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Financial ratios are often used to classify firms into different clusters of financial performance. This study aims to classify firms using financial ratios with advanced techniques and identify the transition matrix of firms moving clusters during the COVID-19 period.

This study uses compositional data (CoDa) analysis based on existing clustering methods with transformed data by weighted logarithms of financial ratios. The data include 66 listed firms in Vietnam’s food and beverage and fishery sectors over a three-year period from 2019 to 2021, including the COVID-19 period.

These firms can be classified into three clusters of distinctive characteristics, which can serve as benchmarks for solvency and profitability. The results also show the migration from one cluster to another during the COVID-19 pandemic, allowing for the calculation of the transition probability or the transition matrix.

The findings indicate three distinct clusters (good, average and below-average firm performance) that can help financial analysts, accountants, investors and other strategic decision-makers in making informed choices.

Clustering firms with their financial ratios often suffer from various limitations, such as ratio choices, skewed distributions, outliers and redundancy. This study is motivated by a weighted CoDa approach that addresses these issues. This method can be extended to classify firms in multiple sectors or other emerging markets.

Scholars have extensively studied the concept of strategic entrepreneurship (SE), shedding light on its antecedents, dynamics and outcomes. However, a notable gap exists in understanding the reliability of its performance implications, which explains the inherent risks as well as the possibility of yielding outliers (instances of exceptionally high or low performance). Addressing this gap, this study aims to present a detailed analysis of the implications of SE for the variance of resulting performance distribution.

This conceptual study uses the deductive theory-building approach to dissect the four dimensions of SE (entrepreneurial mindset, entrepreneurial leadership and culture, managing resources strategically and applying creativity and developing innovations) as presented by Ireland et al.’s (2003) model, offering theoretical propositions on how each of them influences the variability of resulting performance distribution.

This study demonstrates that the strategic entrepreneurship (SE) dimensions have distinct impacts on the reliability/variability of performance outcomes, acting as boosters or attenuators in the volatile, uncertain, complex and ambiguous (VUCA) context.

The study uniquely links each component of SE with outcome variability in VUCA environments, thereby shifting the focus from traditional performance metrics to outcome variability. This approach complements the existing body of knowledge on the performance implications of the SE construct by integrating a previously neglected critical perspective on the reliability of resulting performance distribution. These insights allow subsequent investigation of SE’s outcomes, including explaining the likelihood of obtaining positive outlier performance or firm failure.

The banking sector is one of the main drivers of any developed economy and the decisions of individual banks can have global consequences on markets. In recent decades, the European banking sector has undergone major transformations, including restructuring, mergers and changes in regulation and supervision. This has attracted the interest of academics and policymakers alike. The purpose of this paper is to analyze the efficiency in the European banking sector, but there is no consensus in the literature on which factors of banks affect their efficiency.

This study analyzes data from the consolidated financial statements of a sample of 471 banks over the period 2005–2022 from 39 countries. Two methodologies are applied: data envelopment analysis methodology for the calculation of efficiency, both input- and output-oriented, and Tobit regression model to determine which variables significantly affect banks’ efficiency scores.

The results show that the efficiency scores are similar in the input-oriented and output-oriented model. The Tobit model shows that the variables that positively affect efficiency are the ROA, size, capital ratio and liquidity. On the other hand, the variables that decrease the extent of efficiency are the provisions ratio and the fact of being a financial entity under the Single Supervisory Mechanism.

The main contribution of this study is a more comprehensive and global approach that includes aspects of the most important insights from the previous literature, over a very extended period and including bank and macroeconomic environment characteristics.

Corporate real estate management (CREM) is complex due to an increasing number of real estate (RE) added values and the tensions between them. RE managers are faced with trade-offs: to choose a higher performance for one added value at the cost of another. CREM research mainly deals with trade-offs in a hypothetical sense, without looking at the characteristics of the RE portfolio nor the specific context in which trade-offs are made. The purpose of this paper is to further develop the concept of real estate value (REV) optimisation with regard to tensions between decreasing CO₂ emissions and supporting user activities.

Mixed method study. REV optimisation between user activities and energy efficiency for police stations in the Netherlands built between 2000 and 2020 is analysed. This is complemented by interviews with an RE manager and senior user of police stations and analysis of policy documents.

