ANALYZING THE ROLE OF COMPUTER SCIENCE IN SHAPING MODERN ECONOMIC AND MANAGEMENT PRACTICES. BIBLIOMETRIC ANALYSIS

Eduardo Sánchez-García

eduardo.sanchez@ua.es
University of Alicante (Spain)

Javier Martínez-Falcó


University of Alicante (Spain)
https://orcid.org/0000-0001-9004-5816

Bartolomé Marco-Lajara


University of Alicante (Spain)
https://orcid.org/0000-0001-8811-9118

Jolanta Słoniec


Lublin University of Technology (Poland)
https://orcid.org/0000-0002-8869-5059

Abstract

The application of computer science in management and economics is a rapidly growing field that combines the analytical and technological capabilities of computer science with the strategic and operational needs of management and economics. The main aim of this research paper is to analyze the main academic contributors, sources, and international collaborations from 2014 to 2022 in computer science in the areas of management and economics, as well as to analyze the main subtopics developed over time. Bibliometric techniques were used to carry out the literature review, which allows an objective analysis of the academic literature through quantitative indicators. The results reveal a significant shift towards data-driven decision making in management, with artificial intelligence and machine learning improving predictive analytics, operational efficiency, and economic forecasting and modeling, highlighting the essential role of digital transformation in these disciplines, with significant implications for researchers, practitioners and decision-makers. It concludes that all stakeholders should work to develop a more informed and innovative approach to maximize the exploitation of the potential offered by computational sciences in different contexts. This includes the integration of advanced computational tools to improve decision making and operational efficiency, or the exploitation of computational models for more effective forecasting and policy decision making, as well as the continuous analysis of emerging areas in this field, being aware of the ethical, privacy and security challenges presented by these technologies, in order to ensure a responsible and equitable application.


Keywords:

computer science, computer applications, management, economics, new technologies

Abdurakhimovich, U. A. (2023). The Vital Role of Web Programming in the Digital Age. Journal of Science-Innovative Research in Uzbekistan, 1(6), 42-51. https://universalpublishings.com/index.php/jsiru/article/view/1933
  Google Scholar

Aggarwal, K., Mijwil, M. M., Al-Mistarehi, A. H., Alomari, S., Gök, M., Alaabdin, A. M. Z., & Abdulrhman, S. H. (2022). Has the future started? The current growth of artificial intelligence, machine learning, and deep learning. Iraqi Journal for Computer Science and Mathematics, 3(1), 115-123. http://dx.doi.org/10.52866/ijcsm.2022.01.01.013
  Google Scholar

Akter, S., McCarthy, G., Sajib, S., Michael, K., Dwivedi, Y. K., D’Ambra, J., & Shen, K. N. (2021). Algorithmic bias in data-driven innovation in the age of AI. International Journal of Information Management, 60, 102387. http://dx.doi.org/10.1016/j.ijinfomgt.2021.102387
  Google Scholar

Almeida, F., Santos, J. D., & Monteiro, J. A. (2020). The challenges and opportunities in the digitalization of companies in a post-COVID-19 World. IEEE Engineering Management Review, 48(3), 97-103. http://dx.doi.org/10.1109/emr.2020.3013206
  Google Scholar

Ardern, C. L., Büttner, F., Andrade, R., Weir, A., Ashe, M. C., Holden, S., ... & Winters, M. (2022). Implementing the 27 PRISMA 2020 Statement items for systematic reviews in the sport and exercise medicine, musculoskeletal rehabilitation and sports science fields: the PERSiST (implementing Prisma in Exercise, Rehabilitation, Sport medicine and SporTs science) guidance. British journal of sports medicine, 56(4), 175-195. http://dx.doi.org/10.1136/bjsports-2021-103987
  Google Scholar

Borgholthaus, C. J., White, J. V., & Harms, P. D. (2023). CEO dark personality: A critical review, bibliometric analysis, and research agenda. Personality and Individual Differences, 201, 111951. http://dx.doi.org/10.1016/j.paid.2022.111951
  Google Scholar

Boyadzhieva, Z., Nielsen, S. M., Buttgereit, F., Christensen, R., & Palmowski, A. (2023). Optimizing the reporting and conduct of systematic literature reviews and meta-analyses. Zeitschrift für Rheumatologie, 82(2), 175-176. http://dx.doi.org/10.1007/s00393-023-01329-2
  Google Scholar

Brauner, P., Dalibor, M., Jarke, M., Kunze, I., Koren, I., Lakemeyer, G., ... & Ziefle, M. (2022). A computer science perspective on digital transformation in production. ACM Transactions on Internet of Things, 3(2), 1-32. http://dx.doi.org/10.1145/3502265
  Google Scholar

