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This study sought to examine the relation of cultural practices and values with favoritism and nepotism/cronyism. Additionally, this study's purpose was also to examine how trust mediates the relation between culture and favoritism.

Correlations were used for exploratory investigation into the bivariate relations between culture and favoritism and nepotism/cronyism across 97 cultures. Hierarchical linear regression analyses were then conducted to examine the cultural correlates of favoritism and nepotism/cronyism holding all other variables constant. Lastly, partial least squares structural equation modeling was used to examine the mediating role of societal levels of trust.

Bivariate correlations showed that collectivism, familism, uncertainty avoidance, and power distance are positive correlates of both favoritism and nepotism/cronyism. Institutional collectivism, future orientation and trust, on the other hand, were negative correlates of favoritism and nepotism/cronyism. Uncertainty avoidance and trust were key correlates of favoritism while familism and future orientation were key correlates of nepotism/cronyism. Trust fully mediated the relation between culture and favoritism but did not mediate the relation between culture and nepotism/cronyism.

This study adds to the current body of literature on culture and favoritism. Notably, the findings regarding different key cultural correlates with respect to favoritism and nepotism/cronyism provide valuable implications for expanding our understanding of the psychological and social nuances of favoritism. Specifically, favoritism in transactions and interactions with those not bound by social commitment relationships may be explained by beliefs while interactions with those with social relationships (e.g., family and friends) may be explained by preferences.

Recent developments in neuroscience have generated great expectations in the education world globally. However, building a bridge between brain science and education has been hard. Educational researchers and practitioners more often than not hold unrealistic images of neuroscience, some naively positive and others blindly negative. Neuroscientist looking at how the brain reacts and changes during mental tasks involving reading or mathematics usually discuss education as some constant and undifferentiated “social environment” of the brain, either assuming it to be a “black box” or evoking an image of perfect schooling and full access to it. In this review, we claim that a more productive and realistic relationship between neuroscience and the comparative study of education can be thought about in terms of the hypothesis that formal education is having a significant role in the cognitive and neurological development of human populations around the world. We review research that supports this hypothesis and implications for future studies.

The purpose of this study is to analyze the effect of China’s potential domestic emission control area (DECA) with 0.1 per cent sulphur limit on sulphur emission reduction.

The authors calculate the fuel cost of a direct path within the DECA and a path that bypasses the DECA for ships that sail between two Chinese ports in view of the DECA. Ships adopt the path with the lower cost and the resulting sulphur dioxide (SO₂) emissions can be calculated. They then conduct sensitivity analysis of the SO₂ emissions with different values of the parameters related to sailing distance, fuel price and ships.

The results show that ships tend to detour to bypass the DECA when the distance between the two ports is long, the ratio of the price of low sulphur fuel and that of high sulphur fuel is high and the required time for fuel switching is long. If the time required for fuel switching is less than 12 h or even 24 h, it can be anticipated that a large number of ships will bypass the DECA, undermining the SO₂ reduction effect of the DECA.

This study points out the size and shape difference between the emission control areas in Europe and North America and China’s DECA affects ships’ path choice and SO₂ emissions.

Smart grid is an integration between traditional electricity grid and communication systems and networks. Providing reliable services and functions is a critical challenge for the success and diffusion of smart grids that needs to be addressed. The purpose of this study is to determine the critical criteria that affect smart grid reliability from the perspective of users and investigate the role big data plays in smart grid reliability.

This study presents a model to investigate and identify criteria that influence smart grid reliability from the perspective of users. The model consists of 12 sub-criteria covering big data management, communication system and system characteristics aspects. Multi-criteria decision-making approach is applied to analyze data and prioritize the criteria using the fuzzy analytic hierarchy process based on the triangular fuzzy numbers. Data was collected from 16 experts in the fields of smart grid and Internet of things.

The results show that the “Big Data Management” criterion has a significant impact on smart grid reliability followed by the “System Characteristics” criterion. The “Data Analytics” and the “Data Visualization” were ranked as the most influential sub-criteria on smart grid reliability. Moreover, sensitivity analysis has been applied to investigate the stability and robustness of results. The findings of this paper provide useful implications for academicians, engineers, policymakers and many other smart grid stakeholders.

The users are not expected to actively participate in smart grid and its services without understanding their perceptions on smart grid reliability. Very few works have studied smart grid reliability from the perspective of users. This study attempts to fill this considerable gap in literature by proposing a fuzzy model to prioritize smart grid reliability criteria.