Metodología para evaluar el impacto de estrategias orientadas a incentivar la difusión de innovaciones energéticas limpias a partir de la influencia social

dc.contributorFranco Cardona, Carlos Jaime
dc.contributorCadavid Higuita, Diana Lorena
dc.contributorUniversidad Nacional de Colombia - Sede Medellín
dc.contributorSistemas Energéticos
dc.creatorArdila Franco, Laura Andrea
dc.date.accessioned2020-09-11T19:32:42Z
dc.date.accessioned2022-09-21T14:24:12Z
dc.date.available2020-09-11T19:32:42Z
dc.date.available2022-09-21T14:24:12Z
dc.date.created2020-09-11T19:32:42Z
dc.date.issued2020-08-06
dc.identifierArdila, Laura. 2020. «Metodología para evaluar el impacto de estrategias orientadas a incentivar la difusión de innovaciones energéticas limpias a partir de la influencia social». Universidad Nacional de Colombia, Medellin.
dc.identifierL. Ardila, «Metodología para evaluar el impacto de estrategias orientadas a incentivar la difusión de innovaciones energéticas limpias a partir de la influencia social», Universidad Nacional de Colombia, Medellin, 2020.
dc.identifierArdila, L., 2020. Metodología para evaluar el impacto de estrategias orientadas a incentivar la difusión de innovaciones energéticas limpias a partir de la influencia social. Universidad Nacional de Colombia, Medellin.
dc.identifierArdila, L. Metodología para evaluar el impacto de estrategias orientadas a incentivar la difusión de innovaciones energéticas limpias a partir de la influencia social. (Universidad Nacional de Colombia, 2020).
dc.identifierArdila L. Metodología para evaluar el impacto de estrategias orientadas a incentivar la difusión de innovaciones energéticas limpias a partir de la influencia social. [Medellin]: Universidad Nacional de Colombia; 2020.
dc.identifierhttps://repositorio.unal.edu.co/handle/unal/78451
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/3365798
dc.description.abstractEl análisis de los mecanismos que permitan incentivar la difusión de innovaciones energéticas limpias es un tópico actual de investigación. A pesar de que en la literatura es posible identificar trabajos que han modelado la toma de decisiones e influencia social en el proceso de difusión, aún hace falta incorporar elementos de racionalidad limitada a las teorías, usar modelos de difusión en aplicaciones prácticas para industrias específicas y analizar a profundidad el impacto de la estructura de la red sobre el proceso de difusión. En esta Tesis de doctorado se presenta una metodología desarrollada para evaluar el impacto de estrategias orientadas a incentivar la difusión de innovaciones energéticas limpias a partir de la influencia social. La metodología consta de 4 Fases: Definición del problema, Configuración del modelo de simulación, Análisis de resultados, y Evaluación de las estrategias de influencia social. El desarrollo secuencial de estas etapas permite al tomador de decisiones realizar un análisis completo de las estrategias consideradas facilitando la comparación de los resultados de forma cualitativa y cuantitativa. Los resultados de esta investigación están orientados al desarrollo de nuevo conocimiento, a un mayor entendimiento del fenómeno de difusión de innovaciones energéticas limpias y a la aplicación de la metodología desarrollada a casos concretos con innovaciones diferentes en países distintos lo que demuestra que es un instrumento que trasciende a las aplicaciones locales y puede ser usado en diversos escenarios.
dc.description.abstractThe analysis of the mechanisms that allow to encourage the diffusion of clean energy innovations is a current research topic. Although in the literature it is possible to identify works that have shaped decision-making and social influence in the diffusion process, it is still necessary to incorporate elements of limited rationality into theories, use diffusion models in practical applications for specific industries, and analyze in depth the impact of the network structure on the diffusion process. In this PhD thesis, a methodology developed to evaluate the impact of strategies oriented to incentivize the diffusion of clean energy innovations based on social influence is presented. The methodology consists of 4 Phases: Definition of the problem, Configuration of the simulation model, Analysis of results, and Evaluation of the strategies of social influence. The sequential development of these stages allows the decision maker to carry out a complete analysis of the strategies considered, facilitating the comparison of the results in a qualitative and quantitative way. The results of this research are oriented to the development of new knowledge, to a better understanding of the phenomenon of diffusion of clean energy innovations and to the application of the methodology developed to specific cases with different innovations in different countries, which shows that it is an instrument that transcends to local applications and can be used in various scenarios.
dc.languagespa
dc.publisherMedellín - Minas - Doctorado en Ingeniería - Sistemas
dc.publisherUniversidad Nacional de Colombia - Sede Medellín
dc.relationAbar, Sameera, Georgios K. Theodoropoulos, Pierre Lemarinier, and Gregory M.P. O’Hare 2017 Agent Based Modelling and Simulation Tools: A Review of the State-of-Art Software. Computer Science Review 24: 13–33.
dc.relationAdams, Richard, Sally Jeanrenaud, John Bessant, David Denyer, and Patrick Overy 2016 Sustainability-Oriented Innovation: A Systematic Review: Sustainability-Oriented Innovation. International Journal of Management Reviews 18(2): 180–205.
dc.relationAhmad, Amreen, Tanvir Ahmad, and Abhishek Bhatt 2020 HWSMCB: A Community-Based Hybrid Approach for Identifying Influential Nodes in the Social Network. Physica A: Statistical Mechanics and Its Applications 545: 123590.
dc.relationAjzen, Icek 1991 The Theory of Planned Behavior. Organizational Behavior and Human Decision Processes 50(2): 179–211.
dc.relationAllan, C. 2014 Diffusion of Green Technology: A Survey. International Review of Environmental and Resource Economics 7(1): 1–33.
dc.relationAlyousef, Ammar, Adedamola Adepetu, and Hermann de Meer 2017 Analysis and Model-Based Predictions of Solar PV and Battery Adoption in Germany: An Agent-Based Approach. Computer Science - Research and Development 32(1–2): 211–223.
dc.relationANDI, and FENALCO 2018 Informe de vehículos eléctricos e híbridos a Diciembre de 2017. Bogotá.
dc.relationANDI, and FENALCO 2019 Informe de vehículos eléctricos e híbridos a Diciembre de 2018. Bogotá.
dc.relationANDI, and FENALCO 2020a Informe de vehículos eléctricos e híbridos a Diciembre de 2019. Bogotá.
