Corrigendum to "Impact of Nigeria's industrial sector on level of inefficiency for energy consumption: Fisher Ideal index decomposition analysis" [Heliyon 7, Issue 5, May 2021, article e06952].

[This corrects the article DOI: 10.1016/j.heliyon.2021.e06952.].

Prospects of natural gas consumption in Pakistan: based on the LMDI-STIRPAT PLSR framework.

The natural gas (NG) forms the sizeable portion of the primary energy consumption in Pakistan. However, its depleting domestic reserves and increasing demand is challenging to balance the supply-demand in the country. This paper investigates the relationship between NG consumption and driving factors using LMDI-STIRPAT PLSR framework. It is learned that fossil energy structure and per capita gross domestic product (GDP) are most influencing factors on NG consumption, followed by non-clean energy structure, energy intensity, and population. The factors were further modelled to forecast the future values of NG consumption for various scenarios. It is found that NG consumption would be 42.107 MTOE under the high development scenario which would be twice the baseline scenario. It is projected that indigenous NG production will fall from 4 to 2 billion cubic feet/day and demand will increase by 1.5 billion cubic feet/day. Therefore, an optimized strategy is required for a long-term solution to cater this increasing supply-demand.

A Contribution to Sustainable Human Resource Development in the Era of the COVID-19 Pandemic.

This examines the six drivers and twelve detailed practices of sustainable human resource development (S-HRD) before and during the COVID-19 pandemic across different organizations in Poland. The empirical strategy is based on explorative research conducted using surveys in Poland between 2020 and 2021. The results confirm that the surveyed organizations implemented S-HRD practices driven mainly by the expectations of external stakeholders. They neglected the areas of caring for employees' well-being and developing environmental awareness before the COVID-19 pandemic. During the pandemic, most companies maintained their approach to S-HRD. This research is unique because it adds to the body of literature advocating the significance of S-HRD for organizational resilience before, during, and after extreme events. Generalizing the results is challenging because the snowball sample has significant restrictions. However, future research may overcome these shortcomings by using larger samples based on probability or random sampling techniques.

Nexus between macroeconomic uncertainty, oil prices, and exports: evidence from quantile-on-quantile regression approach.

International trade is key to boosting the economic growth and development of an economy. Hence, it becomes critical to analyze its determinants. The present study attempts to empirically analyze the determinants of trade exports of Pakistan with its top-5 trade partners. The prior literature suffers from biased findings due to deploying the aggregate data and ignoring the likely asymmetries in the drivers of the exports. The present study has used the monthly data of oil prices and macroeconomic uncertainty in order to empirically investigate the determinants of exports. For the purpose of analysis, several advanced econometric (quantile unit root, cointegration, and granger causality) tests and (quantile-on-quantile regression) techniques are utilized to handle the issue of asymmetries in the modeled series. The findings reveal a positive and significant relationship between oil prices in Pakistan and exports. Furthermore, macroeconomic uncertainty has a significantly negative impact on the country's exports. Based on the results, key policy implications are provided.

Dirty versus clean fuel for cooking in Pakistan: regional mapping and correlates.

Based on the Pakistan Demographic and Health Survey (PDHS) 2017-18 data, the study intends to present the relative status of a particular fuel (type) in terms of its level of use in different regions of Pakistan. At the same time, the study investigates the determinants of the household type of fuel used for cooking in Pakistan. Socioeconomic characteristics of the households and household heads are taken as determinants of the main type of fuel (clean or dirty) used for cooking by the households. Binary logistic regression is applied as an estimation technique. Over the country, wood stands first as the most widely used type of fuel followed by natural gas followed by LPG. Animal dung and charcoal are respectively ranked as the fourth and fifth most commonly used types of fuel for cooking by households in Pakistan. In comparison amongst the four provinces of Pakistan, the use of wood as well as charcoal as the fuel type for cooking (in relative terms) is the most common in Balochistan province. Likewise, Punjab province is the most frequent user of liquefied petroleum gas (LPG), crop residues, and animal dung, while Sindh province is the most frequent user of natural gas. Households possessing agricultural land and livestock and with large household sizes had more probability to use dirty sources of fuel for cooking. Households with better wealth status and residing in urban areas were more likely to use clean sources of fuel for cooking. Household head's higher educational status and male-gender had more likelihood to use clean sources of fuel for cooking.

