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Dynamic Strategies for Successful Online Crowdfunding

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  • Zhuoxin Li

    (McCombs School of Business, The University of Texas at Austin, 2110 Speedway Stop B6500, Austin, Texas, 78712)

  • Jason A. Duan

    (McCombs School of Business, The University of Texas at Austin, 2110 Speedway Stop B6700, Austin, Texas, 78712)

Abstract

Crowdfunding is a fast emerging internet fundraising mechanism for soliciting capital from the crowd to support entrepreneurial ventures. This paper empirically investigates the dynamics of investors’ backing behaviors in the presence of network externalities and a finite time window. The proposed model captures how investors dynamically update their expectations on the prospect of a project based on its current funding status and time progress. Model estimation shows that investors are more likely to back a project that has already attracted a critical mass of funding (positive network externalities). For the same amount of achieved funding, the backing propensity declines over time (negative time effects). These two opposing forces give rise to a critical mass of funding the project must attain on time to achieve successful funding by the deadline. Counterfactual simulations show that projects may fail to attain the critical mass because of unfavorable shocks in investor visits at the early stage of the funding cycle. We derive dynamic seeding strategies for project owners to maximize the likelihood of funding success.

Suggested Citation

  • Zhuoxin Li & Jason A. Duan, 2014. "Dynamic Strategies for Successful Online Crowdfunding," Working Papers 14-09, NET Institute.
  • Handle: RePEc:net:wpaper:1409
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    Cited by:

    1. Mi (Jamie) Zhou & Baozhou Lu & Weiguo (Patrick) Fan & G. Alan Wang, 2018. "Project description and crowdfunding success: an exploratory study," Information Systems Frontiers, Springer, vol. 20(2), pages 259-274, April.
    2. Sardar Muhammad Usman & Farasat Ali Shah Bukhari & Huiwei You & Daniel Badulescu & Darie Gavrilut, 2020. "The Effect and Impact of Signals on Investing Decisions in Reward-Based Crowdfunding: A Comparative Study of China and the United Kingdom," JRFM, MDPI, vol. 13(12), pages 1-20, December.
    3. Belleflamme, Paul & Omrani, Nessrine & Peitz, Martin, 2015. "The economics of crowdfunding platforms," Information Economics and Policy, Elsevier, vol. 33(C), pages 11-28.
    4. Gorkem Turgut Ozer & Brad N. Greenwood & Anandasivam Gopal, 2023. "Digital Multisided Platforms and Women’s Health: An Empirical Analysis of Peer-to-Peer Lending and Abortion Rates," Information Systems Research, INFORMS, vol. 34(1), pages 223-252, March.
    5. Claudia Niemeyer & Timm Teubner & Margeret Hall & Christof Weinhardt, 2018. "The Impact of Dynamic Feedback and Personal Budgets on Arousal and Funding Behaviour in Participatory Budgeting," Group Decision and Negotiation, Springer, vol. 27(4), pages 611-636, August.
    6. Jascha-Alexander Koch & Jens Lausen & Moritz Kohlhase, 2021. "Internalizing the externalities of overfunding: an agent-based model approach for analyzing the market dynamics on crowdfunding platforms," Journal of Business Economics, Springer, vol. 91(9), pages 1387-1430, November.
    7. BELLEFLAMME Paul, & LAMBERT Thomas, & SCHWIENBACHER Armin,, 2019. "Crowdfunding dynamics," LIDAM Discussion Papers CORE 2019014, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. Mi (Jamie) Zhou & Baozhou Lu & Weiguo (Patrick) Fan & G. Alan Wang, 0. "Project description and crowdfunding success: an exploratory study," Information Systems Frontiers, Springer, vol. 0, pages 1-16.
    9. Ivelin Elenchev & Aleksandar Vasilev, 2019. "Forecasting the Success Rate of Reward Based Crowdfunding Projects," Managing Global Transitions, University of Primorska, Faculty of Management Koper, vol. 17(1 (Spring), pages 51-77.
    10. Gerritsen, Dirk F., 2015. "Security analysts’ target prices and takeover premiums," Finance Research Letters, Elsevier, vol. 13(C), pages 205-213.
    11. Zhuoxin Li & Sirkka L. Jarvenpaa, 2015. "Motivating IT-Mediated Crowds: The Effect of Goal Setting on Project Performance in Online Crowdfunding," Working Papers 15-07, NET Institute.
    12. Hossain Mokter & Oparaocha Gospel Onyema, 2017. "Crowdfunding: Motives, Definitions, Typology and Ethical Challenges," Entrepreneurship Research Journal, De Gruyter, vol. 7(2), pages 1-14, April.
    13. Barlow, Euan & Tezcaner Öztürk, Diclehan & Revie, Matthew & Akartunalı, Kerem & Day, Alexander H. & Boulougouris, Evangelos, 2018. "A mixed-method optimisation and simulation framework for supporting logistical decisions during offshore wind farm installations," European Journal of Operational Research, Elsevier, vol. 264(3), pages 894-906.
    14. Oguzhan Aygoren & Stefan Koch, 2021. "Community Support or Funding Amount: Actual Contribution of Reward-Based Crowdfunding to Market Success of Video Game Projects on Kickstarter," Sustainability, MDPI, vol. 13(16), pages 1-18, August.
    15. Moradi, Masoud & Badrinarayanan, Vishag, 2021. "The effects of brand prominence and narrative features on crowdfunding success for entrepreneurial aftermarket enterprises," Journal of Business Research, Elsevier, vol. 124(C), pages 286-298.
    16. Kuti, Mónika & Galambosné Tiszberger, Mónika & Czigler, Enikő, 2018. "Magyarországról indított közösségi finanszírozású kampányok. A Kickstarter-platform esete [Kick-starter campaigns launched from Hungary]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(2), pages 206-225.

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    More about this item

    Keywords

    crowdfunding; group buying; entrepreneurship; network externality; hazards model; Bayesian inference;
    All these keywords.

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • L26 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Entrepreneurship
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software

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