Decision Support Systems X: Cognitive Decision Support Systems and Technologies: 6th International Conference on Decision Support System Technology, ... Notes in Business Information Processing)

✍ Scribed by José María Moreno-Jiménez (editor), Isabelle Linden (editor), Fatima Dargam (editor), Uchitha Jayawickrama (editor)

• Publisher: Springer
• Year: 2020
• Tongue: English
• Leaves: 189
• Category: Library

✦ Synopsis

This book constitutes the proceedings of the 6th International Conference on Decision Support Systems Technologies, ICDSST 2020, organised in Zaragoza, Spain, in May 2020. The conference was held online only due to the Corona 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 topic of this year’s conference was “Cognitive Decision Support Systems and Technologies”. The 13 papers presented in this volume were carefully reviewed and selected from 51 submissions. Theywere organized in topical sections named: methodological contributions; case studies and applications; and overview (on the current state and future trends of DSS, BI, and data analytics research).

✦ Table of Contents

EURO Working Group on Decision Support Systems
Preface
Organization
Contents
Methodological Contributions
Two Sides of Collective Decision Making - Votes from Crowd and Knowledge from Experts
1 Introduction
2 Different Roles of Experts and the Crowd for Making Collective Decisions
3 The Importance of COMSOC for Collective Decision Making
4 Importance of Public Opinion and Shortcomings of Crowd Voting
4.1 About the Importance of Public Opinion and Crowd Voting
4.2 Shortcomings of Crowd Voting
5 The Need for Involving Experts in Crowd Voting Procedures
6 A Proposal for Future Research
7 Conclusion and Future Work
References
Using Multi-level DEA to Go Beyond the Three Dimensions of Sustainability
1 Introduction
2 Methodology
2.1 Sustainability and Data Envelopment Analysis
2.2 Model Formulation
2.3 Data and Sub-indicators
3 Results
4 Conclusions
References
Analysis of Graphical Visualizations for Multi-criteria Decision Making in FITradeoff Method Using a Decision Neuroscience Experiment
1 Introduction
2 FITradeoff Method
3 Neuroscience Experiment to Investigate Graphical Visualization in DSS
4 Results
5 Discussion of Results
6 Conclusion
References
The Multi-Actor Multi-Criteria Analysis (MAMCA): New Software and New Visualizations
1 Introduction
1.1 Supply Chain Management Case Study
2 MAMCA Methodology
3 The New MAMCA Software
3.1 The Evaluation Steps and Visualizations
3.2 New Features in the Software
3.3 Enhanced ``Participation'' Concept
4 Discussion and Future Work
5 Conclusion
References
Complexity Clustering of BPMN Models: Initial Experiments with the K-means Algorithm
1 Introduction
2 Related Work
3 Complexity Assessment Methodology
3.1 Data Preprocessing
3.2 Clustering
3.3 Analysis
4 Evaluation of BPMN Models
4.1 Scenario 1: Equal Priority
4.2 Scenario 2: High CFC and Low NOAJS Priority
4.3 Examples from Literature
5 Final Remarks and Future Work
References
Case Studies and Applications
To Click or Not to Click? Deciding to Trust or Distrust Phishing Emails
1 Introduction
2 Background Theory and Assumptions
2.1 On Interpretation and Understanding
2.2 On Insider Threats
2.3 On Trust and Distrust
3 Research Proposal and Experimental Protocol
3.1 Description of the Study
3.2 Discussion of the Preliminary Results
3.3 Presentation of Future Works
4 Conclusions and Perspectives
References
Management Information System for Police Facility Location
1 Introduction
2 Theoretical Background
2.1 Covering Problems
2.2 Clustering Methods and the K-Means Method
3 The MIS
4 The Case Study
4.1 Candidate Locations
4.2 Optimal Allocation
4.3 Comparison of Performance
5 Final Considerations
References
An Automated Corpus Annotation Experiment in Brazilian Portuguese for Sentiment Analysis in Public Security
1 Introduction
2 Background
2.1 Automated Corpus Annotation
2.2 Topic Modeling
2.3 Sentiment Polarity Labeling
3 Experiment Description
3.1 Searching and Selecting a Pre-existing Annotated Corpus
3.2 Tweets’ Collection and Preprocessing
3.3 Topic Modeling
3.4 Polarity Labeling Over the Selected Tweets
4 Experiment Results
4.1 Pre-existing Annotated Corpus Characteristics
4.2 Extracted Tweets Characteristics
4.3 Topic Modeling Results
4.4 Polarity Labeling and Public Security Related Corpus Obtention
5 Concluding Remarks
References
An E-government Procurement Decision Support System Model for Public Private Partnership Projects in Egypt
1 Introduction
2 Literature Review
2.1 E-procurement Concept, Benefits, and Challenges
2.2 Adopting E-procurement in Governments
2.3 Public–Private Partnerships: Concept, Benefits, and E-government Rationale
3 The Concept of E-government Procurement in Egypt
3.1 Background of the Case
3.2 Using DSS in PPP E-government Procurement Process
3.3 E-procurement Model Development Under PPP in Egypt
4 Discussion of Theoretical and Managerial Implications
5 Conclusion, Recommendations, and Limitations
References
Determinants of Recommendation in the Airline Industry: An Application of Online Review Analysis
1 Introduction
2 Methodology
2.1 Data Collection
3 Results
3.1 Descriptive Summary
3.2 A New Way to Split Dataset: ‘Recommenders and Non-recommenders’
3.3 Logistic Regression
3.4 Text Analysis
4 Conclusion
References
Artificial Intelligence Based Decision Making for Venture Capital Platform
1 Introduction
1.1 Decision Making Process of Venture Capitalists
2 Machine Intelligence for Venture Capital Platforms
2.1 Deal-Sourcing System
2.2 Market and Competition
2.3 Opportunity Evaluation System
3 Experiments and Results
3.1 Deal-Sourcing System
3.2 Market and Competition
3.3 Opportunity Evaluation
4 Conclusions
References
Supporting Operational Decisions on Desalination Plants from Process Modelling and Simulation to Monitoring and Automated Control with Machine Learning
1 Introduction
2 Overall MIDES Process
3 MDC & MIDES Process from Lab to Pilot Scale
3.1 The Lab-Scale MDC
3.2 The Pre-Pilot MDC
3.3 The Pilot-Scale MDC
4 MIDES Process Modelling and Simulation
4.1 IPSEpro – SimTech’s Integrated Process Simulation Environment
4.2 IPSEpro in MIDES
4.3 IPSEpro Online Platform - Implementation
4.4 MIDES Desalination Process Model Used Online
5 MIDES Monitoring and Automated Control
5.1 Monitoring Control System in the Pre-pilot
6 The Operational Decision Making Support in the MIDES Pilot Desalination Plant
7 Summary and Conclusion
References
Overview
DSS, BI, and Data Analytics Research: Current State and Emerging Trends (2015–2019)
1 Introduction
2 Comparison of DSS, BI, and DA
2.1 DSS
2.2 BI
2.3 DA
3 Emerging Trends
3.1 DSS
3.2 BI
3.3 DA
4 Conclusions
References
Author Index