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The purpose of this study is to derive a physics based complete-flux approximation scheme by solving suitable nonlinear boundary value problems (BVP) for finite volume method for mixed convection problems, to study the mixed convection phenomenon inside partially and differentially heated cavity for various sets of flow parameters. And, to study the impact of source terms on the cell-face fluxes for various sets of flow parameters for mixed convection problems.

The governing equations have been discretized by finite volume method on a staggered grid, and the cell-face fluxes have been approximated by local nonlinear BVP. The cell-face flux is represented as a sum of homogeneous and an inhomogeneous flux term. The proposed flux approximation is fully physics based as it considers the pressure gradient term, thermal buoyancy term and the other source terms in the cell-face flux calculation. The scheme comes out to be second order accurate in space tested with known solution. Also, the scheme has been implemented to study the mixed convection problems in a partially and differentially heated cavity.

The numerical order of convergence study shows that the proposed scheme is of second order in space. The scheme is first validated with existing benchmark literature for the mixed convection problem. As the proposed cell-face flux approximation scheme is a homogeneous part and an inhomogeneous part, this study quantifies the influence of the several source terms on the cell-face flux with the help of the inhomogeneous flux term. Then, the mixed convection problems in a partially and differentially heated cavity has been studied. Also, the effect of heat transfer rate at the hot wall is studied for different height of the heat source with different directions of wall movement. The numerical findings show that the local Nusselt number at the left wall is higher when the top and bottom walls move in opposite directions compared to when they move in the same direction, regardless of the Richardson number. In addition, the heat transfer rate at the hot portion of the left wall increases uniformly as the Richardson number decreases when the walls move in opposite directions. However, when the top and bottom walls move in the same direction, the increase in heat transfer rate is not uniform due to the formation of secondary re-circulation of the fluid near the bottom wall.

In this work, the flux approximation is conducted through local nonlinear BVPs, an approach that, to the authors’ knowledge, has not been previously applied to mixed convection problems. One of the strong advantages of the proposed scheme is that it can quantify the influence of source terms, namely, pressure gradient, cross-flux and the thermal buoyancy force, on the cell face fluxes required in the finite volume methods. Furthermore, the study explores mixed convection in a partially and differentially heated cavity, which is also novel within the current literature. These factors contribute to the originality and scientific value of the research.

Singular perturbation turning point problems (SP-TPPs) involving parabolic convection–diffusion Partial Differential Equations (PDEs) with large spatial delay are studied in this paper. These type of equations are important in various fields of mathematics and sciences such as computational neuroscience and require specialized techniques for their numerical analysis.

We design a numerical method comprising a hybrid finite difference scheme on a layer-adapted mesh for the spatial discretization and an implicit-Euler scheme on a uniform mesh in the temporal variable. A combination of the central difference scheme and the simple upwind scheme is used as the hybrid scheme.

Consistency, stability and convergence are investigated for the proposed scheme. It is established that the present approach has parameter-uniform convergence of OΔτ+K−2(lnK)2, where Δτ and K denote the step size in the time direction and number of mesh-intervals in the space direction.

Parabolic SP-TPPs exhibiting twin boundary layers with large spatial delay have not been studied earlier in the literature. The presence of delay portrays an interior layer in the considered problem’s solution in addition to twin boundary layers. Numerical illustrations are provided to demonstrate the theoretical estimates.

Nanosized honeycomb-configured materials are used in modern technology, thermal science and chemical engineering due to their high ultra thermic relevance. This study aims to scrutinize the heat transmission features of magnetohydrodynamic (MHD) honeycomb-structured graphene nanofluid flow within two squeezed parallel plates under Joule dissipation and solar thermal radiation impacts.

Mass, energy and momentum preservation laws are assumed to find the mathematical model. A set of unified ordinary differential equations with nonlinear behavior is used to express the correlated partial differential equations of the established models, adopting a reasonable similarity adjustment. An approximate convergent numerical solution to these equations is evaluated by the shooting scheme with the Runge–Kutta–Fehlberg (RKF45) technique.

