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Dark (Netflix, 2017–2020) is a German-produced science fiction television series, created by Baran bo Odar and Jantje Friese. Set in the geographically ambiguous small town of Winden, Dark is an intricate time-travel saga primarily across different epochs. With its emphasis on uncanny natural settings and fairy tale tropes (such as lost children, mysterious travelers, magical devices, etc.), Dark can easily be interpreted as fairy tale. Central is young Jonas Kahnwald who loses his father and witnesses the mysterious disappearance of a local boy. These traumas lead to shocking truths about his heritage. Jonas is the hero (both victim and seeker, after Propp's definition) though his twisting quest brings him face-to-face with two older versions of himself: The middle-aged Jonas fulfils a mentor/donor role for the younger but is conflicted in his desires to both perpetuate and unpick ‘the knot’. Later, Jonas encounters cataclysmic extremist ‘Adam’, a mature version of himself who acts as antagonist. Thusly, Dark centres White male trauma, agency, and ego to reflect responses to historic cultural trauma (such as the notion of the ‘anti-Heimat’) whilst also critiquing traditional conceptions of masculinity through young Jonas's actions. This chapter maps the interplay and representation of ego and trauma. Through textual analysis and with reference to relevant cultural, psychological, and philosophical scholarship, my exploration follows the threads of what Dark communicates about contemporary German masculinity in the face of trauma and how it reflects Western, White cultural thinking about the self.

In this study, we examine the influence of a firm’s environmental, social, and governance (ESG) performance on analysts’ stock recommendations and earnings forecast accuracy in the Chinese context.

We take a textual analysis approach to analyst research reports issued between 2010 and 2019, and differentiate between two distinct analyst categories: “sustainability analysts,” which refer to those more inclined to incorporate ESG information into their analyses, and “other analysts.”

Our evidence indicates that sustainability analysts tend to be significantly more likely than others to provide positive stock recommendations and demonstrate enhanced accuracy in forecasting earnings for companies with superior ESG performance. Our additional analyses reveal that this finding is particularly prominent for analysts who graduated from institutions emphasizing the protection of the environment, those recognized as star analysts, those affiliated with ESG-oriented brokerages, and forecasts made by analysts in the later part of the sample period. Our findings further indicate that sustainability analysts exhibit a more pronounced negative response when confronted with a negative ESG event.

In general, the evidence from this study reveals the interplay between ESG factors and analyst behavior, offering valuable implications for both financial analysts and sustainable investment strategies.

This study aims to investigate the impact of facial-based perceived trustworthiness on stock valuation, particularly, in the initial public offering (IPO). IPO settings provide the opportunity to investigate whether information asymmetry resulting from company newness in the market would influence the incorporation of soft information in the form of executive facial trustworthiness in stock valuation.

We use a recent machine learning algorithm to detect facial landmarks and then calculate a composite facial trustworthiness measure using several facial features that have previously been observed in neuroscience and psychological studies to be the most determining factor of perceived trustworthiness. We then regress the facial trustworthiness of IPO firm executives to IPO underpricing.

Utilizing machine learning algorithms, we find that the facial trustworthiness of the company executive negatively impacts the extent of IPO underpricing. This result implies that investors incorporate the facial trustworthiness of company executives into stock valuation. The IPO underpricing also shows that the cost of equity is higher when perceived trustworthiness is low. With regard to the higher information asymmetry in IPO transactions, such a negative impact implies the role of facial trustworthiness in alleviating information asymmetry.

This study provides evidence of the impact of top management personal characteristics on firms’ financial transactions in the Indonesian context. From the perspective of investors and other fund providers, this study shows evidence that heuristics still play an important role in financial decision-making. This is also an indication of investor reliance on soft information. Our research method also provides a new opportunity for the use of machine-learning algorithms in processing non-conventional types of data in finance research, which is still relatively rare in emerging markets like Indonesia. To the best of our knowledge, our study is the first to use personalized measures of trust generated through machine-learning algorithms in IPO settings in Indonesia.

This study explores the impact of transformational leadership on work engagement within remote work settings. More specifically, we investigate whether supervisor’s perceived digital communication skills moderate the relationship between perceived supervisor support and work engagement.

Moderated mediation model has been tested using a sample of 410 consultants in Italy who worked within a fully remote work setting during Covid-19 pandemic.

Drawing on construal level theory and social presence theory, our study provides insights into the dynamics of leadership and work engagement in remote work settings. We demonstrate that, despite the challenges posed by physical distance, transformational leaders can effectively stimulate the work engagement of remote collaborators. Moreover, our findings suggest that the perceived digital communication skills of supervisors play a crucial role in moderating the relationship between perceived supervisor support and work engagement. This underscores the importance of supervisors' adept use of digital tools in conveying psychological presence and fostering employee engagement in remote work environments.

Our study highlights the importance of developing supervisors' digital communication skills to support and stimulate employee engagement in remote work settings.

This study contributes to the literature by providing one of the first empirical tests of the relationship between transformational leadership, perceived supervisor support, supervisor’s digital communication skills and work engagement within a remote work setting. By challenging prior assumptions and offering novel insights, our research enhances understanding of leadership dynamics and provides practical guidance for organizations navigating the challenges of remote work.

Developing nursing leadership has become a key policy priority to achieve universal health coverage. This study aims to explore the current status, developing trends and research frontiers in the field of nursing leadership.

In total, 1,137 articles and reviews on nursing leadership from 1985 to 2022 were retrieved from the Web of Science Core Collection database. Trends of publications, journals, countries/regions, institutions, documents and keywords were visualized and analyzed using Microsoft Excel and CiteSpace software.

