Is Cryptocurrency Technology Adoption Effective in Individuals’ Investment Behavior?

Document Type : Research Paper

Authors

1 Faculty of Economics, Marmara University, Marmara, Turkey

2 Facultyof Economics, Marmara University, Marmara, Turkey

Abstract

Behavioral intentions of individuals occur as a result of positive or negative evaluations of any object or idea. It is a determinant that has a significant impact on transforming an individual’s ideas into behavior. The structure and effectiveness of information in financial markets are vital to understanding the behavior of investors, because the digital economy that develops with crypto money is psychologically significantly different from the cash economy. Accordingly, this study examined the main intentions or motivational factors that persuade individuals to invest in cryptocurrencies and the way these factors affect the actual investment behavior. This was done in the context of behavioral considerations in finance through the Unified Technology Acceptance Model (UTAUT). As a result of the model estimation, it has been concluded that the performance expectation is an important factor behind the investment behavior, and its effect changes considering positive or negative news about the pricing of cryptocurrencies.

Keywords

Main Subjects

References

Afthanorhan, W. M., & Afthanorhan, B. W. (2013). A comparison of partial least square structural equation modeling (PLS-SEM) and covariance based structural equation modeling (CBSEM) for confirmatory factor analysis. International Journal of Engineering Science and Innovative Technology, 2(5), 198-205.
Agosto, A., & Cafferata, A. (2020). Financial bubbles: A study of co-explosivity in the cryptocurrency market. Risks, 8(2), 1–14. https://doi.org/10.3390/risks8020034. 
Agrebi, S., & Jallais, J. (2015). Explain the intention to use smartphones for mobile shopping. Journal of Retailing and Consumer Services, 22, 16-23.
Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In  J. Kuhl & J. Beckman (Eds.), Action control, from cognition to behaviour (pp. 11-39). Springer.
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(44), 293–307.
Alazab, M., Alhyari, S., Awajan, A., Abdallah, A. B. (2021). Blockchain technology in supply chain management: An empirical study of the factors affecting user adoption/acceptance. Cluster Computing, 24, 83-101. https://doi.org/10.1007/s10586-020-03200-4
Almarashdeh, I.,   Eldaw, K. E., Alsmadi, M., Alghamdi, F., Jaradat, G., Althunibat, A., Alzaqebah, M., & Mohammad, R. M. A. (2021). The adoption of bitcoins technology: The difference between perceived future expectation and intention to use bitcoins: Does social influence matter? International Journal of Electrical and Computer Engineering, 11(6), 5351-5366.
Alzahrani, S. & Daim, T. U. (2019). Evaluation of the cryptocurrency adoption decision using hierarchical decision modeling (HDM). 2019 Portland International Conference on Management of Engineering and Technology (PICMET), Portland, OR, USA, pp. 1-7
Arı, E., Yılmaz, V., & Başkan, E. (2015). Seçmen oy verme davranişlarinin betimlenmesi için bir yapisal eşitlik model önerisi: Yalova ili mahalli idareler seçimi örneği [A structural equation model proposal for describing the voting behavior of the voters: An example of local administrations in Yalova]. Uluslararası Alanya İşletme Fakültesi Dergisi, 7(3), 1-17.
Arias-Oliva M., Pelegrin-Borondo J., & Matias-Clavero G. (2019). Variables influencing cryptocurrency Use: A technology acceptance model in Spain. Frontier Psychology, 10(475). https://doi.org/10.3389/fpsyg.2019.00475
Barak, O. (2008). Davranışsal finans teori ve uygulama [Behavioral finance theory and practice]. Ankara: Gazi Published.
Baur, D. G., & McDermott, T. K. J. (2012). Safe haven assets and investor behaviour under uncertainty. SSRN Electronic Journal, 392, 1-60. https://doi.org/10.2139/ssrn.2004796
Birch, D. (2017). Before Babylon, beyond Bitcoin. London Publishing Partnership.
Böhme, R., Christin, N., Edelman, B., & Moore, T. (2015). Bitcoin: Economics, technology, and governance. Journal of Economic Perspectives, 29(2), 213–238.
