Principle Component Analysis in Conjuction with Data Driven Methods for Sediment Load Prediction

This study investigates sediment load prediction and generalization from laboratory scale to field scale using principle component analysis (PCA) in conjunction with data driven methods of artificial neural networks (ANNs) and genetic algorithms (GAs). Five main dimensionless parameters for total load are identified by using PCA. These parameters are used in the input vector of ANN for predicting total sediment loads. In addition, nonlinear equations are constructed, based upon the same identified dimensionless parameters. The optimal values of exponents and constants of the equations are obtained by the GA method. The performance of the so-developed ANN and GA based methods is evaluated using laboratory and field data. Results show that the expert methods (ANN and GA), calibrated with laboratory data, are capable of predicting total sediment load in field, thus showing their transferability. In addition, this study shows that the expert methods are not transferable for suspended load, perhaps due to insufficient laboratory data. Yet, these methods are able to predict suspended load in field, when trained with respective field data.     

Sales force leadership during strategy implementation: a social network perspective

Many new marketing strategies falter in the execution phase where managers fail to make frontline employees fully committed to implementing the new initiatives. While formal managers can apply transformational and transactional leadership behaviors to increase salespeople’s strategy commitment, peers can also exert a great deal of informal influence on salespeople. Building on recent social network perspectives of leadership, this paper investigates the interplay between the sales manager’s leadership styles and peer effects during the implementation of a new strategy in a large sales organization. The authors find that salespeople with high network centrality but low strategy commitment not only lower their peers’ commitment but also hurt the effectiveness of a transformational manager. Specially, the influence of a central salesperson becomes stronger when the sales group has lower external connectivity. However, sales managers’ transactional leadership can decrease the non-committed central salesperson’s influence over peers.     

Talking in the present,caring for the future: Language and environment

This paper identifies a new source that explains environmental behaviour: the presence of future tense marking in language. We predict that languages that grammatically mark the future affect speakers’ intertemporal preferences and thereby reduce their willingness to address environmental problems. We first show that speakers of languages with future tense marking are less likely to adopt environmentally responsible behaviours and to support policies to prevent environmental damage. We then document that this effect holds across countries: future tense marking is an important determinant of climate change policies and global environmental cooperation. The results suggest that there may be deep and surprising obstacles for attempts to address climate change.     

European Multi Model Ensemble (EMME): A New Approach for Monthly Forecast of Precipitation

Regarding the ability of data mining algorithms for post-processing the output of climate models, and on the other hand, the successful application of multi-model ensemble approaches in climate forecasts, in this paper, some important data mining algorithms are evaluated for the monthly forecast of precipitation over Iran. For this purpose, four European climate models, from DWD, ECMWF, CMCC and Meteo-France, with six lead times, are used to be post-processed by applying four different algorithms including artificial neural networks, support vector regression, decision tree and random forests. Based on the proposed approach, 72 different models are provided for 12 months, each month with six lead times. The approach is applied for the monthly forecast of precipitation over Iran. According to the results, the neural network and random forest methods performed better than the decision tree and the support vector machine. This advantage preserved for all months of the year. Also, the proposed multi-model approach outperformed any of the individual European models.

     

Aspects of Governance and $$\hbox {CO}_2$$Emissions: A Non-linear Panel Data Analysis

The reduction of \(\hbox {CO}_2\)emissions has been at the centre of worldwide debates on environmental issues, though its inclusion as one of the millennium development goals (MDGs) by the United Nations has changed the focus of relative literature. Among many, one of the World Bank’s “recipes” to achieve a higher position toward MDGs has been to undertake reforms for a better governance. While, the majority of researches’ focus has been on one single aspect and its relationship with the environment, some studies, have simultaneously considered two governance dimensions. In this paper, we focus on the role of several aspects of governance on \(\hbox {CO}_2\)emissions. This provides us with a chance to explore the possible impacts of all aspects of governance on a more direct measure of emissions, that is different to previous researches which have focused on the indirect transmission and considered the maximum of two. Using the IV method within panel data analysis, we show that only one single aspect of governance, Control of Corruption, has a negative significant effect on \(\hbox {CO}_2\)emissions and its effect has a non-linear relationship. The non-linearity exists in both parametric and nonparametric analysis after controlling for endogeneity.     

Self-assessed vs. statistical evidence of racial discrimination: the case of indigenous Australians

This paper provides new insights on the labour market discrimination faced by indigenous Australians one of the most disadvantaged indigenous populations in developed countries. Combining two large, nationally representative datasets, we decompose the employment gap between indigenous and non-indigenous populations as of 2014–2015, and show that differences in characteristics between the two groups account for only 43% of the employment gap for females, and 23% of the gap for males. We then demonstrate that statistical measures are positively related to discrimination reports of females and negatively related to discrimination reports of males. Our findings underscore the importance of improving transparency in employment processes for addressing the issue of disadvantage of racial minorities.     

On the role of governance and health aid on child mortality: a cross-country analysis

Globally, child mortality rates continue to be unacceptably high despite improvement in child health outcomes. The role of macro level indicators, such as governance and health aid on child mortality, remains under-researched. The aim of this article is to analyse the influence of governance and health aid on child mortality using cross-country data. A negative association between governance and the mortality rate of children less than 5 years of age was found using System Generalised Method of Moments Dynamic Panel, the linkage also exists in the results of quantile and semi-parametric regression. However, as in other literature, the role of health aid on child mortality remains ambiguous.