Machine Learning in Islamic Economics and Finance: A Comparative Bibliometric Analysis with The Conventional Field

Hasan Kazak; Boran Arik; Ahmet Tayfur Akcan

doi:10.31436/ijema.v33i2.1454

Authors

Hasan Kazak Necmettin Erbakan University, Turkey
Boran Arik Necmettin Erbakan University, Turkey
Ahmet Tayfur Akcan Necmettin Erbakan University, Turkey

DOI:

https://doi.org/10.31436/ijema.v33i2.1454

Keywords:

Bibliometric anaysis, Economy, Islamic finance, Islamic economy, Machine learning

Abstract

The aim of the study is to perform a bibliometric mapping analysis of machine learning research on Islamic economics and finance in the Web of Science (WOS) database. In the study, a bibliometric analysis was performed on all studies written on the topic of “Machine Learning” with WOS data and in the fields of “Economics” and “Finance” as well as “Islamic Economics” and “Islamic Finance.” The tool VOSviewer (1.6.18) was used to classify the data within the research framework. As a result of the analysis, authoritative authors, journals, institutions, and the most frequently referenced sources in the field were identified. Besides that, information about the country that has done the most work in the field was also expressed as a result of the VOSViewer (1.6.18) program. When evaluating the literature, no study was identified that includes both economic and financial concerns on machine learning and presents a comparative bibliometric mapping analysis by studying Islamic economics and Islamic finance issues. It is believed that this study will contribute to literature in this regard.

References

Ahmed, S., M.M. Alshater, A.E. Ammari, and H. Hammami, “Artificial Intelligence and Machine Learning in Finance: A Bibliometric Review.” Research in International Business and Finance 61, (2022): 101646.

Aslam, F., K.S. Mughal, A. Ali, and Y.T. Mohmand, “Forecasting Islamic Securities Index Using Artificial Neural Networks: Performance Evaluation of Technical Indicators.” Journal of Economic and Administrative Sciences 37, no. 2 (2020): 253–71.

Bijos, J.C.B.F., V.M. Zanta, J. Morató, L.M. Queiroz, and K.P.S.R. Oliveira-Esquerre. “Improving Circularity in Municipal Solid Waste Management Through Machine Learning in Latin America and the Caribbean.” Sustainable Chemistry and Pharmacy 28 (2022): 100740.

Bircan, T., A. Akda? Salah, and Q. Haodong, “A Bibliometric Analysis of Computational Social Science in Turkish Academia.” IEEE (2023): 1–4.

Brunton, S.L., J.L. Proctor, and N. Kutz, “Discovering Governing Equations from Data by Sparse Identification of Nonlinear Dynamical Systems.” PNAS 113, no. 15 (2016): 3932–937.

Cai, W.C., M.K. Linnenluecke, M. Marrone, and A.K. Singh, “Machine Learning and Expert Judgement: Analyzing Emerging Topics in Accounting and Finance Research in the Asia–Pacific.” Abacus 55, no. 4 (2019): 709-33.

Caraka, R.E., F.A. Hudaefi, P. Ugiana, T. Toharudin, A.E. Tyasti, N.E. Goldameir, and R.C. Chen, “Indonesian Islamic Moral Incentives in Credit Card Debt Repayment: A Feature Selection Using Various Data Mining.” International Journal of Islamic and Middle Eastern Finance and Management 15, no. 1 (2022): 100–24.

Carrasco-Garrido, C., C. De-Pablos-Heredero, and J.L. Rodríguez-Sánchez. “Exploring Hybrid Telework: A Bibliometric Analysis.” Heliyon 9, no. 12 (2023): e22472.

D’Amato, D., N. Droste, B. Allen, M. Kettunen, K. Lähtinen, J. Korhonen, P. Leskinen, B. Matthies, and A. Toppinen, “Green, Circular, Bio Economy: A Comparative Analysis of Sustainability Concepts.” Journal of Cleaner Production 168 (2017): 716-34.

Dwivedi, Y.K., L. Hughes, E. Ismagilova, G. Aarts, C. Coombs, T. Crick, Y. Duan et al. “Artificial Intelligence (AI): Multidisciplinary Perspectives on Emerging Challenges, Opportunities, and Agenda for Research, Practice and Policy.” International journal of information management 57 (2021): 101994.

ElKattan, A., D. Gavilan, M. Elsharnouby, and A. Mahran. “Mapping Sharing Economy Themes: Science Mapping, Topic Modeling, and Research Agenda.” Journal of Marketing Analytics (2023): 1–22.