The impression of pertinent evolving parameters on the temperature, fluid velocity, entropy generation, skin friction coefficients and the heat transference rate is explored. Further, the significance of the irreversibility nature of heat transfer due to evolving flow parameters are evaluated. It is noted that the heat transference rate performance is improved due to the imposition of the allied magnetic field, Joule dissipation, heat absorption, squeezing and thermal buoyancy parameters. The entropy generation upsurges due to rising magnetic field strength while its intensification is declined by enhancing the porosity parameter.

The uniqueness of this research work is the numerical evaluation of MHD honeycomb-structured graphene nanofluid flow within two squeezed parallel plates under Joule dissipation and solar thermal radiation impacts. Furthermore, regression models are devised to forecast the correlation between the rate of thermal heat transmission and persistent flow parameters.

This study aims to investigate entropy generation through natural convection and examine heat transfer properties within a partially heated and cooled enclosure influenced by an angled magnetic field. The enclosure, subjected to consistent heat production or absorption, contains a porous medium saturated with a hybrid nanofluid blend of Cu-Fe₃O₄ and MoS₂-Fe₃O₄.

The temperature and velocity equations are converted to a dimensionless form using suitable non-dimensional quantities, adhering to the imposed constraints. To solve these transformed dimensionless equations, the finite-difference method, based on the MAC (Marker and Cell) technique, is used. Comprehensive numerical simulations address various control parameters, including nanoparticle volume fraction, Rayleigh number, heat source or sink, Darcy number, Hartmann number and slit position. The results are illustrated through streamlines, isotherms, average Nusselt numbers and entropy generation plots, offering a clear visualization of the impact of these parameters across different scenarios.

Results obtained show that the Cu-Fe₃O₄ hybrid nanofluid exhibits higher entropy generation than the MoS₂-Fe₃O₄ hybrid nanofluid when comparing them at a Rayleigh number of 10⁶ and a Darcy number of 10^–1. The MoS₂ hybrid nanofluid demonstrates a low permeability, as evidenced by an average Darcy number of 10^–3, in comparison to the Cu hybrid nanofluid. The isothermal contours for a Rayleigh number of 10⁴are positioned parallel to the vertical walls. Additionally, the quantity of each isotherm contour adjacent to the hot wall is being monitored. The Cu and MoS₂ nanoparticles exhibit the highest average entropy generation at a Rayleigh number of 10⁵ and a Darcy number of 10^–1, respectively. When a uniform heat sink is present, the temperature gradient in the central part of the cavity decreases. In contrast, the absence of a heat source or sink leads to a more intense temperature distribution within the cavity. This differs significantly from the scenario where a uniform heat sink regulates the temperature.

The originality of this study is to examine the generation of entropy in natural convection within a partially heated and cooled enclosure that contains hybrid nanofluids. Partially heated corners are essential for optimizing heat transfer in a wide range of industrial applications. This enhancement is achieved by increasing the surface area, which improves convective heat transfer. These diverse applications encompass fields such as chemical engineering, mechanical engineering, surface research, energy production and heat recovery processes. Researchers have been working on improving the precision of heated and cold corners using various methods, such as numerical, experimental and analytical approaches. These efforts aim to enhance the broad utility of these corners further.

This study aims to explore the extent to which customer orientation and creative benefits offered by a firm may weaken rather than strengthen customer engagement. In doing so, it sheds new light on how customer orientation and creative benefits may facilitate rather than hinder engagement by customers.

A field study provides a test of the proposed effects in a hedonic consumption setting with 1,703 customers of an online dating service. Furthermore, an experimental study with 277 executives in a functional consumption setting (new mobile app) helps affirm the robustness of the field study findings.

This research theorizes and examines how communal relationship norms between customers and a firm, along with customers’ psychological empowerment, mediate the effect of customer orientation and creative benefits on customer engagement. A provocative finding of the study is that communal relationship norms help boost, whereas psychological empowerment reduces, the effects of both customer orientation and creative benefits on customer engagement.

The research examines different relationship norms and how they can become integral to customer–company relationships; this perspective helps reveal the underlying dynamics. It contributes to the literature on customer engagement by theorizing and demonstrating the link between customer orientation and customer engagement, two central constructs in the marketing literature. It theorizes and demonstrates that providing creative benefits brings about a direct competitive advantage for the product itself, and acts as a significant variable that explains the company−customer relationship.

