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Yapay Zekânın Yönetim Alanında İncelenmesi: Bibliyometrik Bir Analiz

Year 2024, Volume: 5 Issue: 1, 1 - 17, 30.06.2024

Abstract

Yapay zekâ uygulamaları işletmelerde günden güne daha fazla yer almaktadır. Yönetim alanında yapay zekâ son yıllarda giderek artmaktadır. Bu araştırmanın amacı, yönetim alanında yapay zekânın uygulanması ve etkisini birbirine bağlı bir şekilde ele alan bilimsel literatürün bibliyometrik bir analizini yapmaktır. Analiz için “yönetimde yapay zekâ” konulu yayınlar Web of Science veri tabanından alınmıştır. Başlangıçta 156.287 yayın görülüp, dışlama ve dahil etme kriteri sonucunda 199 makale veri seti olarak kullanılmıştır. Bu kriterler 2023 yılı sonuna kadar yönetim alanında yapay zekâ konusunu inceleyen makaleleri oluşturmaktadır. Vosviewer programı ile ortak yazar analizi, ortak atıf analizi, anahtar kelime analizi, bibliyografik eşleşme analizleri yapılmıştır. Analiz bulguları ile araştırmacılar, bu alanda en çok atıf alan yazarları, en çok yayın yapan dergileri, ilişkili olan diğer kavram ve konuları görme imkanı bulabilecektir. Araştırmanın bu açıdan faydalı olabileceği düşünülmektedir. Analiz tarihi ve WoS taraması dikkate alınarak bu konuda Türkiye adresli bir yayın görüntülenmediği söylenebilir. Bu yüzden özellikle Türkiye’deki araştırmacılar açısından yönetim alanında yapay zekâ araştırmalarının yapılması alana özgün çalışmalar kazandırabilecektir. Analizlerin genel sonucu olarak ise, yapay zekanın yönetim alanındaki uygulamalarının büyümeye eğilimli ve gelişmekte olan bir çalışma alanı olduğu ifade edilebilir.

Ethical Statement

Bu makale araştırma ve yayın etiğine uygundur. Mevcut çalışma için mevzuat gereği etik izni alınmaya ihtiyaç yoktur

