Modeling and Simulation - The insight delivering tool for innovation

The main purpose of this article is to comprehend the performance through the state of research of innovation to account for the characteristics of the findings on the criteria of modeling and simulation regarding the field. A literature review is the tool chosen for the collection of data and devel...

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Fecha de publicación:
2017
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Universidad del Rosario
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Repositorio EdocUR - U. Rosario
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spa
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oai:repository.urosario.edu.co:10336/13573
Acceso en línea:
https://doi.org/10.48713/10336_13573
http://repository.urosario.edu.co/handle/10336/13573
Palabra clave:
Innovation
Literature review
Simulation
Modeling
Administración general
Negocios internacionales
Administración de empresas
Administración -- Métodos de simulación
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License
Abierto (Texto Completo)
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oai_identifier_str oai:repository.urosario.edu.co:10336/13573
network_acronym_str EDOCUR2
network_name_str Repositorio EdocUR - U. Rosario
repository_id_str
dc.title.spa.fl_str_mv Modeling and Simulation - The insight delivering tool for innovation
title Modeling and Simulation - The insight delivering tool for innovation
spellingShingle Modeling and Simulation - The insight delivering tool for innovation
Innovation
Literature review
Simulation
Modeling
Administración general
Negocios internacionales
Administración de empresas
Administración -- Métodos de simulación
title_short Modeling and Simulation - The insight delivering tool for innovation
title_full Modeling and Simulation - The insight delivering tool for innovation
title_fullStr Modeling and Simulation - The insight delivering tool for innovation
title_full_unstemmed Modeling and Simulation - The insight delivering tool for innovation
title_sort Modeling and Simulation - The insight delivering tool for innovation
dc.contributor.advisor.none.fl_str_mv Pulgarín Molina, Sergio Andrés
dc.subject.spa.fl_str_mv Innovation
Literature review
Simulation
Modeling
topic Innovation
Literature review
Simulation
Modeling
Administración general
Negocios internacionales
Administración de empresas
Administración -- Métodos de simulación
dc.subject.ddc.none.fl_str_mv Administración general
dc.subject.lemb.spa.fl_str_mv Negocios internacionales
Administración de empresas
Administración -- Métodos de simulación
description The main purpose of this article is to comprehend the performance through the state of research of innovation to account for the characteristics of the findings on the criteria of modeling and simulation regarding the field. A literature review is the tool chosen for the collection of data and development of this paper. A search was established to identify the existing literature using modeling, simulation and innovation as key words. After a thorough revision it was identified that what has been written in the field may be classified in the following categories: diffusion; networks, collaborations and communities, and validation of models and simulation, thus the performance will be approached from these angles. Taking into account how researchers from different areas of knowledge implement them as helpful tools to grasp innovation processes, it becomes evident in this paper that modeling and simulation have implications as an insight delivering tool by contributing to a comprehensive approach of how autonomous various uncertainties of a complex system are ultimately inter-reliant. This paper fulfils an identified need to understand the characterization that modeling and simulation have given to the field of innovation up to date.
publishDate 2017
dc.date.accessioned.none.fl_str_mv 2017-07-25T13:36:38Z
dc.date.available.none.fl_str_mv 2017-07-25T13:36:38Z
dc.date.created.none.fl_str_mv 2017-07-18
dc.date.issued.none.fl_str_mv 2017
dc.type.eng.fl_str_mv bachelorThesis
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_7a1f
dc.type.spa.spa.fl_str_mv Trabajo de grado
dc.identifier.doi.none.fl_str_mv https://doi.org/10.48713/10336_13573
dc.identifier.uri.none.fl_str_mv http://repository.urosario.edu.co/handle/10336/13573
url https://doi.org/10.48713/10336_13573
http://repository.urosario.edu.co/handle/10336/13573
dc.language.iso.none.fl_str_mv spa
language spa
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.acceso.spa.fl_str_mv Abierto (Texto Completo)
dc.rights.cc.spa.fl_str_mv Atribución-NoComercial-SinDerivadas 2.5 Colombia
Atribución-SinDerivadas 2.5 Colombia
dc.rights.uri.none.fl_str_mv http://creativecommons.org/licenses/by-nd/2.5/co/
rights_invalid_str_mv Abierto (Texto Completo)
Atribución-NoComercial-SinDerivadas 2.5 Colombia
Atribución-SinDerivadas 2.5 Colombia
http://creativecommons.org/licenses/by-nd/2.5/co/
http://purl.org/coar/access_right/c_abf2
dc.format.mimetype.none.fl_str_mv application/pdf
dc.publisher.spa.fl_str_mv Universidad del Rosario
dc.publisher.department.spa.fl_str_mv Facultad de administración
dc.publisher.program.spa.fl_str_mv Administrador de negocios internacionales
institution Universidad del Rosario
dc.source.bibliographicCitation.none.fl_str_mv Ahrweiler, P., Gilbert, N. and Pyka, A. (2010). Agency and structure: a social simulation of knowledge-intensive industries. Computational and Mathematical Organization Theory, 17(1), pp.59-76.