The findings highlight the advantages and challenges associated with encouraging customer engagement. First, they suggest that companies emphasize their customer orientation and creative benefits. Second, managers should try to minimize the possible process of raising customers’ psychological empowerment while maximizing the impact of communal relationship norms.

This study identifies psychological empowerment as a key reason customer-oriented companies that provide creative benefits still struggle to engage their customers. It also suggests viable tactics to overcome barriers to enhanced customer engagement, such as by minimizing the effects of customers’ psychological empowerment while maximizing the impact of their perceived communal relationship norms.

Artificial intelligence (AI) has become a pivotal technology in both marketing and daily life. Despite extensive research on the benefits of AI, its adverse effects on customers have received limited attention.

We employed meta-analysis to synthesise effect sizes from 45 studies encompassing 50 independent samples (N = 19,503) to illuminate the negative facets of AI's impact on customer responses.

Adverse effects of AI, including privacy concern, perceived risks, customer alienation, and uniqueness neglect, have a negative and significant effect on customers' cognitive (perceived benefit, trust), affective (attitude and satisfaction) and behavioural responses (purchase, loyalty, well-being). Additionally, moderators in AI (online versus offline), customer (age, male vs. female), product (hedonic vs. utilitarian, high vs. low involvement), and firm level (service vs. manufacturing) and national level (individualism, power distance, masculinity, uncertainty avoidance, long-term orientation) moderate these relationships.

Our findings inform marketing managers about the drawbacks of utilising AI as part of their value proposition and provide recommendations on how to minimise these effects in different contexts. Additionally, policymakers need to consider the dark side of AI, especially among the vulnerable groups.

This paper is among the first research studies that synthesise previous research on the dark side of AI, providing a comprehensive view of its diminishing impact on customer responses.

The study examined a wide range of proactive supply chain practices to demonstrate a cross-linkage among them and to understand their effects on both practitioners of previous decision-making models, frameworks, strategies and policies. Here, six supply chain practices are empirically evaluated based on 28 constructs to investigate a comprehensive model and confirm the connections for achieving performance and competence. The study presents a conceptual model and examines the influence of many crucial factors, i.e. supply chain collaboration, knowledge, information sharing, green human resources (GHR) management and lean-green (LG) practices on supply chain performance.

Structural equation modeling (SEM) examines the conceptual model and allied relationship. A sample of 175 respondents' data was collected to test the hypothesized relations. A resource based view (RBV) was adopted, and the questionnaires-based survey was conducted on the Indian supply chain professionals to explore the effect of LG and green human resource management (GHRM) practices on supply chain performance.

The study presented five constructs for supply chain capabilities (SCCA), five constructs for supply chain collaboration and integration (SCIN), four constructs for supply chain knowledge and information sharing (SCKI), five constructs for GHR, five constructs for LG practices (LGPR) and four constructs for lean-green SCM (LG-SCM) firm performance to be utilized for validation by the specific industry, company size and operational boundaries for attaining sustainability. The outcome emphasizes that SCCA positively influence GHRM, LG practices and LG supply chain firm performance. However, LG practices do not influence LG-SCM firm performance, particularly in India.

The study exploited multiple practices in a conceptual model to provide a widespread understanding of decision-making to assist in developing a holistic approach based on different practices for attaining organizational sustainability. The study stimulates the cross-pollination of ideas between many supply chain practices to better understand SCCA, SCIN, SCKI, GHRM and LG-SCM under a single roof for retaining organization performance.

The utilization of mobile fitness applications (apps) is on the rise, making user retention and engagement critical factors in the commercial success of these apps. However, research in this area is limited and fragmented. The objective of this study is to conduct a thorough review of the available literature on the effects of digital innovations, gamification, artificial intelligence (AI) and machine learning (ML) on user engagement with fitness mobile apps. The findings reveal the relationships between gamification, the use of AI/ML and technology adoption on user engagement, interaction and intent to use. Additionally, the study highlights the importance of understanding how user experience, customer experience and brand experience impact customer retention and contribute to the overall success of mobile fitness apps. Furthermore, the study also identifies the gaps in the current research and recommends further studies to be conducted in these areas. Future research is encouraged to incorporate elements from the experience domains to provide consumers with engaging interactions and improve retention and commercial success for mobile fitness apps.

