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The purpose of this paper is to determine the effect of the industrial sector, renewable energy consumption and nonrenewable energy consumption in Indonesia on the ecological footprint from 1990 to 2020 in the short and long term.

This paper uses vector error correction model (VECM) analysis to examine the relationship in the short and long term. In addition, the impulse response function is used to enable future forecasts up to 2060 of the ecological footprint as a measure of environmental degradation caused by changes or shocks in industrial value-added, renewable energy consumption and nonrenewable energy consumption. Furthermore, forecast error decomposition of variance (FEVD) analysis is carried out to predict the percentage contribution of each variable’s variance to changes in a specific variable. Granger causality testing is used to enhance the analysis outcomes within the framework of VECM.

Using VECM analysis, the speed of adjustment for environmental damage is quite high in the short term, at 246%. This finding suggests that when there is a short-term imbalance in industrial value-added, renewable energy consumption and nonrenewable energy consumption, the ecological footprint experiences a very rapid adjustment, at 246%, to move towards long-term balance. Then, in the long term, the ecological footprint in Indonesia is most influenced by nonrenewable energy consumption. This is also confirmed by the Granger causality test and the results of FEVD, which show that the contribution of nonrenewable energy consumption will be 10.207% in 2060 and will be the main contributor to the ecological footprint in the coming years to achieve net-zero emissions in 2060. In the long run, renewable energy consumption has a negative effect on the ecological footprint, whereas industrial value-added and nonrenewable energy consumption have a positive effect.

For the first time, value added from the industrial sector is being used alongside renewable and nonrenewable energy consumption to measure Indonesia’s ecological footprint. The primary cause of Indonesia’s alarming environmental degradation is the industrial sector, which acts as the driving force behind this issue. Consequently, this contribution is expected to inform the policy implications required to achieve zero carbon emissions by 2060, aligned with the G20 countries’ Bali agreement of 2022.

The eco-innovation is considered one of the possible ways to tackle climate change. However, the conflicting empirical evidence related to the role of eco-innovation on environmental quality becomes a motivation to explore the effect of eco-innovation on environmental degradation proxied by ecological footprint. Besides, it controls economic growth, remittance inflows, trade openness and total energy consumption in the environmental degradation function.

Uses the Augmented Auto Regressive Distributed Lag (AARDL) approach to examine the cointegration relation among the series during the period ranging from 1975 to 2017 for India within the environmental Kuznets curve (EKC) framework.

The result suggests that eco-innovation can mitigate climate change by reducing the ecological footprint. Similarly, economic growth reduces the ecological footprint in the short- and long-run. However, the square of economic growth is positive and significant. Thus, it shows evidence against the conventional EKC hypothesis. The results also reveal that remittance inflows have an insignificant negative role on the ecological footprint, while total energy consumption and trade openness harm the environment by enhancing the ecological footprint.

This study provides important implications for climate change mitigation. Thus, the government should promote eco-innovation to mitigate climate change by offering a favorable legal environment to the firms to adopt the same in their production and consumption activities. It also suggests that initiatives like green strategies should give serious attention while incurring research expenditure.

No prior studies assess the impact of eco-innovation on the ecological footprint for the period of 1975–2017 in India.

The primary purpose is to investigate the dynamic relationships among urbanization, energy use and environmental pollution in the context of India from 1971 to 2018. The paper also examines the validity of Environmental Kuznets Curve (EKC) hypothesis in the present Indian context.

The study uses a nonlinear autoregressive distributed lag cointegration test (Shin et al., 2014) to investigate the dynamic relationship among the mentioned variables. The Wald test is also used to statistically check the presence of asymmetry. Additionally, the VECM test is applied to examine the causality among the variables.

This study documents that urbanization in India is good for environment in the long run, whereas energy consumption is bad for the environment. It also finds that positive and negative shocks of energy and urbanization exert asymmetric impacts on ecological footprint. Furthermore, the results could not validate the EKC hypothesis for India.