Brem, A., Giones, F., & Werle, M. (2021). The AI digital revolution in innovation: A conceptual framework of artificial intelligence technologies for the management of innovation. IEEE Transactions on Engineering Management, 70(2), 770-776. http://dx.doi.org/10.1109/tem.2021.3109983
  Google Scholar

Carbonell-Alcocer, A., Romero-Luis, J., Gertrudix, M., & Wuebben, D. (2023). Datasets on the assessment of the scientific publication's corpora in circular economy and bioenergy approached from education and communication. Data in Brief, 47, 108958. http://dx.doi.org/10.1016/j.dib.2023.108958
  Google Scholar

Dima, A., Bugheanu, A. M., Boghian, R., & Madsen, D. Ø. (2022). Mapping Knowledge Area Analysis in E-Learning Systems Based on Cloud Computing. Electronics, 12(1), 62. http://dx.doi.org/10.3390/electronics12010062
  Google Scholar

Ellegaard, O., & Wallin, J. A. (2015). The bibliometric analysis of scholarly production: How great is the impact?. Scientometrics, 105, 1809-1831.
  Google Scholar

Ellis, L. A., Churruca, K., Clay-Williams, R., Pomare, C., Austin, E. E., Long, J. C., ... & Braithwaite, J. (2019). Patterns of resilience: a scoping review and bibliometric analysis of resilient health care. Safety Science, 118, 241-257. http://dx.doi.org/10.1007/s11192-015-1645-z
  Google Scholar

Ferguson-Cradler, G. (2023). Narrative and computational text analysis in business and economic history. Scandinavian Economic History Review, 71(2), 103-127. http://dx.doi.org/10.1080/03585522.2021.1984299
  Google Scholar

García-Lillo, F., Seva-Larrosa, P., & Sánchez-García, E. (2023). What is going on in entrepreneurship research? A bibliometric and SNA analysis. Journal of Business Research, 158, 113624. http://dx.doi.org/10.1016/j.jbusres.2022.113624
  Google Scholar

Gregory, R. W., Henfridsson, O., Kaganer, E., & Kyriakou, H. (2021). The role of artificial intelligence and data network effects for creating user value. Academy of management review, 46(3), 534-551. http://dx.doi.org/10.5465/amr.2019.0178
  Google Scholar

Gupta, M., Parvathy, Givi, J., Dey, M., Kent Baker, H., & Das, G. (2023). A bibliometric analysis on gift giving. Psychology & Marketing, 40(4), 629-642. http://dx.doi.org/10.1002/mar.21785
  Google Scholar

Innocenti, T., Feller, D., Giagio, S., Salvioli, S., Minnucci, S., Brindisino, F., ... & Ostelo, R. (2022). Adherence to the PRISMA statement and its association with risk of bias in systematic reviews published in rehabilitation journals: A meta-research study. Brazilian Journal of Physical Therapy, 100450. http://dx.doi.org/10.1016/j.bjpt.2022.100450
  Google Scholar

Kalamara, E., Turrell, A., Redl, C., Kapetanios, G., & Kapadia, S. (2022). Making text count: economic forecasting using newspaper text. Journal of Applied Econometrics, 37(5), 896-919. http://dx.doi.org/10.1002/jae.2907
  Google Scholar

Karimjanova, R. M., & Soliyeva, G. A. (2022). The Role and Importance of Marketing Research in the Modernization of the Economy of the Republic. European journal of innovation in nonformal education, 2(1), 220-224. https://inovatus.es/index.php/ejine/article/view/212
  Google Scholar

Katsamakas, E., & Sanchez-Cartas, J. M. (2023). A computational model of the competitive effects of ESG. Plos one, 18(7), e0284237. http://dx.doi.org/10.1371/journal.pone.0284237
  Google Scholar

Khan, W. Z., Rehman, M. H., Zangoti, H. M., Afzal, M. K., Armi, N., & Salah, K. (2020). Industrial internet of things: Recent advances, enabling technologies and open challenges. Computers & electrical engineering, 81, 106522. http://dx.doi.org/10.1016/j.compeleceng.2019.106522
  Google Scholar

Kuroki, M. (2023). Integrating data science into an econometrics course with a Kaggle competition. The Journal of Economic Education, 1-15. http://dx.doi.org/10.1080/00220485.2023.2220695
  Google Scholar

Lee, C. S., Cheang, P. Y. S., & Moslehpour, M. (2022). Predictive analytics in business analytics: decision tree. Advances in Decision Sciences, 26(1), 1-29. http://dx.doi.org/10.47654/v26y2022i1p1-29
  Google Scholar

