A Literature Review on Business Process Management


  • Fatimazohra Trabelsi IMS Team, ADMIR Laboratory, Rabat IT Center, ENSIAS, Mohammed V University, Rabat, Morocco.
  • Amal Khtira IMS Team, ADMIR Laboratory, Rabat IT Center, ENSIAS, Mohammed V University, Rabat, Morocco.
  • Bouchra El Asri IMS Team, ADMIR Laboratory, Rabat IT Center, ENSIAS, Mohammed V University, Rabat, Morocco.


Business process management, modeling, process mining, data mining, systematic literature review


Business Process (BP) is a set of coordinated tasks that define how to achieve organizational goals. It emerges as an efficient tool, whose main goal is supporting the design, administration, setup, disclosure and analysis of business processes, and organizations use it to identify opportunities to reduce costs, increase service or product quality, etc. The goal of BPM is to manage business processes. Organizations wish to manage perfectly these processes instead of fixing the non-ideal process setups or outcomes in a reactive manner. At present, variability management in the business processes domain is considered as a key of reuse. Process mining offers a set of techniques that retrieves information from event logs and gives companies a better understanding of their processes. Process mining has gained significant attention in both research and industry as a range of data mining tools has emerged. In this study, we will provide a systematic literature review from 2017 to 2021; we will use Kitchenham method to conduct this SLR. Data source as IEEE, ACM, Springer and ScienceDirect are used to obtain literature. We had, as a result, 51 papers from 3079 papers to complete this paper. This SLR had for objective to see the research trend on the topics of business process management, improvement, modeling and approaches using data mining.


H. L-Mora and P. R.P-Sanchez, ``The Evolution of Business Process Management: A Bibliometric Analysis,'' School of Business Administration, Technological Institute of Costa Rica, Cartago 30101, Costa Rica, vol. 9, April2021.

W. Li, H. ZHU, W. LIU, D. CHEN , J. JIANG , AND Q. JIN, (Senior Member, IEEE), " An Anti-Noise Process Mining Algorithm Based on Minimum Spanning Tree Clustering." emph{IEEE ACCESS} Shangai, China, 2018, vol6.

E. A. El H. Amor and S. A. Ghannouchi, ``Toward an Ontology-based model of key performance indicators for business process improvement '' emph{ IEEE/ACS 14th International Conference on Computer Systems and Applications}, Sousse, RIADI Laboratory-ENSI Manouba, Tunisia, 2017

S. Debois, T. T. Hildebrandt, P. H. Laursen and K. R. Ulrik, ``Declarative Process Mining for DCR Graphs'' emph{the ACM Symposium on applied computing},IT University of Copenhagen, Copenhagen, Denmark, 2017.

S. Azzouzi, S. A. Ghannouchi and Z. Brahmi, ``Modeling of a Collaborative Learning Process with Business Process Model Notation'' emph{International conference on Biomolecular Engineering}.,Laboratory RIADI-GDL, ENSI, Mannouba, Tunisia, 2017.

D. Bano, M. Weske and A. Nikaj, ``Discovering Business Process Architectures from Event Logs,'' Hasso Plattner Institute, University of Potsdam, Potsdam, Germany, 2021.

M. T. G-Lopez, A. M. R. Quintero, L. Parody, J. M. P. Alvarez and M Reichert ``An Architecture for Querying Business Process, Business Process Instances, and Business Data Models,'' Institute of Databases and Information Systems, Ulm University, Ulm, Germany,2018.

S. Lee, I. Choi, H. Kim, J. Lim and S. Sung "Comprehensive Simulation and Redesign System for Business Process and Organizational Structure"emph{IEEE ACCESS}, Department of Industrial and Management Engineering, Pohang University of Science and Technology (POSTECH), Pohang 36763, South Korea, vol8, 2020.

A. E. M-Chamorro, M. Resinas and A. R.-Cortes "Predictive monitoring of business processes: a survey"emph{IEEE Transaction on Service Computing}, Dpto. de Lenguajes y Sistemas Informaticos, University of Seville,Spain, 2017.

