한국IT서비스학회지 (Journal of Information Technology Services)

한국IT서비스학회 (Korea Society of IT Services)
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콘텐츠 창작자들의 NFT 시장 참여에 대한 긍·부정 요인 연구: 혼합적 방법론을 적용하여

Exploring Factors that Affect Content Creators' Participation in the NFT Market: Applying Mixed-methods Approach

  • 양지훈 (한국문화관광연구원 문화산업연구센터) ;
  • 윤상혁 (한국기술교육대학교 산업경영학부)
  • 투고 : 2022.07.07
  • 심사 : 2022.08.20
  • 발행 : 2022.08.31
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초록

NFTs, which guarantee ownership of digital files using blockchain technology, are the new field for the content industry. The NFT provided new opportunities for content creators to trade digital contents without going through mediation freely. Additionally, collectors and investors can safely and easily own their works without the threat of illegal copies. However, since only a limited number of content creators are participating in the NFT market, there needs to be an influx of various content creators and a process of popularization for this market to grow and develop into the main stage. Furthermore, research on NFT has been limited, and understanding the drivers of creators choosing to participate in NFT is insufficient. Thus, this study aims to identify the factors affecting content creators participating in NFT by applying a mixed-methods approach and presenting practical implications. Using topic modeling and in-depth interviews, this study derives the positive and negative factors and suggests strategies to activate content creators' participation in the NFT market. Through this, we can guide that management implication to reduce the risks and costs of participating in NFTs is needed to encourage the participation of creators. It will also provide insight into ways to develop the NFT content market.

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과제정보

이 논문은 2022년도 한국기술교육대학교 신임교수 연구과제 지원에 의하여 연구되었음.

