【Author】
Li, Jian; Wan, Xiang (Shawn); Cheng, Hsing Kenneth; Zhao, Xi
【Source】INFORMATION SYSTEMS RESEARCH
【Abstract】The rapid advancement and adoption of blockchain technology have heralded an explosive growth of Initial Coin Offerings (ICOs) as a new and popular fundraising approach for blockchain start-ups. To motivate blockchain individuals to invest in the subsequent ICO, a growing number of blockchain-based project founders employ the airdrop campaign, through which they distribute a specific amount of free official tokens or promotional tokens to potential investors on the blockchain with or without their permission. Of paramount concern to the founders contemplating whether to launch an airdrop campaign are whether the airdrop campaign has a positive effect on the potential investors' investment behaviors in their ICOs and how the efficacy of the airdrop may vary with investors. To address these critical questions, we implement a regression discontinuity design by leveraging the quasi -randomization of a blockchain project's promotional airdrop campaign on the Ethereum platform. We find that the promotional airdrop leads to a 2.3 times increase in the potential investors' ICO investment probability, as well as a significant and positive effect on their investment amount. We further find that the airdrop is more effective in increasing the investment for individuals with transacted projects dissimilar to the focal project than those with similar ones, which supports the diversification perspective in investment. We also find that the airdrop can motivate token receivers to stick with the focal project for a longer period. We show the generalizability of our findings by leveraging the randomized token airdrop strategies of multiple ICO projects. Our study contributes to the literature on ICOs and marketing strategy for financial instruments and provides important implications to blockchain start-ups on whether and how to launch an airdrop campaign.
【Keywords】initial coin offering (ICO); airdrop; token drop; project similarity; natural language processing; diversification
【文献类型】Article; Early Access
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