Pricing Decisions on Reward-Based Crowdfunding with Bayesian Review System Facing Strategic Consumers - Yuting Chen; Rong Zhang; Bin Liu (Discrete Dynamics in Nature and Society)
Crowdfunding marks a popular and sustainable means by which small and microentrepreneurs obtain financial resources for their innovative project. Consumers increasingly rely on online reviews to make purchase decisions. However, the crowdfunding nowadays lacks a form type of review system. This paper is designed to extend research on the optimal pricing decision with review system for the reward-based crowdfunding. Firstly, a Bayesian analysis is established to construct consumers’ belief update process in presence of review system. Secondly, we take the strategies without the review system as a benchmark to explore the impacts of review system under preannounced pricing and responsive pricing. Finally, through the equilibrium analysis, we find that the review system has a positive impact on the creator under responsive pricing policy. The fraction of favorable review has a large effect on the profit of preannounced pricing. When the fraction is about 80%, the profit is the maximum. Generally speaking, the review system will make more profit for the creator.