Alexander, L., Lameez and van Knippenberg, D. (2014). Teams in Pursuit of Radical Innovation: A Goal Orientation Perspective. Academy of Management Review, 39(4), pp.423-438.
Almirall, E., and Casadesus-Masanell, R. (2010). Open versus Closed Innovation: A Model of Discovery and Divergence. The Academy of Management Review, 35(1), 27-47. Retrieved from: http://www.jstor.org/stable/27760039
Argyris, C. and Schön, D. (1996). “Organizational Learning: A Theory of Action Perspective”, Addison-Wesley, Reading, MA
Audretsch, D. (1995). “Innovation and Industry Evolution”, The MIT Press, Cambridge, MA.
Beckenbach, F., Daskalakis, M. and Hofmann D. (2012). “Agent-based modeling of novelty creating behavior and sectoral growth effects—Linking the creative and the destructive side of innovation”, J Evol Econ 22, pp. 513–542.
Cevikarslan, S. (2013). “Heterogeneity in innovation strategies, evolving consumer preferences and market structure: An evolutionary multi-agent based modeling approach”. UNU- MERIT, Maastricht
Chandler, G. and Hanks, S. (1998). “An Investigation of New Venture Teams in Emerging Businesses”, Babson College, Wellesley, MA.
Chang, M. and Harrington, J. Jr. (2006). “Agent-Based Models of Organizations”, Handbook of Computational Economics, Vol. 2, Agent-Based Computational Economics, ed. Kenneth L. Judd and Leigh Tesfatsion. Amsterdam: North-Holland.
Cooper, A. and Bruno, A. (1997) “Success among high-technology firms”, Business Horizons
Dawid, H. (2006). “Agent-based Models of Innovation and Technological Change”, Handbook of Computational Economics. Tesfatsion L, Judd K (Eds) 2: Agent-Based Computational Economics. North-Holland, pp. 1235-1272.
Doutriaux, J. (1992). “Emerging high-tech firms: how durable are their comparative start-up advantages?”, Journal of Business Venturing 7, pp. 303–322.
Duffy, J. (2006). “Agent-based models and human subject experiments”, Handbook of Computational Economics. Tesfatsion L, Judd K (Eds) 2: Agent-Based Computational Economics. North-Holland.
Feeser, H. and Willard, G. (1989). “Incubator and performance: a comparison of high and low growth high tech firms”, Journal of Business Venturing 4, pp. 429-442.
Freeman, C. (1994). “The economics of technical change”, Cambridge Journal of Economics 18, pp. 463–514.
Garcia, R. (2005). “Uses of agent-based modeling in innovation/new product development research”. Journal of Product Innovation and Management 22 (5).
Garcia, R. and Jager, W., (2011). “Special issue on agent-based modeling of innovation diffusion”, J. Product Innov. Manage. 28(2), pp. 146–318.
Gay, B. and Dousset, B. (2005). “Innovation and network structural dynamics: Study of the alliance network of a major sector of the biotechnology industry”, Research Policy 34, pp. 1457–1475
Gilbert, G. Pyka, A. and Ahrweiler, P. (2010). “Agent-based modeling of innovation networks: the fairytale of spillover”, Innovation networks: new approaches in modeling and analyzing. Springer Verlag, pp. 101-126.
Gilbert, G. and Troitzsch, K. (2005). Simulation for the social scientist. 1st ed. Maidenhead, England: Open University Press.
Gilbert, N. Pyka, A. and Ahrweiler, P. (2001). “Innovation networks–– a simulation approach”, Journal of Artificial Societies and Social Simulation 4 (3). Retrieved from: http://www.soc.sur- rey.ac.uk/JASSS/4/3/8.html.
