1
PhD Student of Financial engineering. Department of Financial. Faculty of Management, Economics and Accounting. Tabriz Branch. Islamic Azad University. Tehran. Iran.
2
Associate Professor. Department of Economics. Faculty of Management, Economics and Accounting. Tabriz Branch. Islamic Azad University. Tehran. Iran
3
Associate Professor. Department of Accounting. Faculty of Management, Economics and Accounting. Tabriz Branch. Islamic Azad University. Tehran. Iran
10.22034/ijfma.2025.78709.2298
Abstract
The present study was conducted with the aim of identifying and ranking the risks of real estate tokenization in Iran. The present study was a fundamental and mixed study in terms of purpose, in the qualitative part, based on the grounded theory method was used, and in the quantitative part, the structural equation modeling method was used. The statistical population in the qualitative section of the panel of experts in real estate renovation in Iran, 10 of whom were selected as the sample based on the rule of theoretical saturation and by purposive method, and the statistical population in the quantitative section was academic experts, officials and executive actors, 200 of whom were selected as the sample based on Cochran's formula and available method. The data collection tool in the qualitative part was semi-structured interviews and in the quantitative part was a researcher-made questionnaire whose validity and reliability were confirmed. To analyze the data, MAXQDA 13.28 and Smart PLS 3.2 software were used. The indices of goodness of fit and GOF=0.735 showed that the developed model had a good fit with the experimental data. The results also showed that LLR (β=0.749), ECR (β=0.688), SOR (β=0.651), TCR (β=0.617), FER (β=0.574), IOR (β=0.523), CRR (β=0.458) and IR (β=0.369) are the most important risks of tokenization of real estate in Iran (P<0.01).
Arzyabi, Vida. (2023). Modeling the factors influencing the valuation of non-fungible tokens (NFTs) from the perspective of investors [Master’s thesis, University of Tehran, Kish International Campus].
Bate, G.W. (2025). Blockchain and the Future of Tokenization. Research-Technology Management, 68(3): 59–62. [Link]
Bergkamp, M.C. (2024). Tokenization of Real Estate Assets: Ownership Dispersion, Diversification, Liquidity and Correlation with Economic Fundamentals and Crypto Market Sentiment. Business Economics. [Link]
Creswell, J.W. (2005). Qualitative inquiry and research design: Choosing among five approaches. Sage publications.
Charmaz, K. (2006). Grounding grounded theory: a practical guide through qualitative analysis. London: Sage Publications Ltd.1-148.
Corbin, J., & Strauss, A. (2008). Basics of qualitative research: Techniques and procedures for developing grounded theory (3rd ed.). Sage Publications, Inc.
Danaeefard, Hossein, Alvani, Seyed Mehdi, & Azar, Adel. (2019). Qualitative research methodology in management: A comprehensive approach. Tehran: Eshraghi (Safar).
Fakhimi Akmal, Matin. (2023). A study of asset token issuance on the blockchain as an alternative to asset securitization with emphasis on the ninth clause of the Resistance Economy to strengthen the country's financial system [Master’s thesis, Imam Sadegh University].
Fazli, Mohammad Javad. (2022). Factors influencing the adoption of blockchain-based real estate tokens by banks [Master’s thesis, Allameh Tabataba’i University].
Fernández, Walter D. (2004), Using the Glaserian Approach in Grounded Studies of Emerging Business Practices. Electronic Journal of Business Research Methods, 2(2).
Gholam Abolfazl, Farzaneh. (2023). Real estate tokenization: Based on the operational experience of Lotus Pirouzi token at Parsian Bank (1st ed.). Tehran: Lotus Pirouzi Innovation Cooperative Company.
Glaser, Barney G. (1978), Theoretical Sensitivity: Advances in the Methodology of Grounded Theory, Mill Valley, California: The Sociology Press.
Goulding, H. (2000). Grounded Theory Methodology and Consumer Behavior, Procedures, Practice and Pitfalls. Advances in Consumer Research. 27, 261-267.
