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To improve the thermal performance of base fluid, nanoparticles of three types are dispersed in the base fluid. A novel theory of non-Fourier heat transfer is used for design and development of models. The thermal performance of sample fluids is compared to determine which types of combination of nanoparticles are the best for an optimized enhancement in thermal performance of fluids. This article aims to: (i) investigate the impact of nanoparticles on thermal performance; and (ii) implement the Galerkin finite element method (GFEM) to thermal problems.

The mathematical models are developed using novel non-Fourier heat flux theory, conservation laws of computational fluid dynamics (CFD) and no-slip thermal boundary conditions. The models are approximated using thermal boundary layer approximations, and transformed models are solved numerically using GFEM. A grid-sensitivity test is performed. The accuracy, correction and stability of solutions is ensured. The numerical method adopted for the calculations is validated with published data. Quantities of engineering interest, i.e. wall shear stress, wall mass flow rate and wall heat flux, are calculated and examined versus emerging rheological parameters and thermal relaxation time.

The thermal relaxation time measures the ability of a fluid to restore its original thermal state, called thermal equilibrium and therefore, simulations have shown that the thermal relaxation time associated with a mono nanofluid has the most substantial effect on the temperature of fluid, whereas a ternary nanofluid has the smallest thermal relaxation time. A ternary nanofluid has a wider thermal boundary thickness in comparison with base and di- and mono nanofluids. The wall heat flux (in the case of the ternary nanofluids) has the most significant value compared with the wall shear stresses for the mono and hybrid nanofluids. The wall heat and mass fluxes have the highest values for the case of non-Fourier heat and mass diffusion compared to the case of Fourier heat and mass transfer.

An extensive literature review reveals that no study has considered thermal and concentration memory effects on transport mechanisms in fluids of cross-rheological liquid using novel theory of heat and mass [presented by Cattaneo (Cattaneo, 1958) and Christov (Christov, 2009)] so far. Moreover, the finite element method for coupled and nonlinear CFD problems has not been implemented so far. To the best of the authors’ knowledge for the first time, the dynamics of wall heat flow rate and mass flow rate under simultaneous effects of thermal and solute relaxation times, Ohmic dissipation and first-order chemical reactions are studied.

Brand crowdfunding, launched through brands’ social media platforms, can provide a myriad of crowdfunding and branding benefits, such as strengthening brands’ social networks, validating product launches, generating mass exposure and enabling cocreation. Gamification positions brand crowdfunding as an exciting and joyful activity that more deeply engages prosumers. Anchored on resource-based theory, theory of planned behavior and service-dominant logic, this paper aims to develop a brand crowdfunding framework for established brands with insights from two emerging markets: China and India.

A deductive cross-sectional design is used to gather data from an established brand’s (e.g. Xiaomi) social media followers in China (n = 826) and India (n = 358), which is analyzed through PLSc-SEM.

The results reveal that social media brand engagement is an antecedent of brand crowdfunding participation, brand crowdfunding intention is a predictor of brand loyalty and gamification is a significant moderator in technology-oriented societies.

The paper develops a brand crowdfunding framework that provides insights on how established brands can leverage crowdfunding to enhance their new product development process. The results contribute to the social media brand engagement, crowdfunding, gamification and emerging markets literature.

This research studies a location-allocation problem considering the m/m/m/k queue model in the blood supply chain network. This supply chain includes three levels of suppliers or donors, main blood centers (laboratories for separation, storage and distribution centers) and demand centers (hospitals and private clinics). Moreover, the proposed model is a multi-objective model including minimizing the total cost of the blood supply chain (the cost of unmet demand and inventory spoilage, the cost of transport between collection centers and the main centers of blood), minimizing the waiting time of donors in blood donating mobile centers, and minimizing the establishment of mobile centers in potential places.

Since the problem is multi-objective and NP-Hard, the heuristic algorithm NSGA-II is proposed for Pareto solutions and then the estimation of the parameters of the algorithm is described using the design of experiments. According to the review of the previous research, there are a few pieces of research in the blood supply chain in the field of design queue models and there were few works that tried to use these concepts for designing the blood supply chain networks. Also, in former research, the uncertainty in the number of donors, and also the importance of blood donors has not been considered.