Espina-Romero, L., and J. Guerrero Alcedo. “Fields Touched by Digitalization: Analysis of Scientific Activity in Scopus.” Sustainability 14 (2022): 14425.

Fischer, T., and C. Krauss, “Deep Learning with Long Short-Term Memory Networks for Financial Market Predictions.” European Journal of Operational Research 270, no. 2 (2018): 654–69.

François-Lavet, V., P. Henderson, R. Islam, M.G. Bellemare, and J. Pineau. “An Introduction to Deep Reinforcement Learning.” Foundations and Trends® in Machine Learning 11, no. 3–4 (2018): 219–354.

Gabrel, V., C. Murat, and A. Thiele, “Recent Advances in Robust Optimization: An Overview.” European Journal of Operational Research 235, no. 3 (2014): 471–83.

Ghasiya, P., and K. Okamura. “Understanding the Middle East through the Eyes of Japan’s Newspapers: A Topic Modelling and Sentiment Analysis Approach.” Digital Scholarship in the Humanities 36, no. 4 (2021): 871-85.

Ghlamallah, E., C. Alexakis, M. Dowling, and A. Piepenbrink. “The Topics of Islamic Economics and Finance Research.” International Review of Economics and Finance 75 (2021): 145–60.

Goodell, J., S. Kumar, W.M. Lim, and D. Pattnaik. “Artificial Intelligence and Machine Learning in Finance: Identifying Foundations, Themes, and Research Clusters from Bibliometric Analysis.” Journal of Behavioral and Experimental Finance 32 (2021): 100577.

Gundu, K., A. Jamwal, A. Yadav, R. Agrawal, J. Jain, and S. Kumar. “Circular Economy and Sustainable Manufacturing: A Bibliometric-Based Review” Recent Advances in Industrial Production (2022): 137-47.

Hakak, S., M. Alazab, S. Khan, T.R. Gadekallu, P.K.R. Maddikunta, and W.Z. Khan. “An Ensemble Machine Learning Approach Through Effective Feature Extraction to Classify Fake News.” Future Generation Computer Systems 117 (2021): 47–58.

Mnif, E., M.K. Hassan, A. Jarboui, and K. Mouakhar. “Big Data Tools for ISLAMIC Financial Analysis.” Intelligent Systems in Accounting Finance & Management 27, no. 1 (2020): 10-21.

He, H., W.S. Oetting, Brott, M.J., and S. Basu. “Power Of Multifactor Dimensionality Reduction and Penalized Logistic Regression for Detecting Gene-Gene Interaction in a Case-Control Study.” BMC Medical Genetics 10 (2009): 1-17.

Heberger, A.E., C.A. Christie, and M.C. Alkin. “A Bibliometric Analysis of the Academic Influences of and on Evaluation Theorists’ Published Works.” American Journal of Evaluation 31, no. 1 (2010): 24–44.

Hidalgo, C.A. “Economic Complexity Theory and Applications.” Nature Reviews Physics 3, no. 2 (2021): 92–113.

Hudaefi, F.A., M.K. Hassan, M. Abduh, and I.S. Beik. “Knowledge Discovery of Zakat Administration Worldwide from YouTube and Zoom Via Text Mining.” Journal of Islamic Accounting and Business Research 14, no. 1 (2022): 159–80.

Hussain, E., M. Hasan, M.A. Rahman, I. Lee, T. Tamanna, and M.Z. Parvez. “Corodet: A Deep Learning Based Classification for COVID-19 Detection Using Chest X-Ray Images.” Chaos, Solitons & Fractals 142 (2021): 1-12.

Jamwal, A., R. Agrawal, M. Sharma, G.S. Dangayach, and S. Gupta. “Application of Optimization Techniques in Metal Cutting Operations: A Bibliometric Analysis.” Materials Today: Proceedings 38 (2021): 365–70.

Kartiwi, M., T.S. Gunawan, T. Arundina, and M.A. Omar. “Feature Selection for Financial Data Classification: Islamic Finance Application.” 2018 IEEE 5th International Conference on Smart Instrumentation, Measurement and Application (ICSIMA) (2018): 1–4.

Khan, S., and M.R. Rabbani. “Artificial Intelligence and NLP -Based Chatbot for Islamic Banking and Finance.” International Journal of Information Retrieval Research (IJIRR) 11, no. 3 (2021): 65–77.

Kumar, S., D. Sharma, S. Rao, W.M. Lim, and S. Mangla. “Past, Present, And Future of Sustainable Finance: Insights from Big Data Analytics Through Machine Learning of Scholarly Research.” Annals of Operations Research 345 (2025): 1061-104.

