Forthcoming Articles

International Journal of Blockchains and Cryptocurrencies

International Journal of Blockchains and Cryptocurrencies (IJBC)

Forthcoming articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.

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International Journal of Blockchains and Cryptocurrencies (4 papers in press)

Regular Issues

  • Blockchain and AI-driven triple-entry accounting: transforming audit transparency in Saudi banks   Order a copy of this article
    by Rasha Fallatah 
    Abstract: This study assesses whether the use of blockchain technology for Triple Entry Accounting, combined with Machine Learning (ML), can enhance Auditability, Fraud Detection, and Transparency within the Saudi Banking Industry.The results of this study suggest improvements under simulated conditions in audit accuracy, fraud detection, data integrity, and audit cycle efficiency. These findings support emerging global trends in financial-audit innovations, and are consistent with objectives contained within Vision 2030 related to Digital Financial Governance. This paper provides simulation-based evidence supporting the development of a realistic audit simulation model and suggests the potential feasibility of blockchain-ML-based auditing systems in developing digital economies, subject to validation using real-world data.The research was conducted as a simulation-based experimental study using a synthetic dataset designed to represent banking transactions across five simulated Saudi banks. The study compares traditional double-entry accounting practices and periodic auditing procedures with a blockchain-enhanced triple-entry accounting framework integrated with machine learning-based anomaly detection.
    Keywords: blockchain; TEA; triple-entry accounting; machine learning; auditability; Saudi banks; continuous auditing; fraud detection; FinTech; Vision 2030.
    DOI: 10.1504/IJBC.2026.10078921
     
  • What drives consumers to purchase cryptocurrencies? An empirical investigation   Order a copy of this article
    by Rachna Jain, Shikha Sharma 
    Abstract: Cryptocurrencies emerged as a viable alternative to the conventional monetary system. It provides a technologically advanced, convenient, and decentralised mode of money that deals with high-risk, high-return investments. The objective of the study is to investigate consumer opinion within the framework of the TAM to examine the effects of perceived risk (PR), perceived ease of use (PE), and perceived trust (PT) factors on perceived benefits (PB), which drives the intention to buy cryptocurrencies. The PLS-SEM method analysed a cross-sectional quantitative sample. There is a significant association of PEU (b = 0.250, p = 0.001), PT (b = 0.427, p = 0.019), and PB (b = 0.158, p = 0.000) on the decision-making of consumers to buy cryptocurrencies. Policymakers/regulators design guidelines that protect investors by promoting ethical marketing practices and mitigating systemic risks. Digital platform developers ensure the privacy of financial/personal information, transparent fee disclosures, AI customer-assistance, accessibility and an interactive dashboard to build consumers’ trust.
    Keywords: cryptocurrency; ease of use; trust; risk; benefits; purchase intention; technology acceptance.
    DOI: 10.1504/IJBC.2026.10078929
     
  • Detecting and quantifying cryptocurrency pump-and-dump dynamics in noisy markets   Order a copy of this article
    by Mahya Karbalaii 
    Abstract: This study examines cryptocurrency pump-and-dump (P&D) detection in noisy, illiquid markets, focusing on Poloniex, where many trading pairs exhibit dormancy, sparse volume, and abrupt price-volume bursts. We develop a transparent, market-only, unsupervised framework combining price-volume thresholding, exponentially weighted moving averages (EWMA), and volatility adjusted filtering. The model is evaluated against manually collected Telegram confirmed P&D announcements. Because this ground truth is incomplete, evaluation is treated as a positive unlabelled setting: confirmed announcements are known positives, while unmatched model outputs remain unlabelled candidate signals rather than definitive false positives. Recall is therefore the primary criterion, with confirmation-based precision and F1 used only as auxiliary selectivity measures. The selected EWMA plus volatility-adjusted specification preserves recall close to the highest-recall alternative while improving selectivity. Its candidate signals are further examined using minute-level data to characterise accumulation, rapid activation, high-low divergence, and potential malicious actor profitability under conservative execution assumptions.
    Keywords: cryptocurrency; blockchain technology; market manipulation; pump and dump; anomaly detection; disinformation.
    DOI: 10.1504/IJBC.2026.10078989
     
  • The effect of dynamic capabilities on blockchain adoption and subsequent efficiency in the UAE financial services industry   Order a copy of this article
    by Rachid Moustaquim, Abdulla Al Derei 
    Abstract: The purpose of this study is to investigate how dynamic capabilities drive blockchain adoption and enhance operational efficiency in the UAE financial services industry. With a focus on dynamic capabilities theory (DCT), we have constructed and verified a conceptual model with 11 hypotheses that is tested using survey data from 274 financial professionals and analysed via Partial Least Squares Structural Equation Modelling. The results of this research indicate that leadership vision, business orientation, market knowledge, information technology capability, organisational learning, and organisational agility significantly strengthen sensing, seizing, and reconfiguring capabilities of financial institutions. These capabilities strongly support blockchain adoption, which in turn positively affects operational efficiency (β = 0.676). The model explains over 50% of the variance. This study advances the understanding of the relationships between dynamic capabilities, blockchain adoption, and efficiency, and provides new empirical evidence in the UAE to demonstrate how dynamic capabilities can enable efficiency gains through blockchain adoption.
    Keywords: DCT; dynamic capabilities theory; blockchain adoption; operational efficiency; SmartPLS; PLS-SEM; partial least squares structural equation modelling; financial services industry; banks; cross-border payments; financial institutions.
    DOI: 10.1504/IJBC.2026.10079087
     

 

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