Research Article
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Year 2024, Volume: 11 Issue: 2, 120 - 135, 31.12.2024
https://doi.org/10.17261/Pressacademia.2024.1959

Abstract

References

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  • Ajzen, I. (2011). The theory of planned behavior: Reactions and reflections. Psychology & Health, 26(9), 1113-1127.
  • Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211.
  • Ajzen, I., & Fishbein, M. (1977). Attitude-behavior relations: A theoretical analysis and review of empirical research. Psychological Bulletin, 84(5), 888–918.
  • Al-amri, R., Zakaria, N. H., Habbal, A., & Hassan, S. (2019). Cryptocurrency adoption: current stage, opportunities, and open challenges. International Journal of Advanced Computer Research, 9, 293-307.
  • Al-Bashayreh, M. & Almajali, D., Altamimi, A., Masa'deh, Ra'Ed., & Al-Okaily, M. (2022). An Empirical Investigation of Reasons Influencing Student Acceptance and Rejection of Mobile Learning Apps Usage. Sustainability Journal, 14 (1), 1-14.
  • Al-Fagih, Khaled. (2016). An empirical analysis of factors predicting the behavioral intention to adopt Internet shopping technology among non-shoppers in a developing country context: Does gender matter? Journal of Retailing and Consumer Services, 30(2), 140-164.
  • Almajali, D., Omar, F., Alsokkar, A., Alsherideh, A., Masa’Deh, R., & Dahalin, Z. (2022). Enterprise resource planning success in Jordan from the perspective of IT-Business strategic alignment. Cogent Social Sciences, 8(1), 206-209.
  • Almuraqab, N. A. S. (2020). Predicting determinants of the intention to use digital currency in the UAE: An empirical study. The Electronic Journal of Information System in Developing Countries, 86(3), 1-12.
  • Aloosh, A. & Ouzan, S. (2019). The Psychology of Cryptocurrency Prices. Finance Research Letters, 33, 101192. https://doi.org/10.1016/j.frl.2019.05.010
  • Al-Qaysi, N., Mohamad, N. N., & Al-Emran, M. (2020). Employing the technology acceptance model in social media: A systematic review. Education and Information Technologies, 25. https://doi.org/10.1007/s10639-020-10197-1
  • Angorani, S. (2024). Global dynamics of cryptocurrency adoption: An empirical exploration of fintech's influence on the evolution of digital currencies. Journal of Indonesian Economy and Business, 2, 47-64.
  • Arias-Oliva, M., Borondo, J., & Matias C. G. (2019). Variables influencing cryptocurrency use: a technology acceptance model in Spain. Frontiers in Psychology, 10, 475-497.
  • Arpaci, I., & Bahari, M. (2023). A complementary SEM and deep ANN approach to predict the adoption of cryptocurrencies from the perspective of cyber security. Computers in Human Behavior, 143(8), 147-169.
  • Bhattacherjee, A. (2012). Social science research: Principles, methods, and practices. Global Text Project, Textbooks Collection, Vol. 3. https://doi.org/digitalcommons.usf.edu/oa_textbooks/3
  • Boxer, M., & Thompson, N. (2020). Herd behavior in cryptocurrency markets. Proceedings of the 31st Australasian Conference on Information Systems, Wellington, New Zealand. https://espace.curtin.edu.au/handle/20.500.11937/81762
  • Byrne, B. M. (2010). Structural Equation Modeling with Amos: Basic Concepts, Applications, and Programming (2nd ed.). New York: Taylor and Francis Group.
  • Chainalysis, (2023). The 2023 global crypto adoption index: Central & Southern Asia are leading the way in grassroots crypto adoption. https://www.chainalysis.com/blog/2023-global-crypto-adoption-index
  • Chen, L. & Aklikokou, A. (2019). Determinants of E-government adoption: Testing the mediating effects of perceived usefulness and perceived ease of use. International Journal of Public Administration, 43, 1-16.
  • Communications Authority of Kenya (2023). Annual Report: Financial Year 2022-2023. https://www.ca.go.ke/sites/default/files/202401/Annual%20Report%20Financial%20Year%202022-2023.
  • Davis, D. & Davis, D. F. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13. https://doi.org/319-. 10.2307/249008
  • Doblas, M. (2019). Awareness and attitude towards cryptocurrencies in relation to adoption among college students in a private tertiary institution in cagayan de oro city, philippines. International Journal of Advanced Research and Publication, 3(4), 15-29.
  • El-Chaarani H., Abiad Z., El-Nemar S. & Sakka G. (2023). Factors affecting the adoption of cryptocurrencies for financial transactions. EuroMed Journal of Business, 19(1), 20-45.
  • Farah, M., Hasni, M., & Abbas, A. (2018). Mobile-banking adoption: empirical evidence from the banking sector in Pakistan. International Journal of Bank Marketing. 36(1).
  • Fettahoğlu, S., & Sayan, Ö. (2021). Attitudes of individuals about using cryptocurrencies: evidence from Turkey. İstanbul Ticaret Üniversitesi Sosyal Bilimler Dergisi, 20(42), 1122-1146.
  • Fornell, C., Larcker, D., Perreault, W., & Anderson, C. (1988). Structural Equation Modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411–423.
  • Fu, J. R., Farn, C. K., & Chao, W. P. (2006). Acceptance of electronic tax filing: A study of taxpayer intentions. Information and Management, 43(1), 109–126.
  • Gazali, M. H. (2019). Bitcoin investment behavior: A pilot study. International Journal on Perceptive and Cognitive Computing, 5, 81-86.
  • Goodhue, D.L. & Thompson, R.L. (1995). Task-Technology Fit and Individual Performance. MIS Quarterly, 19 (2), 213-235.
