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This paper investigates the relationship between the sustainable finance disclosure regulation (SFDR) and the performance of unlisted real estate funds.

While existing literature has primarily focused on the impact of voluntary sustainability disclosure, such as certifications or reporting standards, this study addresses a significant research gap by constructing and analyzing the financial J-Curve of 40 funds under the SFDR. The authors employ a panel regression analysis to examine the effects of different SFDR categories on fund performance.

The findings reveal that funds categorized under Article 8 of the SFDR do not exhibit significantly poorer performance compared to funds categorized under Article 6 during the initial phase after launch. On average, Article 8 funds even demonstrate positive returns earlier than their peers. However, the panel regression analysis suggests that Article 8 funds slightly underperform when compared to Article 6 funds over time.

While investors may not anticipate lower initial returns when opting for higher SFDR categories, they should nevertheless be aware of the limitations inherent in the existing SFDR labeling system within the unlisted real estate sector.

To the best of our knowledge, this study represents the first quantitative examination of unlisted real estate fund performance under the SFDR. By providing unique insights into the J-Curves of funds, our research contributes to the existing body of knowledge on the impact of sustainability regulations in the financial sector.

This paper aims to examine the relationship between environmental, social and governance (ESG) performance and systemic risk sensitivity of Chinese listed companies. From the consumer loyalty and investor structure perspectives, the relationship between ESG performance and systemic risk sensitivity is analyzed.

Since Morgan Stanley Capital International (MSCI) ESG officially began to analyze and track China A-shares from 2018, 275 listed companies in the SynTao Green ESG testing list for 2015–2021 are selected as the initial model. To measure the systematic risk sensitivity, this study uses the beta coefficient, from capital asset pricing model (CPAM), employing statistics and data (STATA) software.

The study reveals that high ESG rating companies have high corresponding consumer loyalty and healthy trading structure of institutional investors, thereby the systemic risk sensitivity is lower. This paper reveals that companies with high ESG rating are significantly less sensitive to systemic risk than those with low ESG rating. At the same time, ESG has a weaker impact on the systemic risk of high-cap companies than low-cap companies.

The study helps the companies understand the influence of market value on the relationship between ESG performance and systemic risk sensitivity. Moreover, this paper explains explicitly why ESG performance insulates a firm’s stock from market downturns with the lens of consumer loyalty theory and investor structure theory.

The paper provides new insights on the company’s ESG performance that significantly affects the company’s systemic risk sensitivity.

Employee Stock Options [ESOs] have been used widely as a component of employees' compensation. To maximise the incentive effect of these options it is very important to understand the exercise decision of the employees. This is an important financial decision that is dependent on both rational and psychological factors. This paper aims to study the mediating role of Herding Bias on Personality Traits and the employees' decision to exercise ESOs.

The data were collected through a self-structured questionnaire from 210 employees of Banks and NBFCs [Non-Banking Financial Companies] who have received and exercised the ESOs. SPSS MACRO version 25 was used to understand the mediational effect of Herding Bias on Personality Traits and Employees' decision to exercise their ESOs.

The results showed that Personality Traits affect the employees' decision to exercise their ESOs. The study also shows a partial negative mediating effect of Herding Bias on Personality Traits and employees' decision to exercise ESOs.

Limited study has been conducted on how the employees make their decision to exercise ESOs. Although extant studies have touched upon the importance of including behavioural biases in ascertaining the exercise decision of the employees, the predictors of the behavioural biases have not been studied under this context. To the best of the author's knowledge, this study is the first in itself to study the inter-linkage between Personality Traits, Herding Bias and employees' decision to exercise ESOs.

This study examines the Robo-Advisors (RA) based on Artificial Intelligence (AI), a new service that digitises and automates investment decisions in the financial and banking industries to provide low-cost and personalised financial advice. The RAs use objective algorithms to select portfolios, reduce behavioural biases, and improve transactions. They are inexpensive, accessible, and transparent platforms. Objective algorithms improve the believability of portfolio selection.

