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This study aims to determine how the attitudes toward artificial intelligence (AI) of religious tourists affect their AI self-efficacy and their engagement in AI. This study specifically intends to investigate the mediating role of AI self-efficacy in the relationship between attitudes toward AI and the engagement in AI of religious tourists. This study also seeks to identify the role of AI assistant use as a moderator in the relationship between attitudes toward AI and AI self-efficacy.

The data used in this study was gathered from a sample of 282 religious tourists who had just visited Karbala, central Iraq. Purposive sampling, which comprises a focused and systematic approach to data collection, was used after carefully assessing the distinctive characteristics and properties of the research population.

The results showed that attitudes to AI had a noticeable impact on AI self-efficacy, which, in turn, exerted a positive impact on engagement with AI. In addition, the use of AI assistants acted to positively moderate AI self-efficacy in terms of mediating the link between attitudes to AI and AI engagement.

The distinctive focus on religious tourists adds an original perspective to the existing literature, shedding light on how their attitudes towards AI impact not only their self-efficacy but also their engagement in dealing with AI. In addition, this study delves into the moderating role of AI assistant use, introducing a unique factor in understanding the complex interplay between attitudes, self-efficacy, and engagement in the context of religious tourism. The selection of Karbala, central Iraq, as this study site further adds originality, providing insights into a specific religious and cultural context.

Prior studies have found that managers adjust operational activities to tackle climate risk. However, the effects of climate risk on accounting practices are largely ignored in the literature. This paper investigates whether and how climate risk influences managers’ decision-making on the level of accounting conservatism and explains the results based on two competing channels: valuation demand and contracting demand.

Using firm level climate risk measures, we build a modified Basu (1997) model to conduct our econometric tests. In the baseline model, we use earnings before extraordinary items as the dependent variable, referred to as the earnings model. We control for different levels of fixed effect to identify the shocks of climate risk and mitigate potential concerns on endogeneity and bias in the model. A series of robustness tests provide supporting evidence for our baseline results and our explanation.

Using a sample of 35,832 firm-year observations on listed US firms over the period 2002 to 2019, we find that the perception of climate risk drives managers to choose the less conservative accounting policies. We conclude that the results are consistent with the valuation demand explanation but inconsistent with the contracting demand explanation.

The study provides additional evidence on how managers respond to climate risk by adjusting their corporate polices, specifically accounting policies. Our findings contradict the results of prior studies. We explain our results from a unique perspective. Overall, the study provides valuable insights for academics, investors, managers and policymakers.

Green finance aims to promote sustainable financial activities, environmental conservation and ecological balance. This study examines how renewable energy consumption (REN), technological innovation (TEC) and green finance (GRF) influence CO2 emissions in Vietnam from 2000 to 2022.

We utilize a novel three-stage methodology including quantile-on-quantile regression, wavelet coherence and wavelet-quantile regression to explore the relationship in the structure of intercorrelation in terms of quantile, time and frequency.

The findings show that Vietnam will increase environmental quality for higher green development. Specifically, there is a negative influence of TEC, REN and GRF on CO2 emissions across different quantiles and timescales.

The study recommends policies that support green development and reduce carbon emissions, such as increasing the use of renewable energy and conducting well-planned research to achieve a carbon-free, sustainable environment.

This article looks into the effects of GRF, TEC and REN on CO2 emissions in Vietnam. Some studies argue that green development in underdeveloped nations is insufficient to reduce CO2 emissions, thereby limiting the sample to a few advanced economies. Adopting diverse methodologies demonstrates the varied and intricate nature of understanding CO2 drivers. Additionally, our work makes detailed policy implications for Vietnam to meet its net-zero emission target and achieve sustainable development by 2050.

This investigation delves into the rationale behind the preferential applicability of the non-Newtonian nanofluid model over alternative frameworks, particularly those incorporating porous medium considerations. The study focuses on analyzing the mass and heat transfer characteristics inherent in the Williamson nanofluid’s non-Newtonian flow over a stretched sheet, accounting for influences such as chemical reactions, viscous dissipation, magnetic field and slip velocity. Emphasis is placed on scenarios where the properties of the Williamson nanofluid, including thermal conductivity and viscosity, exhibit temperature-dependent variations.

