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This paper examines the factors which impact the behavioral intentions toward cryptocurrency based on signaling theory.

Data were collected through online questionnaire, and responses from 223 individuals in Lebanon were analyzed through SEM technique using Amos 24.

The outcomes portrayed the positive effect of perceived benefits and trust in cryptocurrency on behavioral intentions toward cryptocurrency; while not supporting the hypothesized influence of herd behavior and regulatory support.

This paper is among the first studies to adopt Signaling Theory (ST) in the cryptocurrency behavioral intentions research. Moreover, it is of the initial efforts in Lebanon and Middle East in evaluating behavioral intentions to use cryptocurrency, and it provide insights for future researchers, crypto project owners, crypto investors and crypto trading platforms.

Despite the importance of tax policy in reducing energy consumption and carbon emissions, there is a dearth of research on the environmental impact of indirect taxes. This paper examines the impact of indirect taxes on carbon dioxide (CO₂) emissions, with an emphasis on institutional quality.

The study uses the Government Revenue Dataset (2021), comprising 143 countries, dividing into 114 developing and 29 developed countries, during the period between 1996 and 2019. The author adopts panel data techniques, with Driscoll–Kraay standard errors to account for the issue of cross-sectional dependence (CSD).

The results indicate that indirect tax revenues have a negative and significant impact on CO₂ emissions for the total sample. The subsample analysis revealed that while indirect taxes reduce carbon emissions in developing countries, opposed results are reported for developed countries. This finding implies that most of the advanced countries have already reached a high level of taxes, at which carbon emissions increase as indirect tax increases further. Interestingly, the results revealed that institutional quality enhances the role of indirect taxes in mitigating carbon emissions for both developing and developed countries.

To the best of the authors' knowledge, this is the sole study using the newly developed tax data by the United Nations University, World Institute for Development Research (UNU-WIDER) to investigate the impact of indirect taxes on carbon emissions, with an emphasis on institutional quality. The existing literature focuses on specific taxes, like carbon taxes, with no comprehensive research on the link between indirect taxes and carbon emissions.

This study explored the tax evasion and corruption–economic development nexus in Ghana and the moderating role of institutional quality in this relationship.

To achieve this objective, this study employed the structural equation modelling (SEM) strategy and maximum likelihood (ML) estimation method on selected quarterised data from 1996 to 2020.

The study found that tax evasion has a positive impact on GDP per capita and urbanisation but a negative impact on the Economic Freedom of the World Index (EFWI). The study revealed that corruption has a positive relationship with GDP per capita but relates with EFWI inversely. Finally, the study found that institutional quality moderates the nexus between tax evasion and corruption and economic development.

The findings imply that the quality of state institutions has a significant impact on the government's ability to control tax evasion and corruption in order to drive economic development.

One novelty of the study is the examination of the combined effects of tax evasion and corruption as exogenous variables in a single econometric model. Again, to moderate the multivariate relationships of the study, the principal component analysis (PCA) was used to create an institutional quality index. The study recommends that policymakers implement comprehensive tax evasion and corruption reduction strategies simultaneously in order to increase tax revenues for economic development and SDGs achievement.

The paper intends to show the role of fear of COVID-19 and the relevance of customer empowerment (CU_EMP) and customers’ perceived value of digital service transactions (CU_PV_DST) in promoting green bank service purchase intention (GBS_PI), despite the antagonistic impacts brought in other sectors and the relevance of customer empowerment (CU_EMP) and customers’ perceived value of digital service transactions (CU_PV_DST) as important mediating variables of the relation.

The structured questionnaire helped collect survey data from 323 small business people. The model relationship was assessed through EFA, CFA by SPSS-AMOS and SEM using bootstrapping procedures in Smart-PLS.

The findings of this study show that there is a significant effect of fear of COVID-19 pandemic (F_COVID-19P) on CU_EMP and GBS_PI. CU_EMP influences GBS_PI, whereas F_COVID-19P influences GBS_PI indirectly via CU_EMP. Furthermore, there is a substantial effect of F_COVID-19P on CU_PV_DST and GBS_PI. Thus, F_COVID-19P significantly influences GBS_PI indirectly via CU_PV_DST.

Capitalizing on the COVID-19 wave by empowering customers technologically, improving the legal framework and increasing the perceived value of green service by using an innovative mechanism. In addition, fostering cultural change and emphasizing altruistic values through green advertisements have been explored in this study.

Green services are healthier for smart/green economy and are health-protective for coping with health risks.