Marco-Lajara, B., Martínez-Falcó, J., Sánchez-García, E., & Millan-Tudela, L. A. (2023a). Analyzing the Role of Renewable Energy in Meeting the Sustainable Development Goals: A Bibliometric Analysis. Energies, 16(7), 3137. http://dx.doi.org/10.3390/en16073137
  Google Scholar

Marco-Lajara, B., Martínez-Falcó, J., Millan-Tudela, L. A., & Sánchez-García, E. (2023b). Analysis of the structure of scientific knowledge on wine tourism: A bibliometric analysis. Heliyon, 9, e13363. http://dx.doi.org/10.1016/j.heliyon.2023.e13363
  Google Scholar

Martínez-Falcó, J., Marco-Lajara, B., Sánchez-García, E., & Visser, G. (2023a). Aligning the Sustainable Development Goals in the Wine Industry: A Bibliometric Analysis. Sustainability, 15(10), 8172. http://dx.doi.org/10.3390/su15108172
  Google Scholar

Martínez-Falcó, J., Marco-Lajara, B., Sánchez-García, E., & Millan-Tudela, L. A. (2023b). Happiness Management in the Corporate Domain: A Bibliometric Analysis. In New Perspectives and Possibilities in Strategic Management in the 21st Century: Between Tradition and Modernity (pp. 86-104). IGI Global. http://dx.doi.org/10.4018/978-1-6684-9261-1.ch005
  Google Scholar

Migliavacca, M., Patel, R., Paltrinieri, A., & Goodell, J. W. (2022). Mapping impact investing: A bibliometric analysis. Journal of International Financial Markets, Institutions and Money, 81, 101679. http://dx.doi.org/10.1016/j.intfin.2022.101679
  Google Scholar

Milosz, E., & Milosz, M. (2014). Small computer enterprise on competitive market–decision simulation game for business training of computer science specialist. In ICERI2014 Proceedings (pp. 1831-1838). IATED. https://library.iated.org/view/MILOSZ2014SMA
  Google Scholar

Milosz, M., & Lukasik, E. (2015, March). Reengineering of computer science curriculum according to technology changes and market needs. In 2015 IEEE Global Engineering Education Conference (EDUCON) (pp. 689-693). IEEE. http://dx.doi.org/10.1109/educon.2015.7096044
  Google Scholar

Miłosz, M., & Kozhanova, A. (2016). Building dynamic models of technical-economic systems using Causal Diagrams. In INTED2016 Proceedings (pp. 6152-6160). IATED. http://dx.doi.org/10.21125/inted.2016.0464
  Google Scholar

Monaghan, S., Tippmann, E., & Coviello, N. (2020). Born digitals: Thoughts on their internationalization and a research agenda. Journal of International Business Studies, 51, 11-22. http://dx.doi.org/10.1057/s41267-019-00290-0
  Google Scholar

Montalvo-Falcón, J. V., Sánchez-García, E., Marco-Lajara, B., & Martínez-Falcó, J. (2023). Sustainability Research in the Wine Industry: A Bibliometric Approach. Agronomy, 13(3), 871. http://dx.doi.org/10.3390/agronomy13030871
  Google Scholar

Nazer, L. H., Zatarah, R., Waldrip, S., Ke, J. X. C., Moukheiber, M., Khanna, A. K., ... & Mathur, P. (2023). Bias in artificial intelligence algorithms and recommendations for mitigation. PLOS Digital Health, 2(6), e0000278. http://dx.doi.org/10.1371/journal.pdig.0000278
  Google Scholar

Ni, L., Bausch, G., & Benjamin, R. (2023). Computer science teacher professional development and professional learning communities: A review of the research literature. Computer Science Education, 33(1), 29-60. http://dx.doi.org/10.1080/08993408.2021.1993666
  Google Scholar

Nojeem, L., Shun, M., Embouma, M., Inokon, A., & Browndi, I. (2023). Customer Relationship Management and Algebraic Multigrid: An Analysis of Integration and Performance. International Journal of Basic and Applied Sciences, 10(2023), 129-135.
  Google Scholar

Popescu, D. V., Dima, A., Radu, E., Dobrotă, E. M., & Dumitrache, V. M. (2022). Bibliometric analysis of the green deal policies in the food chain. Amfiteatru Economic, 24(60), 410-428. http://dx.doi.org/10.24818/ea/2022/60/410
  Google Scholar

Sadeeq, M. M., Abdulkareem, N. M., Zeebaree, S. R., Ahmed, D. M., Sami, A. S., & Zebari, R. R. (2021). IoT and Cloud computing issues, challenges and opportunities: A review. Qubahan Academic Journal, 1(2), 1-7. http://dx.doi.org/10.48161/qaj.v1n2a36
  Google Scholar

