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This study aims to endeavour to decode artificial intelligence (AI)-based tokens' complex dynamics and predictability using a comprehensive multivariate framework that integrates technical and macroeconomic indicators.

In this study we used advance machine learning techniques, such as gradient boosting regression (GBR), random forest (RF) and notably long short-term memory (LSTM) networks, this research provides a nuanced understanding of the factors driving the performance of AI tokens. The study’s comparative analysis highlights the superior predictive capabilities of LSTM models, as evidenced by their performance across various AI digital tokens such as AGIX-singularity-NET, Cortex and numeraire NMR.

This study finding shows that through an intricate exploration of feature importance and the impact of speculative behaviour, the research elucidates the long-term patterns and resilience of AI-based tokens against economic shifts. The SHapley Additive exPlanations (SHAP) analysis results show that technical and some macroeconomic factors play a dominant role in price production. It also examines the potential of these models for strategic investment and hedging, underscoring their relevance in an increasingly digital economy.

According to our knowledge, the absence of AI research frameworks for forecasting and modelling current aria-leading AI tokens is apparent. Due to a lack of study on understanding the relationship between the AI token market and other factors, forecasting is outstandingly demanding. This study provides a robust predictive framework to accurately identify the changing trends of AI tokens within a multivariate context and fill the gaps in existing research. We can investigate detailed predictive analytics with the help of modern AI algorithms and correct model interpretation to elaborate on the behaviour patterns of developing decentralised digital AI-based token prices.

This study aims to broaden the understanding of the mechanisms through which workplace bullying might affect employees’ intention to leave the organisation, as well as the mediating role of burnout in the relationship between workplace bullying and turnover intention.

The sample included 884 employees from different Portuguese organisations operating in the tertiary sector and industry. This study uses structural equation modelling to evaluate the hypothesised model.

The results suggest that workplace bullying causes high levels of burnout in victims and increases their turnover intentions. The results further suggest that burnout fully mediates the effect of workplace bullying on turnover intentions.

Organisations should work to reduce these problems in workplace environments, focusing on HRM models that prevent the precursors of workplace bullying, particularly those associated with low determination of HR practices and the emphasis on employee participation. Implementing workplace ethical guidelines as part of an annual action plan can contribute to cultivating organisational cultures that reject any form of devaluation of human worth within the organisation.

There is little knowledge on the mediating role of burnout in the relationship between workplace bullying and turnover intention. This study answers the call for further empirical research from those who have argued that more information is needed and contributes to the growing debate on this topic and its effects on Portuguese employees. This study seeks to fill these gaps by developing a model of workplace bullying and its consequences and exploring burnout’s potential mediating role.

The purpose of this study is to examine the association between carbon emissions and earnings management (EM). This study also considers the effect of female CEOs on the association between carbon emissions and EM.

This study uses the carbon disclosure project (CDP) for carbon emissions data, the Compustat database for financial information and the ExecuComp database for female CEOs. The empirical sample of this study consists of 1,692 firm-year observations in the USA that voluntarily participated in the CDP survey from 2007 to 2015. Regression analysis and robustness tests are conducted for this study and both accrual and real EM are considered.

This study provides evidence that firms with female CEOs who voluntarily disclose their carbon emissions information engage in less real EM. Thus, the presence of female CEOs moderates the association between carbon emissions and EM. This study/paper also finds a positive association between carbon emissions and real EM, although there is an insignificant association between carbon emissions and accruals EM.

The association between carbon emissions and EM has important implications for investors, regulators and policymakers. This study suggests that policymakers should improve the conditions that promote inclusion of females in the top management positions to constrain EM.

This study focuses on the USA, which is one of the major contributors to carbon emissions in the world. The presence of female CEOs moderates the association between carbon emissions and EM and firms with female CEOs show a greater impact on EM.

This study aims to investigate how despotic leadership affects employee well-being through bullying behavior. The study further investigates emotional intelligence as a conditional variable on the association between bullying behavior and employee well-being.

