Difusión de productos a través de redes sociales: una revisión bibliográfica utilizando la teoría de grafos

Difusión de productos a través de redes sociales: una revisión bibliográfica utilizando la teoría de grafos

Contenido principal del artículo

Sebastián Robledo-Giraldo
Néstor Darío Duque-Méndez
Jorge Iván Zuluaga-Giraldo


La difusión de productos a través de redes sociales es un campo de aplicación del mercadeo, donde la decisión de compra de un consumidor es influenciada por factores internos y externos como su red de conocidos y familiares. El propósito de esta investigación es identificar las principales perspectivas y plantear futuras investigaciones, apoyados en la revisión selectiva del estado del arte. Para la orientación de la búsqueda y la selección de artículos se utilizó la teoría de grafos, aprovechando las posibilidades de reconocer las conexiones entre los diferentes trabajos, arrojando para su análisis 18 artículos clásicos y 23 artículos actuales. A partir de esto se obtuvo, como resultado de la investigación, cuatro (4) estrategias de mercadeo diferentes: enfocadas a los influenciadores, a los no influenciadores, grupos pequeños y estrategias tradicionales de mercadeo.

Palabras clave: difusión de productos, redes sociales, teoría de grafos.




The diffusion of products through social networking is an application field of marketing, where the buying decision of a consumer is influenced by internal and external factors as their network of friends and relatives. The purpose of this research is to identify the main perspectives and propose future research, supported in state of the art selective review. As input for the orientation of search and articles selection, graph theory was used, leveraging the odds of recognizing the links among different works, providing for analysis 18 classic articles and 23 current articles. The result of the investigation showed four different marketing strategies: focused on influencers, non-influencers, small groups and traditional marketing strategies.

Keywords: diffusion of products, social networks, graph theory.


Los datos de descargas todavía no están disponibles.

Detalles del artículo

Biografía del autor/a (VER)

Sebastián Robledo-Giraldo, Universidad Nacional de Colombia, Manizales.

Magister en Administración de Negocios.

Néstor Darío Duque-Méndez, Universidad Nacional de Colombia, Manizales.

Doctor en Ingeniería.

Jorge Iván Zuluaga-Giraldo, Universidad de Manizales.

Administrador de Empresas.

Amini, M., Wakolbinger, T., Racer, M., y Nejad, M. G. (2012). Alternative supply chain production–sales policies for new product diffusion: An agent-based modeling and simulation approach. European Journal of Operational Research, 216(2), 301–311. doi:10.1016/j.ejor.2011.07.040.

Baker, S. (2009). What’s a Friend Worth? Business Week, January(6), 32–36.

Barabási, A.-L., y Jeong, R. A. H. (1999). Mean-field theory for scale-free random networks. Statistical Mechanics and its Applications, 272(1), 173–187.

Bass, F. M. (1969). A New Product Growth for Model Consumer Durables.Management Science, 15(5), 215–227. doi:10.1287/mnsc.1040.0264.

Bastian, M., Heymann, S., y Jacomy, M. (2009).Gephi: an open source software for exploring and manipulating networks. International AAAI Conference on Weblogs and Social Media.

Bianconi, G., y Barabási, A.-L.(2001). Competition and multiscaling in evolving networks. Europhysics Letters (EPL), 54(4), 436–442. doi:10.1209/epl/i2001-00260-6.

Brown, J. J., y Reingen, P. H. (1987). Social ties and Word-of-Mouth referral behavior. Journal of Consumer Research, 14(3), 350–362.

Bulte, C. Van den, y Wuyts, S. (2007). Social Networks and Marketing. Cambridge, MA: Marketing Science Institute.

Burt, R. S. (1987). Social contagion and innovation: Cohesion versus structural equivalence. American journal of Sociology, 92(6), 1287–1335.

Ceci, F., y Iubatti, D. (2012). Personal relationships and innovation diffusion in SME networks: A content analysis approach. Research Policy, 41(3), 565–579. doi:10.1016/j.respol.2011.10.003.

Cho, Y., Hwang, J., y Lee, D. (2012). Identification of effective opinion leaders in the diffusion of technological innovation: A social network approach. Technological Forecasting and Social Change, 79(1), 97–106. doi:10.1016/j.techfore.2011.06.003.

Christakis, N. A., y Fowler, J. H. (2008). The collective dynamics of smoking in a large social network.New England journal of medicine, 358(21), 2249–2258.

