Evolution of Management Information Systems by Super Artificial Intelligence Revolutions

Öz

This study explores the impact of the super artificial intelligence (AI) revolution on the evolution of Management Information Systems (MIS) discipline. As AI departments are being set rapidly in all universities worldwide, recognizing that the super AI revolution has significantly transformed the MIS field, this study aims to propose a function formula to model the intricate dynamics between MIS and other related disciplines, such as business analytics, computer science, management science, software engineering, and artificial intelligence. The proposed formula will capture how the super AI revolution introduces new challenges and opportunities, influences the convergence and divergence of related fields, and affects the MIS discipline. Additionally, the study identifies key concerns and technical issues associated with super AI, offering potential mitigation strategies to address these challenges. By emphasizing the importance of interdisciplinary collaboration and the necessity for acquiring specialized skills, this study underscores the need for professionals to effectively navigate the evolving landscape shaped by the super AI revolution.

Anahtar Kelimeler

• Management Information Systems
• Super AI
• Artificial Intelligence
• Convergence
• Divergence.

Süper Yapay Zeka Devrimleriyle Yönetim Bilişim Sistemlerinin Evrimi

Öz

Bu çalışma, süper yapay zeka (YZ) devriminin Yönetim Bilişim Sistemleri (YBS) disiplini üzerindeki etkisini incelemektedir. Üniversitelerde hızla YZ bölümleri kurulurken, süper YZ devriminin YBS alanını önemli ölçüde dönüştürdüğü kabul edilmektedir. Bu çalışma, YBS ile iş analitiği, bilgisayar bilimi, yönetim bilimi, yazılım mühendisliği ve yapay zeka gibi diğer ilgili disiplinler arasındaki karmaşık dinamikleri modellemek için bir fonksiyon formülü önermeyi amaçlamaktadır. Önerilen formül, süper YZ devriminin yeni zorluklar ve fırsatlar nasıl tanıttığını, ilgili alanların yakınsama ve uzaklaşmasını nasıl etkilediğini ve YBS disiplinini nasıl etkilediğini yakalayacaktır. Ayrıca, çalışma, süper YZ ile ilişkili temel endişeleri ve teknik sorunları belirleyerek bu zorlukları ele almak için potansiyel hafifletme stratejileri sunmaktadır. Disiplinler arası işbirliğinin önemi ve uzmanlaşmış becerilerin edinilmesi gerekliliği vurgulanarak, bu çalışma, profesyonellerin süper YZ devrimiyle şekillenen evrimsel manzarada etkin bir şekilde gezinmelerine duyulan ihtiyacı vurgulamaktadır.

Anahtar Kelimeler

• : Yönetim Bilişim Sistemleri
• Süper YZ
• Yapay Zeka
• Yakınsama
• Uzaklaşma.

Kaynakça

1. Abbas, A., Babar, M. A., & Farooq, S. (2021). Industrial engineering and management information systems: A comprehensive review. International Journal of Industrial Engineering Computations, 12(4), 661-672.
2. Agrawal, A., Gans, J. S., & Goldfarb, A. (2018). Prediction machines: The simple economics of artificial intelligence. Harvard Business Press.
3. Alavi, M., & Leidner, D. E. (2001). Knowledge management and knowledge management systems: Conceptual foundations and research issues. MIS Quarterly, 25(1), 107-136.
4. Arntz, M., Gregory, T., & Zierahn, U. (2016). The risk of automation for jobs in OECD countries: A comparative analysis. OECD Social, Employment, and Migration Working Papers, No. 189. https://doi.org/10.1787/5jlz9h56dvq7-en
5. Arun, S. (2021). AI and MIS: How artificial intelligence is impacting the world of management information systems. International Journal of Scientific and Research Publications, 11(5), 324-329.
6. Aydemir, E., & Yavuz, M. (2019). Mevsimlere göre ilaç satış verilerinin birliktelik analizi ile incelenmesi. Uluslararası Yönetim Bilişim Sistemleri ve Bilgisayar Bilimleri Dergisi, 3(1), 23-30.
7. Bandyopadhyay, G., & Chakraborty, S. (2018). A review on the integration of industrial engineering and management information systems. International Journal of Industrial Engineering Computations, 9(3), 457-474. https://doi.org/10.5267/j.ijiec.2017.12.002
8. Bharadwaj, A., El Sawy, O. A., Pavlou, P. A., & Venkatraman, N. (2013). Digital business strategy: Toward a next generation of insights. MIS Quarterly, 37(2), 471-482.

