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This study aims to identify the enabling factors for Building Information Modeling (BIM) adoption in Vietnamese construction enterprises and uncover their interrelationships. This will help stakeholders focus on controlling and allocating resources (time, personnel, and costs) appropriately to adopt BIM and differentiate themselves from fierce competition in the architectural, engineering, construction and operations (AECO) industry.

This study first identifies and evaluates 32 enabling factors for applying BIM in the Vietnamese construction industry according to the TOE extended framework. Afterwards, a hybrid questionnaire survey using a convenient sampling method is conducted to capture stakeholders' views. The exploratory factor analysis (EFA) and the partial least squares structural equation modelling (PLS-SEM) technique are then applied to identify the constructs of the enabling factors and their interrelationships.

The study extracts six constructs that could have a significant impact on the adoption of BIM in construction enterprises, namely: technical feasibility (TF), human resources and management (HRM), company business vision (CBV), political environment (PE), economic viability (EV), and legal aspects (LA). Based on eleven proposed hypotheses, the analysis results confirm nine hypotheses and show that the HRM, TF, and CBV have the strongest effects on managers in evaluating the factors for BIM.

The results of the study fill the gap in knowledge by discovering the interrelationships among the enabling factors for BIM adoption in construction enterprises. The results might support the construction enterprises and their stakeholders in increasing the application of BIM, and digital transformation in construction industry.

In response to growing concerns over the negative consequences of Internet addiction on adolescents’ mental health, coupled with conflicting results in this literature stream, this meta-analysis sought to (1) examine the association between Internet addiction and depressive symptoms in adolescents, (2) examine the moderating role of Internet freedom across countries, and (3) examine the mediating role of excessive daytime sleepiness.

In total, 52 studies were analyzed using robust variance estimation and meta-analytic structural equation modeling.

There was a significant and moderate association between Internet addiction and depressive symptoms. Furthermore, Internet freedom did not explain heterogeneity in this literature stream before and after controlling for study quality and the percentage of female participants. In support of the displacement hypothesis, this study found that Internet addiction contributes to depressive symptoms through excessive daytime sleepiness (proportion mediated = 17.48%). As the evidence suggests, excessive daytime sleepiness displaces a host of activities beneficial for maintaining mental health. The results were subjected to a battery of robustness checks and the conclusions remain unchanged.

The results underscore the negative consequences of Internet addiction in adolescents. Addressing this issue would involve interventions that promote sleep hygiene and greater offline engagement with peers to alleviate depressive symptoms.

This study utilizes robust meta-analytic techniques to provide the most comprehensive examination of the association between Internet addiction and depressive symptoms in adolescents. The implications intersect with the shared interests of social scientists, health practitioners, and policy makers.

The objective of this paper is to evaluate whether the data from consignors, logistics service providers (LSPs) and consignees contribute to the prediction of air transport shipment delays in a machine learning application.

The research database contained 2,244 air freight intercontinental shipments to 4 automotive production plants in Latin America. Different algorithm classes were tested in the knowledge discovery in databases (KDD) process: support vector machine (SVM), random forest (RF), artificial neural networks (ANN) and k-nearest neighbors (KNN).

Shipper, consignee and LSP data attribute selection achieved 86% accuracy through the RF algorithm in a cross-validation scenario after a combined class balancing procedure.

These findings expand the current literature on machine learning applied to air freight delay management, which has mostly focused on weather, airport structure, flight schedule, ground delay and congestion as explanatory attributes.

Despite its devastating nature, the COVID-19 pandemic has also catalyzed a substantial surge in the adoption and integration of technological tools within economies, exerting a profound influence on the dissemination of information among participants in stock markets. Consequently, this present study delves into the ramifications of post-pandemic dynamics on stock market behavior. It also examines the relationship between investors' sentiments, underlying behavioral drivers and their collective impact on global stock markets.

Drawing upon data spanning from 2012 to 2023 and encompassing major world indices classified by Morgan Stanley Capital International’s (MSCI) market and regional taxonomy, this study employs a threshold regression model. This model effectively distinguishes the thresholds within these influential factors. To evaluate the statistical significance of variances across these thresholds, a Wald coefficient analysis was applied.