The outcome of the study suggests designing an environmental policy which considers the nonlinearity of the investigated relationships and bearing in mind the use of comprehensive indicator like ecological footprint is equally important to address the wide-ranging problem of the environment. Policy reorientation towards the production and consumption of green energy, investment in research and development, and use of efficient technology is very crucial to achieve sustainable outcomes in the long run.

In this study, the researchers use the ‘ecological footprint’ variable to obtain a more accurate and comprehensive assessment of environmental deterioration. The mentioned dynamic relationships are investigated using an improved methodology of the NARDL model, which assumes the asymmetric impact of the explanatory variables on the response variable. The novelty of this study lies in examining the non-linear impact of urbanization and energy on ecological footprint which is inadequately addressed in the context of Indian economy.

This paper investigates the (a)symmetric effects of financial development in the presence of economic growth, energy consumption, urbanization and foreign direct investment on environmental quality of South Africa between 1980 and 2017.

A robust measure of financial development is generated using banking institutions and non-banking institutions market-based financial development indicators, while environmental quality is measured using carbon footprint, non-carbon footprint and ecological footprint. The objectives of the study are captured using linear and non-linear autoregressive distributed lag.

The result from the symmetric analysis suggests that financial development stimulates carbon footprint and ecological footprint in the short run; however, financial development abates non-carbon footprint. In the long run, financial development has a significant negative effect on carbon footprint and ecological footprint. However, the asymmetric analysis established strong asymmetric effect in the short run, while no asymmetric effect is found in the long run. The short run asymmetric analysis reveals that positive shock in financial development increases carbon footprint and ecological footprint; however, positive changes in financial development reduce non-carbon footprint. Negative shocks in financial development, on the other hand, have a positive impact carbon footprint, non-carbon footprint and ecological footprint.

The study's outcome implies that the concept of “more finance, more growth” could also be applied to “more finance, better environment” in South Africa. The study offers vital policy suggestions for the realization of sustainable development in South Africa.

This empiric adds to the body of knowledge on the influence of financial development on various components of environmental quality (carbon footprint, non-carbon footprint and ecological footprint) in South Africa.

Considering the evolving importance of green finance, this study uses climate-related development mitigation finance as a proxy of green finance and investigates the impact of green finance on ecological footprint as an indicator of environmental quality along with the influence of economic growth, renewable energy, greenhouse gas emissions, trade openness and urbanization across 47 developing countries over the period 2000–2018.

After finding the presence of cross-sectional dependency among variables, the second-generation panel unit root test was employed to detect the order of integration among the variables. Since all the variables were found to be stationary, Westerlund cointegration technique was employed to detect the long-run relationship among the variables. Then, the long-run elasticity among the dependent and independent variables was tested using fully modified ordinary least squares (FMOLS), dynamic ordinary least squares (DOLS) and pooled mean group–autoregressive distributed lag (PMG–ARDL) approaches.

The empirical findings suggest the presence of long-run relationship among all the variables, namely, ecological footprint, green finance, economic growth, renewable energy consumption, greenhouse gas emissions, trade openness and urbanization for the selected developing countries in the sample. Furthermore, economic growth, greenhouse gas emissions, trade openness and urbanization, all have a positive and significant impact on the ecological footprint, whereas renewable energy consumption and green finance have a significant and negative impact on the ecological footprint, which supports the view that environmental quality is improved with the greater use of renewable energy technologies and allocation of greater amounts of more green finance.

The empirical results of this study offer policymakers and regulators some implications for environmental policy for protecting the countries from ecological issues.

The study of sustainability within universities is recognized as essential for debates and research; in the long term, the “sustainable university” concepts can contribute to sustainability from a larger perspective. This study aims to propose a conceptual model for evaluating the students’ sustainability considering their interactions with the university and the environment. The proposed model is titled Sunshine model. It is applied to students of the La Salle University, Peru.

