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This chapter addresses one of the most common and long-standing problems among college students, namely depression, as well as a potential consequence of depression, suicide. A formal definition of depression is presented, and symptoms of depression are discussed. Notably, clinical depression is differentiated from “feeling down” or having “the blues.” Common measures of depression for college students are described, and the current prevalence of depression among college students is explored, along with data pertaining to trends and trajectories. Particular attention is devoted to differences in rates and severity of depression among students of various ethnicities, gender identities, disabilities and sexual orientations. Next, the chapter covers various theories about and studies on the causes and consequences of depression, as well as preventive and remedial efforts that students can engage in to minimize the adverse effects of depression. The chapter concludes with a focus on college student suicide, including its prevalence, predictors of suicidal thoughts and behaviors and prevention and treatment of college student suicide.

Despite its devastating nature, the COVID-19 pandemic has also catalyzed a substantial surge in the adoption and integration of technological tools within economies, exerting a profound influence on the dissemination of information among participants in stock markets. Consequently, this present study delves into the ramifications of post-pandemic dynamics on stock market behavior. It also examines the relationship between investors' sentiments, underlying behavioral drivers and their collective impact on global stock markets.

Drawing upon data spanning from 2012 to 2023 and encompassing major world indices classified by Morgan Stanley Capital International’s (MSCI) market and regional taxonomy, this study employs a threshold regression model. This model effectively distinguishes the thresholds within these influential factors. To evaluate the statistical significance of variances across these thresholds, a Wald coefficient analysis was applied.

The empirical results highlighted the substantive role that investors' sentiments and behavioral determinants play in shaping the predictability of returns on a global scale. However, their influence on developed economies and the continents of America appears comparatively lower compared with the Asia–Pacific markets. Similarly, the regions characterized by a more pronounced influence of behavioral factors seem to reduce their reliance on these factors in the post-pandemic landscape and vice versa. Interestingly, the post COVID-19 technological advancements also appear to exert a lesser impact on developed nations.

This study pioneers the investigation of these contextual dissimilarities, thereby charting new avenues for subsequent research studies. These insights shed valuable light on the contextualized nexus between technology, societal dynamics, behavioral biases and their collective impact on stock markets. Furthermore, the study's revelations offer a unique vantage point for addressing market inefficiencies by pinpointing the pivotal factors driving such behavioral patterns.

A major source of external funding for US airports comes from issuing municipal bonds. Credit rating agencies evaluate the bonds using multiple factors, but the judgments behind the ratings are not well understood. This paper examines if airport rate-setting methods affect the bond ratings of US airports.

Using a set of unbalanced panel data for 58 hub airports from 2010 to 2019, we examine the effect of the rate-setting methods and other airport characteristics on Fitch’s airport bond rating.

We find that compensatory airports consistently receive a very high bond rating from Fitch. The probability of getting a very high Fitch rating increases by ∼28 percentage points for a compensatory airport. Additionally, the probability of getting a very high rating is about 33 percentage points higher for a legacy hub.

The study uses Fitch bond ratings. Future studies could examine if S&P’s and Moody’s ratings are also influenced by airport rate-setting methods and legacy hub status.

The results uncover the linkage between bond ratings and their determinants for US airports. This information is important for investors when assessing airport creditworthiness and for airport operators as they manage capital project financing.

This is the first study to evaluate the effects of rate-setting methods on airport bond rating and also the first to document a statistically significant relationship between airports’ legacy hub status and bond ratings.

This paper aims to understand whether the relationship between psychological empowerment, psychological well-being and higher person–job fit based on the self-determination theory could have mitigated the Great Resignation crisis.

A cross-sectional study was conducted by collecting data from 351 respondents working in Indian organizations (Nifty, 2020) using a standardized questionnaire by using the multifaceted psychological construct within the work context.

This study highlights that a moderated mediation relationship between psychological empowerment (specifically “impact” or “choice”) and psychological well-being (specifically “environmental mastery”) is impacted by the person–job “demand-abilities” fit and enhances the intention to stay in the current “great resignation” context.

The authors map the theoretical and empirical research of the “intention to stay” by developing the “demand-abilities” fit, which leads to higher levels of psychological empowerment and psychological well-being to build adaptability through effective learning practices.

The authors establish the underlying linkages and future research agenda to strengthen the “intention to stay” during the extraordinarily stressful context of the covid-19 pandemic.

Grounded in the stakeholder theory and signaling theory, this study aims to broaden the research agenda on environmental, social and governance (ESG) investing by uncovering public sentiments and key themes using Twitter data spanning from 2009 to 2022.

Using various machine learning models for text tonality analysis and topic modeling, this research scrutinizes 1,842,985 Twitter texts to extract prevalent ESG investing trends and gauge their sentiment.

