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This study scrutinizes the impact of economic globalization on ecological footprint while endogenizing economic growth and energy consumption during 1990–2018 in India.

For time series analysis, the standard unit root test has been employed to unveil the integration order. Then, the cointegration was confirmed using autoregressive distributed lag (ARDL) analysis. Further, the study executed the dynamic ARDL simulation model to estimate long-run and short-run results along with simulation and robotic prediction.

The cointegration analysis confirms the existence of a long-run association among variables. Further, economic globalization reduces the ecological footprint in the long-run. Similarly, energy consumption decreases the ecological footprint. In contrast, economic growth spurs the ecological footprint in India.

The present study makes valuable and original contributions to the literature by applying a multivariate ecological footprint function, assessing the impact of economic globalization on ecological footprint while considering economic growth and energy consumption in India.

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.

For mitigating climate change, renewable energy consumption is recognized as one of the policy measures worldwide. However, there is a dearth of empirical studies focusing on education as one of the determinants of renewable energy consumption in the existing literature. Thus, this study aims to explore the impact of education, economic growth and foreign direct investment, financial development, CO₂ emissions and urbanization on renewable energy consumption.

This study considers a balanced panel of selected South Asian Association of Regional Cooperation (SAARC) countries, namely, India, Pakistan, Sri Lanka, Nepal and Bangladesh, during the period 1995–2015. The study uses sophisticated second-generation panel data models for empirical analysis.

The result reveals that education and economic growth significantly enhance renewable energy consumption, whereas foreign direct investment, financial development, CO₂ emissions and urbanization reduce it. Further, unidirectional causality from education, economic growth and urbanization to renewable energy consumption was observed, whereas a bidirectional causality was found between renewable energy consumption and financial development.

The emanated finding of this study is supposed to be helpful for the environmentalists, economists, banking sector and the practitioners in urban development can take insights from the study while framing the energy policy.

This is the first study that examines the role of education on renewable energy consumption in heterogeneous panel data settings for the selected SAARC countries.

This empirical study explores the role of tourism development (TD) in India's environmental degradation. Since sustainable eco-tourism is essential for India, whose long-term economic prosperity also depends on robust tourism growth. Hence, this study offers specific policy proposals for sustainable tourism based on the simulated outcomes.

The study employed the quarterly data from 1995Q1–2018Q4 for empirical validation. Moreover, the autoregressive distributed lag (ARDL) approach, Toda and Yamamoto (TY) causality model and wavelet coherence are also used to analyse the role of TD in India's environmental degradation.

The ARDL bounds test confirms the long-run relationship between the series. The long-run results from the ARDL model also indicate the driving role of TD in India's environmental degradation. In addition, the usage of the wavelet coherence method confirms the changes in TD that leads to changes in India's pollution level at different frequencies and periods, especially in the long run.

Since this analysis is India-specific, these findings may lack generalizability to other developing economies. Therefore, researchers are encouraged to examine the impact of tourism growth on the natural environment in other countries either in a panel or time-series framework.

This study suggests crucial implications for checking the pollution sands from TD without sacrificing tourism-led economic growth. This would be possible if the usage of green energy in India's transport sector is promoted.

This is the first study that analyzes the impact of TD on environmental degradation in the ARDL, wavelet coherence, TY frameworks for enabling the Indian economy for a sustainable tourism practice.

The purpose of this study is to dissect the transport infrastructure performance, public spending in transport infrastructure development and the manufacturing sector in determining the transport sector energy consumption.

An analysis of transport energy consumption with the transport infrastructure performance, public spending in transport infrastructure and manufacturing sector output in India using annual data for the period 1987–2019. The study used the autoregressive distributed lag (ARDL) bounds test approach along with FMOLS, DOLS and canonical cointegration regression (CCR) methods.

The results of the ARDL bounds test provide evidence for the long- and short-run relationships among study variables. It evidenced that transport infrastructure performance reduces transport energy consumption by using FMOLS, DOLS and CCR methods. Furthermore, the inference of the positive impact of value added in the manufacturing sector on transport energy consumption validates the higher energy demand of the manufacturing sector from a mobility perspective.

The estimated finding of this study is expected to be contributing to policy-making discussions on transport infrastructure and manufacturing sector development in an emerging economy like India with insights on energy consumption.

To the best of the authors’ knowledge, this is the first study that integrates the impact of manufacturing sector output on transport sector energy consumption along with transport infrastructure performance and public investment in the transport infrastructure.