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Über dieses Buch

This book constitutes the refereed proceedings of the Second International Conference on Decision Support Systems Technology, ICDSST 2016, held in Plymouth, UK, May 23-25. The theme of the event was “Decision Support Systems Addressing Sustainability & Societal Challenges”, organized by the EURO (Association of European Operational Research Societies) working group of Decision Support Systems (EWG-DSS).

The 15 full papers presented in this book were selected out of 51 submissions after being carefully reviewed by internationally experts from the ICDSST 2016 Program Committee and external invited reviewers. The selected papers are representative of current and relevant research activities in various areas of decision support systems, such as sustainability and societal challenges; risk management and project portfolio management; business intelligence and knowledge management; and technologies to improve system usability.



DSS Applications Addressing Sustainability and Societal Challenges


A Decision Support System for Multiple Criteria Alternative Ranking Using TOPSIS and VIKOR: A Case Study on Social Sustainability in Agriculture

TOPSIS and VIKOR are two well-known and widely-used multiple attribute decision making methods. Many researchers have compared the results obtained from both methods in various application domains. In this paper, we present the implementation of a web-based decision support system that incorporates TOPSIS and VIKOR and allows decision makers to compare the results obtained from both methods. Decision makers can easily upload the input data and get thorough illustrative results. Moreover, different techniques are available for each step of these methods. A real-world case study on social sustainability in agriculture is presented to highlight the key features of the implemented system. The aim of this study is to classify and rank the rural areas of Central Macedonia in Northern Greece using a set of eight social sustainability indicators.
Jason Papathanasiou, Nikolaos Ploskas, Thomas Bournaris, Basil Manos

An Operations Research-Based Morphological Analysis to Support Environmental Management Decision-Making

In this paper the authors present a meta-model aiming to support decision-makers that wish to know more about how to use systems models to cope with the integration of environmental concerns into the company strategy. This is made by using a General Morphological Analysis (GMA) to bridge the gap between Operations Research (OR) analysts, decision-makers and stakeholders, making all of them part of the problem structuring and formulation process, particularly in societal issues like the environmental ones. The novelty of this approach is two-fold: (i) there are no examples in literature of a GMA research that address a linkage between environmental practices, strategic objectives, and the integration of stakeholders in the decision-making process at the level of a company; (ii) there is no GMA that had covered all the phases of a decision-making problem (problem definition, problem analysis and problem solving) in such a context.
Maria de Fátima Teles, Jorge Freire de Sousa

Searching for Cost-Optimized Strategies: An Agricultural Application

We consider a system modeled as a set of interacting components evolving along time according to explicit timing constraints. The decision making problem consists in selecting and organizing actions in order to reach a goal state in a limited time and in an optimal manner, assuming actions have a cost. We propose to reformulate the planning problem in terms of model-checking and controller synthesis such that the state to reach is expressed using a temporal logic. We have chosen to represent each agent using the formalism of Priced Timed Game Automata (PTGA) and a set of knowledge. PTGA is an extension of Timed Automata that allows the representation of cost on actions and the definition of a goal (to reach or to avoid). This paper describes two algorithms designed to answer the planning problem on a network of agents and proposes practical implementation using model-checking tools that shows promising results on an agricultural application: a grassland based dairy production system.
Christine Largouet, Yulong Zhao, Marie-Odile Cordier

Enhancing Antenatal Clinics Decision-Making Through the Modelling and Simulation of Patients Flow by Using a System Dynamics Approach. A Case for a British Northwest Hospital

In the past 60 years, the maternal mortality rate in the United Kingdom has dropped considerably. However, the number of high-risk pregnancies including those complicated by pre-existing maternal health problems e.g. diabetes or lifestyle illnesses e.g. obesity has resulted in an increased demand on obstetric outpatient management of pregnancy at British National Health Service hospitals. In addition, patients also expect better access and convenient appointments in the antenatal clinic. Despite on-going work in these areas, long delays in clinic waiting rooms continue to be a great source of frustration for patients and staff. These delays have a considerable social cost to the economy and a financial cost to the health economy. Therefore, this paper considers a realistic study for supporting decision-makers in antenatal clinics in British northwest hospitals by using a system dynamics approach through causal-loop diagrams. The focus is to enhance the performance of the clinic, by understanding the flow of patients though a hospital clinic thereby aiming to reduce waiting times for patients.
Jorge E. Hernandez, Ted Adams, Hossam Ismail, Hui Yao