dc.relationANDI, and FENALCO 2020b Informe de vehículos eléctricos e híbridos a Marzo 2020. Bogotá.
dc.relationÁrea Metropolitana del Valle de Aburra, Empresas Públicas de Medellín E.S.P, and Empresa de Transporte Masivo del Valle de Aburrá Limitada 2015 Convenio Marco de Cooperación Interinstitucional CT-2015-000783 En EPM - CM200 de 2015 En El ÁREA - CN2015-0195 En El Metro.
dc.relationÁrea Metropolitana del Valle de Aburra, Empresas Públicas de Medellín E.S.P, Empresa de Transporte Masivo del Valle de Aburrá Limitada, Municipio de Medellín, and Metroplus S.A 2016 Otrosí No. 01 Del Convenio Marco de Cooperación Interinstitucional.
dc.relationÁrea Metropolitana del Valle de Aburra, Empresas Públicas de Medellín E.S.P, Empresa de Transporte Masivo del Valle de Aburrá Limitada, Municipio de Medellín, and Metroplus S.A 2017 Otrosí No. 02 Del Convenio Marco de Cooperación Interinstitucional.
dc.relationÁrea Metropolitana del Valle de Aburra, Empresas Públicas de Medellín E.S.P, Empresa de Transporte Masivo del Valle de Aburrá Limitada, Municipio de Medellín, and Metroplus S.A 2019 Modificación al Otrosí No. 02 Del Convenio Marco de Cooperación Interinstitucional.
dc.relationAscarza, Eva, Peter Ebbes, Oded Netzer, and Matthew Danielson 2017 Beyond the Target Customer: Social Effects of Customer Relationship Management Campaigns. Journal of Marketing Research 54(3): 347–363.
dc.relationBakshy, Eytan, Jake M. Hofman, Winter A. Mason, and Duncan J. Watts 2011 Everyone’s an Influencer: Quantifying Influence on Twitter. In Proceedings of the Fourth ACM International Conference on Web Search and Data Mining - WSDM ’11 P. 65. Hong Kong, China: ACM Press. http://portal.acm.org/citation.cfm?doid=1935826.1935845, accessed March 15, 2020.
dc.relationBalci, Osman 1994 Validation, Verification, and Testing Techniques throughout the Life Cycle of a Simulation Study. Annals of Operations Research 53(1): 121–173.
dc.relationBehdani, Behzad 2012 Evaluation of Paradigms for Modeling Supply Chains as Complex Socio-Technical Systems. In Simulation Conference (WSC), Proceedings of the 2012 Winter Pp. 1–15.
dc.relationBhimani, Hardik, Anne-Laure Mention, and Pierre-Jean Barlatier 2019 Social Media and Innovation: A Systematic Literature Review and Future Research Directions. Technological Forecasting and Social Change 144: 251–269.
dc.relationBohlmann, Jonathan D., Roger J. Calantone, and Meng Zhao 2010 The Effects of Market Network Heterogeneity on Innovation Diffusion: An Agent-Based Modeling Approach: The Effects of Market Network Heterogeneity on Innovation Diffusion. Journal of Product Innovation Management 27(5): 741–760.
dc.relationBossomaier, Terry R. J., and David G. Green 2000 Complex Systems. Cambridge : New York, NY, USA: Cambridge University Press.
dc.relationBrown, Maxwell 2013 Catching the PHEVer: Simulating Electric Vehicle Diffusion with an Agent-Based Mixed Logit Model of Vehicle Choice. Journal of Artificial Societies and Social Simulation 16(2).
dc.relationBstieler, Ludwig, Thomas Gruen, Billur Akdeniz, et al. 2018 Emerging Research Themes in Innovation and New Product Development: Insights from the 2017 PDMA‐UNH Doctoral Consortium. Journal of Product Innovation Management 35(3): 300–307.
dc.relationBurt, Ronald S. 1987 Social Contagion and Innovation: Cohesion versus Structural Equivalence. American Journal of Sociology 92(6). JSTOR, University of Chicago Press: 1287–1335.
dc.relationByrka, Katarzyna 2009 Attitude-Behavior Consistency:Campbell’s Paradigm in Environmental and Health Domains. Technische Universiteit Eindhoven. http://repository.tue.nl/642840, accessed July 26, 2019.
dc.relationByrka, Katarzyna, Arkadiusz Jȩdrzejewski, Katarzyna Sznajd-Weron, and Rafał Weron 2016 Difficulty Is Critical: The Importance of Social Factors in Modeling Diffusion of Green Products and Practices. Renewable and Sustainable Energy Reviews 62: 723–735.
dc.relationCadavid, Lorena 2015 Aproximación Metodológica al Análisis de La Difusión de Innovaciones En Productos Que Utilizan Tecnologías Limpias Considerando Elecciones Individuales de Adopción. Universidad Nacional de Colombia.
dc.relationCampbell, Donald T. 1963 Social Attitudes and Other Acquired Behavioral Dispositions. In Psychology: A Study of a Science. Study II. Empirical Substructure and Relations with Other Sciences. Volume 6. Investigations of Man as Socius: Their Place in Psychology and the Social Sciences. Pp. 94–172. New York: McGraw-Hill. http://content.apa.org/books/10590-003, accessed February 6, 2019.
dc.relationCannarella, C, and V Piccioni 2008 Innovation Diffusion and Architecture and Dynamics of Local Territorial Networks. Trames. Journal of the Humanities and Social Sciences 12(2): 215.
dc.relationCao, Jinjian, Chul Hun Choi, and Fu Zhao 2017 Agent-Based Modeling of the Adoption of High-Efficiency Lighting in the Residential Sector. Sustainable Energy Technologies and Assessments 19: 70–78.
dc.relationCarrington, Peter J., John Scott, and Stanley Wasserman, eds. 2005 Models and Methods in Social Network Analysis. 1st edition. Cambridge University Press. https://www.cambridge.org/core/product/identifier/9780511811395/type/book, accessed March 8, 2020.
dc.relationChen, T, and L Chai 2010 Attitude towards the Enviroment and Green Products: Consumer’s Perspective. Management Science and Engineering 4(2): 27–39.
dc.relationCheng, Hsiang-Lin 2010 Seeking Knowledge or Gaining Legitimacy? Role of Social Networks on New Practice Adoption by OEM Suppliers. Journal of Business Research 63(8): 824–831.