This study adopts a qualitative approach consisting of an exploratory examination of seven different RA case studies and analyses the RA platforms used in the banking industry.

The findings provide two different approaches to running a business that are appropriate for either fully automated or hybrid RAs through the realisation of two platform model frameworks. The research reveals that relying solely on algorithms and not including any services involving human interaction in a company model is inadequate to meet the requirements of customers in decision-making.

This study emphasises key robo-advisory features, such as investor profiling, asset allocation, investment strategies, portfolio rebalancing, and performance evaluation. These features provide managers and practitioners with new information on enhancing client satisfaction, improving services, and adjusting to dynamic market demands.

This study fills the research gap related to the analysis of RA platform models by providing a meticulous analysis of two different types of RAs, namely, fully automated and hybrid, which have not received adequate attention in the literature.

This study aims to examine the cryptocurrency adoption (CA) level among Indian retail investors who use cryptocurrency as an investment and mode of transaction.

Through self-administered survey questionnaires, data is collected from 397 retail investors of Haryana (India). This study adopted a quantitative method using partial least squares structural equation modeling (PLS-SEM).

This paper offered a robust model with a high explanatory value for CA in which four of the five proposed factors of diffusion of innovation theory (trialability, compatibility, complexity and observability) and one of the two proposed factors of consumer behavioral theory (perceived value) significantly influences CA. More specifically, the absence of regulatory support is a barrier to the broad adoption of cryptocurrencies, as its regulations are necessary to mitigate or minimize uncertain outcomes.

This research primarily focuses on CA in India. Thus, it can be extended to cover diverse other countries for more precise results.

The results provide insights to the government to design the policies, better regulate and make investment strategies that can ultimately enhance CA. In addition, the study’s results also inform financial educators, policymakers, employers and academicians about the significance of several variables affecting CA in India.

From a social standpoint, this study is an advance that directs central banks and governments to develop, regulate and manage digital currencies and implement a digital currency ecosystem. Moreover, the results assist in understanding investors’ perceptions and decision-making perspectives toward cryptocurrencies through the country’s digitalization.

This paper fills the study gap to assist policymakers and cryptocurrency experts in broadening their knowledge base and recognizing prioritized intentions. Additionally, this study provides a theoretical model with the latent variable for a present and pertinent matter.

The purpose of this study is to examine the extent to which promoting sense of community moderates the relationship between servant leadership style and socially responsible leadership (SRL) of public universities in Uganda.

The study adopted cross-sectional survey design to collect data at one point in time using self-administered questionnaires from 214 respondents to examine the relationship between servant leadership and socially responsible leadership with promoting sense of community as a moderator. The study used statistical package for social scientists (SPSS) PROCESS MACRO to establish clusters among the surveyed public universities and later a model was derived.

The study found a significant moderating effect of promoting sense of community on servant leadership and socially responsible leadership. Implying that investment in promoting sense of community creates awareness about the socially responsible leadership in public universities.

Managers of public universities need to pay keen interest in promoting sense of community to boost socially responsible leadership by building a strong servant leadership style through promoting sense of community for senior managers and leaders especially heads of departments, faculty deans and principals in public universities.

This study contributes to socially responsible leadership literature by advancing the idea that SRL is an important resource that enhances through instituting servant leadership and promoting sense of community in a complex environment. Ideally, servant leadership and promoting sense of community is one of the drivers of customer value, efficiency and effectiveness of public universities.

In the stock market, herding behavior occurs when investors mimic the actions of others in their investment decisions. As a result, the market becomes inefficient and speculative bubbles form. This study aims to investigate the relationship between information, overconfidence, market sentiment, experience and national culture, and herding behavior among Malaysian investors. A total of 400 questionnaires are distributed to bank institutions' investors. The survey design based on cross-sectional data is analyzed using the Partial Least Squares Structural Equation Model. The results indicate that information, market sentiment, experience, and national culture are positively related to herding behavior, while overconfidence has no effect. With this, the government should strengthen regulations to prevent the dissemination of misleading information. Moreover, investors are encouraged to overcome narrow thinking by expanding their understanding of different cultures when making investment decisions.

