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The purpose of the study is to examine the factors that influence people's intention to adopt electric vehicles (EVs). The study used an expanded theory of planned behaviour (TPB) along with the addition of perceived trust and consideration of future consequences (CFC).

The study is based on primary data collected from 282 respondents in Punjab through a questionnaire. The collected data were analysed using SPSS 26 and AMOS 24 to perform confirmatory factor analysis and structural equation modelling.

The empirical analysis indicates that attitude, subjective norms and perceived trust have a significant influence on the adoption intention (AI) of EVs.

The implications provide policymakers and marketers with better insights into marketing EVs in the trajectory of sustainable mobility. Marketers should create focussed marketing materials that highlight the environmental ease of use, lower running costs and sophisticated technology of electric automobiles. The limitations of the study provide valuable insights for future researchers.

This is the first study that uses CFC with the TPB model in the context of AI of EVs specifically for the Punjab region.

Textile, listed as one of the highly environmentally sensitive goods, its trade is susceptible to be influenced by the implementation of stringent environmental policies. This paper aims to investigate the long-run relationship between revealed comparative advantage (RCA) and Environmental Policy Stringency Index (EPSI) for textile exports of G20 countries in panel data setup.

Apart from trend analysis, the authors have employed Pedroni and Westerlund panel cointegration method and fully modified ordinary least square (FMOLS) method to study the long-run relationship between RCA and EPSI in presence of cross-sectional dependence.

A strong link between trade and environmental stringency is observed for textile in the present study. For G20 countries, slight evidence of the Pollution Haven Hypothesis has also been witnessed in the study. Correspondingly, the results reveal the presence of long-run association between the variables under study, implying that stringent environmental policies reduce RCA for some countries, whereas some countries witness the Porter hypothesis.

The results imply that policy formulation should not aim at limiting the efforts of connecting RCA to environmental stringency but to set trade policies in a wider framework, considering environmental concerns, as these are inseparable subjects. However, this study also provides relevant real-world implications that can support further research.

The present study has important implications for textile exporters such as green innovations. The Porter hypothesis can be a beneficial tool for G20 exporters in enhancing their export performance, especially for the ones dealing in environmentally sensitive goods. This study offers relevant policy implications and provides directions for future research on global trade and environment nexus.

This study deals in a debatable area of research that evaluates the interlinkages between environmental stringency and global trade flows in the G20 countries. An important observation of the study is the asymmetrical nature of policy stringency across different countries and its impact on trade. The unavailability of updated data is the limitation of the present study.

Trade of environmentally sensitive goods (ESGs) is often exposed to countries with less stringent regulations suggesting that those countries have comparative advantage in the polluting sector. The Group of Twenty (G20) members are among the highest polluters, globally. Different stringency policies are enacted time to time in G20 to control environment pollution. However, the impact of policy stringency on export performance of ESGs is seldom examined. The paper aims to address some of the issues concerning this matter.

The present study aims to address the short run and long-run association between Revealed Comparative Advantage of ESGs and Environmental Policy Stringency Index for the period of 1990–2019 in G20. Periodic fluctuations and time adjustment mechanism are also studied. Second Generation Panel Cointegration, Vector Error Correction, Impulse Response Function and Variance Decomposition methods are employed to address the objectives.

Result is evident that more exposure to stringent environmental regulations reduces the comparative advantage of ESGs in the long run. But there is no evidence of the short-run relationship between the variables. The possible reason could be that new regulations enacted prove fruitful in the long run.

The novelty of the study is to focus on inter linkages between stringency and global export competitiveness in G20, almost nonexistent in the past studies. The study also provides a road map to policymakers to find out potential ways for sustainable development by balancing environmental stringency measures and international trade.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-08-2022-0560