IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i16p12176-d1213601.html
   My bibliography  Save this article

Which Industrial Sectors Are Affected by Artificial Intelligence? A Bibliometric Analysis of Trends and Perspectives

Author

Listed:
  • Lorena Espina-Romero

    (Escuela de Postgrado, Universidad San Ignacio de Loyola, Lima 15024, Peru)

  • José Gregorio Noroño Sánchez

    (Facultad de Derecho, Universidad del Sinú “Elías Bechara Zainúm”, Monteria 230001, Colombia)

  • Humberto Gutiérrez Hurtado

    (Escuela de Postgrado, Universidad San Ignacio de Loyola, Lima 15024, Peru)

  • Helga Dworaczek Conde

    (Programa Maestría en Administración—MBA, Universidad Santo Tomás, Bogota 110231, Colombia)

  • Yessenia Solier Castro

    (Escuela de Posgrado, Universidad César Vallejo, Lima 15314, Peru)

  • Luz Emérita Cervera Cajo

    (Escuela de Posgrado, Universidad César Vallejo, Lima 15314, Peru)

  • Jose Rio Corredoira

    (Escuela de Negocios, Universidad Internacional SEK, Quito 170134, Ecuador)

Abstract

In recent times, artificial intelligence (AI) has been generating a significant impact in various industry sectors, which implies that companies must be ready to adjust to this promising start and progress in the direction of sustainability. The objective of this paper was to analyze the industrial sectors impacted by artificial intelligence during the period 2018–2022. The methodology consisted of applying a quantitative and bibliometric approach to a collection of 164 manuscripts indexed in Scopus with the help of statistical packages such as RStudio version 4.3.0, VOSviewer version 1.6.19, and Microsoft Excel 365. The results indicate that artificial intelligence is having a growing impact in sectors such as technology, finance, healthcare, the environment, and construction. Geographically, the most impacted sectors are in Europe and Asia, while the least impacted are in the Americas, Africa, and Oceania. It is proposed to conduct future research using AI in power quality (PQ), energy storage systems (ESSs) and hydrogen fuel cell (HFC) systems to contribute, firstly, in the transition to a more sustainable economy, followed by a decrease in dependence on fossil fuels. This research contributes to existing knowledge and paves the way for future exploration of qualitative aspects and emerging trends in the field of artificial intelligence influence in industrial sectors.

