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Thermophoresis deposition of particles is a crucial stage in the spread of microparticles over temperature gradients and is significant for aerosol and electrical technologies. To track changes in mass deposition, the effect of particle thermophoresis is therefore seen in a mixed convective flow of Williamson hybrid nanofluids upon a stretching/shrinking sheet.

The PDEs are transformed into ordinary differential equations (ODEs) using the similarity technique and then the bvp4c solver is employed for the altered transformed equations. The main factors influencing the heat, mass and flow profiles are displayed graphically.

The findings imply that the larger effects of the thermophoretic parameter cause the mass transfer rate to drop for both solutions. In addition, the suggested hybrid nanoparticles significantly increase the heat transfer rate in both outcomes. Hybrid nanoparticles work well for producing the most energy possible. They are essential in causing the flow to accelerate at a high pace.

The consistent results of this analysis have the potential to boost the competence of thermal energy systems.

It has not yet been attempted to incorporate hybrid nanofluids and thermophoretic particle deposition impact across a vertical stretching/shrinking sheet subject to double-diffusive mixed convection flow in a Williamson model. The numerical method has been validated by comparing the generated numerical results with the published work.

This study aims to assess the oxidative stability of avocado oil (AO) at various temperatures, using butylated hydroxytoluene (BHT) as an artificial antioxidant and different concentrations of ultrasonic extract of Chlorella vulgaris.

Extracts of C. vulgaris were obtained using four solvents: water, acetone, ethanol and 80% ethanol-aqueous. Standard techniques were used to conduct qualitative phytochemical screening of the extracts. The extracted samples were analyzed for total phenolics, total flavonoids, antioxidant activity and phenolic compound fractionation. Some physicochemical parameters of AO treated with various concentrations of C. vulgaris ultrasonic extract compared to a 200 ppm BHT and exposed to different temperatures were measured.

The highest phenolic, flavonoids content and antioxidant activity was achieved by 80% ethanolic extract of C. vulgaris . The results showed that exposure of AO to high temperatures led to significant changes in the oil's physicochemical properties. These changes increased as the temperature increased. On the other hand, adding 80% ethanolic extract of C. vulgaris into AO reduced the effect of heat treatment on the change in physicochemical properties.

Adding 80% ethanolic extract of C. vulgaris into AO can potentially reduce the impact of heat treatment on the alteration of physicochemical properties.

This study aims to find out how pomposia fruit powder (Syzygium cumini L.) mixed with roasted coffee (RCO) affected antioxidants, phytochemicals, lipid peroxidation inhibition and sensory attributes.

Pomposia fruits (Syzygium cumini L.) powder (PFP) was integrated with RCO at levels of 0.0%, 5.0%, 10.0%, 15.0% and 20.0%. RCO, PFP and binary mixtures containing RCO: PFP were evaluated for their total phenolics (TP), total flavonoids (TF), anthocyanin content (AC), antioxidant activity and phenolic compounds fractionation. The oxidative indices of coffee oil samples were measured throughout different storage intervals. Additionally, sensory characteristics of RCO enriched with different PFP doses were evaluated.

PFP samples exhibited the greatest TP content (1910 mg/100 g), whereas RCO samples had the lowest concentration (1090 mg/100 g). As more PFP was added, the corresponding coffee blends’ concentrations of TP, TF and AC were improved significantly. PFP possesses a radical-scavenging activity that is about 1.20 times more than RCO’s. DPPH (2,2-diphenyl-1-picrylhydrazyl) radical-scavenging activity jumped significantly from 74.13% in control (untreated) samples to 77.64%, 78.39% and 80.15% for samples enriched with 10.0%, 15.0% and 20% PFP, respectively. Significant increases in gallic acid, hesperidine, benzoic acid, chlorogenic acid, hispertin, catechol, quercetin, pyrogallol and rutin were detected when RCO was mixed with different quantities of PFP. At the end of storage trial, the coffee oil treated with 20% PFP had AV, PV and TBA values that were about 1.70, 1.95 and 1.66 times lower, respectively, than those of the control sample that had not had PFP addition. The RCO with 5.0% PFP achieved the greatest over acceptability grades.

To the best of the authors’ knowledge, this study was the first study to evaluate the effect of incorporating various level of pomposia fruit powder into RCO. The findings shows that adding different concentrations of pomposia fruit powder into RCO can indeed enhance the radical-scavenging activity of the coffee and potentially extend its shelf life.

The purpose of this study is to identify a critical pathway of the effect of big data analytics capabilities (BDACs) on strategic vigilance based on hierarchical process and a capability approach.

The researcher adopted a qualitative approach using interviews and a quantitative approach based on the interpretative structural modeling (ISM) fuzzy cross-impact matrix multiplication applied to classification (MICMAC) approach. A primary theoretical approach was also conducted to identify BDACs previously cited in the literature.

Four main subdivisions of BDACs were identified: management capabilities, infrastructure flexibility, talent capability and technology. Management capabilities followed by big data technical knowledge and associated with talent capabilities generate a flexible infrastructure to enhance SV. A dynamic capability perspective of knowledge and information is also required for SV.