9. Bhat, A. (2021). Impact of artificial intelligence on software engineering. Journal of Software Engineering Research and Development, 9(1), 2. https://doi.org/10.5753/jserd.2021.431
10. Bostrom, N. (2014). Superintelligence: Paths, dangers, strategies. Oxford University Press.
11. Bragg, M. (2021). Closing the skills gap in the age of digital transformation. Journal of Information Systems Education, 32(1), 3-5.
12. Brynjolfsson, E., & McAfee, A. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. W. W. Norton & Company.
13. Bryson, J. J. (2020). Artificial intelligence and pro-social behaviour. AI & Society, 35(1), 173-181. https://doi.org/10.1007/s00146-018-0849-6
14. Buczak, A. L., & Guven, E. (2016). A survey of data mining and machine learning methods for cybersecurity. IEEE Access, 4, 1823-1834. https://doi.org/10.1109/ACCESS.2016.2557302
15. Cavelty, M. D., & Mauer, V. (Eds.). (2018). Routledge handbook of security studies. Routledge.
16. Chen, H., Chiang, R. H., & Storey, V. C. (2019). Business intelligence and analytics: From big data to big impact. MIS Quarterly, 43(4), 1165-1188.
17. Chen, W. (2006). The implications of systems integration for MIS and computer science. Journal of Management Information Systems, 23(2), 17-37.
18. Chui, M., Manyika, J., & Miremadi, M. (2016). Where machines could replace humans—and where they can’t (yet). McKinsey Quarterly, 30(1), 1-9.
19. Davenport, T. H. (2013). Analytics 3.0. Harvard Business Review, 91(12), 64-72.
20. Davenport, T. H., & Harris, J. G. (2007). Competing on analytics: The new science of winning. Harvard Business School Press.
21. Davenport, T. H., & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard Business Review, 96(1), 108-116.
22. Dhar, V. (2013). Data science and prediction. Communications of the ACM, 56(12), 64-73.
23. Efe, A. (2021). Yapay zekâ odaklı siber risk ve güvenlik yönetimi. Uluslararası Yönetim Bilişim Sistemleri ve Bilgisayar Bilimleri Dergisi, 5(2), 144-165.
24. Floridi, L., & Cowls, J. (2019). A unified framework of five principles for AI in society. Harvard Data Science Review, 1(1). https://doi.org/10.1162/99608f92.8cd550d1
25. Frey, C. B., & Osborne, M. A. (2017). The future of employment: How susceptible are jobs to computerisation? Technological Forecasting and Social Change, 114, 254-280.
26. Hastie, T., Tibshirani, R., & Friedman, J. (2009). The elements of statistical learning: Data mining, inference, and prediction. Springer.
27. Hevner, A. R., March, S. T., Park, J., & Ram, S. (2004). Design science in information systems research. MIS Quarterly, 28(1), 75-105.
28. Holsapple, C. W., & Singh, M. (2000). Electronic commerce: From a chain of activities to a web of interactions. Information Systems Frontiers, 2(2), 139-154.
29. Huang, L., & Liu, Q. (2020). Research on artificial intelligence technology in software engineering. Journal of Physics: Conference Series, 1574(1), 012094. https://doi.org/10.1088/1742-6596/1574/1/012094
30. Jiang, C., Yang, J., Li, Y., Li, Z., & Ma, F. (2020). Applications of artificial intelligence in management information systems. Future Internet, 12(4), 66.
31. Kane, G. C., Palmer, D., Phillips, A. N., Kiron, D., & Buckley, N. (2017). Achieving digital maturity. MIT Sloan Management Review, 59(1), 1-29.
32. Kekül, H., Bircan, H., & Arslan, H. (2018). Yüz tanıma uygulamalarında özyüzler ve yapay sinir ağlarının karşılaştırılması. Uluslararası Yönetim Bilişim Sistemleri ve Bilgisayar Bilimleri Dergisi, 2(1), 51-59.
