Intent to Invest in Cryptocurrency Amid Uncertainty : A Theory of Planned Behavior Approach

Authors

DOI:

https://doi.org/10.17010/ijf/2025/v19i12/175877

Keywords:

theory of planned behavior, attitude to invest, willingness to invest, cryptocurrency, pandemic management.
JEL Classification Codes : D1, D8, G1
Publication Chronology: Paper Submission Date : September 2, 2024 ; Paper sent back for Revision : March 31, 2025 ; Paper Acceptance Date : October 20, 2025 ; Paper Published Online : December 15, 2025

Abstract

Purpose : Investors sometimes have difficulties in making appropriate decisions during unpredictable times such as the COVID-19 pandemic. Based on the extended theory of planned behavior (TPB), the objective of this study was to validate the psychological antecedents of willingness to invest in cryptocurrency during the outbreak of the COVID - 19 pandemic.

Design/Methodology/Approach : This study was conducted by collecting primary data from 204 respondents using a structured online questionnaire, which was further analyzed using SPSS Amos 23.0. The current research explored the association between variables named “subjective norms,” “perceived self-efficacy,” and “attitude to invest.”

Findings : The findings suggested that “subjective norms” and “perceived self-efficacy” are the major factors influencing investors’ attitudes toward cryptocurrency investment, directly impacting their intentions for the same. The pandemic underscored the dual nature of cryptocurrencies, demonstrating advantages such as enabling remote transactions and providing a hedge against economic instability, while simultaneously displaying difficulties, including environmental implications and market volatility.

Practical Implications : The results have important reference significance for future investors who intend to invest in the crypto-assets market. The findings of the study provided important insights to investors and financial planners on which psychological factors affect whether to make a cryptocurrency investment during volatile periods, such as the COVID-19 era. Learning these key aspects will provide scientists with tools to navigate choppy waters, which will ultimately make them better decision-makers.

Originality : This research enhanced the existing body of knowledge by uniquely incorporating the extended theory of planned behavior into the context of cryptocurrency investments during a global crisis. It offered an extensive comprehension of investor psychology during periods of uncertainty, essential for both scholarly study and pragmatic investment strategies.

Downloads

Download data is not yet available.

Published

2025-12-15

How to Cite

Khilar, R. P., & Singh, S. (2025). Intent to Invest in Cryptocurrency Amid Uncertainty : A Theory of Planned Behavior Approach. Indian Journal of Finance, 19(12), 49–65. https://doi.org/10.17010/ijf/2025/v19i12/175877

References

1) Abbasi, G. A., Tiew, L. Y., Tang, J., Goh, Y.-N., & Thurasamy, R. (2021). The adoption of cryptocurrency as a disruptive force: Deep learning-based dual stage structural equation modelling and artificial neural network analysis. PLoS ONE, 16(3), Article ID e0247582. https://doi.org/10.1371/journal.pone.0247582

2) Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-t

3) Ajzen, I. (2011). The theory of planned behaviour: Reactions and reflections. Psychology & Health, 26(9), 1113–1127. https://doi.org/10.1080/08870446.2011.613995

4) Ajzen, I. (2020). The theory of planned behavior: Frequently asked questions. Human Behavior and Emerging Technologies, 2(4), 314–324. https://doi.org/10.1002/hbe2.195

5) Alharbi, A., & Sohaib, O. (2021). Technology readiness and cryptocurrency adoption: PLS-SEM and deep learning neural network analysis. IEEE Access, 9, 21388–21394. https://doi.org/10.1109/ACCESS.2021.3055785

6) Annapurna, R., & Basri, S. (2024). Role of emotions in stock investment decisions : A critical review of the literature. Indian Journal of Finance, 18(5), 50–65. https://doi.org/10.17010/ijf/2024/v18i5/173842

7) Anser, M. K., Zaigham, G. H., Rasheed, M. I., Pitafi, A. H., Iqbal, J., & Luqman, A. (2020). Social media usage and individuals' intentions toward adopting Bitcoin: The role of the theory of planned behavior and perceived risk. International Journal of Communication Systems, 33(17), Article no. e4590. https://doi.org/10.1002/dac.4590

