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This paper aims to explore the determinants causing fake information proliferation on social media platforms and the challenges to control the diffusion of fake news phenomena.

The authors applied the systematic review methodology to conduct a synthetic analysis of 37 articles published in peer-reviewed journals retrieved from 13 scholarly databases.

The findings of the study displayed that dissatisfaction, behavior modifications, trending practices to viral fake stories, natural inclination toward negativity and political purposes were the key determinants that led individuals to believe in fake news shared on digital media. The study also identified challenges being faced by people to control the spread of fake news on social networking websites. Key challenges included individual autonomy, the fast-paced social media ecosystem, fake accounts on social media, cutting-edge technologies, disparities and lack of media literacy.

The study has theoretical contributions through valuable addition to the body of existing literature and practical implications for policymakers to construct such policies that might prove successful antidote to stop the fake news cancer spreading everywhere via digital media. The study has also offered a framework to stop the diffusion of fake news.

This study aims to examine the perceptions and opinions of relevant stakeholders regarding entrepreneurship opportunities and growth in the Gilgit-Baltistan (GB) province of Pakistan. Specifically, it focuses on the role of special economic zones (SEZs), such as Maqpondass SEZ and the China–Pakistan Economic Corridor (CPEC), in fostering nascent entrepreneurship (NE) and promoting regional development.

The study employs ordered logistic regression to estimate the relationship between various independent variables and nascent entrepreneurship (NE). The independent variables include awareness of CPEC (AAC), awareness of Maqpondass SEZ (AAMEZ), SEZ incentives (SEZInc), regional market competitiveness (RMC), loan availability (LA) and education and experience (EE).

The findings indicate a robust positive relationship between SEZ-based industries and the growth of local small businesses and enterprises in Gilgit-Baltistan. Furthermore, the study suggests that government incentives, access to finance, skill development, relevant knowledge, and connections with local businesses facilitate the establishment of new ventures.

The study underscores the importance of focusing on human capital development, providing financial assistance, and creating incentives for adopting advanced technology to foster the growth of local businesses in Gilgit-Baltistan through SEZs. It emphasizes the need for policymakers and stakeholders to prioritize initiatives that support entrepreneurship and innovation in the region.

This study contributes to the existing literature by providing novel insights into the perceptions of entrepreneurship development in Gilgit-Baltistan, particularly concerning the influence of natural resources and SEZs. It fills a gap in the research by offering valuable implications for policymakers, researchers, and practitioners seeking to promote sustainable economic development in the region.

This study aims to investigate whether organizational complexity (hereafter firm complexity) increases audit report lag (ARL) in a unique environment of GCC countries.

The research study uses a panel data set of 6,084 firm-year observations of nonfinancial firms from GCC economies from 2009 to 2022. First, the study uses an ordinary least square estimator to examine the association of firm complexity with ARL. Second, for robustness purposes, the study applies the propensity score matching technique.

This research study finds that the firms’ complexity increases ARL. Supporting the argument that auditors respond to firm complexity with increased effort, the authors find a positive relation of firm complexity with ARL. This relationship is augmented by auditor change, auditors’ tenure, auditor-qualified opinion and adoption of IFRS. In addition, the authors also find that Big-4 and audit firm industry specialization curtail the positive impact of firm complexity on ARL.

Firms in the GCC have less time to complete their audit and complex firms are likelier to have bigger ARLs. This study provided evidence regarding the curtailing effect of audit quality in GCC. Our findings suggest policymakers and reformers choose improved audit quality to reduce the possibility of larger ARL.

This study enriches the scholarship by presenting a mechanism for reducing the ARL of complex firms through higher audit quality. This study contributes to agency theory by emphasizing audit quality’s important role in emerging markets.

This study mainly aims to explore the causal nexus between big data-driven organizational capabilities (BDDOC) and supply chain innovation capabilities (SCIC) and innovation performance (IP), then explore the indirect effect of SCIC and also test the moderating effects for both internal supply chain integration (ISCI) and external supply chain integration (ESCI) into the relationship between BDDOC and SCIC.

In order to test the conceptual model and the hypothesized relationships between all the constructs, the data were collected using a self-reported questionnaire by workers in Jordanian small and medium manufacturing enterprises. Partial least squares-structural equation modeling (PLS-SEM) was employed to test the model.