  • Hair, J., Hult, G., Tomas, M. Ringle, C., & Sarstedt, M. (2014). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Sage Publishers. http://www.sagepub.com/books/Book237345 Book's Homepage: http://www.pls-sem.com
  • Hair, J., Black, W., Babin, B., & Anderson, R. (2010). Multivariate Data Analysis: A Global Perspective. Publisher: Pearson ISBN: 0135153093
  • Holmes-Smith, P., Coote, L., & Cunningham, E. (2006). Structural Equation Modelling: From the Fundamentals to Advanced Topics. Streams Statsline, Melbourne.
  • Hussain, M. Arif, K., & Mubeen, M. (2023). Factors affecting the adoption of cryptocurrency. Global Journal for Management and Administrative Sciences, 4, 91-111.
  • Hu, P. J., Chau, P. Y. K., Sheng, O. R. L., & Tam, K. Y. (1999). Examining the technology acceptance model using physician acceptance of telemedicine technology. Journal of Management Information Systems, 16(2), 91–112.
  • Idrees, M., Khan, S., Furquan, M., & Zafar, M. (2024). the awareness, acceptance and adoption of cryptocurrency with the moderating effect of trust: A perspective of TAM. Migration Letters. 21. 600-617.
  • Illia, A., Lawson-Body, A., Lee, S, & Akalin, G. (2023). Determinants of cryptocurrency exchange adoption: A conceptual model. International Journal of Technology and Human Interaction, 19, 1-14.
  • Jariyapan P., Mattayaphutron S., Gillani SN., & Shafique O. (2022). factors influencing the behavioral intention to use cryptocurrency in emerging economies during the covid-19 pandemic: Based on technology acceptance model 3, perceived risk, and financial literacy. Front Psychology. 12:814087. https://doi.org/10.3389/fpsyg.2021.814087
  • Johns, G. (2006). The essential impact of context on organizational behavior. Academy of Management Review, 31(2), 386-408.
  • Johnston, H., Wells, R., Shanks, E., Boey, T., & Parsons, B. (2024). Student perspectives on the use of generative artificial intelligence technologies in higher education. International Journal for Educational Integrity, 20(1), 1-21.
  • Kim, M. (2021). A Psychological approach to bitcoin usage behavior in the era of COVID-19: Focusing on the role of attitude towards money. Journal of retailing and consumer services, 62(1).
  • Khan M. Z., Ali Y., Sultan H. B., Hasan M., & Baloch, S. (2020). Future of currency: a comparison between traditional, digital fiat and cryptocurrency exchange mediums. International Journal of Blockchains Cryptocurrencies, 1(1), 206–224.
  • Khan, I. U., Hameed, Z., & Khan, S. (2017). Understanding online banking adoption in a developing country: UTAUT2 with cultural moderators. Journal of Global Information Management, 25(1), 43-65.
  • Kher R., Terjesen S., & Liu C. (2021). Blockchain, Bitcoin, and ICOs: a review and research agenda. Small Business Economics, 56(2), 1699-1720.
  • Kline, R. B. (2013). Beyond significance testing: Statistics reform in the behavioral sciences (2nd ed.). Washington DC: American Psychological Association. https://doi.org/10.1037/14136-000
  • Lone A. H. & Naaz R. (2021). Applicability of Blockchain smart contracts in securing Internet and IoT: a systematic literature review. Computer Science Review, 39(1), 9-20.
  • Mailizar M. & Johar, R. (2021). Examining Students’ Intention to Use Augmented Reality in a Project-Based Geometry Learning Environment. International Journal of Instruction, 14(2), 773-790.
  • Maruf, T. I., Manaf, N., Haque, A., & Maulan, S. (2021). Factors affecting attitudes towards using ride-sharing apps. International journal of business, economics, and law, 25(2), 60-70.
  • Mattsson C., Criscione T., & Ruddick W. (2022). Sarafu community inclusion currency 2020–2021. Scientific Data, 9(1), 1-39.
  • Mazambani, L., & Mutambara, El. (2019). Predicting fintech innovation adoption in South Africa: the case of cryptocurrency. South African Journal of Economic and Management Sciences, 11(1), 30-50
  • Mendoza-Tello, J., Mora, H., Pujol, F., & Lytras, M. (2019). Disruptive innovation of cryptocurrencies in consumer acceptance and trust. Information Systems and e-Business Management. 17(1), 195-222.
  • Merhi, M., Hone, K., & Tarhini, Ali. (2019). A cross-cultural study of the intention to use mobile banking between Lebanese and British consumers: Extending UTAUT2 with security, privacy and trust. Technology in Society, 9, Article ID 101159. http://doi.org/10.1016/j.techsoc.2019.101151
  • Mweetwa, L., & Mwange, A. (2023). Major models and theories of cryptocurrency technology adoption: A theoretical review. International Journal of Multidisciplinary Research and Growth Evaluation, 4(1), 661-673.
  • Muttaqin, H., Deswantiyar, R., & Kartono, R. (2023). Analysis of consumer motivation for using cryptocurrency in Indonesia. Budapest international research and critics institute, 6 (1), 424-436.
  • Nadeem M. A., Liu Z., Pitafi A. H., Younis A., & Xu Y. (2021). Investigating the Adoption Factors of Cryptocurrencies—A Case of Bitcoin: Empirical Evidence from China. SAGE Open, 11(1). https://doi.org/10.1177/2158244021998704
  • Ndemo, B. (2022). Role of Cryptocurrency in Sub-Saharan Africa. Brookings Foresight Africa, 2022, 5(1). https://www.brookings.edu/articles/the-role-of-cryptocurrencies-in-sub-saharan-africa/
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DETERMINANTS OF CRYPTOCURRENCY ADOPTION: EVIDENCE FROM AN EMERGING ECONOMY

