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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.

The data for this case were obtained primarily through a series of in-person interviews in Penang between the authors and Pete Browning (a pseudonym) from 2017 to early 2019. The authors also consulted secondary data sources, including publicly available material on BMax and “Company B”.

This case examines a key decision, or set of decisions, in the life of a small- to medium-sized management consultancy group, namely, whether they might expand their operations in Southeast Asia, and if so, where. These key decisions came in the wake of their having already established a very modest scale presence there, with an operating base on the island of Penang just off the north western coast of Peninsular Malaysia. The initial establishment of a Southeast Asian branch had been somewhat spontaneous in nature – a former colleague of one of the two managing partners in the USA was on the ground in Malaysia and available: he became the local partner in the firm. But the firm had now been eyeing expansion within the region, with three markets under particular consideration (Singapore, Indonesia and Thailand) and a further two (Vietnam and China) also seen as possible targets, though at a more peripheral level. The questions facing the decision makers were “was it time they expand beyond Malaysia?” and “if so, where?”

This case could be used effectively in undergraduate courses in international business. The key concepts on which the case focuses are the factors affecting market entry, particularly the choice of market and the assessment of potential attractiveness such markets offer.

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.

Women working in public relations (PR) in the 1990s developed the power of metamodern pragmatism to avoid being constrained in this decade of contradictions.

This was a time of promise for female empowerment and careers. The PR industry in Britain had quadrupled in size, yet increased feminisation and professionalisation did not resolve gender inequity. Indeed, alongside the existence of ‘old boys clubs’ and hedonistic macho agencies in the industry, the 1990s offered a lad's mag culture and an AbFab image of PR.

An original collaborative historical ‘Café Delphi’ method was developed using three themes (sex, sexuality and sexism) to explore women's careers and contributions in the expanding and increasingly powerful field of PR in the United Kingdom during the 1990s. It built on feminist critique of the industry and paradoxical portrayals of women resulting from significant changes in media, popular culture and a pluralistic marketplace.

Individual and collective experiences of women working in PR at the time reveal the power of attitudes to affect their ability to achieve equality and empowerment. Women navigated tensions between the benefits of accelerated pluralism and the patriarchal resistance in the workplace through performative choices and a deep sense of pragmatism.

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.

This study aims to investigate the impact of pollution control bonds (PCBs) on overinvestment within utility firms.

This empirical study analyzes a data set comprising 215 US energy firms observed from 2011 to 2021, using the ordinary least square regression with standard errors adjusted for firm-level clustering.

The study reveals a negative relationship between PCBs and overinvestment, indicating that PCBs are an effective tool in curbing excessive investment. Additionally, it demonstrates that chief executive officer (CEO) overconfidence diminishes the influence of PCBs on overinvestment. These findings remain robust across various metrics for measuring overinvestment and CEO overconfidence, as well as when alternative estimation methods are used. These results align with insights derived from agency theory and upper echelon theories.

Regulators are encouraged to actively promote the use of PCBs as a financing tool for environmentally focused initiatives. To achieve this, regulatory bodies should enhance their presence within the utility sector, particularly in regions grappling with higher pollution levels. This requires the implementation of strategic policies and regulatory frameworks aimed at mitigating excessive investments. Simultaneously, policymakers should take proactive measures to introduce financial instruments designed to optimize investment efficiency, thus facilitating eco-friendly projects.

To the best of the authors’ knowledge, this paper holds the distinction of being the first to examine the impact of a specific type of green bond, namely, PCBs, on overinvestment. Furthermore, it contributes to the literature on personality traits, particularly within the context of the upper echelon theory, by investigating the moderating influence of CEO overconfidence.

This paper aims to examine the extent to which sell-side analysts efficiently incorporate firms’ corporate social responsibility (CSR) activities into their earnings forecasts. In addition, this paper also investigate the CSR information efficiency of analysts vis-à-vis that of investors.