Gilbert, N., Ahrweiler, P. and Pyka A. (2010). “Learning in innovation networks: Some simulation experiments”. P Ahrweiler (Ed), Innnovation in complex social systems. London: Routledge.
Gilbert, N., Jager, W., Deffuant, G. and Adjali, I. (2007). “Complexities in markets: Introduction to the special issue”. Journal of Business Research 60 (8).
Gonzalez-Avella, J., Cosenza, M., Klemm, K., Eguluz, V. and San Miguel, M. (2007). “Information feedback and mass media effects in cultural dynamics”, J. Artif. Soc. Soc. Simul. 10(3).
Higgins, J. and Green, S. (2008). Cochrane handbook for systematic reviews of interventions. 1st ed. Chichester, England: Wiley-Blackwell.
Jaffe, A., Newell, R. and Stavins, R. (2003). “Technological change and the environment”, Mäler K. and Vincent J. (ed) Handbook of environmental economics. Elsevier Science BV, Amsterdam, pp 461–516.
Janssen, M. (2009). “Understanding artificial Anasazi”. J. Artificial Society. Soc. Simul. 12, pp. A244–A260.
Jiang, Z. and Hao, Y. (2011) “Game analysis of technology innovation alliance stability based on knowledge transfer”, Computational and Mathematical Organization Theory; Dordrecht19.4, pp. 403-421.
Kauffman, S. and Macready, W. (1995). “Technological evolution and adaptive organizations”, Complexity 1 (2), pp. 26–43.
Ma, T. and Nakamori Y. (2005). “Agent-based modeling on technological innovation as an evolutionary process”, European Journal of Operational Research 166, pp. 741–755.
Maddison, A. (1991). “Dynamic Forces in Capitalist Development: A Long-Run Comparative View”, University Press, Oxford.
Millington, J. and Wainwright, J. (2016). “Comparative Approaches for Innovation in Agent-Based Modeling of Landscape Change”. LAND, 5(2), 13.
Nan, N., Zmud, R. and Yetgin, E. (2013). A complex adaptive systems perspective of innovation diffusion: an integrated theory and validated virtual laboratory. Computational and Mathematical Organization Theory, 20(1), pp.52-88.
Pfeifer, T., Schmitt, R. and Voigt, T. (2005), “Managing change: quality-oriented design of strategic change processes”, The TQM Magazine, Vol. 17 No. 4, pp. 297-308
Pourdehnad, J., Maani, K.E. and Sedehi, H. (2002), "System dynamics and intelligent agent-based simulation: where is the synergy?", Proceedings of the 20th International Conference of the System Dynamics Society.
Pulgarín, S. (2013). “Hacia un Modelo explicativo del proceso innovador para los centros universitarios de emprendimiento de la ciudad de Bogotá: Una aproximación desde las exaptaciones y la diversidad”, 1st ed. [ebook] Bogotá: Universidad del Rosario. Available at: http://www.urosario.edu.co/Escuela-de-Administracion/Investigacion/Documentos/Linea-de-Investigacion-en-Emprendimiento-e-Innovac/Hacia-un-modelo-explicativo-del-proceso-innovador/
Rycroft, R and Kash, D. (1999) “The Complexity Challenge”, Technological Innovation for the 21st Century, Pinter, London.
Sahal, D. (1981). “Patterns of Technological Innovation”, Addison- Wesley Pub. Co., Advanced Book Program/World Science Division, 1981.
Schwarz, N. and Ernst, A. (2010). “Agent-based modeling of the diffusion of environmental innovations—an empirical approach”, Technol. Forecast. Soc. Change 76, pp. 497-511
Shibanai, Y., Yasuno, S. and Ishiguro, I., (2001). “Effects of global information feedback on diversity: Extensions to Axelrod’s adaptive culture model”, J. Conflict Res. 45(1), pp. 80–96.
Squazzoni, F. (2010). “The impact of agent-based models in the social sciences after 15 years of incursions”, Hist. Econ. Ideas VVIII, pp. 197–233.
Thurston, P. (1986), “When Partners Fall Out”, Harvard Business Review.
Univerisdad del Rosario (n.d). Como escribir fichas de lectura y reseñas. Retrieved from: http://www.urosario.edu.co/cienciashumanas/Documentos/Nuevas-guias-academicas/Como-escribir-fichas-de-lectura-y-resenas.pdf
Watts, D. and Dodds, P. (2007). “Influentials, networks, and public opinion formation”, J. Consumer Res. 34, pp. 441–458.