Year 2024, Volume: 11 Issue: 2, 120 - 135, 31.12.2024
https://doi.org/10.17261/Pressacademia.2024.1959

Abstract

Purpose- Cryptocurrency adoption has tremendously improved in Sub-Saharan Africa's emerging economies. Despite this trend, less emphasis has been placed on determinants of cryptocurrency adoption in such economies. This study extended the Theory of Reasoned Action (TRA), Theory of Planned Behavior (TPB), and Technology Acceptance Model (TAM), to examine aspects that determine cryptocurrency adoption in Kenya. The study findings may assist policymakers in developing a sturdy regulatory framework for adopting digital assets and monitoring Virtual Asset Service Providers (VASPs).
Methodology- Data was collected through questionnaires from 400 students, graduates, and investors who had information about cryptocurrency. The study employed a structural equation model to estimate our latent constructs.
Findings- Results confirmed the hypotheses that perceived utility, perceived ease of usage, perceived risk, attitude, and subjective norms are significant constructs in determining behavioral intent to use cryptocurrency in Kenya. Further, the mediatory role of attitude on cryptocurrency adoption was also confirmed.
Conclusion- Policies that promote the introduction of an e-cash platform, regulation of digital system currencies, social mass awareness, and cryptocurrency companies with good reputations should be introduced by the government to ensure the development of the cryptocurrency market in Kenya.