A novel mathematical model guided by the theory of linear programming has been proposed that can help health-care administrators in optimizing the blood supply chain networks.

By building upon solid literature and theory, the current study proposes a novel model for improving the supply chain of blood.

The purpose of this study is to analyze the transportation of heat and mass in three-dimensional (3D) shear rate-dependent viscous fluid. Thermal enhancement plays a significant role in industrial and engineering applications. For this, the authors dispersed trihybrid nanoparticles into the fluid to enhance the working fluid’s thermal enhancement.

The finite element method is a numerical scheme and is powerful in achieving convergent and grid-independent solutions compared with other numerical techniques. This method was initially assigned to structural problems. However, it is equally successful for computational fluid dynamics problems.

Wall shear stress has shown an increasing behavior as the intensity of the magnetic field is increased. Simulations have predicted that Ohmic heat in the case of trihybrid nanofluid (MoS₂–Al₂O₃–Cu/C₂H₆O₂) has the greatest value in comparison with mono and hybrid nanofluids. The most significant influence of chemical reaction on the concentration in tri-nanofluid is noted. This observation is pointed out for both types of chemical reaction (destructive or generative) parameters.

Through a literature survey, the authors analyzed that no one has yet to work on a 3D magnetohydrodynamics Carreau–Yasuda trihybrid nanofluid over a stretched sheet for improving heat and mass transfer over hybrid nanofluids. Herein, molybdenum disulfide (MoS₂), aluminum oxide (Al₂O₃) and copper (Cu) nanoparticles are mixed in ethylene glycol (C₂H₆O₂) to study the thermal enhancement and mass transport of their corresponding resultant mono (Cu/C₂H₆O₂), hybrid (Al₂O₃–Cu/C₂H₆O₂) and trihybrid (MoS₂–Al₂O₃–Cu/C₂H₆O₂) nanofluids.

As our world becomes increasingly more technology driven and global competition continues to intensify, the technology resource components available to a firm will be required to become more sophisticated in order to achieve and maintain a competitive advantage. Higher levels of sophistication are achieved through technological innovation that is effectively managed. But, to effectively manage technological innovation, we must first come to a clearer understanding of the resource components of technology. This paper describes the way various people perceive the meaning of technology, discusses the confusion that exists, and suggests a construct for classifying the components of technology to mitigate the confusion. Finally, a framework for benchmarking and technology assessment is presented to suggest a way for a firm to better manage its technology component sophistication level for global competition.

The quality of construction projects is mainly dependent on the process quality during the construction phase than product quality. The key factors that influence the process quality of building projects in Pakistan during the construction phase of building life cycle are evaluated from literature. This paper aims to discuss these issues.

The factors were ranked using the traditional relative importance index (RII) and the second synthetic grey relational analysis method. The findings indicate that during the construction phase the selection of an appropriate contractor is the most important factor. The existence of feedback system and quality of shop drawings received from subcontractors are also very significant factors, according to the grey relational model.

Measures for the improvement of process quality in Pakistan are suggested. The results from both methods are not entirely comparable; however, if one considers uncertainty in data, then the second synthetic GRA-based ranking should be preferred over RII in decision making.

The study is pioneer in the evaluation of key factors influencing process quality during building construction projects in Pakistan using a set of traditional and novel methods. The results of this study are significant in improving the process quality during different phases of construction.

Twitter users’ generated data, known as tweets, are now not only used for communication and opinion sharing, but they are considered an important source of trendsetting, future prediction, recommendation systems and marketing. Using network features in tweet modeling and applying data mining and deep learning techniques on tweets is gaining more and more interest.

In this paper, user interests are discovered from Twitter Trends using a modeling approach that uses network-based text data (tweets). First, the popular trends are collected and stored in separate documents. These data are then pre-processed, followed by their labeling in respective categories. Data are then modeled and user interest for each Trending topic is calculated by considering positive tweets in that trend, average retweet and favorite count.

The proposed approach can be used to infer users’ topics of interest on Twitter and to categorize them. Support vector machine can be used for training and validation purposes. Positive tweets can be further analyzed to find user posting patterns. There is a positive correlation between tweets and Google data.

The results can be used in the development of information filtering and prediction systems, especially in personalized recommendation systems.

