MAPPING THE GLOBAL RESEARCH LANDSCAPE OF CRYPTOCURRENCY PRICE: A BIBLIOMETRIC AND THEMATIC ANALYSIS

This study evaluates the evolution of cryptocurrency price research through a bibliometric network analysis and a thematic review of publications from 2014 to 2022. Three main themes are identified: cryptocurrency behavior, predictive modeling techniques, and factors influencing cryptocurrency prices. The findings reveal inconsistencies in the literature regarding predictive models and contributing factors, highlighting significant theoretical gaps. Future research directions are proposed, including the development of hybrid forecasting models that integrate machine learning, behavioral factors, and macro-financial indicators. This review offers valuable insights for scholars, investors, and policymakers aiming to enhance forecasting accuracy, manage risk, and better understand the complexities of the digital asset ecosystem.

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Publication Details

Journal
International Journal of Innovation and Industrial Revolution
Published
2025-09-18
DOI
https://doi.org/10.35631/ijirev.722031
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
0.00

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article

MAPPING THE GLOBAL RESEARCH LANDSCAPE OF CRYPTOCURRENCY PRICE: A BIBLIOMETRIC AND THEMATIC ANALYSIS

Mohd Tahir Ismail, Azlan Abdul Aziz, Amirah Hazwani Abdul Rahim, Nurul Hafizah Azizan et al.
International Journal of Innovation and Industrial Revolution
Blockchain Technology Applications and Security
article

MAPPING THE GLOBAL RESEARCH LANDSCAPE OF CRYPTOCURRENCY PRICE: A BIBLIOMETRIC AND THEMATIC ANALYSIS

Mohd Tahir Ismail, Azlan Abdul Aziz, Amirah Hazwani Abdul Rahim, Nurul Hafizah Azizan, Anis Mardiana Ahmad, Nurazlina Abdul Rashid
article en

Abstract

This study evaluates the evolution of cryptocurrency price research through a bibliometric network analysis and a thematic review of publications from 2014 to 2022. Three main themes are identified: cryptocurrency behavior, predictive modeling techniques, and factors influencing cryptocurrency prices. The findings reveal inconsistencies in the literature regarding predictive models and contributing factors, highlighting significant theoretical gaps. Future research directions are proposed, including the development of hybrid forecasting models that integrate machine learning, behavioral factors, and macro-financial indicators. This review offers valuable insights for scholars, investors, and policymakers aiming to enhance forecasting accuracy, manage risk, and better understand the complexities of the digital asset ecosystem.

International Journal of Innovation and Industrial RevolutionVol. 7(22)
Universiti Sains Malaysia (MY), Universiti Malaysia Kelantan (MY), Universiti Malaysia Perlis (MY), Universiti Teknologi MARA (MY)
Universiti Teknologi MARA
Openalex Percentile: Top 55%
Blockchain Technology Applications and Security
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