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Contemporary focus on infections and deaths in the event of pandemics may distract health institutions and medical practitioners from the psychosocial consequences of the outbreak in individuals. In light of the devastation, persistency and scarcity of pandemics, it is imperative to delve into individuals' psychological state and self-preservation instincts when confronted with the environmental danger arising from pandemic conditions and the environmental restrictions being imposed.

Guided by the self-preservation theory, the authors advance a research model to elucidate the moderated mediation effect of secondary traumatic stress on an individual's reactions when faced with environmental danger and restriction. The authors also consider the moderating influence of environmental restriction and media use diversity. The authors subsequently validated the research model via a survey with 2,016 respondents in China. The authors employed PLS-SEM to analyze the data and assess the hypothesized paths.

Analytical results revealed that secondary traumatic stress fully mediated the impact of environmental danger on external reliance but suppresses the mediating effects on internal reliance. The authors further confirmed that environmental restriction moderated the relationship between environmental danger and reliance. Furthermore, the authors attest to the moderating influence of media use diversity on the relationship between secondary traumatic stress and external reliance.

This study not only extends the theoretical lens of self-preservation to public health emergencies but also yields practical guidelines for coping with pandemics. Insights from this study can be harnessed to aid populations worldwide in coping and recovering from pandemics.

The purpose of this paper is to evaluate the insights of founding entrepreneurs to understand what they consider as motivating factors in their decision to act upon entrepreneurial intentions. Using this information, the entrepreneurial trigger event influence was conceptualized, and a scale developed for use in subsequent testable models.

Qualitative and quantitative techniques were used to construct an instrument that measures the presence and influence of entrepreneurial behavior triggers. The concept of triggering events was explored with 14 founding entrepreneurs. Themes emerged from this enquiry process which informed the development of four primary entrepreneurial triggering events. Over 600 entrepreneurs participated in the study. Exploratory factor analysis was used to identify dimensions of entrepreneurial triggers and was tested using confirmatory factor analysis.

Entrepreneurs perceive that personal fulfillment and job dissatisfaction serve as two significant trigger events which will lead individuals to engage in entrepreneurial behaviors. This research supports theorizing that suggests entrepreneurial trigger events have influence in motivating individuals to act upon entrepreneurial intentions and some trigger events may have more influence toward behavior than others.

This research is subject to multiple limitations. Trigger events were limited to those identified in literature and the interviews. Most entrepreneurs participating in this study were from a limited geographic region. The entrepreneurs in this study reported their triggering event based on their memory which could have been affected by inaccurate recall or memory bias. No attempt has been made to model the comparative effects of the different variables on entrepreneurial outcomes. Finally, the entrepreneurial trigger event instrument did not measure the participant's demographics or psychographics which could have played a role in the influence of reported trigger event.

This study extends previous research that trigger events serve as catalysts for entrepreneurial behavior. Findings support the premise that different types of triggers have different levels of influence as antecedents of entrepreneurial behavior. Specifically, positive, negative, internal and external entrepreneurial triggering events were explicated. The Entrepreneurial Trigger Event Scale created to facilitate this study enables researchers to explore the effects of types and perceived influences of precipitating trigger events on the intentions of the individual that result in entrepreneurial behavior. The optimized instrument further expanded Shapero's (1975) proposed theory of the origins of entrepreneurial behavior.

The development of a scale provides researchers with the opportunity to include the influence of entrepreneurial trigger events, as perceived by entrepreneurs, in future testable models. Entrepreneurial development organizations can use the knowledge to assist in understanding when potential entrepreneurs may act upon entrepreneurial intentions. Information gained can have significant implications for understanding the initiation of entrepreneurial behavior, entity establishment and business growth.

This research responds to a call for investigation into the influence of entrepreneurial trigger events on a person's decision to act upon entrepreneurial intentions. It is an early attempt to conceptualize a relevant construct of entrepreneurial trigger event influence and to develop a scale for use in empirical testing. It is distinguished by using planned behaviors, push and pull, motivation and drive reduction theories. These theories are applied to the perceptions of successful entrepreneurs to develop a construct and validate it.

This research investigates the critical role of data governance (DG) in shaping a data-driven culture (DDC) within organizations, recognizing the transformative potential of data utilization for efficiency, opportunities, and productivity. The study delves into the influence of DG on DDC, emphasizing the mediating effect of data literacy (DL).

The study empirically assesses 125 experienced managers in Indonesian public service sector organizations using a quantitative approach. Structural Equation Modeling (SEM) analysis was chosen to examine the impact of DG on DDC and the mediating effects of DL on this relationship.

The findings highlight that both DG and DL serve as antecedents to DDC, with DL identified as a crucial mediator, explaining a significant portion of the effects between DG and DDC.

Beyond unveiling these relationships, the study discusses practical implications for organizational leaders and managers, emphasizing the need for effective policies and strategies in data-driven decision-making.

This research fills an important research gap by introducing an original model and providing empirical evidence on the dynamic interplay between DG, DL, and DDC, contributing to the evolving landscape of data-driven organizational cultures.

The purpose of this study was to explore the relationship between entrepreneurial passion for founding firms (EPFF) and persistence in venture start-ups and to examine the mediating role of searching and scanning alertness, association and connection alertness and evaluation and judgment alertness (i.e. entrepreneurial alertness).

Using a three-way parallel mediation involving searching and scanning alertness, association and connection alertness and evaluation and judgment alertness, on data from 342 serial entrepreneurs from Nigeria, the authors examined the influence of EPFF on persistence in venture start-ups, through a parallel mediation involving searching and scanning alertness, association and connection alertness and evaluation and judgment alertness.