This study helps in understanding the theories used in this context by linking them to F_COVID-19P with CU_EMP, CU_PV_DST and GBS_PI and contributes to the literature of both. Furthermore, this is the only study that has used SEM to study this kind of interrelation.

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 purpose of this paper is to analyse the influence of economic growth, digitalisation, eco-innovation, energy consumption and patents on environmental technologies on the volume of greenhouse gas emissions (GHG) recorded in European countries for a period of nine years (2010–2018).

Two empirical methods were integrated into the theoretical approach developed based on the analysis of the current scientific framework. Multiple linear regression, an extended version of the OLS model, and a non-causal analysis as a robustness method, Dumitrescu–Hurlin, were used to achieve the proposed research objective.

Digitalisation described by the number of individual Internet users and patents on environmental technologies determines the amount of GHG in Europe, and economic growth continues to have a significant effect on the amount of emissions, as well as the consumption of renewable energy. European countries are not framed in well-established patterns, but the economic growth, digitalisation, eco-innovation and renewable energy have an impact on the amount of GHG in one way or another. In many European countries, the amount of GHGs is decreasing as a result of economic growth, changes in the energy field and digitalisation. The positive influence of economic growth on climate neutrality depends on its degree of sustainability, while patents have the same conditional effect of their translation into environmentally efficient technologies.

This study has a number of limitations which derive, first of all, from the lack of digitalisation indicators. The missing data restricted the inclusion in the analysis of variables relevant to the description of the European digitalisation process, also obtaining conclusive results on the effects of digitalisation on GHG emissions.

A similar analysis of the relationship among the amount of greenhouse gas emissions and economic growth, digitalisation, eco-innovation and renewable energy is less common in the literature. Also, the results can be inspirational in the sphere of macroeconomic policy.

The aim of the paper is to rank and analyze the key strategies to sustainable finance adoption in the manufacturing sector using Fuzzy Delphi method (FDM), Interpretive Structural Modeling (ISM) and MICMAC (impact matrix cross-reference multiplication applied to a classification) analysis.

The study develops a novel framework to identify and analyze the mutual relationships among set of sustainable policies using extensive literature survey and experts opinion. Initially, the study found 14 strategies to implement sustainable finance with the help of vast literature. Then, the list of identified factors were screened through Fuzzy Delphi Method (FDM). Based on driving and dependence power, the final list of factors are divided into three categories.

The study findings reveal that “environmental rules and practices”, “financial incentives, tax reduction and subsidy”, have strongest driving power for promoting sustainable financial system in Pakistani manufacturing sector. Furthermore, “environmental awareness” and “long term vision” are found to be highly influenced by other corresponding elements in a system.

The ISM approach assists professionals, academics, and managers in identifying and ranking policies in implementing green business techniques. The hierarchical representation of ISM results provides a roadmap for decision-makers to navigate and prioritize factors effectively, facilitating the implementation of strategies that contribute to sustainable growth within organizations.

The study results provide interesting clues regarding green finance policies that provide the foundations, incentives, protections or other provisions that support the ecological conservancy’s mission. Specifically, the findings guide that government must offer research grants to private enterprises, research and development institutions, and universities to promote environmental protection and develop transformative technologies such as waste recycling, renewable energy, carbon capture, and power consumption.

The exploration of strategies for sustainable finance adoption with the help of mixed methodological approach and classification of these strategies on the basis of importance level is a new attempt in the field of manufacturing sector.

Motivated by the 2030 UN Sustainable Development Goals (SDG-7: clean and affordable energy, SDG-8: sustainable economic growth, SDG-13: climate action), this study aims to investigate the role of economic complexity, disaggregated energy consumption in addition to economic growth, financial development, globalization and urbanization on the ecological footprint of United Arab Emirates (UAE).

This study adopts unit root tests (with and without a structural break), autoregressive distributed lag (ARDL) bounds test and dynamic ordinary least squares.

The results obtained from the ARDL model suggest that economic complexity (EC), nonrenewable energy and economic growth increase the ecological footprint in both the short and long run, thus deteriorating the environment. However, renewable energy and urbanization reduce the ecological footprint in UAE during the two periods, thus improving environmental quality. Globalization and financial development have different influences on ecological footprint during these periods. These findings are robust to other estimation techniques.

Based on these results, this study offers significant policy implications such as increasing renewable energy supply, particularly solar energy and aligning the product manufacturing structure and complexity toward producing environmentally friendly products which can be used to realize the nation’s agenda of reducing fossil fuels consumption to 38% by 2050 and achieving sustainable environment and growth.

This study provides an empirical attempt to investigate the influence of EC and renewable and nonrenewable energy on the ecological footprint of the UAE.