The paper reached a set of interesting results where it was confirmed that there is a positive and statistically significant relationship between BDDOC, SCIC and IP in addition to confirming the indirect effect of SCIC between BDDOC and IP. The results also showed that there is a moderating role for both ESCI and ISCI.

This study can be considered the first study in the current literature that investigates these constructs as shown in the research model. Therefore, the paper presents an interesting set of theoretical and managerial contributions that may contribute to covering part of the research gap in the literature.

This study aims to examine the relationship between tool adoption and information literacy within smallholder farmers (SHFs).

A structured questionnaire was used to gather data for this quantitative study from 225 SHFs. Structural equation modelling was done to test the hypotheses.

The findings established that tool adoption dimensions (Information and communication technologies (ICT) acceptance, language use and information culture) positively and significantly influenced information literacy. Information culture had the strongest impact.

The study enriches the situated learning theory (SLT) literature by introducing tool adoption as a predictor of information literacy in a new context of SHFs. Use of tools as independent variables is a positive deviation from previous studies that have used them as mediating variables. Despite the contributions, the cross-sectional design study undermines the ability to solicit more detailed perspectives from the lived in experience of the respondents.

Managers should promote usage of context-specific tools like local radio stations and mobile phones, but also use language tailored to farmer contexts when disseminating information. Policymakers should leverage on social and cultural settings when designing information interventions.

The study highlights critical factors that significantly promote information use for improved productivity for SHFs, cumulatively increasing the country’s gross domestic product (GDP). Socially, findings may reduce on their poverty levels of farmers.

This study offers a novel perspective in information literacy domain by using the SLT to delineate contextual tools that are paramount in predicting of information literacy in an under research informal context of SHFs.

This study investigates the role of market concentration and efficiency in banking system stability during the COVID-19 pandemic. We empirically test the hypothesis that market concentration and efficiency are significant determinants of bank performance and stability during the time of crises, using a sample of 575 banks in 20 countries in the Middle East and North Africa (MENA).

The main sources of bank data are the BankScope and BankFocus (Bureau van Dijk) databases, World Bank development indicators, and official websites of banks in MENA countries. This study combined descriptive and analytical approaches. We utilize a panel dataset and adopt panel data econometric techniques such as fixed/random effects and the Generalized Method of Moments (GMM) estimator.

The results reveal that market concentration negatively affects bank profitability, whereas improved efficiency further enhances bank performance and contributes to the banking sector’s overall stability. Furthermore, our analysis indicates that during the COVID-19 pandemic, bank stability strongly depended on the level of market concentration, but not on bank efficiency. However, more efficient banks are more profitable and stable if the banking institutions are Islamic. Similarly, Islamic banks with the same level of efficiency demonstrated better overall financial performance during the pandemic than their conventional peers did.

The main limitation is related to the period of COVID-19 pandemic that was covered in this paper (2020–2021). Therefore, further investigation of the COVID-19 effects on bank profitability and risk will require an extended period of the pandemic crisis, including 2022.

This study provides information that will enable bank managers and policymakers in MENA countries to assess the growing impact of market concentration and efficiency on the banking sector stability. It also helps them in formulating suitable strategies to mitigate the adverse consequences of the COVID-19 pandemic. Our recommendations are useful guides for policymakers and regulators in countries where Islamic and conventional banking systems co-exist and compete, based on different business models and risk management practices.

The authors contribute to the banking stability literature by investigating the role of market concentration and efficiency as the main determinants of bank performance and stability during the COVID-19 pandemic. This study is the first to analyze banking sector stability in the MENA region, using both individual and risk-adjusted aggregated performance measures.

Current research efforts exhibit a surge imperative for a building information modelling (BIM) approach that embodies a repository of all relevant data of existing building components while monitoring and consistently recording numerous components’ functions throughout its lifecycle, especially in Egypt. This research paper aims to develop an integrated as-is BIM-facility management (FM) information model for the existing building’s components via a case study, depicting a repository for historical data and knowledge amassed from inspections and conveying maintenance decisions automatically during the FM practices.

The developed approach pursues four successive steps: data acquisition and processing of building components; components recognition from point clouds; modelling scanned point clouds; and quick response code information transfer to BIM components.