The purpose of this study is to identify the drivers and future scenarios of Iran’s Social Security Organization.

The research is applied in terms of orientation and mixed in terms of methodology. In this research, the methods of theme analysis, root definitions, fuzzy Delphi and Cocoso were used. The theoretical population is the managers and senior experts of the social security organization, and the sampling method was done in a judgmental way. The tools of data collection were interviews and questionnaires. The interview tool was used to extract the main and subdrivers of the research and develop the scenarios.

Through theme analysis, 35 subdrivers were extracted in the form of economic, sociocultural, financial and investment, policy, marketing, environmental and legal themes. Due to the large number of subdrivers, these factors were screened with fuzzy Delphi. Eleven drivers had defuzzied coefficient higher than 0.7 and were selected for final prioritization. The final drivers were prioritized with the CoCoSo technique, and the two drivers of social security holdings governance and state of government revenues had the highest priority. Based on these two drivers, four scenarios of prosperity, resilient social security, unstable development and collapse have been developed.

Some of the suggestions of the research are: using the capacity of FinTechs and financial startups to invest the government revenues of the organization, using digital technologies such as business intelligence for more efficient decisions and developing corporate governance in the organization.

This study aims to investigate the influence of CEO’s only-child status on corporate social responsibility (CSR) practices. It seeks to extend the understanding of upper echelon theory by examining unexplored CEO characteristics and their impact on CSR decisions.

The paper uses manually collected CEO family information and Chinese Stock and Market Accounting Research data as a basis to examine the influence of CEOs’ early-life experiences on their engagement in CSR activities. The study applies attachment security theory from developmental psychology and uses upper echelon theory, particularly focusing on CEOs’ only-child status. A comparative analysis of philanthropic donations between CEOs who are only children and those who have siblings is conducted. The study also examines the moderating effects of corporate slack resources and CEO shareholdings.

Preliminary findings suggest that CEOs who are only children are more likely to engage in CSR compared to their counterparts with siblings. However, the difference in donation amounts between the two groups tends to attenuate with decreased slack resources and increased CEO shareholdings.

To the best of the authors’ knowledge, this research represents the first attempt to investigate being the only child in one’s family and the CSR-related decision of CEOs, which extends the upper echelon theory by introducing the family science theory into the management domain.

This paper aims to explore how HR leaders can help their managers ditch the traditional command-and-control leadership style and instead adopt an enquiry-led management approach – Operational Coaching^®. This approach helps managers to develop coaching-related behaviours in their day-to-day interactions with teams, to cultivate a culture that is more collaborative, inclusive and innovative with measurable improvements in engagement, productivity and performance.

Responding to the UK’s woeful productivity and employee engagement levels, the Government sponsored a large-scale academic research study (designed, conducted and independently evaluated by the London School of Economics, LSE) to assess the impact of managers learning to use an Operational Coaching^® style of management. Managers in 62 organisations across 14 sectors worked through a learning programme designed to build managers’ confidence in using intentional enquiry as a part of their everyday management style.

LSE proved, statistically significantly, that managers increased the amount of time they spent coaching their team members by an average of 70% and generated a 74 times return on investment. LSE also noted that intervention group organisations indicated a positive sixfold improvement in employee retention than in control group organisations.

When managers learn to use an Operational Coaching^® style of management in their day-to-day work with others, it allows them to learn how to challenge, support and grow the capabilities of their team members in ways that measurably benefit the individual and the organisation. Colleagues are more engaged, recognised and rewarded. As their competency and confidence grows, managers are released from aspects of their to-do lists and are able to invest even more attention towards coaching their team members.