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The adoption of cryptocurrency as a disruptive force: Deep learning-based dual stage structural equation modelling and artificial neural network analysis

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  • Ghazanfar Ali Abbasi
  • Lee Yin Tiew
  • Jinquan Tang
  • Yen-Nee Goh
  • Ramayah Thurasamy

Abstract

In recent years, the growth of cryptocurrency has undergone an enormous increase in cryptocurrency markets all around the world. Sadly, only insignificant heed has been paid to the unveiling of determinants of cryptocurrency adoption globally, particularly in emerging markets like Malaysia. The purpose of the study is to examine whether the application of deep learning-based dual-stage Partial Least Square-Structural Equation Modelling (PLS-SEM) & Artificial Neural Network (ANN) analysis enable better in-depth research results as compared to single-step PLS-SEM approach and to excavate factors which can predict behavioural intention to adopt cryptocurrency. The Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model were extended with the inclusion of trust and personnel innovativeness. The model was further validated by introducing a new path model compared to the original UTAUT2 model and the moderating role of personal innovativeness between performance expectancy and price value, with a sample of 314 respondents. Contrary to previous technology adoption studies that used PLS-SEM & ANN as single-stage analysis, this study further enhanced the analysis by applying a deep learning-based dual-stage PLS-SEM and ANN method. The application of deep learning-based dual-stage PLS-SEM & ANN analysis is a novel methodological approach, detecting both linear and non-linear associations among constructs. At the same time, it is regarded as a superior statistical approach as compared to traditional hybrid shallow SEM & ANN single-stage analysis. Also, sensitivity analysis provides normalised importance using multi-layer perceptron with the feed-forward-back-propagation algorithm. Furthermore, the deep learning-based dual-stage PLS-SEM & ANN revealed that trust proved to be the strongest predictor in driving user intention. The introduction of this new methodology and the theoretical contribution opens the vistas of the extant body of knowledge in technology-adoption related literature. This study also provides theoretical, practical and methodological contributions.