References

  • Artsın, M. (2020). Bir metin madenciliği uygulaması: Vosvıewer. Eskişehir Teknik Üniversitesi Bilim ve Teknoloji Dergisi B - Teorik Bilimler, 8(2), 344-354. https://dergipark.org.tr/en/pub/estubtdb/issue/56628/644637
  • Atabay, E., Çizel, B. & Ajanovic, E. (2019). Akıllı şehir araştırmalarının R programı ile bibliometrik analizi. O. Emir (Ed.), Akıllı şehirler, 20. Ulusal Turizm Kongresi, Anadolu Üniversitesi Basımevi, 3, 1130-1137.
  • Brynjolfsson, E., & McAfee, A. (2017). The business of artificial intelligence. Harvard Business Review, July issue. https://starlab-alliance.com/wp-content/uploads/2017/09/AI-Article.pdf
  • Cappelli, P., P. Tambe, & V. Yakubovich. (2019). Artificial Intelligence in human resources management: Challenges and a path forward. California Management Review, 61 (4), 15–42. https://doi.org/10.1177/0008125619867910
  • Coats, P. K. (1989). A banker’s use of simulation and artificial intelligence for assessing the economics of electronic money networks. European Journal of Operational Research, 41(3), 290–301. https://doi.org/10.1016/0377-2217(89)90250-6
  • Cummings, M. M. (2014). Man versus machine or man + machine? IEEE Intelligent Systems. 29(5), 62–69. https://doi.org/10.1109/MIS.2014.87
  • Elsbach, K. D., & Stigliani, I. (2019). New information technology and implicit bias. Academy of Management Perspectives, 33, 185–206. https://doi.org/10.5465/amp.2017.0079
  • Erer, B. (2023). Yönetim alanında duygusal zekâ: Bibliyometrik analiz. Uluslararası Yönetim Akademisi Dergisi, 6(3), 727-740. https://doi.org/10.33712/mana.1309409
  • Fethi, M. D., & Pasiouras, F. (2010). Assessing bank efficiency and performance with operational research and artificial intelligence techniques: A survey. European Journal of Operational Research. 204(2), 189–198. https://doi.org/10.1016/j.ejor.2009.08.003
  • Guerrin, F., (1991). Qualitative reasoning about an ecological process: İnterpretation in hydroecology. Ecological Modelling, 54(3-4), 165-201. https://doi.org/10.1016/0304-3800(91)90177-3
  • Hawkins, D. T. (2001). Bibliometrics of electronic journals in information science. Information Research, 7(1), 7-1. https://informationr.net/ir/7-1/paper120.html
  • Hırlak, B. (2024). Yönetim alanındaki whıstleblowıng araştırmalarının bibliyometrik analizi. R&S - Research Studies Anatolia Journal, 7(2), 154-185. https://doi.org/10.33723/rs.1451312
  • Ho, Y. S., & Wang, M. H. (2020). A bibliometric analysis of artificial intelligence publications from 1991 to 2018. COLLNET Journal of Scientometrics and Information Management, 14(2), 369–392. https://doi.org/10.1080/09737766.2021.1918032
  • Jain, A. S., & Meeran, S. (1999). Deterministic job-shop scheduling: Past, present and future. European Journal of Operational Research, 113(2), 390–434. https://doi.org/10.1016/S0377-2217(98)00113-1
  • Kearney, C., and T. Meynhardt. 2016. Directing corporate entrepreneurship strategy in the public sector to public value: Antecedents, components, and outcomes. International Public Management Journal 19 (4):543–72. https://doi.org/10.1080/10967494.2016.1160013.
  • Kessler, M. M. (1963). Bibliographic coupling between scientific papers. American Documentation, 14(1), 10–25. https://doi.org/10.1002/asi.5090140103
  • Kong, H., Y. Yuan, Y. Baruch, N. Bu, X. Jiang, & K. Wang. 2021. Influences of artificial intelligence (AI) awareness on career competency and job burnout. International Journal of Contemporary Hospitality Management, 33 (2), 717–34. https://doi.org/10.1108/IJCHM-07-2020-0789
  • Kurnaz, A. (2021). Etnosentrizm ile ilgili çalışmaların bibliyometrik analizi. Beykoz Akademi Dergisi, 9(2), 98-118. https://doi.org/10.14514/BYK.m.26515393.2021.9/2.98-118
  • Levinthal, D. A., & March, J. G. (1993). The myopia of learning. Strategic Management Journal, 14, 95–112. https://doi.org/10.1002/smj.4250141009
  • Lindley, M.R., Shoolery, J.N., Smith, D.H. & Djerassi (1983), C. Applications of artificial-intelli¬gence for chemical inference. 43. Application of the computer-program genoa and two-dimensional NMR-spectroscopy to structure elucidation. Organic Magnetic Resonance, 21, 405-411. https://doi.org/10.1080/09737766.2021.1918032
  • Llanos-Herrera, G.R. & Merigo, J.M. (2019). Overview of brand personality research with bibliometric indicators. Kybernetes, 48 (3), 546-569. https://doi.org/10.1108/K-02-2018-0051
