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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.

Might the impact of the financial stress on exchange markets be asymmetric and exposed to regime changes? Departing from the existing literature, highlighting that the domestic and foreign financial stress in terms of money market have substantial effects on exchange market, this paper aims to investigate the impacts of the bond yield spreads of three emerging countries (Mexico, Russia, and South Korea) on their exchange market pressure indices using monthly observations for the period 2010:01–2019:12. Additionally, the paper analyses the impact of bond yield spread of the US on the exchange market pressure indices of the three mentioned emerging countries. The authors hypothesized whether the negative and positive changes in the bond yield spreads have varying effects on exchange market pressure indices.

To address the research question, we measure the bond yield spread of the selected countries by using the interest rate spread between 10-year and 3-month treasury bills. At the same time, the exchange market pressure index is proxied by the index introduced by Desai et al. (2017). We base the empirical analysis on nonlinear vector autoregression (VAR) models and an asymmetric quantile-based approach.

The results of the impulse response functions indicate that increases/decreases in the bond yield spreads of Mexico, Russia and South Korea raise/lower their exchange market pressure, and the effects of shocks in the bond yield spreads of the US also lead to depreciation/appreciation pressures in the local currencies of the emerging countries. The quantile connectedness analysis, which allows for the role of regimes, reveals that the weights of the domestic and foreign bond yield spread in explaining variations of exchange market pressure indices are higher when exchange market pressure indices are not in a normal regime, indicating the role of extreme development conditions in the exchange market. The quantile regression model underlines that an increase in the domestic bond yield spread leads to a rise in its exchange market pressure index during all exchange market pressure periods in Mexico, and the relevant effects are valid during periods of high exchange market pressure in Russia. Our results also show that Russia differs from Mexico and South Korea in terms of the factors influencing the demand for domestic currency, and we have demonstrated the role of domestic macroeconomic and financial conditions in surpassing the effects of US financial stress. More specifically, the impacts of the domestic and foreign financial stress vary across regimes and are asymmetric.

This study enriches the literature on factors affecting the exchange market pressure of emerging countries. The results have significant economic implications for policymakers, indicating that the exchange market pressure index may trigger a financial crisis and economic recession.

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).

Managers must make numerous strategic decisions in order to initiate and implement a business model innovation (BMI). This paper examines how managers perceive the management team interacts when making BMI decisions. The paper also investigates how group biases and board members’ risk willingness affect this process.

Empirical data were collected through 26 in-depth interviews with German managing directors from 13 companies in four industries (mobility, manufacturing, healthcare and energy) to explore three research questions: (1) What group effects are prevalent in BMI group decision-making? (2) What are the key characteristics of BMI group decisions? And (3) what are the potential relationships between BMI group decision-making and managers' risk willingness? A thematic analysis based on Gioia's guidelines was conducted to identify themes in the comprehensive dataset.

First, the results show four typical group biases in BMI group decisions: Groupthink, social influence, hidden profile and group polarization. Findings show that the hidden profile paradigm and groupthink theory are essential in the context of BMI decisions. Second, we developed a BMI decision matrix, including the following key characteristics of BMI group decision-making managerial cohesion, conflict readiness and information- and emotion-based decision behavior. Third, in contrast to previous literature, we found that individual risk aversion can improve the quality of BMI decisions.

This paper provides managers with an opportunity to become aware of group biases that may impede their strategic BMI decisions. Specifically, it points out that managers should consider the key cognitive constraints due to their interactions when making BMI decisions. This work also highlights the importance of risk-averse decision-makers on boards.

This qualitative study contributes to the literature on decision-making by revealing key cognitive group biases in strategic decision-making. This study also enriches the behavioral science research stream of the BMI literature by attributing a critical influence on the quality of BMI decisions to managers' group interactions. In addition, this article provides new perspectives on managers' risk aversion in strategic decision-making.

This chapter aims to estimate the impact of the use of an innovative cultivation method on the social, economic and environmental aspects in the French region Aix-en-Provence, by using the survey data for 200 heterogeneous vegetable producers (organic and conventional). It distinguishes three types of producers in the French region Aix-en-Provence. First, conventional producers (n = 100) who used a high level of mechanization, better access to water, high yield, high labor costs. Second, certified organic producers (n = 70) who used organic technologies such as biotechnology and rotation, low yield, high organic product price compared to conventional products, a family workforce and high transport. Third, noncertified organic producers (n = 30) have used the same technologies as certified organic producers, while they sell their products at the same price as conventional products. Labor is the member of the family. These noncertified farms are marked by high operating and transport costs and low yield compared to conventional producers or certified organic producers. The results show that this cultivation method has a positive effect on the environmental aspect, however a negative one on the social and economic aspect.

This study examines the effects of financial literacy and financial risk tolerance on investor behavior by introducing social stigma as a mediator and emotional intelligence as a moderating factor.

Data is collected from 761 financially independent individual investors, with a minimum age of 25 years, a minimum of five years of stock market experience and residing in five selected major Indian cities. The collected data is subsequently analyzed using SmartPLS. Homogeneous purposive sampling followed by snowball sampling was employed.

The findings of the study demonstrate a strong and noteworthy impact of financial literacy on investor behavior. The research reveals that social stigma acts as a partial mediator and emotional intelligence plays a significant moderator with direct effects and indirect effects between financial literacy, financial risk tolerance, social stigma and investor behavior.