Chatterjee, P., & Rose, R. L. (2012). Do payment mechanisms change the way consumers perceive products? Journal of Consumer Research, 38(6), 1129–1139. doi:10.1086/661730 
Chen, L., Gillenson, M. L., & Sherrell, D. L. (2002). Enticing online consumers: An extended technology acceptance perspective. Information & Management, 39(8), 705-719.
Cheng, S., & Terry, L. (2008). The role of the customer-seller relationship of the intention of the customer to complain: A study of Chinese restaurateurs. International Journal of Hospitality and Tourism Research, 27(4), 552-562.
Chow, Y. Y., Sugathan, S. K., Kalid, K. S., & Arshad, N. I. (15-16 March, 2019). What determines the acceptance of cryptocurrency in Malaysia? An analysis based on UTAUT2 [paper presentation]. International conference on recent advancements in engineering and technology (ICRAET-18). Siddhartha Institute of Technology & Sciences, Telangana, India.
Claian, P., Rajcaniova, M., & Kancs, D. (2016). The economics of Bitcoin price formation. Applied Economics, 48(19), 1799-1815.
CSBS (2017). Consumer Survey: Consumer Attitudes on Bitcoin and Other Virtual Currencies.     https://www.csbs.org/regulatory/ep/Documents/Final Report-VirtualCurrencySurvey2014.pdf.
Davis, F. D. (1986). A technology acceptance model for empirically testing new end-user information systems: Theory and results [unpublished PhD dissertation]. Massachusetts Institute of Technology.
Davis, F. D., Bagozzi, P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003.
Davis, F. D., & Venkatesh, V. (1996). A critical assessment of potential measurement biases in the technology acceptance model: Three experiments. International Journal of Human-Computer Studies, 45(1), 19- 45.
Diniz, E. H., Cernev, A. K., & Nascimento, E. (2016). Mobile social money: An exploratory study of the views of managers of community banks. Revista de Administração, 51(3), 299–309.
Duong, C. M., Pescetto, G. M. R., & Santamaria, D. (2017). How value–glamour investors use financial information: UK evidence of investor’s confirmation bias. The European Journal of Finance, 20(6), 524-549. http://dx.doi.org/10.2139/ssrn.1688255
Ekşioğlu, E. (2017). Elektronik Para Kullanımının Ekonomik Etkileri (Türkiye Üzerinde Bir Uygulama) [Economic Effects of Using Electronic Money (An Application on Turkey)] [unpublished PhD Thesis]. Cumhuriyet Üniversitesi.
Engelberg, J., & Parsons, C. (2011). The causal impact of media in financial markets. The Journal of Finance, 66(1), 67-97.
Feng, W., Wang, Y., & Zhang, Z. (2018). Informed trading in the Bitcoin market. Finance Research Letters, 26, 63-70. https:// doi.org/10.1016/j.frl.2017.11.009
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Addison-Wesley Publishing.
Fitrianie, S., Horsch, C., Beun, R. J., Griffioen-Both, F., & Brinkman, W.-P. (2021). Factors affecting user’s behavioral intention and use of a mobile-phone-delivered cognitive behavioral therapy for insomnia: A small-scale UTAUT analysis. Journal of Medical Systems, 45(12), 1-18
Folkinshteyn, D., & Lennon, M. (2016). Braving Bitcoin: A technology acceptance model (TAM) analysis. Journal of Information Technology Case and Application Research, 184(4), 220–249.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
Frazzini, A. (2006). The disposition effect and underreaction to new. The Journal of Fınance, 11(4), 22-30.
Gamage, T. C., & Tajeddini, K. (2022). A multi-layer organizational culture framework for enhancing the financial performance in tourism and hospitality family firms. Tourism Management, 91(3), (104516),
Gamage, T. C., Tajeddini, K., & Tajeddini, O. (2022). Why Chinese travelers use WeChat to make hotel choice decisions: A uses and gratifications theory perspective. Journal of Global Scholars of Marketing Science, 32(2), 285-312. 
Gerard, D. (2018). Bitcoin is less about technology than psychology. https://davidgerard.co.uk/blockchain/2018/02/02/bitcoin-is-less-about-technology-than-psychology-jungle-world-interview-original-interview-in-english/