8) Apergis, N. (2022). COVID-19 and cryptocurrency volatility: Evidence from asymmetric modelling. Finance Research Letters, 47(Part A), Article ID 102659. https://doi.org/10.1016/j.frl.2021.102659

9) Arli, D., van Esch, P., Bakpayev, M., & Laurence, A. (2021). Do consumers really trust cryptocurrencies? Marketing Intelligence & Planning, 39(1), 74–90. https://doi.org/10.1108/MIP-01-2020-0036

10) Assaf, A., Bhandari, A., Charif, H., & Demir, E. (2022). Multivariate long memory structure in the cryptocurrency market: The impact of COVID-19. International Review of Financial Analysis, 82, Article ID 102132. https://doi.org/10.1016/j.irfa.2022.102132

11) Awasthi, A., & Shaukat, M. (2025). Dynamics of long memory in the cryptocurrency market. Indian Journal of Finance, 19(8), 8–28. https://doi.org/10.17010/ijf/2025/v19i8/175231

12) Ayedh, A., Echchabi, A., Battour, M., & Omar, M. (2021). Malaysian Muslim investors' behaviour towards the blockchain-based Bitcoin cryptocurrency market. Journal of Islamic Marketing, 12(4), 690–704. https://doi.org/10.1108/JIMA-04-2019-0081

13) Aziz, S., Md Husin, M., Hussin, N., & Afaq, Z. (2019). Factors that influence individuals' intentions to purchase family takaful mediating role of perceived trust. Asia Pacific Journal of Marketing and Logistics, 31(1), 81–104. https://doi.org/10.1108/APJML-12-2017-0311

14) Bagozzi, R. P., & Yi, Y. (2012). Specification, evaluation, and interpretation of structural equation models. Journal of the Academy of Marketing Science, 40(1), 8–34. https://doi.org/10.1007/s11747-011-0278-x

15) Bandura, A. (1997). Self-efficacy: The exercise of control. W. H. Freeman. https://psycnet.apa.org/record/1997-08589-000

16) Bandura, A. (2000). Health promotion from the perspective of social cognitive theory. In P. Norman, C. Abraham, & M. Conner (eds.), Understanding and changing health behaviour: From health beliefs to self-regulation (pp. 299–339). Harwood Academic Publishers. https://psycnet.apa.org/record/2001-16477-012

17) Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107(2), 238–246. https://doi.org/10.1037/0033-2909.107.2.238

18) Bowden, J., & Gemayel, R. (2022). Sentiment and trading decisions in an ambiguous environment: A study on cryptocurrency traders. Journal of International Financial Markets, Institutions and Money, 80, Article ID 101622. https://doi.org/10.1016/j.intfin.2022.101622

19) Cadet, F. (2022). Bitcoin: Bringing new meaning to purchasing power & bridging the wealth gap. In Association of Marketing Theory and Practice Proceedings 2022 (Paper No. 54). https://digitalcommons.georgiasouthern.edu/amtp-proceedings_2022/54

20) Chau, P. Y. (1997). Reexamining a model for evaluating information center success using a structural equation modeling approach. Decision Sciences, 28(2), 309–334. https://doi.org/10.1111/j.1540-5915.1997.tb01313.x

21) Chopra, M., & Saldi, R. (2022). Investment in Bitcoin: A delusion or diligence? Indian Journal of Finance, 16(7), 8–22. https://doi.org/10.17010/ijf/2022/v16i7/170632

22) Coeckelbergh, M., & Reijers, W. (2016). Cryptocurrencies as narrative technologies. ACM SIGCAS Computers and Society, 45(3), 172–178. https://doi.org/10.1145/2874239.2874264

23) Conner, M. (2015). Extending not retiring the theory of planned behaviour: A commentary on Sniehotta, Presseau and Araújo-Soares. Health Psychology Review, 9(2), 141–145. https://doi.org/10.1080/17437199.2014.899060

