Decision support systems XI : decision support systems, analytics and technologies in response to global crisis management : 7th International Conference on Decision Support System Technology, ICDSST 2021, Loughborough, UK, May 26-28, 2021, Proceedings / Uchitha Jayawickrama, Pavlos Delias, María Teresa Escobar, Jason Papathanasiou (eds.).
International Conference on Decision Support System Technology (7th : 2021 : Online); Jayawickrama, Uchitha, editor; Delias, Pavlos, editor; Escobar, María Teresa, editor.; Papathanasiou, Jason, editor
2021
T58.62
Available Online

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Title Decision support systems XI : decision support systems, analytics and technologies in response to global crisis management : 7th International Conference on Decision Support System Technology, ICDSST 2021, Loughborough, UK, May 26-28, 2021, Proceedings / Uchitha Jayawickrama, Pavlos Delias, María Teresa Escobar, Jason Papathanasiou (eds.).
Meeting Name International Conference on Decision Support System Technology (7th : 2021 : Online)
ISBN 9783030739768 (electronic bk.)
3030739767 (electronic bk.)
9783030739751 (print)
3030739759
DOI https://doi.org/10.1007/978-3-030-73976-8
Published Cham, Switzerland : Springer, [2021]
Language English
Description 1 online resource (xiv, 135 pages) : illustrations (some color)
Item Number 10.1007/978-3-030-73976-8 doi
Call Number T58.62
Dewey Decimal Classification 658.4/03
Summary This book constitutes the proceedings of the 7th International Conference on Decision Support Systems Technologies, ICDSST 2021, held during May 26-28, 2021. The conference was planned to take place in Loughborough, UK, and changed to an online format due to the COVID-19 pandemic. The EWG-DSS series of International Conference on Decision Support System Technology (ICDSST) is planned to consolidate the tradition of annual events organized by the EWG-DSS in offering a platform for European and international DSS communities, comprising the academic and industrial sectors, to present state-of-the-art DSS research and developments, to discuss current challenges that surround decision-making processes, to exchange ideas about realistic and innovative solutions, and to co-develop potential business opportunities. The main aim of this year's conference is to investigate the role DSS and related technologies can play in mitigating the impact of pandemics and post-crisis recovery. The 10 papers presented in this volume were carefully reviewed and selected from 44 submissions. They were organized in two topical sections named: multiple criteria approaches and advances in decision support systems' technologies and methods.
Note " ... initially planned to be held in Loughborough, UK, during May 26-28, 2021, but eventually held virtually due to the ongoing COVID-19 pandemic."--Preface
Includes author index.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed May 20, 2021).
Added Author Jayawickrama, Uchitha, editor
Delias, Pavlos, editor
Escobar, María Teresa, editor.
Papathanasiou, Jason, editor
Series Lecture notes in business information processing ; 414. 1865-1348
Linked Resources Online Access
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Multiple Criteria Approaches
The Multi-Actor Multi-Criteria Analysis (MAMCA) for Mass-Participation Decision Making
Using FITradeoff Method for supply selection with decomposition and holistic evaluations for Preference Modelling
DEX2Web
A Web-Based Software Implementing the Multiple-Criteria Decision-Making Method DEX
Comparison of AHP, PAPRICA, PROMETHEE, DEX and TOPSIS on an application for employee selection
A Survey on Criteria for Smart Home Systems with Integration into the Analytic Hierarchy Process
Advances in Decision Support Systems' technologies and methods
Modelling the Effects of Lockdown and Social Distancing in the Management of the Global Coronavirus Crisis
Why the UK Tier System Failed
A case study initiating discrete event simulation as a tool for decision making in I4.0 manufacturing
Methodology for Multi-Aspect Ontologies Development: Use Case of DSS Based on Human-Machine Collective Intelligence
Investigating oversampling techniques for fair machine learning models
Using AI to Advance Factory Planning: A Case Study to Identify Success Factors of Implementing an AI-Based Demand Planning Solution.

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