The empirical results highlighted the substantive role that investors' sentiments and behavioral determinants play in shaping the predictability of returns on a global scale. However, their influence on developed economies and the continents of America appears comparatively lower compared with the Asia–Pacific markets. Similarly, the regions characterized by a more pronounced influence of behavioral factors seem to reduce their reliance on these factors in the post-pandemic landscape and vice versa. Interestingly, the post COVID-19 technological advancements also appear to exert a lesser impact on developed nations.

This study pioneers the investigation of these contextual dissimilarities, thereby charting new avenues for subsequent research studies. These insights shed valuable light on the contextualized nexus between technology, societal dynamics, behavioral biases and their collective impact on stock markets. Furthermore, the study's revelations offer a unique vantage point for addressing market inefficiencies by pinpointing the pivotal factors driving such behavioral patterns.

Disasters can affect the important sector of tourism across the world. This study aims to combine qualitative findings from 13 publications to enhance disaster management plans for the security and resilience of the tourist industry.

The authors used Noblit and Hare’s seven-step meta-ethnography method, identifying 13 qualitative studies on tourism disaster management through extensive searches in key databases (WoS, Scopus and Google Scholar), meeting inclusion criteria. NVivo 12 aided in coding, translation and comprehension of related ideas.

Five interrelated and third-ordered conceptual categories were identified: extreme natural and malevolent events, lack of risk management and emerg+ency response, sustainable tourism, tourism resilience factors, disaster awareness and preparedness. Effective strategies demand collaboration, resource allocation and local engagement.

This study offers a novel synthesis of qualitative research in tourism disaster management, enhancing understanding of resilience in the industry. It provides unique insights on cross-cultural dynamics, stakeholder engagement and integrated strategies while showcasing the utility of meta-ethnography in business and management research.

Construction sustainability (CS) is a strategic reaction to the sustainability expectations of the construction industry's external stakeholders. The extant literature has viewed the environmental, social and economic dimensions of CS as having independent effects on financial performance. Due to the influence of common stakeholders, however, interactions in these dimensions will be present in their effect on financial performance. Accordingly, this study identifies the mechanisms of the interactions between the three CS dimensions and how they jointly affect financial performance.

Content analysis of GRI reports of 60 large construction organisations, followed by a hierarchical regression analysis was used to identify the interactions between environmental, social and economic CS in their effect on financial performance.

Economic CS was found to indirectly, and not directly, affect financial performance, the effect being mediated by both environmental and social CS. Environmental CS was found to have a strong negative effect on financial performance, whilst social CS was found to have a strongly significant positive effect on financial performance.

The motivation for engaging in CS is that investment in economic CS will have a positive effect on both environmental and social CS outcomes, which, in turn can have a combined effect on financial performance.

This is one of the first studies investigating the effect of interactions between the environmental, social and economic CS dimensions on the financial performance of construction organisations. It is also one of the first studies that applies a sociotechnical framework to this relationship.

This study aims to examine the multidimensional nature of institutional distance as a driver of acquisition decisions in emerging markets. Then, this study aims to offer a nuanced perspective on the role of its various formal and informal dimensions by taking into account the potential contingency role played by a firm’s context experience.

Building on institutional economics and organizational institutionalism, this study explores the heterogeneity of institutional distance and its effects on the decision to enter emerging versus advanced markets through cross-border acquisitions. Thus, institutional distance is disentangled into its formal and informal dimensions, the former being captured by regulatory efficiency, country governance and financial development. Furthermore, our framework examines the moderating effect of an acquiring firm’s experience in institutionally similar environments, defined as context experience. The hypotheses are analyzed on a sample of 496 cross-border acquisitions by Italian companies in 41 countries from 2008 to 2018.

Findings indicate that at an increasing distance in terms of regulatory efficiency and financial development, acquiring firms are less likely to enter emerging markets, while informal institutional distance is positively associated with such acquisitions. Context experience mitigates the negative effect of formal distance and enhances the positive effect of informal distance.

This study contributes to institutional distance literature in multiple ways. First, by bridging institutional economics and organizational institutionalism and second, by examining the heterogeneity of formal and informal dimensions of distance, this study offers a finer-grained perspective on how institutional distance affects acquisition decisions. Finally, it offers a contingency perspective on the role of context experience.

Introduction: This chapter examines the impact of Financial Technology (Fintech) on Environmental, Social, and Governance (ESG) goals to promote a sustainable financial system. Digital payment platforms, blockchain applications, and AI-powered analytics have revolutionised the financial landscape in recent years. These advancements have made integrating ESG principles into investment decisions and business practices easier.