Cruz, J. P., y Olaya, C. (2008). A system dynamics model for studying the structure of network marketing organizations. In The 2008 International Conference of the System Dynamics Society (pp. 1–34). Athens, Greece.

Delre, S. A., Jager, W., y Bijmolt, T. (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. doi:10.1111/j.1540-5885.2010.00714.x.

Delre, S. A., Jager, W., Bijmolt, T. H. a., y Janssen, M. A. (2007). Targeting and timing promotional activities: An agent-based model for the takeoff of new products. Journal of Business Research, 60(8), 826–835. doi:10.1016/j.jbusres.2007.02.002

Euler, Leonhard. “Solutio problematis ad geometriam situs pertinentis” Commentarii academiae scientiarum Petropolitanae 8 (1741): 128-140.

Fang, X., Hu, P. J.-H., Li, Z., y Tsai, W. (2013). Predicting Adoption Probabilities in Social Networks.Information Systems Research, 24(1), 128–145. doi:10.1287/isre.1120.0461.

Garcia, R. (2005). Uses of Agent-Based-Modeling in Innovation/New Product Development Research. Journal of Product Innovation Management, 22(5), 380–398.

Godes, D., y Mayzlin, D. (2004). Using Online Conversations to Study Word-of-Mouth Communication.Marketing Science, 23(4), 545–560. doi:10.1287/mksc.1040.0071.

Goldenberg, J., Han, S., Lehmann, D. R., y Hong, J. W. (2009). The Role of Hubs in the Adoption Process.Journal of Marketing, 73(2), 1–13. doi:10.1509/jmkg.73.2.1.

Goldenberg, J., Libai, B., Moldovan, S., y Muller, E. (2007).The NPV of bad news.International Journal of Research in Marketing, 24(3), 186–200. doi:10.1016/j.ijresmar.2007.02.003.

Goldenberg, J., Libai, B., y Muller, E. (2002). Riding the saddle: How cross-market communications can create a major slump in sales. The Journal of Marketing, 66(2), 1–16.

Goldenberg, J., Lowengart, O., y Shapira, D. (2009). Zooming In: Self-Emergence of Movements in New Product Growth.Marketing Science, 28(2), 274–292. doi:10.1287/mksc.1080.0395.

Granovetter, M. (1973).The strength of weak ties.American journal of sociology, 78, 1360– 1380.

Granovetter, M. (1985). Economic action and social structure: the problem of embeddedness. American Journal of Sociology, 91(3), 481–510.

Haenlein, M., y Libai, B. (2013a).Targeting Revenue Leaders for a New Product.Journal of Marketing, 77(3), 65–80. doi:10.1509/jm.11.0428.

Hill, S., Provost, F., y Volinsky, C. (2006). Network-Based Marketing: Identifying Likely Adopters via Consumer Networks.Statistical Science, 21(2), 256–276. doi:10.1214/088342306000000222.

Hinz et al. (2012).Seeding Strategies for Viral Marketing: An Empirical Comparison.Journal of Marketing, 75(6), 55–71.

Iribarren, J. L., y Moro, E. (2011). Affinity Paths and information diffusion in social networks. Social Networks, 33(2), 134–142.

Iyengar, R., Bulte, C. Van den, y Valente, T. W. (2011). Opinion leadership and social contagion in new product diffusion.Marketing Science, 30(2), 195–212.

Janssen, M. A., y Jager, W. (2001). Fashions, habits and changing preferences: Simulation of psychological factors affecting market dynamics. Journal of economic psychology, 22, 745–772.

Katona, Z., Zubcsek, P. P., y Sarvary, M. (2010). Network Effects and Personal Influences: The Diffusion of an Online Social Network. Journal of Marketing Research, 48(3), 425–443.

Kossinets, G., y Watts, D. J. (2006). Empirical analysis of an evolving social network. Science (New York, N.Y.), 311(5757), 88–90. doi:10.1126/science.1116869.

Kratzer, J., y Lettl, C. (2009). Distinctive Roles of Lead Users and Opinion Leaders in the Social Networks of Schoolchildren.Journal of Consumer Research, 36(4), 646–659. doi:10.1086/599324.

Laciana, C., Rovere, S., y Podestá, G. (2013). Exploring associations between micro-level models of innovation diffusion and emerging macro-level adoption patterns. Statistical Mechanics and its Applications, 392(8), 1873–1884.