Itai, Agur., German Villegas, Bauer., Tommaso, Mancini-Griffoli., Maria, Soledad., Martinez, Peria., and Brandon, Tan. (2025). Tokenization and Financial Market Inefficiencies. Fintech Notes. 001. [Link]
Izadin, Ahmad Al Izham. and Rosylin, Yusof. (2024). Democratizing Real Estate Investment: A Systematic Review of Tokenization in Real Estate. [Link]
Joshi, Shashank. & Choudhury, Arhan. (2022). Tokenization of Real Estate Assets Using Blockchain. International Journal of Intelligent Information Technologies. 18(3): 1-12. [Link]
Khanifar, Hossein, & Moslemi, Nahid. (2023). Principles and foundations of qualitative research methods (Vol. 1, 6th ed.). Tehran: Negah Danesh.
Khodapanah Ajirloo, Mostafa. (2024). Examining the consequences of real-world asset (RWA) tokenization for financial reporting and the need to develop new accounting standards. 9th International Conference on Management, Accounting, Economics, and Social Sciences, Hamedan, Iran. [Link]
Kline RB. Principles and practice of structural equation modeling, 4th ed. New York: Guilford press. 2015:534. [Link]
Kreppmeier, Julia., Laschinger, Ralf., Steininger, Bertram I., Dorfleitner, G. (2023). Real estate security token offerings and the secondary market: Driven by crypto hype or fundamentals?. Journal of Banking and Finance. 154: 106940. [Link]
Liu, Ang. & Chen, Cheng. (2025). From real estate financialization to decentralization: A comparative review of REITs and blockchain-based tokenization. Geoforum. 159: 104193. [Link]
Mohsenin, Shahriar. (2017). Structural equations based on partial least squares (PLS) using Smart PLS software: Educational and applied. Tehran: Mehraban Nashr.
Nekouhat, Benyamin. (2023). Blockchain in real estate: Recent developments and practical applications. 21st National Conference on Computer Science and Information Technology Engineering, Babol, Iran. [Link]
Pourghasemi, Amirhossein, Rahimi, Ali, & Shakeri, Eghbal. (2023). Exploring the advantages and challenges of infrastructure financing through tokenization. 20th National Conference on New Events in Management, Economics, and Accounting, Babol, Iran. [Link]
Strauss, A. & Corbin, J. (2015). Basics of Qualitative Research Techniques and Procedures for Developing Grounded Theory (4th ed.). Thousand Oaks: CA: Sage.
Swinkels, L. (2023). Empirical evidence on the ownership and liquidity of real estate tokens. Financ Innov. 9(45). [Link]
Yavari, Kazem, Timoora, Fatemeh, & Najjarzadeh, Reza. (2023). Investigating factors influencing the success of initial coin offerings using random forest algorithm. Modern Economy and Trade, 18(60), 169–199. [Link]
Amirkhani,S. , Ale Emran,R. and Baradaran Hassan Zadeh,R. (2026). Tokenization of Real Estate and Identifying it's Risks in Iran. International Journal of Finance & Managerial Accounting, 13(49), 101-118. doi: 10.22034/ijfma.2025.78709.2298
MLA
Amirkhani,S. , , Ale Emran,R. , and Baradaran Hassan Zadeh,R. . "Tokenization of Real Estate and Identifying it's Risks in Iran", International Journal of Finance & Managerial Accounting, 13, 49, 2026, 101-118. doi: 10.22034/ijfma.2025.78709.2298
HARVARD
Amirkhani S., Ale Emran R., Baradaran Hassan Zadeh R. (2026). 'Tokenization of Real Estate and Identifying it's Risks in Iran', International Journal of Finance & Managerial Accounting, 13(49), pp. 101-118. doi: 10.22034/ijfma.2025.78709.2298
CHICAGO
S. Amirkhani, R. Ale Emran and R. Baradaran Hassan Zadeh, "Tokenization of Real Estate and Identifying it's Risks in Iran," International Journal of Finance & Managerial Accounting, 13 49 (2026): 101-118, doi: 10.22034/ijfma.2025.78709.2298
VANCOUVER
Amirkhani S., Ale Emran R., Baradaran Hassan Zadeh R. Tokenization of Real Estate and Identifying it's Risks in Iran. IJFMA, 2026; 13(49): 101-118. doi: 10.22034/ijfma.2025.78709.2298