Exploring emotional intelligence in financial decisions enriches academic programs by integrating it into financial education. Collaboration between academia and financial institutions yields practical tools, infusing emotional intelligence into services. This prompts systemic shifts, reshaping education and societal discourse, fostering inclusive, emotionally intelligent financial landscapes, aiming to redefine both academic teachings and real-world financial practices.

Integrating emotional intelligence into government-led financial literacy programs can transform societal perspectives on financial decision-making. Customized services, destigmatizing workshops and collaborative efforts with academia foster an emotionally intelligent financial landscape, reshaping traditional paradigms.

Promoting open societal discussions about finances combats stigma, fostering a supportive space for risk-taking. Emphasizing emotional intelligence in awareness campaigns cultivates inclusivity and confidence. Normalizing financial talks empowers individuals, enhancing their well-being. Elevating both financial literacy and emotional intelligence enhances overall financial health, nurturing a community adept at navigating financial journeys.

This study marks a notable contribution to behavioral finance and social stigma theory by examining their intersection with emotional intelligence. It uniquely introduces social stigma as a mediator and emotional intelligence as a moderator, unexplored in this context. This novelty underscores the research’s significance, offering practical insights into financial well-being.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-08-2023-0626

The purpose of this paper is to fill the momentous gap by explicitly investigating the asymmetric effects of monetary policy (MP) on non-bank financial intermediation (NBFI) assets.

The authors utilized panel data from 29 countries for the period of 2012–2020 and used the quantile regression estimation. In addition to simultaneous quantile regression (SQR), the authors also employ quantile regression with clustered data (Parente and Silva, 2016) and the generalized quantile regression (GQR) method (Powell, 2020).

The empirical results show a significant heterogeneous impact of MP. While there is a positive relationship between MP and NBFI assets (“waterbed effect”) at lower quantiles of NBFI assets, at middle and higher quantiles, MP has a negative impact on NBFI assets (“search for yield” effect). The authors further find that negative impact strengthens as the quantile levels of NBFI assets rise from mid to high. Findings also reveal that “procyclicality” (except higher quantile) and “institutional demand” hypotheses hold. However, regarding “regulatory arbitrage,” mixed results are observed indicating the impact of Basel III requirements.

Previous empirical studies have concentrated on either the Dynamic Stochastic General Equilibrium (DSGE) framework or conditional mean regression approaches and delivered mixed findings of the MP effects on NBFI. The current paper takes a step toward dealing with this issue by deploying quantile regression methodology, which shows the impact of MP on NBFI at different conditional distributions (quantiles) of NBFI assets instead of just NBFI's conditional mean distribution.

Our result of this paper aims to indicate that the beta pricing formula could be applied in a long-term model setting as well.

In this paper, we show that the capital asset pricing model can be derived from a three-period general equilibrium model.

We show that our extended model yields a Pareto efficient outcome.

The capital asset pricing model (CAPM) model can be used for pricing long-lived assets.

Long-term modelling and sustainability can be modelled in our setting.

Our results were only known for two periods. The extension to 3 periods opens up a large scope of applicational possibilities in asset pricing, behavioural analysis and long-term efficiency.

Gender-diverse people experience unique cultural and interpersonal stigma in mainstream society and sometimes within their own communities; they face allegations of inauthenticity based on their nonconformity to either cisnormative or transnormative gender regimes. Based on 21 in-depth life history interviews, we unveil the intricate interactional process of negotiating identity and authenticity in the biographical work of gender-diverse individuals. In this study, gender-diverse people engaged in a “gender audit” with their gender-diverse interviewer. Gender audits yield verbal performances of gender with oneself and others. Ambiguity was “accounted for” or “embraced and created” in their biographical work to organize their life stories and undermine binary essentialism – a discourse that was “discursively constraining.” Gender audits took place in participants' day-to-day lives, either through self-audits, questioning from others, or both. In the final analysis, we assert that we all engage in gender auditing. Gender audits are intersubjective sites of domination, subordination, resistance, and social change. Gender diversity, then, can be viewed as a product of gender in flux.

Heating, ventilating, air-conditioning and cooling (HVAC) systems are crucial in daily health-care facility services. Design-related defects can lead to maintenance issues, causing service disruptions and cost overruns. These defects can be avoided if a link between the early design stages and maintenance feedback is established. This study aims to use experts’ experience in HVAC maintenance in health-care facilities to list and evaluate the risk of each maintenance issue caused by a design defect, supported by the literature.

Following semistructured interviews with experts, 41 maintenance issues were identified as the most encountered issues. Subsequently, a survey was conducted in which 44 participants evaluated the probability and impact of each design-caused issue.

Chillers were identified as the HVAC components most prone to design defects and cost impact. However, air distribution ducts and air handling units are the most critical HVAC components for maintaining healthy conditions inside health-care facilities.

The unavailability of comprehensive data on the cost impacts of all design-related defects from multiple health-care facilities limits the ability of HVAC designers to furnish case studies and quantitative approaches.

This study helps HVAC designers acquire prior knowledge of decisions that may have led to unnecessary and avoidable maintenance. These design-related maintenance issues may cause unfavorable health and cost consequences.