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Chasing Market Growth and Matching Performance in Two-Sided Platforms: Evidence from the Lazy-Minting Policy in an NFT Marketplace

匹配(统计) 质量(理念) 产品(数学) 产业组织 业务 市场份额 平衡(能力) 新产品开发 上市时间 营销 经济 安全性令牌 价格溢价 市场份额分析 市场规模 微观经济学 市场价格 最佳匹配
作者
Hong Zhang,Hongchang Wang,Amit Mehra,Zhiqiang Zheng
出处
期刊:Management Science [Institute for Operations Research and the Management Sciences]
标识
DOI:10.1287/mnsc.2022.03573
摘要

A common challenge faced by two-sided marketplaces is to expand the market while ensuring satisfactory matching of the two sides. We study a new platform growth strategy that increases market thickness with free entry while allowing suppliers to discretionarily signal product quality to buyers, thus forming a tiered market structure that maintains matching performance. We consider such an example with nonfungible token (NFT) markets where suppliers could choose to delay the entry cost of the NFT creation fee until an NFT is sold (lazy minting) or pay the fee up front at the time of NFT creation (gas minting). We use the difference-in-differences strategy to identify the impact of this lazy-minting policy on market matching performance. We find that the impacts of this policy are multifaceted: Although the introduction of lazy minting reduces the average matching likelihood of an NFT by 98.2%, it increases the gas-minting segment’s matching likelihood by 112.3% and first-sale price by 126.5%. Overall, this new growth strategy benefits the platform because of increased total sales and higher revenues. We unravel two mechanisms: the market thickness effect and the quality signaling effect. For the latter, we introduce a systematic framework to empirically establish the quality signaling mechanism with a separating equilibrium, where suppliers prefer gas minting for their high-quality creations. This effectively sends a quality signal that buyers could rely on to recognize high-quality NFTs. This new platform growth strategy provides generic implications for platforms endeavoring to balance market thickness and matching performance. This paper was accepted by Anindya Ghose, information systems. Supplemental Material: The online appendices and data files are available at https://doi.org/10.1287/mnsc.2022.03573 .
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