Suggested Citation

  • Lorena Espina-Romero & José Gregorio Noroño Sánchez & Humberto Gutiérrez Hurtado & Helga Dworaczek Conde & Yessenia Solier Castro & Luz Emérita Cervera Cajo & Jose Rio Corredoira, 2023. "Which Industrial Sectors Are Affected by Artificial Intelligence? A Bibliometric Analysis of Trends and Perspectives," Sustainability, MDPI, vol. 15(16), pages 1-18, August.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:16:p:12176-:d:1213601
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/16/12176/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/15/16/12176/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jose Ramon Saura & Ana Reyes-Menendez & Cesar Alvarez-Alonso, 2018. "Do Online Comments Affect Environmental Management? Identifying Factors Related to Environmental Management and Sustainability of Hotels," Sustainability, MDPI, vol. 10(9), pages 1-20, August.
    2. Aria, Massimo & Cuccurullo, Corrado, 2017. "bibliometrix: An R-tool for comprehensive science mapping analysis," Journal of Informetrics, Elsevier, vol. 11(4), pages 959-975.
    3. Moritz Jellenz & Vito Bobek & Tatjana Horvat, 2020. "Impact of Education on Sustainable Economic Development in Emerging Markets—The Case of Namibia’s Tertiary Education System and its Economy," Sustainability, MDPI, vol. 12(21), pages 1-26, October.
    4. Chloe Satinet & François Fouss, 2022. "A Supervised Machine Learning Classification Framework for Clothing Products’ Sustainability," Sustainability, MDPI, vol. 14(3), pages 1-26, January.
    5. Langley, David J. & van Doorn, Jenny & Ng, Irene C.L. & Stieglitz, Stefan & Lazovik, Alexander & Boonstra, Albert, 2021. "The Internet of Everything: Smart things and their impact on business models," Journal of Business Research, Elsevier, vol. 122(C), pages 853-863.
    6. Gianfranco Lombardo & Mattia Pellegrino & George Adosoglou & Stefano Cagnoni & Panos M. Pardalos & Agostino Poggi, 2022. "Machine Learning for Bankruptcy Prediction in the American Stock Market: Dataset and Benchmarks," Future Internet, MDPI, vol. 14(8), pages 1-23, August.
    7. Callan Harker & Maureen Hassall & Paul Lant & Nikodem Rybak & Paul Dargusch, 2022. "What Can Machine Learning Teach Us about Australian Climate Risk Disclosures?," Sustainability, MDPI, vol. 14(16), pages 1-22, August.
    8. Robert M. Chiles & Garrett Broad & Mark Gagnon & Nicole Negowetti & Leland Glenna & Megan A. M. Griffin & Lina Tami-Barrera & Siena Baker & Kelly Beck, 2021. "Democratizing ownership and participation in the 4th Industrial Revolution: challenges and opportunities in cellular agriculture," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 38(4), pages 943-961, December.
    9. Roman Baraniuk & Welf-Guntram Drossel, 2021. "Smart Modulation for Control Systems with High Regulation Capabilities for Cooling Systems Optimisation and Carbon Footprint Reduction in Industry," Energies, MDPI, vol. 14(24), pages 1-14, December.
    10. Hadjout, D. & Torres, J.F. & Troncoso, A. & Sebaa, A. & Martínez-Álvarez, F., 2022. "Electricity consumption forecasting based on ensemble deep learning with application to the Algerian market," Energy, Elsevier, vol. 243(C).
    11. Sarkar, Mainak & De Bruyn, Arnaud, 2021. "LSTM Response Models for Direct Marketing Analytics: Replacing Feature Engineering with Deep Learning," Journal of Interactive Marketing, Elsevier, vol. 53(C), pages 80-95.
    12. Sufyan Habib & Nawaf N. Hamadneh, 2021. "Impact of Perceived Risk on Consumers Technology Acceptance in Online Grocery Adoption amid COVID-19 Pandemic," Sustainability, MDPI, vol. 13(18), pages 1-16, September.
    13. Beata Gavurova & Sylvia Jencova & Radovan Bacik & Marta Miskufova & Stanislav Letkovsky, 2022. "Artificial intelligence in predicting the bankruptcy of non-financial corporations," Oeconomia Copernicana, Institute of Economic Research, vol. 13(4), pages 1215-1251, December.
    14. Liu, Liang & Yang, Kun & Fujii, Hidemichi & Liu, Jun, 2021. "Artificial intelligence and energy intensity in China’s industrial sector: Effect and transmission channel," Economic Analysis and Policy, Elsevier, vol. 70(C), pages 276-293.
    15. Mohamed Mohamed Khaleel & Mohd Rafi Adzman & Samila Mat Zali, 2021. "An Integrated of Hydrogen Fuel Cell to Distribution Network System: Challenging and Opportunity for D-STATCOM," Energies, MDPI, vol. 14(21), pages 1-26, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lorena Espina-Romero & Doile Ríos Parra & José Gregorio Noroño-Sánchez & Gloria Rojas-Cangahuala & Luz Emerita Cervera Cajo & Pedro Alfonso Velásquez-Tapullima, 2024. "Navigating Digital Transformation: Current Trends in Digital Competencies for Open Innovation in Organizations," Sustainability, MDPI, vol. 16(5), pages 1-19, March.
    2. Svetozar D. Jankovic & Dejan M. Curovic, 2023. "Strategic Integration of Artificial Intelligence for Sustainable Businesses: Implications for Data Management and Human User Engagement in the Digital Era," Sustainability, MDPI, vol. 15(21), pages 1-19, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wang, Xinxin & Xu, Zeshui & Qin, Yong & Skare, Marinko, 2021. "Service networks for sustainable business: A dynamic evolution analysis over half a century," Journal of Business Research, Elsevier, vol. 136(C), pages 543-557.
