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Enabling Process Management for Loosely Framed Knowledge-intensive Processes
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Enabling Process Management for Loosely Framed Knowledge-intensive Processes

1st ed. 2020

Book Details

Format Paperback / Softback
ISBN-10 303066192X
ISBN-13 9783030661922
Edition 1st ed. 2020
Publisher Springer Nature Switzerland AG
Imprint Springer Nature Switzerland AG
Country of Manufacture GB
Country of Publication GB
Publication Date Jan 24th, 2021
Print length 202 Pages
Ksh 8,100.00
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This book is a revised version of the PhD dissertation written by the author at the Department of Business Informatics and Operations Management at Ghent University in Belgium. It addresses shortcomings in Business Process Management concerning loosely framed knowledge-intensive processes, which are characterized by their numerous valid process variants and their reliance on knowledge workers to apply their knowledge to decide on a suitable process variant that fits the context of a specific process execution. The goal was to lay the foundation for a process-aware business process management (IT-)system to support such processes. Several proof-of-concept implementations have been made for the core components and were evaluated in the domain of the healthcare. Starting from an artificial, but realistic, case about patients that arrive in the emergency room with suspected arm fractures and later progressing to a case study of the diagnosis and treatment of patients in the emergency department of a real hospital, using data from their patient files. In 2020, the PhD dissertation won the “CAiSE PhD award”, granted to outstanding PhD theses in the field of Information Systems Engineering.

This book is a revised version of the PhD dissertation written by the author at the Department of Business Informatics and Operations Management at Ghent University in Belgium.

It addresses shortcomings in Business Process Management concerning loosely framed knowledge-intensive processes, which are characterized by their numerous valid process variants and their reliance on knowledge workers to apply their knowledge to decide on a suitable process variant that fits the context of a specific process execution. The goal was to lay the foundation for a process-aware business process management (IT-)system to support such processes. Several proof-of-concept implementations have been made for the core components and were evaluated in the domain of the healthcare. Starting from an artificial, but realistic, case about patients that arrive in the emergency room with suspected arm fractures and later progressing to a case study of the diagnosis and treatment of patients in the emergency department of a real hospital, using data from their patient files. 

In 2020, the PhD dissertation won the "CAiSE PhD award", granted to outstanding PhD theses in the field of Information Systems Engineering.


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