  • Merigo, J.M., Cancino, C.A., Coronado, F. & Urbano, D. (2016). Academic research in innovation: Acountry analysis, Scientometrics, 108(2), 559-593. https://doi.org/10.1007/s11192-016-1984-4
  • Merigo, J.M., Mas-Tur, A., Roig-Tierno, N. & Ribeiro-Soriano, D. (2015). A bibliometric overview of the journal of business research between 1973 and 2014. Journal of Business Research, 68 (12), 2645-2653. https://doi.org/10.1016/j.jbusres.2015.04.006
  • Michailidis, M. P. 2018. The challenges of AI and blockchain on HR recruiting practices. Cyprus Review 30 (2):169–80. https://www.researchgate.net/publication/332697930_The_challenges_of_AI_and_blockchain_on_HR_recruiting_practices
  • Mitchell, T., & E. Brynjolfsson. (2017). Track how technology is transforming work. Nature 544 (7650), 290–92. https://doi.org/10.1038/544290
  • Nankervis, A., J. Connell, R. Cameron, A. Montague, & V. Prikshat. 2021. ‘Are we there yet?’ Australian HR professionals and the fourth industrial revolution. Asia Pacific Journal of Human Resources 59 (1), 3–19. https://doi.org/10.1111/1744-7941.12245
  • Nedelkoska, L., & G. Quintini. (2018). Automation, Skills Use and Training. Paris: OECD. https://doi.org/10.1787/1815199X
  • Nilsson, N. J. (1971). Problem-solving methods in. Artificial Intelligence, 5. https://cse.buffalo.edu/~rapaport/572/S02/nilsson.8puzzle.pdf
  • Paesano, A. (2021). Artificial intelligence and creative activities inside organizational behavior. International Journal of Organizational Analysis. https://www.emerald.com/insight/content/doi/10.1108/IJOA-09-2020-2421/full/html
  • Palos-Sánchez, P. R., Baena-Luna, P., Badicu, A., & Infante-Moro, J. C. (2022). Artificial ıntelligence and human resources management: A bibliometric analysis. Applied Artificial Intelligence, 36(1). https://doi.org/10.1080/08839514.2022.2145631
  • Pan, Y., F. Froese, N. Liu, Y. Hu, & M. Ye. (2022). The adoption of artificial intelligence in employee recruitment: The influence of contextual factors. International Journal of Human Resource Management 33 (6), 1125–47. https://doi.org/10.1080/09585192.2021.1879206
  • Perianes-Rodriguez, A., Waltman, L. & Van Eck, N.J. (2016). Constructing bibliometric networks: a comparison between full and fractional counting. Journal of Informetrics, 10 (4), 1178-1195. https://doi.org/10.1016/j.joi.2016.10.006
  • Pritchard, A. (1969). Statistical bibliography or bibliometrics? Journal of Documentation, 25(4), 348. https://cir.nii.ac.jp/crid/1570009750342049664
  • Raisch, S., & Krakowski, S. (2020). Artificial Intelligence and Management: The Automation-Augmentation Paradox. Academy of Management Review. https://doi.org/10.5465/2018.0072
  • Rykun, E. (2019). Artificial intelligence in HR management– what can we expect? The Boss Magazine. https://thebossmagazine.com/ai-hr-management/
  • Shah, S.H.H., Lei, S., Ali, M., Doronin, D. & Hussain, S.T. (2020). Prosumption: Bibliometric analysis using HistCite and VOSviewer. Kybernetes, 49(3), 1020-1045. https://doi.org/10.1108/K-12-2018-0696
  • Toprak, M., Özel, D., & Çalışkan, S. (2022). Yapay zeka kullanımı ve insan kaynakları yönetimi. Uluslararası Eşitlik Politikası Dergisi, 2(2), 76-103. https://dergipark.org.tr/tr/pub/uepd/issue/74154/1224044
  • Van Eck, N.J. & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84 (2), 523-538. https://doi.org/10.1007/s11192-009-0146-3.
  • Van Eck, N.J. & Waltman, L. (2018). VOSviewer Manual, Universitteit Leiden. https://doi.org/10.3402/jac.v8.30072
  • Varma, A., C. Dawkins, & K. Chaudhuri. (2022). Artificial intelligence and people management: A critical assessment through the ethical lens. Human Resource Management Review. https://doi.org/10.1016/j.hrmr.2022. 100923
  • Vošner, H.B., Kokol, P., Bobek, S., Železnik, D. & Završnik, J. (2016). A bibliometric retrospective of the journal computers in human behavior (1991-2015). Computers in Human Behavior, 65, 46-58. https://doi.org/10.1016/j.chb.2016.08.026
  • Vrontis, D., M. Christofi, V. Pereira, S. Tarba, A. Makrides, & E. Trichina. (2022). Artificial intelligence, robotics, advanced technologies and human resource management: A systematic review. International Journal of Human Resource Management, 33(6), 1237–66. https://doi.org/10.1080/09585192.2020.1871398