The model combines academic performance, happiness and the ecological footprint to quantify university students’ sustainability. A structured questionnaire survey was elaborated and applied to get the raw data that feeds the three methods. The students’ average grades evaluate academic performance. Happiness is quantified by the happiness index method, and the ecological footprint is measured by the demand for food, paper, electricity, transport and built-up areas. Results are evaluated under both approaches, overall group performance and clusters.

The proposed model avoids misleading interpretations of a single indicator or discussions on sustainability that lack a conceptual model, bringing robustness in assessing students’ sustainability in universities. To have a low ecological footprint, the student needs to need up to 1 planet for their lifestyle, be considered happy with at least 0.8 (of 1) for happiness index, and have good academic performance with at least a grade of 7 (of 10) in their course. Regarding the case study, La Salle students show a high academic grade degree of 7, a high level for happiness index of 0.8 and low performance for ecological footprint by demanding 1.8 Earth planets, resulting in an “environmentally distracted” overall classification for students with 2019 data. From a cluster approach, 81% of evaluated students (n = 603) have low performance for ecological footprint, whereas 31% have low performance for indicators of recreational activities of happiness. Changing lifestyles and making more recreational activities available play crucial roles in achieving higher sustainability for the La Salle students.

The happiness assessment questionnaire can be subject to criticism, as it was created as a specific method for this type of audience based on existing questionnaires in the literature. Although it can be seen as an important approach for diagnoses, the proposed model does not consider the cause–effect aspect. The decision-maker must consider the sociocultural aspects before implementing plan actions.

University managers can better understand why university students have high or low sustainability performance and provide more effective actions toward higher levels of students’ sustainability.

The proposed model, Sunshine model, overcomes the single-criteria existing tools that access the sustainability of universities. Rather than focusing on university infrastructure, the proposed model focuses on the students and their relationship with the university.

Driven by the Sustainable Development Goals (goals 7, 8, 12 and 13), this study investigates the moderating role of financial development in the link between energy poverty and a sustainable environment in African nations.

Panel cointegration analysis, fully modified least squares, Driscoll and Kraay least squares and method of moments quantile regression were used as estimation techniques to examine the link between financial development, energy poverty and sustainable environment for 28 African nations. Energy poverty is measured using two proxies-access to clean energy and access to electricity, while the environment is gauged using ecological footprint.

The regression outcomes show that access to clean energy and electricity negatively impacts the ecological footprint across all the quantiles; hence, energy poverty increases environmental degradation. Financial development positively influences environmental degradation in the region at the upper quantiles. Similarly, the interactive term of energy poverty and financial development has a significant positive impact on ecological footprint; thus, the financial sector adds to energy poverty and environmental degradation. The results of other variables hint that per capita income and institutions worsen environmental quality while urbanisation strengthens the environment.

This study offers fresh insights into the moderating effect of financial development in the link between energy poverty and sustainable environment in African countries.

The paper assesses the moderating function of institutions in the financial development and environmental nexus covering India for the time period 1980–2019.

Deviating from extant literature which has mostly used emissions of major greenhouse gasses as a measure of environmental quality, the present study uses a broad measure of environmental quality called ecological footprint (EFP). Financial development is measured using a robust proxy recently introduced by International Monetary Fund (IMF). This index is multifaceted and covers three broad dimensions of financial sector in terms of depth, efficiency and access of both financial institutions and markets, thus outperforming the exclusively bank-based measures used in the past literature. Further institutional quality index is generated using the data from international country risk guide. Finally, autoregressive distributed lag model is used for the empirical estimation of short-run and long-run results.

The empirical estimates reveal that financial development and institutional quality are good for long-run environmental sustainability of India, whereas economic growth degrades the environment in the long- run. The results also attest to the existence of pollution heaven hypothesis in India for long run. Furthermore, regarding the moderating role of institutions, the study reveals that institutional quality complements financial development in affecting environment in the short run. While as, in the long run, they play a substitutive role whereby sound institutions cover-up the inefficiencies in financial system.