Biocapacity convergence clubs in Latin America: an analysis of their determining factors using quantile regressions.

Latin America experiences an increasing urban primacy index and a rapid expansion of the financial system, putting direct pressure on the demand for resources to satisfy the consumption of large cities. We investigate the convergence of per capita biocapacity in 16 Latin America countries and evaluate the factors that influence its evolution over time. Specifically, we analyze the impact of the urban primacy index, economic progress, and the financial globalization index on the convergence of per capita biocapacity. We use the methodological framework developed by Phillips and Sul Econometrica 75:1771-1855, (2007) to analyze the convergence and the formation of convergence clubs of biocapacity during 1970-2017. The findings indicate that the countries of the region do not share a common trend of biocapacity, although they are grouped into five converging clubs. Biocapacity transition analysis reveals that countries have heterogeneous transition pathways between them. Using marginal effects, we find that the urban primacy index and economic progress reduce the biocapacity. The effect of the financial globalization index on biocapacity is not conclusive. The quantile regressions reveal that quantiles' impact of the urban primacy index and financial globalization on per capita biocapacity is heterogeneous. However, the effect of economic progress on biocapacity that predominates among quantiles is positive. The adoption of common policies among the countries that form the converging clubs could improve the effectiveness of pro-environmental policies and promote the achievement of the Sustainable Development Goals related to environmental quality.

Globalization toward environmental sustainability and electricity consumption to environmental degradation: does EKC inverted U-shaped hypothesis exist between squared economic growth and CO2 emissions in top globalized economies.

The study inspects the inverted U shape of the environmental Kuznets curve (EKC) hypothesis following the influence of economic growth on CO2 emissions and the reaction of electricity consumption and globalization toward CO2 emissions in top globalized economies. This study has taken the data of the top 9 globalized countries from 1990 to 2019 while adopting fully modified ordinary least squares and dynamic ordinary least squares panel cointegration approaches to determine the long run effects and Dumitrescu and Hurlin panel causality for the directions of the causality among the variables. According to the long-term findings of the research, economic growth and electricity consumption substantially contribute to CO2 secretions. On the other hand, the squared growth and globalization mitigate CO2 emissions and contribute to environmental sustainability. However, the inverse influence of squared growth on CO2 emissions shows the presence of the inverted U shape of the EKC hypothesis. Furthermore, Dumitrescu and Hurlin causality measures have shown the bi-directional causality of electricity consumption and economic growth with CO2 emissions and globalization with economic growth. At the same time, unidirectional causality exists from globalization to CO2 emissions, economic growth to electricity consumption, and electricity consumption to globalization. The study recommends long-term globalization and sustainable development projects to ensure environmental sustainability in these globalized economies.

Determinants of Social Commerce Usage and Online Impulse Purchase: Implications for Business and Digital Revolution.

Since their introduction in the early 2000s, the use of social networking websites has exploded. Many businesses are seeing increased revenue due to their social commerce strategy. Despite the popularity of social commerce websites, some consumers are still hesitate to use them. This study aims to evaluate the factors that influence the adoption of social commerce. A sample of 721 Chinese We Chat users took part in the research. The findings reveal that social capital mediates the positive effect of social commerce adoption and perceived ease of use (PERU) on techno-stress and online impulse purchasing. Likewise, information overloading mediates the positive effect of social commerce adoption and PERU on techno-stress and online impulse purchasing. The findings have implications for both practice and research in understanding social commerce adoption in emerging economies.

The asymmetric nexus between air pollution and COVID-19: Evidence from a non-linear panel autoregressive distributed lag model.

