Antecedents of the Adoption of Cryptocurrency Investment in an Emerging Market: The Role of Behavioural Bias

Vilani Sachitra *

University of Sri Jayewardenepura, Nugegoda, Sri Lanka.

Saduni Rajapaksha

University of Sri Jayewardenepura, Nugegoda, Sri Lanka.

*Author to whom correspondence should be addressed.


Abstract

Cryptocurrencies have become a popular discussion in the global economy as an increasing number of people adopt these despites their recent conception. As a result, governments worldwide are racing to incorporate assets into their legal frameworks. While Sri Lanka does not have a legal framework for such assets, there is a growing base for cryptocurrency investors in the country. This study analyzes the antecedents that drive Sri Lankan investors towards cryptocurrency investments and the influence of commonly known behavioral biases among these investors to examine the validity of behavioral finance theories in cryptocurrency markets. A structured questionnaire was distributed on social media platforms, which yielded 158 responses. Descriptive analysis was used to evaluate the demographic characteristics of the respondents, and PLS-SEM was used to examine the path model analysis of associations among the study variables. The findings suggest that the majority of respondents are males under 35 years of age with high educational qualifications, and that technical, economic, social, and personal factors are their main adoption motivators. The analysis of behavioral biases suggests that heuristic-driven and frame-dependent biases influence cryptocurrency adoption decisions. As a highly discussed topic in today’s world, there is a lack of studies focusing on the adoption motivators and behavioral biases of cryptocurrency investors. These findings provide valuable insights and enrich the existing knowledge in the domain of cryptocurrency, as this study is a pioneering endeavor focusing on behavioral biases in cryptocurrency markets.

Keywords: Cryptocurrency, behavioral biases, prospect theory, Sri Lanka, adoption


How to Cite

Sachitra, V., & Rajapaksha, S. (2023). Antecedents of the Adoption of Cryptocurrency Investment in an Emerging Market: The Role of Behavioural Bias. Asian Journal of Economics, Business and Accounting, 23(20), 61–77. https://doi.org/10.9734/ajeba/2023/v23i201092

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References

Liébana-Cabanillas F, Sánchez-Fernández J, Muñoz-Leiva F. Antecedents of the adoption of the new mobile payment systems: The moderating effect of age. Computers in Human Behavior. 2014;35:464-478.

Guych N, Anastasia S, Simon Y, Jennet A. Factors influencing the intention to use cryptocurrency payments: An examination of blockchain economy. 2018;11-12.

Bouri E, Gupta R, Roubaud D. Herding behaviour in the cryptocurrency market. Dept. of Economics working paper series, University of Pretoria; 2018.

CoinGecko. Crypto market cap charts. CoinGecko; 2022. Available:https://www.coingecko.com/en/global-charts

Son J, Park J. Effects of financial education on sound personal finance in Korea: Conceptualization of mediation effects of financial literacy across income classes. International journal of consumer studies. 2019;43(1):77-86.

Yoong J, Ferreira VRDM. Improving financial education effectiveness through behavioural economics: OECD key findings and way forward. OECD Publishing. 2013;1:1926-1982.

Pompian MM. Behavioral finance and investor types: Managing behavior to make better investment decisions. John Wiley & Sons; 2012.

Hoffmann AO, Shefrin H, Pennings JM. Behavioral portfolio analysis of individual investors; 2010. SSRN 1629786.

Nian LP, Chuen DLK. Introduction to Bitcoin, in: Handbook of Digital Currency. Elsevier. 2015;5–30. Available:https://doi.org/10.1016/B978-0-12-802117-0.00001-1

European Central Bank. Virtual currency schemes: a further analysis. Publications Office, LU; 2015.

Vranken H. Sustainability of bitcoin and blockchains. Current opinion in environmental sustainability. 2017;28:1-9.

Urquhart A. The inefficiency of bitcoin. Economics Letters. 2016;148:80-82.

Böhme R, Christin N, Edelman B, Moore T. Bitcoin: Economics, technology, and governance. Journal of economic Perspectives. 2015;29(2):213-238.

Baur DG, Dimpfl T. The volatility of Bitcoin and its role as a medium of exchange and a store of value. Empirical Economics. 2021;61(5):2663-2683.

Economy Next. Sri Lanka cryptocurrency users should take own risk: CB officials; 2021.

Bohr J, Bashir M. July. Who uses bitcoin? an exploration of the bitcoin community. In 2014 Twelfth Annual International Conference on Privacy, Security and Trust. 2014;94-101. IEEE.

Schuh S, Shy O. April. US consumers adoption and use of Bitcoin and other virtual currencies. In DeNederlandsche bank, Conference entitled Retail payments: mapping out the road ahead; 2016.

Xi D, OBrien TI, Irannezhad E. Investigating the investment behaviors in cryptocurrency. The Journal of Alternative Investments. 2020;23(2):141-160.

Al Shehhi A, Oudah M, Aung Z. Investigating factors behind choosing a cryptocurrency. In 2014 IEEE international conference on industrial engineering and engineering management. 2014;1443-1447. IEEE.

Alzahrani S, Daim TU. Analysis of the cryptocurrency adoption decision: Literature review. In 2019 Portland International Conference on Management of Engineering and Technology (PICMET). 2019a;1-11. IEEE.

Presthus W, OMalley NO. Motivations and barriers for end-user adoption of bitcoin as digital currency. Procedia Computer Science. 2017;121:89-97.

Khairuddin IE, Sas C, Clinch S, Davies N. Exploring motivations for bitcoin technology usage. In Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems. 2016;2872-2878.

Alzahrani S, Daim TU. Evaluation of the cryptocurrency adoption decision using hierarchical decision modeling (HDM); 2019b.

