Abstract
This paper presents a framework to facilitate the selection of the most appropriate company to be contracted among competitive bids. This framework is intended to be integrated in e-marketplaces to comply with the major technological advances in the construction industry. A novel feature of the system is that it allows bilateral evaluations between companies to better understand general contractor-subcontractor relationships and to improve the level of transparency within the construction sector. The performance assessment system incorporates other innovative features, such as the ability to specify a set of performance indicators suitable for inclusion in e-marketplaces covering three different perspectives: company reliability, operation performance, and bid attributes. The system also allows the integration of the preferences of the decision maker concerning the selection of the best company for a given work. (C) 2013 American Society of Civil Engineers.

Abstract
The purpose of this paper is to develop a robust methodology to assess municipalities' performance concerning the consumption of resources in residential buildings. The assessment is carried out at a municipal level to inform decision makers about the relative position of their municipalities compared to others. In addition, the factors associated to better levels of municipal performance are identified, and the extent of their effects is quantified. The study uses an enhanced stochastic frontier panel model based on data of energy, water and materials consumption in Lisbon municipalities during the period 2003-2009. The study reveals that the municipalities' performance has remained stable over the years, although there are considerable differences in performance among municipalities. In addition, it is concluded that municipal performance tends to improve with the environmental policy expenditure and scale size, and decline with buildings' age, population density and the proportion of buildings with private ownership.

Abstract
This paper investigates the impact of internationalization and diversification strategies on the financial performance of construction industry companies. The results obtained can guide the design of strategies to pursue company growth and achieve competitive advantage. The evaluation of companies' performance is based on the use of the Data Envelopment Analysis technique to aggregate financial indicators using optimized weights. The impact of internationalization and diversification on company performance is explored using truncated regression, controlling for the effect of contextual factors such as company age, size and time. Data Envelopment Analysis and truncated regression were complemented with bootstrapping to ensure the robustness of the results obtained. The activity of Portuguese and Spanish contractors in the period 2002 to 2011 is used as case study. The empirical results show that internationalization has a positive impact on financial performance, although this effect is only statistically significant for Spanish contractors. Diversification has a nonlinear relationship with performance, benefiting companies with either a small number of core activities or companies with a broad scope of activities.

Abstract
Urban metabolism accounts of total annual energy, water, and other resource flows are increasingly available for a variety of world cities. For local decision makers, however, it may be important to understand the variations of resource consumption within the city. Given the difficulty of gathering suburban resource consumption data for many cities, this article investigates the potential of statistical downscaling methods to estimate local resource consumption using socioeconomic or other data sources. We evaluate six classes of downscaling methods: ratio-based normalization; linear regression (both internally and externally calibrated); linear regression with spatial autocorrelation; multilevel linear regression; and a basic Bayesian analysis. The methods were applied to domestic energy consumption in London, UK, and our results show that it is possible to downscale aggregate resource consumption to smaller geographies with an average absolute prediction error of around 20%; however, performance varies widely by method, geography size, and fuel type. We also show how mapping these results can quickly identify districts with noteworthy resource consumption profiles. Further work should explore the design of local data collection strategies to enhance these methods and apply the techniques to other urban resources such as water or waste.

Abstract
Local actions are seen as of major importance for the achievement of climate change mitigation targets. In the past few years, the number of local action plans towards climate change mitigation has been increasing, and it is essential to analyze their contribution to the achievement of global targets. Even if the relationship between local action plans and the reduction of energy use and GHG emissions is often assumed, this has not yet been validated nor quantified by empirical studies involving a large number of municipalities. Thus, the aim of this paper is to. perform an empirical analysis on the link between local action plans and energy use and GHG emissions. The analysis is composed by a test of hypothesis and a regression analysis, performed for the municipalities of three European countries Portugal, Sweden and United Kingdom. The main conclusion is that, in the context of these three countries, the analysis performed was not able to detect a significant impact related to the existence of local plans on GHG emissions. From the panel data regression analysis, it was possible to confirm that external factors, not directly related to local climate change mitigation actions, have a significant impact on GHG emissions.

Abstract
Empirical data for residential indoor temperature and its determinants have important implications for policymakers in terms of the assessment of thermal comfort, health of occupants and the use for supporting energy demand models. With the purpose of advancing this knowledge, the indoor temperatures of 141 households in the Northern Portugal were measured at a half-hourly basis during the winter of 2013-2014. The observed mean winter daily indoor temperature at the occupied period was 14.9 degrees C for the bedrooms and 16.6 degrees C for the living rooms. The results show that indoor temperatures are significantly below the comfort levels generally accepted, which could be an indication of future potential rebound effects. Results also reinforce the idea that 'cold homes' during winter season are a reality even in the southern European countries. Models for predicting the daily mean bedroom and living room temperature were developed using an enhanced linear regression with panel-corrected standard errors. The results showed that climatic conditions, and especially building characteristics, affect significantly the bedroom and living room's indoor temperatures.