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This research aspires to contribute in the area of exploration of the psychological traits evolving by practitioners within the project management profession. Specifically, it investigates whether there is any difference in optimism levels among experienced project management practitioners and newcomers in the profession.

The research used the life orientation test-revised (LOTR) (Scheier et al., 1994) to calculate respondents’ optimism scores. With these scores at hand, the researchers could then apply inferential statistics in order to deduce any differences observed among optimism score and the respondents’ characteristics (age, years of experience etc.).

Based on the results of this research, several demographic variables were shown to be statistically significant with optimism. These were (1) the number of years of experience the respondent had in managing projects, (2) working in a government organisation and (3) possessing specific project management certifications, all of which were found to adversely affect the respondent’s optimism score.

This research was unique in applying a well-known psychological test instrument (LOTR) to provide insight into the psychological impacts of a career as an information technology (IT) project manager. It is also highly likely that this correlation between the length of time working as a project manager and the adverse impact on their optimism would also apply to not just IT project managers but all experienced project managers.

The primary objective of this research is to provide evidence that there are two distinct layers of investor sentiments that can affect asset valuation models. The first is general market-wide sentiments, while the second is biased approaches toward specific assets.

To achieve the goal, the authors conducted a multi-step analysis of stock returns and constructed complex sentiment indices that reflect the optimism or pessimism of stock market participants. The authors used panel regression with fixed effects and a sample of the US stock market to improve the explanatory power of the three-factor models.

The analysis showed that both market-level and stock-level sentiments have significant contributions, although they are not equal. The impact of stock-level sentiments is more profound than market-level sentiments, suggesting that neglecting the stock-level sentiment proxies in asset valuation models may lead to severe deficiencies.

In contrast to previous studies, the authors propose that investor sentiments should be measured using a multi-level factor approach rather than a single-factor approach. The authors identified two distinct levels of investor sentiment: general market-wide sentiments and individual stock-specific sentiments.

The paper redefines workplace spirituality (WS/WPS) by transcending the existential vacuum (in psychiatric terms a sense of lack of meaning of human existence and thus of work), leading to the development of workplace creativity, productivity and satisfaction, targeting operational profitability and organizational optimization.

Spirituality is analyzed philosophically, following the Nietzschean definition in response to Schopenhauer’s primordial suffering. Philosophical syncretism yields a viable organizational culture change model of spiritualizing the workplace. For this purpose, specific techniques are proposed which are combined with those already applied to various large companies and organizations.

Spirituality in the workplace acts as a catalyst for developing beneficial qualities by increasing employee job satisfaction, organizational efficiency and business profitability, when equally responding to stakeholders’ needs.

The suggested change model holistically fosters organizational, operational, individual and collective effectiveness through work place spirituality redefined.

For the first time spirituality in the workplace is discussed under a brand new perspective, resulting in an interdisciplinary emerging model, contributing to the field by providing guidance to academics and practitioners to its auspicious implementation through organizational culture change.

The applications of Artificial Intelligence (AI) in various areas of professional and knowledge work are growing. Emotions play an important role in how users incorporate a technology into their work practices. The current study draws on work in the areas of AI-powered technologies adaptation, emotions, and the future of work, to investigate how knowledge workers feel about adopting AI in their work.

We gathered 107,111 tweets about the new AI programmer, GitHub Copilot, launched by GitHub and analysed the data in three stages. First, after cleaning and filtering the data, we applied the topic modelling method to analyse 16,130 tweets posted by 10,301 software programmers to identify the emotions they expressed. Then, we analysed the outcome topics qualitatively to understand the stimulus characteristics driving those emotions. Finally, we analysed a sample of tweets to explore how emotional responses changed over time.

We found six categories of emotions among software programmers: challenge, achievement, loss, deterrence, scepticism, and apathy. In addition, we found these emotions were driven by four stimulus characteristics: AI development, AI functionality, identity work, and AI engagement. We also examined the change in emotions over time. The results indicate that negative emotions changed to more positive emotions once software programmers redirected their attention to the AI programmer's capabilities and functionalities, and related that to their identity work.

Overall, as organisations start adopting AI-powered technologies in their software development practices, our research offers practical guidance to managers by identifying factors that can change negative emotions to positive emotions.

Our study makes a timely contribution to the discussions on AI and the future of work through the lens of emotions. In contrast to nascent discussions on the role of AI in high-skilled jobs that show knowledge workers' general ambivalence towards AI, we find knowledge workers show more positive emotions over time and as they engage more with AI. In addition, this study unveils the role of professional identity in leading to more positive emotions towards AI, as knowledge workers view such technology as a means of expanding their identity rather than as a threat to it.

Goal orientation shapes employees’ approach to and interpretation of workplace aspects such as supervisors’ behavior. However, research has not fully examined the effect of goal orientation as an antecedent of abusive supervision. Drawing from victim precipitation theory, this study aims to fill this research gap by investigating how employees’ goal orientation influences their perception of abusive supervision.