References

  • Abbasi, G., Jagaveeran, M., Goh, Y. N., & Tariq, B. (2021). The impact of the type of content use on smartphone addiction and academic performance: Physical activity as moderator. Technology in Society, 64(2), 101-129.
  • Ajzen, I. (2011). The theory of planned behavior: Reactions and reflections. Psychology & Health, 26(9), 1113-1127.
  • Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211.
  • Ajzen, I., & Fishbein, M. (1977). Attitude-behavior relations: A theoretical analysis and review of empirical research. Psychological Bulletin, 84(5), 888–918.
  • Al-amri, R., Zakaria, N. H., Habbal, A., & Hassan, S. (2019). Cryptocurrency adoption: current stage, opportunities, and open challenges. International Journal of Advanced Computer Research, 9, 293-307.
  • Al-Bashayreh, M. & Almajali, D., Altamimi, A., Masa'deh, Ra'Ed., & Al-Okaily, M. (2022). An Empirical Investigation of Reasons Influencing Student Acceptance and Rejection of Mobile Learning Apps Usage. Sustainability Journal, 14 (1), 1-14.
  • Al-Fagih, Khaled. (2016). An empirical analysis of factors predicting the behavioral intention to adopt Internet shopping technology among non-shoppers in a developing country context: Does gender matter? Journal of Retailing and Consumer Services, 30(2), 140-164.
  • Almajali, D., Omar, F., Alsokkar, A., Alsherideh, A., Masa’Deh, R., & Dahalin, Z. (2022). Enterprise resource planning success in Jordan from the perspective of IT-Business strategic alignment. Cogent Social Sciences, 8(1), 206-209.
  • Almuraqab, N. A. S. (2020). Predicting determinants of the intention to use digital currency in the UAE: An empirical study. The Electronic Journal of Information System in Developing Countries, 86(3), 1-12.
  • Aloosh, A. & Ouzan, S. (2019). The Psychology of Cryptocurrency Prices. Finance Research Letters, 33, 101192. https://doi.org/10.1016/j.frl.2019.05.010
  • Al-Qaysi, N., Mohamad, N. N., & Al-Emran, M. (2020). Employing the technology acceptance model in social media: A systematic review. Education and Information Technologies, 25. https://doi.org/10.1007/s10639-020-10197-1
  • Angorani, S. (2024). Global dynamics of cryptocurrency adoption: An empirical exploration of fintech's influence on the evolution of digital currencies. Journal of Indonesian Economy and Business, 2, 47-64.
  • Arias-Oliva, M., Borondo, J., & Matias C. G. (2019). Variables influencing cryptocurrency use: a technology acceptance model in Spain. Frontiers in Psychology, 10, 475-497.
  • Arpaci, I., & Bahari, M. (2023). A complementary SEM and deep ANN approach to predict the adoption of cryptocurrencies from the perspective of cyber security. Computers in Human Behavior, 143(8), 147-169.
  • Bhattacherjee, A. (2012). Social science research: Principles, methods, and practices. Global Text Project, Textbooks Collection, Vol. 3. https://doi.org/digitalcommons.usf.edu/oa_textbooks/3
  • Boxer, M., & Thompson, N. (2020). Herd behavior in cryptocurrency markets. Proceedings of the 31st Australasian Conference on Information Systems, Wellington, New Zealand. https://espace.curtin.edu.au/handle/20.500.11937/81762
  • Byrne, B. M. (2010). Structural Equation Modeling with Amos: Basic Concepts, Applications, and Programming (2nd ed.). New York: Taylor and Francis Group.
  • Chainalysis, (2023). The 2023 global crypto adoption index: Central & Southern Asia are leading the way in grassroots crypto adoption. https://www.chainalysis.com/blog/2023-global-crypto-adoption-index
  • Chen, L. & Aklikokou, A. (2019). Determinants of E-government adoption: Testing the mediating effects of perceived usefulness and perceived ease of use. International Journal of Public Administration, 43, 1-16.
  • Communications Authority of Kenya (2023). Annual Report: Financial Year 2022-2023. https://www.ca.go.ke/sites/default/files/202401/Annual%20Report%20Financial%20Year%202022-2023.
