Abstract
Innovation is a driver of economic growth, wealth and prosperity. On the other hand, corruption emerges as a worldwide problem responsible for sapping resources, inequality, human suffering and poverty. This study hypothesizes that national culture, measured using Hofstede 's six cultural dimensions, have an impact on corruption and innovation, and that highly corrupt nations are less innovative. Data were obtained from Hofstede's, Transparency International, and Global Innovation websites for the year 2012. The findings support the claim that most national culture aspects have an impact on corruption, although their impact on innovation is less measurable. Corruption was found to have a strong and negative effect on innovation. Our results draw attention to the usefulness of Hofstede's six-dimension framework in research and the need for further analysis on how corruption influences innovation through mechanisms other than national culture.

Abstract
This study analyzes Standard & Poor’s 500 Index top 250 companies’ responses to Bloomberg’s disclosed calculations of CEO pay ratios. The results suggest that CEO pay ratios, CEO compensations and average worker compensations do not seem to be related to the decision to respond. They also indicate that many of the corporations have adopted a strategy of avoiding the issue or deflecting attention from it by either choosing not to respond or criticizing the technicalities of the calculation of the CEO pay ratios. Corporations that responded largely conceptualize and communicate the rationale for high executive compensation in performance-driven language.

Abstract
The adoption of electric vehicles (EVs) on a large scale can lead to significant social and economic benefits. The effort of promoting the use of EVs in road transportation is essential to meet the climate change targets and manage the ever unstable prices of perilously diminishing fossil fuels. On the other hand, there are still many uncertainties in the market regarding the acceptability of EVs by the final consumer. In this paper the effect of high penetration of EVs on thermal ageing of a real residential distribution transformer, part of an isolated electric grid, is analysed. A weekend scenario conditioned by off-peak tariff is studied. A transformer thermal model is used to estimate the hot-spot temperature (?h) and top-oil temperature (?o) given the load ratio in Sao Miguel, a Portuguese Island. Real data are utilised for the main inputs of the model, i.e. transformer parameters, residential load, peak and off-peak tariffs and EV parameters. Conclusions are finally drawn. © 2016 IEEE.

Abstract
Olive trees are one of the most economically important perennial crops in Portugal. During the last decade, the Alentejo olive-growing region has suffered a significantly change in the crop production system, with the regional pollen index (RPI) and olive fruit production registering a significant growth. The aim of this study was to ascertain the utility of this highly variable production and pollen data in crop forecasting modeling. Airborne pollen was sampled using a Cour-type trap from 1999 to 2015. A linear regression model fitted with the regional pollen index as the independent variable showed an accuracy of 87% in estimating olives fruit production in Alentejo. However, the average deviation between observed and modeled production was 32% with half of the tested years presenting deviations between 36 and 66%. The low accuracy of this model is a consequence of the great overall variation and significant upward trend observed in both the production and the RPI dataset that conceal the true association between these variables. In order to overcome this problem, a detrend procedure was applied to both time series to remove the trend observed. The regression model fitted with the fruit production and the RPI detrended data showed a lowest forecasting accuracy of 63% but the average deviation between observed and modeled production decrease to 14% with a maximum deviation value of 33%. This procedure allows focusing the analysis on the production fluctuations related to the biological response of the trees rather than with the changes in the production system.

Abstract
This article seeks to add to the body of knowledge on the role played by brand experience and its relationship with satisfaction, trust and service quality in the development of loyalty. Structural Equation Modelling (sem) is used to analyze 690 telecommunications multiple-play users in the Portuguese telecommunications market. Our conclusions show that brand experiences can be used to generate loyalty, trust and quality perceptions; although satisfaction was confirmed to be the main loyalty predictor, service quality has an important indirect effect. In order to build customer loyalty, marketers must manage brand experiences, service quality, satisfaction and trust. Brand experiences can be explored as a way to differentiate services, to change customers’ perceptions toward a brand and, ultimately, lead to customer retention. Furthermore, providing reliable services is of the utmost importance for service providers.

Abstract
The present article proposes a mathematical decision support system model to measure the performance of incubated technology-based firms (TBFs) suppliers. The research was conducted based on three steps: (1) a literature review, in order to parameterise the research in relation to the theme; (2) the construction of a measuring system, based on the presumptions permeated by the analytic hierarchy process (AHP); and (3) the application of the system at three companies. The findings demonstrated the mathematical modelling developed is capable of providing satisfactory results to the reality of the sector studied, presenting the situation of the suppliers evaluated, independent of the nature of the indicated critical success factors (CSFs). Also, this tool supports companies by providing a strong foundation to organise the information regarding the service level delivered by each supplier, according to previous research on the theme.