Search results

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 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.