Werker, C., Brenner, T. (2004). “Empirical calibration of simulation models”, Papers on Economics and Evolution #0410, Max Planck Institute for Research into Economic Systems, Jena.
Weyant, J. (2011). “Accelerating the development and diffusion of new energy technologies: Beyond the ‘valley of death’”, Energy Econ. 33, pp. 674–682.
Wu, D., Kefan, X., Hua, L., Shi, Z., Olson, D. (2010). “Modeling technological innovation risks of an entrepreneurial team using system dynamics: An agent-based perspective”, Technological Forecasting & Social Change 77, pp. 957-869.
Ziman, J. (2000). “Evolutionary Models for Technological Change”, Technological Innovation as an Evolutionary Process, Cambridge University Press, pp. 3–12.
Zou, G. and Yilmaz, L. (2010). Dynamics of knowledge creation in global participatory science communities: open innovation communities from a network perspective. Computational and Mathematical Organization Theory, 17(1), pp.35-58
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spelling Pulgarín Molina, Sergio Andrés80165821600Echenique, DanielaAdministrador de Negocios Internacionales05bd724f-556e-40a6-b655-0fc52168cd71-12017-07-25T13:36:38Z2017-07-25T13:36:38Z2017-07-182017The main purpose of this article is to comprehend the performance through the state of research of innovation to account for the characteristics of the findings on the criteria of modeling and simulation regarding the field. A literature review is the tool chosen for the collection of data and development of this paper. A search was established to identify the existing literature using modeling, simulation and innovation as key words. After a thorough revision it was identified that what has been written in the field may be classified in the following categories: diffusion; networks, collaborations and communities, and validation of models and simulation, thus the performance will be approached from these angles. Taking into account how researchers from different areas of knowledge implement them as helpful tools to grasp innovation processes, it becomes evident in this paper that modeling and simulation have implications as an insight delivering tool by contributing to a comprehensive approach of how autonomous various uncertainties of a complex system are ultimately inter-reliant. This paper fulfils an identified need to understand the characterization that modeling and simulation have given to the field of innovation up to date.application/pdfhttps://doi.org/10.48713/10336_13573 http://repository.urosario.edu.co/handle/10336/13573spaUniversidad del RosarioFacultad de administraciónAdministrador de negocios internacionalesAbierto (Texto Completo)Atribución-NoComercial-SinDerivadas 2.5 ColombiaAtribución-SinDerivadas 2.5 ColombiaEL AUTOR, manifiesta que la obra objeto de la presente autorización es original y la realizó sin violar o usurpar derechos de autor de terceros, por lo tanto la obra es de exclusiva autoría y tiene la titularidad sobre la misma. PARGRAFO: En caso de presentarse cualquier reclamación o acción por parte de un tercero en cuanto a los derechos de autor sobre la obra en cuestión, EL AUTOR, asumirá toda la responsabilidad, y saldrá en defensa de los derechos aquí autorizados; para todos los efectos la universidad actúa como un tercero de buena fe. EL AUTOR, autoriza a LA UNIVERSIDAD DEL ROSARIO, para que en los términos establecidos en la Ley 23 de 1982, Ley 44 de 1993, Decisión andina 351 de 1993, Decreto 460 de 1995 y demás normas generales sobre la materia, utilice y use la obra objeto de la presente autorización. -------------------------------------- POLITICA DE TRATAMIENTO DE DATOS PERSONALES. Declaro que autorizo previa y de forma informada el tratamiento de mis datos personales por parte de LA UNIVERSIDAD DEL ROSARIO para fines académicos y en aplicación de convenios con terceros o servicios conexos con actividades propias de la academia, con estricto cumplimiento de los principios de ley. Para el correcto ejercicio de mi derecho de habeas data cuento con la cuenta de correo habeasdata@urosario.edu.co, donde previa identificación podré solicitar la consulta, corrección y supresión de mis