Comparing Election Methods Where Each Voter Ranks Only Few Candidates

Election rules are formal processes that aggregate voters preferences, typically to select a single candidate, called the winner. Most of the election rules studied in the literature require the voters to rank the candidates from the most to the least preferred one. This method of eliciting preferences is impractical when the number of candidates to be ranked is large. We ask how well certain election rules (focusing on positional scoring rules and the Minimax rule) can be approximated from partial preferences collected through one of the following procedures: (i) randomized-we ask each voter to rank a random subset of $\ell$ candidates, and (ii) deterministic-we ask each voter to provide a ranking of her $\ell$ most preferred candidates (the $\ell$-truncated ballot). We establish theoretical bounds on the approximation ratios and we complement our theoretical analysis with computer simulations. We find that mostly (apart from the cases when the preferences have no or very little structure) it is better to use the randomized approach. While we obtain fairly good approximation guarantees for the Borda rule already for $\ell = 2$, for approximating the Minimax rule one needs to ask each voter to compare a larger set of candidates in order to obtain good guarantees

Regional development assessment using parametric and non-parametric ranking methods: A comparative analysis of Slovenia and Croatia

In this paper we describe several regional development-assessment methods and subsequently apply them in a comparative development level analysis of the Slovenian and Croatian municipalities. The aim is to compare performance and suitability of several parametric and non-parametric ranking methods and to develop a suitable multivariate methodological framework for distinguishing development level of particular territorial units. However, the usefulness and appropriateness of various multivariate techniques for regional development assessment is generally questionable and there is no clear consensus about how to carry out such analysis. Two main methodological approaches are based on parametric and non-parametric methods, where in the former an explicit econometric model containing theory-implied causal and possibly simultaneous relationships is estimated using likelihood-based methods and formally assessed in terms of the goodness of fit and other test statistics, subsequently allowing for estimation of the development level on a metric scale, while in the later, territorial units or regions are essentially classified into clusters or groups differing in the development level, but no formal inferential methods are applied to confirm the validity of the model, or to establish the difference in the development level on a metric scale. The possible advantages of the first approach are in the existence of formal testing and evaluation procedures, as well as in producing interval ranks of the analysed units, while its disadvantages are in the lack of robustness; often unrealistic distributional assumptions; and possible invalidity of the theoretically implied causal relationships. In this paper we consider a parametric, inferential approach based on maximum likelihood estimation of the linear structural equation model with latent variables for metric-scale development ranking, and a non-parametric approach based on cluster analysis for development grouping. Our analysis is based on ten regional development variables such as income per capita, population density, age index, etc. which are similarly collected and generally compatible for both analysed countries. Within the parametric approach, a simultaneous equation econometric model is estimated and latent scores are computed for each underlying latent development variable, where three latent constructs are postulated corresponding to economic, structural and demographic development dimensions. In the non-parametric approach, a combination of Ward?s hierarchical method and K-means clustering procedure is applied to classify the territorial units. We apply both methodological frameworks to Slovenian and Croatian municipality data and assess their regional development level. We further compare the performance of both methods and show to which degree their results are compatible. Finally, we propose a unified framework based on both parametric and non-parametric methods, where clustering techniques are performed both on the original development indicators and on the computed latent scores from the structural equation model, and compare these results with the results from each of the two methods applied separately. We show that a combined parametric/non-parametric approach is superior to each approach applied individually and propose a methodological framework capable of estimating the development level of territorial units or regions on a metric scale, while in the same time preserving the robustness of the non-parametric techniques.

Multi-criteria decision analysis with probabilistic risk assessment for the management of contaminated ground water

Traditionally, environmental decision analysis in subsurface contamination scenarios is performed using cost–benefit analysis. In this paper, we discuss some of the limitations associated with cost–benefit analysis, especially its definition of risk, its definition of cost of risk, and its poor ability to communicate risk-related information. This paper presents an integrated approach for management of contaminated ground water resources using health risk assessment and economic analysis through a multi-criteria decision analysis framework. The methodology introduces several important concepts and definitions in decision analysis related to subsurface contamination. These are the trade-off between population risk and individual risk, the trade-off between the residual risk and the cost of risk reduction, and cost-effectiveness as a justification for remediation. The proposed decision analysis framework integrates probabilistic health risk assessment into a comprehensive, yet simple, cost-based multi-criteria decision analysis framework. The methodology focuses on developing decision criteria that provide insight into the common questions of the decision-maker that involve a number of remedial alternatives. The paper then explores three potential approaches for alternative ranking, a structured explicit decision analysis, a heuristic approach of importance of the order of criteria, and a fuzzy logic approach based on fuzzy dominance and similarity analysis. Using formal alternative ranking procedures, the methodology seeks to present a structured decision analysis framework that can be applied consistently across many different and complex remediation settings. A simple numerical example is presented to demonstrate the proposed methodology. The results showed the importance of using an integrated approach for decision-making considering both costs and risks. Future work should focus on the application of the methodology to a variety of complex field conditions to better evaluate the proposed methodology

