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Diffusion of innovation within an agent-based model: Spinsons, independence and advertising

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  • Piotr Przybyla
  • Katarzyna Sznajd-Weron
  • Rafal Weron

Abstract

We modify a two-dimensional variant of a two-state non-linear voter model and apply it to understand how new ideas, products or behaviors spread throughout the society in time. In particular, we want to find answers to two important questions in the field of diffusion of innovation: Why does the diffusion of innovation take sometimes so long? and Why does it fail so often? Because these kind of questions cannot be answered within classical aggregate diffusion models, like the Bass model, we use an agent-based modeling approach.

Suggested Citation

  • Piotr Przybyla & Katarzyna Sznajd-Weron & Rafal Weron, 2013. "Diffusion of innovation within an agent-based model: Spinsons, independence and advertising," HSC Research Reports HSC/13/04, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    • Handle: RePEc:wuu:wpaper:hsc1304
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    1. Tal Garber & Jacob Goldenberg & Barak Libai & Eitan Muller, 2004. "From Density to Destiny: Using Spatial Dimension of Sales Data for Early Prediction of New Product Success," Marketing Science, INFORMS, vol. 23(3), pages 419-428, August.
    2. Rand, William & Rust, Roland T., 2011. "Agent-based modeling in marketing: Guidelines for rigor," International Journal of Research in Marketing, Elsevier, vol. 28(3), pages 181-193.
    3. K. Sznajd-Weron & R. Weron, 2002. "A Simple Model Of Price Formation," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 13(01), pages 115-123.
    4. Katarzyna Sznajd-Weron & Józef Sznajd, 2000. "Opinion Evolution In Closed Community," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 11(06), pages 1157-1165.
    5. Kacperski, Krzysztof & Hołyst, Janusz A., 2000. "Phase transitions as a persistent feature of groups with leaders in models of opinion formation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 287(3), pages 631-643.
    6. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    7. Anna Kowalska-Pyzalska & Katarzyna Maciejowska & Katarzyna Sznajd-Weron & Rafal Weron, 2013. "Going green: Agent-based modeling of the diffusion of dynamic electricity tariffs," HSC Research Reports HSC/13/05, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    8. F. Slanina & H. Lavicka, 2003. "Analytical results for the Sznajd model of opinion formation," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 35(2), pages 279-288, September.
    9. Sznajd-Weron, K. & Weron, R., 2003. "How effective is advertising in duopoly markets?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 324(1), pages 437-444.
    10. Jacob Goldenberg & Oded Lowengart & Daniel Shapira, 2009. "Zooming In: Self-Emergence of Movements in New Product Growth," Marketing Science, INFORMS, vol. 28(2), pages 274-292, 03-04.
    11. Tatiana Bouzdine-Chameeva & Serge Galam, 2011. "Word-Of-Mouth Versus Experts And Reputation In The Individual Dynamics Of Wine Purchasing," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 14(06), pages 871-885.
    12. Weyant, John P., 2011. "Accelerating the development and diffusion of new energy technologies: Beyond the "valley of death"," Energy Economics, Elsevier, vol. 33(4), pages 674-682, July.
    13. Kacperski, Krzysztof & Hoł yst, Janusz A., 1999. "Opinion formation model with strong leader and external impact: a mean field approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 269(2), pages 511-526.
    14. Galam, Serge & Vignes, Annick, 2005. "Fashion, novelty and optimality: an application from Physics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 351(2), pages 605-619.
    15. Galam, Serge, 1997. "Rational group decision making: A random field Ising model at T = 0," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 238(1), pages 66-80.
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    Cited by:

    1. Katarzyna Maciejowska & Arkadiusz Jedrzejewski & Anna Kowalska-Pyzalska & Katarzyna Sznajd-Weron & Rafal Weron, 2015. "Two faces of word-of-mouth: Understanding the impact of social interactions on demand curves for innovative products," HSC Research Reports HSC/15/09, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    2. Katarzyna Byrka & Arkadiusz Jedrzejewski & Katarzyna Sznajd-Weron & Rafal Weron, 2015. "Difficulty is critical: Psychological factors in modeling diffusion of green products and practices," HSC Research Reports HSC/15/10, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    3. Anna Kowalska-Pyzalska & Katarzyna Maciejowska & Katarzyna Sznajd-Weron & Rafal Weron, 2014. "Diffusion and adoption of dynamic electricity tariffs: An agent-based modeling approach," HSC Research Reports HSC/14/01, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    4. Kowalska-Pyzalska, Anna & Maciejowska, Katarzyna & Suszczyński, Karol & Sznajd-Weron, Katarzyna & Weron, Rafał, 2014. "Turning green: Agent-based modeling of the adoption of dynamic electricity tariffs," Energy Policy, Elsevier, vol. 72(C), pages 164-174.
    5. Anna Kowalska-Pyzalska, 2015. "Social acceptance of green energy and dynamic electricity tariffs - a short review," HSC Research Reports HSC/15/07, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    6. Weron, Tomasz & Kowalska-Pyzalska, Anna & Weron, Rafał, 2018. "The role of educational trainings in the diffusion of smart metering platforms: An agent-based modeling approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 591-600.
    7. Simpson, Jesse R. & Mishra, Sabyasachee & Talebian, Ahmadreza & Golias, Mihalis M., 2019. "An estimation of the future adoption rate of autonomous trucks by freight organizations," Research in Transportation Economics, Elsevier, vol. 76(C).
    8. Kowalska-Pyzalska, Anna, 2018. "What makes consumers adopt to innovative energy services in the energy market? A review of incentives and barriers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3570-3581.
    9. Anna Kowalska-Pyzalska & Katarzyna Maciejowska & Katarzyna Sznajd-Weron & Rafal Weron, 2013. "Going green: Agent-based modeling of the diffusion of dynamic electricity tariffs," HSC Research Reports HSC/13/05, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    10. Anna Kowalska-Pyzalska, 2016. "What makes consumers adopt to innovative energy services in the energy market?," HSC Research Reports HSC/16/09, Hugo Steinhaus Center, Wroclaw University of Technology.
    11. Hadzibeganovic, Tarik & Stauffer, Dietrich & Han, Xiao-Pu, 2018. "Interplay between cooperation-enhancing mechanisms in evolutionary games with tag-mediated interactions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 676-690.
    12. Raducha, Tomasz & Gubiec, Tomasz, 2017. "Coevolving complex networks in the model of social interactions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 427-435.

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    More about this item

    Keywords

    Agent-based model; Diffusion of innovation; Word of mouth marketing; Conformity; Advertising; Spinson;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D70 - Microeconomics - - Analysis of Collective Decision-Making - - - General
    • M37 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Advertising

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