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Investors' behavior in financial markets is often under the influence of various psychological and cognitive factors, as well as personality characteristics. This research explores which behavioral factors and personality traits affect investment decisions and, consequently, investment performance.

A survey analysis was conducted on a sample of 310 investors in Croatia. Partial least squares structural equation modeling was used to obtain the results.

Overconfidence heuristic, prospect theory elements, emotions and stability and plasticity (as big two personality dimensions) positively affect investment decisions, while herding has a negative effect. Investment decisions, observed through the preference for long-term investments, consequently have a positive effect on the investment performance satisfaction.

This research proposes a unique comprehensive model of the effect of numerous different cognitive and psychological behavioral factors on investment decisions. Furthermore, the influence of investment decisions on investment performance is observed simultaneously. Understanding human behavior based on their personal characteristics can help investors to make better investment decisions. Advisors can learn from human behavior and guide their clients in the right direction when it comes to stock investment. Scientists will be able to replicate the model with other data and make comparative analyses.

The purpose of this study is to investigate the association between nonaudit services (NAS) and out-of-period adjustments (OOPAs). Over the years, the number of OOPAs has risen while the number of restatements has decreased. This could indicate an improvement in financial reporting quality. It could also indicate the use of a type of stealth restatement for opportunistic purposes. These less prominent restatements are more likely to go undetected and could perpetuate opportunistic disclosure and mitigate the likelihood of unfavorable market reactions.

The authors use a two-stage multivariate regression analysis to examine the relationship between NAS and the reporting of an OOPA. The authors use prior research on NAS to guide the model development. The authors perform several robustness checks including different types of NAS and different characteristics of OOPAs.

The results indicate that NAS has a significantly negative association with the existence of OOPAs. The core findings suggest that NAS does not impair auditor independence. Rather, greater amounts of NAS may contribute to knowledge spillover, which leads to higher financial reporting and audit quality. The results are robust to several additional tests.

The results raise interesting implications for regulators, executives, auditors, investors and future research. The authors provide insight into the relationship between NAS and auditor independence.

To the best of the authors’ knowledge, prior research has not considered the effect of NAS on OOPAs. The authors contribute to the literature by providing evidence that OOPAs, a form of stealth restatements, is an important consideration in audit quality research.

This study aims to evaluate the current situation of education for sustainable development, climate change education and environmental education in a nationwide context. Methodologically, this study calls for more research to go beyond case studies and take a similar approach to examine university curricula and facilitate cross-country comparisons.

This paper examines the status of climate and sustainability curricula in Taiwan’s higher education system. Using the course catalog for the 2020–2021 academic year, the authors constructed a unique data set that includes 1,827 courses at 29 major universities in Taiwan. In each institution, the authors search for course titles that include “climate,” “sustainable/sustainability” and “environment/environmental” as keywords and code the courses according to their disciplines.

The finding highlights the variations across institutional types and subject matters. Public universities have an average of 4.94 related courses per 1,000 students, whereas private universities have only 3.13. In general, the relevant courses are more concentrated in the STEM and bioscience fields. The curricula, however, are seriously constrained by the disciplinary structure and foster few transdisciplinary perspectives.

The authors seek to go beyond case studies and offer one of the most comprehensive curricula samples at the national level. Taiwan adds an important data point, as the current literature focuses heavily on the USA and Europe.

A charity’s core purpose is legally mandated and delivery thereof is not a corporate social responsibility (CSR) activity which, by definition, is voluntary in nature. Any CSR activity not required by law should be “incidental” and be an outcome of a core purpose/object and not a focus of activity. The purpose of this study, therefore, is to address the lack of research into voluntary CSR activities conducted by charities so that charities might have a clearer operating platform and do not involuntarily contravene legislation.

This was an exploratory investigation using purposive sampling of senior leaders in UK charities. This study uses a case study approach to identify pragmatic areas of concern and also identify practical actions.

The conventional hierarchical ordering of Carroll’s CSR pyramid (1991) for profit-focussed organisations were found to be inconsistent with those for charitable organisations which were: ethical, legal, economic and philanthropic/voluntary/incidental.

This was an exploratory study and would benefit from further investigation.