Review of Artificial Intelligence in the Field of Management: A Bibliometric Analysis

Year 2024, Volume: 5 Issue: 1, 1 - 17, 30.06.2024

Abstract

Applications of artificial intelligence are increasingly prevalent in businesses. In the field of management, the utilisation of artificial intelligence has significantly grown in recent years. This research aims to conduct a bibliometric analysis of the scientific literature that examines the application and impact of artificial intelligence in management in an interconnected manner. Publications on the topic of "artificial intelligence in management" were sourced from the Web of Science database for analysis. Initially, 156,287 publications were identified, and after applying exclusion and inclusion criteria, a dataset of 199 articles was used. These criteria encompassed articles that examined the subject of artificial intelligence in the field of management up to the end of 2023. Using the Vosviewer software, analyses such as co-author analysis, co-citation analysis, keyword analysis, and bibliographic coupling analysis were conducted. The findings of the analysis will enable researchers to identify the most cited authors, the journals with the highest number of publications, and other related concepts and topics in this field. The research is considered to be beneficial in this regard. Considering the analysis date and WoS scanning, it can be said that there is no publication addressing Türkiye on this subject. Therefore, especially for researchers in Turkey, conducting artificial intelligence research in the field of management can provide original studies to the field. As a general result of the analyses, it can be stated that the applications of artificial intelligence in the field of management represent a growing and developing area of study.

Ethical Statement

This paper complies with research and publication ethics. There is no need to obtain ethics permission for the current study, as required by the legislation.

