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Found 6289 publications
Do Eco-Emotions and Climate Change Perceptions Influence Environmentally Conscious Decisions? Implications for Business Strategies
Publication Name: Business Strategy and the Environment
Publication Date: 2026-01-01
Volume: Unknown
Issue: Unknown
Page Range: Unknown
Description:
Despite growing research on explicating travelers' decision-making processes regarding greener travel options, there remains potential for exploring nuances of different factors and mechanisms that may encourage higher green travel. Grounded in the propositions of the push–pull–mooring framework, our study attempts to explicate whether eco-emotions (anxiety and grief as push factors) and environmental cognitions (climate change perceptions and destination social responsibility as pull factors) influence travelers' green consumption values and green travel intentions. Data collected via Prolific from 291 green travelers was analyzed using covariance-based structural equation modeling to test the hypothesized associations. In general, the study results affirm the hypothesized push and pull effects for green consumption values, which in turn play a mediating role to amplify the effects of push and pull factors on green travel intentions, rather than substituting for them. The findings raise significant implications for theory and also provide actionable insights for developing operating and communication strategies for industry practitioners.
Open Access: Yes
DOI: 10.1002/bse.70548
Joint Audit Research: A Systematic Literature Review and Future Research Agenda
Publication Name: Accounting Perspectives
Publication Date: 2026-01-01
Volume: Unknown
Issue: Unknown
Page Range: Unknown
Description:
We perform a systematic literature review in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) protocol to uncover the characteristics and evolution of research on joint audits. The sample includes 53 papers published in the Scopus database from January 2007 to May 2025. Although many researchers have examined the primary benefits and drawbacks of joint auditing, the research on this subject remains relatively sparse compared to other areas of auditing, suggesting it warrants further exploration. Most joint audit research has focused on two main aspects—audit quality and fees—while only a few studies have examined audit report delays, the concentration of the audit market, and other limited topics related to joint auditing. This study also offers critical perspectives for future research avenues. This analysis serves as a valuable resource for researchers and practitioners seeking to deepen their understanding of joint audits.
Open Access: Yes
Cognitive Approaches to Multimodal Mobility: Integrating E-Scooters with Public Transport in Győr, Hungary
Publication Name: Lecture Notes in Networks and Systems
Publication Date: 2026-01-01
Volume: 1768 LNNS
Issue: Unknown
Page Range: 72-77
Description:
The Public transport and micromobility roles, particularly electric scooters (e-scooters), are increasingly recognised as pivotal for sustainable urban mobility when integrated rather than made to compete. Cognitive mobility behaviour—how individuals select and combine transport modes—was examined through a systematic literature review, traffic counts conducted at peak-hour junctions, and an online survey of residents’ travel habits in Győr, Hungary. It was found that 46% of trips are made by private car, 24% by public transport, 8% by bicycle, 22% on foot, and only 1–3% by e-scooter. E-scooters were observed to be primarily used for short trips and first/last-mile connections, and reductions in car dependence were noted when e-scooters were integrated with public transport. The survey revealed that e-scooters most often replace walking (42%) and public transport (36%), with limited substitution of private car trips (13%). Significant gaps were identified in multimodal integration, infrastructure, legal frameworks, traffic monitoring, and public awareness. It is recommended that multimodal hubs, dedicated e-scooter lanes, improved traffic counting, and clearer regulations be implemented to support modal shift, enhance safety, and maximise environmental benefits.
Open Access: Yes
The Silent Signal: A Mirror Leadership and Intercultural Communication Beyond Strategic Boundaries
Publication Name: Journal of Intercultural Communication
Publication Date: 2026-01-01
Volume: 26
Issue: 1
Page Range: 115-130
Description:
The post-pandemic work environment has intensified emotional strain, hybrid-work fatigue, and cognitive disengagement, making it increasingly difficult for leaders to sustain trust and authentic engagement in diverse, digitally disrupted teams. Existing leadership models emphasize cognition and behavior but overlook the real-time emotional, relational, and physiological processes that shape contemporary managerial dynamics. This study introduces Mirror Leadership, a novel theoretical framework grounded in Emotional Appraisal Theory (EAT) and Polyvagal Theory (PVT) to explain how leaders influence team well-being through emotional co-regulation, reflective attunement, and embodied presence. Using a conceptual research design and narrative synthesis across neuroscience, psychology, and leadership studies, the paper advances six propositions that describe how Mirror Leaders cultivate psychological safety, resilience, relational repair, and trust in hybrid and multicultural contexts. The model offers a distinct theoretical contribution by integrating cognitive appraisal mechanisms with neurophysiological processes of safety and connection, thereby reframing leadership as a symbolized, neuro-emotional, and intercultural process rather than a solely cognitive or strategic function. Findings suggest that emotionally attuned and synchronized leaders foster biologically grounded trust, intercultural cohesion, and affective stability during uncertainty. The study further outlines implications for research, including the need for empirical validation using physiological and behavioral measures, and implications for practice, such as enhancing leadership development, cross-cultural training, and emotionally intelligent management in hybrid workplaces. Mirror Leadership thus provides a foundational and globally relevant framework for understanding emotionally intelligent and culturally competent leadership in the new world of work.