Sánchez-García, E., Martínez-Falcó, J., Marco-Lajara, B., & Millán-Tudela, L. A. (2023). Looking into literature in the field of circular supply chain and the subtopic from a customers’ perspective: A bibliometric approach. Journal of Cleaner Production, 417, 137900. http://dx.doi.org/10.1016/j.jclepro.2023.137900
  Google Scholar

Sarker, I. H. (2021). Data science and analytics: an overview from data-driven smart computing, decision-making and applications perspective. SN Computer Science, 2(5), 377. http://dx.doi.org/10.1007/s42979-021-00765-8
  Google Scholar

Sarker, I. H. (2022). Ai-based modeling: Techniques, applications and research issues towards automation, intelligent and smart systems. SN Computer Science, 3(2), 158. http://dx.doi.org/10.1007/s42979-022-01043-x
  Google Scholar

Schubert, V., Kuehner, S., Krauss, T., Trat, M., & Bender, J. (2023). Towards a B2B integration framework for smart services in Industry 4.0. Procedia Computer Science, 217, 1649-1659. http://dx.doi.org/10.1016/j.procs.2022.12.365
  Google Scholar

Sezgin, A., Orbay, K., & Orbay, M. (2022). Educational Research Review From Diverse Perspectives: A Bibliometric Analysis of Web of Science (2011–2020). SAGE Open, 12(4), 21582440221141628. http://dx.doi.org/10.1177/21582440221141628
  Google Scholar

Sharma, R., Shishodia, A., Gunasekaran, A., Min, H., & Munim, Z. H. (2022). The role of artificial intelligence in supply chain management: mapping the territory. International Journal of Production Research, 60(24), 7527-7550. http://dx.doi.org/10.1080/00207543.2022.2029611
  Google Scholar

Shin, D., & Park, Y. J. (2019). Role of fairness, accountability, and transparency in algorithmic affordance. Computers in Human Behavior, 98, 277-284. http://dx.doi.org/10.1016/j.chb.2019.04.019
  Google Scholar

Squazzoni, F., Polhill, J. G., Edmonds, B., Ahrweiler, P., Antosz, P., Scholz, G., ... & Gilbert, N. (2020). Computational models that matter during a global pandemic outbreak: A call to action. JASSS-The Journal of Artificial Societies and Social Simulation, 23(2), 10. http://dx.doi.org/10.18564/jasss.4298
  Google Scholar

Workentin, M., Castro Arteaga, M., Alamgir, A. K. M., & Kupka, C. F. (2022). PRISMA statement and Cochrane reviews: Striving to improve quality and validity of systematic reviews. Toronto, CA: Access Alliance. http://dx.doi.org/10.13140/RG.2.2.13610.29121
  Google Scholar

Yun, C., Shun, M., Jackson, K., Newiduom, L., & Browndi, I. (2023). Algebraic Multigrid and the Future of Computer Science. International Journal of Engineering and Applied Sciences, 11(2023), 167-172.
  Google Scholar

Zhao, C., Wu, M., Liu, J., Duan, Z., Shen, L., Shangguan, X., ... & Wang, Y. (2023a). Progress and Prospects of Data-Driven Stock Price Forecasting Research. International Journal of Cognitive Computing in Engineering. 4, 100-108. http://dx.doi.org/10.1016/j.ijcce.2023.03.001
  Google Scholar

Zhao, L., Yang, M. M., Wang, Z., & Michelson, G. (2023b). Trends in the dynamic evolution of corporate social responsibility and leadership: A literature review and bibliometric analysis. Journal of Business Ethics, 182(1), 135-157. http://dx.doi.org/10.1007/s10551-022-05035-y
  Google Scholar

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Published
2024-03-30

Cited by

Sánchez-García, E., Martínez-Falcó, J., Marco-Lajara, B., & Słoniec, J. (2024). ANALYZING THE ROLE OF COMPUTER SCIENCE IN SHAPING MODERN ECONOMIC AND MANAGEMENT PRACTICES. BIBLIOMETRIC ANALYSIS. Applied Computer Science, 20(1), 189–207. https://doi.org/10.35784/acs-2024-12

Authors

Eduardo Sánchez-García 
eduardo.sanchez@ua.es
University of Alicante Spain

Authors

Javier Martínez-Falcó 

University of Alicante Spain
https://orcid.org/0000-0001-9004-5816

Authors

Bartolomé Marco-Lajara 

University of Alicante Spain
https://orcid.org/0000-0001-8811-9118

Authors

Jolanta Słoniec 

Lublin University of Technology Poland
https://orcid.org/0000-0002-8869-5059

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