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Über dieses Buch

This book constitutes the proceedings of the Third International Conference on Decision Support Systems, ICDSST 2017, held in Namur, Belgium, in May 2017. The EWG-DSS series of the International Conference on Decision Support System Technology (ICDSST) offers a platform for European and international DSS communities, comprising the academic and industrial sectors, in order 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 “Data, Information and Knowledge Visualization in Decision Making”.
The 13 papers presented in this volume were carefully reviewed and selected from 53 submissions. They were organized in topical sections named: visualization case studies; visualization perspectives; analytics and decision; and Multi-Criteria Decision Making.



Visualization Case Studies


A Visual Decision Support System for Helping Physicians to Make A decision on New Drugs

When new drugs come onto the market, physicians have to decide whether they will consider the new drug for their future prescriptions. However, there is no absolute “right” decision: it depends on the physician’s opinion, practice and patient base. Here, we propose a visual approach for supporting this decision using iconic, interactive and graphical presentation techniques for facilitating the comparison of a new drug with already existent drugs. By comparing the drug properties, the physician is aided in his decision task.
We designed a prototype containing the properties of 4 new drugs and 22 “comparator” drugs. We presented the resulting system to a group of physicians. Preliminary evaluation results showed that this approach allowed physicians to make a decision when they were lacking information about the new drug, and to change their mind if they were overconfident in the new drug.
Jean-Baptiste Lamy, Adrien Ugon, Hélène Berthelot, Madeleine Favre

Automatic Traffic Enforcement Camera Operation, Based on a Business Intelligence System

Since 2012, a new automatic traffic enforcement camera project has been in operation in Israel. Several databases are included in this project, i.e. sensor data, traffic reports, and road accident records. In 2014 a business intelligence system was developed to obtain all the data from the sensors of the new project and to merge them with the existing data to run the project effectively and efficiently. The aim of this paper is to present the process and the configuration of the business intelligence system, and to present the improvements in all measurements. In this paper we demonstrate the importance of a business intelligence system for operating, engineering, researching and managing aspects of a project.
Mali Sher, Guy Shifrin

Multicriteria Decision Making for Healthcare Facilities Location with Visualization Based on FITradeoff Method

This paper proposes an application of the Flexible Interactive Tradeoff (FITradeoff) method for siting healthcare facilities. The selection of the location of complex facilities, as hospitals, can be considered as a multidimensional decision problem for the several issues to be taken into account and, moreover, for the variety of stakeholders that should be involved. The case study under investigation is the location of “La Città della Salute”, a new large healthcare facility in Lombardy Region (Italy). Starting from a cross disciplinary literature review, a multidimensional evaluation framework has been defined and applied to the case study by considering the point of view of one Decision Maker (DM). The application shows that a smaller effort is required from the DM using the FITradeoff method.
Marta Dell’Ovo, Eduarda Asfora Frej, Alessandra Oppio, Stefano Capolongo, Danielle Costa Morais, Adiel Teixeira de Almeida

Business Process Modelling and Visualisation to Support e-Government Decision Making: Business/IS Alignment

Alignment between business and information systems plays a vital role in the formation of dependent relationships between different departments in a government organization and the process of alignment can be improved by developing an information system (IS) according to the stakeholders’ expectations. However, establishing strong alignment in the context of the eGovernment environment can be difficult. It is widely accepted that business processes in the government environment plays a pivotal role in capturing the details of IS requirements. This paper presents a method of business process modelling through UML which can help to visualise and capture the IS requirements for the system development. A series of UML models have been developed and discussed. A case study on patient visits to a healthcare clinic in the context of eGovernment has been used to validate the models.
Sulaiman Alfadhel, Shaofeng Liu, Festus O. Oderanti

Visualization Perspectives


Visualization for Decision Support in FITradeoff Method: Exploring Its Evaluation with Cognitive Neuroscience