Despite the opportunity of this research and the originality of results, some limitations have to be mentioned and can constitute further directives for future researchers, such as the problem of result generalization. First, this research was based in Saudi Arabia, and a comparative approach to defining BDAC on an international level can be more beneficial in providing an exhaustive list of these capabilities. Second, reliability issues, in this research can be addressed due to the use of qualitative data collection which is considered by many researchers as unspecified and can lack scientific rigor. Future studies can improve the number of interviews during the data collection process and data process using an advanced methodological approach. Third, the effect of BDAC in SV according to the hierarchical final modal is not quantified, future work can use this research model to appreciate each effect using a quantitative approach such as correlation and structural equation modeling while considering respondents with different profiles to take into account different point of view in this concern.

This research enriches the BDAC and MICMAC literature and contributes to this aspect in three main levels. First, by providing an additional empirical asset in this field, this study offers by the way a new case to the big data literature on the banking sector. Based on the limited knowledge as well as results collected from different databases and rigorously analyzed, this subject was not treated previously and the author could not find similar studies with the same approach dealing with the key BDACs in Saudi Arabia.

This research presents three main implications for policymakers and researchers interested in big data analytics (BDA) through a capability and strategic perspective. First, to attain SV, they should prioritize the development of interactive interfaces and open platforms as the primary step before collecting information and deconstructing it to guarantee the generation of knowledge and make decisions effectively. Second, policymakers must introduce organizational technologies in terms of technology management, technical knowledge and technology for decision-making. This requires simultaneous sharing and communication according to relational management. Third, the research conclusions have many critical managerial ramifications for banks in Saudi Arabia while considering the adoption of BDAC. The importance of BDACs (especially technical aspects) in shaping the decision-making to be strategically vigilant emphasizes policymakers’ orientation by paying close attention to these aspects and specific training programs to facilitate the use of such technologies and guarantee strong security measures. Moreover, findings support a balance between technical and functional BDAC.

The adoption of a knowledge-based dynamic capabilities (KBDCs) view to analyze the interaction between different BDACs in banks in Saudi Arabia to be strategically vigilant using a mixed approach.

In today’s intricate and dynamic construction sector, traditional project management techniques, which view projects in isolation, are no longer sufficient. Project Portfolio Management (PPM) has proven to be an efficient alternative solution for handling multiple construction projects. As such, based on a Machine Learning (ML) approach, this study aims to explore the Critical Success Factors (CSFs) influencing the adoption of PPM, aiming to enhance PPM implementation in construction projects.

A questionnaire based on CSFs gathered from prior studies was developed and validated by experts. Afterward, exploratory data analysis is conducted to understand CSF–PPM relationships. Preprocessing techniques ensure uniformity in variable magnitudes. Lastly, ML techniques, namely Linear Discriminant Analysis (LDA), Logistic Regression (LR) and Extra Trees Classifier (ETC) are developed to model and investigate CSFs' impact on PPM adoption.

The findings pointed out that the ETC model marginally outperforms other ML models with a classification accuracy of 93%. Also, the project size, utilized PPM tool and resource allocation-related factors are the most significant CSFs that influenced the PPM performance by about 48.5%.

This study contributes to the existing body of knowledge by raising awareness among construction companies and other project stakeholders about the pivotal CSFs that must be considered when prioritizing projects and designing an optimal PPM approach.

Despite the growing literature on business model innovation (BMI) and its implications for firm performance, the research on the antecedents of BMI is still at a budding stage. Therefore, the purpose of this paper is to bridge this gap by examining the causal relationships between knowledge management, BMI, competitive advantage, and firm performance.

A purposive sample of 300 micro, small, and medium enterprises was collected with more than 500 employees and total revenue between 50 and 500 million Indian Rupees, according to the Development Act, 2005. The collected data were analyzed using structural equation modeling through smart PLS 3.

The study’s findings show that knowledge management significantly influences BMI. This study also highlights the synergic impact of Knowledge management and BMI on firm performance. Furthermore, findings highlight the mediating role of competitive advantage in the relationship between knowledge management, BMI, and firm performance.

Understanding the impact of BMI and knowledge management is crucial for business owners, managers, and other stakeholders to plan for the continuous improvement of their businesses. Managers can secure a favorable position in the competitive market and improve organizational performance by paying attention to effectively managing their knowledge resources.

The study is one of the first few empirical efforts to investigate the causal relationships between knowledge management, BMI and firm performance. The study adds to the scant literature in this area by highlighting the mediating role of competitive advantage.

The purpose of this paper is to study the effects of sports sponsorship on brand equity using two managerially related outcomes: price premium and market share.

This study uses a best–worst discrete choice experiment (BWDCE) and compares the outcome with that of the purchase intention scale, an established probabilistic measure of purchase intention. The total sample consists of 409 fans of three soccer teams sponsored by three different competing brands: Nike, Adidas and Puma.

