Identifying On-time Reward Delivery Projects with Estimating Delivery Duration on Kickstarter

TL;DR

This paper develops models to predict whether reward-based crowdfunding projects on Kickstarter will deliver rewards on time and estimates their delivery durations, addressing a gap in understanding reward delivery timelines.

Contribution

It introduces novel features for assessing reward difficulty, and presents predictive and regression models for on-time delivery and duration estimation, respectively.

Findings

Models achieve 82.5% accuracy in on-time delivery prediction.

Regression model attains 78.1 RMSE and 0.108 NRMSE early in the delivery timeline.

Features reveal latent difficulty levels of project rewards.

Abstract

In Crowdfunding platforms, people turn their prototype ideas into real products by raising money from the crowd, or invest in someone else's projects. In reward-based crowdfunding platforms such as Kickstarter and Indiegogo, selecting accurate reward delivery duration becomes crucial for creators, backers, and platform providers to keep the trust between the creators and the backers, and the trust between the platform providers and users. According to Kickstarter, 35% backers did not receive rewards on time. Unfortunately, little is known about on-time and late reward delivery projects, and there is no prior work to estimate reward delivery duration. To fill the gap, in this paper, we (i) extract novel features that reveal latent difficulty levels of project rewards; (ii) build predictive models to identify whether a creator will deliver all rewards in a project on time or not; and (iii) build a regression model to estimate accurate reward delivery duration (i.e., how long it will take to produce and deliver all the rewards). Experimental results show that our models achieve good performance -- 82.5% accuracy, 78.1 RMSE, and 0.108 NRMSE at the first 5% of the longest reward delivery duration.