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The phenomenon of corporate social responsibility (CSR) is an ever-evolving concept due to its multidimensionality. However, a plethora of studies have investigated CSR to achieve different organizational-related objectives, and its potential link to shape employee’s extra-role behavior, especially employee pro-environmental behavior (EB) in the era of Industry 4.0, is underexplored in the literature. To bridge this gap, the current study aims to explain the relationship between CSR and EB with the mediating role of ethical leadership (EL) in the banking sector of Pakistan. The data of the current survey were collected (n = 459) from different banking employees within the city of Lahore through a self-administered questionnaire (paper–pencil technique). The hypotheses were validated through the structural equation modeling (SEM) technique in AMOS. The empirical results of the current study confirmed that CSR positively relates to EB, and EL partially mediates this relationship. These findings are helpful for professionals to realize the significance of CSR and EL to shape EB in order to mitigate the environmental footprint of an organization.

The global focus on the use of renewable energy resources was mainly reignited by the signing of the Kyoto Protocol Agreement in 1997. Since then, the world has seen a great deal of progress in terms of the production and consumption of renewable energy. This in turn is rapidly powering economic growth and social development around the globe. Contrary to popular belief, the use of renewable energy is not limited to developed countries only. The developing countries are also rapidly endorsing renewable energy as a vital engine of economic growth and societal development. In this regard, even though renewable energy production and consumption are in their infancy in BRICS, these countries are taking concrete steps towards the development of renewable energy resources. The results of previous studies have indicated that with an increase in the GDP of a country its carbon footprint also tends to increase, the Brazil, Russia, India, China, and South Africa (BRICS) countries are no exception in this regard. One of the main challenges in research related to measuring the contribution of renewable energy towards economic growth is the use of a singular model or techniques that may not be appropriate for the generalization of the results. This study intends to overcome this challenge by application of multiple econometric-based models which include the “Cross Dependency” test, the unit root test, and “CIPS” (cross-sectional augmented IPS). Besides these the second generation, stochastic models based upon econometrics, such as the DOLS test (dynamic ordinary least square) and the FMOLS (fully modified ordinary least square) are also applied for verification of the contribution of renewable energy towards the economic growth of the BRICS countries. The novelty of the study mainly stems from fact that these models are seldom applied in tandem and especially in the BRICS countries. The results of the study indicate that the existence of the bi-directional relationship between the use of renewable energy and economic growth is mainly indicated by the increase in GDP, thus lending support to the feedback hypothesis. Moreover, the conservation hypothesis was proven by the existence of a unidirectional causality relationship between the use of renewable energy and CO2 emissions. Alongside these, the study also included sensitivity analysis to gauge the impact of the growth of GDP on the CO2 emissions of BRICS countries, and regression analysis was performed to create an EKC curve which was used to gauge not only the sensitivity but also to help in highlighting the impact of using renewable energy in controlling and reducing CO2 emissions, thus proving the EKC theory. Thus, it can be deduced that increase in CO2 emissions is of major concern for the BRICS countries, which has led them to increase the production of renewable energy. Based upon the findings of the present study it is recommended that policymakers should encourage the use of renewable energy by offering incentives in financial terms, such as interest-free or low-interest loans, subsidies and feed-in tariffs.

Project no. 132805 has been implemented with support provided from the National Research, Development, and Innovation Fund of Hungary, financed under the K_19 funding scheme and supported by the János Bolyai Research Scholarship of the Hungarian Academy of Sciences (BO/00095/18 and BO/8/20)

Global warming is one of the most important challenges nowadays. Sustainability practices and technologies have been proven to significantly reduce the amount of energy consumed and incur economic savings. Sustainability assessment tools and methods have been developed to support decision makers in evaluating the developments in sustainable technology. Several sustainability assessment tools and methods have been developed by fuzzy logic and neural network machine learning techniques. However, a combination of neural network and fuzzy logic, neuro-fuzzy, and the ensemble learning of this technique has been rarely explored when developing sustainability assessment methods. In addition, most of the methods developed in the literature solely rely on fuzzy logic. The main shortcoming of solely using the fuzzy logic rule-based technique is that it cannot automatically learn from the data. This problem of fuzzy logic has been solved by the use of neural networks in many real-world problems. The combination of these two techniques will take the advantages of both to precisely predict the output of a system. In addition, combining the outputs of several predictors can result in an improved accuracy in complex systems. This study accordingly aims to propose an accurate method for measuring countries’ sustainability performance using a set of real-world data of the sustainability indicators. The adaptive neuro-fuzzy inference system (ANFIS) technique was used for discovering the fuzzy rules from data from 128 countries, and ensemble learning was used for measuring the countries’ sustainability performance. The proposed method aims to provide the country rankings in term of sustainability. The results of this research show that the method has potential to be effectively implemented as a decision-making tool for measuring countries’ sustainability performance, This article belongs to the Collection Advanced Methodologies for Sustainability Assessment: Theory and Practice