Geuder, J., Kinateder, H., & Wagner, N. F. (2019). Cryptocurrencies as financial bubbles: The case of Bitcoin. Finance Research Letters,  31, 179-184. https://doi.org/10.1016/j.frl.2018.11.011 
Goswami, A., & Dutta, S. (2016). Gender differences in technology usage – A literature review. Open Journal of Business and Management, 4, 51-59.
Grable, J., & Lytton, R. H. (1999). Financial risk tolerance revisited: The development of a risk assessment instrument. Financial Services Review, 8, 163–181.
Gunawan, F. E., & Novendra, R. (2017). An analysis of Bitcoin acceptance in Indonesia. ComTech: Computer, Mathematics and Engineering Applications, 8(4), 241-247.
Gupta, S., Gupta, S., Mathew, M., & Sama, H. R. (2020). Prioritizing intentions behind investment in cryptocurrency: A fuzzy analytical framework. Journal of Economic Studies, ahead-of-print(ahead-of-print). doi:10.1108/jes-06-2020-0285
Gürsoy, Ş.T. Çiçeklioğlu, M., Börekçi, N., Soyer, M.T., Öcek, Z. (2008). İzmir Karşıyaka belediye çalışanlarında çevresel risk algılama düzeyi. Cumhuriyet Üniversitesi Tıp Fakültesi Dergisi, 30(1), 20-27.
Hair, J., Anderson, R., Tatham, R. and Black, W. (1998). Multivariate data analysis. 5th Edition, New Jersey: Prentice Hall.
Hair Jr, J., Sarstedt, M., Hopkins, L., & Kuppelwieser, V. G. (2014). Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research. European Business Review, 26(2), 106-121. https://doi.org/10.1108/EBR-10-2013-0128
Hayes, A. S. (2017). Cryptocurrency value formation: an empirical study leading to a cost of production model for valuing Bitcoin. Telematics and Informatics, 34(7), 1308–1321. https://doi. org/10.1016/j.tele.2016.05.005
Hilferding, R. (1981), Finance capital. Routledge&Kegan Paul.
Jörg, H., Hubona, G., & Ray, P. A. (2016). Using PLS path modeling in new technology research: Updated guidelines. Industrial Management & Data Systems, 116(1), 2-20. https://doi.org/10.1108/IMDS-09-2015-0382
Junadi, S., & Fenrianto, J. A. (2015). Model of factors influencing consumers’ intention to use e-payment system in Indonesia. Procedia Computer Science, 59, 214–220.
Kabak A., & Çelik Z. (4-6 December, 2020). Tüketicilerin kripto para kullanim niyeti ile ilişkili faktörlerin belirlenmesine yönelik uygulamali bir araştırma [An applied research to determine the factors associated with consumers' intention to use cryptocurrencies] [paper presentation]. 6th International GAP Social Sciences Congress, Şanlıurfa, Turkey.
Kijsanayotin, B., Pannarunothai, S., & Speedie, S. M. (2009). Factors influencing health information technology adoption in Thailand’s community health centers: Applying the UTAUT model. International Journal of Medical Informatics, 78(6), 404–416. https://doi.org/10.1016/j.ijmedinf.2008.12.005
Kline, P. (1994). An easy guide to factor analysis. Routledge.
Kotler, P. (2000). Kotler ve Pazarlama, (Translated into Turkish by N. Muallimoğlu). İstanbul: Sistem Published.
Lansky, J. (2018). Possible state approaches to cryptocurrencies. Journal of Systems Integration, 9, 19–31.
Lapuz, J., & Griffiths, M. (2010). The role of chips in poker gambling: An empirical pilot study. Gambling Research, 22(1), 34–39.
Lee, L. (2015). New kids on the blockchain: How Bitcoin’s technology could reinvent the stock market. Hastings Business Law Journal, 12, 81–132.
Madhavan, A. (2000). Market microstructure: A survey. Journal of Financial Markets, 3(3), 205–258. https://traders.berkeley.edu/papers/Market%20Microstructure.pdf
Marketwatch, (2021). Bitcoin.  https://www.marketwatch.com/investing/fund/bito.
Mendoza-Tello, J. C., Mora, H. M., Pujol-López, F. A., & Lytras, M. D. (2018). Social commerce as a driver to enhance trust and intention to use cryptocurrencies for electronic payments. Institute of Electrical and Electronics Engineers Access, 6, 50737-50751.
Moon, J. W., & Kim, Y. G. (2001). Extending the TAM for a World Wide Web context. Information & Management, 38(4), 217-230.
Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192–222.
Natarajan, T., Balasubramanian, S. A., & Kasilingam, D. L. (2017). Understanding the intention to use mobile shopping applications and its influence on price sensitivity. Journal of Retailing and Consumer Services, 37, 8-22.