Nursing leadership research showed an overall increase in number despite slight fluctuations in annual publications. The USA was the leading country in nursing leadership research, and the University of Alberta was the most productive institution. The Journal of Nursing Management was the most widely published journal that focused on nursing leadership, followed by the Journal of Nursing Administration. Keyword analysis showed that the main research hotspots of nursing leadership are improvement, practice and impact of nursing leadership.

This article summarizes the current state and frontiers of nursing leadership for researchers, managers and policy makers, as well as follow-up, development and implementation of nursing leadership. More research is needed that focuses on the improvement, practice and impact of nursing leadership, which are cyclical, complementary and mutually reinforcing. Longitudinal and intervention studies of nursing leadership, especially on patient prognosis, are also particularly needed.

The purpose of this paper is to understand the customer sentiment towards telemedicine apps and also to apply machine learning algorithms to analyse the sentiments in the adoption during the COVID-19 pandemic.

Text mining that uses natural language processing to extract insights from unstructured text is used to find out the customer sentiment towards the telemedicine apps during the COVID-19 pandemic. Machine learning algorithms like support vector machine (SVM) and Naïve Bayes classifier are used for classification, and their sensitivity and specificity are found using a confusion matrix.

The paper explores the customer sentiment towards telemedicine apps and their adoption during the COVID-19 pandemic. Text mining that uses natural language processing to extract insights from unstructured text is used to find out the customer sentiment towards the telemedicine apps during the COVID-19 pandemic. Machine learning algorithms like SVM and Naïve Bayes classifier are used for classification, and their sensitivity and specificity are found using a confusion matrix. The customers who used telemedicine apps have positive sentiment as well as negative sentiment towards the telemedicine apps. Some of the customers have concerns about the medicines delivered, their delivery time, the quality of service and other technical difficulties. Even a small percentage of doctors feel uncomfortable in online consultation through the application.

The primary value of this paper lies in providing an overview of the customers’ approach towards the telemedicine apps, especially during the COVID-19 pandemic.

This study aims to explore how people with concurrent mental health and substance use disorders and lived experience of deep social marginalization perceived barriers and facilitators to mainstream social participation. The purpose of this study is to identify meaningful and relevant learning content for a virtual reality-based intervention to promote social participation in this group.

This formative qualitative study was conducted in Norway during Autumn 2022. Nine in-depth individual interviews with adults recovering from dual diagnosis were conducted, audiotaped, transcribed and analysed using reflexive thematic analysis in a collaborative analysis process.

Results indicated that social alienation, poor social skills, stigma, low self-esteem and social anxiety were key barriers to social participation in this group. This study suggests a need to learn appropriate social behaviour in mainstream society, in addition to better employability skills, civic literacy and health literacy to improve utilization of social opportunities.

This study implies that virtual reality-based interventions for promoting social participation in people with dual diagnosis should primarily focus on learning and practising appropriate social behaviour in shared public spaces before practising advanced social skills such as employability skills in simulated work environments. Learning and practising social skills appears decisive for using more complex social opportunities, such as in education, health, social services and work.

This research provides suggestions for the content of a novel virtual reality-based intervention to promote social participation among people in recovery from dual diagnosis.

This study examines the relationship between servant leadership and its dimensions on firm performance, with big data playing the role of a mediator.

Survey responses used for analysis in this study have been taken from business managers associated reputed private sector organizations in India. A conceptual model is proposed grounded to the Conservation of Resource Theory (COR). Structural equation modeling has been used to test the proposed model.

Servant leadership significantly relates to firm performance, whereby Big Data is seen to play the role of a mediator. The results also indicate that none of the dimensions of servant leadership independently affect firm performance.

The study adds to extant research by examining the mediating mechanism of Big Data in servant leadership and firm performance. It also suggests that each dimension of servant leadership gets reflected in overall servant leadership. Here it is important to note that Big Data analytics partially mediate the effectiveness of servant leadership.

This research analyzes the impact of transformational leadership on task performance in sales team members, considering the mediating role of leader–member exchange (LMX), perceived organizational support and work engagement.

A structural equations model was analyzed utilizing the partial least squares (PLS-SEM) method based on data collected from a survey of 142 members and 19 leaders of sales teams in Colombian companies.

The present study establishes that social exchange variables, including perceived organizational support and LMX, mediate the relationship between transformational leadership and task performance. Nevertheless, work engagement does not demonstrate a statistically significant mediating effect.

The outcomes of this study contribute significant insights into how transformational leadership, directly and indirectly, affects task performance in an emerging economy. It specifically addresses the cultural context of Colombia, marked by a high distance to power and a perceived low aversion to uncertainty – contrary to a desired higher uncertainty avoidance.

Esta investigación analiza el impacto del liderazgo transformacional en el desempeño de tareas de los miembros de equipos de ventas, considerando el rol mediador de factores como el intercambio líder-miembro (LMX), el apoyo organizacional percibido y el engagement laboral.

A partir de una encuesta realizada a 142 miembros y 19 líderes de equipos de ventas en empresas colombianas, se analizó un Modelo de Ecuaciones Estructurales utilizando la metodología de Mínimos Cuadrados Parciales (PLS-SEM).

Se identifica el rol mediador de variables de intercambio social como el LMX y el apoyo organizacional percibido en la relación existente entre el liderazgo transformacional y el desempeño de tareas; sin embargo, no se encuentra un efecto mediador significativo del engagement laboral.

Los resultados de este estudio aportan importantes perspectivas sobre cómo el liderazgo transformacional afecta, directa e indirectamente, el desempeño en las tareas en una economía emergente. Aborda específicamente el contexto cultural de Colombia, caracterizado por una alta distancia al poder y una baja aversión a la incertidumbre percibida, en contraste con una mayor aversión a la incertidumbre deseada.