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Project description and crowdfunding success: an exploratory study

Author

Listed:
  • Mi (Jamie) Zhou

    (Virginia Polytechnic Institute and State University)

  • Baozhou Lu

    (China University of Petroleum)

  • Weiguo (Patrick) Fan

    (Virginia Polytechnic Institute and State University)

  • G. Alan Wang

    (Virginia Polytechnic Institute and State University)

Abstract

Existing research on antecedent of funding success mainly focuses on basic project properties such as funding goal, duration, and project category. In this study, we view the process by which project owners raise funds from backers as a persuasion process through project descriptions. Guided by the unimodel theory of persuasion, this study identifies three exemplary antecedents (length, readability, and tone) from the content of project descriptions and two antecedents (past experience and past expertise) from the trustworthy cue of project descriptions. We then investigate their impacts on funding success. Using data collected from Kickstarter, a popular crowdfunding platform, we find that these antecedents are significantly associated with funding success. Empirical results show that the proposed model that incorporated these antecedents can achieve an accuracy of 73 % (70 % in F-measure). The result represents an improvement of roughly 14 percentage points over the baseline model based on informed guessing and 4 percentage points improvement over the mainstream model based on basic project properties (or 44 % improvement of mainstream’s performance over informed guessing). The proposed model also has superior true positive and true negative rates. We also investigate the timeliness of project data and find that old project data is gradually becoming less relevant and losing predictive power to newly created projects. Overall, this study provides evidence that antecedents identified from project descriptions have incremental predictive power and can help project owners evaluate and improve the likelihood of funding success.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:infosf:v::y::i::d:10.1007_s10796-016-9723-1
    DOI: 10.1007/s10796-016-9723-1
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    References listed on IDEAS

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    Cited by:

    1. Bagheri, Afsaneh & Chitsazan, Hasti & Ebrahimi, Ashkan, 2019. "Crowdfunding motivations: A focus on donors' perspectives," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 218-232.
    2. Saif Ullah & Yulin Zhou, 2020. "Gender, Anonymity and Team: What Determines Crowdfunding Success on Kickstarter," JRFM, MDPI, vol. 13(4), pages 1-26, April.
    3. Chan, C.S. Richard & Park, Haemin Dennis & Huang, Julie Y. & Parhankangas, Annaleena, 2020. "Less is more? Evidence for a curvilinear relationship between readability and screening evaluations across pitch competition and crowdfunding contexts," Journal of Business Venturing Insights, Elsevier, vol. 14(C).
    4. Hamed M. Zolbanin & Dursun Delen & Durand Crosby & David Wright, 2020. "A Predictive Analytics-Based Decision Support System for Drug Courts," Information Systems Frontiers, Springer, vol. 22(6), pages 1323-1342, December.
    5. Duan, Yang & Hsieh, Tien-Shih & Wang, Ray R. & Wang, Zhihong, 2020. "Entrepreneurs' facial trustworthiness, gender, and crowdfunding success," Journal of Corporate Finance, Elsevier, vol. 64(C).
    6. Roman Lukyanenko & Andrea Wiggins & Holly K. Rosser, 0. "Citizen Science: An Information Quality Research Frontier," Information Systems Frontiers, Springer, vol. 0, pages 1-23.
    7. Susana Bernardino & J. Freitas Santos, 2020. "Crowdfunding: An Exploratory Study on Knowledge, Benefits and Barriers Perceived by Young Potential Entrepreneurs," JRFM, MDPI, vol. 13(4), pages 1-24, April.
    8. Keng Yang, 2019. "Research on Factors Affecting Solvers’ Participation Time in Online Crowdsourcing Contests," Future Internet, MDPI, vol. 11(8), pages 1-13, August.
    9. Chan, Ho Fai & Moy, Naomi & Schaffner, Markus & Torgler, Benno, 2021. "The effects of money saliency and sustainability orientation on reward based crowdfunding success," Journal of Business Research, Elsevier, vol. 125(C), pages 443-455.
    10. Xiaobei Liang & Xiaojuan Hu & Jiang Jiang, 2020. "Research on the Effects of Information Description on Crowdfunding Success within a Sustainable Economy—The Perspective of Information Communication," Sustainability, MDPI, vol. 12(2), pages 1-36, January.
    11. Hamed M. Zolbanin & Dursun Delen & Durand Crosby & David Wright, 0. "A Predictive Analytics-Based Decision Support System for Drug Courts," Information Systems Frontiers, Springer, vol. 0, pages 1-20.
    12. Messeni Petruzzelli, Antonio & Natalicchio, Angelo & Panniello, Umberto & Roma, Paolo, 2019. "Understanding the crowdfunding phenomenon and its implications for sustainability," Technological Forecasting and Social Change, Elsevier, vol. 141(C), pages 138-148.
    13. Michael J. Ryoba & Shaojian Qu & Ying Ji & Deqiang Qu, 2020. "The Right Time for Crowd Communication during Campaigns for Sustainable Success of Crowdfunding: Evidence from Kickstarter Platform," Sustainability, MDPI, vol. 12(18), pages 1-22, September.
    14. Felipe, Israel José dos Santos & Mendes-Da-Silva, Wesley & Leal, Cristiana Cerqueira & Braun Santos, Danilo, 2022. "Reward crowdfunding campaigns: Time-to-success analysis," Journal of Business Research, Elsevier, vol. 138(C), pages 214-228.
    15. Peter Konhäusner & Bing Shang & Dan-Cristian Dabija, 2021. "Application of the 4Es in Online Crowdfunding Platforms: A Comparative Perspective of Germany and China," JRFM, MDPI, vol. 14(2), pages 1-19, January.
    16. Chan, C.S. Richard & Pethe, Charuta & Skiena, Steven, 2021. "Natural language processing versus rule-based text analysis: Comparing BERT score and readability indices to predict crowdfunding outcomes," Journal of Business Venturing Insights, Elsevier, vol. 16(C).
    17. Michael J. Ryoba & Shaojian Qu & Yongyi Zhou, 2021. "Feature subset selection for predicting the success of crowdfunding project campaigns," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(3), pages 671-684, September.
    18. Qianzhou Du & Jing Li & Yanqing Du & G. Alan Wang & Weiguo Fan, 2021. "Predicting crowdfunding project success based on backers' language preferences," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(12), pages 1558-1574, December.
    19. Roman Lukyanenko & Andrea Wiggins & Holly K. Rosser, 2020. "Citizen Science: An Information Quality Research Frontier," Information Systems Frontiers, Springer, vol. 22(4), pages 961-983, August.
    20. Zhao, Liang & Shneor, Rotem & Sun, Zhe, 2022. "Skin in the game: Self-funding and reward crowdfunding success," Business Horizons, Elsevier, vol. 65(1), pages 89-100.

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