With sports sponsorship, fans were willing to pay more for the sponsor’s product, with the sponsoring brand obtaining the highest market share. Prominent brands generally performed better than less prominent brands. The best–worst scaling method was also 35% more accurate in predicting brand choice than a purchase intention scale.

Future research could use the same method to study other types of sponsors, such as title sponsors or other product categories.

Sponsorship managers can use this methodology to assess the return on investment in sponsorship engagement.

Prior sponsorship studies on brand equity tend to ignore market share or fans’ willingness to pay a price premium for a sponsor’s goods and services. However, these two measures are crucial in assessing the effectiveness of sponsorship. This study demonstrates how to conduct such an assessment using the BWDCE method. It provides a clearer picture of sponsorship in terms of its economic value, which is more managerially useful.

The research on corporate social responsibility (CSR) and firm performance (FP) has seen a surge over the years. However, the role of corporate reputation (CR), advertising strategy and market competition is still unclear. The purpose of this study is to consider this gap and test an integrative model of CSR-FP, in the context of India.

The data for CSR expenditure were collected from the annual reports of the selected companies. CR was captured using the ranks of Fortune India 500, Business Standard 1,000 and Economic Times 500. The financial data were collected from CMIE (Prowess) database.

Results of structural equation modeling (SEM) revealed a significant relationship between CSR expenditure of the firm and its reputation; but no relationship between CR and performance. When CR increases, the performance of a firm may not improve. Competitive intensity (CI) had no statistically significant role in the CR-FP relationship for performance. Results suggest that reputed firms perform well despite high competition within an industry. High reputation is effective in improving performance irrespective of competition. CI has a positive impact in the reputation–performance linkage. Advertising intensity (AI) played a significant moderating role in the CSR intensity and CR relationship.

This research represents an added value for the literature on CSR by highlighting the importance of CR, advertising strategy and market competition in the relationship between CSR and FP. The findings have several implications for theory and practice, which have been discussed in the study.

The purpose of this study is to identify the factors that influence the willingness of Saudi Arabian students from four universities in Saudi Arabia, to adopt learning management systems (LMSs). This will be accomplished by using two popular technology acceptance models unified theory of acceptance and use of technology (UTAUT) and theory of planned behavior (TPB).

In total, 445 undergraduates from four Saudi educational institutions participate in filling out the study questionnaire. To investigate the correlations between the variables, the study used structural equation modeling for data analysis.

The results of the study show that effort expectancy (EE), subjective norm (SN), attitude toward behavior (ATB) and perceived behavioral control (PBC) are found to be substantially connected with their intentions to use (ITU) LMSs. The findings also show that there is a strong relationship between students’ intentions and their actual use of LMSs.

Like many studies, this research has some limitations. The primary limitation is that the findings of the study cannot be extrapolated to other settings since the report’s analysis and investigation were limited to four Saudi universities. Therefore, to generalize the study’s findings, similar research needs to be conducted in other Gulf and similar cultural universities.

The integrated model identifies key factors that influence the intent of Saudi Arabian students to use LMS, including EEs, social influence, ATB and PBC. This model can help develop solutions for the obstacles that prevent students from using LMS. The findings can be used to provide assistance to increase the likelihood of LMS acceptance as part of the educational experience. The model may also inspire further research on this topic in the Gulf nations, particularly in Saudi Arabia.

As none of the relevant studies conducted previously in Saudi Arabia has integrated the two models to study the students’ ITU LMSs, this study combines two major theories, TPB and UTAUT, in the context of Saudi Arabia, contributing to the field of technology use in education by expanding empirical research and providing a thorough understanding of the challenges associated with the use of LMS in Saudi universities. This study should be viewed as filling a crucial gap in the field. Moreover, this integrated model, using more than one theoretical perspective, brings a thorough comprehension of the barriers that hinder students’ adoption of LMSs in the academic context in Saudi Arabia and thus assists in making effective decisions and reaching viable solutions.

This study aims to develop a framework that demonstrates the role of social capital in alleviating knowledge hiding behaviour in organisations while also considering the moderating roles of perceived organisational politics and the perceived value of knowledge in this process.

The authors conducted a systematic literature review of research papers on the topic of knowledge hiding to develop a framework for mitigating knowledge hiding.

This paper conceptualises social capital into three interrelated dimensions (e.g. structural, cognitive and relational). Based on the findings of the review, all the three social capital dimensions can potentially mitigate an individual’s propensity towards knowledge hiding. Additionally, the paper integrates two potential moderators: perceived organisational politics and perceived value of knowledge, which could undermine the outcomes of social capital in mitigating knowledge hiding.

Although the proposed framework may provide preliminary insights to practitioners and scholars, one of its key limitations is that it is conceptual. Future empirical research is needed to validate the proposed framework.

Existing research has focused on studying the antecedents and consequences of knowledge hiding. However, scant scholarly work explores how such behaviour can be mitigated. This paper addresses this gap and contributes to understanding how organisations can alleviate the prevalence of knowledge hiding by developing their social capital and by focusing on contextual factors.