The emergence of a new coronavirus (COVID-19) has become a major global concern that has damaged human health and disturbing environmental quality. Some researchers have identified a positive relationship between air pollution (fine particulate matter PM2.5) and COVID-19. Nonetheless, no inclusive investigation has comprehensively examined this relationship for a tropical climate such as India. This study aims to address this knowledge gap by investigating the nexus between air pollution and COVID-19 in the ten most affected Indian states using daily observations from 9th March to September 20, 2020. The study has used the newly developed Hidden Panel Cointegration test and Nonlinear Panel Autoregressive Distributed Lag (NPARDL) model for asymmetric analysis. Empirical results illustrate an asymmetric relationship between PM2.5 and COVID-19 cases. More precisely, a 1% change in the positive shocks of PM2.5 increases the COVID-19 cases by 0.439%. Besides, the estimates of individual states expose the heterogeneous effects of PM2.5 on COVID-19. The asymmetric causality test of Hatemi-J's (2011) also suggests that the positive shocks on PM2.5 Granger-cause positive shocks on COVID19 cases. Research findings indicate that air pollution is the root cause of this outbreak; thus, the government should recognize this channel and implement robust policy guidelines to control the spread of environmental pollution.

Smart IoT and Machine Learning-based Framework for Water Quality Assessment and Device Component Monitoring.

Water is the most important natural element present on earth for humans, yet the availability of pure water is becoming scarce and decreasing. An increase in population and rise in temperatures are two major factors contributing to the water crisis worldwide. Desalinated, brackish water from the sea, lake, estuary, or underground aquifers is treated to maximize freshwater availability for human consumption. However, mismanagement of water storage, distribution, or quality leads to serious threats to human health and ecosystems. Sensors, embedded and smart devices in water plants require proactive monitoring for optimal performance. Traditional quality and device management require huge investments in time, manual efforts, labour, and resources. This research presents an IoT-based real-time framework to perform water quality management, monitor, and alert for taking actions based on contamination and toxic parameter levels, device and application performance as the first part of the proposed work. Machine learning models analyze water quality trends and device monitoring and management architecture. The results display that the proposed method manages water monitoring and accessing water parameters efficiently than other works.

Comprehending the environmental regulation, biased policies and OFDI reverse technology spillover effects: a contingent and dynamic perspective.

Technology spillovers have the substantial effect on the industrial structure in emerging economies especially from OFDI (Outward Foreign Direct Investment). This research aims to examines the issue on how environmental regulation and biased policies can more effectively promote the OFDI reverse technology spillover effect, specifically the technology spillovers. By classifying the key industries mentioned in the '12th Five-Year Plan' and '13th Five-Year Plan', this research uses panel data from 2010 to 2019 obtained from provincial OFDI in China and utilizes difference in difference (DID) model and threshold regression approach to validate the analysis. The results show that the key industrial policy is favorable to the local OFDI reverse technology spillover. From the outlook of economic significance, the industrial policy increases the regional OFDI reverse technology spillover by 0.133%. Findings of our study further reveals that the environmental regulation and biased policy effectively promote the regional OFDI reverse technology spillover with certain stability. This study findings will be beneficial for policy makers to stimulate the reverse technology spillover impact of local OFDI more effectively from three aspects such as regional marketization level, innovation ability and financial structure.

Renewable and non-renewable energy consumption driven sustainable development in ASEAN countries: do financial development and institutional quality matter?

