds. California Management Review, v. 48, n. 4, 2006.
FLEMING, Lee. Recombinant uncertainty in technological search. Management science, v. 47, n. 1, p. 117-132, 2001.
GILBERT, N. A simulation of the structure of academic science' Sociological Research Online vol. 2(2), 1997.
GILBERT, Nigel; PYKA, Andreas, AHRWEILER, Petra, Innovation Networks - A Simulation Approach. Journal of Artificial Societies and Social Simulation vol. 4, no. 3, 2001
GOLDBERG, D. The Design of Innovation, Lessons from and for Competent Genetic Algorithms. Kluwer Academic Publishers, Boston, MA, (2002).
HOLLAND J.H., Adaptation in natural and artificial system, Ann Arbor, The University of Michigan Press, 1975.
LUNDVALL, Bengt-Åke et al. National systems of production, innovation and competence building. Re-search policy, v. 31, n. 2, p. 213-231, 2002.
MALHOTRA, Arvind et al. Radical innovation without collocation: A case study at Boeing-Rocketdyne. MIS quarterly, p. 229-249, 2001.
MITCHELL, Melanie. An Introduction to Genetic Algorithms. MIT Press, 1996.
NELSON, Richard R. On the uneven evolution of human know-how. Research Policy, v. 32, n. 6, p. 909-922, 2003.
RITTER, Thomas; GEMÜNDEN, Hans Georg. Network competence: its impact on innovation success and its antecedents. Journal of Business Research, v. 56, n. 9, p. 745-755, 2003.
RIECHMANN, Thomas. "Genetic Algorithms and Economic Evolution," Computing in Economics and Finance 1999 1011, Society for Computational Economics, 1999.
SCHWEFEL, Hans-Paul. Evolution and Optimum Seeking, Wiley Interscience, New York, 1995.
TEECE, David J. Capturing value from technological innovation: Integration, strategic partnering, and licensing decisions. Interfaces, v. 18, n. 3, p. 46-61, 1988.
TODOROVA, Gergana; DURISIN, Boris. Absorptive capacity: valuing a reconceptualization. Academy of Management Review, v. 32, n. 3, p. 774-786, 2007.
WILKINSON, Ian; DEBENHAM, John, Exploitation versus Exploration in Market Competition, 2003. UNSW School of Marketing Working Paper No. 03/1. Available at SSRN: http://ssrn.com/ab-stract=387081 or http://dx.doi.org/10.2139/ssrn.387081
WOOLDRIDGE, Jeffrey M. “Introductory Econometrics: a modern approach”, Thomson: South-West-ern, 2nd edition, 2003.
WOOLDRIDGE, M.; JENNINGS, N.R. Intelligent agents: theory and practice. Knowledge Engineering Re-view, 10: 115-152, 1995.
ZAHRA, Shaker A.; GEORGE, Gerard. Absorptive capacity: A review, reconceptualization, and extension. Academy of management review, v. 27, n. 2, p. 185-203, 2002.