Li, C., L. Bai, L. Yao, S.T. Waller, and W. Liu. “A Bibliometric Analysis and Review on Reinforcement Learning for Transportation Applications.” Transportmetrica B: Transport Dynamics 11, no. 1 (2023): 1-40.

Lundberg, S.M., G. Erion, H. Chen, A. DeGrave, J.M. Prutkin, B. Nair, R. Katz, J. Himmelfarb, N. Bansal, and S.-I. Lee. “From Local Explanations to Global Understanding with Explainable AI for Trees.” Nature Machine Intelligence 2, no. 1 (2020): 56–67.

Madzík, P., L. Falát, L. Copuš, and M. Valeri. “Digital Transformation in Tourism: Bibliometric Literature Review Based on Machine Learning Approach.” European Journal of Innovation Management 26, no. 7 (2023): 177–205.

Magazzino, C., A.S. Alola, and N. Schneider. “The Trilemma of Innovation, Logistics Performance, and Environmental Quality in 25 Topmost Logistics Countries: A Quantile Regression Evidence.” Journal of Cleaner Production 322 (2021): 129050.

Maria, M. R., R. Ballini, and R.F. Souza. “Evolution of Green Finance: A Bibliometric Analysis Through Complex Networks and Machine Learning.” Sustainability 15, no. 2 (2023): 1-27.

Muñoz, J., and R. Castañeda. “Use of Machine Learning in Volatility: A Review Using K-Means.” Revista Universidad y Empresa 25 (2023): 1–28.

Nazareth, N., and Y.V. Ramana Reddy. “Financial Applications of Machine Learning: A Literature Review.” Expert Systems with Applications 219, (2023): 119640.

Pattnaik, D., S. Kumar, B. Burton, and W.M. Lim. “Economic Modelling at Thirty-Five: A Retrospective Bibliometric Survey.” Economic Modelling 107 (2022):105712.

Polyzos, E., A. Samitas, and K. Syriopoulos. “Islamic Banking, Efficiency and Societal Welfare: A Machine-Learning, Agent-Based Study.” International Journal of Islamic and Middle Eastern Finance and Management 16, no. 4 (2022): 777–801.

Tabor, D.P., L.M. Roch, S.K. Saikin, C. Kreisbeck, D. Sheberla, J.H. Montoya, S. Dwaraknath et al. “Accelerating the Discovery of Materials for Clean Energy in the Era of Smart Automation.” Nature Reviews Materials 3, no. 5 (2018): 5-20.

Tlemsani, I., F. Marir, and M. Majdalawieh. “Screening of Murabaha Business Process Through Quran and Hadith: A Text Mining Analysis.” Journal of Islamic Accounting and Business Research 11, no. 9 (2020): 1889–905.

Touri, O., R. Ahroum, and B. Achchab. “Management and Monitoring of the Displaced Commercial Risk: A Prescriptive Approach.” International Journal of Emerging Markets 19, no. 6 (2024): 1748-765.

Waheed, A., M. Goyal, D. Gupta, A. Khanna, F. Al-Turjman, and P. Pinheiro. “CovidGAN: Data Augmentation Using Auxiliary Classifier GAN for Improved Covid-19 Detection.” IEEE Access 8 (2020): 91916-23.

Walas Mateo, F., and A. Redchuk. “IIoT/IoT and Artificial Intelligence/Machine Learning as a Process Optimization Driver under Industry 4.0 Model.” Journal of Computer Science and Technology 21 (2021): 170-76.

Wang, J., Y. Zhou, and F. Cooke. “Low-Carbon Economy and Policy Implications: A Systematic Review and Bibliometric Analysis.” Environmental Science and Pollution Research 29 (2022): 1–20.

Wang, Q., R. Huang, and R. Li. “Towards Smart Energy Systems: A Survey About the Impact of COVID-19 Pandemic on Renewable Energy Research.” Energy Strategy Reviews 41 (2022): 100845.

Xi, J., X. Liu, J. Wang, L. Yao, and C. Zhou. “A Systematic Review of COVID-19 Geographical Research: Machine Learning and Bibliometric Approach.” Annals of the American Association of Geographers 113, no. 3 (2023): 581–98.

Yesilyaprak, M., A. Polat, Ö. Özgür, and S. ?ahal. “The Profit Rate-Interest Rate Nexus Evidence from Machine Learning Algorithms.” Turkish Journal of Islamic Economics 10, no. 1 (2023): 137-61.

Zakaria, N., A. Sulaiman, F.S. Min, and A. Feizollah. “Machine Learning in the Financial Industry: A Bibliometric Approach to Evidencing Applications.” Cogent Social Sciences 9, no. 2 (2023): 2276609.