24) Corbet, S., Hou, Y., Hu, Y., Larkin, C., & Oxley, L. (2020). Any port in a storm: Cryptocurrency safe-havens during the COVID-19 pandemic. Economics Letters, 194, Article ID 109377. https://doi.org/10.1016/j.econlet.2020.109377

25) Dong, X., Song, L., & Yoon, S.-M. (2021). How have the dependence structures between stock markets and economic factors changed during the COVID-19 pandemic? The North American Journal of Economics and Finance, 58, Article ID 101546. https://doi.org/10.1016/j.najef.2021.101546

26) Echchabi, A., Aziz, H. A., & Tanas, I. N. (2021). Determinants of investment in cryptocurrencies: The case of Morocco. Rafgo, 1(1), 1–6. https://akuntansi.pnp.ac.id/rafgo/index.php/RAFGO/article/view/2

27) Egorova, N. E., & Torzhevskiy, K. A. (2016). Bitcoin: Main trends and perspectives. Journal of Economics, Management and Trade, 12(1), 1–11. https://doi.org/10.9734/bjemt/2016/19763

28) Elnadi, M., & Gheith, M. H. (2022). What makes consumers reuse ride-hailing services? An investigation of Egyptian consumers' attitudes towards ride-hailing apps. Travel Behaviour and Society, 29, 78–94. https://doi.org/10.1016/j.tbs.2022.06.002

29) Fang, F., Ventre, C., Basios, M., Kanthan, L., Martinez-Rego, D., Wu, F., & Li, L. (2022). Cryptocurrency trading: A comprehensive survey. Financial Innovation, 8, Article no. 13. https://doi.org/10.1186/s40854-021-00321-6

30) Foley, S., Li, S., Malloch, H., & Svec, J. (2022). What is the expected return on Bitcoin? Extracting the term structure of returns from options prices. Economics Letters, 210, Article ID 110196. https://doi.org/10.1016/j.econlet.2021.110196

31) Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18(3), 382–388. https://doi.org/10.1177/002224378101800313

32) Foroutan, P., & Lahmiri, S. (2022). The effect of COVID-19 pandemic on return-volume and return-volatility relationships in cryptocurrency markets. Chaos, Solitons & Fractals, 162, Article ID 112443. https://doi.org/10.1016/j.chaos.2022.112443

33) Gautam, S., Kumar, P., & Dahiya, P. (2024). The influence of neurotransmitters on cryptocurrency investment decision-making: The mediating role of risk tolerance and moderating role of investment experience. Indian Journal of Finance, 18(10), 40–55. https://doi.org/10.17010/ijf/2024/v18i10/174613

34) Gill, K., Kumar, H., & Singh, A. K. (2023). Evaluating the efficiency of the global cryptocurrency market. Indian Journal of Finance, 17(11), 8–25. https://doi.org/10.17010/ijf/2023/v17i11/173325

35) Goodell, J. W., & Goutte, S. (2021). Co-movement of COVID-19 and Bitcoin: Evidence from wavelet coherence analysis. Finance Research Letters, 38, Article ID 101625. https://doi.org/10.1016/j.frl.2020.101625

36) Gupta, S., Gupta, S., Mathew, M., & Sama, H. R. (2021). Prioritizing intentions behind investment in cryptocurrency: A fuzzy analytical framework. Journal of Economic Studies, 48(8), 1442–1459. https://doi.org/10.1108/JES-06-2020-0285

37) Hagger, M. S., & Hamilton, K. (2021). Effects of socio-structural variables in the theory of planned behavior: A mediation model in multiple samples and behaviors. Psychology & Health, 36(3), 307–333. https://doi.org/10.1080/08870446.2020.1784420

38) Hair Jr., J. F., Harrison, D. E., & Risher, J. J. (2018). Marketing research in the 21st century: Opportunities and challenges. ReMark - Revista Brasileira De Marketing, 17(5), 666–699. https://doi.org/10.5585/bjm.v17i5.4173