Suggested Citation

  • Ghazanfar Ali Abbasi & Lee Yin Tiew & Jinquan Tang & Yen-Nee Goh & Ramayah Thurasamy, 2021. "The adoption of cryptocurrency as a disruptive force: Deep learning-based dual stage structural equation modelling and artificial neural network analysis," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-26, March.
    • Handle: RePEc:plo:pone00:0247582
    DOI: 10.1371/journal.pone.0247582
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    2. Uikey, Ashish Ashok & Marak, Zericho R. & AlSaleh, Dhoha & Baber, Ruturaj, 2024. "Decoding intentions to purchase organic food products in an emerging economy via artificial neural networks," Agricultural and Resource Economics: International Scientific E-Journal, Agricultural and Resource Economics: International Scientific E-Journal, vol. 10(4), December.
    3. Drăgan, George Bogdan & Ben Arfi, Wissal & Tiberius, Victor & Ammari, Aymen & Khvatova, Tatiana, 2025. "Navigating the green wave: Understanding behavioral antecedents of sustainable cryptocurrency investment," Technological Forecasting and Social Change, Elsevier, vol. 210(C).
    4. Sudersan Behera & Sarat Chandra Nayak & A. V. S. Pavan Kumar, 2024. "Evaluating the Performance of Metaheuristic Based Artificial Neural Networks for Cryptocurrency Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 64(2), pages 1219-1258, August.
    5. Mohamed Bouteraa & Brahim Chekima & Nelson Lajuni & Ayesha Anwar, 2023. "Understanding Consumers’ Barriers to Using FinTech Services in the United Arab Emirates: Mixed-Methods Research Approach," Sustainability, MDPI, vol. 15(4), pages 1-22, February.
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    7. Messner, Wolfgang, 2024. "Exploring multilevel data with deep learning and XAI: The effect of personal-care advertising spending on subjective happiness," International Business Review, Elsevier, vol. 33(1).
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    10. Munish Gupta & Sanjay Taneja & Vikas Sharma & Amandeep Singh & Ramona Rupeika-Apoga & Kshitiz Jangir, 2023. "Does Previous Experience with the Unified Payments Interface (UPI) Affect the Usage of Central Bank Digital Currency (CBDC)?," JRFM, MDPI, vol. 16(6), pages 1-23, May.
    11. Hwang Kim, 2024. "An empirical analysis of navigation behaviors across stock and cryptocurrency trading platforms: implications for targeting and segmentation strategies," Electronic Commerce Research, Springer, vol. 24(3), pages 2113-2141, September.
    12. Chenlu Dang & Fan Wang & Zimo Yang & Hongxia Zhang & Yufeng Qian, 2022. "RETRACTED ARTICLE: Evaluating and forecasting the risks of small to medium-sized enterprises in the supply chain finance market using blockchain technology and deep learning model," Operations Management Research, Springer, vol. 15(3), pages 662-675, December.
    13. Basco, Rodrigo & Hair, Joseph F. & Ringle, Christian M. & Sarstedt, Marko, 2022. "Advancing family business research through modeling nonlinear relationships: Comparing PLS-SEM and multiple regression," Journal of Family Business Strategy, Elsevier, vol. 13(3).
    14. Mark P. Doblas & Jishanis Mae G. Becaro & Jayendira P. Sankar & Vinodh K. Natarajan & Yoganandham G. & Arumugasamy G., 2024. "Testing Integrative Models of the Change Behavior in the Intention to Adopt Cryptocurrency," SAGE Open, , vol. 14(2), pages 21582440241, May.
    15. Gudergan, Siegfried P. & Moisescu, Ovidiu I. & Radomir, Lăcrămioara & Ringle, Christian M. & Sarstedt, Marko, 2025. "Special issue editorial: Advanced partial least squares structural equation modeling (PLS-SEM) applications in business research," Journal of Business Research, Elsevier, vol. 188(C).
    16. Mohammad El Hajj & Imad Farran, 2024. "The Cryptocurrencies in Emerging Markets: Enhancing Financial Inclusion and Economic Empowerment," JRFM, MDPI, vol. 17(10), pages 1-27, October.
    17. Larbi-Siaw, Otu & Xuhua, Hu & Owusu, Ebenezer & Owusu-Agyeman, Abigail & Fulgence, Brou Ettien & Frimpong, Samuel Akwasi, 2022. "Eco-innovation, sustainable business performance and market turbulence moderation in emerging economies," Technology in Society, Elsevier, vol. 68(C).
    18. Chen, Xia & Miraz, Mahadi Hasan & Gazi, Md. Abu Issa & Rahaman, Md. Atikur & Habib, Md. Mamun & Hossain, Abu Ishaque, 2022. "Factors affecting cryptocurrency adoption in digital business transactions: The mediating role of customer satisfaction," Technology in Society, Elsevier, vol. 70(C).
    19. Kanellos Toudas & Démétrios Pafos & Paraskevi Boufounou & Athanasios Raptis, 2024. "Cryptocurrency, Gold, and Stock Exchange Market Performance Correlation: Empirical Evidence," FinTech, MDPI, vol. 3(2), pages 1-13, June.
    20. Zhengtang Fu & Peiwu Dong & Siyao Li & Yanbing Ju, 2021. "An intelligent cross-border transaction system based on consortium blockchain: A case study in Shenzhen, China," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-22, June.
    21. Ashish Ashok Uikey & Zericho Marak & Dhoha Alsaleh & Ruturaj Baber, 2024. "Decoding Intentions to Purchase Organic Food Products in an Emerging Economy via Artificial Neural Networks," Post-Print hal-04861233, HAL.
    22. Albahri, A.S. & Alnoor, Alhamzah & Zaidan, A.A. & Albahri, O.S. & Hameed, Hamsa & Zaidan, B.B. & Peh, S.S. & Zain, A.B. & Siraj, S.B. & Alamoodi, A.H. & Yass, A.A., 2021. "Based on the multi-assessment model: Towards a new context of combining the artificial neural network and structural equation modelling: A review," Chaos, Solitons & Fractals, Elsevier, vol. 153(P1).
    23. Ghazanfar Ali Abbasi & Noor Fareen Abdul Rahim & Hongyan Wu & Mohammad Iranmanesh & Benjamin Ng Chee Keong, 2022. "Determinants of SME’s Social Media Marketing Adoption: Competitive Industry as a Moderator," SAGE Open, , vol. 12(1), pages 21582440211, January.
    24. K. Kajol & Srijanani Devarakonda & Ranjit Singh & H. Kent Baker, 2025. "Drivers influencing the adoption of cryptocurrency: a social network analysis approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-25, December.

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