The Model of Influencing Factors on Metaverse Governance in Smart Cities (Qualitative Approach)

Subject Areas : International Journal of Finance, Accounting and Economics Studies

farzad fallahian ¹ ( Tehran Azad University of Science and Research )
Ata Allah Abtahi ² ( Faculty of Economics and Management, Islamic Azad University, Science and Research Branch, Tehran, Iran )
Neda Soleimani ³ ( )

Received: 2024-01-26 Accepted : 2024-03-03 Published : 2024-08-03

Keywords: Metaverse Governance, Smart Governance, Smart City,

Abstract :

Purpose: The current research was conducted with the purpose of "presenting a model of factors affecting the metaverse governance of the smart city using thematic analysis technique. Design/methodology/approach: this research was applied in terms of purpose and in terms of the qualitative-quantitative method based on a thematic analysis approach and 15 qualified professors and experts who were aware of smart city metaverse governance were used in the form of interviews Findings: In this study, the analysis of the collected qualitative data was done through open coding and axial coding. In the open coding stage, the researcher identified 32 concepts and expanded them according to their characteristics and dimensions. Out of the 32 extracted codes, 13 codes were repeated, and 19 codes were confirmed after sorting. Then, from the primary raw data, the preliminary categories related to the phenomenon under investigation by dividing the information into the formation categories of information about the phenomenon under study, asking questions about the data, comparing cases, events, and other states of phenomena for The similarities and differences were discussed and categorized into 4 categories: 1) Smart ICT, 2) Ethics, 3) External and internal cooperation and participation, and 4) Organizational processes implications: In line with the proposal for future research, researchers are advised to measure the causal, contextual, and interventional factors of smart governance using the meta-composite approach and database, or to analyze and evaluate its effect on variables with appropriate semantic affinity.

References:

1. Hataminejad, Hossein; Mansoori Tzait, Abulfazl (1400). Investigating the effects of the smart city on the livability of cities (Mashhad Metropolis Region 9), Magazine: Vision of Future Cities, No. 6, pp. 1-13.
2. Khanpour, Saeed; Nouri, Seyyed Ali; Responsible author: Zabihi, Hossein (1400). Citizen participation components in the smart city; A case study of Tehran Metropolis, Journal: Geografi Sarzemin, No. 72, pp. 1-17

