Investigating Role of Blockchain in Making your Greetings Valuable
DOI:
https://doi.org/10.36676/urr.2023-v10i4-009Keywords:
Blockchain, Opensea, Young parrot, NFTAbstract
Current study is mostly focused on the exploration of the role of blockchain technology in enhancing the value of greetings. To accomplish this goal, renowned blockchain-based greetings NFTs from Opensea and Young Parrot have been taken into account. The welcome non-fungible tokens (NFTs) are built upon the Matic and Core blockchain networks. In order to get insight into the key determinants that significantly impact the demand for blockchain-based NFTs used for greetings, a comprehensive survey was undertaken including all facets of this burgeoning phenomenon. Extensive research has been undertaken to enhance comprehension of the determinants that propel the demand for NFTs based on blockchain technology within the domain of greetings. The factors under consideration include the pricing, overall quantity, use case, and popularity of NFTs. A survey was conducted on Twitter, using a sample size of 525 individuals. Based on the findings of the conducted study, it can be deduced that the primary determinant of the value attributed to greetings is their level of popularity. Furthermore, it has been observed that the Love Emogie have a restricted availability. The limited availability of just 43 Love Emojie has contributed to the heightened demand for NFTs owing to their inherent scarcity. However, it is also noted that pricing and use case have a substantial influence.
References
B. Guidi and A. Michienzi, “From NFT 1.0 to NFT 2.0: A Review of the Evolution of Non-Fungible Tokens,” Futur. Internet, vol. 15, no. 6, pp. 1–23, 2023, doi: 10.3390/fi15060189.
A. B. Mahmoud, “The Metaverse and Web 3.0: Revolutionising Consumption and Communication for the Future,” Handb. Res. Consum. Behav. Anal. Metaverse Adopt. a Virtual World, pp. 322–345, 2023, [Online]. Available: https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-6684-7029-9.ch015.
F. Limano, “New Digital Culture Metaverse Preparation Digital Society for Virtual Ecosystem,” E3S Web Conf., vol. 388, 2023, doi: 10.1051/e3sconf/202338804057.
J. Thomason, “Metaverse, token economies, and non-communicable diseases,” Glob. Heal. J., vol. 6, no. 3, pp. 164–167, 2022, doi: 10.1016/j.glohj.2022.07.001.
K. M. Abuzagia and S. A. A. Hadoud, “Overview : Technology Roadmap Of The Future Trend Of Metaverse Based On Iot,” Int. Sci. Technol. J., vol. 28, no. 27, pp. 1–15, 2022.
D. Zimmermann, A. Wehler, and K. Kaspar, “Self-representation through avatars in digital environments,” Curr. Psychol., vol. 42, no. 25, pp. 21775–21789, 2022, doi: 10.1007/s12144-022-03232-6.
D. B. Rawat and H. El Alami, “Metaverse: Requirements, Architecture, Standards, Status, Challenges, and Perspectives,” IEEE Internet Things Mag., vol. 6, no. 1, pp. 14–18, 2023, doi: 10.1109/iotm.001.2200258.
M. A. I. Mozumder, M. M. Sheeraz, A. Athar, S. Aich, and H. C. Kim, “Overview: Technology Roadmap of the Future Trend of Metaverse based on IoT, Blockchain, AI Technique, and Medical Domain Metaverse Activity,” Int. Conf. Adv. Commun. Technol. ICACT, vol. 2022-February, no. February, pp. 256–261, 2022, doi: 10.23919/ICACT53585.2022.9728808.
D. Gursoy, S. Malodia, and A. Dhir, “The metaverse in the hospitality and tourism industry: An overview of current trends and future research directions,” J. Hosp. Mark. Manag., vol. 31, no. 5, pp. 527–534, 2022, doi: 10.1080/19368623.2022.2072504.
P. Bhattacharya et al., “Towards Future Internet: The Metaverse Perspective for Diverse Industrial Applications,” Mathematics, vol. 11, no. 4, pp. 1–41, 2023, doi: 10.3390/math11040941.
M. A. I. Mozumder et al., “Metaverse for Digital Anti-Aging Healthcare: An Overview of Potential Use Cases Based on Artificial Intelligence, Blockchain, IoT Technologies, Its Challenges, and Future Directions,” Appl. Sci., vol. 13, no. 8, 2023, doi: 10.3390/app13085127.
S. Ali et al., “Metaverse in Healthcare Integrated with Explainable AI and Blockchain: Enabling Immersiveness, Ensuring Trust, and Providing Patient Data Security,” Sensors, vol. 23, no. 2, pp. 1–17, 2023, doi: 10.3390/s23020565.
L. Bojic, “Metaverse through the prism of power and addiction: what will happen when the virtual world becomes more attractive than reality?,” Eur. J. Futur. Res., vol. 10, no. 1, 2022, doi: 10.1186/s40309-022-00208-4.
E. A. Firmansyah and U. H. Umar, “Metaverse in business research: a systematic literature review,” Cogent Bus. Manag., vol. 10, no. 2, 2023, doi: 10.1080/23311975.2023.2222499.
E. Elem, “Metaverse Framework : A Case Study on E-Learning,” pp. 1–13, 2022.
Y. K. Dwivedi et al., “Metaverse marketing: How the metaverse will shape the future of consumer research and practice,” Psychol. Mark., vol. 40, no. 4, pp. 750–776, 2023, doi: 10.1002/mar.21767.
S. Wu, L. Xu, Z. Dai, and Y. Pan, “Factors Affecting Avatar Customization Behavior in Virtual Environments,” Electron., vol. 12, no. 10, pp. 1–21, 2023, doi: 10.3390/electronics12102286.