dc.relationChoi, Hanool, Sang-Hoon Kim, and Jeho Lee 2010 Role of Network Structure and Network Effects in Diffusion of Innovations. Industrial Marketing Management 39(1): 170–177.
dc.relationCiudad Luz 2018 Propuesta Técinca Proyecto - Barrios Solares Providencia. Santiago de Chile: Ciudad Luz.
dc.relationClausen, Jens, and Klaus Fichter 2019 The Diffusion of Environmental Product and Service Innovations: Driving and Inhibiting Factors. Environmental Innovation and Societal Transitions 31: 64–95.
dc.relationComuna Energética 2014 Comunas Con Estrategias Energéticas Locales - Providencia. Santiago de Chile: Ministerio de Energía de Chile. http://www.minenergia.cl/comunaenergetica/?p=841.
dc.relationCongreso de la República 2017 Ley 1844 de 2017. http://www.secretariasenado.gov.co/senado/basedoc/ley_1844_2017.html.
dc.relationDearing, James W. 2009 Applying Diffusion of Innovation Theory to Intervention Development. Research on Social Work Practice 19(5): 503–518.
dc.relationDeffuant, Guillaume, Sylvie Huet, and Frédéric Amblard 2005 An Individual‐Based Model of Innovation Diffusion Mixing Social Value and Individual Benefit. American Journal of Sociology 110(4): 1041–1069.
dc.relationDelre, S.A., W. Jager, T.H.A. Bijmolt, and M.A. Janssen 2007 Targeting and Timing Promotional Activities: An Agent-Based Model for the Takeoff of New Products. Journal of Business Research 60(8): 826–835.
dc.relationDelre, Sebastiano A., Wander Jager, Tammo H. A. Bijmolt, and Marco A. Janssen 2010 Will It Spread or Not? The Effects of Social Influences and Network Topology on Innovation Diffusion. Journal of Product Innovation Management 27(2): 267–282.
dc.relationDelre, Sebastiano A., Wander Jager, and Marco A. Janssen 2007 Diffusion Dynamics in Small-World Networks with Heterogeneous Consumers. Computational and Mathematical Organization Theory 13(2): 185–202.
dc.relationDelre, Sebastiano Alessio 2007 The Effects of Social Networks on Innovation Diffusion and Market Dynamics. S.l.; Groningen: s.n.] ; University Library Groningen] [Host. http://irs.ub.rug.nl/ppn/304001422, accessed March 8, 2020.
dc.relationDeroı̈an, Frédéric 2002 Formation of Social Networks and Diffusion of Innovations. Research Policy 31(5): 835–846.
dc.relationDugundji, Elenna R, and László Gulyás 2008 Sociodynamic Discrete Choice on Networks in Space: Impacts of Agent Heterogeneity on Emergent Outcomes. Environment and Planning B: Planning and Design 35(6): 1028–1054.
dc.relationEdwards-Schachter, Mónica 2018 The Nature and Variety of Innovation. International Journal of Innovation Studies 2(2): 65–79.
dc.relationEIA 2019 International Energy Outlook 2019 with Projections to 2050. Washington: U.S. Energy Information Administration. https://www.eia.gov/outlooks/ieo/pdf/ieo2019.pdf, accessed March 10, 2020.
dc.relationENEL, EBP, and TIKUNA 2018 Informe de factibilidad – Proyecto MicroRed Solar Urbana Providencia - Modelamiento de un sistema vecinal-asociativo para viabilizar la primera Microred Urbana en Latinoamérica.
dc.relationEpstein, Joshua M. 2008 Why Model? Journal of Artificial Societies and Social Simulation 11(4). https://EconPapers.repec.org/RePEc:jas:jasssj:2008-57-1.
dc.relationFaber, Albert, Marco Valente, and Peter Janssen 2010 Exploring Domestic Micro-Cogeneration in the Netherlands: An Agent-Based Demand Model for Technology Diffusion. Energy Policy 38(6): 2763–2775.
dc.relationFornell, Claes, and David F. Larcker 1981 Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research 18(1): 39–50.
dc.relationForrester, J. W. 1995 The Beginning of System Dynamics. McKinsey Quarterly: 4–17.
dc.relationFowler, J. H, and N. A Christakis 2008 Dynamic Spread of Happiness in a Large Social Network: Longitudinal Analysis over 20 Years in the Framingham Heart Study. BMJ 337(dec04 2): a2338–a2338.
dc.relationFrederiks, Elisha R., Karen Stenner, and Elizabeth V. Hobman 2015 Household Energy Use: Applying Behavioural Economics to Understand Consumer Decision-Making and Behaviour. Renewable and Sustainable Energy Reviews 41: 1385–1394.
dc.relationGilbert, G. Nigel, and Klaus G Troitzsch 2005 Simulation for the Social Scientist. Maidenhead, England; New York, NY: Open University Press.
dc.relationGoldenberg, J, B Libai, S Solomon, N Jan, and D Stauffer 2000 Marketing Percolation. Physica A: Statistical Mechanics and Its Applications 284(1–4): 335–347.
dc.relationGoldenberg, Jacob, and Sol Efroni 2001 Using Cellular Automata Modeling of the Emergence of Innovations. Technological Forecasting and Social Change 68(3): 293–308.
dc.relationGoldenberg, Jacob, Barak Libai, Sarit Moldovan, and Eitan Muller 2007 The NPV of Bad News. International Journal of Research in Marketing 24(3): 186–200.
dc.relationGonzález-Bailón, Sandra 2009 Networks and Mechanisms of Interdependence. Theoretical Developments beyond the Rational Action Model. Revista Internacional de Sociología 67(3): 537–558.
dc.relationGranovetter, Mark 1985 Economic Action and Social Structure: The Problem of Embeddedness. American Journal of Sociology 91(3): 481–510.
dc.relationGranovetter, Mark S. 1973 The Strength of Weak Ties. American Journal of Sociology 78(6): 1360–1380.
dc.relationGreve, Henrich R. 2005 Interorganizational Learning and Heterogeneous Social Structure. Organization Studies 26(7): 1025–1047.
dc.relationGreve, Henrich R. 2009 Bigger and Safer: The Diffusion of Competitive Advantage. Strategic Management Journal 30(1): 1–23.