Fuzzy Inference Approach to Uncertainty in Budget Preparation and Execution

In recent times, diverse uncertainties in the global economic environment have made it difficult for most countries to meet their financial obligations. For example, according to statistics from European Commission, 24 out of 29 recorded European Economic Area member countries had budget deficits in 2014. Therefore through modelling and simulations, this paper proposes flexible decision support schemes that could be used in managing the uncertainties in budgeting. Rather than entirely relying on estimates of anticipated revenues (which are uncertain and difficult to predict) in government budgeting, the scheme proposes incorporating fuzzy inference systems (which is able to capture both the present and future uncertainty) in predicting the anticipated revenues and consequently, in proposing government expenditures. The accuracy of fuzzy rule base helps in mitigating adverse effects of uncertainties in budgeting. We illustrated the proposed scheme with a case study which could easily be adapted and implemented in any budgeting scenarios.
Festus Oluseyi Oderanti

DSS to Support Business Resilience/Risk Management and Project Portfolio Management


Detectability Based Prioritization of Interdependent Supply Chain Risks

Supply chain risks must be assessed in relation to the complex interdependent interaction between these risks. Generally, risk registers are used for assessing the importance of risks that treat risks in silo and fail to capture the systemic relationships. Limited studies have focused on assessing supply chain risks within the interdependent network setting. We adapt the detectability feature from the Failure Modes and Effects Analysis (FMEA) and integrate it within the theoretically grounded framework of Bayesian Belief Networks (BBNs) for prioritizing supply chain risks. Detectability represents the effectiveness of early warning system in detecting a risk before its complete realization. We introduce two new risk measures and a process for prioritizing risks within a probabilistic network of interacting risks. We demonstrate application of our method through a simple example and compare results of different ranking schemes treating risks as independent or interdependent factors. The results clearly reveal importance of considering interdependency between risks and incorporating detectability within the modelling framework.
Abroon Qazi, John Quigley, Alex Dickson, Şule Önsel Ekici, Barbara Gaudenzi

E-Commerce Development Risk Evaluation Using MCDM Techniques

Electronic commerce (EC) development takes place in a complex and dynamic environment that includes high levels of risk and uncertainty. This paper proposes a new method for assessing the risks associated with EC development using multi-criteria decision-making techniques A model based on the analytic hierarchy process (AHP) and the technique for order of preference by similarity to ideal solution (TOPSIS) is proposed to assist EC project managers and decision makers in formalizing the types of thinking that are required in assessing the current risk environment of their EC development in a more systematic manner than previously. The solution includes the use of AHP for analyzing the problem structure and determining the weights of risk factors. The TOPSIS technique helps to obtain a final ranking among projects, and the results of an evaluation show the usefulness performance of the method.
Salem Alharbi, Mohsen Naderpour

Scaling Issues in MCDM Portfolio Analysis with Additive Aggregation

This paper discusses a typically scaling issue, which can arise in the context of multicriteria (MCDM) portfolio analysis: the portfolio size effect. By analyzing previous application this issue may happen by the impact of an additive aggregation for the standard portfolio construction model. Thus, it has been shown that the scaling issue may arise even when baseline correction procedures are adopted and this paper suggests that additionally to the baseline adjustment, a ratio scale correction may be necessary, depending on the combination of values and constraints considered by the problem.
Carolina Lino Martins, Jonatas Araujo de Almeida, Mirian Batista de Oliveira Bortoluzzi, Adiel Teixeira de Almeida

DSS Technologies Underpinned by Business Intelligence and Knowledge Management


A Knowledge Based System for Supporting Sustainable Industrial Management in a Clothes Manufacturing Company Based on a Data Fusion Model

In this paper we propose a knowledge based system (KBS), based on smart objects and a data fusion model to support industrial management decision making applied to a clothes manufacturing enterprise. The management processes cover factory-production levels to higher decision-making levels. Therefore, the proposed KBS contributes to solving different kind of decision problems, including factory supervision, production planning and control, productivity management, real-time monitoring, and data acquisition and processing. The web access via different middleware devices and tools at different process levels, along with the use of integrated algorithms, decision methods, and smart objects, promote an optimized use of knowledge and resources. In this paper the proposed KBS is introduced and an example of its use is illustrated with an example of a clothes manufacturing resources selection, using the embedded dynamic multi-criteria fusion model.
Gasper G. Vieira, Leonilde R. Varela, Rita A. Ribeiro

Knowledge Management as an Emerging Field of Business Intelligence Research: Foundational Concepts and Recent Developments