    2. Ruijie Zhu & Guojing Zhao & Zehai Long & Yangjie Huang & Zhaoxin Huang, 2022. "Entrepreneurship or Employment? A Survey of College Students’ Sustainable Entrepreneurial Intentions," Sustainability, MDPI, vol. 14(9), pages 1-15, May.
    3. Gessler, Michael & Bohlinger, Sandra & Zlatkin-Troitschanskaia, Olga, 2021. "International vocational education and training research: An introduction to the special issue," International Journal for Research in Vocational Education and Training (IJRVET), European Research Network in Vocational Education and Training (VETNET), European Educational Research Association, vol. 8(4), pages 1-15.
    4. Maria Lourdes Ordoñez Olivo & Zoltán Lakner, 2023. "Shaping the Knowledge Base of Bioeconomy Sectors Development in Latin American and Caribbean Countries: A Bibliometric Analysis," Sustainability, MDPI, vol. 15(6), pages 1-18, March.
    5. Lucy Semerjian & Kunle Okaiyeto & Mike O. Ojemaye & Temitope Cyrus Ekundayo & Aboi Igwaran & Anthony I. Okoh, 2021. "Global Systematic Mapping of Road Dust Research from 1906 to 2020: Research Gaps and Future Direction," Sustainability, MDPI, vol. 13(20), pages 1-21, October.
    6. Johnson Ankrah & Ana Monteiro & Helena Madureira, 2022. "Bibliometric Analysis of Data Sources and Tools for Shoreline Change Analysis and Detection," Sustainability, MDPI, vol. 14(9), pages 1-23, April.
    7. Juan F. Prados-Castillo & Miguel Ángel Solano-Sánchez & Pilar Guaita Fernández & José Manuel Guaita Martínez, 2023. "Potential of the Crypto Economy in Financial Management and Fundraising for Tourism," Sustainability, MDPI, vol. 15(6), pages 1-15, March.
    8. Vuong, Quan-Hoang & Huyen, Nguyen Thanh Thanh & Pham, Thanh-Hang & Phuong, Luong Anh & Nguyen, Minh-Hoang, 2020. "Mapping the intellectual and conceptual structure of research on gender issues in the family business: A bibliometric review," OSF Preprints jgnrw, Center for Open Science.
    9. Tong Chen & Mo Wang & Jin Su & Jianjun Li, 2023. "Unlocking the Positive Impact of Bio-Swales on Hydrology, Water Quality, and Biodiversity: A Bibliometric Review," Sustainability, MDPI, vol. 15(10), pages 1-19, May.
    10. Merve Anaç & Gulden Gumusburun Ayalp & Kamil Erdayandi, 2023. "Prefabricated Construction Risks: A Holistic Exploration through Advanced Bibliometric Tool and Content Analysis," Sustainability, MDPI, vol. 15(15), pages 1-31, August.
    11. Quan-Hoang Vuong & Huyen Thanh T. Nguyen & Thanh-Hang Pham & Manh-Toan Ho & Minh-Hoang Nguyen, 2021. "Assessing the ideological homogeneity in entrepreneurial finance research by highly cited publications," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-11, December.
    12. David N. Matzig & Clemens Schmid & Felix Riede, 2023. "Mapping the field of cultural evolutionary theory and methods in archaeology using bibliometric methods," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-17, December.
    13. Shuangqing Sheng & Wei Song & Hua Lian & Lei Ning, 2022. "Review of Urban Land Management Based on Bibliometrics," Land, MDPI, vol. 11(11), pages 1-25, November.
    14. Maksym Obrizan, 2018. "Economists in Ukraine: who are they and where do they publish?," Working Papers 3181, Research Consulting and Development.
    15. Hongxia Jin & Lu Lu & Haojun Fan, 2022. "Global Trends and Research Hotspots in Long COVID: A Bibliometric Analysis," IJERPH, MDPI, vol. 19(6), pages 1-14, March.
    16. Gour Gobinda Goswami & Tahmid Labib, 2022. "Modeling COVID-19 Transmission Dynamics: A Bibliometric Review," IJERPH, MDPI, vol. 19(21), pages 1-19, October.
    17. Das, Kallol & Patel, Jayesh D. & Sharma, Anuj & Shukla, Yupal, 2023. "Creativity in marketing: Examining the intellectual structure using scientometric analysis and topic modeling," Journal of Business Research, Elsevier, vol. 154(C).
    18. Chungil Chae & Jeong-Ha Yim & Jaeeun Lee & Sung Jun Jo & Jeong Rok Oh, 2020. "The Bibliometric Keywords Network Analysis of Human Resource Management Research Trends: The Case of Human Resource Management Journals in South Korea," Sustainability, MDPI, vol. 12(14), pages 1-37, July.
    19. Adriana AnaMaria Davidescu & Eduard Mihai Manta & Adina Teodora Stoica-Ungureanu & Magdalena Anton (Musat), 2022. "Could Religiosity and Religion Influence the Tax Morale of Individuals? An Empirical Analysis Based on Variable Selection Methods," Mathematics, MDPI, vol. 10(23), pages 1-32, November.
    20. Zoltán Lakner & Brigitta Plasek & Gyula Kasza & Anna Kiss & Sándor Soós & Ágoston Temesi, 2021. "Towards Understanding the Food Consumer Behavior–Food Safety–Sustainability Triangle: A Bibliometric Approach," Sustainability, MDPI, vol. 13(21), pages 1-23, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:16:p:12176-:d:1213601. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.