dc.relationGrimm, Volker, Uta Berger, Donald L. DeAngelis, et al. 2010 The ODD Protocol: A Review and First Update. Ecological Modelling 221(23): 2760–2768.
dc.relationGruber, Mario 2020 An Evolutionary Perspective on Adoption-Diffusion Theory. Journal of Business Research 116: 535–541.
dc.relationGuseo, Renato, and Mariangela Guidolin 2015 Heterogeneity in Diffusion of Innovations Modelling: A Few Fundamental Types. Technological Forecasting and Social Change 90: 514–524.
dc.relationHaenlein, Michael, and Barak Libai 2013 Targeting Revenue Leaders for a New Product. Journal of Marketing 77(3): 65–80.
dc.relationHauser, Christoph, Gottfried Tappeiner, and Janette Walde 2007 The Learning Region: The Impact of Social Capital and Weak Ties on Innovation. Regional Studies 41(1): 75–88.
dc.relationHesselink, Laurens X.W., and Emile J.L. Chappin 2019 Adoption of Energy Efficient Technologies by Households – Barriers, Policies and Agent-Based Modelling Studies. Renewable and Sustainable Energy Reviews 99: 29–41.
dc.relationHidayatno, Akhmad, Bramka Arga Jafino, Andri D. Setiawan, and Widodo Wahyu Purwanto 2020 When and Why Does Transition Fail? A Model-Based Identification of Adoption Barriers and Policy Vulnerabilities for Transition to Natural Gas Vehicles. Energy Policy 138: 111239.
dc.relationHill, Shawndra, Foster Provost, and Chris Volinsky 2006 Network-Based Marketing: Identifying Likely Adopters via Consumer Networks. Statistical Science 21(2): 256–276.
dc.relationHinz, Oliver, Bernd Skiera, Christian Barrot, and Jan U. Becker 2011 Seeding Strategies for Viral Marketing: An Empirical Comparison. Journal of Marketing 75(6): 55–71.
dc.relationHohnisch, M., S. Pittnauer, and D. Stauffer 2008 A Percolation-Based Model Explaining Delayed Takeoff in New-Product Diffusion. Industrial and Corporate Change 17(5): 1001–1017.
dc.relationHojnik, Jana, and Mitja Ruzzier 2016 What Drives Eco-Innovation? A Review of an Emerging Literature. Environmental Innovation and Societal Transitions 19: 31–41.
dc.relationHolland, John H. 2002 Complex Adaptive Systems and Spontaneous Emergence. In Complexity and Industrial Clusters. Alberto Quadrio Curzio and Marco Fortis, eds. Pp. 25–34. Heidelberg: Physica-Verlag HD. http://www.springerlink.com/index/10.1007/978-3-642-50007-7_3, accessed July 27, 2013.
dc.relationHötte, Kerstin 2019 How to Accelerate Green Technology Diffusion? An Agent-Based Approach to Directed Technological Change with Coevolving Absorptive Capacity. SSRN Electronic Journal. https://www.ssrn.com/abstract=3312654, accessed August 2, 2020.
dc.relationHu, Hai-hua, Jun Lin, Yanjun Qian, and Jian Sun 2018 Strategies for New Product Diffusion: Whom and How to Target? Journal of Business Research 83: 111–119.
dc.relationIEA 2019 World Energy Outlook 2019. Paris: IEA. https://www.iea.org/reports/world-energy-outlook-2019, accessed March 10, 2020.
dc.relationIRENA 2019 Global Energy Transformation. A Roadmap to 2050. Abu Dhabi: International Renewable Energy Agency. https://www.irena.org/-/media/Files/IRENA/Agency/Publication/2019/Apr/IRENA_Global_Energy_Transformation_2019.pdf, accessed March 12, 2020.
dc.relationIribarren, José Luis, and Esteban Moro 2011 Affinity Paths and Information Diffusion in Social Networks. Social Networks 33(2): 134–142.
dc.relationIyengar, Sheena 2011 El Arte de Elegir: Decisiones Cotidianas. Qué Dicen de Nosotros y Cómo Podemos Mejorarlas. Gestión 2000.
dc.relationJager, W, and M Janssen 2012 An Updated Conceptual Framework for Integrated Modeling of Human Decision Making: The Consumat II. In P. 18. Brussels. https://www.rug.nl/staff/w.jager/jager_janssen_eccs_2012.pdf.
dc.relationJager, Wander 2000 Modelling Consumer Behaviour. University of Groningen. http://www.rug.nl/research/portal/files/9914467/thesis.pdf.
dc.relationJager, Wander, Marco Janssen, and Marija Bockarjova 2014 Diffusion Dynamics of Electric Cars and Adaptive Policy: Towards an Empirical Based Simulation. In Advances in Social Simulation. Bogumił Kamiński and Grzegorz Koloch, eds. Pp. 259–270. Advances in Intelligent Systems and Computing. Berlin, Heidelberg: Springer Berlin Heidelberg. http://link.springer.com/10.1007/978-3-642-39829-2_23, accessed March 8, 2020.
dc.relationJonsson, Stefan 2009 Refraining from Imitation: Professional Resistance and Limited Diffusion in a Financial Market. Organization Science 20(1): 172–186.
dc.relationKaiser, Florian G., Katarzyna Byrka, and Terry Hartig 2010 Reviving Campbell’s Paradigm for Attitude Research. Personality and Social Psychology Review 14(4): 351–367.
dc.relationKaiser, Florian G., and Mark Wilson 2004 Goal-Directed Conservation Behavior: The Specific Composition of a General Performance. Personality and Individual Differences 36(7): 1531–1544.
dc.relationKang, Daekook, Bomi Song, Byoungun Yoon, Youngjo Lee, and Yongtae Park 2015 Diffusion Pattern Analysis for Social Networking Sites Using Small-World Network Multiple Influence Model. Technological Forecasting and Social Change 95: 73–86.
dc.relationKangur, Ayla 2014 STECCAR: Simulating the Transition to Electric Cars Using the Consumat Agent Rationale. Master Thesis, University of Groningen. http://fse.studenttheses.ub.rug.nl/id/eprint/12386.
dc.relationKangur, Ayla, Wander Jager, Rineke Verbrugge, and Marija Bockarjova 2017 An Agent-Based Model for Diffusion of Electric Vehicles. Journal of Environmental Psychology. http://linkinghub.elsevier.com/retrieve/pii/S0272494417300026, accessed March 24, 2017.