The proposed approach incorporates the as-is BIM with the building components’ as-is FM information to portray a repository for historical data and knowledge collected from inspections to proactively benefit facility managers in simplifying, expediting and enhancing maintenance decisions automatically during FM practices.

This paper presents a digital alternative to manual maintenance recordkeeping concerning building components to retrieve their as-is and historical data using a case study in Egypt. This paper proposes a broad scan to as-is information BIM approach for the existing building’s components to condone maintenance interventions using a versatile, affordable, readily available and multi-functional method for scanning the building’s components using a handheld tool.

The purpose of this study is to examine the sociocultural implications of caring for persons with COVID-19 in a developing country context.

In total, 156 nurses participated in the study. Stratified random sampling methodology was used. Data were collected via online self-administered questionnaire. Descriptive and inferential statistics, including ANOVA tests were done.

Nurses experienced stigmatization, discrimination and reduced income. Nurses functioned on the frontline during the COVID-19 pandemic and encountered negative sociocultural experiences from a personal, social and professional perspective. ANOVA showed statistically significant relationships between the conflicts between their work role, family commitments and level of physical interactions with a number of variables.

Data were collected from one Regional Health Authority and may not be representative of the national population of nurses. Further, as the researchers depended on gatekeepers to access participants, the recruitment process may not have been entirely based on randomization as originally agreed.

The findings from this study can be used as a framework to develop context specific programmes and policies to support health professionals, including nurses.

Pandemics, while not new, contribute to serious sociocultural challenges for individuals and families, as well as nurses, as part of their professional roles. In this regard, maintaining effective social networks must be central to effective functioning in crisis situations, such as pandemics.

Nurses have played a key role, working both to identify, isolate and manage those with COVID-19 and supporting those who have non-COVID-19 related health needs. While nurses have been at the forefront delivering care in these uncertain times, doing so puts them at great risk, for not only contracting COVID-19 but also for experiencing negative psychosocial effects that may be due to the nature of their jobs.

The use of waste polyethylene terephthalate (PET) plastics derived from shredded bottles in concrete is not formalized yet, especially in reinforced members such as beams and columns. The disposal of plastic wastes in concrete is a viable alternative to manage those wastes while minimizing the environmental impacts associated to recycling, carbon dioxide emissions and energy consumption.

This paper evaluates the suitability of 2D deterministic and stochastic finite element (FE) modeling to predict the shear strength behavior of reinforced concrete (RC) beams without stirrups. Different concrete mixtures prepared with 1.5%–4.5% PET additions, by volume, are investigated.

Test results showed that the deterministic and stochastic FE approaches are accurate to assess the maximum load of RC beams at failure and corresponding midspan deflection. However, the crack patterns observed experimentally during the different stages of loading can only be reproduced using the stochastic FE approach. This later method accounts for the concrete heterogeneity due to PET additions, allowing a statistical simulation of the effect of mechanical properties (i.e. compressive strength, tensile strength and Young’s modulus) on the output FE parameters.

Data presented in this paper can be of interest to civil and structural engineers, aiming to predict the failure mechanisms of RC beams containing plastic wastes, while minimizing the experimental time and resources needed to estimate the variability effect of concrete properties on the performance of such structures.

The purpose of this research is to develop a framework of an ontology-based Asset Information Model (AIM) for a Digital Twin (DT) platform and enhance predictive maintenance practices in building facilities that could enable proactive and data-driven decision-making during the Operation and Maintenance (O&M) process.

A scoping literature review was accomplished to establish the theoretical foundation for the current investigation. A study on developing an ontology-based AIM for predictive maintenance in building facilities was conducted. Semi-structured interviews were conducted with industry professionals to gather qualitative data for ontology-based AIM framework validation and insights.

The research findings indicate that while the development of ontology faced challenges in defining missing entities and relations in the context of predictive maintenance, insights gained from the interviews enabled the establishment of a comprehensive framework for ontology-based AIM adoption in the Facility Management (FM) sector.

The proposed ontology-based AIM has the potential to enable proactive and data-driven decision-making during the process, optimizing predictive maintenance practices and ultimately enhancing energy efficiency and sustainability in the building industry.

The research contributes to a practical guide for ontology development processes and presents a framework of an Ontology-based AIM for a Digital Twin platform.