A decision support methodology to enhance the competitiveness of the Turkish automotive industry

This is the post-print (final draft post-refereeing) version of the article. Copyright @ 2013 Elsevier B.V. All rights reserved.Three levels of competitiveness affect the success of business enterprises in a globally competitive environment: the competitiveness of the company, the competitiveness of the industry in which the company operates and the competitiveness of the country where the business is located. This study analyses the competitiveness of the automotive industry in association with the national competitiveness perspective using a methodology based on Bayesian Causal Networks. First, we structure the competitiveness problem of the automotive industry through a synthesis of expert knowledge in the light of the World Economic Forum’s competitiveness indicators. Second, we model the relationships among the variables identified in the problem structuring stage and analyse these relationships using a Bayesian Causal Network. Third, we develop policy suggestions under various scenarios to enhance the national competitive advantages of the automotive industry. We present an analysis of the Turkish automotive industry as a case study. It is possible to generalise the policy suggestions developed for the case of Turkish automotive industry to the automotive industries in other developing countries where country and industry competitiveness levels are similar to those of Turkey

A Review and Classification of Approaches for Dealing with Uncertainty in Multi-Criteria Decision Analysis for Healthcare Decisions

Multi-criteria decision analysis (MCDA) is increasingly used to support decisions in healthcare involving multiple and conflicting criteria. Although uncertainty is usually carefully addressed in health economic evaluations, whether and how the different sources of uncertainty are dealt with and with what methods in MCDA is less known. The objective of this study is to review how uncertainty can be explicitly taken into account in MCDA and to discuss which approach may be appropriate for healthcare decision makers. A literature review was conducted in the Scopus and PubMed databases. Two reviewers independently categorized studies according to research areas, the type of MCDA used, and the approach used to quantify uncertainty. Selected full text articles were read for methodological details. The search strategy identified 569 studies. The five approaches most identified were fuzzy set theory (45 % of studies), probabilistic sensitivity analysis (15 %), deterministic sensitivity analysis (31 %), Bayesian framework (6 %), and grey theory (3 %). A large number of papers considered the analytic hierarchy process in combination with fuzzy set theory (31 %). Only 3 % of studies were published in healthcare-related journals. In conclusion, our review identified five different approaches to take uncertainty into account in MCDA. The deterministic approach is most likely sufficient for most healthcare policy decisions because of its low complexity and straightforward implementation. However, more complex approaches may be needed when multiple sources of uncertainty must be considered simultaneousl

A Review and Classification of Approaches for Dealing with Uncertainty in Multi-Criteria Decision Analysis for Healthcare Decisions

The Author(s) 2015. This article is published with open access at Springerlink.com Abstract Multi-criteria decision analysis (MCDA) is increasingly used to support decisions in healthcare involving multiple and conflicting criteria. Although uncertainty is usually carefully addressed in health eco-nomic evaluations, whether and how the different sources of uncertainty are dealt with and with what methods in MCDA is less known. The objective of this study is to review how uncertainty can be explicitly taken into account in MCDA and to discuss which approach may be appro-priate for healthcare decision makers. A literature review was conducted in the Scopus and PubMed databases. Two reviewers independently categorized studies according to research areas, the type of MCDA used, and the approach used to quantify uncertainty. Selected full text articles wer

Risk Quadruplet: Integrating Assessments of Threat, Vulnerability, Consequence, and Perception for Homeland Security and Homeland Defense

Risk for homeland security and homeland defense is often considered to be a function of threat, vulnerability, and consequence. But what is that function? And are we defining and measuring these terms consistently? Threat, vulnerability, and consequence assessments are conducted, often separately, and data from one assessment could be drastically different from that of another due to inconsistent definitions of terms and measurements, differing data collection methods, or varying data sources. It has also long been a challenge to integrate these three disparate assessments to establish an overall picture of risk to a given asset. Further, many agencies conduct these assessments and there is little to no sharing of data, methodologies, or results vertically (between federal, state, and local decision-makers) or horizontally (across the many different sectors), which results in duplication of efforts and conflicting risk assessment results. Obviously, risk is a function of our perceptions and those perceptions can influence our understanding of threat, vulnerability, and consequence. Some assessments rely on perceptions (elicited from subject matter experts) in order to qualify or quantify threat, vulnerability, and consequence. Others exclude perception altogether, relying on objective data, if available. Rather than fault the subjectivity of our perceptions, or muddle objective assessments with personal opinions, it makes sense to embrace our perceptions, but segregate them as a unique component of risk. A risk quadruplet is proposed to systematically collect and integrate assessments of threat, vulnerability, consequence, and perception, such that each dimension can be explored uniquely, and such that all four components can be aggregated into an overall risk assessment in a consistent, transparent, traceable, and reproducible manner. The risk quadruplet draws from the fields of homeland security, homeland defense, systems engineering, and even psychology to develop a model of risk that integrates all four assessments using multicriteria decision analysis. The model has undergone preliminary validation and has proven to be a viable solution for ranking assets based on the four proposed components of risk

