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Quality assessment of textile products is of prime concern to intimately meet consumer demands. The dilemma faced by textile producers is to figure out the stability among quality criteria and efficiently deal with target specifications. Hence, the basic devotion is to attain the optimum value product which entirely satisfies the views and perceptions of consumers. Selection of best fabric among several alternatives in the presence of contradictory measures is a disputing problem in multicriteria decision-making.

In the current study, the analytic hierarchy process (AHP) and preference ranking organization method for enrichment evaluation (PROMETHEE) are proficiently used to solve the problem in selection of branded woven shawls. AHP method verifies comparative weights of the criteria selection, while the ranking of fabric alternatives grounded on specific net-outranking flows is executed through PROMETHEE II method.

The collective AHP and PROMETHEE approaches are applied for the useful accomplishment of grading of branded shawls based on multicriteria weights, used for effective selection of fabric materials in the textile market.

In the apparel industry, fabric and garment manufacturers often rely on hit-and-trial methods, leading to significant wastage of valuable resources and time, in achieving the desirable fabric qualities. The implementation of the findings can assist apparel manufacturers in streamlining their fabric selection processes based on multiple criteria. By adopting this method, industry players can make informed decisions, ensuring a balance between quality standards and consumer expectations, thereby enhancing both product value and market competitiveness.

The methods of Visual PROMETHEE and AHP are assimilated to offer a complete method for the selection and grading of fabrics with reference to multiple selection criteria.

Physical activity is an eminent practice for the maintenance of physical and mental health. Physical fitness always enables students to perform their various tasks efficiently specifically in academic performance. Student health is a principal factor for the performance of all kinds of activities particularly in academic performance. This study aimed to evaluate physical activity among university students and the factors for being inactive.

A questionnaire was designed and distributed among the students via WhatsApp, Skype and email, however, some responses were collected physically to maintain the quality of data. The questionnaire was categorized into demographic factors, current physical activity status and reasons for physical inactivity. Each section was further divided into questions and total 24 questions were asked from each individual for evaluation of inactiveness.

The finding of this research explored that enormous number of students are doing part time jobs and unable to find enough time for relaxation. The research was limited and evaluated limited factors and explored that 60.6% of students had less time for entertainment and this is only 2 h for this 60.6% of students. Among all factors of physical activity walking was preferable for 48.34% of the students. Students want to participate in healthy activities. Moreover, students are unable to perform physical exercise due to busy schedules of jobs (47.02%), part-time job burden (15.89%), study burden (35.10%) and poor health conditions (1.32%).

This study concluded that higher percentage of students have stress of limited resources and under this stress condition they are unable to take a balanced diet which they considered cost-effective. They did not perform maximum in their academic and daily activities and did not participate in sports activities. It was also observed that institutions did not provide a sufficient platform for physical activity for students. The research shows the factors which affect the student’s academic performance as being physically inactive. Evaluation of results explored that numerous students have limited resources during their career development and their attention remain diverted to overcome their limited resources which keep them physically unfit. The findings also explored that physically inactive students have heavy study and job burden which is not overcome and analyzed by their institutions.

This paper aims to explore the value of geographic diversification in the context of deglobalization, drawing evidence from a quasi-natural experiment – the Brexit referendum that took place on 23 June 2016 in the UK.

This study applies an event study methodology to estimate the impact of the Brexit vote on a cross-section of firms with varying levels of geographic diversification – undiversified UK firms, UK firms with significant operations in the European Union (EU) and globally diversified UK firms. This study deploys a Heckman two-stage regression approach to address sample selection bias.

This study finds that undiversified UK firms experienced negative cumulative abnormal returns (CARs) around the Brexit referendum. The value of UK firms with majority sales within the UK declined by 0.9 percentage points, on average, in the three days centred on the Brexit referendum. In contrast, UK firms that are globally diversified, with the majority of sales within the EU are unaffected, while diversified firms in the rest of the world generated positive CARs of 1.8 percentage points over the same period. These results are robust to firm characteristics, selection bias and alternative measures of CARs and diversification.

This study is subject to some limitations that open avenues for future work. There are a few available proxies of diversification and further work on developing other proxies is much needed. Further work may also examine the long-term impact of diversification on UK firms. This study considered Brexit as a quasi-natural experiment, and this study could be applied to other deglobalization events like COVID-19 and can enhance the generalizability of diversification strategy in the deglobalized world. Findings may stimulate future work to explore how another form of diversification – product diversification has affected firm returns around Brexit. Finally, this study has focused on the UK as its base case. It may be interesting to corroborate the findings by exploring the impact of Brexit on European firms, who hitherto Brexit, had some operations in the UK.