References

  • Artsın, M. (2020). Bir metin madenciliği uygulaması: Vosvıewer. Eskişehir Teknik Üniversitesi Bilim ve Teknoloji Dergisi B - Teorik Bilimler, 8(2), 344-354. https://dergipark.org.tr/en/pub/estubtdb/issue/56628/644637
  • Atabay, E., Çizel, B. & Ajanovic, E. (2019). Akıllı şehir araştırmalarının R programı ile bibliometrik analizi. O. Emir (Ed.), Akıllı şehirler, 20. Ulusal Turizm Kongresi, Anadolu Üniversitesi Basımevi, 3, 1130-1137.
  • Brynjolfsson, E., & McAfee, A. (2017). The business of artificial intelligence. Harvard Business Review, July issue. https://starlab-alliance.com/wp-content/uploads/2017/09/AI-Article.pdf
  • Cappelli, P., P. Tambe, & V. Yakubovich. (2019). Artificial Intelligence in human resources management: Challenges and a path forward. California Management Review, 61 (4), 15–42. https://doi.org/10.1177/0008125619867910
  • Coats, P. K. (1989). A banker’s use of simulation and artificial intelligence for assessing the economics of electronic money networks. European Journal of Operational Research, 41(3), 290–301. https://doi.org/10.1016/0377-2217(89)90250-6
  • Cummings, M. M. (2014). Man versus machine or man + machine? IEEE Intelligent Systems. 29(5), 62–69. https://doi.org/10.1109/MIS.2014.87
  • Elsbach, K. D., & Stigliani, I. (2019). New information technology and implicit bias. Academy of Management Perspectives, 33, 185–206. https://doi.org/10.5465/amp.2017.0079
  • Erer, B. (2023). Yönetim alanında duygusal zekâ: Bibliyometrik analiz. Uluslararası Yönetim Akademisi Dergisi, 6(3), 727-740. https://doi.org/10.33712/mana.1309409
  • Fethi, M. D., & Pasiouras, F. (2010). Assessing bank efficiency and performance with operational research and artificial intelligence techniques: A survey. European Journal of Operational Research. 204(2), 189–198. https://doi.org/10.1016/j.ejor.2009.08.003
  • Guerrin, F., (1991). Qualitative reasoning about an ecological process: İnterpretation in hydroecology. Ecological Modelling, 54(3-4), 165-201. https://doi.org/10.1016/0304-3800(91)90177-3
  • Hawkins, D. T. (2001). Bibliometrics of electronic journals in information science. Information Research, 7(1), 7-1. https://informationr.net/ir/7-1/paper120.html
  • Hırlak, B. (2024). Yönetim alanındaki whıstleblowıng araştırmalarının bibliyometrik analizi. R&S - Research Studies Anatolia Journal, 7(2), 154-185. https://doi.org/10.33723/rs.1451312
  • Ho, Y. S., & Wang, M. H. (2020). A bibliometric analysis of artificial intelligence publications from 1991 to 2018. COLLNET Journal of Scientometrics and Information Management, 14(2), 369–392. https://doi.org/10.1080/09737766.2021.1918032
  • Jain, A. S., & Meeran, S. (1999). Deterministic job-shop scheduling: Past, present and future. European Journal of Operational Research, 113(2), 390–434. https://doi.org/10.1016/S0377-2217(98)00113-1
  • Kearney, C., and T. Meynhardt. 2016. Directing corporate entrepreneurship strategy in the public sector to public value: Antecedents, components, and outcomes. International Public Management Journal 19 (4):543–72. https://doi.org/10.1080/10967494.2016.1160013.
  • Kessler, M. M. (1963). Bibliographic coupling between scientific papers. American Documentation, 14(1), 10–25. https://doi.org/10.1002/asi.5090140103
  • Kong, H., Y. Yuan, Y. Baruch, N. Bu, X. Jiang, & K. Wang. 2021. Influences of artificial intelligence (AI) awareness on career competency and job burnout. International Journal of Contemporary Hospitality Management, 33 (2), 717–34. https://doi.org/10.1108/IJCHM-07-2020-0789
  • Kurnaz, A. (2021). Etnosentrizm ile ilgili çalışmaların bibliyometrik analizi. Beykoz Akademi Dergisi, 9(2), 98-118. https://doi.org/10.14514/BYK.m.26515393.2021.9/2.98-118
  • Levinthal, D. A., & March, J. G. (1993). The myopia of learning. Strategic Management Journal, 14, 95–112. https://doi.org/10.1002/smj.4250141009
  • Lindley, M.R., Shoolery, J.N., Smith, D.H. & Djerassi (1983), C. Applications of artificial-intelli¬gence for chemical inference. 43. Application of the computer-program genoa and two-dimensional NMR-spectroscopy to structure elucidation. Organic Magnetic Resonance, 21, 405-411. https://doi.org/10.1080/09737766.2021.1918032
  • Llanos-Herrera, G.R. & Merigo, J.M. (2019). Overview of brand personality research with bibliometric indicators. Kybernetes, 48 (3), 546-569. https://doi.org/10.1108/K-02-2018-0051
  • Merigo, J.M., Cancino, C.A., Coronado, F. & Urbano, D. (2016). Academic research in innovation: Acountry analysis, Scientometrics, 108(2), 559-593. https://doi.org/10.1007/s11192-016-1984-4