Energy consumption for sustainable development has become a crucial issue in recent years. The anthropogenic effects of traditional energy sources (non-renewables) underscore the need for renewable energy and efforts to promote its adoption have comprised policy makers' strategies to achieve sustainable development. At the same time, institutional stability is a necessary element needed to meet the goal of sustainable development via improved management of resources and technology diffusion. The literature shows some contradictory findings on this matter and this study aims to clarify. Thus, this research scrutinizes the contribution of renewable and non-renewable energies in sustainable development while also taking into account financial development and institutional quality in ASEAN countries from 1980 to 2018. To assess for co-integration, a pooled mean group (PMG) regression technique is employed and the findings from this technique are verified by using fully modified ordinary least square (FMOLS), dynamic ordinary least square (DOLS), and canonical cointegration regression (CCR) techniques in conjunction with other panel-based econometric procedures to evaluate the robustness of the model. The findings reveal a significantly positive influence for renewable energy and a significantly adverse impact for non-renewable energy with respect to sustainable development in ASEAN countries. In addition, the results indicate that institutional quality and financial development have adverse effects on sustainable development. Therefore, this research recommends sustainable management of non-renewables and greater promotion of renewables by strengthening institutional quality in ASEAN countries.

A district-level analysis for measuring the effects of climate change on production of agricultural crops, i.e., wheat and paddy: evidence from India.

The present study aims to examine the impact of climate change on wheat and rice yield in Punjab, India, during 1981-2017. The study employs fully modified ordinary least squares (FMOLS), dynamic ordinary least squares (DOLS), and pooled mean group (PMG) approaches. The Pedroni cointegration has established a long-run relationship of climate variables with rice and wheat crops. FMOLS and DOLS models show that minimum temperature has a positive effect on both wheat and rice. In contrast, the maximum temperature is found to be negatively contributing to both crops. Rainfall has a significant adverse impact on the production of wheat. In the study period, seasonal rainfall has been found detrimental for the production of wheat and rice crops, indicating that excess rainfall proved counterproductive. Moreover, the Dumitrescu-Hurlin causality test has revealed a unidirectional causality running from minimum temperature, rainfall, and maximum temperature for rice and wheat production. The findings of the study suggest that the government should invest in developing stress-tolerant varieties of wheat and rice, managing crop residuals to curb other environmental effects, and sustaining natural resources for ensuring food security.

Impact of renewable energy consumption, financial development and natural resources on environmental degradation in OECD countries with dynamic panel data.

This research used panel data from 1995 to 2019 to examine the impact of financial development, natural resource, industrial production, renewable energy consumption, and total reserve on environmental degradation in (38) OECD countries by using dynamic panel data models, i.e., one-step difference GMM, one-step system GMM, and two-step system GMM model, respectively. The examined findings of one-step difference GMM, one-step system GMM, and two-step system GMM demonstrate that renewable energy consumption and natural resource help to reduce the environmental degradation while financial development, industrial production, and total reserve cause environmental degradation in OECD countries. Based on the examined results, significant policy implications are suggested to improve the environmental quality in OECD countries.

Mitigating energy production-based carbon dioxide emissions in Argentina: the roles of renewable energy and economic globalization.

The energy sector of Argentina is predominantly reliant on fossil fuels. Consequently, such fossil fuel dependency within the nation's power sector, in particular, has aggravated the environmental quality in Argentina by amplifying the nation's energy production-based carbon emission levels. However, keeping into consideration the international commitments pledged by Argentina under the Paris Accord and the Sustainable Development Goals agenda, it is pertinent for this South American country to curb its energy production-based emission of greenhouse gases, especially carbon dioxide. Against this milieu, this study examines the impacts of renewable electricity generation, economic globalization, economic growth, and urbanization on carbon dioxide emissions generated from the production of electricity and heat in the context of Argentina. Using annual frequency data from 1971 to 2016, recent econometric methods are applied to control for multiple structural breaks in the data. The major findings from the ecnometric analyses affirmed long-run associations between renewable electricity generation, economic globalization, economic growth, urbanization, and energy production-based carbon dioxide emissions in Argentina. Besides, enhancing renewable electricity output shares is found to curb these emissions while economic globalization and urbanization are witnessed to boost them. Moreover, renewable electricity generation and economic globalization are found to jointly reduce the energy production-related carbon dioxide emissions in Argentina. The results also validate the authenticity of the Environmental Kuznets Curve (EKC) hypothesis. Finally, the causality analysis reveals evidence of unidirectional causalities running from renewable electricity generation, economic globalization, economic growth, and urbanization to energy production-related carbon dioxide emissions in Argentina. In line with these findings, this study recommends several viable policies which can be implemented to help Argentina control the growth of its energy production-based carbon dioxide emissions.

