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Children with autism spectrum disorder (ASD) face difficulty with educational attainment because of to their inability to interact with others. One intervention that is used to increase social skills in individuals with ASD is social stories. This study aimed at exploring the impact of digital social stories in improving social skills of two students with ASD in the UAE.

An experimental AB single-subject study was conducted to investigate the impact of digital social stories on nonverbal communication, targeting two specific behaviors: raising hands before leaving one’s seat (TB1) and playing and sharing toys with peers (TB2). Two digital social stories (DSS1 and DSS2) were developed for the purpose of this study and transformed using a digital platform to be displayed on an iPad (tablet).

This study involved two male participants with ASD (10 and 11 years old). Participant one demonstrated improvement in TB1 (mean of 1.11) because of DSS1 in the intervention phase. Participant two demonstrated improvement of 18% in TB2 ( mean of 0.18) as a result of DSS2 in the intervention phase.

Both students that participated in the study showed a positive change in their target behaviors during the intervention phase intervention at different levels. Using an ABA study design would have been stronger in establishing a more valid causal relation in this single-subject design study. However, due the COVID-19 closures and curfews, the researchers had to switch to the AB design.

This study demonstrated how social stories had a positive impact on ASD social skills. Further, it indicated the potential effectiveness of using digital social stories to reduce undesirable behaviors or increase a desirable behaviors in children who have ASD.

This study explores the factors influencing knowledge hiding (KH) in international construction projects (ICPs), focussing on the role of ethnic minorities (EMs) and interpersonal distrust (ID). It also aims to understand how these factors influence KH and explore the mediating effect of ID on the relationship between EMs and KH.

A survey questionnaire was developed and distributed to professionals participating in ICPs. We used structural equation modelling (SEM) to analyse 294 valid responses, examining the effect of EMs, ID and demographic variables on KH behaviours. Our approach integrates insights from social identity theory (SIT) and actor network theory (ANT) to provide a comprehensive framework for understanding the observed dynamics.

The findings reveal that EMs significantly influence KH behaviours, with ID partially mediating this relationship. Additionally, demographic variables such as gender and age also play significant roles in KH behaviours. However, the degree of education did not show a significant impact on KH. Our results emphasise the critical importance of addressing ID and fostering inclusive environments to reduce KH.

While our study sheds light on the complex dynamics of KH in ICPs, further research could explore additional contextual factors and organisational influences. While our study emphasises the importance of inclusive practices and trust-building to mitigate KH, it also recognises the need for a deeper understanding of power dynamics and organisational contexts.

Our findings underscore the importance of creating transparent and inclusive cultures of knowledge sharing (KS). Implementing inclusion initiatives and providing cultural awareness training can enhance project outcomes and organisational success. We also propose a practical framework to mitigate KH by promoting trust, inclusivity and effective KS practices.

This study contributes to the understanding of knowledge management in multicultural project teams by integrating SIT and ANT, offering a comprehensive perspective on the factors driving KH in ICPs. The findings pave the way for future investigations into power dynamics and organisational contexts within ICPs.

Narrative disclosures offer further elucidation of a company's financial performance beyond what is presented in numerical format. This can assist stakeholders in gaining a deeper comprehension of the elements that impact reported earnings, thereby improving the quality of financial information. The current research explores the impact of narrative disclosure on the earnings quality of firms listed on the Amman Stock Exchange (ASE).

Appropriating an index to measure the narrative disclosure level in the research sample firms, the research utilizes an analysis of the textual content of nonfinancial reports and statements issued by the management of the ASE-listed nonfinancial firms between 2013 and 2022. The financial statements issued in the annual financial reports are also adopted to extract data on earnings quality and the controlling variables. The analysis of the data and attainment of the findings necessitate using the panel data.

It is indicated that narrative disclosure affects earnings quality. To be precise, the greater the narrative disclosure, the lower the absolute value of the voluntary discretionary accruals and thus the higher the quality of accounting earnings.

The findings contribute to new research on disclosure issues, particularly narrative disclosure, which enhances reader confidence in financial and nonfinancial reports and prevents misleading and manipulated information.

This research helps decision-makers understand the relationship between reports, statements and earnings quality in a firm. It's unique in exploring this relationship, especially in developing countries. The study is the first of its kind in Jordan, known for its economic stability and strategic location in the Middle East, making its findings applicable to similar environments.

