Topic Modelling of Contemporary Management Information Systems Research: A Latent Dirichlet Allocation Approach

Authors : Ahmet Ayaz, Ahmet Kamil Kabakuş, Üstün Özen, Ömer Alkan, Serdar Aydın

Pages : 342-354

View : 49 | Download : 55

Publication Date : 2025-01-29

Article Type : Research Paper

Abstract :This research thoroughly explores the expansive academic discourse on Management Information Systems (MIS), investigating its branches, influential theories, and diverse topics. Employing a topic modeling approach, the study analyzes 7852 article abstracts from the Scopus database (2022-2023) using the Latent Dirichlet Allocation algorithm. The goal is to identify research gaps and delineate key areas of interest. The findings suggest that the corpus of articles can be distinctly classified into varied thematic categories, each representing significant facets within the MIS domain. The analytical outcome postulates the existence of seven distinct thematic clusters such as “Digital Innovation and Business Performance”, “Cost Optimization and Demand Analysis”, “Advancements in Machine Learning and Deep Learning”, “Sustainable Practices in Green Logistics and Supply Chain Management”, “Impact of the COVID-19 Pandemic on Social Interaction and Crisis Management Strategies in Businesses”, “Decision Making Systems and the Efficacy of Optimization Models”, and “Consumer Satisfaction and Behavioral Analysis in Online Services”. These insights not only underscore the heterogeneity and breadth of the MIS field but also underscore the dynamic nature of the discipline. The derived results hold the potential to steer future inquiries and foster novel contributions within the realm of MIS.
Keywords : Yönetim bilişim sistemleri, Konu modelleme, Gizli Dirichlet Ataması, Metin madenciliği, Makine öğrenmesi