First, the paper uses the index of financial development developed by the IMF in order to quantify the level of financial development in India overtime. The index is based on three key dimensions of financial development such as the depth, efficiency and access of both financial institutions and markets. However, the index completely neglects the role of financial stability in determining financial development. Thus, future studies that are based on this IMF introduced index of financial development should incorporate the stability dimension to it. Second, this empirical study focused exclusively on India and employed aggregate EFP to measure environmental quality. Further studies can complement the content of this research by conducting similar studies to capture country-specific characteristics of other emerging economies and also scrutinize the impact on the six sub-indices of EFP.

The results of the study reveal that the effect of financial development, and institutions on ecological footprint is sensitive to time dynamics. Moreover, the findings offer important policy implications to government and policy makers in India on how to curb the menace of environmental degradation.

The paper addresses the gap in the literature by examining the moderating role of institutional quality in the financial development and ecological footprint nexus in India. Furthermore, the authors employ a robust proxy for both financial development and environmental quality unlike extant studies on India.

The purpose of this examine the impact of income inequality and shadow economy on environmental degradation given the growing income inequality, shadow economy and ecological degradation in developing countries. Thus, this study is motivated to offer empirical insight into how income inequality and shadow economy influence the environment in African countries.

Data from 29 countries in Africa between 2000 and 2017 were used, while the novel method of moments quantile regression of Machado and Silva (2019) and Dumitrescu and Hurlin (D-H) (2012) granger causality is used as the estimation techniques.

The results established the presence of cross-sectional dependence and slope heterogeneity in the panel, while Westerlund panel cointegration confirmed the long-run cointegration among the variables. The results from the quantile regression suggest that income inequality increases environmental degradation from the 5th to the 30th quantiles, while from the 70th quantiles, income inequality reduces ecological degradation. The shadow economy negatively influences environmental degradation across the quantiles, strengthening environmental quality. Per capita income (economic growth) and financial development positively impact environmental degradation throughout the quantiles. However, urbanization reduces environmental degradation from 60th to 95th quantiles. The D-H causality established a two-way relationship between income inequality and environmental degradation, while one-way from shadow economy, per capita income and urbanization to environmental degradation were established.

This study provides fresh insights into the nexus between shadow economy and environmental quality in the presence of higher levels of income inequality for the case of African region. The study applies quantile analysis via moment proposed by Machado and Silva (2019). This technique shows that the impact of income inequality and shadow economy on environmental degradation is heterogeneous across the quantiles of ecological footprints in Africa.

System dynamics has several applications in the built environment, and few studies indicate that it has potential in evaluating sustainability. Sustainability in the built environment involves numerous entities and multiple trade-offs. Hence, a Multi-Criteria Decision-Making (MCDM) method is ideal for promoting sustainability-based decision-making in the built environment. Therefore, this study integrates system dynamics with an MCDM method to enable the sustainability assessment by capturing the time-induced dynamic changes affecting long time sustainability performance of buildings.

Conventional sustainability assessment tools in the built environment lack a comprehensive evaluation that balances the needs of the society, economy and environment. This study develops a system dynamics-based framework to enable sustainability-conscious decision-making and policy analysis in the built environment.

Various material, technology and water-related policies specific to the buildings are investigated for a case study building. It is found that the effect of penetration of renewable energy technology to the tune of 80% and above in the energy mix is a much superior policy in sustainability improvement in comparison to material and water-related policies. The study also demonstrates the effect of weights assigned for the different indicators on sustainability-based decisions.

The study provides a methodological framework for a sustainability-based decision support system for the built environment that enables dynamic performance evaluation by coupling system dynamics with the MCDM. This coupling further strengthens system dynamics as a decision-making and policy analysis for sustainability evaluation in the built environment.