Coordination and Dynamic Promotion Strategies in Crowdfunding with Network Externalities

Li, Zhuoxin; Duan, Jason A.; Ransbotham, Sam

doi:10.1111/poms.13150

Cited by 33 publications

(24 citation statements)

References 56 publications

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“…Videos also can help introduce projects and give people closer looks at creators' work. Some scholars account empirically for the presence of visual information [14,9,19]. Mollick [1] argues that the inclusion of video signals preparation and higher project quality; in turn, the presence of video is associated with greater crowdfunding success (see also [7,20,6].…”

Section: Number Of Pictures and Videosmentioning

confidence: 99%

Extracting Image Characteristics to Predict Crowdfunding Success

Blanchard¹,

Noseworthy²,

Pancer³

et al. 2022

Preprint

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Despite an increase in the empirical study of crowdfunding platforms and the prevalence of visual information, operations management and marketing literature has yet to explore the role that image characteristics play in crowdfunding success. The authors of this manuscript begin by synthesizing literature on visual processing to identify several image characteristics that are likely to shape crowdfunding success. After detailing measures for each image characteristic, they use them as part of a machine-learning algorithm (Bayesian additive trees), along with project characteristics and textual information, to predict crowdfunding success. Results show that the inclusion of these image characteristics substantially improves prediction over baseline project variables, as well as textual features. Furthermore, image characteristic variables exhibit high importance, similar to variables linked to the number of pictures and number of videos. This research therefore offers valuable resources to researchers and managers who are interested in the role of visual information in ensuring new product success.Crowdfunding allows entrepreneurs to request funding from many investors simultaneously, usually in exchange for future products or equity stakes [1,2]. Recent legislative changes also give consumers and firms new ways to interact along these lines. Since 2016, when the U.S. Securities and Exchange Commission (SEC) allowed investors of all net worth amounts to participate in crowdfunding, there has been a substantial increase in the amount of money raised on crowdfunding platforms; in 2020, it reached $500 million in the United States alone, according to the Crowdfunding Center 1 . Dozens of different crowdfunding platforms support rewards-based investing (e.g., Kickstarter, Indiegogo) and equity-based investing (e.g., SeedInvest, StartEngine), and others specialize in individual help (e.g., GoFundMe) and nonprofit funding (e.g., Mightycause). The number of international crowdfunding platforms also has grown, with platforms covering all regions of the world (e.g., JD Crowdfunding and Jingdong in China, Babyloan in France, Crowdprop in South Africa).Both operations management and marketing literature have found many interesting uses for increasingly available crowdfunding data. Some operations management authors leverage crowdfunding data to substantiate the role of new technologies in selecting and disseminating new ideas [3,4], whereas others have sought to identify predictors of crowdfunding success (c.f., [5,6])-such as backer dynamics [7], referral timing [8], founder updates [9], and frequency 1 https://www.thecrowdfundingcenter.com/

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Section: Number Of Pictures and Videosmentioning

confidence: 99%

Extracting Image Characteristics to Predict Crowdfunding Success

Blanchard¹,

Noseworthy²,

Pancer³

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…Researchers intensively study network effects of two-sided platforms in recent years. Li et al [23] examine the network effects of backers on crowdfunding projects. Hinz et al [24] propose an influx-outflow model for estimation of network effects on two-sided business-to-consumer (B2C) platforms.…”

Section: Literature Reviewmentioning

confidence: 99%

Coordinating Demand and Supply for Crowd Logistics Platforms with Network Effect

Wang

Xie

2021

Mathematical Problems in Engineering

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The crowd logistics platforms connect stochastic demand with uncertain delivery supply which is provided by independent service providers. Considering direct-network effects and cross-network effects between the demand and supply side, a dynamic surge pricing model for crowd logistics platforms is built. The pricing strategy is derived to coordinate the supply with demand to equilibrium. Furthermore, the pricing strategy minimizing cumulative delivery orders is analyzed. The numerical simulation results show that the dynamic surge pricing strategies can stimulate the uncertain delivery supply for maximizing platforms’ revenue. And, direct-network effects pose a positive impact on the dynamic surge pricing strategy. In contrast, the cross-network effects have a negative impact on the pricing strategy. However, direct-network effects and cross-network effects negatively influence platforms’ revenue.

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“…While recent operations research has been concentrated on rewards-based (pre-selling) funding (Li et al 2020, Wei et al 2020 or debt-based funding (Lu et al 2020), equity funding has different dynamics (Roma et al 2018). Overall, funders in rewards-based or debt-based do not have to look for guidance in what to fund because they support projects they care about.…”

Section: Equity Crowdfundingmentioning

confidence: 99%

“…This implies that lead investors with a network of followers and experience in assessing startups in a crowdfunding context are essential to a crowdfunding platform's success. These crowdfunding campaigns must ensure that the quality of their offerings is properly communicated (Chakraborty and Swinney 2021), that misconduct of both the startup team and potential investors is effectively policed (Belavina et al 2020), and that the coordination between the startups and their investors is efficiently managed (Li et al 2020). While these activities could all be fulfilled by an experienced lead investor, none of these studies address how high-performing investors can be identified and engaged by the platform as lead investors to improve their funding operations.…”

Section: Identifying High-performance Investorsmentioning

confidence: 99%

Improving Funding Operations of Equity‐based Crowdfunding Platforms

Aggarwal

Lee

Osting

et al. 2021

Production and Operations Management

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E quity-based crowdfunding platforms enable investors to come together to invest in startups and help lay-investors to follow the lead of investors with good startup evaluation skills. Crowdfunding platforms often gather users' inputs to evaluate investors and startups, but such inputs are quite noisy and often rely on past performance. Many investors with good evaluation skills do not have substantial past investment experience but still can lead investment rounds. This helps provide investment opportunities to lay-investors who otherwise do not get to join investors with proven records. Without identifying such investors with potential, platforms lose the opportunity to put together investors to fund worthy startups and lose business. We develop a Bayesian model to address this problem and improve funding operations of equity-based crowdfunding platforms. Specifically, the model helps platforms to better assess investors' evaluation skills, identify lead investors for lay-investors to follow, and increase funding opportunities on the platforms. To test the effectiveness of the proposed model, we gathered data from 319 actual investors listed on one of the largest crowdfunding platforms in the United States, picked startups randomly for investors to evaluate, and had investors evaluate startups in two ways-our approach and the conventional approach. We also discuss an extension of this Bayesian model that penalizes investors in case investors perform well by randomness. Furthermore, we used a Bayesian framework to help platforms better predict startup valuations accounting for investors' evaluation skills.

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Coordination and Dynamic Promotion Strategies in Crowdfunding with Network Externalities

Cited by 33 publications

References 56 publications

Extracting Image Characteristics to Predict Crowdfunding Success

Extracting Image Characteristics to Predict Crowdfunding Success

Coordinating Demand and Supply for Crowd Logistics Platforms with Network Effect

Improving Funding Operations of Equity‐based Crowdfunding Platforms

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