Gibbs Sampling Dirichlet Multinomial Mixture emerges as the optimal topic modeling method, unveiling significant topics such as “Physical risk of climate change,” “Employee Health, Safety and well-being” and “Water management and Scarcity.” RoBERTa, an attention-based model, outperforms other machine learning models in sentiment analysis, revealing a predominantly positive shift in public sentiment toward ESG investing over the past five years.

This study establishes a framework for sentiment analysis and topic modeling on alternative data, offering a foundation for future research. Prospective studies can enhance insights by incorporating data from additional social media platforms like LinkedIn and Facebook.

Leveraging unstructured data on ESG from platforms like Twitter provides a novel avenue to capture company-related information, supplementing traditional self-reported sustainability disclosures. This approach opens new possibilities for understanding a company’s ESG standing.

By shedding light on public perceptions of ESG investing, this research uncovers influential factors that often elude traditional corporate reporting. The findings empower both investors and the general public, aiding managers in refining ESG and management strategies.

This study marks a groundbreaking contribution to scholarly exploration, to the best of the authors’ knowledge, by being the first to analyze unstructured Twitter data in the context of ESG investing, offering unique insights and advancing the understanding of this emerging field.

Companies are increasingly appointing a Chief Sustainability Officer (CSO) to anchor the need to highlight climate change at the senior management level. This study aims to examine how CSO power and sustainability-based compensation influence climate reporting and carbon performance.

Using one of the largest data sets to date, consisting of 18,834 company years through the author’s observations, spanning an 11-year period (2011–2021) in 33 countries. This paper used quantitative methods – specifically, ordinal logistic regression estimation. This paper measures the level of climate change disclosure based on the carbon disclosure leadership methodology. Carbon performance is based on the intensity of carbon emissions (Scope 1, Scope 2), which is a quantitative and relatively more objective measure.

The results suggest that climate change disclosure continued to increase and the carbon emissions intensity of the companies in this study gradually decreased over the sample period. This paper finds that the presence of the CSO within the top management team has a positive and significant influence on the level of information on climate change of the companies in the sample. This finding confirms the idea that the managerial capacity of CSOs motivates the disclosure of climate change. The empirical results confirm that there are differences in the role that the CSO and sustainability-based compensation play in influencing the quality of climate information disclosure in developed and developing countries.

The recourse on a mixed theoretical framework, which highlights upper echelons theory, argues the understanding of the role of CSOs in explaining the relationship between climate change disclosure–carbon performance relationship. The novelty of the study lies in the approaches adopted to describe the quality of climate change disclosure. To control for endogeneity, this paper uses a difference-in-difference analysis by adding a firm to the Morgan Stanley Capital International index as an exogenous shock.

Management discretion in the decision to reduce payroll costs is an important but under-researched issue in management accounting. The authors leverage the experimental environment to test the role of organizational culture (close vs. distant) and managerial communion (concern for others) along with their interaction with sales decline persistence (one vs. two periods) on planned layoff decisions. The authors find that communal managers are hesitant to downsize employees and that a close organizational culture interacts with one period sales declines to reduce layoffs although the influence of culture is reduced with persistent sales declines. The authors also examine the influence of culture and communion on managers’ preference for pay cuts as an alternative to layoffs. The authors find that a close culture and higher communion are associated with decisions to choose pay cuts over layoffs; however, these costs interact such that managers low in communion in a distant culture express a higher preference for layoffs. These findings illustrate the combined influence of economic, organizational, and dispositional factors on manager decisions about the extent and form of labor cost reductions due to sales declines.

This study examines the moderating role of female directors on the relationship between the firms’ characteristics and tax avoidance in an emerging economy.

This study employs the second-generation unit root test and the generalised method of moments (GMM) techniques. The Kao residual cointegration test corroborates a long-run cointegration among variables.

Female directors demonstrate mixed and unusual findings. No significant impact of female directors on tax avoidance is found. In addition, the presence of female directors does not show any negative or significant moderating impacts on the relationship between leverage, firm age, board size and tax avoidance. However, having more female directors can negatively and significantly moderate the relationship between more profitable firms, larger firms and tax avoidance. These findings show that the board of directors could use the presence of female directors to maximise their opportunistic behaviour, such as to avoid tax.

Research limitations – The study is limited by considering only 62 listed firms. The scope could be extended to include non-listed firms.

Research implications – There is increasing pressure for female directors on boards from diverse stakeholders, such as the European Commission, national governments, politicians, employer lobby groups, shareholders, and Fortune and Financial Times Stock Exchange (FTSE) rankings. This study provides input to decision-makers putting gender quota laws into practice. Our findings can help policy-makers adopt regulatory reforms to control tax avoidance practices and enhance organisational legitimacy. Policymakers can change their policy to include female directors up to the threshold suggested by the critical mass theory.

This is the first attempt in Bangladesh to explore the role of female directors in the relationship between the firms' characteristics and tax avoidance. The current study has significant ramifications for bringing gender diversity into practice as a component of good corporate governance.