The economy of the Palestinian Territories (PT) is small, poorly developed, and highly dependent on Israel; at the same time, the land is limited, Israel controls 80‐85 per cent of the Palestinian water, and there is large‐scale unemployment. Faced with this situation, small and micro‐enterprises have come to play a critical role in the economy of the PT. Donors, the Palestinian Authority (PA), and UNRWA have recognised that many of the managers suffer from managerial weaknesses, and training is one of the long‐term keys to promote the development of small and micro‐enterprises and alleviate the problem of persistent unemployment in the PT. To support the peace agreement, the International Community promised to support the Palestinian economy. Part of this aid has been spent for small and micro‐enterprise development, and for establishing managerial training programmes. These programmes aim to encourage economic development of the PT, through supporting small business education and entrepreneurship training. These programmes suffered from various problems, such as lack of professional trainers, the majority of the managers did not attend the training programme courses, some of these programmesmissed funding. Therefore, some training programmes were closed during the last two years. On the other hand, the managers of small businesses still suffer from various managerial problems. However, this article presents a description of the current situation in PT. Especially, the economic and managerial situation, particularly for the SMEs and TPs in the PT.

By addressing the dearth of literature on the subject of cybersecurity risks and artificial intelligence (AI), this study aims to close a research gap by concentrating on the ever-changing environment of online social networks (OSNs) and technology. The main goals are to classify cyberattacks into categories like malware, phishing/spam and network intrusion detection; to identify efficient algorithms for preventing cyber threats; to review relevant literature from 2019 to 2020; and to use machine learning algorithms to detect suspicious behavior related to malware. The study offers a novel framework that suggests particular machine learning algorithms for every kind of cyber threat, hence improving cybersecurity knowledge and reaction capacities. This makes the research useful for examining the impact of cybersecurity on smart cities.

Thirty papers have been examined on AI and machine learning algorithms, including K-nearest-neighbor (KNN), convolutional neural networks (CNN) and Random Forest (RF), that were published in 2019 and 2020. Using analytical software (NVivo), a qualitative approach is used to retrieve pertinent data from the chosen research. The researchers divide cyberattacks into three groups: network intrusion detection, phishing/spam and malware.

The study’s conclusions center on how AI and machine learning algorithms linked to cybersecurity are reviewed in the literature, how cyberattacks are classified and how an inventive framework for identifying and reducing risks is proposed. This makes the research useful for researching the implications of cybersecurity for smart cities.

The practical implications of this research are noteworthy, particularly in the realms of technology, AI, machine learning and innovation. The utilization of the NVivo technique enhances decision-making in uncertain situations, making the study’s results more reliable. The findings showcase the applicability of tools in analyzing malicious cyberattacks to address issues related to social media attacks, emphasizing their practical utility. The study’s relevance is further highlighted by a real-world example, where a Kuwaiti public sector fell victim to a malware attack, underlining the importance of cybersecurity measures aligned with the New Kuwait 2035 strategic development plan. The innovative framework presented in the research guides the selection of algorithms for detecting specific malicious attacks, offering practical insights for securing information technology (IT) infrastructure in Kuwait.

The rapid digitization in Kuwait, accelerated by the COVID-19 pandemic, underscores the pivotal role of technology in government services. Ma’murov et al. (2023) emphasize the significance of digitization, particularly in accessing and verifying COVID-19 information. The call for a dedicated digital library for preserving pandemic-related material aligns with the evolving digital landscape. Cybersecurity emerges as a critical concern in Kuwait and the Gulf Cooperation Council (GCC), necessitating transnational cooperation (Nasser Alshabib and Tiago Martins, 2022). In the local context, the inefficiency of information security systems and low awareness among government employees pose cybersecurity challenges (Abdulkareem et al., 2014). Social media’s role during the pandemic highlights its significance, yet the need for cybersecurity in this domain remains underexplored (Ma’murov et al., 2023; Safi et al., 2023).

The unique aspect of the paper is its in-depth investigation of the relationship between cybersecurity and AI in OSNs. It uses a special application of machine learning methods, including CNN, RF and KNN, to identify suspicious behavior patterns linked to malware. The detailed analysis of 30 research papers released between 2019 and 2020, which informs the choice of suitable algorithms for diverse cyber threats, further emphasizes the study’s uniqueness. The novel framework that has been suggested categorizes assaults and suggests certain machine learning techniques for identification, offering a useful instrument to improve comprehension and reactions to a variety of cybersecurity issues.

This study contributes to the understanding of the health effects of pesticides exposure and of how pesticides have been and should be regulated.

This study presents literature reviews for the period 2000–2013 on (i) the health effects of pesticides and on (ii) preference valuation of health risks related to pesticides, as well as a discussion of the role of benefit-cost analysis applied to pesticide regulatory measures.