datos.http://creativecommons.org/licenses/by-nd/2.5/co/http://purl.org/coar/access_right/c_abf2Ahrweiler, P., Gilbert, N. and Pyka, A. (2010). Agency and structure: a social simulation of knowledge-intensive industries. Computational and Mathematical Organization Theory, 17(1), pp.59-76.Alexander, L., Lameez and van Knippenberg, D. (2014). Teams in Pursuit of Radical Innovation: A Goal Orientation Perspective. Academy of Management Review, 39(4), pp.423-438.Almirall, E., and Casadesus-Masanell, R. (2010). Open versus Closed Innovation: A Model of Discovery and Divergence. The Academy of Management Review, 35(1), 27-47. Retrieved from: http://www.jstor.org/stable/27760039Argyris, C. and Schön, D. (1996). “Organizational Learning: A Theory of Action Perspective”, Addison-Wesley, Reading, MAAudretsch, D. (1995). “Innovation and Industry Evolution”, The MIT Press, Cambridge, MA.Beckenbach, F., Daskalakis, M. and Hofmann D. (2012). “Agent-based modeling of novelty creating behavior and sectoral growth effects—Linking the creative and the destructive side of innovation”, J Evol Econ 22, pp. 513–542.Cevikarslan, S. (2013). “Heterogeneity in innovation strategies, evolving consumer preferences and market structure: An evolutionary multi-agent based modeling approach”. UNU- MERIT, MaastrichtChandler, G. and Hanks, S. (1998). “An Investigation of New Venture Teams in Emerging Businesses”, Babson College, Wellesley, MA.Chang, M. and Harrington, J. Jr. (2006). “Agent-Based Models of Organizations”, Handbook of Computational Economics, Vol. 2, Agent-Based Computational Economics, ed. Kenneth L. Judd and Leigh Tesfatsion. Amsterdam: North-Holland.Cooper, A. and Bruno, A. (1997) “Success among high-technology firms”, Business HorizonsDawid, H. (2006). “Agent-based Models of Innovation and Technological Change”, Handbook of Computational Economics. Tesfatsion L, Judd K (Eds) 2: Agent-Based Computational Economics. North-Holland, pp. 1235-1272.Doutriaux, J. (1992). “Emerging high-tech firms: how durable are their comparative start-up advantages?”, Journal of Business Venturing 7, pp. 303–322.Duffy, J. (2006). “Agent-based models and human subject experiments”, Handbook of Computational Economics. Tesfatsion L, Judd K (Eds) 2: Agent-Based Computational Economics. North-Holland.Feeser, H. and Willard, G. (1989). “Incubator and performance: a comparison of high and low growth high tech firms”, Journal of Business Venturing 4, pp. 429-442.Freeman, C. (1994). “The economics of technical change”, Cambridge Journal of Economics 18, pp. 463–514.Garcia, R. (2005). “Uses of agent-based modeling in innovation/new product development research”. Journal of Product Innovation and Management 22 (5).Garcia, R. and Jager, W., (2011). “Special issue on agent-based modeling of innovation diffusion”, J. Product Innov. Manage. 28(2), pp. 146–318.Gay, B. and Dousset, B. (2005). “Innovation and network structural dynamics: Study of the alliance network of a major sector of the biotechnology industry”, Research Policy 34, pp. 1457–1475Gilbert, G. Pyka, A. and Ahrweiler, P. (2010). “Agent-based modeling of innovation networks: the fairytale of spillover”, Innovation networks: new approaches in modeling and analyzing. Springer Verlag, pp. 101-126.Gilbert, G. and Troitzsch, K. (2005). Simulation for the social scientist. 1st ed. Maidenhead, England: Open University Press.Gilbert, N. Pyka, A. and Ahrweiler, P. (2001). “Innovation networks–– a simulation approach”, Journal of Artificial Societies and Social Simulation 4 (3). Retrieved from: http://www.soc.sur- rey.ac.uk/JASSS/4/3/8.html.Gilbert, N., Ahrweiler, P. and Pyka A. (2010). “Learning in innovation networks: Some simulation experiments”. P Ahrweiler (Ed), Innnovation in complex social systems. London: Routledge.Gilbert, N., Jager, W., Deffuant, G. and Adjali, I. (2007). “Complexities in markets: Introduction to the special issue”. Journal of Business Research 60 (8).Gonzalez-Avella, J., Cosenza, M., Klemm, K., Eguluz, V. and San Miguel, M. (2007). “Information feedback and mass media effects in cultural dynamics”, J. Artif. Soc. Soc. Simul. 10(3).Higgins, J. and Green, S. (2008). Cochrane handbook for systematic reviews of interventions. 