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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 examines the impact of corporate governance on succession planning and organizational performance. Drawing on agency theory, the main purpose of this study is to identify the effect of corporate governance on succession planning by measuring the different characteristics of the board of directors.

This multi-quantitative research used primary and archival data. A total of 281 valid questionnaires were collected from Chinese listed family firms to gauge succession planning. Relevant archival data were obtained to measure board characteristics and organizational performance. All hypotheses were examined through structural equation modeling.

The outcomes indicate that corporate governance positively influences succession planning and, in turn, boosts superior organizational performance, which uncovers the mediating effect of succession planning on the relationship between corporate governance and organizational performance. Our findings reveal that board independence and education facilitate the development of succession planning, which is crucial in the family business’s life cycle.

The results of this study contribute to management succession, strategic management and leadership research by demonstrating how corporate governance fosters organizational performance through succession planning, thereby expanding the application scenarios of agency theory in family firms. Additionally, the article also enriches our understanding of how family businesses apply sound governance structures to promote organizational strategic decision-making during the succession process.

In the context of ongoing Israel-Palestine war, this study aims to explore whether consumer animosity (CA) influences individuals’ reluctance to purchase brands contributing towards the hostile nation. Furthermore, it investigates the mediating effects of product judgement (PJ), boycott motivation (BM) and boycott participation (BP) in this relationship. It also examines the moderating roles of susceptibility to subjective norms (SSN) and switching barriers (SB) in shaping their relationships with purchase aversion (PA).

Using existing validated scales, the authors designed and administered an online survey to collect 589 responses from India and Gulf Cooperation Council (GCC) countries. Using Smart PLS 4.0, the authors tested the hypothesized direct and indirect (mediated-moderated) relationships.

The findings reveal that in India, CA towards certain brands leads to negative evaluations, BM and BP. In GCC countries, it positively influences BM and BP. In general, SB subsides the influence of BM, PJ and BP on PA; however, SB has no moderating effects at all in the study.

Drawing upon the theory of planned behaviour, this paper offers novel insights into mediating and moderating roles of selected variables, namely, PJ, BM, BP, SSN and SB, in the direct relationship of CA and PA.

The purpose of this study was to understand the unique mental health concerns and access barriers experienced by South Asian Muslim youth populations living in the Peel Region of Toronto, Canada.

For this qualitative exploratory study, interviews (n = 15) were conducted with mental health professionals, educators and spiritual leaders (n = 11) who work with South Asian Muslim youth living in Peel Region, as well as with South Asian Muslim youth themselves (n = 4, aged 20–23). Interview transcripts were analyzed using reflexive thematic analysis.

Four primary themes emerged from the data: challenges and stressors, barriers, facilitators and hope and recovery. South Asian Muslim youth navigate a number of unique stressors related to the domains of culture, religion and family dynamics, as well as the impact of migration.

The findings stress the necessity of creating culturally safe, multilevel strategies to meet the nuanced challenges and diverse needs of South Asian Muslim youth communities.

This is one of the few papers to the knowledge that addresses the mental health needs and service access barriers of youth populations at the intersections of South Asian diasporic community belonging and Muslim faith in Canada.

Using and promoting green technologies in residential buildings might be a far more practical strategy for developing a sustainable built environment. The primary goal of this study is to examine homeowners' knowledge and awareness of the different green technologies and concepts that can be adopted to improve the quality of their homes.

The study employed a sequential mix technique methodology in order to accomplish its goal. A total of 156 respondents were chosen for a survey within the research areas using a simple random sample approach, while interviewees were chosen using a purposive sampling approach methodology. Descriptive and inferential statistics as well as content analysis were used to analyze the quantitative and qualitative data, respectively.

The findings indicate that homeowners have moderate knowledge of green technologies. It was also evident that print and electronic media are excellent at capturing and reaching a diverse range of homeowners interested in learning about sustainable development issues. Furthermore, the top three green technologies that most homeowners are aware of are using local materials over imported materials, grey water reclaiming and reuse technology and solar water heating technology. Subsequently, the homeowners in the three communities have differing opinions about the majority (82%) of the green technologies examined.