This study aims to investigate the machining performance of CVD-coated carbide tools by considering most crucial machinability aspects: cutting force, tool life, surface roughness and chip morphology in high-speed hard turning of AISI 4340 alloy steel under a sustainable minimum quantity lubrication (MQL) environment.

The purpose of this study is to analyze the performance of coated carbide tools under MQL environment therefore, machining tests were performed in accordance with the Taguchi L9 orthogonal array, accommodating the three crucial machining parameters such as cutting speed (V = 300–400 m/min), feed rate (F = 0.1–0.2 mm/rev) and depth of cut (DOC = 0.2–0.4 mm). The measured or calculated values obtained in each experimental run were validated for normality assumptions before drawing any statistical inferences. Taguchi signal-to-noise (S/N) ratio and analysis of variance methodologies were used to examine the effect of machining variables on the performance outcomes.

The quantitative analysis revealed that the depth of cut exerted the most significant influence on cutting force, with a contributing rate of 60.72%. Cutting speed was identified as the primary variable affecting the tool life, exhibiting a 47.58% contribution, while feed rate had the most dominating impact on surface roughness, with an overall contributing rate of 89.95%. The lowest cutting force (184.55 N) and the longest tool life (7.10 min) were achieved with low machining parameters at V = 300 m/min, F = 0.1 mm/rev, DOC = 0.2 mm. Conversely, the lowest surface roughness (496 nm) was achieved with high cutting speed, low feed rate and moderate depth of cut at V = 400 m/min, F = 0.1 mm/rev and DOC = 0.3 mm. Moreover, the microscopic examination of the chips revealed a serrated shape formation under all machining conditions. However, the degree of serration increased with an incremental raise with cutting speed and feed rate.

The study is limited to study the effect of machining parameters within the stated range of cutting speed, feed rate and depth of cut as well as other parameters.

Practitioners may consider to adopt this machining technique to create more sustainable working environment as well as eliminate the disposal cost of the used metal cutting fluid.

By applying this machining technique, diseases caused by metal cutting fluid to the mechanist will be significantly reduced, therefore creating better lifestyles.

Hard turning is commonly carried out with advanced cutting tools such as ceramics, cubic boron nitride and polycrystalline cubic boron nitride to attain exceptional surface finish. However, the high cost of these tools necessitates exploration of alternative approaches. Therefore, this study investigates the potential of using cost-effective, multilayer-coated carbide tools under MQL conditions to achieve comparable surface quality.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-01-2024-0013/

The purpose of this study is to examine how Industry 4.0 (I4.0) implementation might improve marketing performance (MP). Early adopters now have the chance to capitalize on the advantages of this successful implementation owing to the transition to I4.0. To improve MP, businesses must be able to identify and manage their effective implementation of I4.0 technologies, which are essential to improve industrial performance.

A survey was created and sent to 311 samples of manufacturing companies. To investigate the hypothesis created in this context, the study includes a survey-based analysis. To present the study’s findings, partial least squares-structural equation modeling has been used.

According to the findings, it can be concluded that an efficient implementation of Industry 4.0 (EII) can improve MP by positively impacting consumer loyalty and increasing customer loyalty (CL) positively enhancing by product customization (PC). The study’s key results, however, are how both PC and CL affect MP.

The intensive production technologies that are at the center of I4.0 will be better understood by professionals thanks to this study. The Internet of Things, artificial intelligence, additive manufacturing, sophisticated robots and many more are examples of these technologies. I4.0’s application strengthens efficiency and high-quality production. The I4.0 concept is gaining popularity in both developed and emerging countries due to its higher performance. Additionally, business people are actively working to implement I4.0 and make it a big success.

The study identifies the successful adoption of I4.0 that has a substantial impact on businesses’ MP. However, there is a lack of noteworthy studies that can concentrate on the marketing reach with I4.0 deployment. As a result, the goal of the current research is to comprehend how I4.0 will affect MP.