Recommender Systems in Business Process Management: A Systematic Literature Review

Abstract

Recommender systems have the potential to enhance decision-making and to improve business process execution in the domain of Business Process Management (BPM). By analyzing data and providing personalized recommendations, these systems can assist users in making profound decisions and so foster the achievement of their business goals. In our study that is based on the PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) methodology, we examine the usage of recommender systems in BPM, focusing on the objectives, methods, and input data utilized. We searched eight databases and included papers that focus on process execution and recommendation methods while excluding those that are not digitally available, not in English, patents, miscellany, or proceedings, or focused solely on business process modeling. This results in 33 papers, addressing the research questions, that are analysed in detail. The discussion highlights research gaps related to user preferences and input data, suggesting that further investigation is needed to enhance the effectiveness of recommender systems in business process management.