dc.relationKarakaya, Emrah, Antonio Hidalgo, and Cali Nuur 2014 Diffusion of Eco-Innovations: A Review. Renewable and Sustainable Energy Reviews 33: 392–399.
dc.relationKemp, René, and Massimiliano Volpi 2008 The Diffusion of Clean Technologies: A Review with Suggestions for Future Diffusion Analysis. Journal of Cleaner Production 16(1): S14–S21.
dc.relationKempe, David, Jon Kleinberg, and Éva Tardos 2003 Maximizing the Spread of Influence through a Social Network. In Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD ’03 P. 137. Washington, D.C.: ACM Press. http://portal.acm.org/citation.cfm?doid=956750.956769, accessed March 14, 2020.
dc.relationKiesling, Elmar, Markus Günther, Christian Stummer, and Lea M. Wakolbinger 2011 Agent-Based Simulation of Innovation Diffusion: A Review. Central European Journal of Operations Research 20(2): 183–230.
dc.relationKim, Shintae, Keeheon Lee, Jang Kyun Cho, and Chang Ouk Kim 2011 Agent-Based Diffusion Model for an Automobile Market with Fuzzy TOPSIS-Based Product Adoption Process. Expert Systems with Applications 38(6): 7270–7276.
dc.relationKnepell, Peter L., and Deborah C. Arangno 1993 Simulation Validation: A Confidence Assessment Methodology. IEEE Computer Society Press Monograph. Los Alamitos, Calif: IEEE Computer Society Press.
dc.relationKnobloch, Florian, and Jean-Francois Mercure 2016 The Behavioural Aspect of Green Technology Investments: A General Positive Model in the Context of Heterogeneous Agents. Environmental Innovation and Societal Transitions 21: 39–55.
dc.relationKocsis, G, and F Kun 2008 The Effect of Network Topologies on the Spreading of Technological Developments. J Stat Mech Theory Exp 10: 10–14.
dc.relationKollmuss, Anja, and Julian Agyeman 2002 Mind the Gap: Why Do People Act Environmentally and What Are the Barriers to pro-Environmental Behavior? Environmental Education Research 8(3): 239–260.
dc.relationKowalska-Pyzalska, Anna, Katarzyna Maciejowska, Karol Suszczyński, Katarzyna Sznajd-Weron, and Rafał Weron 2014 Turning Green: Agent-Based Modeling of the Adoption of Dynamic Electricity Tariffs. Energy Policy 72: 164–174.
dc.relationKravari, Kalliopi, and Nick Bassiliades 2015 A Survey of Agent Platforms. Journal of Artificial Societies and Social Simulation 18(1): 11.
dc.relationLee, Sungjoon 2013 An Integrated Adoption Model for E-Books in a Mobile Environment: Evidence from South Korea. Telematics and Informatics 30(2): 165–176.
dc.relationLippert, S.K., and H. Forman 2005 Utilization of Information Technology: Examining Cognitive and Experiential Factors of Post-Adoption Behavior. IEEE Transactions on Engineering Management 52(3): 363–381.
dc.relationMartins, André C.R., Carlos de B. Pereira, and Renato Vicente 2009 An Opinion Dynamics Model for the Diffusion of Innovations. Physica A: Statistical Mechanics and Its Applications 388(15–16): 3225–3232.
dc.relationMcCoy, Daire, and Seán Lyons 2014 Consumer Preferences and the Influence of Networks in Electric Vehicle Diffusion: An Agent-Based Microsimulation in Ireland. Energy Research & Social Science 3: 89–101.
dc.relationMinisterio de Energía 2014 Ley 20527 Regula El Pago de Las Tarifas Eléctricas de Las Generadoras Residenciales. https://www.leychile.cl/Navegar?idNorma=1038211&idVersion=2014-09-06.
dc.relationMinisterio de Energía 2020a Factores de Emisión Sistema. Gráfico de factores de emisión - Energía Abierta Beta Una iniciativa de la Comisión Nacional de Energía. Chile: Ministerio de Energía de Chile. http://energiaabierta.cl/visualizaciones/factor-de-emision-sic-sing/.
dc.relationMinisterio de Energía 2020b Explorador Solar. Explorador solar - Una base de radiación solar para Chile. Santiago de Chile: Ministerio de Energía de Chile. http://www.minenergia.cl/exploradorsolar/.
dc.relationMittal, Anuj, Caroline C. Krejci, and Michael C. Dorneich 2019 An Agent-Based Approach to Designing Residential Renewable Energy Systems. Renewable and Sustainable Energy Reviews 112: 1008–1020.
dc.relationMoglia, Magnus, Stephen Cook, and James McGregor 2017 A Review of Agent-Based Modelling of Technology Diffusion with Special Reference to Residential Energy Efficiency. Sustainable Cities and Society 31: 173–182.
dc.relationMoldovan, Sarit, Eitan Muller, Yossi Richter, and Elad Yom-Tov 2017 Opinion Leadership in Small Groups. International Journal of Research in Marketing 34(2): 536–552.
dc.relationMontalvo, Carlos 2008 General Wisdom Concerning the Factors Affecting the Adoption of Cleaner Technologies: A Survey 1990–2007. Journal of Cleaner Production 16(1, Supplement 1): S7–S13.
dc.relationMontalvo, Carlos, and René Kemp 2008 Cleaner Technology Diffusion: Case Studies, Modeling and Policy. Journal of Cleaner Production 16(1, Supplement 1): S1–S6.
dc.relationMukherjee, Sanghamitra Chattopadhyay, and Lisa Ryan 2020 Factors Influencing Early Battery Electric Vehicle Adoption in Ireland. Renewable and Sustainable Energy Reviews 118: 109504.
dc.relationMuller, Eitan, and Renana Peres 2019 The Effect of Social Networks Structure on Innovation Performance: A Review and Directions for Research. International Journal of Research in Marketing 36(1): 3–19.
dc.relationMundaca, Luis, Lena Neij, Ernst Worrell, and Michael McNeil 2010 Evaluating Energy Efficiency Policies with Energy-Economy Models. Annual Review of Environment and Resources 35(1): 305–344.
dc.relationMunicipalidad de Providencia 2016 Estrategia Energética Providencia 2016 - 2030. Santiago de Chile: Municipalidad de Providencia.
