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This study aims to analyze the socio-ecological policy trade-off caused by technological innovations in the post-COVID-19 era. The study outcomes are utilized to design a comprehensive policy framework for attaining sustainable development goals (SDGs).

Study is done for 100 countries over 1991–2019. Second-generation estimation method is used. Innovation is measured by total factor productivity, environmental quality is measured by carbon dioxide (CO₂) emissions and social dimension is captured by unemployment.

Innovation–CO₂ emissions association is found to be inverted U-shaped and innovation–unemployment association is found to be U-shaped.

The study outcomes show the conflicting impact of technological innovation leading to policy trade-off. This dual impact of innovation is considered during policy recommendation.

The policy framework recommended in the study shows a way to address the objectives of SDG 8, 9 and 13 during post-COVID-19 period.

Policy recommendations in the study show a way to internalize the negative social externality exerted by innovation.

This study contributes to the literature by considering the policy trade-off caused by innovation and recommending an SDG-oriented policy framework for the post-COVID-19 era.

The purpose of this paper is to provide a survey of the empirical literature on environmental Kuznets curve (EKC) estimation of carbon dioxide (CO₂) emissions over the period of 1991–2017.

This survey categorizes the studies on the basis of power of income in empirical models of EKC. It has been hypothesized that the EKC shows an inverted U-shaped association between economic growth and CO₂ emissions.

For all the contexts, the results of EKC estimation for CO₂ emissions are inconclusive in nature. The reasons behind this discrepancy can be attributed to the choice of contexts, time period, explanatory variables, and methodological adaptation.

The future studies in this context should not only consider new set of variables (e.g. corruption index, social indicators, political scenario, energy research and development expenditures, foreign capital inflows, happiness, population education structure, public investment toward alternate energy exploration, etc.), but also the data set should be refined, so that the EKC estimation issues raised by Stern (2004) can be addressed.

By far, no study in the literature of ecological economics has focused on the empirical estimation of EKC for CO₂ emissions. This particular context has been used for this study, as CO₂ is one of the highest studied pollutants in the ecological economics, and especially within the EKC hypothesis framework.

In the present study, the authors intended to investigate whether the economic growth drivers such as per capita income, financial development, nonrenewable energy solutions and trade expansion have invigorated the level of environmental pollution in the eight developing nations of South and Southeast Asia.

Considering the possibility of the cross-sectional dependency, the authors employed relatively new econometric approaches, that is, the Westerlund cointegration test and cross-sectional augmented distributed lag mean estimation (CS-DL) for the period of 1990–2015.

The simulation results of the study confirmed an N-shaped environmental Kuznets curve, which raised a question on the existing economic policies in these nations. Further, the study reported that the improvements in the financial sector, nonrenewable energy consumption and trade expansion contributed to increasing the level of CO₂ emissions in the long run.

Based on the results, the authors intended to provide a unique policy framework because the present policies are generating a trade-off between economic and environmental goals. If the suggested framework is employed across sectors, the given countries may likely achieve the sustainable development goals by 2030.

Over the last couple of years, the Chinese manufacturing sector was affected by the onset of the US–China trade war and the outbreak of coronavirus disease 2019 (COVID-19). In such a scenario air quality in China has encountered a shock, and the impacts of these two incidents are unknown. In this study, the authors analyze the convergence of air quality in China in the presence of multiple structural breaks and how the impacts of these two events are different from each other.

In order to assess the nature of shocks in the presence of multiple structural breaks, unit root tests with multiple structural breaks are employed.

The results reveal that air quality in China is showing the sign of convergence, and it is consistent across 18 provinces which are worst hit by the outbreak of COVID-19. In the presence of transitory shocks, the impact of COVID-19 outbreak is found to be higher, whereas the impact of the US–China trade war is found to be more persistent. Lastly, the outbreak of COVID-19 has been found to have more impact on pollutants with higher severity of health hazard.

To the best of the authors’ knowledge, this is the first study that contributes to the empirical literature in terms of investigating the convergence of overall air pollution and individual air pollutants taking COVID-19 and the trade war into account.

The purpose of this paper is to try to formulate a conceptual model for service-oriented export pricing by looking at both demand- and supply-side considerations by taking export price as a function of domestic price of service.

Continuous time optimization technique has been adopted for maximization of the profit earned by firms in the domestic and foreign market for both demand- and supply-side scenarios. Dynamic simulations have also been carried out to find out the sensitivity of parameters in diverse scenarios.

Different results have been received for demand and supply sides for export price optimization. Various pricing objectives have been aligned to the price determining parameters in accordance with the dynamic simulation performances.

Continuous time optimization served our purpose, as sustainability of the same decision over a longer period was not considered. However, discrete time optimization can be taken up, if the effect of a series of decisions is scrutinized. More flexibility can be incorporated in the model, if a range of domestic price is considered over the singular domestic price.

This paper is significant for those firms, which are willing to extend their operations beyond the national boundary. The models derived here can give them an idea about how to price service in foreign market.

Aligning pricing objectives with export price determining parameters by considering demand and supply side perspectives in a continuous time optimization model is a new contribution in the existing literature.

Aim of the present monograph is the economic analysis of the role of MNEs regarding globalisation and digital economy and in parallel there is a reference and examination of some legal aspects concerning MNEs, cyberspace and e‐commerce as the means of expression of the digital economy. The whole effort of the author is focused on the examination of various aspects of MNEs and their impact upon globalisation and vice versa and how and if we are moving towards a global digital economy.