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Event Information Systems. A Process and Data Reference Model for Event Management

Advances in Information Systems and Management Science, Bd. 62

Markus Heuchert

ISBN 978-3-8325-5289-3
330 pages, year of publication: 2021
price: 49.00 €
Events are an essential element of society. Advancing digital technologies and the ongoing globalization has put forward a variety of different business, leisure, or scientific events that need to be managed in order to take place. As a result of the proliferation of digital technology, IT systems are an indispensable part of this management process. Amid this pandemic crisis, these systems have become increasingly important due to the relocation of events into the virtual sphere.

Since every event entails different requirements, event management systems need to be very flexible. In contrast to other application systems, this flexibility is needed during use as the requirements of future events are not known during the initial selection and roll-out of the software. This calls for an intensified dialogue between the business and IT to match technical possibilities with practical requirements. Currently, adequate means to support this dialogue are lacking.

To this end, this dissertation presents a reference model that encompasses the essential processes and data structures in the domain. In 36 application cases, the reference model is instantiated and evaluated. Practitioners and researchers are the intended audiences of this work. Researchers may use it as a foundation to design novel IT artifacts in the domain. Practitioners benefit from the first comprehensive tool to support the design and use of digital technology in event management.

Markus Heuchert studied Information Systems at the University of Münster. Subsequently, he worked as a research assistant at the European Research Center for Information Systems (ERCIS) and founded the Event Information Systems GmbH. As a technically versed generalist, he excels in topics related to process and data management backed by his experience in consulting. In March 2021, he completed his doctoral studies.

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Keywords:
  • Event Management
  • Process Modeling
  • Data Modeling
  • Process Management
  • Event Software

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