The findings will serve as a useful guide to assist practitioners and policymakers in implementing appropriate methods to integrate green technologies into housing projects and subsequently encourage their adoption.

This study aims to examine the factors that affect individuals’ intentions of participating in waqf-based crowdfunding model in Kuwait.

This study adopted the unified theory of acceptance and use of technology (UTAUT) model. The data were collected by online questionnaire survey based on 419 donors in waqf institutions in Kuwait. The data were analysed using the partial least squares structural equation modelling technique.

The results illustrate that performance expectancy, effort expectancy, social influence and facilitating condition positively affect behavioural intention towards waqf-based crowdfunding projects.

The paper presents an alternative source for waqf institutions to raise capital to develop waqf assets in majority and minority Muslim countries. The findings of this study hold significant implications for government officials and policymakers.

To the best of the authors’ knowledge, this paper is the first to explore waqf crowdfunding in Kuwait using the UTAUT model. There needs to be more research on waqf-giving behaviour in Kuwait, particularly concerning crowdfunding, which has become more popular recently. Thus, this paper aims to address this gap and contribute new insights to the field.

This paper aims to examine existing literature on halal food consumption from the perspective of consumer behaviour research. It identifies progress, current state and gaps and provides direction for future research to advance the field.

This paper reviewed papers from 2007 to 2023 using Scopus and WOS databases. The review used the Theories–Context–Characteristics–Methods (TCCM) framework and followed the scientific procedures and rationales for systematic literature reviews (SPAR-4-SLR) protocol.

The review summarises the methods, theory and approaches used in the topic and presents key findings and a proposed framework. It can guide future researchers in developing their models, making it a valuable starting point for future research. Despite the existence of SRL in halal food to the best of the authors’ knowledge, this work is the first review that proposes a model for halal food in consumer behaviour.

This review provides a twofold contribution. First, this review's theoretical contribution is advancing consumer behaviour literature on halal food. Second, this work's practical contribution is to enrich practitioners' understanding of the antecedents of consumer behaviour regarding halal food. This is the first review proposing a consumer behaviour model for Halal food. It makes a theoretical contribution to understanding consumer behaviour on Halal food and provides practical insights for practitioners.

In recent times, ternary hybrid nanofluid has garnered attention from scientist and researchers due to its improved thermal efficiency. This study aims to delve into the examination of ternary hybrid nanofluid (Al₂O₃–Cu–TiO₂/water), particularly concerning axisymmetric flow over a nonlinearly permeable stretching/shrinking disk. In addition, the investigation of convective boundary conditions and thermal radiation effects is also considered within the context of the described flow problem.

Mathematical formulations representing this problem are reduced into a set of ordinary differential equations (ODEs) using similarity transformation. The MATLAB boundary value problem solver is then used to solve the obtained set of ODEs. The impact of considered physical parameters such as suction parameter, radiation parameter, nonlinear parameter, nanoparticle volumetric concentration and Biot number on the flow profiles as well as the physical quantities is illustrated in graphical form.

The findings revealed the thermal flux for the nonlinearly shrinking disk is approximately 1.33%, significantly higher when compared to the linearly shrinking disk. Moreover, the existence of dual solutions attributed to the nonlinear stretching/shrinking disk is unveiled, with the first solution being identified as the stable and reliable solution through temporal stability analysis.

Understanding ternary hybrid nanofluid behavior and flow has applications in engineering, energy systems and materials research. This study may help develop and optimize nanofluid systems like heat exchangers and cooling systems.