The data from 257 nurses and their immediate supervisors (dyads) were collected on convenience basis using a cross-sectional design. Further, structural equation modeling was used to analyze the data.

The study noted that despotic leadership negatively affects employee well-being. Specifically, despotic leaders were noted to trigger employees’ bullying behavior that ultimately diminish their well-being. The study noted emotional intelligence as a conditional variable such that individuals with high emotional intelligence are more likely to buffer the negative association between bullying behavior and employee well-being.

This study highlights the importance of employee well-being and suggests the management focus on their leadership style. Further, the study suggests to Human Resource practitioners the importance of personality traits (emotional intelligence) at the time of recruitment, as it serves as a coping strategy to diminish employee well-being.

Drawing upon the conservation of resources, this study shed light on the mediating role of bullying behavior between negative leadership (despotic) and well-being. In addition, emotional intelligence has not been examined as a conditional variable between bullying behavior and employee well-being.

Abusive supervision (AS) provides insights into the darker aspects of leadership behavior and its effects on employees. Understanding and addressing AS can contribute to creating healthier work environments and promoting employee well-being. The effect of abusive leadership (AS) on counterproductive work behaviors (CWB) in nursing staff is examined through the theoretical lens of the social exchange theory.

Data were collected from 302 nursing staff working at public and private hospitals through a self-administered questionnaire. Measurement scales were adapted from the literature and the data were tested for validity and reliability before performing hypotheses testing through structural equation modeling in SmartPLS 4.0.

AS positively affects CWB, and psychological contract breach mediates this relationship. However, employees with high Islamic work ethics (IWE) are less concerned with supervisors' dysfunctional behaviors and pay less attention to them; thus, IWE buffers the effect of AS on CWBs.

A positive and supportive organizational climate is crucial for attracting and retaining skilled healthcare professionals. When healthcare professionals are subjected to abusive behaviors, their ability to share knowledge, adopt safety protocols and provide the best patient care may be hampered. Therefore, addressing AS in hospitals is vital to promoting a positive work environment, enhancing employee well-being and improving patient care.

Innovation has become a necessity for the information technology (IT) sector, especially during COVID-19 pandemic. Therefore, this study aims to investigate how knowledge sharing affects employees’ innovative work behavior (IWB). Specifically, the study examined occupational self-efficacy (as mediating mechanism) and entrepreneurial leadership (as boundary condition) to encourage IWB.

The study used social media platforms to collect data from 270 employees working in the IT sector through “google forms” on convenience basis between March and August, 2021. The study applied structural equation modeling in two stages to examine the measurement model (for uni-dimensionality) and the structural model (for hypotheses testing).

The study noted that knowledge sharing positively affects employees’ IWB and occupational self-efficacy positively explains this association. In addition, employees’ perception of entrepreneurial leadership strengthens the association between knowledge sharing and IWB.

The study collected data from a developing country during COVID-19 by using a cross-sectional design that may restrict causality. However, the findings suggest the management not only encourages knowledge sharing environment but also engages employees in various training that motivate them to experiment with new ideas and techniques.

This study extends the existing literature on knowledge sharing and IWB by exploring occupational self-efficacy as mediating mechanism and entrepreneurial leadership as a boundary condition.

The purpose is to derive the most effective place in the air for an aerial robot, viz., drone to use as an alternative communication system during disasters.

In this technology-driven era, various concepts are becoming the area of interest for multiple researchers. Drone technology is also one of them. The researchers, with interest in drones, are therefore trying to understand the various uses of employing drones in diverse applications which are mind-boggling, starting from civil applications (viz., an inspection of power lines, counting wildlife, delivering medical supplies to inaccessible regions, forest fire detection, and landslide measurement) to military applications (viz., real-time monitoring, surveillance, patrolling, and demining). However, one area where its usage is still to be exploited in many countries is using drones as a relay when communication lines are disrupted due to natural calamities. This will be particularly helpful in rescuing the affected people as the aerial node will enable them to communicate to the rescue team using mobiles/ordinary landline telephones even when regular communication towers are destroyed due to disastrous natural calamities, for example, tsunamis, earthquakes, and floods. Various algorithms, namely, water filling algorithm, advanced water filling algorithm, equal power distribution algorithm, and particle swarm optimization, were therefore studied and analyzed using simulation in addition to various path loss models to realize the desired place for an aerial robot, viz., drone in the air, which will eventually be used as an alternative communication system for badly hit ground users due to any disaster.