dc.relationMunicipalidad de Providencia 2018a Providencia Instalará 89 Paneles Solares En La Comuna. Newsletter Soy Providencia, January 31. https://providencia.cl/provi/site/artic/20180131/pags/20180131182729.html.
dc.relationMunicipalidad de Providencia 2018b Se Abren Postulaciones Para Los Barrios Solares de Providencia. Newsletter Soy Providencia, March 5. https://providencia.cl/provi/site/artic/20180305/pags/20180305180316.html.
dc.relationMunicipalidad de Providencia 2018c Con Éxito de Convocatoria Se Cerró Inscripción de Programas de Energía Solar. Newsletter Soy Providencia, April 2. https://providencia.cl/provi/site/artic/20180402/pags/20180402184933.html.
dc.relationMunicipalidad de Providencia 2018d Providencia Tendrá Los Primeros Barrios Solares Interconectados de América Latina. Newsletter Soy Providencia, July 5. https://providencia.cl/provi/site/artic/20180402/pags/20180402184933.html.
dc.relationMurakami, Y., Y. Takabayashi, and Y. Noro 2014 Photovoltaic Power Prediction and Its Application to Smart Grid. In 2014 IEEE Innovative Smart Grid Technologies - Asia (ISGT ASIA) Pp. 47–50. Kuala Lumpur, Malaysia: IEEE. http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6873762, accessed March 8, 2020.
dc.relationNakata, Toshihiko, Diego Silva, and Mikhail Rodionov 2011 Application of Energy System Models for Designing a Low-Carbon Society. Progress in Energy and Combustion Science 37(4): 462–502.
dc.relationNan, Ning, Robert Zmud, and Emre Yetgin 2014 A Complex Adaptive Systems Perspective of Innovation Diffusion: An Integrated Theory and Validated Virtual Laboratory. Computational and Mathematical Organization Theory 20(1): 52–88.
dc.relationNewton, Peter, and Denny Meyer 2013 Exploring the Attitudes-Action Gap in Household Resource Consumption: Does “Environmental Lifestyle” Segmentation Align with Consumer Behaviour? Sustainability 5(3): 1211–1233.
dc.relationNi, Chengzhang, Jun Yang, and Demei Kong 2020 Sequential Seeding Strategy for Social Influence Diffusion with Improved Entropy-Based Centrality. Physica A: Statistical Mechanics and Its Applications 545: 123659.
dc.relationNikolai, Cynthia, and Gregory Madey 2009 Tools of the Trade: A Survey of Various Agent Based Modeling Platforms. Journal of Artificial Societies and Social Simulation 12(2): 2.
dc.relationNoppers, Ernst, Kees Keizer, Marija Bockarjova, and Linda Steg 2015 The Adoption of Sustainable Innovations: The Role of Instrumental, Environmental, and Symbolic Attributes for Earlier and Later Adopters. Journal of Environmental Psychology.
dc.relationONU 2015 Resolución A/RES/70/1 Transformar Nuestro Mundo: La Agenda 2030 Para El Desarrollo Sostenible. http://www.un.org/es/comun/docs/?symbol=A/RES/70/1, accessed March 8, 2020.
dc.relationONU 2020 Objetivos de Desarrollo Sostenible. Objetivos de Desarrollo Sostenible. Programa de Las Naciones Unidas Para El Desarrollo. https://www.undp.org/content/undp/es/home/sustainable-development-goals.html, accessed March 8, 2020.
dc.relationOrdanini, Andrea, Gaia Rubera, and Robert DeFillippi 2008 The Many Moods of Inter-Organizational Imitation: A Critical Review. International Journal of Management Reviews 10(4): 375–398.
dc.relationOsterwalder, Alexander, Yves Pigneur, and Tim Clark 2010 Business Model Generation: A Handbook for Visionaries, Game Changers, and Challengers. Hoboken, NJ: Wiley.
dc.relationPallotti, Francesca, and Alessandro Lomi 2011 Network Influence and Organizational Performance: The Effects of Tie Strength and Structural Equivalence. European Management Journal 29(5): 389–403.
dc.relationPalmer, J., G. Sorda, and R. Madlener 2015 Modeling the Diffusion of Residential Photovoltaic Systems in Italy: An Agent-Based Simulation. Technological Forecasting and Social Change 99: 106–131.
dc.relationPapadopoulos, Thanos, Zoe Radnor, and Yasmin Merali 2011 The Role of Actor Associations in Understanding the Implementation of Lean Thinking in Healthcare. International Journal of Operations & Production Management 31(2): 167–191.
dc.relationPeng, Gang, Debabrata Dey, and Atanu Lahiri 2014 Healthcare IT Adoption: An Analysis of Knowledge Transfer in Socioeconomic Networks. Journal of Management Information Systems 31(3): 7–34.
dc.relationPeng, Gang, and Jifeng Mu 2011 Technology Adoption in Online Social Networks. Journal of Product Innovation Management 28(s1): 133–145.
dc.relationPeng, Sancheng, Yongmei Zhou, Lihong Cao, et al. 2018 Influence Analysis in Social Networks: A Survey. Journal of Network and Computer Applications 106: 17–32.
dc.relationPeres, Renana 2014 The Impact of Network Characteristics on the Diffusion of Innovations. Physica A: Statistical Mechanics and Its Applications 402: 330–343.
dc.relationPeres, Renana, Eitan Muller, and Vijay Mahajan 2010 Innovation Diffusion and New Product Growth Models: A Critical Review and Research Directions. International Journal of Research in Marketing 27(2): 91–106.
dc.relationRahmandad, Hazhir, and John Sterman 2008 Heterogeneity and Network Structure in the Dynamics of Diffusion: Comparing Agent-Based and Differential Equation Models. Management Science 54(5): 998–1014.
dc.relationRai, Varun, and Scott A. Robinson 2015 Agent-Based Modeling of Energy Technology Adoption: Empirical Integration of Social, Behavioral, Economic, and Environmental Factors. Environmental Modelling & Software 70: 163–177.
dc.relationRao, K. Usha, and V.V.N. Kishore 2010 A Review of Technology Diffusion Models with Special Reference to Renewable Energy Technologies. Renewable and Sustainable Energy Reviews 14(3): 1070–1078.