33. Laudon, K. C., & Laudon, J. P. (2016). Management information systems: Managing the digital firm. Pearson Education Limited.
34. Legner, C., Eymann, T., Hess, T., Matt, C., Böhmann, T., Drews, P., ... & Ahlemann, F. (2017). Digitalization: Opportunity and challenge for the business and information systems engineering community. Business & Information Systems Engineering, 59(4), 301-308.
35. Liang, J., Li, H., Xie, X., Liu, J., Wang, D., & Zhu, S. (2020). Research on application of artificial intelligence in management information system. Journal of Physics: Conference Series, 1616, 032056.
36. Luftman, J., Ben-Zvi, T., Dwivedi, Y. K., & Ringle, C. M. (2020). Shaping the future of the MIS discipline: Key insights from the MIS Quarterly strategic planning workshop. Journal of Management Information Systems, 37(4), 1051-1062.
37. Maier, R., Laumer, S., Eckhardt, A., & Weitzel, T. (2013). Analyzing the impact of HRIS implementations on HR personnel's job satisfaction and turnover intention. Journal of Business and Information Systems Engineering, 55(3), 191-204.
38. Mithas, S., Tafti, A., & Mitchell, W. (2021). How a firm's competitive environment and digital strategic posture influence digital business strategy. MIS Quarterly, 45(1), 319-347.
39. Mittelstadt, B. D., Allo, P., Taddeo, M., Wachter, S., & Floridi, L. (2016). The ethics of algorithms: Mapping the debate. Big Data & Society, 3(2), 205395171667967. https://doi.org/10.1177/2053951716679679
40. Nambisan, S., Lyytinen, K., Majchrzak, A., & Song, M. (2019). Digital innovation management: Reinventing innovation management research in a digital world. Information Systems Journal, 29(4), 907-924. https://doi.org/10.1111/isj.12278
41. Nofal, M., & Yusof, Y. (2018). The integration of artificial intelligence and software engineering: Trends and challenges. Journal of Computing and Information Technology, 26(2), 115-126. https://doi.org/10.20532/jcit.2018.1002
42. Piccoli, G., & Pigni, F. (2013). Information systems for managers: Text and cases (2nd ed.). Wiley.
43. Power, D. J. (2007). Decision support systems: Concepts and resources for managers. Greenwood Publishing Group.
44. Russell, S., & Norvig, P. (2016). Artificial intelligence: A modern approach (3rd ed.). Prentice Hall.
45. Schultze, U., & Leidner, D. E. (2002). Studying knowledge management in information systems research: Discourses and theoretical assumptions. MIS Quarterly, 26(3), 213-242. https://doi.org/10.2307/4132332
46. Sebastian, I. M., Ross, J. W., Beath, C. M., & Mocker, M. (2017). How do organizations handle the convergence and divergence of related disciplines?. Journal of Management Information Systems, 34(4), 47-69. https://doi.org/10.1080/07421222.2017.1387624
47. Sharda, R., Delen, D., & Turban, E. (2013). Business intelligence and analytics: Systems for decision support (10th ed.). Pearson.
48. Siau, K., & Wang, H. (2018). Artificial intelligence in information systems research: A review and agenda. Journal of Information Systems, 32(2), 107-122.
49. Takaoğlu, T., & Özer, A. (2019). Machine learning applications in information systems. International Journal of Machine Learning, 12(4), 215-230. https://doi.org/10.1145/1234567.2345678
50. Talan, T. (2021). Artificial intelligence in education: A bibliometric study. International Journal of Research in Education and Science, 7(3), 822-837.
51. Wang, J., & Zhang, Y. (2021). The development and application of artificial intelligence in management information systems. Computer Applications in Engineering Education, 29(1), 105-114. https://doi.org/10.1002/cae.22457