Öksüz Karademir, C., & Kuş, O. (2020). Exploring crypto-currency ownership in the context of technology acceptance model and technology adopter categories: Coin-optimistics, observes and coin-sceptics. Ankara Üniversitesi Sosyal Bilimler Dergisi, 11(2), 43-59.
Polat, M., & Akbıyık, A. (2019). Sosyal medya ve yatirim araçlarinin değeri arasindaki ilişkinin incelenmesi: Bitcoin örneği [Examining the relationship between social media and the value of investment instruments: Bitcoin example]. Akademik İncelemeler Dergisi, 14(1), 443-462.
Popper, N. (2015). Digital gold: Bitcoin and the inside story of the misfits and millionaires trying to reinvent money. Harper.
Prelec, D. R., & Loewenstein, G. (1998). The red and the black: Mental accounting of savings and debt. Marketing Science, 17, 4–28.
Raykov, T., & Marcoulides, G. A. (2006). A first course in structural equation modeling. Lawrence Erlbaum Associates.
Rogers, E. M. (1995). Diffusion of innovations. Simon & Schuster Press.
Schaupp, L. C., & Festa, M. (2018). Cryptocurrency adoption and the road to regulation. Proceedings of the 19th Annual International Conference on Digital Government Research Governance in the Data Age - Dgo ’18. doi:10.1145/3209281.3209336 
Schumacker, R. E., & Lomax, R. G. (2004). A beginner’s guide to structural equation modeling. Lawrence Erlbaum Associates Publishers.
Shahzad, F., Xiu, G., Wang, J., & Shahbaz, M. (2018). An empirical investigation on the adoption of cryptocurrencies among the people of mainland China. Technology in Society, 55, 33–44.
Steinmetz, F., von Meduna, M., Ante, L., & Fiedler, I. (2021). Ownership, uses and perceptions of cryptocurrency: Results from a population survey. Technological Forecasting and Social Change, 173(121073). https://doi.org/10.1016/j.techfore.2021.121073
Szajna, B. (1996). Empirical evaluation of the revised technology acceptance model. Management Science, 42(1), 85-92.
Tajeddini, K., Gamage, T. C., Ul Hameed, W., Qumsieh-Mussalam, G., Chaijani, M. H., Rasoolimanesh, S. M., & Kallmuenzer, A. (2022). How self-gratification and social values shape revisit intention and customer loyalty of airbnb customers. International Journal of Hospitality Management, 100(3).
Tajeddini, K., & Nikdavoodi, J. N. (2014). Cosmetic buying behavior: Examining the effective factors. Journal of Global Scholars of Marketing Science, 24(4), 395-410.
Tajeddini, K., Rasoolimanesh, S. M., Gamage, T. C., & Martin, E. (2021). Exploring the visitors’ decision-making process for Airbnb and hotel accommodations using value-attitude-behavior and theory of planned behavior. International Journal of Hospitality Management, 96, 102950.
Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144-176.
Tetlock, P. C., Saar-Tsechansky, M., & Macskassy, S. (2008). More than words: Quantifying language to measure firms’ fundamental. The Journal of Finance, 63(3), 1437-1467.
Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991). Personal computing: Toward a conceptual model of utilization. MIS Quarterly, 15(1), 125-143.
Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and research agenda on interventions. Decision Sciences, 39(2), 273-315.
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. Management Information Systems Quarterly, 27(3), 425–478.
Veronesi, P. (1999). Stock market overreactions to bad news in good times: A rational expectations equilibrium model. Review of Financial Studies, 12(5), 975-1007.
Wixom, B. H., & Todd, P. A. (2005). A theoretical integration of user satisfaction and technology acceptance. Information Systems Research, 16(1), 85-102.
Zhu, Z., Liu, Y., Cao, X., & Dong, W. (2022). Factors affecting customer intention to adopt a mobile chronic disease management service: differentiating age effect from experiential distance perspective. Journal of Organizational and End User Computing, 34(4), 1-2.
Interdisciplinary Journal of Management Studies (Formerly known as Iranian Journal of Management Studies)
Volume 16, Issue 2
April 2023
Pages 375-393

Files

Share

How to cite

Statistics