Libai, B., Bolton, R., Bugel, M. S., de Ruyter, K., Gotz, O., Risselada, H., y Stephen, A. T. (2010). Customer-to-Customer Interactions: Broadening the Scope of Word of Mouth Research. Journal of Service Research, 13(3), 267– 282. doi:10.1177/1094670510375600.

Libai, B., Muller, E., y Peres, R. (2013). Decomposing the Value of Word-of-Mouth Seeding Programs: Acceleration Versus Expansion. Journal of Marketing Research, 50, 161.

Liu, X., Jiang, T., y Ma, F. (2013). Collective dynamics in knowledge networks: Emerging trends analysis. Journal of Informetrics, 7(2), 425–438. doi:10.1016/j.joi.2013.01.003.

Liu-Thompkins, Y. (2012). Seeding Viral Content The Role of Message and Network Factors. Journal of Advertising Research., 59–72. doi:10.2501/JAR-52-4-000-000.

Liu-Thompkins, Y., y Rogerson, M. (2012). Rising to Stardom: An Empirical Investigation of the Diffusion of User-generated Content. Journal of Interactive Marketing, 26(2), 71–82. doi:10.1016/j.intmar.2011.11.003.

Mahajan, V., Muller, E., y Bass, F. M. (1990). New product diffusion models in marketing: A review and directions for research. The Journal of Marketing, 54(1), 1–26.

McPherson, M., Smith-Lovin, L., y Cook, J. M. (2001). Birds of a feather: Homophily in social networks. Annual review of sociology, 27, 415–444.

Nitzan, I., y Libai, B. (2011). Social effects on customer retention.Journal of Marketing, 75(April), 1–63.

Pegoretti, G., Rentocchini, F., &Vittucci- Marzetti, G. (2012). Anagent-based model of innovation diffusion: network structure and coexistence under different information regimes. Journal of Economic Interaction and Coordination, 7(2), 145–165. doi:10.1007/s11403-012-0087-4.

Peres, R., Muller, E., y Mahajan, V. (2010). Innovation diffusion and new product growth models: A critical review and research directions. International Journal of Research in Marketing, 27(2), 91–106. doi:10.1016/j.ijresmar.2009.12.012.

Robledo-Giraldo, S., y Osorio-Zuluaga, G. A. (2012).Potencial de ingresos pasivos para los distribuidores en empresas de mercadeo multinivel con un plan de compensación binario. Revista respuestas, 17(2), 13–20.

Rogers. (1962). Diffusion of innovations (Free Press.). New York.

Rogers, E. M. (2003). Diffusion of Innovations.

Sci2, T. (2009).Science of Science (Sci2) Tool.Indiana University and SciTech Strategies. Retrieved from http://sci2.cns.iu.edu.

Tonta, Y., y Darvish, H. R. (2010). Diffusion of latent semantic analysis as a research tool: A social network analysis approach. Journal of Informetrics, 4(2), 166–174. doi:10.1016/j.joi.2009.11.003.

Van den Bulte, C., y Lilien, G. L. (2001). Medical Innovation Revisited: Social Contagion versus Marketing Effort1. American Journal of Sociology, 106(5). R

Van den Bulte, C., y Stremersch, S. (2004). Social contagion and income heterogeneity in new product diffusion: A meta-analytic test. MARKETING SCIENCE, 23(4), 530–544.doi:10.1287/mksc.1040.0054.

Van den Bulte, C., y Yoshi, Y. V. (2007). New product diffusion with influentials and imitators. Marketing Science, 26(3), 400–421. doi:10.1287/mksc.l060.0224.

Wasserman, S. (1994). Social Network Analysis: Methods and applications. Vol 8.Cambridge University Press.

Watts, D. J., y Dodds, P. S. (2007). Influentials, Networks, and Public Opinion Formation. Journal of Consumer Research, 34(4), 441–58.

Watts, D. J., y Strogatz, S. H. (1998). Collective dynamics of “small-world” networks. Nature, 393(6684), 440–2. doi:10.1038/30918.

Winkler, W. E. (1990). String Comparator Metrics and Enhanced Decision Rules in the Fellegi-Sunter Model of Record Linkage. Proceedings of the Section on Survey Research Methods (American Statistical Association), 354–359.

Yansong, H. (2013). Hyperlinked actors in the global knowledge communities and diffusion of innovation tools in nascent industrial field. Technovation, 33(2-3), 38–49. doi:10.1016/j.technovation.2012.10.001.

Artículos más leídos del mismo autor/a

Sistema OJS - Metabiblioteca |