It's never too late: Funding dynamics and self pledges in reward-based crowdfunding

Crosetto, Paolo; Regner, Tobias

doi:10.1016/j.respol.2018.04.020

Cited by 107 publications

(92 citation statements)

References 55 publications

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“…The plot indicates sharp increases in the cumulative pledged amount, in the beginning of campaigns but as well at later points of time. This is in line with existing evidence from conventional reward crowdfunding sites (van de Rijt et al 2014;Colombo et al 2015;Crosetto and Regner 2018). Besides the pledge boosts, several campaigns also increase their pledge level at a fairly steady pace, moving along a somewhat linear trajectory.…”

Section: Dynamics Of Pledges and Deletionssupporting

confidence: 87%

“…Our analysis of success determinants at the membership platform Patreon is consistent with the results from conventional reward crowdfunding portals (e.g., Mollick 2014;Colombo et al 2015;Crosetto and Regner 2018). A more in-depth analysis of the campaigns' content promises to be an intriguing path for future research.…”

Section: Discussionsupporting

confidence: 76%

“…The previous research on conventional reward crowdfunding platforms, like Kickstarter or Indiegogo, shows that projects' communication with funders is a key driver of success. For instance, Mollick (2014), Colombo et al (2015), Crosetto and Regner (2018) find that Web site measures like videos, images and blog entries are determinants of project success. 1 This evidence suggests that effort put into communicating the project's goal pays off as it is rewarded by the crowd.…”

Section: Introductionmentioning

confidence: 99%

“…1 This evidence suggests that effort put into communicating the project's goal pays off as it is rewarded by the crowd. Studies analyzing the dynamics in reward crowdfunding show herding behavior among the crowd, very early in the funding period (van de Rijt et al 2014;Colombo et al 2015) but also later (Crosetto and Regner 2018).…”

Section: Introductionmentioning

confidence: 99%

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Crowdfunding a monthly income: an analysis of the membership platform Patreon

Regner¹

2020

J Cult Econ

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Membership platforms allow creators to crowdfund a monthly income, while campaigns on conventional reward crowdfunding portals aim to reach a specified funding target within a preset period. We study transaction-level data from Patreon, the biggest membership platform, to gain insights about behavioral patterns at this emerging type of crowdfunding. Our analysis shows that hundreds of creators crowdfund a sizable income (more than $2500 monthly). We also find that measures of communication quality are determinants of project success, in line with the related literature. Funding dynamics-pledges as well as deletions-are heterogeneous across campaigns. Our analysis suggests that the option to delete the monthly pledge to a creator at any time serves as a feedback mechanism. We conclude that crowdfunding a monthly income offers the creative class a viable alternative to advertising-based business models.

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Section: Dynamics Of Pledges and Deletionssupporting

confidence: 87%

Section: Discussionsupporting

confidence: 76%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Crowdfunding a monthly income: an analysis of the membership platform Patreon

Regner¹

2020

J Cult Econ

Self Cite

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“…Communication, in the form of updates, is used as a key to increase investments during the funding period by the project creators in equity-based crowdfunding [8]. Some studies focus on investigating the dynamics of reward-based crowdfunding [9][10][11][12][13]. In [14], a field experiment was performed to study the effect of an investment in a project which was previously unfunded.…”

Section: Crowdfunding Dynamicsmentioning

confidence: 99%

Topic Predictions and Optimized Recommendation Mechanism Based on Integrated Topic Modeling and Deep Neural Networks in Crowdfunding Platforms

Shafqat

Byun

2019

Applied Sciences

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The accelerated growth rate of internet users and its applications, primarily e-business, has accustomed people to write their comments and reviews about the product they received. These reviews are remarkably competent to shape customers' decisions. However, in crowdfunding, where investors finance innovative ideas in exchange for some rewards or products, the comments of investors are often ignored. These comments can play a markedly significant role in helping crowdfunding platforms to battle against the bitter challenge of fraudulent activities. We take advantage of the language modeling techniques and aim to merge them with neural networks to identify some hidden discussion patterns in the comments. Our objective is to design a language modeling based neural network architecture, where Recurrent Neural Networks (RNN) Long Short-Term Memory (LSTM) is used to predict discussion trends, i.e., either towards scam or non-scam. LSTM layers are fed with latent topic distribution learned from the pre-trained Latent Dirichlet Allocation (LDA) model. In order to optimize the recommendations, we used Particle Swarm Optimization (PSO) as a baseline algorithm. This module helps investors find secure projects to invest in (with the highest chances of delivery) within their preferred categories. We used prediction accuracy, an optimal number of identified topics, and the number of epochs, as metrics of performance evaluation for the proposed approach. We compared our results with simple Neural Networks (NNs) and NN-LDA based on these performance metrics. The strengths of both integrated models suggest that the proposed model can play a substantial role in a better understanding of crowdfunding comments.

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Crowdfunding industry—History, development, policies, and potential issues

Ying

Harris

Lam

2019

Journal of Public Affairs

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Crowdfunding has gained a great deal of attention from policy makers, researchers, and practitioners. This paper attempts to provide an overview of the history and development of the industry and discusses different types of crowdfunding and their public policies. It is identified that the operation of peer-to-peer lending and equitybased crowdfunding is regulated by the Financial Authority; the reward-based crowdfunding (RBC) and donation-based crowdfunding (DBC) is yet to be regulated, neither in the United Kingdom or United States. The lack of rules and regulations in the latter two models highlights the burning issues such as potential fraud and malpractice. Therefore, we suggest that it is timely to consider regulating the two types of crowdfunding possibly by governance mechanism with reporting requirements to keep track of the fund and to provide timely information. Additionally, it is advisable that practitioners to work on an agreed framework to establish industry standard, so potential investors can compare and assess the quality of projects easily. Finally, the management of crowdfunding platforms especially the RBC and DBC platforms should be improved. The ease of launching campaigns has made it difficult for both initiators and investors to succeed in the crowdfunding process. Further research to develop some form of assessment framework would be useful to both parties.

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It's never too late: Funding dynamics and self pledges in reward-based crowdfunding

Cited by 107 publications

References 55 publications

Crowdfunding a monthly income: an analysis of the membership platform Patreon

Crowdfunding a monthly income: an analysis of the membership platform Patreon

Topic Predictions and Optimized Recommendation Mechanism Based on Integrated Topic Modeling and Deep Neural Networks in Crowdfunding Platforms

Crowdfunding industry—History, development, policies, and potential issues

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