dc.relationRisselada, Hans, Peter C. Verhoef, and Tammo H.A. Bijmolt 2014 Dynamic Effects of Social Influence and Direct Marketing on the Adoption of High-Technology Products. Journal of Marketing 78(2): 52–68.
dc.relationRixen, Martin, and Jürgen Weigand 2014 Agent-Based Simulation of Policy Induced Diffusion of Smart Meters. Technological Forecasting and Social Change 85: 153–167.
dc.relationRobledo, Sebastian, German Osorio, and Carolina Lopez 2014 Networking En Pequeña Empresa: Una Revisión Bibliográfica Utilizando La Teoria de Grafos. Revista Vínculos 11(2). https://revistas.udistrital.edu.co/index.php/vinculos/article/view/9664, accessed March 8, 2020.
dc.relationRogers, Everett M. 1976 New Product Adoption and Diffusion. Journal of Consumer Research: 290–301.
dc.relationRogers, Everett M. 1995 Diffusion of Innovations. 4th ed. New York: Free Press.
dc.relationRyan, Brynce, and Neal C. Gross 1943 The Diffusion of Hybrid Seed Corn in Two Iowa Communities. Rural Sociology 8(1): 15–24.
dc.relationSargent, Robert G. 2011 Verification and Validation of Simulation Models. In Proceedings of the 2011 Winter Simulation Conference: (WSC 2011) ; Phoenix, Arizona, USA, 11 - 14 December 2011 ; [Including the MASM (Modeling and Analysis for Semiconductor Manufacturing) Conference]. IEEE Systems, Man, and Cybernetics Society, American Statistical Association, Association for Computing Machinery, and Sanjay Jain, eds. Pp. 183–198. Piscataway, NJ: IEEE.
dc.relationScheller, Fabian, Simon Johanning, and Thomas Bruckner 2019 A Review of Designing Empirically Grounded Agent-Based Models of Innovation Diffusion: Development Process, Conceptual Foundation and Research Agenda. Beiträge des Instituts für Infrastruktur und Ressourcenmanagement, 01/2019. Leipzig: Universität Leipzig, Institut für Infrastruktur und Ressourcenmanagement (IIRM). http://hdl.handle.net/10419/191981.
dc.relationSchmitt, Philipp, Bernd Skiera, and Christophe Van den Bulte 2011 Referral Programs and Customer Value. Journal of Marketing 75(1): 46–59.
dc.relationSEC 2019a Listado de Las Instalaciones Inscritas Ante La SEC, Mediante El Trámite Eléctrico TE4. Generación Distribuida - Instalaciones inscritas - Energía Abierta Beta Una iniciativa de la Comisión Nacional de Energía. Chile: Superintendencia de Electricidad y Combustibles. http://datos.energiaabierta.cl/dataviews/235587/generacion-distribuida-instalaciones-declaradas/.
dc.relationSEC 2019b Cantidad de Proyectos Declarados Desde 2015 a La Fecha de La Comuna de Providencia En Relación al Proceso de Conexión Del Artículo 149 Bis de La Ley General de Servicios Eléctricos.
dc.relationShepherd, Simon, Peter Bonsall, and Gillian Harrison 2012 Factors Affecting Future Demand for Electric Vehicles: A Model Based Study. Transport Policy 20(0): 62–74.
dc.relationShi, Yingying, Yongchao Zeng, Jean Engo, et al. 2020 Leveraging Inter-Firm Influence in the Diffusion of Energy Efficiency Technologies: An Agent-Based Model. Applied Energy 263: 114641.
dc.relationSilvestre, Bruno S., and Diana Mihaela Ţîrcă 2019 Innovations for Sustainable Development: Moving toward a Sustainable Future. Journal of Cleaner Production 208: 325–332.
dc.relationSopha, Bertha Maya, Christian A. Klӧckner, and Dona Febrianti 2016 Using Agent-Based Modeling to Explore Policy Options Supporting Adoption of Natural Gas Vehicles in Indonesia. Journal of Environmental Psychology. http://linkinghub.elsevier.com/retrieve/pii/S0272494416300585, accessed March 31, 2017.
dc.relationSterman, John D 2000 Business Dynamics : Systems Thinking and Modeling for a Complex World. Boston [etc.]: Irwin/McGraw-Hill.
dc.relationStrang, David, and Sarah A. Soule 1998 Diffusion in Organizations and Social Movements: From Hybrid Corn to Poison Pills. Annual Review of Sociology 24. JSTOR, Annual Reviews: 265–290.
dc.relationStummer, Christian, Elmar Kiesling, Markus Günther, and Rudolf Vetschera 2015 Innovation Diffusion of Repeat Purchase Products in a Competitive Market: An Agent-Based Simulation Approach. European Journal of Operational Research 245(1): 157–167.
dc.relationSun, Xiaohua, Xiaoling Liu, Yun Wang, and Fang Yuan 2019 The Effects of Public Subsidies on Emerging Industry: An Agent-Based Model of the Electric Vehicle Industry. Technological Forecasting and Social Change 140: 281–295.
dc.relationTapia, Claudio 2020 Estrategia Energética Local y Articulación Con Proyectos de Sistemas Fotovoltáicos Para Casas En La Municipalidad de Providencia - Santiago de Chile. Presencial en Santiago de Chile - Caupolicán 1151. May 16.
dc.relationTariq, Adeel, Yuosre F. Badir, Waqas Tariq, and Umair Saeed Bhutta 2017 Drivers and Consequences of Green Product and Process Innovation: A Systematic Review, Conceptual Framework, and Future Outlook. Technology in Society 51: 8–23.
dc.relationTatarynowicz, Adam, Maxim Sytch, and Ranjay Gulati 2016 Environmental Demands and the Emergence of Social Structure: Technological Dynamism and Interorganizational Network Forms. Administrative Science Quarterly 61(1): 52–86.
dc.relationThiriot, Samuel, and Jean-Daniel Kant 2008 Using Associative Networks to Represent Adopters’ Beliefs in a Multiagent Model of Innovation Diffusion. Advances in Complex Systems 11(02): 261–272.
dc.relationTian, Shanjun, and Shiyan Chang 2020 An Agent-Based Model of Household Energy Consumption. Journal of Cleaner Production 242: 118378.
dc.relationTodd, Peter M, and Gerd Gigerenzer 2003 Bounding Rationality to the World. Journal of Economic Psychology 24(2): 143–165.
