Exploring Service Science 9th International Conference, IESS 2018, Karlsruhe, Germany, September 19-21, 2018, Proceedings /

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Satzger, Gerhard (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Patrício, Lia (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Zaki, Mohamed (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Kühl, Niklas (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Hottum, Peter (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2018.
• Έκδοση: 1st ed. 2018.
• Σειρά: Lecture Notes in Business Information Processing, 331
• Θέματα: Application software.; Management information systems.; Big data.; Health informatics.; Management.; Industrial management.; Information Systems Applications (incl. Internet).; Business IT Infrastructure.; Computer Appl. in Administrative Data Processing.; Big Data/Analytics.; Health Informatics.; Innovation/Technology Management.
• Φυσική περιγραφή: XIII, 416 p. 67 illus. online resource.
• ISBN: 9783030007133
• ISSN: 1865-1348 ;
• DOI: 10.1007/978-3-030-00713-3

This book constitutes the proceedings of the 9th International Conference on Exploring Services Science, IESS 2018, held in Karlsruhe, Germany, in September 2018. The 30 papers presented in this volume were carefully reviewed and selected from 67 submissions. The book is structured in six parts, each featuring contributions describing current research in a particular domain of service science: Service Design and Innovation; Smart Service Processes; Big Data in Services; Service Topics Open Exploration; Design Science Research in Services. The book offers an extended, ICT-focused vision on services and addresses multiple relevant aspects, including underlying business models, the necessary processes and technological capabilities like big data and machine learning. The academic work showcased at the conference should help to advance service science and its application in practice.