Role of financial development, environmental-related technologies, research and development, energy intensity, natural resource depletion, and temperature in sustainable environment in Canada.

Environmental sustainability concerns are increasing worldwide; both developing and developed countries face environmental degradation. Literature has highlighted the environment-growth nexus; however, the impact of environmental-related technologies on the environment is ignored in early studies. This study aims to explore the implications of financial development, environmental-related technologies, research and development, energy intensity, renewable energy production, natural resource depletion, and temperature in a sustainable environment in Canada by using a time series model, i.e., dynamic ARDL simulations (Jordan and Philips 2018) with data from 1989 to 2020. The examined findings of the dynamic ARDL simulations indicate that environmental-related technologies in Canada help to reduce environmental degradation both in the short run and in the long run. At the same time, financial development, energy intensity, renewable energy production, research and development, natural resource depletion, and temperature causes boost the environmental degradation in Canada. To achieve sustainable environment, Canada needs to improve innovations in the environmental-related technologies for achieving sustainable growth and environment.

Impact of globalization, institutional quality, economic growth, electricity and renewable energy consumption on Carbon Dioxide Emission in OECD countries.

This research for the first time examines the influence of the financial development, stock market, globalization, institutional quality, economic growth, electricity, and renewable energy consumption on carbon dioxide emission from 1985 to 2018 in thirty-six (OECD) countries. Cointegrations exist in the used variables based on the examined findings of the Kao, Westerlund, and Pedroni cointegration. Findings of the pooled mean group (PMG) indicate that renewable energy consumption, globalization, and institutional quality assist to reduce the carbon dioxide emission that improve the environment while financial development, stock market, electricity consumption, and economic growth cause to increase the carbon dioxide emission in OECD countries both in the long and in the short run. To reduce carbon dioxide emission, important policy implications are suggested for OECD countries.

Reinvigorating the role of clean energy transition for achieving a low-carbon economy: evidence from Bangladesh.

Achieving carbon-neutrality has become a global agenda following the ratification of the Paris Agreement. For the developing countries, in particular, attaining a low-carbon economy is particularly important since these economies are predominantly fossil-fuel dependent, to which Bangladesh is no exception. Therefore, this study specifically aimed at evaluating the environmental impacts associated with energy consumption and other key macroeconomic variables in the context of Bangladesh over the 1975-2016 period. As opposed to the conventional practice of using carbon dioxide emissions to proxy environmental quality, this study makes a novel attempt to use the carbon footprints to measure environmental welfare in Bangldesh. The outcomes from this study are expected to facilitate the carbon-neutrality objective of Bangladesh and, therefore, enable the nation to comply with its commitments concerning the attainment of the targets enlisted under the Paris Agreement and the United Nations Sustainable Development Goals declarations. The econometric analysis involved the application of methods that are suitable for handling the structural break issues in the data. The overall findings from empirical exercises reveal that aggregate energy consumption, fossil fuel consumption, and natural gas consumption boost the carbon footprint figures of Bangladesh. In contrast, nonfossil fuel consumption and hydroelectricity consumption are witnessed to abate the carbon footprint levels. Besides, economic growth and international trade are also evidenced to further increase the carbon footprints. Hence, these findings suggest that a clean energy transition within the Bangladesh economy can be the panacea to the nation's persitently aggravating environmental hardships. Furthermore, the causality analysis confirmed the presence of unidirectional causalities stemming from total energy consumption, fossil fuel consumption, natural gas consumption, hydroelectricity consumption, economic growth, and international trade to the carbon footprints. On the other hand, nonfossil fuel consumption is found to be bidirectionally associated with carbon footprints. In line with these aforementioned findings, several key policy suggestions are put forward regarding the facilitation of the carbon-neutrality agenda in Bangladesh.