  • Davis, D. & Davis, D. F. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13. https://doi.org/319-. 10.2307/249008
  • Doblas, M. (2019). Awareness and attitude towards cryptocurrencies in relation to adoption among college students in a private tertiary institution in cagayan de oro city, philippines. International Journal of Advanced Research and Publication, 3(4), 15-29.
  • El-Chaarani H., Abiad Z., El-Nemar S. & Sakka G. (2023). Factors affecting the adoption of cryptocurrencies for financial transactions. EuroMed Journal of Business, 19(1), 20-45.
  • Farah, M., Hasni, M., & Abbas, A. (2018). Mobile-banking adoption: empirical evidence from the banking sector in Pakistan. International Journal of Bank Marketing. 36(1).
  • Fettahoğlu, S., & Sayan, Ö. (2021). Attitudes of individuals about using cryptocurrencies: evidence from Turkey. İstanbul Ticaret Üniversitesi Sosyal Bilimler Dergisi, 20(42), 1122-1146.
  • Fornell, C., Larcker, D., Perreault, W., & Anderson, C. (1988). Structural Equation Modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411–423.
  • Fu, J. R., Farn, C. K., & Chao, W. P. (2006). Acceptance of electronic tax filing: A study of taxpayer intentions. Information and Management, 43(1), 109–126.
  • Gazali, M. H. (2019). Bitcoin investment behavior: A pilot study. International Journal on Perceptive and Cognitive Computing, 5, 81-86.
  • Goodhue, D.L. & Thompson, R.L. (1995). Task-Technology Fit and Individual Performance. MIS Quarterly, 19 (2), 213-235.
  • Hair, J., Hult, G., Tomas, M. Ringle, C., & Sarstedt, M. (2014). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Sage Publishers. http://www.sagepub.com/books/Book237345 Book's Homepage: http://www.pls-sem.com
  • Hair, J., Black, W., Babin, B., & Anderson, R. (2010). Multivariate Data Analysis: A Global Perspective. Publisher: Pearson ISBN: 0135153093
  • Holmes-Smith, P., Coote, L., & Cunningham, E. (2006). Structural Equation Modelling: From the Fundamentals to Advanced Topics. Streams Statsline, Melbourne.
  • Hussain, M. Arif, K., & Mubeen, M. (2023). Factors affecting the adoption of cryptocurrency. Global Journal for Management and Administrative Sciences, 4, 91-111.
  • Hu, P. J., Chau, P. Y. K., Sheng, O. R. L., & Tam, K. Y. (1999). Examining the technology acceptance model using physician acceptance of telemedicine technology. Journal of Management Information Systems, 16(2), 91–112.
  • Idrees, M., Khan, S., Furquan, M., & Zafar, M. (2024). the awareness, acceptance and adoption of cryptocurrency with the moderating effect of trust: A perspective of TAM. Migration Letters. 21. 600-617.
  • Illia, A., Lawson-Body, A., Lee, S, & Akalin, G. (2023). Determinants of cryptocurrency exchange adoption: A conceptual model. International Journal of Technology and Human Interaction, 19, 1-14.
  • Jariyapan P., Mattayaphutron S., Gillani SN., & Shafique O. (2022). factors influencing the behavioral intention to use cryptocurrency in emerging economies during the covid-19 pandemic: Based on technology acceptance model 3, perceived risk, and financial literacy. Front Psychology. 12:814087. https://doi.org/10.3389/fpsyg.2021.814087
  • Johns, G. (2006). The essential impact of context on organizational behavior. Academy of Management Review, 31(2), 386-408.
  • Johnston, H., Wells, R., Shanks, E., Boey, T., & Parsons, B. (2024). Student perspectives on the use of generative artificial intelligence technologies in higher education. International Journal for Educational Integrity, 20(1), 1-21.
  • Kim, M. (2021). A Psychological approach to bitcoin usage behavior in the era of COVID-19: Focusing on the role of attitude towards money. Journal of retailing and consumer services, 62(1).
  • Khan M. Z., Ali Y., Sultan H. B., Hasan M., & Baloch, S. (2020). Future of currency: a comparison between traditional, digital fiat and cryptocurrency exchange mediums. International Journal of Blockchains Cryptocurrencies, 1(1), 206–224.