dc.relationTran, Martino 2012 Agent-Behaviour and Network Influence on Energy Innovation Diffusion. Communications in Nonlinear Science and Numerical Simulation 17(9): 3682–3695.
dc.relationTrusov, Michael, Anand V. Bodapati, and Randolph E. Bucklin 2010 Determining Influential Users in Internet Social Networks. Journal of Marketing Research 47(4): 643–658.
dc.relationTsakas, Nikolas 2017 Diffusion by Imitation: The Importance of Targeting Agents. Journal of Economic Behavior & Organization 139: 118–151.
dc.relationUniversidad Pontificia Bolivariana, and Área Metropolitana del Valle de Aburra 2018 Informe Final Convenio de Asociación No. CA 583 de 2017. Actualización Inventario de Emisiones Atmosféricas Del Valle de Aburrá - Año 2016.
dc.relationValente, Thomas W. 1995 Network Models of the Diffusion of Innovations. Quantitative Methods in Communication. Cresskill, N.J: Hampton Press.
dc.relationValente, Thomas W. 1996 Social Network Thresholds in the Diffusion of Innovations. Social Networks 18(1): 69–89.
dc.relationValente, Thomas W. 2010 Social Networks and Health: Models, Methods, and Applications. Oxford ; New York: Oxford University Press.
dc.relationValente, Thomas W., and Rebecca L. Davis 1999 Accelerating the Diffusion of Innovations Using Opinion Leaders. The ANNALS of the American Academy of Political and Social Science 566(1): 55–67.
dc.relationValente, Thomas W., Stephanie R. Dyal, Kar-Hai Chu, Heather Wipfli, and Kayo Fujimoto 2015 Diffusion of Innovations Theory Applied to Global Tobacco Control Treaty Ratification. Social Science & Medicine 145: 89–97.
dc.relationVan Den Bulte, Christophe, Emanuel Bayer, Bernd Skiera, and Philipp Schmitt 2018 How Customer Referral Programs Turn Social Capital into Economic Capital. Journal of Marketing Research 55(1): 132–146.
dc.relationVan den Bulte, Christophe, and Yogesh V. Joshi 2007 New Product Diffusion with Influentials and Imitators. Marketing Science 26(3): 400–421.
dc.relationVaradarajan, Rajan 2017 Innovating for Sustainability: A Framework for Sustainable Innovations and a Model of Sustainable Innovations Orientation. Journal of the Academy of Marketing Science 45(1): 14–36.
dc.relationVelásquez, Juan D. 2014a Una Guía Corta Para Escribir Revisiones Sistemáticas de Literatura Parte 1. DYNA 81(187): 9–10.
dc.relationVelásquez, Juan D. 2014b Una Guía Corta Para Escribir Revisiones Sistemáticas de Literatura Parte 2. DYNA 81(188): 9–10.
dc.relationVelásquez, Juan D. 2015 Una Guía Corta Para Escribir Revisiones Sistemáticas de Literatura Parte 4. DYNA 82(190): 9–12.
dc.relationVillanueva, Julian, Shijin Yoo, and Dominique M. Hanssens 2008 The Impact of Marketing-Induced versus Word-of-Mouth Customer Acquisition on Customer Equity Growth. Journal of Marketing Research 45(1). SAGE Publications Inc: 48–59.
dc.relationViswanathan, Vijay, Sebastian Tillmanns, Manfred Krafft, and Daniel Asselmann 2018 Understanding the Quality–Quantity Conundrum of Customer Referral Programs: Effects of Contribution Margin, Extraversion, and Opinion Leadership. Journal of the Academy of Marketing Science 46(6): 1108–1132.
dc.relationWasserman, Stanley, and Katherine Faust 1994 Social Network Analysis: Methods and Applications. 1st edition. Cambridge University Press. https://www.cambridge.org/core/product/identifier/9780511815478/type/book, accessed March 8, 2020.
dc.relationWatts, Duncan J., and Peter Sheridan Dodds 2007 Influentials, Networks, and Public Opinion Formation. Journal of Consumer Research 34(4): 441–458.
dc.relationWEC 2020 World Energy Issues Monitor 2020: Decoding New Sognals of Change. Londres: World Energy Council. https://www.worldenergy.org/assets/downloads/World_Energy_Issues_Monitor_2020_-_Full_Report.pdf, accessed March 12, 2020.
dc.relationWEC Colombia 2019 Informe III Encuentro Internacional de Movilidad Eléctrica Colombia. Bogotá: World Energy Council Colombia. https://www.energycolombia.org/wp-content/uploads/Informe-III-ENCUENTRO-INTERNACIONAL-DE-MOVILIDAD-EL%C3%89CTRICA.pdf, accessed March 13, 2020.
dc.relationWolf, Ingo, Tobias Schröder, Jochen Neumann, and Gerhard de Haan 2015 Changing Minds about Electric Cars: An Empirically Grounded Agent-Based Modeling Approach. Technological Forecasting and Social Change 94: 269–285.
dc.relationXavier, Amanda F., Ricardo M. Naveiro, Améziane Aoussat, and Tatiana Reyes 2017 Systematic Literature Review of Eco-Innovation Models: Opportunities and Recommendations for Future Research. Journal of Cleaner Production 149: 1278–1302.
dc.relationZhang, Haifeng, and Yevgeniy Vorobeychik 2019 Empirically Grounded Agent-Based Models of Innovation Diffusion: A Critical Review. Artificial Intelligence Review 52(1): 707–741.
dc.relationZhang, Tao, and William J. Nuttall 2011 Evaluating Government’s Policies on Promoting Smart Metering Diffusion in Retail Electricity Markets via Agent-Based Simulation*: Smart Metering Diffusion in Retail Electricity Markets. Journal of Product Innovation Management 28(2): 169–186.
dc.rightsAtribución-SinDerivadas 4.0 Internacional
dc.rightsAtribución-SinDerivadas 4.0 Internacional
dc.rightsAcceso abierto
dc.rightshttp://creativecommons.org/licenses/by-nd/4.0/
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightsDerechos reservados - Universidad Nacional de Colombia
dc.titleMetodología para evaluar el impacto de estrategias orientadas a incentivar la difusión de innovaciones energéticas limpias a partir de la influencia social
dc.typeOtros


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