V. Bucur and L. Miclea, “Entering the Metaverse from the JVM : The State of the Art , Challenges , and Research Areas of JVM-Based Web 3 . 0 Tools and Libraries,” 2023.
V. Arya, R. Sambyal, A. Sharma, and Y. K. Dwivedi, “Brands are calling your AVATAR in Metaverse–A study to explore XR-based gamification marketing activities & consumer-based brand equity in virtual world,” J. Consum. Behav., no. December 2022, pp. 1–30, 2023, doi: 10.1002/cb.2214.
B. C. Cheong, “Avatars in the metaverse: potential legal issues and remedies,” Int. Cybersecurity Law Rev., vol. 3, no. 2, pp. 467–494, 2022, doi: 10.1365/s43439-022-00056-9.
M. Trunfio and S. Rossi, “Advances in Metaverse Investigation: Streams of Research and Future Agenda,” Virtual Worlds, vol. 1, no. 2, pp. 103–129, 2022, doi: 10.3390/virtualworlds1020007.
M. Dudeja, “Adaptation to Transformation of Human Resource Practices and Technology: Web 3.0 Metaverse,” J. Surv. Fish. Sci., vol. 10, pp. 1187–1196, 2023, doi: 10.17762/sfs.v10i4s.1169.
T. C. Wu and C. T. B. Ho, “A scoping review of metaverse in emergency medicine,” Australas. Emerg. Care, vol. 26, no. 1, pp. 75–83, 2023, doi: 10.1016/j.auec.2022.08.002.
Y. K. Dwivedi et al., “Metaverse beyond the hype: Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy,” Int. J. Inf. Manage., vol. 66, 2022, doi: 10.1016/j.ijinfomgt.2022.102542.
S. Adnan Ali and R. Khan, “From Science Fiction to Reality: An Insight into the Metaverse and its Evolving Ecosystem,” no. February, 2023, doi: 10.20944/preprints202302.0224.v1.
V. Talukdar, D. Dhabliya, B. Kumar, S. B. Talukdar, S. Ahamad, and A. Gupta, “Suspicious Activity Detection and Classification in IoT Environment Using Machine Learning Approach,” 2022 Seventh International Conference on Parallel, Distributed and Grid Computing (PDGC). IEEE, Nov. 25, 2022. doi: 10.1109/pdgc56933.2022.10053312.
P. R. Kshirsagar, D. H. Reddy, M. Dhingra, D. Dhabliya, and A. Gupta, “A Scalable Platform to Collect, Store, Visualize and Analyze Big Data in Real- Time,” 2023 3rd International Conference on Innovative Practices in Technology and Management (ICIPTM). IEEE, Feb. 22, 2023. doi: 10.1109/iciptm57143.2023.10118183. Available: http://dx.doi.org/10.1109/ICIPTM57143.2023.10118183.
M. Dhingra, D. Dhabliya, M. K. Dubey, A. Gupta, and D. H. Reddy, “A Review on Comparison of Machine Learning Algorithms for Text Classification,” 2022 5th International Conference on Contemporary Computing and Informatics (IC3I). IEEE, Dec. 14, 2022. doi: 10.1109/ic3i56241.2022.10072502. Available: http://dx.doi.org/10.1109/IC3I56241.2022.10072502
D. Mandal, K. A. Shukla, A. Ghosh, A. Gupta, and D. Dhabliya, “Molecular Dynamics Simulation for Serial and Parallel Computation Using Leaf Frog Algorithm,” 2022 Seventh International Conference on Parallel, Distributed and Grid Computing (PDGC). IEEE, Nov. 25, 2022. doi: 10.1109/pdgc56933.2022.10053161. Available: http://dx.doi.org/10.1109/PDGC56933.2022.10053161
P. R. Kshirsagar, D. H. Reddy, M. Dhingra, D. Dhabliya, and A. Gupta, “A Review on Application of Deep Learning in Natural Language Processing,” 2022 5th International Conference on Contemporary Computing and Informatics (IC3I). IEEE, Dec. 14, 2022. doi: 10.1109/ic3i56241.2022.10073309. Available: http://dx.doi.org/10.1109/IC3I56241.2022.10073309
P. R. Kshirsagar, D. H. Reddy, M. Dhingra, D. Dhabliya, and A. Gupta, “Detection of Liver Disease Using Machine Learning Approach,” 2022 5th International Conference on Contemporary Computing and Informatics (IC3I). IEEE, Dec. 14, 2022. doi: 10.1109/ic3i56241.2022.10073425. Available: http://dx.doi.org/10.1109/IC3I56241.2022.10073425
V. V. Chellam, S. Praveenkumar, S. B. Talukdar, V. Talukdar, S. K. Jain, and A. Gupta, “Development of a Blockchain-based Platform to Simplify the Sharing of Patient Data,” 2023 3rd International Conference on Innovative Practices in Technology and Management (ICIPTM). IEEE, Feb. 22, 2023. doi: 10.1109/iciptm57143.2023.10118194.
P. Lalitha Kumari et al., “Methodology for Classifying Objects in High-Resolution Optical Images Using Deep Learning Techniques,” Lecture Notes in Electrical Engineering. Springer Nature Singapore, pp. 619–629, 2023. doi: 10.1007/978-981-19-8865-3_55.
N. Sindhwani et al., “Comparative Analysis of Optimization Algorithms for Antenna Selection in MIMO Systems,” Lecture Notes in Electrical Engineering. Springer Nature Singapore, pp. 607–617, 2023. doi: 10.1007/978-981-19-8865-3_54.
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