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This article classifies petrol retail companies in Spain based on their financial ratios using the compositional data analysis (CoDA) methodology. This methodology solves the most common distributional problems encountered in the statistical analysis of financial ratios. The main purpose of this article is to show that with the CoDA methodology, accounting figures presenting low values can have a disproportional influence on classification. This problem can be attenuated by applying weighted CoDA, which is a novelty in the financial statement analysis field. The suggested weight of each accounting figure is proportional to its arithmetic mean. The results of Ward clustering show that after weighting, the contributions of the accounting figures to the total variance and to the clustering solution are more balanced, and the clusters are more interpretable. Four distinct financial profiles are identified and related to non-financial variables. Only one of the profiles represents companies in financial distress, with low turnover, low return on assets, high indebtedness, and low liquidity. Further developments include alternative weighting schemes. [ABSTRACT FROM AUTHOR]

The use of multi-criteria evaluation tools in combination with participatory approaches provides a promising framework for integrating multiple interests and perspectives in the effort to provide sustainability. However, the inclusion of diverse viewpoints requires the “compression” of complex issues, a process that is controversial. Ensuring the quality of the compression process is a major challenge, especially with regards to retaining the essential elements of the various perspectives. Based on the lessons learned during a case study that assessed sustainable management options for the Urdaibai Estuary (Basque Country-Southern Europe), we propose a process in which the explicit elicitation of weights (the prioritisation of criteria) within a participatory multi-criteria evaluation serves as a quality assurance mechanism to check the robustness of the evaluation process. The results demonstrate that diverse individual priorities can be grouped in a reduced set of social preferences by means of cluster analysis reinforced with a deliberative appraisal among a wide variety of social actors. The approach presented retains relevant information regarding extreme and sometimes irreconcilable positions, allows an explicit social sensitivity analysis of the MCE process, and enables participants to learn from and reflect upon diverse social preferences without forcing their consensus. [Copyright &y& Elsevier]

Sobriety checkpoints are not usually randomly located by traffic authorities. As such, information provided by non-random alcohol tests cannot be used to infer the characteristics of the general driving population. In this paper a case study is presented in which the prevalence of alcohol-impaired driving is estimated for the general population of drivers. A stratified probabilistic sample was designed to represent vehicles circulating in non-urban areas of Catalonia (Spain), a region characterized by its complex transportation network and dense traffic around the metropolis of Barcelona. Random breath alcohol concentration tests were performed during spring 2012 on 7596 drivers. The estimated prevalence of alcohol-impaired drivers was 1.29%, which is roughly a third of the rate obtained in non-random tests. Higher rates were found on weekends (1.90% on Saturdays and 4.29% on Sundays) and especially at night. The rate is higher for men (1.45%) than for women (0.64%) and it shows an increasing pattern with age. In vehicles with two occupants, the proportion of alcohol-impaired drivers is estimated at 2.62%, but when the driver was alone the rate drops to 0.84%, which might reflect the socialization of drinking habits. The results are compared with outcomes in previous surveys, showing a decreasing trend in the prevalence of alcohol-impaired drivers over time., (Copyright © 2014 Elsevier Ltd. All rights reserved.)