The authors find that EPFF was not significantly related (positive) to persistence in venture start-ups, but that searching and scanning alertness, association and connection alertness and evaluation and judgment alertness mediated the path through which EPFF impacts persistence in venture start-ups. Thus, entrepreneurial alertness is relevant in explaining the relationship between EPFF and persistence in venture start-ups in Nigeria.

The findings of this study highlight the relevance of EPFF and alertness in explaining persistence in venture start-ups in Nigeria.

A separate study of the different behavioral biases does not allow for a full understanding of the complexity and stability of the heterogeneity of beliefs. Therefore, through a more global view of these anomalies, the authors wish to show that they can converge on a single concept, which is the heterogeneity of beliefs.

It is therefore essential to stress that the importance of this study is mainly reflected in the methodological approach used in the construction and analysis of the map and not only in the results achieved. This contribution states that structural analysis, as a means of building the cognitive map, can facilitate the task of investors and other decision-makers, in the identification and analysis of the heterogeneity of beliefs that can therefore guide investors' strategy in decision-making.

The authors have studied the behavior of the investor and its way of interpreting the information and the authors have emphasized the value of studying the concept of heterogeneity of beliefs in its complexity. So that part of the work seems to be relevant and crucial to filling, if you will, that void. In this sense, the authors have shown that behavioral abnormalities are multidimensional concepts: “self-deception”, “cognitive bias”, “emotional bias” and “social bias”.

In particular, this article will aim to achieve the objective of proposing a model for measuring the heterogeneity of beliefs. Thus, the authors want to show that the heterogeneity of beliefs can be measured directly through the different behavioral anomalies.

Our proposed machine learning model contributes to improving the quality of Hire by providing a more nuanced and comprehensive analysis of candidate attributes. Instead of focusing solely on obvious factors, such as qualifications and experience, our model also considers various dimensions of fit, including person-job fit and person-organization fit. By integrating these dimensions of fit into the model, we can better predict a candidate’s potential contribution to the organization, hence enhancing the Quality of Hire.

Within the scope of the investigation, the competencies of the personnel working in the IT department of one in the largest state banks of the country were used. The entire data collection includes information on 1,850 individual employees as well as 13 different characteristics. For analysis, Python’s “keras” and “seaborn” modules were used. The Gower coefficient was used to determine the distance between different records.

The K-NN method resulted in the formation of five clusters, represented as a scatter plot. The axis illustrates the cohesion that exists between things (employees) that are similar to one another and the separateness that exists between things that have their own individual identities. This shows that the clustering process is effective in improving both the degree of similarity within each cluster and the degree of dissimilarity between clusters.

Employee competencies were evaluated within the scope of the investigation. Additionally, other criteria requested from the employee were not included in the application.

This study will be beneficial for academics, professionals, and researchers in their attempts to overcome the ongoing obstacles and challenges related to the securing the proper talent for an organization. In addition to creating a mechanism to use big data in the form of structured and unstructured data from multiple sources and deriving insights using ML algorithms, it contributes to the debates on the quality of hire in an entire organization. This is done in addition to developing a mechanism for using big data in the form of structured and unstructured data from multiple sources.

The purpose of this essay is to explore the ramifications of Web 3.0 on sports media and the desire for the ultimate fan experience.

The essay explains how Web 3.0 will influence (1) the social TV experience, (2) the drive for zero latency in sports streaming, (3) the desire for exclusive sports memorabilia and experiences, (4) artificial intelligence-driven content and (5) the potential decentralization of certain elements within the sports media ecosphere.

The core fan experience will still be recognizable, but AI, VR, blockchain and other elements will be infused within it.

Ramifications on sports media scholarships are offered.

This study aims to explore how managers exercise agency in strategic investment decisions (SIDs) by drawing on their knowledgeability of the strategic context. Specifically, the authors address the role of position–practice relations and irresistible causal forces in this conduct.

The authors examine SID-making (SIDM) practices in four case organisations operating in highly competitive markets, conducting interviews with managers at various levels and analysing company documents. Drawing on strong structuration theory, the authors show how managerial decision makers draw upon their knowledge of organisational context when exercising agency in SIDs.

The authors provide insights into how SIDM behaviour, specifically agents’ conduct, is shaped by a combination of position–practice relations and the agents’ comprehension of their organisation’s context.

The authors extend the SIDM literature by surfacing the issue of how actors’ conjuncturally-specific knowledge of external structures shapes the general dispositions they draw on in exercising agency in practice.

The authors extend the SIDM literature by surfacing the issue of how actors’ conjuncturally-specific knowledge of external structures shapes the general dispositions they draw on in exercising agency in practice. Particularly, the authors contribute to this literature by identifying irresistible causal forces and illuminating why actors might not resist in SIDM processes, despite having the potential to do so.

This paper aims to explore how the maieutic role of management accounting (MA) can be sustained in the context of MA digitalization.

The paper begins with practitioners’ descriptions of the context that makes the MA support of non-routine decisions maieutic. To understand how the maieutic characteristics can be sustained in future MA digitalization, the authors then analyze the discourses these practitioners have about artificial intelligence (AI) in providing MA support.

As a basis, the authors’ data show various maieutic characteristics within the use of MA answers in decision-making as well as within the MA process of generating such answers. The paper then identifies three MA digitalization discourses, namely, “computation,” “judgment” and human-AI “interaction” discourse, each with their unique agendas on how AI should be used.

The paper is based on the premises that AI and digitalization are often discussed without sufficient understanding about the context being digitalized. The authors’ data suggest that MA support in non-routine decision-making is fundamentally maieutic, and AI – as it currently stands – is not expected to change this by providing perfect answers. The authors provide novel insights about maieutic MA support and the current discourses on using AI in MA support, and how digitalization does not necessarily compromise maieutic MA support but instead has the potential to sustain or even enhance it.