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In this study, the authors provide a systematic literature review of articles in the emerging areas of green finance and discuss the status and challenges in sustainability disclosure, which is crucial for the efficiency of green financial instruments. The authors then review the literature on the economic implications of green finance and outline future research directions.

The authors use the analytical framework – Search, Appraisal, Synthesis, and Analysis (SALSA) to conduct the systematic review of the literature.

Increasing public attention to the environment motivates the use of green finance to fund environmentally sustainable projects, and the rise of green finance intensifies the demand for environmental disclosure. Literature has documented tremendous growth in sustainability reporting over time and around the globe, as well as raised concerns about how such reporting lack consistency, comparability, and assurance. Despite these challenges, the authors find that in general, the literature agrees that a firm’s green practice is positively associated with its financial performance and negatively related to a firm’s cost of capital. Green finance is also found to bring about enhanced risk management and economic development.

The authors provide one of the first reviews of green finance, sustainability disclosure and the impact of green finance on financial performance, capital market and economic development.

This paper aims to analyze how decision support systems manage Big data to obtain value.

A systematic literature review was performed with screening and analysis of 72 articles published between 2012 and 2019.

The findings reveal that techniques of big data analytics, machine learning algorithms and technologies predominantly related to computer science and cloud computing are used on decision support systems. Another finding was that the main areas that these techniques and technologies are been applied are logistic, traffic, health, business and market. This article also allows authors to understand the relationship in which descriptive, predictive and prescriptive analyses are used according to an inverse relationship of complexity in data analysis and the need for human decision-making.

As it is an emerging theme, this study seeks to present an overview of the techniques and technologies that are being discussed in the literature to solve problems in their respective areas, as a form of theoretical contribution. The authors also understand that there is a practical contribution to the maturity of the discussion and with reflections even presented as suggestions for future research, such as the ethical discussion. This study’s descriptive classification can also serve as a guide for new researchers who seek to understand the research involving decision support systems and big data to gain value in our society.

There is a pressing need to increase investments in sustainable infrastructure to promote low carbon economic growth and ensure environmental sustainability. Consequently, this study examines the socio-political factors underlying the adoption of green bond financing of infrastructure projects.

Primary data was gathered from experts with advanced experience in, or knowledge of green bonds in the Kumasi Metropolis. To identify respondents with pertinent knowledge that is relevant to the study, purposive and snowball sampling techniques were used. One-sample t-test and relative importance index were used in this study's statistical analysis.

‘Training and experience with sustainable finance’ was seen as the most important social factor underlying the adoption of green bond financing of infrastructure projects by the respondents and ‘Governmental tax-based incentives’ was rated as the leading political factor.

This pioneering research attempts to ascertain the socio-political factors affecting the adoption of green bond financing of infrastructure projects. Emergent results of analysis and concomitant discussions add knowledge to fill a void in literature on the social and political factors affecting the adoption of green bond financing of infrastructure projects in developing countries.

The present paper aims to evaluate the structural impact of exogenously induced fiscal shocks on the Moroccan economy. This entails an analysis of the effect on the GDP of COVID-19-induced fiscal shocks manifesting in terms of budgetary revenues and expenditures. A key aspect of this analysis addresses the size of the tax and fiscal multipliers.

The study examines the structural relationship between five variables during the period between Q1 2009 and Q2 2020 using an SVAR approach that allows for a dynamic interaction between ordinary expenditures and revenues on a quarterly basis.

Positive structural shocks on public spending are likely to negatively impact economic growth. Negative economic growth, in turn, will damage price levels and interest rates, mainly over the long term. However, public-revenue-multiplier-associated shocks exceed these price- and interest-rate multiplier-associated shocks. Indeed, a structural shock to ordinary revenues can have a positive but insignificant impact on the GDP stemming from the ensuing decrease in the government budget deficit that proceeds from the increase in government revenues.

This is one of the first studies in the Moroccan context to assess the impact of the current worldwide pandemic on public finances. In addition, this study highlights the importance of boosting economic recovery through public spending.

Since Islamic markets are growing substantially, there is an urgent need to gain a better understanding of how Muslim consumers perceive products from a religious perspective. The purpose of this paper is to investigate the brain responses of Muslim consumers to Halal and non-Halal products using a functional magnetic resonance imaging (fMRI) technology.

The research model is a simplified version of the theory of planned behavior. The initial experiment began by asking participants to divide a set of images into two groups: Halal and non-Halal products. The fMRI experiment uses a blocked design approach to capture brain activities resulting from presenting the two groups of images to participants, and to record the strength of their attitudes toward purchasing the products.

Across all participants, the level of brain activation in the ventromedial prefrontal cortex increased significantly when Halal images were presented to them. The same results emerged when the Halal images showed raw and cooked meat. The variations in the results may be due to the high emotional sensitivity of Muslim consumers to using religious products.

This study uses a unique approach to monitor brain activity to confirm that consumers from specific market segments respond differently to market products based on their internal beliefs. Findings from this study provide evidence that marketing managers targeting Muslim markets should consider the sensitivity of presenting products in ways that reflect religious principles, in order to gain higher acceptance in this market segment.

Although the literature reports considerable research on Muslim consumers’ behavior, most of the previous studies utilize conventional data collection approaches to target broad segments of consumers by using traditional products. This paper is the first to track the reactions of the Muslim consumer segment to specific types of market products.

