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This study’s objectives are twofold; first, this paper aims to explore the determinants of perceived benefit and perceived risk of Islamic Fintech. Second, this study examines the influence of perceived benefit, perceived risk and user trust on the intention to adopt Islamic Fintech.

The sample of 350 was distributed among the respondents, while a usable sample of 321 was retained for the analysis. The study performed a self-administration survey to collect the sample data while the hypothesized model was tested using SmartPLS.

The results revealed that perceived benefit and perceived risk were significant and positively influenced by their factors. Moreover, perceived benefits showed a positive and significant impact on trust. However, perceived risk had a negative and significant impact on trust. The results also found a strong positive and significant relationship between trust and intention to adopt Islamic Fintech.

The outcome of this research may be used to develop strategies for Fintech and enables the financial sector to attain economies of scale in the world.

The purpose of this study is to investigate the impact of post content, post media and post scheduling strategies on online engagement on Twitter in context of micro celebrities in Pakistan.

For this research, micro celebrities of Pakistan have been defined as the target population. Secondary data consisting of 464 tweets from walls of six micro celebrities belonging to both genders and diverse set of socio-political fields was collected. Tweedie estimation analysis was run to accept or reject the hypotheses. Mean values with standard deviations were utilized to analyze the different engagement patterns of dichotomous variables (content type, content language, mentions, hashtags, text, images, links, videos, hour of the day and day of the week) on online engagement.

Content type, content language, content length, hashtags, mentions, images, links, videos, hour of the day and day of the week have been found to have a significant relationship with online engagement on Twitter.

First, the study has been conducted in context of micro celebrities on Twitter. It did not include influencers on other social media networks. Second, study considered only quantitative aspects of engagement based on secondary data ignoring qualitative aspects of phenomenon due to time and methodology constraints. Third, study did not include link clicks as a measure of engagement as clicks data is not publicly available on the posts.

The study contributes significantly to find out valuable “micro celebrity” strategies in Pakistan. The study suggests micro celebrities to tweet soft content in Urdu language along with relevant hashtags and mentions to get higher engagement on their tweets. Further, tweets should contain maximum number of characters. Micro celebrities should not insert images, links and videos in their tweets as these media types result in lower engagement on Twitter. Micro celebrities should tweet at low hours and weekends.

As this study focuses on investigation of better engagement practices for micro celebrities, it will help general public to express themselves more effectively through social media.

First, this is the first study that investigates the online engagement model for micro celebrities. Second, the online engagement model designed in this study has yet not been investigated to best of our knowledge. The theoretical model combines multiple engagement factors discussed in previous studies conducted on Facebook, YouTube, Instagram and Twitter.

Employees with high career competencies are more successful in career development. However, it is unclear whether proactivity matters for early-career employees. Thus, this study aims to investigate the influence of career competencies and proactive personality on career adaptability and the moderating role of proactive personality in this relationship.

This study adopts a quantitative methodology, collecting data through online questionnaires from respondents (n = 400) who had less than five years of work experience in the UAE. A measurement model and hypotheses testing were conducted using AMOS software. Multigroup structural equation modelling was used to test the moderation model.

The results show a direct relationship between career competencies and career adaptability. However, a proactive personality is insignificantly related to career adaptability. Further, early-career employees with low proactive personality benefit from high career competencies.

This study offers contributions to the emerging understanding of career construction by emphasising the important role of career competencies for early-career employees who manifest a low proactive personality.

This study aims to compare the effects of YouTube information sources (influencer vs word of mouse) on the consumer purchase decision. This paper extends the information adoption model (IAM) to include information language as a central cue and skepticism toward online information as a moderating factor.

A between-subjects experiment, 2 (influencer vs word of mouse) × 2 (positive vs negative information), was designed to test hypotheses. A total of 171 consumers participated in the experiment and multigroup structural equations modeling (AMOS 21) was applied.

The results indicate that consumers perceive argument quality to be more useful when the information comes from word of mouse (WOMS). While information language was deemed more useful when the information source was a YouTube influencer and the information type was positive. The study also found that skepticism toward online information reduced the overall effects, particularly for influencers and positive information.

This study contributes to the theory by identifying and investigating the existing gaps in knowledge. For practitioners, findings speak to the synergetic power of YouTube influencers and WOMS as an effective marketing strategy.

This paper is one of the first to compare the effects of YouTube influencers and consumer comments by using the IAM. It also extends IAM with the inclusion of information language as a central cue and skepticism toward online information as a moderating factor.

This paper aims to investigate the thermal performance of equivalent square and circular thermal systems and compare the heat transport and irreversibility of magnetohydrodynamic (MHD) nanofluid flow within these systems.

The research uses a constraint-based approach to analyze the impact of geometric shapes on heat transfer and irreversibility. Two equivalent systems, a square cavity and a circular cavity, are examined, considering identical heating/cooling lengths and fluid flow volume. The analysis includes parameters such as magnetic field strength, nanoparticle concentration and accompanying irreversibility.

This study reveals that circular geometry outperforms square geometry in terms of heat flow, fluid flow and heat transfer. The equivalent circular thermal system is more efficient, with heat transfer enhancements of approximately 17.7%. The corresponding irreversibility production rate is also higher, which is up to 17.6%. The total irreversibility production increases with Ra and decreases with a rise in Ha. However, the effect of magnetic field orientation (γ) on total EG is minor.

Further research can explore additional geometric shapes, orientations and boundary conditions to expand the understanding of thermal performance in different configurations. Experimental validation can also complement the numerical analysis presented in this study.