S. Sakr, Z. Maamar, A. Awad B. Benatallah, W. M. P. Van Der Aalast, ``Business Process Analytics and Big Data Systems: A Roadmap to Bridge the Gap''emph{ IEEE ACCESS} , University of Tartu, Tartu, Estonia, 2018

A. Djedovic, E. Zunic and A. Karabegovic, "A Combined Process Mining for Improving Business Process"emph{ICSST}, Sarajevo, Bosnia and Herzegovina, 2017

R. Sikal, H. Sbai and L. Kjiri, "Configurable Process Mining: A Comparative Study", emph{ International Conference on Optimization and Application}, AlQualsadi research team, ENSIAS, Mohammed V University of Rabat, Morocco, 2018.

J. Brunk, "Structuring Business Process Context Information for Process Monitoring and Prediction", emph{IEEE 22nd Conference on Business Informatics (CBI)}, University of Muenster - ERCIS Leonardo-Campus 3, 48149 Munster, Germany, 2020

M. O. S. Escobar, R. L. Espinosa, J. M. M. Espinosa, J. J. N. Monroy and G. V. Solar, "Applying Process Mining to Support Management of Predictive Analytics/Data Mining Projects in a Decision Making Center", emph{ The 2019 6th International Conference on Systems and Informatics (ICSAI )}, 2019.

W. M.P. van der Aalst, " Free-Choice Nets for Process Mining and Business Process Management" emph{International Conference on Smart Information and Society}, Process and Data Science (Informatik 9), RWTH Aachen University, Aachen, Germany and Fraunhofer-Institut für Angewandte Informationstechnik (FIT), Sankt Augustin, Germany, 2021.

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J. Becker, J. Brunk, W. Ding, M. Niemann, "Conceptualization of an Integrated Procedure Model for Business Process Monitoring and Prediction", emph{ IEEE 22nd Conference on Business Informatics (CBI)}, University of Muenster - ERCIS Leonardo-Campus 3, 48149 Munster, Germany, 2020.

S. Bharara, A. S. Sabitha and A. Bansal, "A review on Knowledge extraction for Business operation using data mining", emph{ International Conference on Data and Software Engineering}, Computer science and engg. department, Amity University Uttar Pradesh, Noida, India 2017.

R. Bhogal and A. Garg, "Anomaly Detection and Fault Prediction of Breakdown to Repair Process Using Mining Techniques", emph{ International Conference on Intelligent Engineering and Management (ICIEM) }, Department of Computer Science & Engineering, Amity School of Engineering & Technology, University Uttar Pradesh, Noida, India, 2020.

L. G-Banuelos, N. R.T.P van beest, M. Dumas, M. La Rosa and W. Mertens, "Complete and Interpretable Conformance Checking of Business Processes", emph{ IEEE Transactions and Software Engineering }, 2017

F. M. Plumed, L. C. Ochando, C. Ferri, J. H. Orallo, M. Kull, N. Lachiche, M. J. R. Quintana and P. Flach, "CRISP-DM Twenty Years Later: From Data Mining Processes to Data Science Trajectories", emph{ IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING}, 2021.

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J. Baijens, R. Helms and R. Kusters, "Data Analytics Project Methodologies: Which One to Choose?", in emph{International Conference on Big Data in Management}, Department of Information Science Open University Heerlen, The Netherlands, 2020.

M. B. Costa, D. Tamzalit, "Recommendation Patterns for Business Process Imperative Modeling", emph{Symposium on Applied Computing}, Software Eng. and e-Commerce Lab. – SEEC Informatics - Federal I. of Espírito Santo Serra – ES, Brazil, 2017.

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M. Lederer, S. Betz and W. Schmidt, "Digital Transformation, Smart Factories, and Virtual Design – Contributions of Subject Orientation", in emph{ ICSO conference}, ISM International School of Management Karlstr. 35 D-80333 Munich, 2018.