  • Merigo, J.M., Mas-Tur, A., Roig-Tierno, N. & Ribeiro-Soriano, D. (2015). A bibliometric overview of the journal of business research between 1973 and 2014. Journal of Business Research, 68 (12), 2645-2653. https://doi.org/10.1016/j.jbusres.2015.04.006
  • Michailidis, M. P. 2018. The challenges of AI and blockchain on HR recruiting practices. Cyprus Review 30 (2):169–80. https://www.researchgate.net/publication/332697930_The_challenges_of_AI_and_blockchain_on_HR_recruiting_practices
  • Mitchell, T., & E. Brynjolfsson. (2017). Track how technology is transforming work. Nature 544 (7650), 290–92. https://doi.org/10.1038/544290
  • Nankervis, A., J. Connell, R. Cameron, A. Montague, & V. Prikshat. 2021. ‘Are we there yet?’ Australian HR professionals and the fourth industrial revolution. Asia Pacific Journal of Human Resources 59 (1), 3–19. https://doi.org/10.1111/1744-7941.12245
  • Nedelkoska, L., & G. Quintini. (2018). Automation, Skills Use and Training. Paris: OECD. https://doi.org/10.1787/1815199X
  • Nilsson, N. J. (1971). Problem-solving methods in. Artificial Intelligence, 5. https://cse.buffalo.edu/~rapaport/572/S02/nilsson.8puzzle.pdf
  • Paesano, A. (2021). Artificial intelligence and creative activities inside organizational behavior. International Journal of Organizational Analysis. https://www.emerald.com/insight/content/doi/10.1108/IJOA-09-2020-2421/full/html
  • Palos-Sánchez, P. R., Baena-Luna, P., Badicu, A., & Infante-Moro, J. C. (2022). Artificial ıntelligence and human resources management: A bibliometric analysis. Applied Artificial Intelligence, 36(1). https://doi.org/10.1080/08839514.2022.2145631
  • Pan, Y., F. Froese, N. Liu, Y. Hu, & M. Ye. (2022). The adoption of artificial intelligence in employee recruitment: The influence of contextual factors. International Journal of Human Resource Management 33 (6), 1125–47. https://doi.org/10.1080/09585192.2021.1879206
  • Perianes-Rodriguez, A., Waltman, L. & Van Eck, N.J. (2016). Constructing bibliometric networks: a comparison between full and fractional counting. Journal of Informetrics, 10 (4), 1178-1195. https://doi.org/10.1016/j.joi.2016.10.006
  • Pritchard, A. (1969). Statistical bibliography or bibliometrics? Journal of Documentation, 25(4), 348. https://cir.nii.ac.jp/crid/1570009750342049664
  • Raisch, S., & Krakowski, S. (2020). Artificial Intelligence and Management: The Automation-Augmentation Paradox. Academy of Management Review. https://doi.org/10.5465/2018.0072
  • Rykun, E. (2019). Artificial intelligence in HR management– what can we expect? The Boss Magazine. https://thebossmagazine.com/ai-hr-management/
  • Shah, S.H.H., Lei, S., Ali, M., Doronin, D. & Hussain, S.T. (2020). Prosumption: Bibliometric analysis using HistCite and VOSviewer. Kybernetes, 49(3), 1020-1045. https://doi.org/10.1108/K-12-2018-0696
  • Toprak, M., Özel, D., & Çalışkan, S. (2022). Yapay zeka kullanımı ve insan kaynakları yönetimi. Uluslararası Eşitlik Politikası Dergisi, 2(2), 76-103. https://dergipark.org.tr/tr/pub/uepd/issue/74154/1224044
  • Van Eck, N.J. & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84 (2), 523-538. https://doi.org/10.1007/s11192-009-0146-3.
  • Van Eck, N.J. & Waltman, L. (2018). VOSviewer Manual, Universitteit Leiden. https://doi.org/10.3402/jac.v8.30072
  • Varma, A., C. Dawkins, & K. Chaudhuri. (2022). Artificial intelligence and people management: A critical assessment through the ethical lens. Human Resource Management Review. https://doi.org/10.1016/j.hrmr.2022. 100923
  • Vošner, H.B., Kokol, P., Bobek, S., Železnik, D. & Završnik, J. (2016). A bibliometric retrospective of the journal computers in human behavior (1991-2015). Computers in Human Behavior, 65, 46-58. https://doi.org/10.1016/j.chb.2016.08.026
  • Vrontis, D., M. Christofi, V. Pereira, S. Tarba, A. Makrides, & E. Trichina. (2022). Artificial intelligence, robotics, advanced technologies and human resource management: A systematic review. International Journal of Human Resource Management, 33(6), 1237–66. https://doi.org/10.1080/09585192.2020.1871398
There are 42 citations in total.

Details

Primary Language Turkish
Subjects Technology Management
Journal Section Research Articles
Authors

Tuba Bıyıkbeyi 0000-0003-1770-7304

Publication Date June 30, 2024
Submission Date May 30, 2024
Acceptance Date June 29, 2024
Published in Issue Year 2024 Volume: 5 Issue: 1

Cite

APA Bıyıkbeyi, T. (2024). Yapay Zekânın Yönetim Alanında İncelenmesi: Bibliyometrik Bir Analiz. TOGU Career Research Journal, 5(1), 1-17.