참고문헌

  1. 김소담, 전병진, 이소현, "악플의 원인 및 피해 관련 주요 요인 분석: 혼합 방법론 접근", 인터넷전자상거래연구, 제21권, 제6호, 2021, 151-170.
  2. 배정환, 손지은, 송민, "텍스트 마이닝을 이용한 2012년 한국대선 관련 트위터 분석", 지능정보연구, 제19권, 제3호, 2013, 141-156. https://doi.org/10.13088/JIIS.2013.19.3.141
  3. 배재권, "사물인터넷(IoT) 서비스의 혁신저항 및 활성화 저해요인에 관한 연구: 전문가 심층인터뷰 방법을 중심으로", e-비즈니스연구, 제18권, 제2호, 2017, 289-300. https://doi.org/10.15719/GEBA.18.2.201705.289
  4. 송화윤, "NFT 규제에 대한 비교법적 고찰-증권형 및 가상자산형 NFT를 중심으로", 증권법연구, 제23권, 제1호, 2022, 251-286 https://doi.org/10.17785/KJSL.2022.23.1.251
  5. 윤상혁, 양지훈, 한진영, 김형진, "메타버스 성공 요인 분석을 위한 탐색적 연구: 텍스트 마이닝과 인터뷰 혼합방법론", 인터넷전자상거래연구, 제22 권, 제1호, 2022, 41-61.
  6. 천혜정, "연구 방법으로써의 질적 인터뷰: 철학적 의미와 방법적 측면", 한국가족자원경영학회지, 제8권, 제3호, 2004, 113-125.
  7. 최윤진, 이소현, 윤상혁, 김희웅, "Joint Sentiment 토픽모델링 기반 국내 여행 불만족 요인 연구", Korea Business Review, 제24권, 제2호, 2020, 121-141. https://doi.org/10.17287/kbr.2020.24.2.121
  8. Blei, D. M., "Probabilistic topic models", Communications of the ACM, Vol.55, No.4, 2012, 77-84. https://doi.org/10.1145/2133806.2133826
  9. Boyce, C. and P. Neale, Conducting In-Depth Interviews: A Guide for Designing and Conducting in-Depth Interviews for Evaluation Input, Pathfinder international Watertown, MA, 2006.
  10. Chalmers, D., C. Fisch, R. Matthews, W. Quinn, and J. Recker, "Beyond the bubble: Will NFTs and digital proof of ownership empower creative industry entrepreneurs?", Journal of Business Venturing Insights, Vol.17, e00309.
  11. Chang, J., S. Gerrish, C. Wang, J. L. Boyd-Graber, and D. M. Blei, "Reading tea leaves: How humans interpret topic models", In Advances in Neural Information Processing Systems, Vancouver, B.C., Canada, 2009, 288-296.
  12. Chen, Y., "Blockchain Tokens and the Potential Democratization of Entrepreneurship and Innovation", Business Horizons, Vol.61, No.4, 2018, 567-575. https://doi.org/10.1016/j.bushor.2018.03.006
  13. Chohan, R. and J. Paschen, "What Marketers Need to Know about Non-Fungible Tokens (NFTs)", Business Horizons, Vol.ahead-ofprint, No. ahead-of-print, 2021.
  14. Defiprime, "OpenSea Set to Eclipse Traditional Art Sellers with Over $10 Billion in Sales for 2021", 2021. Available at https://defi prime.com/opensea-vs-traditional-art-sellers (Accessed April 4, 2022).
  15. Forbes, "Council Post: NFTs: The Promise And Structural Hurdles To Widespread Adoption", 2022. Available at https://www.forbes.com/sites/forbesfinancecouncil/2022/01/04/nfts-the-promise-and-structural-hurdles-to-widespread-adoption (Accessed April 4, 2022).
  16. Ghosh, D. and R. Guha, "What are we 'tweeting' about obesity? Mapping tweets with topic modeling and geographic information system", Cartography and Geographic Information Science, Vol.40, No.2, 2013, 90-102. https://doi.org/10.1080/15230406.2013.776210
  17. Karim, S., B. M. Lucey, M. A. Naeem, and G. S. Uddin, "Examining the interrelatedness of NFTs, DeFi tokens and cryptocurrencies", Finance Research Letters, Vol.47, 2022, 102696. https://doi.org/10.1016/j.frl.2022.102696
  18. Ko, H., B. Son, Y. Lee, H. Jang, and J. Lee, "The economic value of NFT: Evidence from a portfolio analysis using mean-variance framework", Finance Research Letters, Vol.47, 2022, 102784. https://doi.org/10.1016/j.frl.2022.102784
  19. Laycock, R., "NFT Statistics 2021", 2021. Available at https://www.finder.com/ng/nft-statistics (Accessed June 16, 2022).
  20. Lin, C. and Y. He, "Joint Sentiment/Topic Model for Sentiment Analysis", In Proceedings of the 18th ACM Conference on Information and Knowledge Management, Hong Kong, China, 2009, 375-384.
  21. Maouchi, Y., L. Charfeddine, and G. El Montasser, "Understanding digital bubbles amidst the COVID-19 pandemic: Evidence from DeFi and NFTs", Finance Research Letters, Vol.47, 2021, 102584.
  22. Messari, "Crypto Theses for 2022", 2022. Available at https://www.google.com/search?q=Crypto+Theses+for+2022%2C+Messari(2022)&rlz=1C1CHZL_koKR995KR995&oq=Crypto+Theses+for+2022%2C+Messari(2022)&aqs=chrome..69i57j0i546l3j69i60.358j0j15&sourceid=chrome&ie=UTF-8 (Accessed May 19, 2022).
  23. Mohr, J. W. and P. Bogdanov, "Introduction-topic models: What they are and why they matter", Poetics, Vol.41, No.6, 2013, 545-569. https://doi.org/10.1016/j.poetic.2013.10.001
  24. Nadini, M., L. Alessandretti, F. Di Giacinto, M. Martino, L. M. Aiello, and A. Baronchelli, "Mapping the NFT revolution: Market trends, trade networks, and visual features", Scientific Reports, Vol.11, No.1, 2021, 1-11. https://doi.org/10.1038/s41598-020-79139-8
  25. Newman, D., J. H. Lau, K. Grieser, and T. Baldwin, "Automatic evaluation of topic coherence", In Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Stroudsburg, PA, USA, 2010, 100-108.
  26. Neuman, W. L., Social research methods: Qualitative and quantitative approaches, Pearson, 2014.
  27. Tashakkori, A. and C. Teddlie, "Quality of inferences in mixed methods research: Calling for an integrative framework", Advances in Mixed Methods Research, Vol.53, No.7, 2008, 101-119.
  28. Taylor, J. and K. Sloane, "Art Markets without Art, Art without Objects", Garage J. Stud. Art Museums Cult, Vol.2, 2021, 152-175.
  29. Vasan, K., M. Janosov, and A.-L. Barabasi, "Quantifying NFT-Driven Networks in Crypto Art", Scientific Reports, Vol.12, No.1, 2022, 1-11. https://doi.org/10.1038/s41598-021-99269-x
  30. Venkatesh, V., S. A. Brown, and H. Bala, "Bridging the qualitative-quantitative divide: Guidelines for conducting mixed methods research in information systems", MIS Quarterly, Vol.37, No.1, 2013, 21-54. https://doi.org/10.25300/MISQ/2013/37.1.02
  31. Venkatesh, V., S. A. Brown, and Y. W. Sullivan, "Guidelines for Conducting Mixed-Methods Research: An Extension and Illustration", Journal of the Association for Information Systems, Vol.17, No.7, 2016, 435-495. https://doi.org/10.17705/1jais.00433
  32. Vidal-Tomas, D., "The new crypto niche: NFTs, play-to-earn, and metaverse tokens", Finance Research Letters, Vol.47, 2022, 102742. https://doi.org/10.1016/j.frl.2022.102742
  33. Wang, F.-Y., R. Qin, Y. Yuan, and B. Hu, "Nonfungible tokens: Constructing value systems in parallel societies", IEEE Transactions on Computational Social Systems, Vol.8, No.5, 2021, 1062-1067. https://doi.org/10.1109/TCSS.2021.3109359
  34. Yang, H. C. and Y. Wang, "Social sharing of online videos: Examining american consumers' video sharing attitudes, intent, and behavior", Psychology & Marketing, Vol.32, No.9, 2015, 907-919. https://doi.org/10.1002/mar.20826
  35. Yin, R. K., Case Study Research Design and Methods (4th ed.), Calif Sage Publications, Thousand Oaks, 2009.
  36. Yousaf, I. and L. Yarovaya, "Static and Dynamic Connectedness between NFTs, Defi and Other Assets: Portfolio Implication", Global Finance Journal, Vol.53, 2022, 100-719.
  37. Zhao, W. X., J. Jiang, J. Weng, J. He, E.-P. Lim, H. Yan, and X. Li, "Comparing twitter and traditional media using topic models", In European Conference on Information Retrieval, Springer, 2011, 338-349.