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Voting Participation and Engagement in Blockchain-Based Fan Tokens

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Listed:
  • Lennart Ante
  • Aman Saggu
  • Benjamin Schellinger
  • Friedrich Wazinksi

Abstract

This paper investigates the potential of blockchain-based fan tokens, a class of crypto asset that grants holders access to voting on club decisions and other perks, as a mechanism for stimulating democratized decision-making and fan engagement in the sports and esports sectors. By utilizing an extensive dataset of 3,576 fan token polls, we reveal that fan tokens engage an average of 4,003 participants per poll, representing around 50% of token holders, underscoring their relative effectiveness in boosting fan engagement. The analyses identify significant determinants of fan token poll participation, including levels of voter (dis-)agreement, poll type, sports sectors, demographics, and club-level factors. This study provides valuable stakeholder insights into the current state of adoption and voting trends for fan token polls. It also suggests strategies for increasing fan engagement, thereby optimizing the utility of fan tokens in sports. Moreover, we highlight the broader applicability of fan token principles to any community, brand, or organization focused on customer engagement, suggesting a wider potential for this digital innovation.

Suggested Citation

  • Lennart Ante & Aman Saggu & Benjamin Schellinger & Friedrich Wazinksi, 2024. "Voting Participation and Engagement in Blockchain-Based Fan Tokens," Papers 2404.08906, arXiv.org.
    • Handle: RePEc:arx:papers:2404.08906
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    References listed on IDEAS

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    1. Bastian Popp & Herbert Woratschek, 2016. "Introducing branded communities in sport for building strong brand relations in social media," Sport Management Review, Taylor & Francis Journals, vol. 19(2), pages 183-197, April.
    2. Assaf, Ata & Demir, Ender & Ersan, Oguz, 2024. "Detecting and date-stamping bubbles in fan tokens," International Review of Economics & Finance, Elsevier, vol. 92(C), pages 98-113.
    3. Ricardo Cayolla & Sandra Maria Correia Loureiro, 2014. "Fans club brand relationship: football passion," International Journal of Business and Globalisation, Inderscience Enterprises Ltd, vol. 12(1), pages 82-97.
    4. David Vidal-Tomás, 2023. "Blockchain, sport and fan tokens," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 51(1), pages 24-38, April.
    5. Kevin Filo & Daniel Lock & Adam Karg, 2015. "Sport and social media research: A review," Sport Management Review, Taylor & Francis Journals, vol. 18(2), pages 166-181, April.
    6. Lennart Ante & Benjamin Schellinger & Ender Demir, 2024. "The impact of football games and sporting performance on intra-day fan token returns," Journal of Business Economics, Springer, vol. 94(5), pages 813-850, July.
    7. Funk, Daniel C. & James, Jeff, 2001. "The Psychological Continuum Model: A Conceptual Framework for Understanding an Individual's Psychological Connection to Sport," Sport Management Review, Elsevier, vol. 4(2), pages 119-150, November.
    8. Demir, Ender & Ersan, Oguz & Popesko, Boris, 2022. "Are Fan Tokens Fan Tokens?," Finance Research Letters, Elsevier, vol. 47(PB).
    9. Popp, Bastian & Woratschek, Herbert, 2016. "Introducing branded communities in sport for building strong brand relations in social media," Sport Management Review, Elsevier, vol. 19(2), pages 183-197.
    10. Daniel C. Funk & Jeff James, 2001. "The Psychological Continuum Model: A Conceptual Framework for Understanding an Individual's Psychological Connection to Sport," Sport Management Review, Taylor & Francis Journals, vol. 4(2), pages 119-150, July.
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    1. Saggu, Aman & Ante, Lennart & Demir, Ender, 2024. "Anticipatory gains and event-driven losses in blockchain-based fan tokens: Evidence from the FIFA World Cup," Research in International Business and Finance, Elsevier, vol. 70(PA).

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    More about this item

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • D71 - Microeconomics - - Analysis of Collective Decision-Making - - - Social Choice; Clubs; Committees; Associations
    • D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making

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