Following the use of the OHAM approach, an analytical resolution to the proposed issue is provided. The findings are elucidated through the construction of graphical representations, illustrating the impact of diverse physical parameters on temperature, velocity and concentration profiles.

Remarkably, it is discerned that the magnetic field, viscous dissipation phenomena and slip velocity assumption significantly influence the heat and mass transmission processes. Numerical and theoretical outcomes exhibit a noteworthy level of qualitative concurrence, underscoring the robustness and reliability of the non-Newtonian nanofluid model in capturing the intricacies of the studied phenomena.

Available studies show that no work on the Williamson model is conducted by considering viscous dissipation and the MHD effect past over an exponentially stretched porous sheet. This contribution fills this gap.

The recent meeting of G-20 world leaders, held in New Delhi, in 2023, highlighted that the physical effect of climate change has considerable macro-economic costs at the national and global levels and they have also pledged to accelerate the clean, sustainable and inclusive energy transition along a variety of pathways. Climate change could pose various emerging risks to the firm’s operational and financial activities, specifically for those which are belonging to the energy sector. Thus, this study aims to investigate the impact of climate risks on the financial performance of select energy companies from G-20 countries.

The study considered 48 energy companies from G-20 countries as the sample for the period of 2017 to 2021. To measure the climate change-related physical risks, the study has considered the ND-GAIN climate vulnerability score and the firm’s financial performance has been measured by return on assets, return on equity, return on capital used and price-to-book ratio. To examine the impact of climate risks on the financial performance of the sample companies, the authors have used pooled ordinary least squares (OLS) and fixed/random effect regression analysis and required data diagnosis tests are also performed.

The empirical results suggested that climate risks negatively impacted the financial performance of the sample companies. The market performances of the firms are also being impacted by the physical climate change. The results of panel data regression analysis also confirmed the robustness of the empirical results derived from the pooled OLS analysis suggesting that firms that operated in a less climate-risky country, financially performed better than the firms that operated in a more climate-risky country.

The paper has significant practical implications like it could be helpful for the policymakers, investors, suppliers, researchers and other stakeholders in developing deeper insights about the impact of climate risks on the energy sectors from an international perspective. This study may also help the policymakers in developing policies for the management of climate risk for the energy sector.

This study adds insights to the existing literature in the area of climate risks and firm’s financial performance. Moreover, this may be the first study that attempts to evaluate the impact of climate risks on the financial performance of select energy companies from the G-20’s perspective.

The paper uses foundation models to integrate the green approach in Logistics 5.0. Such integration is innovative in logistics and leads to a more sustainable and prosperous future. By harnessing the power of foundation models and incorporating sustainable principles, this paper can systematize the logistics industry’s environmental framework, increase its social responsibility and ensure its long-term economic viability.

Generalizing environmental sustainability goals requires a multi-layered innovation approach incorporating corporate philosophy, products, processes and business models. In this paper, this comprehensive approach is not just a strategy but a necessity in the current global context. This paper uses the sustainability-oriented innovation (SOI) method, crucial for achieving explicit environmental, social and economic impacts.

Artificial intelligence, especially foundation models, can contribute to green logistics by optimizing routes, reducing packaging waste, improving warehouse layouts and other functions presented in the paper. At the same time, they can also consider social, economic and governance goals.

Artificial intelligence algorithms present challenges such as high initial investment, regulatory compliance and technological integration.

The paper contains implications for developing environmentally sustainable logistics, which is currently one of the most significant challenges. The framework presented can apply to logistics companies.

This paper fulfills an identified need to study sustainability in logistics. The framework is entirely original and not present in the literature. It is essential to help design and implement innovative logistics approaches.

This study aims to critically evaluate the competitiveness of Transformer-based models in financial forecasting, specifically in the context of stock realized volatility forecasting. It seeks to challenge and extend upon the assertions of Zeng et al. (2023) regarding the purported limitations of these models in handling temporal information in financial time series.

Employing a robust methodological framework, the study systematically compares a range of Transformer models, including first-generation and advanced iterations like Informer, Autoformer, and PatchTST, against benchmark models (HAR, NBEATSx, NHITS, and TimesNet). The evaluation encompasses 80 different stocks, four error metrics, four statistical tests, and three robustness tests designed to reflect diverse market conditions and data availability scenarios.

