Abstract
A good relationship between companies and customers is a crucial factor of competitiveness. Market segmentation is a key issue for companies to develop and maintain loyal relationships with customers as well as to promote the increase of company sales. This paper proposes a method for market segmentation in retailing based on customers' lifestyle, supported by information extracted from a large transactional database. A set of typical shopping baskets are mined from the database, using a variable clustering algorithm, and these are used to infer customers lifestyle. Customers are assigned to a lifestyle segment based on their purchases history. This study is done in collaboration with an European retailing company.

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This study develops a framework that combines different management science methods to provide insights concerning the performance of retailing stores. First, the framework enables to specify appropriate targets for stores of a retail network using data envelopment analysis. This involves comparing stores within homogenous groups, that is, supermarkets and hypermarkets. Second, the framework compares the overall performance of these two groups. This requires the combined use of a Malmquist-type index and statistical tests. This index is decomposed into sub-indices for comparing the differences between groups in terms of the efficiency spread in each group of stores and the productivity differences between the best-practice frontiers spanned by the benchmark stores from each group. The hypothesis tests are used to verify if the differences between groups captured by the sub-indices are statistically significant. Journal of the Operational Research Society (2012) 63, 631-645. doi:10.1057/jors.2011.63 Published online 13 July 2011

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This paper describes a performance assessment of Portuguese secondary schools using data envelopment analysis (DEA). The assessment adopts a perspective where schools are viewed as promoting students achievement given their characteristics in terms of academic abilities and socio-economic background. Our sample comprised all secondary schools in Portugal with both basic and secondary education levels. Two types of DEA analysis are performed: one using an output-oriented model that restricts output (exam scores) weights to be linked to the number of students that have done that exam in the school, and the other using a model that restricts factor weights to be equal for all schools. In this model the weight restrictions are linked to the total number of exams done nationally. The first model is well suited for identifying worst performing schools and to assess schools that may specialize in certain subjects, whereas the latter is best suited for improving discrimination between best performing schools when pursuing the identification of benchmarks, as well as to construct performance rankings. Journal of the Operational Research Society (2012) 63, 1098-1115. doi: 10.1057/jors.2011.114 Published online 16 November 2011

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The purpose of the paper is to examine trends in the performance of the Portuguese construction industry, and identify the factors that promote excellence and innovation in the sector. From a methodological perspective, this study enhances the construction of composite indicators using the principles of the "benefit of the doubt" weighting. This involves the use of Data Envelopment Analysis to estimate weights for aggregating the key performance indicators of the construction companies. The paper also proposes a new DEA-based method to assess innovation within an industry, identifying the innovative companies and the extent of innovation. The determinants of good performance and innovation are examined using regression techniques and the statistical significance of the results is ensured by the use of bootstrapping. The study reveals that the Portuguese construction industry experienced a remarkable performance improvement during the 1990s, but this growth trend in performance slowed down in recent years. It is concluded that company performance is strongly affected by the national economic context, and that small specialized companies and large contractors tend to achieve the best performance levels.

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