Twitter microblogging platform offers content posting and sharing to billions of internet users worldwide. Therefore, this work has significant socioeconomic impacts.

This study guides on how Twitter network structure features can be exploited in discovering user interests using tweets. Further, positive correlation of Twitter Trends with Google Trends is reported, which validates the correctness of the authors’ approach.

It is no longer enough to have a technology base to meet customer needs. The competitiveness of the tourism sector is ensured through the innovation capacity that companies can achieve, either through innovation associated with services or through services. The relationship between tourism innovation and business competitiveness in the tourism sector must consider emerging and innovative technologies that appear daily in society. In this context, the information systems applied to tourism must take into consideration the various sectors of activity: accommodation, travel agencies, restaurants and gastronomy, tourist entertainment, transport, among others. In addition to tourism management information system, it must integrate an innovation mechanism, which should be based on the definition of an appropriate business model. The business model that ensures innovation has to integrate design, production, service, and marketing through a new customer relationship, therefore technology must be able to meet the demands inherent in this new model. The purpose of this chapter is to investigate how the concept of Industry 4.0 can affect the development of tourism in Portugal. In this context, it is relevant for tourism that all companies consider the technological drivers of change associated with the concept of Industry 4.0, constituting a technological basis for leveraging tourism companies to a technological environment called ‘Tourism 4.0’.

This paper aims to demonstrate the turnover intentions (TIs) among the academic faculty of higher education institutions (HEIs) in Pakistan through their motivation and commitment toward the concerned institution. It inspects the relationship of dimensions of motivation including an absence of motivation (AM), extrinsic motivation (ExM) and intrinsic motivation (InM) with the dimensions of commitment including affective commitment (AC), continuous commitment (CC) and normative commitment (NC) and finally the academic's TIs.

The paper used the self-determination theory (SDT), the theory of organizational commitment (OC) and the theory of planned behavior (TPB) for its proposed model. A sample of 500 academics, working under higher education commission recognized public and private universities in Punjab Pakistan. A structural equation modeling (SEM) conducted for analysis using an algorithm, bootstrapping and blindfolding techniques.

The outcomes of the research are attention-grabbing, as no direct relationship has been observed between the dimensions of motivation and TIs except InM. The dimensions of commitments are mediating the relationship between motivation and TIs with high significance value. The results reveal a significant adverse effect on TIs through two dimensions of commitment.

As it is the case of a developing country like Pakistan therefore the finding cannot generalize to developed countries.

The findings of this research may lead the policymakers and practitioners of HEIs and controlling body to retain their competent teachers.

This research can help the private sector to develop strategies about the retention of their competent teachers within the institutions that not just value the institution but also will be much beneficial for the students and society.

This paper is identifying how motivation is related to TIs and the role of commitment in it at HEIs. Still, no research has been conducted considering this avenue of SDT, OC and TPB

The productivity of knowledge workers is crucial not only for organizational innovation and competitiveness but also for sustainable development. In the context of knowledge-intensive firms, implementation of knowledge management is likely to increase knowledge worker productivity. Therefore, the purpose of this paper is to examine the influence of knowledge management on knowledge worker productivity.

A research framework on the effects of knowledge management processes on knowledge worker productivity is established and empirically tested with data from 336 knowledge workers at five mobile network operator companies in Pakistan.

The results indicate that knowledge creation and knowledge utilization impact knowledge worker productivity positively and statistically significantly. However, knowledge sharing does not have statistically significant impact on knowledge worker productivity. Demographic factors (gender, managerial position and formal education level) do not moderate the relationship between knowledge management and knowledge worker productivity statistically significantly.

The key limitations are the cross-sectional nature of the data and the geographic limitation to telecom companies in Pakistan.

Irrespective of gender, education and managerial position, implementation of knowledge management can increase knowledge worker productivity. Therefore, knowledge management practices should be implemented to enhance the knowledge worker productivity via fostering the knowledge worker’s engagement in and propensity to knowledge management processes.

This study is among the first to examine the likely influence of knowledge management on the productivity of knowledge workers conclusively while controlling for three individual demographic factors. This study also addresses the effectiveness of knowledge management in the little-explored cultural context of Pakistan.