The research uncovers that while first-generation Transformer models, like TFT, underperform in financial forecasting, second-generation models like Informer, Autoformer, and PatchTST demonstrate remarkable efficacy, especially in scenarios characterized by limited historical data and market volatility. The study also highlights the nuanced performance of these models across different forecasting horizons and error metrics, showcasing their potential as robust tools in financial forecasting, which contradicts the findings of Zeng et al. (2023)

This paper contributes to the financial forecasting literature by providing a comprehensive analysis of the applicability of Transformer-based models in this domain. It offers new insights into the capabilities of these models, especially their adaptability to different market conditions and forecasting requirements, challenging the existing skepticism created by Zeng et al. (2023) about their utility in financial forecasting.

Leadership’s dark side has been on the rise, negatively affecting organizations. The phenomenon, however, is not as simple as it seems. Based on social exchange and conservation of resource theories, current research aims to explore the impact of psychological entitlement on despotic leadership, ultimately leading to instigated workplace incivility. Moreover, emotional exhaustion was tested as a mediator and Islamic work ethics as a moderator.

This study aims to examine the effect of dark side of leadership and for this, the survey approach was used to collect data from 402 bankers from Pakistan’s twin cities (Islamabad and Rawalpindi).

The results showed that psychological entitlement leads to despotism and despotic leaders become a reason for instigated workplace incivility. Results also showed that emotional exhaustion mediated, and Islamic work ethics moderated the relationship.

Bankers have a demanding job which is further exacerbated by despotic leaders feeling psychologically entitled and instigating employees toward uncivil behaviors as they experience emotional exhaustion. Despotic leaders need to be dealt with to reduce instigated incivility and Islamic work ethics can also aid in improving employee behavior.

Literature available on both antecedents and effects of the leadership’s dark side is limited, and this study strives to contribute by extending the literature available on psychological entitlement, despotic leadership and instigated workplace incivility relationships.

Over time, there has been a rise in deviant behavior among hotel employees. This scenario motivates researchers and practitioners to address the issue. The study aims to examine the influence of socio-psychological factors (abusive supervision, workplace ostracism, work-family conflict and emotional exhaustion) on workplace deviance (interpersonal and organizational deviation) in the hotel industry with the moderating effect of interpersonal justice and perceived organizational support.

We gathered data from 416 employees in the hotel industry by employing a convenience sampling method and administered structured questionnaires. Subsequently, we conducted data analysis using structural equation modeling (SEM).

Results showed that abusive supervision had a direct impact on work-family conflict, emotional exhaustion and interpersonal and organizational deviation; similarly, workplace ostracism had a positive impact on work-family conflict, interpersonal and organizational deviation, but it did not significantly impact emotional exhaustion. Finally, interpersonal justice had significant moderators between abusive supervision and interpersonal and organizational deviation.

This study contributes to the extent of research on the antecedents of interpersonal and organizational deviance and the mediating roles of work-family conflict and emotional exhaustion. Secondly, this research developed an integrated conceptual framework for categorizing the causes of interpersonal and organizational deviance by checking the mediation effect of work-family conflict (WFC) and emotional exhaustion (EE). Perceived organizational support (POS) and interpersonal justice (IPJ) as moderators, which is an addition to earlier works in this field of research.

The objective of this study aims to investigate the manner in which Human Resource Practices (HRP), leadership, and intellectual capital contribute to organisational agility within the healthcare sector, and to assess how this agility influences overall organisational performance.

This research was undertaken within healthcare organisations situated in the United Arab Emirates (UAE). The study sample comprised of 275 participants, and the distribution of the sample across various classifications closely mirrored that of the larger population. To assess the formulated hypotheses, the research utilized Partial Least Squares Structural Equation Modeling (PLS-SEM) software.

Results confirmed the proposed framework and uncovered the significance of HRP, leadership and intellectual capital on organisational agility and organisational performance in a dynamic environment like hospitals.

This study demonstrates originality by investigating hospital responsiveness within a highly dynamic context necessitating agility from both managerial and non-technical perspectives. Additionally, it explores the impact of HRP, leadership, and intellectual capital on organisational agility, along with its repercussions for overall organisational performance.