Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Issue title: Re-inventing or Revitalizing: Challenges for the post-pandemic era
Guest editors: Matjaž Novak and Anita Trnavčevič
Article type: Research Article
Authors: Dağlı, İbrahima; * | Pehlivan, Cerenb; 1 | Özbay, Ferhatc; 2
Affiliations: [a] Department of Business Administration, Faculty of Economics, Administrative and Social Sciences, Cyprus West University, Famagusta, Cyprus | [b] Inonu University, Malatya, Turkey | [c] Yalvac Vocational School, Isparta University of Applied Sciences, Yalvac, Turkey
Correspondence: [*] Corresponding author: İbrahim Dağlı, Cyprus West University, Faculty of Economics, Administrative and Social Sciences, Department of Business Administration, Famagusta, Cyprus. E-mail: [email protected]; ORCID ID: 0000-0001-8199-821X.
Note: [1] ORCID ID: 0000-0001-5632-2955.
Note: [2] ORCID ID: 0000-0002-7756-3835.
Abstract: BACKGROUND:Like Bitcoin or any other cryptocurrencies, non-fungible tokens (NFTs) count on blockchain technology, and NFTs are the latest and the most popular in a series of blockchain solutions. Traders in this ecosystem need to pay a dynamic fee, called a gas fee, for making any transactions on the Ethereum blockchain. The gas fee is measured by gwei, and traders must consider this as an additional cost. So, the current price of this fee may affect the decision of NFT creators or traders. OBJECTIVE:This study investigates the interrelationships between NTFs, cryptocurrencies (Ethereum and BTC), and gas fees using daily market data from January 2019 to November 2021. METHOD:Fourier Shin’s (2016) cointegration test, Fully Modified Ordinary Least Squares, and Group Dynamic Least Squares tests were employed to analyze the data. Then, the variance Decomposition method was applied to determine what other variables explain the percentage of the total variance on NFTs— it also used Impulse-response functions for measuring the response of the NFTs variable for one standard deviation shock. RESULTS:Results show that an increase in gas fees, the daily volume of Bitcoin, and the daily volume of Ethereum decrease NFTs sales. There is a unidirectional relationship between lnSales and lnGasFee variables. Also, there is a determined unidirectional relationship between lnBTC and lnSales variables. Lastly, there is a one-way causality relationship between lnSales and lnETH variables. CONCLUSIONS:The primary causation of the relationship between NFTs, gas fees and Ethereum fees is most likely related to the use of Ethereum as the primary means of payment in the NFTs market and gas fees being a significant cost element in NFTs trading. Another point of view is that the dominance of Bitcoin in the market is very effective in pricing of other cryptocurrencies and in the sales and pricing of NFTs indirectly. It is supported by empirical findings that the main elements in the blockchain ecosystem are interrelated.
Keywords: Non-fungible token, cryptocurrencies, and blockchain technology
DOI: 10.3233/HSM-220196
Journal: Human Systems Management, vol. 42, no. 6, pp. 633-645, 2023
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
[email protected]
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office [email protected]
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
如果您在出版方面需要帮助或有任何建, 件至: [email protected]