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The Penguin Effect of NFT for Brands and How Brands can Benefit from NFT
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NFT (non-fungible token) has become one of the most popular terms since last year, a large number of established brands are releasing their own NFT collections. In this proposal, the author first describes the hidden mechanism of NFT and how brands are usually using NFT. Based on the digital asset literature, the author concludes that NFT stands for a digital asset for brands in a decentralized environment. From the BAV survey data and NFT adoption data for 511 brands, the author finds cars, clothing products, and household products account for the top 3 categories that have the largest percentage of NFT adoption. By applying OLS method to multiple features of the brands and classifying whether the brands adopt NFT, and IV estimation to address endogeneity, the author discovers the most important feature for a brand to adopt NFT is interband top list, which is in accordance with the penguin effect in business world. For the next step, the author plans to collect data about the sales of various NFT collections released by these brands and discover under what condition, can the sales of NFT collections become higher for brands. In addition, NFTs are based on decentralized system, which may be disruptive for brands developed in a centralized environment, and inertia and lack of cooperation becomes an obstacle for big brands to adopt NFTs. The author plans to provide managerial insights to tackle this problem.
Title: The Penguin Effect of NFT for Brands and How Brands can Benefit from NFT
Description:
NFT (non-fungible token) has become one of the most popular terms since last year, a large number of established brands are releasing their own NFT collections.
In this proposal, the author first describes the hidden mechanism of NFT and how brands are usually using NFT.
Based on the digital asset literature, the author concludes that NFT stands for a digital asset for brands in a decentralized environment.
From the BAV survey data and NFT adoption data for 511 brands, the author finds cars, clothing products, and household products account for the top 3 categories that have the largest percentage of NFT adoption.
By applying OLS method to multiple features of the brands and classifying whether the brands adopt NFT, and IV estimation to address endogeneity, the author discovers the most important feature for a brand to adopt NFT is interband top list, which is in accordance with the penguin effect in business world.
For the next step, the author plans to collect data about the sales of various NFT collections released by these brands and discover under what condition, can the sales of NFT collections become higher for brands.
In addition, NFTs are based on decentralized system, which may be disruptive for brands developed in a centralized environment, and inertia and lack of cooperation becomes an obstacle for big brands to adopt NFTs.
The author plans to provide managerial insights to tackle this problem.
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