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Ignition of New Product Diffusion in Entrepreneurship: An Agent-Based Approach

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  • Shim Jaehu

    (Queensland University of Technology, Australian Centre for Entrepreneurship Research, Brisbane, Queensland4000, Australia)

  • Bliemel Martin

    (UNSW Business School, UNSW – School of Management, Kensington, New South Wales2052, Australia)

Abstract

New product diffusion is critical to entrepreneurship. Without successful diffusion, the emergence of a new business is incomplete. Although we have several well-established models of the diffusion phenomenon, these models mainly describe the macro-level diffusion patterns after their ignition, thereby ignoring the ignition mechanism. This study conceptualizes an entrepreneur’s introduction of a new product and its diffusion as a generative emergence from a complexity science perspective and employs agent-based modeling and simulation (ABMS) to explain the full ignition-diffusion process as well as ignition failures. In this study’s model, the ignition process is made of individual consumers’ heterogeneous thresholds and their relative levels of activities. These micro-level characteristics and behaviors influence the speed and scope of the diffusion at the macro-level. Our simulations reveal the minimum number of initial adopters required to ignite the diffusion process and show how an entrepreneur’s advertising campaign may accelerate the ignition and diffusion speed. The simulations also reveal how consumers’ negative word-of-mouth may reduce the diffusion scope.

Suggested Citation

  • Shim Jaehu & Bliemel Martin, 2018. "Ignition of New Product Diffusion in Entrepreneurship: An Agent-Based Approach," Entrepreneurship Research Journal, De Gruyter, vol. 8(2), pages 1-17, March.
  • Handle: RePEc:bpj:erjour:v:8:y:2018:i:2:p:17:n:1
    DOI: 10.1515/erj-2016-0014
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    1. Garcia, Rosanna & Rummel, Paul & Hauser, John, 2007. "Validating agent-based marketing models through conjoint analysis," Journal of Business Research, Elsevier, vol. 60(8), pages 848-857, August.
    2. Ross Brown & Colin Mason, 2017. "Looking inside the spiky bits: a critical review and conceptualisation of entrepreneurial ecosystems," Small Business Economics, Springer, vol. 49(1), pages 11-30, June.
    3. Keiki Takadama & Tetsuro Kawai & Yuhsuke Koyama, 2008. "Micro- and Macro-Level Validation in Agent-Based Simulation: Reproduction of Human-Like Behaviors and Thinking in a Sequential Bargaining Game," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 11(2), pages 1-9.
    4. 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.
    5. Frank M. Bass & Trichy V. Krishnan & Dipak C. Jain, 1994. "Why the Bass Model Fits without Decision Variables," Marketing Science, INFORMS, vol. 13(3), pages 203-223.
    6. Jeffery S. McMullen & Dimo Dimov, 2013. "Time and the Entrepreneurial Journey: The Problems and Promise of Studying Entrepreneurship as a Process," Journal of Management Studies, Wiley Blackwell, vol. 50(8), pages 1481-1512, December.
    7. Bliemel Martin J. & McCarthy Ian P. & Maine Elicia M.A., 2014. "An Integrated Approach to Studying Multiplexity in Entrepreneurial Networks," Entrepreneurship Research Journal, De Gruyter, vol. 4(4), pages 367-402, October.
    8. Crawford, G. Christopher & Aguinis, Herman & Lichtenstein, Benyamin & Davidsson, Per & McKelvey, Bill, 2015. "Power law distributions in entrepreneurship: Implications for theory and research," Journal of Business Venturing, Elsevier, vol. 30(5), pages 696-713.
    9. Maine, Elicia & Garnsey, Elizabeth, 2006. "Commercializing generic technology: The case of advanced materials ventures," Research Policy, Elsevier, vol. 35(3), pages 375-393, April.
    10. Nigel Gilbert & Pietro Terna, 2000. "How to build and use agent-based models in social science," Mind & Society: Cognitive Studies in Economics and Social Sciences, Springer;Fondazione Rosselli, vol. 1(1), pages 57-72, March.
    11. East, Robert & Hammond, Kathy & Lomax, Wendy, 2008. "Measuring the impact of positive and negative word of mouth on brand purchase probability," International Journal of Research in Marketing, Elsevier, vol. 25(3), pages 215-224.
    12. Hubert Gatignon & Jehoshua Eliashberg & Thomas S. Robertson, 1989. "Modeling Multinational Diffusion Patterns: An Efficient Methodology," Marketing Science, INFORMS, vol. 8(3), pages 231-247.
    13. Elmar Kiesling & Markus Günther & Christian Stummer & Lea Wakolbinger, 2012. "Agent-based simulation of innovation diffusion: a review," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 20(2), pages 183-230, June.
    14. Lim, Byeong-Lak & Choi, Munkee & Park, Myeong-Cheol, 2003. "The late take-off phenomenon in the diffusion of telecommunication services: network effect and the critical mass," Information Economics and Policy, Elsevier, vol. 15(4), pages 537-557, December.
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