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This work analyzes, through social-environmental reports, whether banks with higher transparency in social-environmental policies better safeguard financial stability in Brazil.

The analysis is carried out through a panel database analysis of the 42 largest Brazilian banks, representing 98% of the Brazilian financial system. Seeking to avoid spurious results, we followed rigorous methodological standards. Hence, we conducted an empirical analysis using a dynamic panel data model, we used the difference generalized method of moments (D-GMM) and the system generalized method of moments (S-GMM).

The results show that the higher the transparency of social-environmental policies, the lower the chance of possible stress on the financial stability of Brazilian banks. In sum, this study builds evidence that disclosing risks related to policies about sustainability can enhance financial stability. It is essential to highlight that social-environmental transparency does not have as direct objective financial stability.

The manuscript submitted represents an original work that analyzes whether banks with higher transparency in social-environmental policies better safeguard financial stability. Some countries, such as Brazil, have their potential for sustainable policies spotlighted due to their green territory and diverse natural ecosystems. Besides having green potential, Brazil is a developing country with a well-developed financial system. These characteristics make Brazil one of the best laboratories for studying the relationship between transparency in social-environmental policies and financial stability.

This study considers the “technology creation” characteristic of technical knowledge-intensive business services (T-KIBS) and examines how human capital and intellectual property rights (IPR) protection affect the location choice of foreign direct investment (FDI) in China for two types of T-KIBS: (1) information transmission, software and information technology (ICT) services and (2) scientific research and technology (SCI) services.

Our empirical analysis is based on panel data on 22 Chinese provinces from 2009 to 2017. We use the generalized method of moments estimation for the regression analysis.

FDI in ICT services prefers regions with high human capital, while FDI in SCI services favors regions with good IPR protection.

Future research could use more comprehensive data and qualitative interviews to enhance the findings.

These findings provide a foundation for China’s future policy on attracting FDI into T-KIBS, especially in areas related to human capital and IPR protection.

This study bridges the research gap on the FDI location choice of T-KIBS in China by clarifying the influences of human capital and IPR protection and providing theoretical support for the location choice of T-KIBS FDI.

This study examines the non-linear impact of financial development on income inequality and analyses the mediators through which financial development affects income inequality.

The study uses a dynamic panel threshold method with an endogeneous threshold variable on a comprehensive sample of 85 countries over the period of 1996-2015.

The author finds that financial development activities increase income inequality in developed countries. However, financial development promotes income equality in developing countries. Further, the study finds that education and institutional quality are the channels through which financial development has non-linear impacts on income inequality.

The study explores relatively new method to examine the nonlinear impact of financial development and also considers new dataset for the main explanatory variable.

This study compares the motives of holding cash between developed (Australian) and developing (Malaysian) financial markets.

For the period 2006–2020, the t-test, fixed-effect and generalised method of moment (GMM) model have been applied to a sample of 1878 (1,165 Australian and 713 Malaysian) firms.

The empirical results reveal that firms in developed financial markets hold higher cash compared to the developing financial markets. The findings confirm that motives to hold cash differ between developed and developing financial markets. The GMM findings further show that cash holdings (CH) in Australia are higher due to higher ratios of cash flow, research and development (R&D) and return on assets (ROA), and lower due to larger dividend payments. In the Malaysian market, however, cash flows and R&D are ineffectual, ROA falls and dividend payments rise CH.

The study helps managers, practitioners and investors understand that firms' distinct economic, institutional, accounting and financial environments are important. To attain the desired outcomes, they must thus comprehend and consider these considerations while developing suitable liquidity strategies.

To the authors' best knowledge, this is the initial research demonstrating how varied cash motives and their ramifications are in developed and developing financial markets. Therefore, this study identifies the importance that CH motives varied among financial markets and that findings from a particular market cannot be generalised to other markets because of the market and financial structural variations.

This study aims to investigate the synergies between the economic environment and the smart living dimension embedded in the current smart city initiatives, focusing on the localization of female entrepreneurship in contemporary cities. This interaction is under-investigated and controversial as it includes cities' practices enabling users and citizens to develop their potential and build their own lives, affecting entrepreneurial and economic outcomes. Building upon the perspective of the innovation ecosystems, this study focuses on the impact of smart living dimensions and R&D investments on the localization of female entrepreneurial activities.

The study uses a Generalized Method of Moments (GMM) and a panel dataset that considers 30 Italian smart city projects for 12 years to demonstrate the relationship between smart living practices in cities and the localization of female entrepreneurship. The complementary effect of public R&D investment is also included as a driver in the “smart” city transition.

The study found that the advancement of smart living practices in cities drives the localization of female entrepreneurship. The study highlights the empirical results, the interaction over the years and a current overview through choropleth maps. The public R&D investment also affects this relationship.

This study advances the theoretical discussion on (1) female entrepreneurial intentions, (2) smart city advancement (as a context) and (3) smart living dimension (as a driver) and offers valuable insight for governance and policymakers.

This study offers empirical contributions to the preliminary academic debate on enterprise development and smart city trajectories at the intersection between human-based practices and female entrepreneurship.

This study offers empirical contributions to the preliminary academic debate on enterprise development and smart city trajectories at the intersection between human-based practices and female entrepreneurship. The findings provide valuable insights into the localization of female entrepreneurship in the context of smart cities.