FITradeoff method uses a flexible and interactive approach for supporting decisions in multicriteria problems in the context of MAVT (Multi-Attribute Value Theory) with partial information. Since the very beginning of the preference elicitation process, a subset of potential optimal alternatives (POA) is selected based on the current partial information provided. Then, the Decision Maker (DM) has the flexibility of interrupting the elicitation process for analyzing the partial result by other means, such as graphical visualization of performance of POA. This flexibility is available in the whole process. Evaluating the visualization confidence for decision support in FITradeoff method is crucial. Furthermore, information for designing of this visualization is relevant. This paper shows how these issues could be approached based on cognitive neuroscience, with particular focus given on eye tracking resources.
Adiel Teixeira de Almeida, Lucia Reis Peixoto Roselli

Incorporating Uncertainty into Decision-Making: An Information Visualisation Approach

Incorporating uncertainty into the decision-making process and exposing its effects are crucial for making informed decisions and maximizing the benefits attained from such decisions. Yet, the explicit incorporation of uncertainty into decision-making poses significant cognitive challenges. The decision-maker could be overloaded, and thus may not effectively take the advantages of the uncertainty information. In this paper, we present an information visualisation approach, called RiDeViz, to facilitate the incorporation of uncertainty into decision-making. The main intention of RiDeViz is to enable the decision-maker to explore and analyse the uncertainty and its effects at different levels of detail. It is also intended to enable the decision-maker to explore cause and effect relationships and experiment with multiple “what-if” scenarios. We demonstrate the utility of RiDeViz through an application example of a financial decision-making scenario.
Mohammad Daradkeh, Bilal Abul-Huda

Process Analytics Through Event Databases: Potentials for Visualizations and Process Mining

Events, routinely broadcasted by news media all over the world, are captured and get recorded to event databases in standardized formats. This wealth of information can be aggregated and get visualized with several ways, to result in alluring illustrations. However, existing aggregation techniques tend to consider that events are fragmentary, or that they are part of a strictly sequential chain. Nevertheless, events’ occurrences may appear with varying structures (i.e., others than sequence), reflecting elements of a larger, implicit process. In this work, we propose several transformation templates to a enable a process perspective for raw event data. The basic idea is to transform event databases into a format suitable for process mining (aka event log) to enable the rich toolbox of process mining tools. We present our approach through the illustrative example of the events that happened in Greece during the referendum period (summer 2015).
Pavlos Delias, Ioannis Kazanidis

Value of Visual Analytics to South African Businesses

There is limited literature on the value that visual analytics provides for businesses, and its broad use in organisations. This research provides some understanding of how South African businesses are using visual analytics in their day to day operations, and the value derived from employing it. The study was interpretive, exploratory and descriptive, producing both quantitative and qualitative data. Individuals within organisations making use of visual analytics completed an online survey, and interviews were conducted with informed business, IT and BI stakeholders. Results were compared with those from an international survey, and thematic analysis highlighted four main themes: usage, value, challenges and technology. Most respondents noted the high added value obtained from visual analytics versus tables of numbers. The research also identified a set of good practices for organisations to employ when embarking on a visual analytics strategy and suggested ways of mitigating potential challenges.
Wisaal Behardien, Mike Hart

Analytics and Decision


Conceiving Hybrid What-If Scenarios Based on Usage Preferences

Nowadays, enterprise managers involved with decision-making processes struggle with numerous problems related to market position or business reputation of their companies. Owning the right and high quality set of information is a crucial factor for developing business activities and gaining competitive advantages on business arenas. However, today retrieving information is not enough anymore. The possibility to simulate hypothetical scenarios without harming the business using What-If analysis tools and to retrieve highly refined information is an interesting way for achieving such business advantages. In a previous work, we introduced a hybridization model that combines What-If analysis and OLAP usage preferences, which helps filter the information and meet the users’ needs and business requirements without losing data quality. The main advantage is to provide the user with a way to overcome the difficulties that arise when dealing with the conventional What-If analysis scenario process. In this paper, we show an application of this methodology using a sample database, and compare the results of a conventional What-if process and our methodology. We designed and developed a specific piece of software, which aims to discover the best recommendations for What-If analysis scenarios’ parameters using OLAP usage preferences, which incorporates user experience in the definition and analysis of a target decision-making scenario.
Mariana Carvalho, Orlando Belo

