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Class Notes: Power of Text-mining in BPM

Blog: BPTrends - Class Notes

Jan vom Brocke and his colleagues, Oliver Mueller, and Stefan Debortoli, at the University of Lichtenstein, provide a detailed account of their investigation of
text-mining’s potential to foster BPM capabilities. Read their Column for Their conclusions.

Author information

Jan vom Brocke, Oliver Müller, and Stefan Debortoli

Jan vom Brocke is head of the BPM group in Liechtenstein. He is Professor of Information Systems, the Hilti Chair of Business Process Management, and Director of the Institute of Information Systems. He is Founder and Co-Director of the award-winning Master Program in Information Systems with Majors in Business Process Management and Data Science and Director of the PhD Program in Information and Process Management at the University of Liechtenstein(see: www.uni.li/mis). Since 2012 he has been appointed Vice-President of the University of Liechtenstein responsible for research and innovation, re-elected in 2015. Jan has over 15 years of experience in IT and BPM projects and he has published more than 300 papers in reknowned outlets, including MIS Quarterly (MISQ), the Journal of Management Information Systems (JMIS), European Journal of Information Systems (EJIS), and the Business Process Management Journal (BPMJ). He has authored and edited 29 books, including Business Process Management – Driving Innovation in a Digital World and Green BPM – Towards the Sustainable Enterprise, and the International Handbook on Business Process Management. Jan is an invited speaker and trusted advisor on BPM serving many organizations around the world. You can contact and follow Jan via his website: janvombrocke.com.
Oliver Müller is an Associate Professor at the IT University of Copenhagen. He holds a BSc and MSc in Information Systems and a PhD in Business Economics from the University of Münster, Germany. The goal of Oliver’s research is to help organizations and individuals to create value through (big) data and analytics. At this, he particularly focuses on extracting knowledge from large amounts of unstructured text data, from both the Internet and enterprise-internal sources. His research has been published in the European Journal of Information Systems, Journal of the Association for Information Systems, Communications of the Association for Information Systems, IEEE Transactions on Engineering Management, and others.
Stefan Debortoli is an associated researcher at the Institute of Information Systems at the University of Liechtenstein. He holds a BSc and MSc in Information Systems and a PhD in Business Economics from the University of Liechtenstein. His doctoral studies focused on applying big data analytics as a new strategy of inquiry in Information Systems Research. In the field of big data analytics, he focused on applying text-mining techniques for research purposes. His work has been published in the European Journal of Information Systems, Communications of the Association for Information Systems, and Business & Information Systems Engineering.

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