This endeavor explores the nexus between health expenditure, consumption of renewable energy, economic growth, and the quality of the environment in 10 central European nations from 2005 to 2018 utilizing the techniques of fully generalized least square (FGLS) and generalized method of moments (GMM) estimation. The outcomes reveal the significant association between health, economic, and environmental factors with green energy utilization. The utilization of fossil fuels negatively influences the quality of the environment and boosts the risk of several diseases associated with the undernourishment and respiratory system and thus increases the death ratio. Furthermore, the utilization of operations based on renewable energy usage exerts a substantial favorable influence upon residents of Central European (CE) nations and thus helps decrease health and pollution-related expenses. So, there needs to be a collaboration among all the stakeholders so that green growth in the service and industrial sectors can be achieved.

Environmental sustainability and energy transition, especially the renewable energy transition, have become critical concerns of nations throughout the world in recent decades.The sustainable and eco-friendly technologies have led to more sustainable methodologies, substantial stewardship of our natural resources, and the conversion to renewable energy sources, all of which have been demonstrated to benefit the environment significantly. However, prior studies have overlooked the ecological sustainability and energy transition effects of green technology innovation. Therefore, this study endeavored to investigate the role of green innovation (lnGRN) and financial globalization (lnFIG) on the sustainability of the environment (lnEFT) and energy transition (lnENT) in the United Kingdom using quarterly data for the period from 1995 to 2020. The study applied the time-varying (bootstrapping) rolling window technique, which can retrieve casual associations among variables at different periods of sub-samples. Besides this, the method is advantageous for addressing the non-consistency of parameters and eliminating the pre-test distortion. The novel Bootstrap Rolling-Window full-sample causality technique results demonstrate that lnGRN and lnFIG have unidirectional causality toward lnEFT and lnENT. Furthermore, the bootstrap rolling-window subsamples in the final stage indicate that lnGRN and lnFIG mitigate lnEFT, whereas lnGRN and lnGDP enhance energy transition. On the other hand, lnGDP and lnETX contribute to environmental deterioration, while lnFIG hinders the energy transition. Several important policy implications are derived from the results to encourage financial globalization, green innovation technologies, renewable energy resources consumption, and environmental taxes.

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We investigate the impact of renewable energy and green practices (RE), transportation services and infrastructure (T.S.), GDP growth (GDP), and forestry and natural resources (AFF) on the sustainable tourism development in the Eastern European Countries (EECs). The study employed cross-sectional dependence and and CIPS unit root test to check stationarity along with the dynamic common correlated effect (DCCE) model proposed by Chudik and Pesaran (2015) to test parameters for ensuring robustness. The outcome of DCCE method suggests that renewable energy (RE), Transport Services (T.S.), Agriculture, Forestry and Fishing (AFF), and economic growth (GDP) have a significantly positive impact on international tourism in the sampled countries of Europe. Our findings could be insightful for policymakers and understanding the impact of renewable energy and transportation services on tourism development, and thereby help in taking appropriate policy measures in the sampled countries.

This study aims at understanding the relationships of certain behavioral biases with the investment performance, and identifies the moderating role of financial literacy upon these hypothesized relationships. Data is collected through questionnaire from the investors trading at Pakistan Stock Exchange (PSX). Structured Equation Modeling (SEM) is used to analyze the data with the results that only anchoring and overconfidence biases have significant effects on investment performance. The results also show that presence of financial literacy does not play any role in improving the performance of investors. Majorly, findings of current study contribute by testing the moderating role of financial literacy between the behavioral biases and the outcome of investment decisions and thus expected to be useful for investors and policy makers.

This empirical study aims to identify the importance of Digital Technologies (DT) as an enabler in the Circular Economy (C.E.) based business model, especially during Covid-19. The concept of 'circular economy' has now been advocated as a methodology to stimulate economic growth in line with the environmental sustainability. Hence, the practices of recycling, reduction, reuse/re-manufacture, and repairing (4R's) are deemed to be the core of a circular economy. Recently, the advent of the pandemic Covid-19 has forced the nations of the world to resort to alternate resource use in their manufacturing and trading of goods and services as the supply chains have almost remained disrupted since Covid-19 appeared. We investigate the impacts of Covid-19 upon the use of technological innovation (T.I.), circular economy practices (CEP), and organizational performance (ORP) incorporating the Structural Equation Modeling (SEM). Our results show that Covid-19 significantly impacted the adoption of technological innovation, circular economy, which leads toward organizational performance. Moreover, the practices and operations under the circular economy framework also appear to influence organizational performance significantly. Our study findings bring forward meaningful insights into improving CEF-cum-technology based practices in developing and emerging markets in Asia, and convey significant implications for the business community, policymakers, and researchers.

Firms adjust their capital structures to avoid financial distress and bankruptcy to sustain in the market. Asian firms have significantly different financial patterns than their USA and European counterparts. The moderation model gains a better understanding of the relationship between the model variables. We tested the moderating roles of life cycle stages and macro-economic factor gross national income per capita to find their moderating impacts on the speed of adjustment towards target capital structures of Asian manufacturing firms from 2010 to 2018. Our sample of manufacturing industries comes from the eleven Asian economies. We used the dynamic GMM model to estimate moderating impacts and applied the pooled OLS and fixed effect estimations to test the validity of the coefficient of lagged leverage. We find that life cycle stages have positive moderating impacts, and different gross national incomes per capita have no significant effects in adjusting the capital structure. We test the combined moderating impacts of the life cycle and gross national income by applying the full model. The results reveal that moderator variables significantly impact adjusting the target capital structure. From the policy perspective, it is recommended that investors should consider the firms’ life cycle stages and per capita income of the economy in making their international investment portfolios. The government should ensure requisite finance for firms at subsidized interest rates to financially support them at critical stages like introduction and decline.