The Ukraine crisis, which began with Russia's military intervention, has violently jolted the modern world. The egregious Russian invasion of Ukraine, on the other hand, has arguably altered the trajectory of the world order. This whiff of war does not exclude any state because all states in the world system are economically, politically, and socially interconnected and dependent on one another. Bangladesh is also feeling the effects of the Ukraine crisis. The crisis has highlighted some challenging aspects of Bangladesh's foreign policy, testing the robustness and independence of its decision-making process regarding United Nations resolutions. Myanmar, like Bangladesh, has appeared befuddled in its response to the crisis. This paper examines how Bangladesh and Myanmar's foreign policy anticipated an unwanted labyrinth by the crisis, which made its moral credibility critical to some extent. Furthermore, the paper discusses how these two countries’ foreign policy trajectories became entangled at a difficult crossroads. We used secondary data sources backed up by scholarly works on Bangladesh and Myanmar foreign policy, relevant books, recent reports, and writings on the subject for this article. This paper also sheds light on Bangladesh's U-Turn in supporting and speaking out in support of the UN resolution on Ukraine's humanitarian crisis.

The main goal of this study is to analyze how monetary debt effects firm behavior of 167 registered manufacturing companies in G-7 countries.

The sample of the present study is taken from the listed firms in G-7 countries. For the building companies, the yearly financial statements of 2007–2018 have been taken from world stock exchange and Thomson Reuters Data Stream. In this study, regression analysis are directed with panel data over the period of 2007–2018 using ordinary least square summary statistics, correlation matrix and generalized method moments. Data were analyzed by employing E Views and Stata 13 software.

The significant findings of the current study indicated that fixed assets, tangible assets, taxes, net cash and profitability have positive association with debt level.

The current work include only registered manufacturing firms in G-7 countries. Moreover, ownership types are not accounted for in this study.

The current analysis is an empirical investigation of antecedents of debt regarding G-7 countries with up-to-date data. Various regression inquires have been made to design the models using different measures of debt and measure of firm performance indicators. These works will assist G-7 countries firms to know the effects of identified factors on time raising debt level.

The current work has been finalized using genuine data of yearly reports and database. This study incorporated antecedents of debt, which have limited discourse in prior literature. Furthermore, this study explores the connection between debt level and firm performance of G-7 countries.

This study aims to evaluate cognitive, personal and environmental factors affecting investors’ behavioral intentions (BI) to invest in ṣukūk (Islamic investment certificates) in Pakistan.

Data from 462 participants were collected through survey-questionnaires by using the convenient sampling technique. Hypothesized proposed relationships among the constructs were examined by applying the structural equation modeling (SEM) technique through smart partial least squares.

Compatibility, internal influence, external influence and intrinsic motivation were found to be significant predictors of investors’ BI to invest in ṣukūk. In addition, it was found that the religious aspect not only affects investors’ BI positively but also works as a moderator in the relationships between BI and both internal and external influence.

The results are quite helpful for ṣukūk issuers and regulators to consider cognitive, personal and environmental factors that might enhance the adoption of ṣukūk, especially among Muslim investors.

This study is among the few research studies that shed light on investors’ BI to invest in ṣukūk. Using social cognitive theory, the study investigates the cognitive, personal and environmental factors influencing ṣukūk adoption, which were previously unexplored. In addition, this is the first study that unveils the influential factors of ṣukūk adoption in Pakistan, a Muslim-majority country.

Based on the job demands–resources (JD-R) model, this study aims to answer a key research question, i.e. can the job characteristics (i.e. job demands and resources) affect intention to retire early? Additionally, a mediating effect of emotional exhaustion and organizational commitment on the relationships of job demands and job resources, respectively, with early retirement intentions has been explored in the study.

The data has been collected from survey of 450 employees from the banking sector in the state of Punjab (India). A structured questionnaire adapted from past literature has been used as survey instrument for the study. Partial least squares structural equation modelling has been applied in the study using latest version of SmartPLS (version 3.2.8) software.

Both job resources and job demands have a direct significant impact on early retirement intentions. Moreover, a significant partial mediation effect of emotional exhaustion and affective organizational commitment has also been found out on the relationship of job demands and job resources with early retirement intentions, respectively.

The study makes incremental contribution by highlighting the role of both deterrent and motivational factors that either instigate or discourage early retirement intentions among employees. It offers valuable insights for the organizations to use efforts for curtailing the excessive job demands that lead to emotional exhaustion and further result in early retirement intentions. Besides this, adequate job resources should be provided to the employees that lead to the development of affective organizational commitment, which further helps in sustaining the workforce until their actual retirement age.

The purpose of this paper is to explore the interrelationship between macroeconomic factors, firm characteristics and financial performance of quoted manufacturing firms in Nigeria. Specifically, the study investigates the effect of interest rate, inflation rate, exchange rate and the gross domestic product (GDP) growth rate, while the firm characteristics were size, leverage and liquidity. The dependent variable financial performance is measured as return on assets (ROA).

The study used the ex post facto research design. The population comprised all quoted manufacturing firms on the Nigerian Stock Exchange. The sample was restricted to companies in the consumer goods sector, selected using non-probability sampling method. The study used multiple linear regression as the method of validating the hypotheses.

The study finds no significant effect for interest rate and exchange rate, but a significant effect for inflation rate and GDP growth rate on ROA. Second, the firm characteristics showed that firm size, leverage and liquidity were significant.

The study has implications for regulators and policy makers in formulating policy decisions. In addition, managers may better understand the interplay between macroeconomic factors, firm characteristics and profitability of firms.

Few studies have addressed the interplay of macroeconomic factors and firm characteristics in determining the profitability of manufacturing firms in the country and developing countries in general.