This study investigates the impact of corporate social responsibility (CSR) on corporate innovation. We selected the listed nonfinancial firms of South Asian Economies. The sample of the study comprised a total of 426 listed manufacturing firms of South Asian Countries for period spans 10 years from 2012 to 2021. In this study, descriptive statistics, multicollinearity diagnostic tests, correlation analysis and two-step dynamic panel system generalized method of moments (GMM) were applied to analyze the data. CSR measured with three proxies' social indicators, environmental indicators, and CSR composite index of social and environmental indicators. However, corporate innovation is captured with number of citations received in a year and number of patents filed in the year. Overall, findings of the study using all measures of CSR shows that CSR significantly and positively related with corporate innovation. Our results find support for CSR-innovation view with all measures of CSR. The findings suggest that the current study is helpful for managers, regulators, policymakers, and researchers. For managers, the study helps them to make the CSR and innovation decision. The policymakers should take appropriate innovative decision while considering factors such as CSR. This study can also be extended by considering this study for developed and emerging economies sample.

Introduction: Why companies pay dividends and the determinants of dividend policy are considered an unresolved dividend puzzle. To reach a consensus over the puzzle, researchers must investigate the factors affecting dividend policy by incorporating all the determinants into a single research effort.

Purpose: We examine the dividend policy determinants of Sri Lankan firms, explicitly focusing on the banking, finance, and insurance (BFI) sectors.

Methodology: This study uses the quantitative approach applying the Generalized Method of Moments (GMM) system to examine the dividend policy determinants by obtaining secondary data from 51 listed BFI organisations in Sri Lanka.

Findings: The analysis disclosed that the variables of changes in revenues, firm size, liquidity, corporate tax, business risk, and profitability have a positive relationship with dividend yield, whereas investment opportunities, leverage, change in revenues, corporate tax, and firm size impact positively on the propensity to pay dividends in BFI organisations in Sri Lanka. Our findings opine that managers in the BFI industries should prioritise changing their dividend policies by paying close attention to factors, such as dividend yield, changes in revenue, firm size, liquidity, corporate tax ratio, business risk, and profitability because the dividend policy is critical to retaining current investors and luring new ones.

Most emerging economies have made conscious efforts through policy initiatives to attract foreign direct investment (FDI). However, a significant obstacle to FDI inflow has been the prevalence of corruption in the host country. This study, therefore, aims to examine whether there is an optimum corruption value that results in threshold effects of corruption on FDI.

To achieve this objective, this study used Hansen’s (1999) panel threshold regression (PTR) model by using a panel data of 30 sub-Saharan African (SSA) countries from 2000 to 2021.

This study finds that the nexus between corruption and FDI has a single threshold effect, with a 5.37% optimum corruption threshold value. At this threshold value, corruption affects FDI negatively. Any corruption value that is below the threshold value also elicits a negative corruption–FDI relationship. Despite having a negative relationship when the corruption value is above the optimum corruption threshold, it is not statistically significant.

The implication of the results is that it is deleterious to use corrupt practices to draw FDI to SSA nations.

To the best of the authors’ knowledge, this study is one of the first in the corruption–FDI nexus literature to use Hansen’s PTR model to estimate an optimal corruption threshold. The authors recommend that policymakers in the selected SSA countries reconsider the use of corruption to attract FDI because there is an optimal corruption threshold that could impact FDI in the host country.

This study empirically demonstrates a contradiction between pillar 3 of Basel norms III and the designation of Systemically Important Banks (SIBs), also known as Too Big to Fail (TBTF). The objective of this study is threefold, which has been approached in a phased manner. The first is to determine the systemic importance of the banks under study; second, to examine if market discipline exists at different levels of systemic importance of banks and lastly, to examine if the strength of market discipline varies at different levels of systemic importance.

This study is based on all the public and private sector banks operating in the Indian banking sector. The Gaussian Mixture Model algorithm has been utilized to classify banks into distinct levels of systemic importance. Thereafter, market discipline has been observed by analyzing depositors' sentiments toward banks' risk (CAMEL indicators). The analysis has been performed by employing the system Generalized Method of Moments (GMM) to estimate models with different dependent variables.

The findings affirm the existence of market discipline across all levels of systemic importance. However, the strength of market discipline varies with the systemic importance of the banks, with weak market discipline being a negative externality of the SIBs designation.

By employing the Gaussian Mixture Model algorithm to develop a framework for categorizing banks on the basis of their systemic importance, this study is the first to go beyond the conventional method as outlined by the Reserve Bank of India (RBI).

Open innovation (OI), by now one of the major concepts for the analysis of innovation, is seen as a methodology for collaboratively designing and implementing solutions by engaging stakeholders in an iterative and inclusive service design process. This paper aims to empirically investigate OI capacities, defined as a cooperative, knowledge-sharing innovation ecosystem, and to explore how it can lead to improved performance of firms in Central and Eastern European (CEE) and Southeastern European (SEE) countries.

The study builds on the World Bank/European Bank for Reconstruction and Development (EBRD’s) Business Environment Enterprise Performance Survey (BEEPS) dataset for 2009, 2013 and 2019. Primarily, the research model was estimated using log-transformed ordinary least squares (OLS). Taking into consideration that this method might produce substantial bias, yielding misleading inferences, this study is fitting Poisson pseudo maximum likelihood estimators with robust standard errors and instrumental variable/generalized method of moments estimation (IV/GMM) approach for comparative results. Secondarily, the research model was tested using structural equation modelling (SEM) to investigate the relationship between five OI capacities and firm performance.

The findings indicate that there is a significant positive relationship between most OI capacities and firm performance, except for innovation, which did not show a statistically significant relationship with firm performance. Specifically, research and development (R&D), knowledge and coopetition are statistically significant and positively associated with firm performance, whereas transformation is statistically significant but negatively associated with firm performance. The IV/GMM estimations’ findings support the view that the firm performance is significantly affected by OI capacities, together with some control variables such as size, age, foreign ownership and year dummy to have a significant impact on firm performance.

This paper fills an identified gap in the literature by investigating the impact of OI on firm performance executed in the specific CEE and SEE country context.