Two studies were conducted to test the hypotheses. In Study 1, 181 employees in 45 departments participated in the survey, and multilevel confirmatory factor analysis, two-level path model and polynomial regression were used. In Study 2, 108 working adults recruited from a professional online survey platform participated in a two-wave time-lagged survey. Confirmatory factor analysis, hierarchical linear regression and polynomial regression were used.

This study found that employees’ learning goal orientation was negatively related to their perception of abusive supervision. In contrast, performance-avoidance goal orientation was positively related to their perception of abusive supervision, whereas performance-approach goal orientation was unrelated to this perception. Moreover, employees’ perception of abusive supervision was greater when learning and performance-approach goal orientation alignment occurred at lower rather than higher levels, and when performance-avoidance and performance-approach goal orientation alignment occurred at higher rather than lower levels.

This research identified two novel victim traits as antecedents of abusive supervision – employees’ learning goal orientation and performance-avoidance goal orientation. Furthermore, adopting a multiple goal perspective, the authors examined the combined effects of goal orientation on employees’ perception of abusive supervision.

To investigate whether additional information of the permanent news flow, especially reporting intensity, can help to increase transparency in housing markets, this study aims to examine the relationship between news coverage or news sentiment and residential real estate prices in Germany at a regional level.

Using methods in the field of natural language processing, in particular word embeddings and dictionary-based sentiment analyses, the authors derive five different sentiment measures from almost 320,000 news articles of two professional German real estate news providers. These sentiment indicators are used as covariates in a first difference fixed effects regression to investigate the relationship between news coverage or news sentiment and residential real estate prices.

The empirical results suggest that the ascertained news-based indicators have a significant positive relationship with residential real estate prices. It appears that the combination of news coverage and news sentiment proves to be a reliable indicator. Furthermore, the extracted sentiment measures lead residential real estate prices up to two quarters. Finally, the explanatory power increases when regressing on prices for condominiums compared with houses, implying that the indicators may rather reflect investor sentiment.

To the best of the authors’ knowledge, this is the first paper to extract both the news coverage and news sentiment from real estate-related news for regional German housing markets. The approach presented in this study to quantify additional qualitative data from texts is replicable and can be applied to many further research areas on real estate topics.

The purpose of this research is to examine the narratives of victims of abusive supervision. We explore the meaning or “lessons” victims derive from those experiences and how they shape the victims’ views of self, work and organization in relation to navigating their subsequent jobs.

We analyzed how appraisals of supervisory abuse transform victims’ narratives and their consequent work attitudes through sensemaking processes. Semi-structured interviews with the past victims of abusive supervision generated a four-stage model of how sensemaking shapes victims’ future work attitudes. Our interpretations were guided through narrative thematic analysis based on the constructionist approach.

Victims’ lessons learned are predominantly framed by their retrospective post-event appraisal of abuse (based on its severity) once individuals are no longer subject to abusive supervision. With greater distance from the abuse, victims can process the abuse and better understand the motivation of the abuser, enabling the process of causal attributions. These attributions further shape victims’ narratives and future work attitudes through a complex interplay of retrospective and prospective sensemaking mechanisms. The victims broadly reported proactive (with higher self-awareness and endurance) and reactive (self-protection, and emotional scars) lessons. A four-stage model was proposed based on our findings.

Abusive supervision remains a persistent issue experienced by many individuals at some point in their working life. However, little is known about how victims make sense of the event post-abuse and how this sense-making guides their future work behaviors. Understanding this phenomenon provides insight into how employees navigate through adversity and construct a more positive future. The contribution of this narrative inquiry is threefold. First, it explores how individual appraisals of supervisory abuse frame their (1) mechanisms of narrative construction; and (2) future work attitudes. Second, our findings demonstrate how narrative construction is a fluid process often informed by the process of retrospective and prospective sensemaking. Finally, our research suggests two broader categories of lessons that victims internalize and carry forward to their subsequent jobs.

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 dissemination of misleading and false information through media can jeopardize a company’s reputation, thus posing a threat to its stock and performance. Institutional investors are known to influence capital markets. Therefore, this paper investigates whether institutional investors engage in shaping the media sentiment stock nexus, stabilize company stocks and enhance performance.

We first investigate the effect of media sentiment on market reactions by using panel regression models. To examine the role of institutional investors, we design a quasi-experiment by exploiting the Financial Crisis of 2008 and go further by examining the heterogeneity across levels of institutional ownership. Due to risk-averse, investors may respond asymmetrically to pessimistic and positive sentiment. Accordingly, we split the sample into two sub-types, good news and bad news, based on keywords representing positive or negative content.

We find supportive evidence that institutional investors have impacts on how the markets react to media news, and the impacts are heterogeneous in the face of bad and good news. We conjecture that institutional investors act as a stabilizer of stock prices through media sentiment management.

This paper confirms the distinctive effects of institutional investors on capital markets, and uncovers the behind-the-scenes intervention and possible causal link running from institutional investors to media sentiment management. It contributes to the broad field of institutional investors' behavior, media news involvement in capital markets and market efficiency.