39) Hu, L.-T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. https://doi.org/10.1080/10705519909540118

40) Ifinedo, P. (2018). Empirical study of Nova Scotia nurses' adoption of healthcare information systems: Implications for management and policy-making. International Journal of Health Policy and Management, 7(4), 317–327. https://doi.org/10.15171/ijhpm.2017.96

41) Iqbal, N., Fareed, Z., Wan, G., & Shahzad, F. (2021). Asymmetric nexus between COVID-19 outbreak in the world and cryptocurrency market. International Review of Financial Analysis, 73, Article ID 101613. https://doi.org/10.1016/j.irfa.2020.101613

42) Kaufmann, H. R., Petrovici, D. A., Filho, C. G., & Ayres, A. (2016). Identifying moderators of brand attachment for driving customer purchase intention of original vs counterfeits of luxury brands. Journal of Business Research, 69(12), 5735–5747. https://doi.org/10.1016/j.jbusres.2016.05.003

43) Kim, E., Ham, S., Yang, I. S., & Choi, J. G. (2013). The roles of attitude, subjective norm, and perceived behavioral control in the formation of consumers' behavioral intentions to read menu labels in the restaurant industry. International Journal of Hospitality Management, 35, 203–213. https://doi.org/10.1016/j.ijhm.2013.06.008

44) Kim, S. T., & Orlova, S. (2021). Is Bitcoin immune to the Covid-19 pandemic? Applied Finance Letters, 10, 48–57. https://doi.org/10.24135/afl.v10i.396

45) Kondo, F. N., & Ishida, H. (2014). A cross-national analysis of intention to use multiple mobile entertainment services. Journal of Global Information Technology Management, 17(1), 45–60. https://doi.org/10.1080/1097198X.2014.910991

46) Lee, Y.-S., Vo, A., & Chapman, T. A. (2022). Examining the maturity of bitcoin price through a catastrophic event: The case of structural break analysis during the COVID-19 pandemic. Finance Research Letters, 49, Article ID 103165. https://doi.org/10.1016/j.frl.2022.103165

47) Linge, A. A., Jiwani, A., & Kakde, B. B. (2024). Factors affecting risk attitude and investors' happiness of newly employed individuals. Indian Journal of Finance, 18(5), 66–80. https://doi.org/10.17010/ijf/2024/v18i5/173843

48) Manzoor, A., Jan, A., & Shafi, M. (2023). Do personality and demographic variances of individual investors challenge the assumption of rationality? A two-staged regression modeling-artificial neural network approach. Indian Journal of Finance, 17(10), 64–78. https://doi.org/10.17010/ijf/2023/v17i10/168549

49) Mattke, J., Maier, C., Reis, L., & Weitzel, T. (2021). Bitcoin investment: A mixed methods study of investment motivations. European Journal of Information Systems, 30(3), 261–285. https://doi.org/10.1080/0960085X.2020.1787109

50) Mazambani, L., & Mutambara, E. (2020). Predicting FinTech innovation adoption in South Africa: The case of cryptocurrency. African Journal of Economic and Management Studies, 11(1), 30–50. https://doi.org/10.1108/AJEMS-04-2019-0152

51) Md Husin, M., Ismail, N., & Rahman, A. A. (2016). The roles of mass media, word of mouth and subjective norm in family takaful purchase intention. Journal of Islamic Marketing, 7(1), 59–73. https://doi.org/10.1108/JIMA-03-2015-0020

52) Mendoza-Tello, J. C., Mora, H., Pujol-López, F. A., & Lytras, M. D. (2019). Disruptive innovation of cryptocurrencies in consumer acceptance and trust. Information Systems and e-Business Management, 17, 195–222. https://doi.org/10.1007/s10257-019-00415-w

53) Minutolo, M. C., Kristjanpoller, W., & Dheeriya, P. (2022). Impact of COVID-19 effective reproductive rate on cryptocurrency. Financial Innovation, 8, Article no. 49. https://doi.org/10.1186/s40854-022-00354-5

54) Mnif, E., Salhi, B., Mouakha, K., & Jarboui, A. (2022). Investor behavior and cryptocurrency market bubbles during the COVID-19 pandemic. Review of Behavioral Finance, 14(4), 491–507. https://doi.org/10.1108/RBF-09-2021-0190

55) 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

56) Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill.