It was found that the effective combination of the water filling algorithm and particle swarm optimization algorithm may be done to place the drone in the air to increase the overall throughput of the affected ground users.

The research is original. None of the parts of this research paper has been published anywhere.

The study aims to investigate the relationships between green intellectual capital, green human resource management (HRM), and sustainability.

The research is based on information gathered from 112 large Malaysian manufacturing companies.

The study findings revealed that green human capital and green relational capital positively influence green HRM. In addition, green HRM positively related to social, environmental and economic performance. Besides, green HRM positively mediates the relationships between green human capital and economic, social and environmental performance. Finally, green relational capital improves sustainability (economic, environmental, and social performance) mediated by green HRM.

The current study contributes to the literature by examining green IC (green human capital, green structural capital, and green relational capital) as an independent variable and green HRM as a mediating variable for sustainability (economic, environmental, and social performance). The findings and recommended for the managers of large manufacturing firms and practitioners to invest in green IC to achieve sustainability through green HRM.

Megaproject's construction is essential for the development and economic growth of any country, especially in the developing world. In Kuwait, megaprojects are facing many restrictions that discourage their execution causing a significant delay in bidding, design, construction and operation phases with the execution quality being affected. The objective of this study is to develop a complexity measurement model using analytic hierarchy process (AHP) for megaprojects in Kuwait, with a focus on the New Kuwait University multi-billion campus Shadadiyah (College of Social Science, Sharia and Law (CSSL)) as a case study.

The study applies a hybrid fuzzy analytic hierarchy process (FAHP) method to compare the results with those obtained using the conventional AHP method. This can facilitate the project management activities during the different stages of construction. Data were collected based on the results of a two-round Delphi questionnaire completed by seniors and experts of the selected project.

It was found that project modeling methodology was responsible for complexity. It was grouped under several categories that include technological, goal, organizational, environmental and cultural complexities. The study compares complexity degrees assessed by AHP and FAHP methods. “Technological Complexity” scores highest in both methods, with FAHP reaching 7.46. “Goal Complexity” follows closely behind, with FAHP. “Cultural Complexity” ranks third, differing between methods, while “Organizational” and “Environmental Complexity” consistently score lower, with FAHP values slightly higher. These results show varying complexity levels across dimensions. Assessing and understanding such complexities were essential toward the completion of such megaprojects.

The contribution of this study is on providing the empirical evidential knowledge for the priority over construction complexities in a developing country (Kuwait) in the Middle East.

This study aims to examine the association between globally responsible leadership (GRL) and pro-environmental behavior (PEB), specifically probing the mediating role of green management initiatives (GMI) in this relationship.

This study used a quantitative research design, using survey data from 390 participants working in manufacturing sector organizations in one of the emerging economies in the Asian region, namely, Pakistan. AMOS was used to test the hypothesized relationships.

The results reveal that GRL has a significant positive link with GMI and PEB. In addition, this study found that GMI mediates the association between GRL and PEB, suggesting that GRL indirectly promotes PEB through the implementation of GMI.

This study has several limitations, including its reliance on self-reported data, its cross-sectional design and its focus on participants from only one nation. Future research may benefit from using mixed-study designs and diverse samples from multiple industries and nations.

The results suggest that businesses can promote PEB among their staff by adopting GRL and implementing GMI. In doing so, businesses can demonstrate their commitment to sustainability, enhancing their credibility and competitive advantage.

This research contributes several new insights to the existing literature on sustainable leadership. First, it provides empirical evidence to support the hypothesis that GRL, GMI and PEB are interrelated. Second, it highlights the mediating role of GMI in this relationship.