The characteristics of the police station portfolio indicate no correlation between user activities and energy efficiency for the case studied. This is complemented by interviews, from which it becomes clear that there was in fact little tension between supporting user activities and energy efficiency. The performances of these two different added values were optimised separately.

This study combines different scales (building and portfolio level) with different types of data: portfolio analysis, document analysis and interviews. This creates a comprehensive image of whether and how the Netherlands police optimised the two RE values.

This paper aims to empirically examine the influence of macroeconomic and socioeconomic factors on improving financial inclusion in India, with a specific focus on two distinct indicators of financial inclusion.

This study has used a time-series data set covering the years 1996 to 2022, using a nonlinear autoregressive distributed lag methodology. This approach allows for the examination of both short- and long-run effects of key macroeconomic and socio-economic indicators, including GDP per capita growth, remittance inflows and the income share held by the lowest 20% of the population on the growth of two financial inclusion indicators: the number of commercial bank branches and ATMs per 100,000 adults.

Model-1 investigates how commercial bank branch growth affects financial inclusion. Positive remittance inflow growth and a rise in the income share of the bottom 20% both lead to increased financial inclusion in both the short and long term, with the effects being more pronounced in the long run. Conversely, negative effects of remittance inflow growth and a decline in GDP per capita growth lead to reduced financial inclusion, primarily affecting the long run. Focusing on ATM growth, Model-2 reveals that positive remittance inflow growth has the strongest impact on financial inclusion in the short term. While income share growth for the bottom 20% and GDP growth also positively influence financial inclusion, their effects become significant only in the long run. Conversely, a decline in GDP per capita growth hinders financial inclusion, primarily affecting the short run.

This study fills a gap in research on macroeconomic and socioeconomic factors influencing financial inclusion in India by examining the impact of GDP per capita growth, remittance inflows and the income share held by the lowest 20% of the population, an area relatively unexplored in the Indian context. Second, the study provides comprehensive distinct results for different financial inclusion indicators, offering valuable insights for policymakers. These findings are particularly relevant for policymakers working toward Sustainable Development Goal 8.10.1, as they can use the results to tailor policies that align with SDG objectives. Additionally, policymakers in other developing nations can benefit from this study’s findings to enhance financial inclusion in their respective countries.

This study empirically examines calendar anomalies, with a specific focus on the day-of-the-week (DOW) effect within the context of socially responsible investing (SRI).

This study analyzes daily returns from the Dow Jones Sustainability Index (DJSI) Asia Pacific for the past five years (2019–2024). The DJSI is widely regarded as a leading benchmark for corporate sustainability and aligns closely with SRI principles. To explore the DOW effect, the study employs various types of regression analysis to identify patterns of significantly abnormal returns on specific trading days of the week.

Through various estimation methods, there is robust evidence of the DOW effect within the DJSI Asia Pacific. Specifically, Tuesday returns are consistently positive and significantly higher than returns on other trading days of the week.

The findings carry managerial implications for SRI-oriented investors aiming to formulate trading strategies that enhance the likelihood of achieving investment goals within the DJSI Asia Pacific. Furthermore, the findings reveal potential market inefficiencies associated with sustainable investment, which warrant further policy consideration.

This is the first study to examine the presence of the DOW effect in stock returns specifically within the SRI context. Furthermore, by analyzing data from the recent five years (2019–2024), this study offers contemporary insights into the patterns of daily returns within the DJSI Asia Pacific.

This study aims to assess how ethical sales behaviour affects switching costs typology, mediated by trust and moderated by brand affiliation, monthly contributions and the number of dependent beneficiaries in medical schemes in South Africa.

A quantitative study targeted a non-probability judgement sample of 250 main members of medical schemes, elicited near health-care facilities in South Africa’s Gauteng province. Data was collected in a face-to-face survey and analysed using structural equation modelling on AMOS version 29 and PROCESS procedure for Statistical Package of Social Science release 2.041.

The results show that ethical sales behaviour negatively affects trust and positively affects evaluation, monetary and personal relational loss costs. Trust positively affects personal relational loss costs, economic risk, evaluation, monetary and benefit loss costs. Moreover, trust mediates the effect of ethical sales behaviour on evaluation, monetary and personal relational loss costs. Finally, the number of dependent beneficiaries, monthly contributions and brand affiliation significantly moderate these interactions.

The paper validates the application of commitment-to-trust theory in mediating how the effects of the general theory of marketing ethics on switching costs typology differ according to the number of dependent beneficiaries, monthly contributions and brand affiliation with medical schemes.