  • Khan, I. U., Hameed, Z., & Khan, S. (2017). Understanding online banking adoption in a developing country: UTAUT2 with cultural moderators. Journal of Global Information Management, 25(1), 43-65.
  • Kher R., Terjesen S., & Liu C. (2021). Blockchain, Bitcoin, and ICOs: a review and research agenda. Small Business Economics, 56(2), 1699-1720.
  • Kline, R. B. (2013). Beyond significance testing: Statistics reform in the behavioral sciences (2nd ed.). Washington DC: American Psychological Association. https://doi.org/10.1037/14136-000
  • Lone A. H. & Naaz R. (2021). Applicability of Blockchain smart contracts in securing Internet and IoT: a systematic literature review. Computer Science Review, 39(1), 9-20.
  • Mailizar M. & Johar, R. (2021). Examining Students’ Intention to Use Augmented Reality in a Project-Based Geometry Learning Environment. International Journal of Instruction, 14(2), 773-790.
  • Maruf, T. I., Manaf, N., Haque, A., & Maulan, S. (2021). Factors affecting attitudes towards using ride-sharing apps. International journal of business, economics, and law, 25(2), 60-70.
  • Mattsson C., Criscione T., & Ruddick W. (2022). Sarafu community inclusion currency 2020–2021. Scientific Data, 9(1), 1-39.
  • Mazambani, L., & Mutambara, El. (2019). Predicting fintech innovation adoption in South Africa: the case of cryptocurrency. South African Journal of Economic and Management Sciences, 11(1), 30-50
  • Mendoza-Tello, J., Mora, H., Pujol, F., & Lytras, M. (2019). Disruptive innovation of cryptocurrencies in consumer acceptance and trust. Information Systems and e-Business Management. 17(1), 195-222.
  • Merhi, M., Hone, K., & Tarhini, Ali. (2019). A cross-cultural study of the intention to use mobile banking between Lebanese and British consumers: Extending UTAUT2 with security, privacy and trust. Technology in Society, 9, Article ID 101159. http://doi.org/10.1016/j.techsoc.2019.101151
  • Mweetwa, L., & Mwange, A. (2023). Major models and theories of cryptocurrency technology adoption: A theoretical review. International Journal of Multidisciplinary Research and Growth Evaluation, 4(1), 661-673.
  • Muttaqin, H., Deswantiyar, R., & Kartono, R. (2023). Analysis of consumer motivation for using cryptocurrency in Indonesia. Budapest international research and critics institute, 6 (1), 424-436.
  • Nadeem M. A., Liu Z., Pitafi A. H., Younis A., & Xu Y. (2021). Investigating the Adoption Factors of Cryptocurrencies—A Case of Bitcoin: Empirical Evidence from China. SAGE Open, 11(1). https://doi.org/10.1177/2158244021998704
  • Ndemo, B. (2022). Role of Cryptocurrency in Sub-Saharan Africa. Brookings Foresight Africa, 2022, 5(1). https://www.brookings.edu/articles/the-role-of-cryptocurrencies-in-sub-saharan-africa/
  • Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric Theory (3rd ed.). New York: McGraw-Hill.
  • Odera, A., & Matiy, A. (2023). Advancing Kenya’s digital literacy initiatives in arid and semi-arid lands. The Kenya Institute for Public Policy Research and Analysis, Policy Brief, No. 8/2023-2024.
  • Ordu A., & Golubski C. (2022). Foresight Africa: Priorities for the continent 2022. Washington DC: Brookings Institution. https://www.brookings.edu/articles/foresight-africa-2022/
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There are 76 citations in total.

Details

Primary Language English
Subjects Finance, Finance and Investment (Other), Business Administration
Journal Section Articles
Authors

Antony Rahim Atellu This is me 0000-0001-5966-8660

Publication Date December 31, 2024
Submission Date July 10, 2024
Acceptance Date November 29, 2024
Published in Issue Year 2024 Volume: 11 Issue: 2

Cite

APA Atellu, A. R. (2024). DETERMINANTS OF CRYPTOCURRENCY ADOPTION: EVIDENCE FROM AN EMERGING ECONOMY. Journal of Economics Finance and Accounting, 11(2), 120-135. https://doi.org/10.17261/Pressacademia.2024.1959

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