57) Ogden, J. (2015). Time to retire the theory of planned behaviour?: One of us will have to go! A commentary on Sniehotta, Presseau and Araújo-Soares. Health Psychology Review, 9(2), 165–167. https://doi.org/10.1080/17437199.2014.898679

58) Osakwe, C. N., Hudik, M., Říha, D., Stros, M., & Ramayah, T. (2022). Critical factors characterizing consumers' intentions to use drones for last-mile delivery: Does delivery risk matter? Journal of Retailing and Consumer Services, 65, Article ID 102865. https://doi.org/10.1016/j.jretconser.2021.102865

59) Park, B.-J. (2022). The COVID-19 pandemic, volatility, and trading behavior in the Bitcoin futures market. Research in International Business and Finance, 59, Article ID 101519. https://doi.org/10.1016/j.ribaf.2021.101519

60) Pham, Q. T., Phan, H. H., Cristofaro, M., Misra, S., & Giardino, P. L. (2021). Examining the intention to invest in cryptocurrencies: An extended application of the theory of planned behavior on Italian independent investors. International Journal of Applied Behavioral Economics (IJABE), 10(3), 59–79. https://doi.org/10.4018/ijabe.2021070104

61) Poonam, & Malik, N. S. (2025a). Risk–return efficiency of stochastic oscillator strategies in BRICS during COVID-19 and geopolitical conflicts. Indian Journal of Finance, 19(10), 39–52. https://doi.org/10.17010/ijf/2025/v19i10/175678

62) Poonam, & Malik, N. S. (2025b). Efficiency and predictive power of technical trading rules in post-COVID-19 era: A study of BRICS stock market. Indian Journal of Finance, 19(1), 52–66. https://doi.org/10.17010/ijf/2025/v19i1/174695

63) Ratten, V., & Ratten, H. (2007). Social cognitive theory in technological innovations. European Journal of Innovation Management, 10(1), 90–108. https://doi.org/10.1108/14601060710720564

64) Salcedo, E., & Gupta, M. (2021). The effects of individual-level espoused national cultural values on the willingness to use Bitcoin-like blockchain currencies. International Journal of Information Management, 60, Article ID 102388. https://doi.org/10.1016/j.ijinfomgt.2021.102388

65) Sharma, D., Ghosh, R., & Sharma, C. S. (2024). Cryptocurrency in the light of sentiments : A bibliometric approach. Indian Journal of Finance, 18(2), 60–75. https://doi.org/10.17010/ijf/2024/v18i2/173521

66) Singh, S., Bharti, I., & Maurya, P. (2025). A comprehensive review of prominent biases and other factors influencing retail investors' decision-making. Indian Journal of Finance, 19(7), 47–74. https://doi.org/10.17010/ijf/2025/v19i7/175196

67) StatMuse. (n.d.). Bitcoin price day by day October 2013. https://www.statmuse.com/money/ask/bitcoin-price-day-by-day-oct-2013

68) Vincent, O., & Evans, O. (2019). Can cryptocurrency, mobile phones, and internet herald sustainable financial sector development in emerging markets? Journal of Transnational Management, 24(3), 259–279. https://doi.org/10.1080/15475778.2019.1633170

69) Yang, H., & Zhou, L. (2011). Extending TPB and TAM to mobile viral marketing: An exploratory study on American young consumers' mobile viral marketing attitude, intent and behavior. Journal of Targeting, Measurement and Analysis for Marketing, 19, 85–98. https://doi.org/10.1057/jt.2011.11