The study of flow dynamics across nonlinear stretching/shrinking disk gains less attention compared to linear stretching/shrinking geometries. Many natural and industrial processes involve nonlinear changes in boundary shapes or sizes. Understanding flow dynamics over nonlinear shrinking/stretching disks is therefore essential for applications in various fields such as materials processing, biomedical engineering and environmental sciences. Hence, this study highlights the axisymmetric flow over a nonlinear stretching/shrinking disk using ternary hybrid nanofluid composed of alumina (Al₂O₃), copper (Cu) and titania (TiO₂). Besides, this study tackles a complex problem involving multiple factors such as suction, radiation and convective boundary conditions. Analyzing such complex systems can provide valuable insights into real-world phenomena where multiple factors interact.

Material extrusion (ME) is a low-cost additive manufacturing (AM) technique that is capable of producing metallic components using desktop 3D printers through a three-step printing, debinding and sintering process to obtain fully dense metallic parts. However, research on ME AM, specifically fused filament fabrication (FFF) of 316L SS, has mainly focused on improving densification and mechanical properties during the post-printing stage; sintering parameters. Therefore, this study aims to investigate the effect of varying processing parameters during the initial printing stage, specifically nozzle temperatures, T_n (190°C–300°C) on the relative density, porosity, microstructures and microhardness of FFF 3D printed 316L SS.

Cube samples (25 x 25 x 25 mm) are printed via a low-cost Artillery Sidewinder X1 3D printer using a 316L SS filament comprising of metal-polymer binder mix by varying nozzle temperatures from 190 to 300°C. All samples are subjected to thermal debinding and sintering processes. The relative density of the sintered parts is determined based on the Archimedes Principle. Microscopy and analytical methods are conducted to evaluate the microstructures and phase compositions. Vickers microhardness (HV) measurements are used to assess the mechanical property. Finally, the correlation between relative density, microstructures and hardness is also reported.

The results from this study suggest a suitable temperature range of 195°C–205°C for the successful printing of 316L SS green parts with high dimensional accuracy. On the other hand, T_n = 200°C yields the highest relative density (97.6%) and highest hardness (292HV) in the sintered part, owing to the lowest porosity content (<3%) and the combination of the finest average grain size (∼47 µm) and the presence of Cr23C6 precipitates. However, increasing T_n = 205°C results in increased porosity percentage and grain coarsening, thereby reducing the HV values. Overall, these outcomes suggest that the microstructures and properties of sintered 316L SS parts fabricated by FFF AM could be significantly influenced even by adjusting the processing parameters during the initial printing stage only.

This paper addresses the gap by investigating the impact of initial FFF 3D printing parameters, particularly nozzle temperature, on the microstructures and physical characteristics of sintered FFF 316L SS parts. This study provides an understanding of the correlation between nozzle temperature and various factors such as dimensional integrity, densification level, microstructure and hardness of the fabricated parts.

This study aims to identify the various economic and non-economic determinants of renewable energy consumption (REC) in Brazil, Russia, India, China and South Africa (BRICS). Due to the adverse effect of carbon emission on the environment, every country is trying for a transition from fossil fuel towards renewable energy. Renewable energy plays a crucial role in reducing carbon emission and combating climate change. Understanding the determinants that influence REC helps to promote this transition.

The study is based on an unbalanced panel data over the period 2002–2019 for all five BRICS nations. The panel corrected standard error (PCSE) method has been adopted to examine the determinants of REC.

Industrialization, population growth and foreign direct investment (FDI) are found to be significant economic determinants of REC while patent on environmental technologies, political instability and industrial design are significant non-economic determinants of REC in the BRICS nations.

The findings imply that to increase REC in BRICS nations, policymakers should incentivize industries for investments in renewable energy, attract FDI aligned with environmental regulations, raise population awareness through training, enforce industrial design standards, establish fair technology transfer frameworks to overcome patent barriers and create stable, long-term renewable energy policies with risk mitigation instruments to address political instability.

The study captures the effect of patents on environmental technologies and industrial design on the consumption of renewable energy. Thus, the novelty lies in investigating unexplored variables in the previous literature likely to affect REC.