Cryptocurrencies have transformed the financial landscape and raised environmental concerns, particularly distinguishing between energy-intensive (dirty) cryptocurrencies and environmentally friendly (green) cryptocurrencies. This study investigates the role of energy-intensive and ecologically friendly cryptocurrencies in sustainable investments, exploring their potential as hedging tools amid market and geopolitical stresses.

Employing a time-varying parameter vector auto-regression (TVP-VAR) connectedness approach, the research analyzes the interactions and spillover effects among clean and dirty cryptocurrencies, green bonds, and traditional financial assets. It also explores portfolio diversification strategies like minimum variance, correlation and connectedness portfolios, evaluating their risk minimization efficacy while incorporating green financial instruments. Empirical data on daily closing prices and financial indices are used to assess financial interconnectedness and evaluate portfolio diversification strategies.

Green bonds consistently provide strong hedging capabilities, while clean cryptocurrencies exhibit a more nuanced role influenced by market maturity and regulations. The results underscore the significance of promoting green finance to bolster investments in sustainable projects and enhance risk management strategies for investors. This research enriches the green finance literature by detailing the financial interconnectedness within the market and providing strategic insights for embedding sustainability in investment portfolios against a backdrop of global economic and geopolitical uncertainties.

The research highlights the importance of green finance in promoting sustainability and reducing environmental impact. It advocates for regulatory frameworks that support sustainable financial instruments, encouraging the development of financial products aligned with environmental goals and fostering a more sustainable economy.

These research findings provide actionable guidance for investors and policymakers to develop diversified investment strategies incorporating green bonds and clean cryptocurrencies capable of balancing risks and returns. The study also urges policymakers to establish clear guidelines and incentives for green investments, improving transparency and effectiveness in green finance markets.

This study uses an innovative TVP-VAR connectedness approach to examine the interactions and spillover effects among clean and dirty cryptocurrencies, green bonds and traditional financial assets. It provides new insights into the roles of green bonds and clean cryptocurrencies as hedging tools in volatile markets, enhancing the understanding of financial interconnectedness and sustainable investment strategies.

This study examines the importance of income income-shifting arrangements of US multinational corporations (MNCs) on future stock price crash risk.

This study employs a sample of 7,641 corporation-year observations over the 2005–2017 period and uses ordinary least squares regression analysis.

The authors find that the income-shifting arrangements of MNCs are positively and significantly associated with stock price crash risk after controlling for corporate tax avoidance and other known determinants of stock price crash risk in the regression model. This result is robust to alternative measures of stock price crash risk and income-shifting, and several endogeneity tests. The authors also observe that income-shifting arrangements increase stock price crash risk both directly and indirectly through the information opacity channel. Finally, in cross-sectional analyses, the authors find that the positive association between income-shifting and stock price crash risk is more pronounced for MNCs that use tax haven subsidiaries and have weak corporate governance mechanisms.

The authors provide new empirical evidence that MNCs will likely face significant capital market consequences regarding their income-shifting arrangements.

This study aims to explore the relationship between managerial ownership and environmental innovation, particularly focusing on the impact of minority shareholder protection within the context of China’s A-share listed companies.

The study employs a fixed effect model over a decade-long sample, analysing secondary data from nonfinancial Chinese A-share firms. The two-stage least squares (2SLS) method is adopted to address endogeneity concerns.

The results demonstrate a significant positive influence of managerial ownership on environmental innovation, suggesting that top managers who have a say in the boardroom are inclined towards sustainable development. The presence of minority shareholders' protection positively moderates this relationship, underlining their roles in fostering environmentally friendly development. The subsample analysis showed that these relationships vary between state-owned enterprises (SOEs) and non-SOEs. It also differs between heavily and lightly polluting industries, which indicates that it is not enough to just have internal self-management, and more external pressure is necessary in heavily polluting industries.

Our study underscores the importance for managers to recognize the potential of aligning their ownership interests with environmental objectives. Companies can enhance their commitment to sustainability by fostering an internal environment that supports minority shareholder rights.

This study specifically focuses on the role of top managers and minority shareholders, providing new empirical evidence on how their influence can drive sustainable development initiatives. It is also among the few studies that differentiate between firm characteristics and pollution intensity, which provides valuable insights into how the impact of managerial ownership and minority shareholder protection varies across different contexts.