Corporate social responsibility actions undertaken by charities need to be carefully evaluated to ensure that they comply with the core charitable purpose or are incidental.

Many employees in charities are motivated by social justice; however, they need to be cautious that they do not exceed the core purpose of the charity.

To the best of the authors’ knowledge, no research was identified which has addressed the fundamental issue of charities’ core purposes and the extent to which charities might legally undertake CSR activities.

The study aims to develop a model that supports the application of data science techniques for real estate professionals in the fourth industrial revolution (4IR) era. The present 4IR era gave birth to big data sets and is beyond real estate professionals' analysis techniques. This has led to a situation where most real estate professionals rely on their intuition while neglecting a rigorous analysis for real estate investment appraisals. The heavy reliance on their intuition has been responsible for the under-performance of real estate investment, especially in Africa.

This study utilised a survey questionnaire to randomly source data from real estate professionals. The questionnaire was analysed using a combination of Statistical package for social science (SPSS) V24 and Analysis of a Moment Structures (AMOS) graphics V27 software. Exploratory factor analysis was employed to break down the variables (drivers) into meaningful dimensions helpful in developing the conceptual framework. The framework was validated using covariance-based structural equation modelling. The model was validated using fit indices like discriminant validity, standardised root mean square (SRMR), comparative fit index (CFI), Normed Fit Index (NFI), etc.

The model revealed that an inclusive educational system, decentralised real estate market and data management system are the major drivers for applying data science techniques to real estate professionals. Also, real estate professionals' application of the drivers will guarantee an effective data analysis of real estate investments.

Numerous studies have clamoured for adopting data science techniques for real estate professionals. There is a lack of studies on the drivers that will guarantee the successful adoption of data science techniques. A modern form of data analysis for real estate professionals was also proposed in the study.

This study aims to explore the connection between demographic traits and the choice of attraction patterns among international repeat tourists.

The study employed a questionnaire survey to collect data from 1550 international repeat tourists who visited Tanzania between November 2022 and July 2023. Convenient sampling was employed as tourists were selected from the three international airports of Tanzania, namely Kilimanjaro International Airport, Julius Nyerere International Airport, and Abeid Aman Karume International Airport. A multinomial logistic regression model was used to examine the impact of socio-demographic characteristics on the selection of attraction patterns among international repeat tourists.

The study revealed that demographic factors, including age, marital status, income level, occupation, and education level, exhibit statistically significant correlations with preferences for distinct attraction patterns. This significance was established through a p-value of less than 0.05 for all the aforementioned variables.

This study is primarily focused on international repeat tourists, thereby limiting insights into the preferences of domestic tourists. To better inform strategies aimed at attracting a larger domestic tourist base, future research may prioritize the investigation of choice of attractions patterns among domestic tourists in relation to their demographic characteristics.

This study contributes to the nuanced understanding of international tourist behavior by unraveling the extent to which demographic traits impact tourists’ choices of attraction patterns, thereby providing insights crucial for effective marketing strategies, improved visitor experiences, and sustainable tourism development strategies.

This study probes the psychological interplay between investor sentiment and the returns of cryptocurrencies Bitcoin and Ethereum. Employing the Granger causality test, the authors aim to gauge how extensively the Fear and Greed Index (FGI) can predict cryptocurrency return movements, exploring the intricate bond between investor emotions and market behavior.

The authors used the Granger causality test to achieve research objectives. Going beyond conventional linear analysis, the authors applied Smooth Quantile Regression, scrutinizing weekly data from July 2022 to June 2023 for Bitcoin and Ethereum. The study focus was to determine if the FGI, an indicator of investor sentiment, predicts shifts in cryptocurrency returns.

The study findings underscore the profound psychological sway within cryptocurrency markets. The FGI notably predicts the returns of Bitcoin and Ethereum, underscoring the lasting connection between investor emotions and market behavior. An intriguing feedback loop between the FGI and cryptocurrency returns was identified, accentuating emotions' persistent role in shaping market dynamics. While associations between sentiment and returns were observed at specific lag periods, the nonlinear Granger causality test didn't statistically support nonlinear causality. This suggests linear interactions predominantly govern variable relationships. Cointegration tests highlighted a stable, enduring link between the returns of Bitcoin, Ethereum and the FGI over the long term.