This work offers some insights for policymakers and regulators around the impact of deglobalization on local firms. Findings suggest that these trends significantly negatively impact the most vulnerable firms (smaller firms with less global reach), while their larger counterparts with significant global reach might be insulated. This finding is important for determining the nature of support needed by different firms in times of deglobalization. The work also offers insights to managers of firms operating in countries where there are real prospects of deglobalization. Specifically, the work highlights the importance of geographic diversification when free movement of goods, services and people is restricted.

This study shows that a certain group of globally diversified firms earned significantly higher returns from the prospect of the UK leaving the EU, thereby highlighting the value of geographic diversification in a time of deglobalization.

This study proposes a novel measure for management’s horizon (short-termism or myopia vs long-termism or hyperopia) derived from easily obtainable firm-level accounting and stock market performance data. The authors use the measure to explore the impact of managements’ horizon on firms’ investment efficiency.

The authors rely on two commonly used but uncorrelated measures of management performance: accounting performance (return on capital employed, ROCE) and stock market performance (average abnormal return, AAR). The authors combine these measures to develop a multidimensional framework for performance, which classifies firms into four groups: efficient (high accounting and high market performance), poor (low accounting and low market performance), myopic (high accounting and low market performance) and hyperopic (low accounting and high market performance). The authors validate this framework and deploy it to explore the relationship between horizon and firms’ investment efficiency.

In validation tests, the authors show that management myopia (hyperopia) explains firms’ decision to cut (grow) research and development investments. Further, as expected, myopic (hyperopic) firms are associated with significantly more (less) accrual and real earnings management. The empirical tests on the link between horizon and investment efficiency suggest that myopic managers cut new investments while their hyperopic counterparts grow the same. Ultimately, the authors find that myopia (hyperopia) exacerbates(mitigates) the over-investment of free cash flow problem.

The authors introduce a framework for assessing management’s horizon using easily obtainable measures of performance. The framework explains inconsistencies in prior empirical research using different measures of performance (accounting versus market). The authors demonstrate its utility by showing that the measure explains decisions around research and development investment, earnings management and firm investments.

This study aims to investigate how the management of supply chain information impacts the performance of the supply chain. This relationship is explored by considering the mediating influence of internal and external integration, which is underpinned by the principles of resource-based theory.

Data was collected from 144 supply chain professionals across different manufacturing companies. The proposed hypotheses were subjected to quantitative analysis using partial least squares structural equation modeling, and the validity of the measurement model was assessed with the assistance of SmartPLS software.

This study identified that information management (IM) significantly and positively affects internal integration (II), customer integration (CI) and supply chain performance (SCP). Similarly, the results showed that II significantly and positively affects SCP. Likewise, CI positively and significantly affected SCP. At the same time, II found a positive yet significant mediating role in the relationship between IM and SCP. CI was found to play a positive but insignificant mediating role in the relationship between IM and SCP.

This research evaluated a second-order model and tested the SCP in conjunction with the resource-based view in the manufacturing industry. This research could be beneficial for researchers, manufacturers and policymakers to attain organizational objectives by implementing an efficient IM system for better integration and SCP.

This article identifies hybrid nanofluids and industrial thermal engineering devices as significant sources of solar energy. In this study, various nanoparticles suspended in base fluids such as water (H2O) and carboxymethyl cellulose (CMC), along with nanoparticles like graphene oxide (GO) and molybdenum disulfide (MoS2), are examined. The model also incorporates permeability and the effects of angled magnetic fields to provide a comprehensive analysis.

We have utilized the fractal fractional operator definition, the quickest and most advanced fractional approach, to address the problems with the hybrid nanofluid suspension. The integral transform scheme, i.e. the Laplace transform, converts the governing equations into a fractional form before various numerical methods are applied to solve the problem. Further, some numerical schemes to address the Laplace inverse are also utilized.

The fractional effects on flow rate and heat transfer are evident at varying time intervals. Consequently, we conclude that as the fractal constraints increase, the momentum and heat profiles decelerate. Furthermore, all necessary conditions are satisfied, resulting in the momentum and temperature fields decreasing near the plate and increasing over time. Additionally, the water-based (H2O + Go + MoS2) solution exhibits a more pronounced impact compared to the CMC-based (CMC + Go + MoS2) hybrid suspension.

The findings could be very useful in enhancing the efficiency of thermal systems. These findings align more accurately with conventional solutions and can be used to build and optimize various heat management strategies.