1st ed. Chichester, England: Wiley-Blackwell.Jaffe, A., Newell, R. and Stavins, R. (2003). “Technological change and the environment”, Mäler K. and Vincent J. (ed) Handbook of environmental economics. Elsevier Science BV, Amsterdam, pp 461–516.Janssen, M. (2009). “Understanding artificial Anasazi”. J. Artificial Society. Soc. Simul. 12, pp. A244–A260.Jiang, Z. and Hao, Y. (2011) “Game analysis of technology innovation alliance stability based on knowledge transfer”, Computational and Mathematical Organization Theory; Dordrecht19.4, pp. 403-421.Kauffman, S. and Macready, W. (1995). “Technological evolution and adaptive organizations”, Complexity 1 (2), pp. 26–43.Ma, T. and Nakamori Y. (2005). “Agent-based modeling on technological innovation as an evolutionary process”, European Journal of Operational Research 166, pp. 741–755.Maddison, A. (1991). “Dynamic Forces in Capitalist Development: A Long-Run Comparative View”, University Press, Oxford.Millington, J. and Wainwright, J. (2016). “Comparative Approaches for Innovation in Agent-Based Modeling of Landscape Change”. LAND, 5(2), 13.Nan, N., Zmud, R. and Yetgin, E. (2013). A complex adaptive systems perspective of innovation diffusion: an integrated theory and validated virtual laboratory. Computational and Mathematical Organization Theory, 20(1), pp.52-88.Pfeifer, T., Schmitt, R. and Voigt, T. (2005), “Managing change: quality-oriented design of strategic change processes”, The TQM Magazine, Vol. 17 No. 4, pp. 297-308Pourdehnad, J., Maani, K.E. and Sedehi, H. (2002), "System dynamics and intelligent agent-based simulation: where is the synergy?", Proceedings of the 20th International Conference of the System Dynamics Society.Pulgarín, S. (2013). “Hacia un Modelo explicativo del proceso innovador para los centros universitarios de emprendimiento de la ciudad de Bogotá: Una aproximación desde las exaptaciones y la diversidad”, 1st ed. [ebook] Bogotá: Universidad del Rosario. Available at: http://www.urosario.edu.co/Escuela-de-Administracion/Investigacion/Documentos/Linea-de-Investigacion-en-Emprendimiento-e-Innovac/Hacia-un-modelo-explicativo-del-proceso-innovador/Rycroft, R and Kash, D. (1999) “The Complexity Challenge”, Technological Innovation for the 21st Century, Pinter, London.Sahal, D. (1981). “Patterns of Technological Innovation”, Addison- Wesley Pub. Co., Advanced Book Program/World Science Division, 1981.Schwarz, N. and Ernst, A. (2010). “Agent-based modeling of the diffusion of environmental innovations—an empirical approach”, Technol. Forecast. Soc. Change 76, pp. 497-511Shibanai, Y., Yasuno, S. and Ishiguro, I., (2001). “Effects of global information feedback on diversity: Extensions to Axelrod’s adaptive culture model”, J. Conflict Res. 45(1), pp. 80–96.Squazzoni, F. (2010). “The impact of agent-based models in the social sciences after 15 years of incursions”, Hist. Econ. Ideas VVIII, pp. 197–233.Thurston, P. (1986), “When Partners Fall Out”, Harvard Business Review.Univerisdad del Rosario (n.d). Como escribir fichas de lectura y reseñas. Retrieved from: http://www.urosario.edu.co/cienciashumanas/Documentos/Nuevas-guias-academicas/Como-escribir-fichas-de-lectura-y-resenas.pdfWatts, D. and Dodds, P. (2007). “Influentials, networks, and public opinion formation”, J. Consumer Res. 34, pp. 441–458.Werker, C., Brenner, T. (2004). “Empirical calibration of simulation models”, Papers on Economics and Evolution #0410, Max Planck Institute for Research into Economic Systems, Jena.Weyant, J. (2011). “Accelerating the development and diffusion of new energy technologies: Beyond the ‘valley of death’”, Energy Econ. 33, pp. 674–682.Wu, D., Kefan, X., Hua, L., Shi, Z., Olson, D. (2010). “Modeling technological innovation risks of an entrepreneurial team using system dynamics: An agent-based perspective”, Technological Forecasting & Social Change 77, pp. 957-869.Ziman, J. (2000). “Evolutionary Models for Technological Change”, Technological Innovation as an Evolutionary Process, Cambridge University Press, pp. 3–12.Zou, G. and Yilmaz, L. (2010). Dynamics of knowledge creation in global participatory science communities: open innovation communities from a network perspective. 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