N. J. Omori, G. M. Tavares, P. Ceravolo and S. B. Jr., "Comparing Concept Drift Detection with Process Mining Tools", in emph{ symposium on information system}, State University of Londrina (UEL), Londrina, Brazil, 2019.

S. Chaveesuk, B. Khalid and W. Chaiyasoonthorn, "Emergence of New Business Environment with Big Data and Artificial Intelligence", Faculty of Administration and Management, King Mongkut’s Institute of Technology King, Ladkrabang, Bangkok, Thailand, 2019.

R. Song, J. Vanthienen, W. Cui, Y. Wang and L. Huang, "Towards a Comprehensive Understanding of the Context Concepts in Context-aware Business Processes" in emph{ ICSO conference} Department of Information Management Beijing Jiaotong University & KU Leuven Beijing, China, 2019.

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S. Yeng, X. Dong, L. Sun, Y. Zhou, R. A. Farneth, H. Xiong, R. S. Burd and I. Marsic, "A Data-driven Process Recommender Framework", in emph{ KDD 2017 Applied Data Science Paper}, Halifax, NS, Canada, 2017.

D. Bano and M. Weske, "Discovering Data Models from Event Logs", in emph{ international conference on conceptual modeling}, Hasso Plattner Institute, University of Potsdam, Germany, 2020.

F. Hasic, L. Devadder, M. Dochez, J. Hanot, J. De Smedt and Jan Vanthienen, "Challenges in Refactoring Processes to Include Decision Modelling", in emph{ International Conference on Busines Process Management}, Leuven Institute for Research on Information Systems (LIRIS), KU Leuven, Leuven, Belgium, 2018.

E. Marengo, W. Nutt a,d M. Perktold, "Construction Process Modeling: Reresenting Activities, Items and Their Interplay", in emph{ International Conference on Busines Process Management}, Faculty of Computer Science, Free University of Bozen-Bolzano, Bolzano, Italy, 2018.

S. Pauwels and T. Calders, "Bayesian Network based Predictions of Business Processes", in emph{ International Conference on Busines Process Management}, University of Antwerp, Antwerp, Belgium 2020.

N. Rizun, A. Revina and V. Meister, "Method of Decision-Making Logic Discovery in the Business Process Textual Data", in emph{ International Conference on Business Information Sytem}, Gdansk University of Technology, 80-233 Gdansk, Poland, 2019.

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M. Weske, M. Montali, I. Weber and J. V. Brocke, "BPM: Foundations, Engineering, Management", Hasso Plattner Institute, University of Potsdam, Potsdam, Germany, 2018.

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M. Khanbabaei, F. M. Sobhani, M. Alborzi and R. Radfar, "Developing an integrated framework for using data mining techniques and ontology concepts for process improvement", in emph{ The journal of Systems and Software}, Department of Information Technology Management, Science and Research Branch, Islamic Azad University, Tehran, Iran, 2017.

N. Saab, R. Helms and M. Zoet, "Predictive quality performance control in BPM: proposing a framework for predicting quality anomalies", in emph{ International Conference on ENTERprise Information Systems}, Open University, Heerlen, The Netherlands, 2018.

A. Meidan, J.A. Garc?a-Garc?a, M.J. Escalona, I. Ramos, "A survey on business processes management suites", in emph{ Computer Standards & Interfaces journal}, 2017.

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A. Leshob, H. Mili, J. G-Huerta and A. Boubaker, "A value-oriented approach to business process specialization: principles, proof-of-concept, and validation", in emph{ The journal of Systems and Software}, LATECE Laboratory, University of Quebec at Montreal, Montreal (Quebec) H2X 3Y7, Canada, 2017.

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How to Cite

Trabelsi, F. ., Amal Khtira, & Bouchra El Asri. (2022). A Literature Review on Business Process Management. American Scientific Research Journal for Engineering, Technology, and Sciences, 90(1), 444–460. Retrieved from https://asrjetsjournal.org/index.php/American_Scientific_Journal/article/view/8298