The primary goals of this research are to examine the thermal and flow properties of hybrid nanofluids for manufacturing purposes of thermal engineering equipment utilizing fractal fractional definition. Further, to improve thermal system productivity by applying sophisticated fractional techniques to better and maximize heat and momentum transmission in these hybrid nanofluid solutions

Artificial Intelligence (AI)-powered technologies are revolutionising the landscape of education, ushering in a myriad of possibilities and challenges. This article delves into the dual nature of AI-driven tools in education, spotlighting pivotal advancements like automated grading, personalised learning algorithms, online monitoring, content filtering, AI-based learning tools, Chat Generative Pre-trained Transformer (ChatGPT) and standardised testing (ST) platforms. Ultimately, the examination reveals a spectrum of advantages, risks and considerations associated with AI-driven educational applications. Employing the PRISMA protocol, this study systematically reviews peer-reviewed literature concerning the implementation and ethical implications of AI in higher education. The analysis incorporates 36 scholarly articles, uncovering the entrepreneurial advantages of AI, such as tailored learning experiences, self-assessment opportunities, heightened efficiency, skill enhancement and reduced educational disparities. Concurrently, the research identifies potential hazards, including user profiling, plagiarism, academic integrity breaches and excessive reliance on technology that may hinder creative learning dynamics. Crucial concerns emerge, encompassing the possible devaluation of educators' roles, privacy issues inherent in personalised learning platforms and the intrusive nature of online surveillance. Additionally, the study highlights biases embedded within AI algorithms and apprehensions regarding job displacement within the academic community. To steer AI integration responsibly within higher education, the investigation explores ethical frameworks and models, offering pragmatic suggestions for institutions. Recommendations advocate for a balanced approach, emphasising judicious AI utilisation and the formulation of institutional policies. This chapter's distinctiveness lies in its innovative stance, striving to reconcile the technical and entrepreneurial benefits of AI applications with the preservation of creativity in higher education contexts.

The main focus is to provide a non-similar solution for the magnetohydrodynamic (MHD) flow of Casson fluid over a curved stretching surface through the novel technique of the artificial intelligence (AI)-based Lavenberg–Marquardt scheme of an artificial neural network (ANN). The effects of joule heating, viscous dissipation and non-linear thermal radiation are discussed in relation to the thermal behavior of Casson fluid.

The non-linear coupled boundary layer equations are transformed into a non-linear dimensionless Partial Differential Equation (PDE) by using a non-similar transformation. The local non-similar technique is utilized to truncate the non-similar dimensionless system up to 2nd order, which is treated as coupled ordinary differential equations (ODEs). The coupled system of ODEs is solved numerically via bvp4c. The data sets are constructed numerically and then implemented by the ANN.

The results indicate that the non-linear radiation parameter increases the fluid temperature. The Casson parameter reduces the fluid velocity as well as the temperature. The mean squared error (MSE), regression plot, error histogram, error analysis of skin friction, and local Nusselt number are presented. Furthermore, the regression values of skin friction and local Nusselt number are obtained as 0.99993 and 0.99997, respectively. The ANN predicted values of skin friction and the local Nusselt number show stability and convergence with high accuracy.

AI-based ANNs have not been applied to non-similar solutions of curved stretching surfaces with Casson fluid model, with viscous dissipation. Moreover, the authors of this study employed Levenberg–Marquardt supervised learning to investigate the non-similar solution of the MHD Casson fluid model over a curved stretching surface with non-linear thermal radiation and joule heating. The governing boundary layer equations are transformed into a non-linear, dimensionless PDE by using a non-similar transformation. The local non-similar technique is utilized to truncate the non-similar dimensionless system up to 2nd order, which is treated as coupled ODEs. The coupled system of ODEs is solved numerically via bvp4c. The data sets are constructed numerically and then implemented by the ANN.

The present research investigates the effects of green supply chain management (GSCM) practices on customer behavioural intentions (e.g. word of mouth [WOM], willingness to pay [WTP] and revisit intention [RI]) and the mediating role of customer satisfaction (CS) in the hospitality industry in Bangladesh.

The authors applied a convenience sampling approach to distribute questionnaires and collect opinions from 404 customers who stayed in Bangladesh's five- and four-star hotels. SmartPLS was applied to examine the proposed hypothesised model.

GSCM practices have positive and significant impacts on CS and behavioural intentions of customers' WOM, WTP and RI. Additionally, CS mediates the association between GSCM practices and three behavioural intentions.

To boost their hotel's financial performance, hoteliers should allocate more resources to improving environmental sustainability practices in supply chain management.

This study's novel contribution to the literature rests in the findings regarding the mediating effect of CS. This adds value to the theory of planned behaviour. Another unique contribution of this study is that it combines three behavioural intentions (willingness to pay, RI and WOM).