Crowdfunding for Design Innovation: Prediction Model With Critical Factors

Abstract

Online reward-based crowdfunding campaigns have emerged as an innovative approach for validating demands, discovering early adopters, and seeking learning and feedback in the design processes of innovative products. However, crowdfunding campaigns for innovative products are faced with a high degree of uncertainty and suffer meager rates of success to fulfill their values for design. To guide designers and innovators for crowdfunding campaigns, this paper presents a data-driven methodology to build a prediction model with critical factors for crowdfunding success, based on public online crowdfunding campaign data. Specifically, the methodology filters 26 candidate factors in the Real-Win-Worth framework and identifies the critical ones via step-wise regression to predict the amount of crowdfunding. We demonstrate the methodology via deriving prediction models and identifying essential factors from 3D printer and smartwatch campaign data on Kickstarter and Indiegogo. The critical factors can guide campaign developments, and the prediction model may evaluate crowdfunding potential of innovations in contexts, to increase the chance of crowdfunding success of innovative products.

Crowdfunding Platform as an Open Innovation Model: The Importance of Effective Platform Governance

“…The developed business model utilizes the Business Model Canvas, and the proposed crowdfunding business model is specifically designed for non-profit organizations [33]. Further research on crowdfunding has also been conducted by Chaoyang Song, Jianxi Luo, Katja Hölttä-Otto, Warren Seering, and Kevin Otto [34]. Using the Data-driven and Critical Factors methods, this study construct a prediction model with important factors for success of reward-based CFP.…”

Digital inclusive finance and asset allocation of Chinese residents: Evidence from the China Household Finance Survey

“…The impact of digital financial inclusion development on enterprises is more about improving the efficiency of financing and improving the level of financial stability. [ 32 ] Internet finance can help enterprises obtain a more comprehensive range of financial support, improve their financing efficiency and reduce their financing costs, and [ 33 ] argue that new technologies can help match the supply and demand of funds over long distances and improve the efficiency of capital use. The development of information technology also helps overcome the information asymmetry problem in traditional financial markets.…”

Data-Driven Design-by-Analogy: State of the Art and Future Directions

“…The crowdsourced solutions make it possible to mine the real-world ideation outputs of complex cognitive tasks generated by thousands of people across the world. In addition, some researchers have observed that crowdfunding platforms (e.g., Kickstarter and Indiegogo) also accumulate product design projects and contain rich design information about product designs, and are therefore potentially useful data sources for analogical design stimuli [100].…”

“…Both have been used in many data-driven DbA studies [5,15,64]. Although crowdsourced design data [97,98,99] and crowdfunded project data [100] have been explored in design research and are also potentially useful for DbA studies, they have not been fully exploited. In addition, most of the current data-driven DbA methods were designed to merely mine textual information as analogy candidates; only a few researchers have focused on the data of other modalities [13,92].…”