Open Access: Yes
PLS-SEM in public procurement research: a systematic review of theoretical foundations, constructs and empirical insights
Publication Name: Journal of Public Procurement
Publication Date: 2026-01-01
Volume: Unknown
Issue: Unknown
Page Range: 1-49
Description:
Purpose – This paper aims to systematically review key theories, constructs and empirical findings from studies that applied partial least squares structural equation modelling (PLS-SEM) within domains of public procurement research. Design/methodology/approach – In this study, a systematic literature review was conducted, from which 37 relevant publications from Scopus and Web of Science (WoS) that met the inclusion criteria and published between 2010 and 2024 were analysed. Findings – Over the period of 15 years, PLS-SEM has been widely applied in public procurement research, especially in developing countries. Past research from 2010 to 2014 focused solely on e-procurement adoption and implementation, whereas from 2015 to 2019, research interests included e-procurement adoption and implementation, strategic alliances and other aspects of the construction industry. Recent studies from 2020 to 2024 further emphasise contemporary issues such as sustainability, innovation, technology adoption and performance. Institutional theory dominates as the primary theoretical lens, followed by resource-based view and agency theory. Key constructs are based on e-procurement, user perceptions, system quality, governance, innovation, sustainability, risks and performance. Despite growing interests, little is known on evidence from moderated mediation analysis, and most reviewed studies revealed mixed research findings in the research field, offering rich opportunities for future research. Social implications – The paper enhances evidence-based policymaking grounded from consolidated theoretical foundations, constructs and findings from the public procurement research. This is relevant for improving public procurement processes, and support transparency and efficiency in the public sector. Technological aspects associated with Internet of Things, artificial intelligence and blockchain have received little attention in public procurement research. Therefore, future studies should consider these technologies, as they have substantial social implications. Originality/value – To the best of the authors’ knowledge, this is the first comprehensive review that consolidates studies using PLS-SEM in public procurement research from Scopus and WoS. This review provides a foundational reference point for future research and offers a clearer picture that shapes the thematic direction of future studies that use PLS-SEM in public procurement research.
Open Access: Yes
Entity-relation enhanced bidirectional information fusion for relational triples extraction
Publication Name: Engineering Applications of Artificial Intelligence
Publication Date: 2026-01-01
Volume: 163
Issue: Unknown
Page Range: Unknown
Description:
Relational triple extraction refers to identifying triples consisting of entities and relations form unstructured texts. The existing studies usually adopt an unidirectional extraction strategy, which fails to fully explore the semantic information related to entities and relations. And they rely heavily on initial extraction results when conducting multi-step extraction. To address this issue, we propose a novel Entity-Relation Enhanced Bidirectional Information Fusion approach (ER-EBIF). Specifically, we adopt a bidirectional extraction strategy of ”entity-to-relation” and ”relation-to-entity” to identify triples. One branch extracts potential relations, then extracts entities associated with those relations. The other branch initially extracts the potential subjects and objects as well as subsequently extracts relations between pairs of entities consisting of subjects and objects. Moreover, the contextual information is enhanced with a self-attention mechanism by integrating the information of potential relations and potential entities to better exploit the semantic information of entities and relations. Extensive experimental results on various datasets show that ER-EBIF exhibits better performance than other baselines and effectiveness in addressing the issue of dependency on initial results in multi-step extraction.
Open Access: Yes
Gender-specific obstacles and employment disparities in the V4 countries: a study on finding the ideal workplace
Publication Name: Regional Statistics
Publication Date: 2026-01-01
Volume: 16
Issue: 1
Page Range: 100-131
Description:
Out of the European Union’s 104 NUTS 1 (Nomenclature of Territorial Units for Statistics – Level 1) regions, those belonging to the Visegrád Group (also known as Visegrád Four or V4), have been selected for this study due to their comparable socioeconomic characteristics and regional relevance. This study aims to determine whether the obstacles to finding the right employer and job role differ between genders in the V4. These regions, through their historical background and intensive economic relations, influence not only their own territories but also the economy and value system of the entire continent. The results show significant differences between the countries in terms of the types and intensity of barriers. In Hungary, language barriers play a crucial role in restricting participation in the international labour market. In Poland, unequal access to educational opportunities is predominant. In Slovakia, the lack of flexible work arrangements tailored to family responsibilities emerged as the most significant obstacle. In certain areas of the Czech Republic, the influence of traditional gender roles was decisive. By identifying these barriers, this study contributes to understanding how gender disparities shape job-seeking experiences across the V4 countries. The research highlights that understanding the differences between countries is essential for a deeper comprehension of labour market barriers. Based on these findings, targeted measures are required, such as expanding language training in Hungary, making educational opportunities more accessible in Poland, and promoting flexible employment forms in Slovakia and less-developed areas of the Czech Republic. The results provide valuable guidance for developing policies aimed at improving gender equality and labour market participation, particularly through region-specific approaches.