An analysis of some mistakes, miracles and myths in supplier selection

This paper analyzes some consequences of formal methods and procedures for supplier selection. It argues that many mistakes and miracles may occur in frequently used procedures. Practical examples are given. In the analysis it turns out that preventing these unwanted effects from occurring may be tackled by methodological improvements. Some examples and guidelines for these are given as well. But another important point lies in the perspectives of the actors in supplier selection: governments and industry policy makers, purchasers, suppliers and (management) researchers. The analysis shows that these different actors often operate from quite different and sometimes conflicting attitudes, assumptions and principles. On the one hand this analysis leads to the conclusion that using some sort of formal approach for supplier selection may be necessary. On the other hand it clarifies the criticism on such an approach and the difficulties associated with its use. The paper concludes with recommendations and implications for policy makers, researchers, and practitioners

Management of Road Infrastructure Safety

Road Infrastructure Safety Management (RISM) refers to a set of procedures that support a road authority in decision making related to the improvement of safety on a road network. Some of these procedures can be applied to existing infrastructure, thus enabling a reactive approach; and other procedures are used in early stages of a project's life-cycle allowing a proactive approach. The objective of this paper is to provide an overview of the most well-known procedures and present a series of recommendations for successful road infrastructure safety management. The work described in the paper was completed by the IRTAD sub-working group on Road Infrastructure Safety Management and presented in detail in the respective Report. The methodology followed on this purpose included the description of the most consolidated RISM procedures, the analysis of the use of RISM procedures worldwide and the identification of possible weaknesses and barriers to their implementation, the provision of good practice examples and the contribution to the scientific assessment of procedures. Specifically, the following RISM procedures were considered: Road Safety Impact Assessment (RIA), Efficiency Assessment Tools (EAT), Road Safety Audit (RSA), Network Operation (NO), Road Infrastructure Safety Performance Indicators (SPI), Network Safety Ranking (NSR), Road Assessment Programs (RAP), Road Safety Inspection (RSI), High Risk Sites (HRS) and In-depth Investigation. Each procedure was described along with tools and data needed for its implementation as well as relevant common practices worldwide. A synthesis summarizing the key information for each procedure was also drafted. Based on a survey on 23 IRTAD member countries from worldwide, the lack of resources or tools is the most commonly stated reason for not applying a RISM procedure. This has been frequently found mainly in European countries. Another common reason is the absence of recommendations/guidelines, especially for SPI, RAP, RSI and RSA. This highlights the importance of the presence of some legislation regulating the application of the procedures. Lack of data was found important mainly for SPI, HRS and EAT. Good practices of road infrastructure safety management have been explored in order to find solutions to the issues highlighted by the survey and provide examples about how these issues have been overcome in some countries. Specifically, issues related to data, legal framework, funding, knowledge, tools and dealing with more RISM procedures were addressed. Finally, nine key messages and six recommendations for better Road Infrastructure Safety Management were developed based on the conclusions made

On procedures for measuring deprivation and living standards of societies in a multi-attribute framework

When a society's overall deprivation or living standard is assessed in a multi-attribute framework, the following procedure is often used. First, for each attribute, a summary index is constructed to reflect a society's performance in relation to this attribute. Then, an indicator of the overall performance of the society in terms of all the attributes together is constructed. This paper discusses a difficulty associated with this procedure. We show that the difficulty lies in its inability to reconcile two highly attractive ethical principles - the first reflecting a requirement of treating individuals symmetrically and the second reflecting a requirement for equity-sensitivity. This problem implies that this widely-used procedure must lead to possibly untenable conclusions, and that it is necessary to adopt alternative procedures. The alternative procedure must permit describing a society's overall deprivation or living standard as an aggregate of the comprehensive deprivations or living standards experienced by the individuals in the society. Working Paper 08-0

Risk assessment for the installation and maintenance activities of a low-speed tidal energy converter

The study presented in this paper, is part of the Deep Green project, which includes the development of a power converter/device for employment in low-speed tidal currents. It mainly focuses on the initial steps to investigate the ways on how to minimize the risks during handling, operation and maintenance (O&M) activities of the full-scale device particularly in offshore operations. As a first tep, the full-scale device offshore installation and O&M tasks are considered. The overall risk analysis and decision making methodology is presented including the Hazard Identification (HAZID) approach which is complemented with a risk matrix for various consequence categories including personnel Safety (S), Environmental impact (E), Asset integrity (A) and Operation (O). In this way, all the major risks involved in the mentioned activities are identified and actions to prevent or mitigate them are presented. The results of the HAZID analysis are also demonstrated. Finally, the last section of this paper presents the discussion, conclusions and future actions for the above-mentioned activities regarding the full-scale device

Equity and economic theory: reflections on methodology and scope

This paper provides an introduction to the recent literature on ordinal distributive justice. Its objetive is to explain the process of the mathematical analysis of fairness and to consider its potential for solving real allocative problems by means of several illustrative examples