This research introduces a constraint-based approach for evaluating heat transport and irreversibility in MHD nanofluid flow within square and circular thermal systems. The comparison of equivalent geometries and the consideration of constraint-based analysis contribute to the originality and value of this work. The findings provide insights for designing optimal thermal systems and advancing MHD nanofluid flow control mechanisms, offering potential for improved efficiency in various applications.

This study aims to shed light on the experience of the United Arab Emirates (UAE) in balancing three main pillars: the environmental criteria, the reduction of CO₂ emissions and the economic growth. Based on the environmental Kuznets curve (EKC) framework, it will assess the causal relationship between economic indicators such as gross domestic product (GDP) per capita, trade openness and energy use and environmental indicators such as CO₂ emissions.

The analysis relies on a period of 40 years (1981–2020) where data is extracted from the World Bank database. This study uses the unit root test for time series stationarity, the optimal lag length test, the “Johansen” test for co-integration and the vector error correction model.

The paper concludes to two major findings. On a short-term basis, CO₂ emissions and economic indicators are negatively correlated, whereas on a long-term basis, there is no association between CO₂ emissions and economic indicators in the UAE.

The research ends with important recommendations. It illustrates the importance of rationalizing the use of primary resources and the necessity to embrace successful and efficient policies in the energy production.

More specifically, UAE is urged to address the problem of CO₂ emissions in the electricity sector and increase awareness of the use of environmentally friendly processes in the transport and industrial sectors. While setting their economic agendas, UAE are encouraged to meet environmental criteria and invest in renewable energy projects such as “Shams 1”, the largest solar power plant outside of Spain and the USA.

The current study is significant in its research on the environmental impact of economic development, trade openness and energy use policies in the UAE. It uses CO₂ emissions as an environmental proxy and evaluates the environmental policies adopted in the UAE to reduce its impact.

The purpose of this paper is to solve the maintenance management problems of generating units under the reliability criterion.

The problem has been formulated as a combinatorial optimization task, with explicit and simultaneous treatment of multiple objectives: maximization of reliability, minimization of fuel costs and minimization of constraint violations. This paper formulates a general generator maintenance management (GMM) problem using a reliability criterion and a novel bio‐inspired search technique, namely, artificial bee colony (ABC) algorithm is applied to determine the optimal generator maintenance schedule.

A novel meta‐heuristic search technique based algorithm has been developed to determine the optimal maintenance schedule of generating units to improve the system reliability.

The contribution of the paper is that an efficient bio‐inspired algorithm based solution technique has been developed to solve a very important problem for a power utility, i.e. the economical and reliable operation of a power system.

Several graphs, streamlines, isotherms and 3D plots are illustrated to enlighten the noteworthy fallouts of the investigation. Embedding flow factors for velocity, induced magnetic field and temperature have been determined using parametric analysis.

Ternary hybrid nanofluids has outstanding hydrothermal performance compared to classical mono nanofluids and hybrid nanofluids owing to the presence of triple tiny metallic particles. Ternary hybrid nanofluids are considered as most promising candidates in solar energy, heat exchangers, electronics cooling, automotive cooling, nuclear reactors, automobile, aerospace, biomedical devices, food processing etc. In this work, a ternary hybrid nanofluid flow that contains metallic nanoparticles over a wedge under the prevalence of solar radiating heat, induced magnetic field and the shape factor of nanoparticles is considered. A ternary hybrid nanofluid is synthesized by dispersing iron oxide (Fe3O4), silver (Ag) and magnesium oxide (MgO) nanoparticles in a water (H₂O) base fluid. By employing similarity transformations, we can convert the governing equations into ordinary differential equations and then solve numerically by using the Runge–Kutta–Fehlberg approach.

There is no fund for the research work.

This kind of study may be used to improve the performance of solar collectors, solar energy and solar cells.

This investigation unfolds the hydrothermal changes of radiative water-based Fe₃O₄-Ag-MgO-H₂O ternary hybrid nanofluidic transport past a static and moving wedge in the presence of solar radiating heating and induced magnetic fields. The shape factor of nanoparticles has been considered in this study.

Cross-layer approach in media access control (MAC) layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in wireless sensor network (WSN) and Internet of Things (IoT) applications. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes. Game theory optimization for distributed may increase the network performance. The purpose of this study is to survey the various operations that can be carried out using distributive and adaptive MAC protocol. Hill climbing distributed MAC does not need a central coordination system and location-based transmission with neighbor awareness reduces transmission power.

Distributed MAC in wireless networks is used to address the challenges like network lifetime, reduced energy consumption and for improving delay performance. In this paper, a survey is made on various cooperative communications in MAC protocols, optimization techniques used to improve MAC performance in various applications and mathematical approaches involved in game theory optimization for MAC protocol.

Spatial reuse of channel improved by 3%–29%, and multichannel improves throughput by 8% using distributed MAC protocol. Nash equilibrium is found to perform well, which focuses on energy utility in the network by individual players. Fuzzy logic improves channel selection by 17% and secondary users’ involvement by 8%. Cross-layer approach in MAC layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in WSN and IoT applications. Cross-layer and cooperative communication give energy savings of 27% and reduces hop distance by 4.7%. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes.

Other optimization techniques can be applied for WSN to analyze the performance.

Game theory optimization for distributed may increase the network performance. Optimal cuckoo search improves throughput by 90% and reduces delay by 91%. Stochastic approaches detect 80% attacks even in 90% malicious nodes.

Channel allocations in centralized or static manner must be based on traffic demands whether dynamic traffic or fluctuated traffic. Usage of multimedia devices also increased which in turn increased the demand for high throughput. Cochannel interference keep on changing or mitigations occur which can be handled by proper resource allocations. Network survival is by efficient usage of valid patis in the network by avoiding transmission failures and time slots’ effective usage.

Literature survey is carried out to find the methods which give better performance.