Open Access: Yes
DOI: 10.15196/RS160105
A SPECTRAL COLLOCATION SCHEME WITH 2D ULTRASPHERICAL WAVELETS FOR FRACTIONAL NONLINEAR GAS DYNAMICS EQUATIONS UNDER CAPUTO–FABRIZIO DERIVATIVE
Publication Name: Fractals
Publication Date: 2026-01-01
Volume: Unknown
Issue: Unknown
Page Range: Unknown
Description:
Gas Dynamics Equations (GDEs) play a fundamental role in modeling fluid flows phenomena across a range of applications, from environmental systems to aerospace engineering. These equations mathematically represent the fundamental laws of mass, momentum and energy conservation. Modeling complex gas flows often requires advanced mathematical tools capable of capturing nonlocal and memory-dependent behavior. Therefore, this study explores the implementation of the Caputo–Fabrizio Fractional Derivative (CFFD) in the analysis of GDEs, highlighting its potential to accurately capture the behavior of complex fluid dynamics systems. A two-dimensional (2D) wavelet-based approach combined with suitable collocation grids is employed to approximate the solutions for spacetime Fractional Gas Dynamics Equations (FGDEs). The concept of the CFFD, with its nonsingular kernel, is integrated into the framework of GDEs, offering a more precise analytical perspective. By reformulating the FGDEs into a system of algebraic equations, the proposed approach enables efficient computation via iterative technique. The error analysis of the numerical results is presented through graphs and tables for three illustrative examples with varying fractional values, demonstrating a strong correlation between the analytical and approximated solutions. The performance of the scheme is evaluated using multiple error metrics, including minimum absolute error, L∞ error, L2 error, and LRMS errors. The absolute errors demonstrate the improvement in results of FGDEs as the wavelet basis increases. The results validate the reliability and ease of implementation of the suggested approach for solving the FGDEs. The study demonstrates the method’s reliability, and potential for solving a wide class of nonlinear fractional models governed by nonlocal dynamics.
Open Access: Yes
Applying Quadri-Partition Neutrosophic Soft Locally Compact Spaces to Enhance Machine Learning and Uncertainty Management
Publication Name: International Journal of Analysis and Applications
Publication Date: 2026-01-01
Volume: 24
Issue: Unknown
Page Range: Unknown
Description:
Within the broader framework of quadri-partition neutrosophic soft bi-topological spaces (QPNSBTS), the concept of quadri-partition neutrosophic soft locally compact space (QPNSLCS) is introduced in this research. It strengthens the theoretical foundation for handling uncertainty in complex topological structures by demonstrating that local compactness, particularly when combined with the Hausdorff requirement, entails the existence of compact neighbors and compactness in subspaces. The key concepts and theorems illustrate how compactness can be effectively used in the context of neutrosophic soft sets, which are a more powerful way to handle unclear and ambiguous data in advanced mathematical and practical applications. Furthermore, a number of machine learning algorithms are used to explore the concept of a tangent similarity between two quadri-partition neutrosophic soft sets. Additionally, the current study includes a number of studies and visualizations to evaluate the effectiveness of different clustering algorithms and dimensionality reduction techniques. Each of the graphics in the findings illustrates a distinct method for viewing and comprehending complex data. The K-means++ initialization (Fig. 6.1) serves as an illustration of how the algorithm's initialization step improves clustering accuracy by choosing centroid (data points) that are widely distributed, reducing the likelihood of subpar clustering performance. More training is required since hidden units are only activated with low activations, according to restricted Boltzmann Machine (RBM) activation patterns (Fig. 6.2). Additionally, the Linear Discriminant Analysis (LDA) plots (Fig. 6.4) and Heatmaps (Fig. 6.3) might provide helpful details regarding the organization and segregation of the datasets. The discussion of the results, which can be devoted to their applicability in terms of clustering, dimensionality reduction, and feature learning, is based on these methods and the associated visual models.
Open Access: Yes