3. Alkhatib, M, El Barachi, M, & Shaalan, K. (2019). An Arabic social media-based framework for incidents and events monitoring in smart cities. Journal of Cleaner Production, 220, 771-785.doi:https://doi.org/10. 1016/j. jclepro. 2019. 02. 063
4. Allam, Z, & Dhunny, Z. A. (2019). On big data, artificial intelligence, and smart cities. Cities, 89, 80-91.doi:https://doi.org/10. 1016/j. cities. 2019. 01. 032
5. Aloqaily, M, Otoum, S, Ridhawi, I. A, & Jararweh, Y. (2019). An intrusion detection system for connected vehicles in smart cities. Ad Hoc Networks, 90, 101842. doi:https://doi.org/10. 1016/j. adhoc. 2019. 02. 001
6. Appio, F. P, Lima, M, & Paroutis, S. (2019). Understanding Smart Cities: Innovation ecosystems, technological advancements, and societal challenges. Technological Forecasting and Social Change, 142, 1-14.doi:https://doi.org/10. 1016/j. techfore. 2018. 12. 018
7. Araujo, V. Mitra, K. Saguna, S. & Åhlund, C. (2019). Performance evaluation of FIWARE: A cloud-based IoT platform for smart cities. Journal of Parallel and Distributed Computing. doi:https://doi.org/10. 1016/j. jpdc. 2018. 12. 010
8. Blanck, M. Ribeiro, J. L. D. & Anzanello, M. J. (2019). A relational exploratory study of business incubation and smart cities - Findings from Europe. Cities, 88, 48-58. doi:https://doi.org/10. 1016/j. cities. 2018. 12. 032
9. Brock, K. den Ouden, E. van der Klauw, K. Podoynitsyna, K. & Langerak, F. (2019). Light the way for smart cities: Lessons from Philips Lighting. Technological Forecasting and Social Change, 142, 194-209. doi:https://doi.org/10. 1016/j. techfore. 2018. 07. 021
10. Camboim, G. F. Zawislak, P. A. & Pufal, N. A. (2019). Driving elements to make cities smarter: Evidence from European projects. Technological Forecasting and Social Change, 142, 154-167. doi:https://doi.org/10. 1016/j. techfore. 2018. 09. 014
11. Camero, A. & Alba, E. (2019). Smart City and Information Technology: A review. Cities, 93, 84-94. doi:https://doi.org/10. 1016/j. cities. 2019. 04. 014
12. Caragliu, A. & Del Bo, C. F. (2019). Smart innovative cities: The impact of Smart City policies on urban innovation. Technological Forecasting and Social Change, 142, 373-383. doi:https://doi.org/10. 1016/j. techfore. 2018. 07. 022
13. Caragliu, A., Del Bo, C., and Nijkamp, P., 2013, Smart Cities in Europe, Routledge, London.
14. Curzon, J. Almehmadi, A, & El-Khatib, K. (2019). A survey of privacy-enhancing technologies for smart cities. Pervasive and Mobile Computing, 55, 76-95. doi:https://doi.org/10. 1016/j. pmcj. 2019. 03. 001
15. Desdemoustier, J. Crutzen, N. Cools, M. & Teller, J. (2019). Smart City appropriation by local actors: An instrument in the making. Cities, 92, 175-186. doi:https://doi.org/10. 1016/j. cities. 2019. 03. 021
16. Elsaeidy, A. Munasinghe, K. S. Sharma, D. & Jamalipour, A. (2019). Intrusion detection in smart cities using Restricted Boltzmann Machines. Journal of Network and Computer Applications, 135, 76-83. doi:https://doi.org/10. 1016/j. jnca. 2019. 02. 026
17. Escolar, S. Villanueva, F. J. Santofimia, M. J. Villa, D. Toro, X. d. & López, J. C. (2019). A Multiple-Attribute Decision Making-based approach for smart city rankings design. Technological Forecasting and Social Change, 142, 42-55. doi:https://doi.org/10. 1016/j. techfore. 2018. 07. 024
18. Haarstad, H. & Wathne, M. W. (2019). Are smart city projects catalyzing urban energy sustainability? Energy Policy, 129, 918-925.doi:https://doi.org/10. 1016/j. enpol. 2019. 03. 001
19. Laufs, J, Borrion, H, & Bradford, B. (2020). Security and the smart city: A systematic review. Sustainable cities and society, PP55
20. Nilssen, M. (2019). To the smart city and beyond? Developing a typology of smart urban innovation. Technological Forecasting and Social Change, 142, 98-104. doi:https://doi.org/10. 1016/j. techfore. 2018. 07. 060
21. Sodhro, A. H. Pirbhulal, S. Luo, Z. & de Albuquerque, V. H. C. (2019). Towards an optimal resource management for IoT based Green and sustainable smart cities. Journal of Cleaner Production, 220, 1167-1179.doi:https://doi.org/10. 1016/j. jclepro. 2019. 01. 188
22. Trencher, G. (2019). Towards the smart city 2. 0: Empirical evidence of using smartness as a tool for tackling social challenges. Technological Forecasting and Social Change, 142, 117-128. doi:https://doi.org/10. 1016/j. techfore. 2018. 07. 033
23. van den Buuse, D. & Kolk, A. (2019). An exploration of smart city approaches by international ICT firms. Technological Forecasting and Social Change, 142, 220-234.doi:https://doi.org/10. 1016/j. techfore. 2018. 07. 029
24. Wang, T. Liang, Y. Jia, W. Arif, M. Liu, A. & Xie, M. (2019). Coupling resource management based on fog computing in smart city systems. Journal of Network and Computer Applications, 135, 11-19. doi:https://doi.org/10. 1016/j. jnca. 2019. 02. 021