Deliberation, Representation, Equity

"What can we learn about the development of public interaction in e-democracy from a drama delivered by mobile headphones to an audience standing around a shopping center in a Stockholm suburb? In democratic societies there is widespread acknowledgment of the need to incorporate citizens’ input in decision-making processes in more or less structured ways. But participatory decision making is balancing on the borders of inclusion, structure, precision and accuracy. To simply enable more participation will not yield enhanced democracy, and there is a clear need for more elaborated elicitation and decision analytical tools. This rigorous and thought-provoking volume draws on a stimulating variety of international case studies, from flood risk management in the Red River Delta of Vietnam, to the consideration of alternatives to gold mining in Roșia Montană in Transylvania, to the application of multi-criteria decision analysis in evaluating the impact of e-learning opportunities at Uganda's Makerere University. Editors Love Ekenberg (senior research scholar, International Institute for Applied Systems Analysis [IIASA], Laxenburg, professor of Computer and Systems Sciences, Stockholm University), Karin Hansson (artist and research fellow, Department of Computer and Systems Sciences, Stockholm University), Mats Danielson (vice president and professor of Computer and Systems Sciences, Stockholm University, affiliate researcher, IIASA) and Göran Cars (professor of Societal Planning and Environment, Royal Institute of Technology, Stockholm) draw innovative collaborations between mathematics, social science, and the arts. They develop new problem formulations and solutions, with the aim of carrying decisions from agenda setting and problem awareness through to feasible courses of action by setting objectives, alternative generation, consequence assessments, and trade-off clarifications. As a result, this book is important new reading for decision makers in government, public administration and urban planning, as well as students and researchers in the fields of participatory democracy, urban planning, social policy, communication design, participatory art, decision theory, risk analysis and computer and systems sciences.

Deliberation, Representation, Equity: Research Approaches, Tools and Algorithms for Participatory Processes

In democratic societies there is widespread acknowledgment of the need to incorporate citizens’ input in decision-making processes in more or less structured ways. But participatory decision making is balancing on the borders of inclusion, structure, precision and accuracy. To simply enable more participation will not yield enhanced democracy, and there is a clear need for more elaborated elicitation and decision analytical tools. This rigorous and thought-provoking volume draws on a stimulating variety of international case studies, from flood risk management in the Red River Delta of Vietnam, to the consideration of alternatives to gold mining in Roșia Montană in Transylvania, to the application of multi-criteria decision analysis in evaluating the impact of e-learning opportunities at Uganda's Makerere University. This book is important new reading for decision makers in government, public administration and urban planning, as well as students and researchers in the fields of participatory democracy, urban planning, social policy, communication design, participatory art, decision theory, risk analysis and computer and systems sciences

Forging Wargamers

How do we establish or improve wargaming education, including sponsors, participants, and future designers? The question stems from the uncomfortable truth that the wargaming discipline has no foundational pipeline, no established pathway from novice to master. Consequently, the wargaming community stands at a dangerous precipice at the convergence of a stagnant labor force and a patchwork system of passing institutional war-gaming knowledge. Unsurprisingly, this can lead to ill-informed sponsors, poorly scoped wargames, an unreliable standard of wargaming expertise, and worst of all, risks the decline of wargaming as an educational and analytical tool. This fundamental challenge is a recurring theme throughout this volume and each author offers their own perspective and series of recommendations

Wargames as Data: Addressing the Wargamer's Trilemma

Policymakers often want the very best data with which to make decisions--particularly when concerned with questions of national and international security. But what happens when this data is not available? In those instances, analysts have come to rely on synthetic data-generating processes--turning to modeling and simulation tools and survey experiments among other methods. In the cyber domain, where empirical data at the strategic level are limited, this is no different--cyber wargames are quickly becoming a principal method for both exploring and analyzing the security challenges posed by state and non-state actors in cyberspace. In this chapter, we examine the design decisions associated with this method.Comment: 3 figure