Karlstrøm H. Do libertarians dream of electric coins?; 2014.

Maurer B, Nelms TC, Swartz L. When perhaps the real problem is money itself!. The practical materiality of Bitcoin. Social semiotics. 2013;23(2):261-277.

Sas C, Khairuddin IE. Design for trust: An exploration of the challenges and opportunities of bitcoin users. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. 2017;6499-6510.

Chuen DLK, Guo L, Wang Y. Cryptocurrency: A new investment opportunity?. The journal of alternative investments. 2017;20(3):16-40.

Krombholz K, Judmayer A, Gusenbauer M, Weippl E. The other side of the coin: User experiences with bitcoin security and privacy; 2016.

Shefrin H. Beyond Greed and Fear: Understanding Behavioral Finance and the Psychology of Investing. Oxford University Press; 2000.

Montier J. Darwin's mind: The evolutionary foundations of heuristics and biases; 2002.

Available:https://doi.org/10.2139/ssrn.373321

Tversky A, Kahneman D. Judgment under uncertainty: heuristics and biases: Biases in judgments reveal some heuristics of thinking under uncertainty. Science. 1974;185(4157):1124-1131.

De Bondt WF, Muradoglu YG, Shefrin H, Staikouras SK, Fromlet H. Behavioral finance-theory and practical application: Systematic analysis of departures from the homo oeconomicus paradigm are essential for realistic financial research and analysis. Business economics. 2001;63-69.

Frensidy B. Agile and tactical in the capital market: Armed with behavioral finance. Jakarta: Salemba Empat; 2016.

Barberis N, Thaler R. A survey of behavioral finance. Handbook of the Economics of Finance. 2003;1:1053-1128.

Thaler RH. Mental accounting and consumer choice. Marketing Science; 1985.

Craggs B, Rashid A. The role of confirmation bias in potentially undermining speculative cryptocurrency decisions. In IEEE International COnference on Security. 2016;1-4.

Handagama S. Economic Uncertainty Drives Crypto Growth in Sri Lanka – CoinDesk; 2021. Available:https://www.coindesk.com (accessed 9.26.21).

Krejcie RV, Morgan DW. Determining Sample Size for Research Activities. Educational and Psychological Measurement. 1970;30:607–610. Available:https://doi.org/10.1177/001316447003000308

Al-Amri R, Zakaria NH, Habbal A, Hassan S. Cryptocurrency adoption: Current stage, opportunities, and open challenges. International journal of advanced computer research. 2019;9(44):293-307.

Ackert LF, Deaves R. Behavioral Finance: Psychology. Decision-Making, and Markets. 2010;97: 99.

Munir FFA. Reliability and validity analysis on the relationship between learning space, students satisfaction and perceived performance using SMART-PLS; 2018.

Ramayah T, Yeap JA, Ahmad NH, Halim HA, Rahman SA. Testing a confirmatory model of Facebook usage in SmartPLS using consistent PLS. International Journal of Business and Innovation. 2017;3(2):1-14.

Hair Jr JF, Sarstedt M, Hopkins L, Kuppelwieser VG. Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research. European business review; 2014.

Sylvie M, Pascal K. Mobile Money: Décryptage dune succes story africaine. Management & Data Science; 2020.

Available:https://doi.org/10.36863/mds.a.14027

Al-Mansour BY. 2020. Cryptocurrency market: Behavioral finance perspective. The Journal of Asian Finance, Economics and Business. 2020;7(12):159-168.

In Portland International Conference on Management of Engineering and Technology (PICMET). 2019;1-7. IEEE.

Babajide AA, Adetiloye KA. Investors’ behavioural biases and the security market: an empirical study of the nigerian security market. Accounting and Finance Research. 2012;1(1): 219-219.

Baker HK, Nofsinger JR. eds. Behavioral finance: Investors, corporations, and markets . John Wiley & Sons. 2010;6.

Chira I, Adams M, Thornton B. Behavioral bias within the decision making process; 2008.

Behavioral finance: Quo vadis?. Journal of Applied Finance (Formerly Financial Practice and Education). 18(2).

Fang F, Ventre C, Basios M, Kanthan L, Martinez-Rego D, Wu F, Li L. Cryptocurrency trading: A comprehensive survey. Financial Innovation. 2022;8(1):1-59.

Kahneman D, Tversky A. Prospect theory: An analysis of decision under risk. In Handbook of the fundamentals of financial decision making: Part I. 2013 99-127.

The material embeddedness of Bitcoin. Distinktion: Scandinavian journal of social theory. 15(1):23-36.

In International conference on financial cryptography and data security. Springer, Berlin, Heidelberg. 555-580.

Lammer DM, Hanspal T, Hackethal A. Who are the Bitcoin investors?. Evidence from indirect cryptocurrency investments . SAFE Working Paper. 2020;277.

International Journal of Academic Research in Business and Social Sciences. 8(1):775-783.

Pompian MM. Behavioral finance and wealth management: How to build investment strategies that account for investor biases. John Wiley & Sons; 2011.

Talwar S, Talwar M, Tarjanne V, Dhir A. Why retail investors traded equity during the pandemic?. An application of artificial neural networks to examine behavioral biases. Psychology & Marketing. 2021;38(11):2142-2163.

The Law Reviews—The Virtual Currency Regulation Review; 2021. Available:https://thelawreviews.co.uk/title/the-virtual-currency-regulation-review/usa

Tversky A, Kahneman D. Rational choice and the framing of decisions. In Multiple criteria decision making and risk analysis using microcomputers. Springer, Berlin, Heidelberg. 1989;81-126.