A Semantics Extraction Framework for Decision Support in Context-Specific Social Web Networks

We are now part of a networked society, characterized by the intensive use and dependence of information systems that deals with communication and information, to support decision-making. It is thus clear that organizations, in order to interact effectively with their customers, need to manage their communication activities at the level of online channels. Monitoring these communications can contribute to obtain decision support insights, reduce costs, optimize processes, etc. In this work, we semantically studied the discursive exchanges of a Facebook group created by a strawberries’ seller, in order to predict, through Social Network Analysis (SNA) and semantic analysis of the posts, the quantities to be ordered by customers. The obtained results show that the unstructured data of the Web’s speech can be used to support the decision through SNA.
Manuela Freire, Francisco Antunes, João Paulo Costa

A Tool for Energy Management and Cost Assessment of Pumps in Waste Water Treatment Plants

Waste Water Treatment Plants (WWTPs) are generally considered energy intensive. Substantial energy saving potentials have been identified by several authors. Pumps consume around 12% of the overall WWTP energy consumption. In this paper we propose a methodology that uses the sensors commonly installed in WWTPs, such as volume and energy sensors, to perform energy benchmarking on pumps. The relationship between energy efficiency and flow rate is used to detect specific problems, and potential solutions are proposed, taking into consideration economical and environmental criteria (cost of externalities in energy production). The methodology integrates energy benchmarking, data-mining, and economical and environmental assessment. In order to make better informed decisions, plant managers can now perform a multivariate analysis within a very short time, using information generally available in WWTPs.
Dario Torregrossa, Ulrich Leopold, Francesc Hernández-Sancho, Joachim Hansen, Alex Cornelissen, Georges Schutz

Multi-Criteria Decision Making


Implementation of an Extended Fuzzy VIKOR Method Based on Triangular and Trapezoidal Fuzzy Linguistic Variables and Alternative Deffuzification Techniques

Many Multi-Criteria Decision Making (MCDM) problems contain information about the criteria and/or the alternatives that is either unquantifiable or incomplete. Fuzzy set theory has been successfully combined with MCDM methods to deal with imprecision. The fuzzy VIKOR method has been successfully applied in such problems. There are many extensions of this method; some of them utilize triangular fuzzy numbers, while others use trapezoidal fuzzy numbers. In addition, there are many defuzzification techniques available that are used in different variants. The use of each one of these techniques can have a substantial impact on the output of the fuzzy VIKOR method. Hence, we extend the fuzzy VIKOR method in order to allow the use of several defuzzification techniques. In addition, we allow the use of both triangular and trapezoidal fuzzy numbers. In this paper, we also present the implementation of a web-based decision support system that incorporates the fuzzy VIKOR method. Finally, an application of the fuzzy VIKOR method on a facility location problem is presented to highlight the key features of the implemented system.
Nikolaos Ploskas, Jason Papathanasiou, Georgios Tsaples

Integrating System Dynamics with Exploratory MCDA for Robust Decision-Making

The aim of this paper is to propose a process to support decision making, in which System Dynamics is combined with Multi Criteria Decision Aid methods to mitigate the limitations of the two methodologies when used alone and find robust policies. The proposed process is based on Exploratory Modeling and Analysis, a framework that allows the use of multiple methods – under different perceptions, detail, and levels of abstraction – in order to address issues of uncertainty and robustness. A case study is used to illustrate how the process can offer deeper insights and act as a valuable decision support system. Finally, it also demonstrates the potential of Exploratory Modeling and Analysis to deal with uncertainties and identify robust policies.
Georgios Tsaples, Jason Papathanasiou, Nikolaos Ploskas


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