This study indicates that the health literature has focused on individuals with direct exposure to pesticides, i.e. farmers, while the literature on preference valuation has focused on those with indirect exposure, i.e. consumers. The discussion highlights the need to clarify the rationale for regulating pesticides, the role of risk perceptions in benefit-cost analysis, and the importance of inter-disciplinary research in this area.

This study relates findings of different disciplines (health, economics, public policy) regarding pesticides, and identifies gaps for future research.

Hospital structures serve to protect and improve public health; however, they are recognized as a major source of environmental degradation. Thus, an effective performance evaluation framework is required to improve hospital sustainability. In this context, this study presents a holistic methodology that integrates the sustainability balanced scorecard (SBSC) with fuzzy Delphi method and fuzzy multi-criteria decision-making approaches for evaluating the sustainability performance of hospitals.

Initially, a comprehensive list of relevant sustainability evaluation criteria was considered based on six SBSC-based dimensions, in line with triple-bottom-line sustainability dimensions, and derived from the literature review and experts’ opinions. Then, the weights of perspectives and their respective criteria are computed and ranked utilizing the fuzzy analytic hierarchy process. Subsequently, the hospitals’ sustainable performance values are ranked based on these criteria using the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution.

A numerical application was conducted in six public hospitals to exhibit the proposed model’s applicability. The results of this study revealed that “Patient satisfaction,” “Efficiency,” “Effectiveness,” “Access to care” and “Waste production,” respectively, are the five most important criteria of sustainable performance.

The new model will provide decision-makers with management tools that may help them identify the relevant factors for upgrading the level of sustainability in their hospitals and thus improve public health and community well-being.

This is the first study that proposes a new hybrid decision-making methodology for evaluating and comparing hospitals’ sustainability performance under a fuzzy environment.

Authenticity/ الصحة (as-sehah) serves as a criterion or predictor variable for the purpose of a comparative theological investigation of employment relations parameters in light of social teachings from Sunni Islam and Roman Catholicism. Authenticity finds initial, shared significance in both religious traditions because of its critically important role in judgments concerning the legitimacy of source documents. It also stands in both traditions as an inspirational goal for human life.

Particular issues of theological method for cross-cultural analysis are addressed by the use of insight-based critical realism as a transcultural foundation. Workplace parameters, the minimal enabling conditions for the possibility of authentic employment relations, are then identified and compared. The authors explore shared expectations for authenticity enabling conditions in terms of the direct and indirect employer: those national laws, systems and traditions that condition the functional range of authenticity that can be actualized within national or other work settings as experienced in the direct employment contract.

The study found remarkable consistency in the minimal conditions identified by Roman Catholic and Sunni Islam social teachings for the prospects of authenticity in employment relations. These conditions addressed seven parameters: work and the concept of labor; private property; the nature of the employment contract; unions and collective bargaining; the treatment of wages; the relationship between managerial prerogative and employee participation; and the crucial role of the state as indirect employer.

Specific minimal or threshold conditions of employment are described to ensure the prospect for authenticity in modern employment relations according to religious traditions. These include just cause employment conditions, unions and collective bargaining support, some form of management consultation/Shura, a living wage and a consultative exercise of managerial prerogative.

The study offers prescriptive and analytical aid to ensure assessment of circumstances fostering authenticity in employment relations.

The method and findings are a first effort to clarify thought and aid mutual understanding for inter-faith employment circumstances based on Roman Catholic and Sunni Islam social teachings through a transcultural foundation in cognitional operations. The criterion variable specification of authenticity conditions offers a fully developed basis to support further empirical research in management spirituality, corporate social responsibility and enterprise sustainability.

The advancement in science and technology has led to the existence and continuous growth of various physical machines and now computer programs which are supposed to perform once thought unbelievable multi-tasks for humans.

Many firms, governments, industries and syndicates are switching to automated process for achieving maximum output and having minimum cost and errors in the manufacturing and various other processes, hence the role of human involvement is getting decreased. With the Industry 4.0 standards being opted, industry gurus have been forecasting the limiting power of human labour and interaction and fears exist complete replacement of human beings from the working environment by robots and automated machines.

Artificial intelligence has aggressively overtaken almost all fields of businesses and human resource (HR) hasn't been either immune to that. Robotics is an important factor as well.

Technology implementation has its own benefits and negative impacts which is creating fears among various professionals with regards to their complete replacement by machines.

The following paper looks deeply into various researches performed by scholars to have a thorough knowledge of present-day status of human–machine collaboration and the challenges organizations are facing. It will help in understanding the current scenario of HR with modern technologies.