Purpose: The main aim of this chapter is to analyse the connections and possibilities that Fintech offers to achieve ESG goals. Understanding how Fintech can facilitate sustainable finance practices is crucial for promoting investment in Fintech.

Methodology: A series of indexes have been examined, including the Global FinTech Index (GFI) in Global and Regional Rank, the Global Sustainable Competitiveness Index, and performing the Green Growth Index, the Green Economic Opportunity Index, the Global Green Finance Index (GGFI), and the Financial Inclusion Index.

Findings: Through comparative analysis, it can be concluded that the countries with the highest rankings are Sweden, Finland, Denmark, Switzerland, and Germany. Sweden ranks highly in the GFI. These results show that these countries rank highly in achieving ESG objectives. Balkan countries, specifically Albania, Bosnia and Herzegovina, and Montenegro, have the weakest results compared to other countries. Policymakers can benefit from the study’s findings to design better regulations and frameworks that promote responsible fintech practices and foster sustainable finance.

Practical Implications: Regulators and agencies responsible for measuring fintech and ESG should strive to align the indexes associated with these two domains as closely as possible. In addition, businesses can utilise the findings of this study to increase awareness about the diverse solutions that fintech offers to achieve the objectives of ESG.

This study empirically examines the impact of motivation, transformational leadership and involvement in strategic planning (SP) on academic staff performance at higher education institutions (HEIs). It also examines how academics' involvement in SP mediates the associations between motivation, transformational leadership and performance.

This article conducted a quantitative approach based on a self-administered survey. Partial least squares structural equation modeling (PLS-SEM) was applied to analyze the data gathered from 192 faculty members at governmental HEIs in Oman.

The results indicated that academic staff motivation has a significant and positive impact on their involvement in SP and performance in HEIs. It is also revealed that employee involvement in SP activities is significantly affected by transformational leadership, while the latter does not affect academic staff performance. There is also a significant association between academic staff involvement in SP and their performance. Moreover, the relationships between motivation, transformational leadership and performance are fully mediated by academic staff involvement in SP at HEIs.

The current empirical work is one of the few endeavors to develop an integrated structural model to investigate how faculty members' performance could be affected by motivation, transformational leadership and involvement in SP. Furthermore, it is considered one of the first attempts to explore the intervening role of academic staff involvement in the SP process in the connections between motivation, transformational leadership and performance within the HEI realm.

In 2020, an outbreak of Salmonella Stanley linked to imported dried wood ear mushrooms affected 55 individuals in the United States of America. These mushrooms, commonly used in Asian cuisine, require processing, like rehydration and cutting, before serving. The US Centres for Disease Control and Prevention advise food preparers to use boiling water for rehydration to inactivate vegetative bacterial pathogens. Little is known about how food handlers prepare this ethnic ingredient and which handling procedures could enable Salmonella proliferation.

This study used content analysis to investigate handling practices for dried wood ear mushrooms as demonstrated in YouTube recipe videos and to identify food safety implications during handling of the product. A total of 125 Chinese- and English-language YouTube videos were analysed.

Major steps in handling procedures were identified, including rehydration, cutting/tearing and blanching. Around 62% of the videos failed to specify the water temperature for rehydration. Only three videos specified a water temperature of 100 °C for rehydrating the mushrooms, and 36% of the videos did not specify the soaking duration. Only one video showed handwashing, cleaning and sanitising of surfaces when handling the dried wood ear mushrooms.

This study found that most YouTube videos provided vague and inconsistent descriptions of the rehydration procedure, including water temperature and soaking duration. Food preparers were advised to use boiling water for rehydration to inactivate vegetative bacterial pathogens. However, boiling water alone is insufficient to inactivate all bacterial spores. Extended periods of soaking and storage could be of concern for spore germination and bacterial growth. More validation studies need to be conducted to provide guidance on how to safely handle the mushrooms.

This study will make a distinctive contribution to the field of food safety by being the first to investigate the handling procedure of a unique ethnic food ingredient, dried wood ear mushrooms, which has been linked to a previous outbreak and multiple recalls in the United States of America. The valuable data collected from this study can help target food handling education as well as influence future microbial validation study design and risk assessment.