A number of prior studies have been conducted to assess the extent of progress within these stages in the BI area. Among them, a study of Eom [1] has provided bibliometric evidence that the decision support system has made meaningful progress over the past three and a half decades (1969–2004). The primary data for this study were gathered from a total of 498 citing articles in the BI/DSS area over the past eight years (2005–2012). This study, based on author cocitation analysis (ACA), presents two important findings. First, the empirical consensus of BI researchers reveals that the focus of business intelligence research is shifting to knowledge management and data mining. Second, since ACA is a supporting quantitative tool that must be used with further qualitative analysis of bibliographic data, we examined the foundational concepts of knowledge management provided by the most influential scholars and their most frequently cited publications.
Sean B. Eom

Updating Business Intelligence and Analytics Maturity Models for New Developments

Recent developments such as real-time, social, predictive and cloud business intelligence and analytics (BI&A) introduce extra ways for organisations to obtain insight and business value from an expanded range of data. Organisations have struggled with the strategy, implementation, and measurement of their BI&A efforts, and a series of business intelligence maturity models (BIMMs) has been introduced to identify strengths and weaknesses of their BI&A situation, and assist remedial action. These BIMMs are however seen to be incomplete and outdated and do not accommodate recent BI&A developments. This study suggests how BIMMs should be modified to cater for these developments. Existing BIMMs were examined, and interviews conducted with BI&A professionals knowledgeable about BIMMs and recent BI&A changes. Findings suggested that existing BIMM dimensions should be modified in various ways to cater for the recent changes in BI&A. In addition, project management was identified as a new BIMM dimension.
Louis Muller, Mike Hart

A Novel Collaborative Approach for Business Rules Consistency Management

This paper presents an approach based on ontology and agents. The major objective is to automatically manage the consistency of business rules introduced by the experts during the capitalization of business rules process as part of a collaborative system dedicated to experts. The Evaluator agent is at the heart of our functional architecture, its role is to detect the problems that may arise in the consistency management module and provide a solution to these problems in order to validate the accuracy of business rules. It uses the knowledge represented in the domain ontology. We exploit the possibilities of TERMINAE method to represent the company’s business model and manage the consistency of the rules that are introduced by business experts. The suggested approach treats here the cases of contradiction, redundancy, invalid rules, the domain violation and the rules never applicable. We conducted some experiments to test the feasibility of our approach.
Nawal Sad Houari, Noria Taghezout

Knowledge Sharing and Innovative Corporate Strategies in Collaborative Relationships: The Potential of Open Strategy in Business Ecosystems

Knowledge is a central resource in gaining competitive advantage. Sharing of knowledge between partners in collaboration has been an important research focus in the area of strategic management. In different collaborative structures, the determinants and capabilities knowledge sharing differ, as do the strategies employed, the positions taken and the roles played. The following conceptual work provides an insight into how knowledge is shared between partners, how knowledge is influenced by the partners’ environment and their capabilities; depending the position they take and the roles they play.
Anna Wulf, Lynne Butel

DSS Technology Improving System Usability and Feasibility


Developing Innovative Tool to Enhance the Effectiveness of Decision Support System

This research centres on Usability Evaluation Methods (UEMSs) with the aim of supporting developers’ decisions in the use of learning resources in achieving efficient usable system design. The suggestion is made pertaining to a new usability evaluation model dEv (stand for Design Evaluation) with the objective to support decisions to overcome three key obstacles: firstly, the involvement of users in the preliminary stages of the development process; (2) developers’ mind set-related issues as a result of either their lack of UEMS or the provision of too many; and (3) the complete lack of understanding surrounding UEMS importance. An experimental approach was applied in addition to a survey-based questionnaire in an effort to examining the issues pertaining to UEMS. Empirical works were carried out with system developers in order to test the dEv, the results of which have been presented from the empirical study to support various considerations, such as: system developers’ decisions and their involvement in the earlier phases of the design of systems; the gathering of specifications and end-users’ feedback; and enhancing usability evaluation learning capacity.
Fahad Almansour, Liz Stuart

How to Support Decision Making of Local Government in Prioritising Policy Menu Responding to Citizens’ Views: An Exploratory Study of Text Mining Approach to Attain Cognitive Map Based on Citizen Survey Data

It has been on the political agenda for the local governments how to satisfy their citizens to enhance their commitment and contribution to the communities. Especially in this ageing population era with tight fiscal conditions, it is essential for the government to know the prioritised policy menu in realising citizen satisfaction. This study aims to explore an applicable system based on citizen survey result. In our study, following literature review, we conducted focus group discussions to explore citizens’ willingness to participate in local policy design, which leads us to be convinced that some activated citizens are supportive to the local governmental policy decision. Based on this qualitative result, we tried to make a cognitive map which indicated which policy fields are prioritised by citizens. Throughout this procedure, we validate the feasible practice to support local governmental decision making based on the result of citizen survey.
Hiroko Oe, Yasuyuki Yamaoka, Eizo Hideshima


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