Despite valuable insights, it's crucial to acknowledge our nonlinear analysis's sensitivity to methodological choices. Specifics of time series data and the chosen time frame may have influenced outcomes. Additionally, direct exploration of macroeconomic and geopolitical factors was absent, signaling opportunities for future research.

This study enriches theoretical understanding by illuminating causal dynamics between investor sentiment and cryptocurrency returns. Its significance lies in spotlighting the pivotal role of investor sentiment in shaping cryptocurrency market behavior. It emphasizes the importance of considering this factor when navigating investment decisions in a highly volatile, dynamic market environment.

This study aims to evaluate the adequacy of climate risk disclosure by providing empirical evidence on whether corporate disclosure meets rising stakeholders’ demand for risk disclosure concerning climate change.

Drawing on a triangulated approach for collecting data from multiple sources in a longitudinal study, we perform a panel regression analysis on a sample of multinational firms between 2007 and 2021. Inspired by the Global Reporting Initiative (GRI) principles, our innovative and inclusive model of measuring firm-level climate risks underscores the urgent need to redefine materiality from a broader value creation (rather than only financial) perspective, including the impact on sustainable development.

The findings of this study provide evidence of limited corporate climate risk disclosure, indicating that organisations have yet to accept the reality of climate-related risks. An additional finding supports the existence of a nexus between higher corporate environmental disclosure and higher corporate resilience to material financial and environmental risks, rather than pervasive sustainability risk disclosure.

We argue that a mechanical process for climate-related risk disclosure can limit related disclosure variability, risk reporting priority selection, thereby broadening the short-term perspective on financial materiality assessment for disclosure.

This study extends recent literature on the adequacy of corporate risk disclosure, highlighting the importance of disclosing material sustainability risks from the perspectives of different stakeholder groups for long-term success. Corporate management should place climate-related risks at the centre of their disclosure strategies. We argue that reducing the systematic underestimation of climate-related risks and variations in their disclosure practices may require regulations that enhance corporate perceptions and responses to these risks.

This study emphasises the importance of reconceptualising materiality from a multidimensional value creation standpoint, encapsulating financial and sustainable development considerations. This novel model of assessing firm-level climate risk, based on the GRI principles, underscores the necessity of developing a more comprehensive approach to evaluating materiality.

This paper aims to examine whether managerial sentiment, extracted from annual reports, is associated with corporate risk-taking in the context of Chinese companies. This study expands the vein of literature on overconfidence theory.

By leveraging textual analysis on Chinese listed companies’ annual reports, the authors construct firm-level managerial sentiment during 2007 and 2021 to examine how managerial sentiment influences corporate risk-taking after control for firm characteristics. Corporate risk-taking is denoted by corporate investment engagements: capital expenditures and net fixed asset investment.

Results show that incentives for corporate risk-taking are likely to increase with the positive managerial sentiment and decrease with the negative sentiment in companies’ annual reports. Positive managerial sentiment is associated with over-/under-investment and low/high investment efficiency. Further additional tests show that the managerial sentiment effect only holds during low economic uncertain years and samples of private-owned firms. Furthermore, the robust tests indicate that there is no endogenous issue between managerial sentiment and corporate risk-taking.

Annual report textual-based managerial sentiment may not perfectly reflect managers’ lower frequency sentiment (e.g. weekly, monthly and quarterly sentiment). Future studies could attempt to capture managers’ on-time sentiment by using media sources and corporate disclosures.

To the best of the authors’ knowledge, this paper is the first research to provide insights into supervising managers’ corporate decisions by observing their textual information usage in corporate disclosure. Moreover, the approach of measuring managerial sentiment might be a solution to monitoring managerial class.

This paper contributes to the literature on accounting and finance studies, adding another piece of empirical evidence on content analysis by examining a unique language and institutional context (i.e. China). Besides, the paper notes that in line with the English version disclosure, based on Chinese semantic words, managerial sentiment in the Chinese-speaking world has magnitude on corporate decisions. The research provides insights into supervising managers’ corporate decisions by observing their textual information usage in corporate disclosure. Moreover, the approach to measuring managerial sentiment may be a practical solution to monitoring managerial class.