This paper measures CSR activities by using CSR strength and CSR concern scores from the Morgan Stanley Capital International Environmental, Social and Governance database. This paper uses analysts’ earnings forecast errors and dispersion as proxies for their information efficiency. To compare the CSR information efficiency of analysts to that of investors, this paper uses the Vt/Pt ratio, which is the equity value estimates inferred from analysts’ earnings forecasts (a proxy for analysts’ CSR information efficiency) to the stock price of the focal company (a proxy for investors’ CSR information efficiency).

The regression analysis indicates that analysts’ earnings forecasts are optimistically biased and more dispersed for firms with positive CSR activities. The paper also finds that analysts’ forecasts are more optimistically biased than investors in interpreting CSR activities.

The lack of standardized protocols in CSR reporting and activities has raised the risk of mispricing by analysts, threatening the stability of sustainable investments. This paper suggests that regulators and standard-setters should establish a uniform framework governing firms’ CSR activities, along with their reporting and measurement, to ensure more consistent and reliable evaluations of CSR practices.

Analysts’ mispricing of CSR activities may distort sustainable investing, as it can overly focus on the positive impacts of stakeholder theory, overlooking agency theory’s warnings about managerial self-interest. Investors need to assess CSR efforts with a dual perspective, acknowledging their societal value but also examining their alignment with shareholder interests.

To the best of the authors’ knowledge, this research is the first to assess the efficiency of analysts versus investors in processing CSR information amidst growing sustainable investment interests. Furthermore, building on Dhaliwal et al. (2012), which found that voluntary CSR disclosures correlate with more accurate analyst forecasts, this research provides fresh perspectives on the evolving nature of how analysts assimilate CSR information over time.

The goal of this paper is to examine the mediating role of organizational social capital between family firms' organizational culture, characterized by their group vs individual orientation and external vs internal orientation, and their performance.

A structural equation model is developed and tested in a sample of 176 US family firms recruited through Prolific Academic.

The authors show that group vs individual cultural orientation fosters bonding social capital, while external vs internal cultural orientation fosters bridging social capital. In turn, family firm performance is only enhanced by bridging social capital, not bonding social capital, which appears to have neutral to negative direct performance effects. Nevertheless, it is noteworthy that bonding social capital facilitates the establishment of bridging ties, leading to overall positive performance outcomes.

The understanding of how organizational culture influences family business heterogeneity and performance, along with the clarification of how bonding social capital fosters or hinders performance, provides novel insights for researchers and practitioners seeking to understand the complexities within the unique context of family businesses.

Given the implementation of a new Certified Public Accountant (CPA) licensure exam and the CPA Evolution Model Curriculum, accounting educators must integrate more advanced skills in their coursework. We illustrate how a commonly-used project in accounting classes, which teaches technical accounting content, can address skills and competencies identified by the Pathways Commission and the American Institute of Certified Public Accountants (AICPA) and, as a result, enhance skills all business school graduates need in the workplace.

We incorporate a financial statement analysis research project under a group work format in three levels of financial accounting classes. Using both quantitative and qualitative analysis, we evaluate changes in student perceptions of skills and competencies important for business graduates.

We find students perceive improvement in critical thinking, problem-solving, the ability to work with other people, their understanding of the course material, and data analysis abilities after completion of the project. We also find statistically significant increases pre-to post-project in student perceptions of their knowledge, confidence, competence, and enthusiasm with respect to accounting material.

We provide an example of how educators can align a commonly-used project with the CPA Evolution Model Curriculum, yet still meet the needs of non-accounting majors and prepare all students for future business careers. Group work has been studied and similar financial statement analysis projects have been implemented in the classroom for years. We contribute by not only extending and updating this research, but also by re-evaluating a project to determine whether it meets the shifting needs of a rapidly changing profession. By doing so, we answer recent researchers’ call for research in higher education that addresses employability and workplace skills.