Artificial Intelligence Applications in Management Information Systems: A Comprehensive Systematic Review with Business Analytics Perspective

Year 2021, Volume: 1 Issue: 1, 25 - 56, 30.04.2021

Halil İbrahim Çelebi

An Erratum to this article was published on May 1, 2023. https://dergipark.org.tr/en/pub/aita/issue/77113/1290881

Abstract

The need to solve very complex problems and the desire to model and understand human behavior are the most important factors that trigger artificial intelligence studies. In addition, today, when digitalization has become a necessity with the industrial revolution, the importance of management information systems located at the interface of information, business and industry has increased even more. In this study, which was prepared by taking these two approaches into consideration, it was aimed to examine the use of artificial intelligence techniques in management information systems literature in a multidimensional and systematic manner, and in this direction, a systematic literature review method supported by semi-automatic modern technique such as text mining was proposed. As a result of the literature review, it has been observed that studies in the field of deep learning and swarm intelligence have gained importance in recent years. When evaluated in terms of application, although information system support and information management are at the forefront in the field of informatics, it is thought that there is a shift towards cybercrime and security and fault detection. Similarly, it can be said that there has been a tendency towards environmental factors in other business areas where production and supply chain studies are seen more. In sectoral evaluations, the value of the health sector has increased while manufacturing-oriented areas are ahead as a result of the digital transformation. When all these findings are evaluated together, it is thought that a detailed guide is presented to the academicians and professionals who will work in the field.

Keywords

artificial inteligence, fuzzy logic, neural networks, deep learning, expert systems, genetic algorithms, meta heuristics, systematic review

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