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This study aims to examine the investment-cash flow sensitivity (ICFS) and the impact of environmental, social and governance (ESG) on ICFS of manufacturing firms in India. Furthermore, it explores the role of group affiliation in such ESG–ICFS nexus.

The paper uses the generalized method of moments regression to analyze the data with a sample of 222 manufacturing firms from 2012 to 2022.

The paper reveals that Indian manufacturing firms mainly depend on internal cash flow for their investment decision, and ESG footprint reduces such sensitivity of investment-cash flow. Furthermore, group-affiliated firms have greater ICFS, and the impact of ESG on ICFS is more noticeable in group-affiliated firms than in standalone counterparts.

This paper provides valuable insights into current literature, with implications that extend to economies, firms, managers and investors. To the authors’ knowledge, this paper examining the impact of ESG on ICFS amidst group affiliation is first-of-its-kind.

A few earlier studies presented infeasible heatline trajectories for natural convection within annular domains involving an inner circular cylinder and outer square/circular enclosure. The purpose of this paper is to revisit and illustrate the correct heatline trajectories for various test cases.

Galerkin finite element based methodology and space adaptive grid have been used to simulate natural convective flows within the annular domains. The prediction of heatlines involves derivatives at the nodes, which are evaluated based on finite element basis functions and contributions from neighboring elements.

The heatlines in the earlier work indicate infeasible heat flow paths such as heat flow from one portion to the other of isothermal hot walls and heat flow across the adiabatic walls. Current results illustrate physically consistent heat flow paths involving perpendicularly emerging heatlines from hot to cold walls for conductive transport, long heat flow paths around the closed-loop heatline cells for convective transport and parallel layout of heatlines to the adiabatic walls. Results also demonstrate complex heatlines involving multiple flow vortices and complex flow structures.

Current work translates heatfunctions from energy flux vectors, which are determined by using basis sets. This work demonstrates the expected heatline trajectories for various scenarios involving conductive and convective heat transport within enclosures with an inner hot object as a first attempt, and the results are precursors for the understanding of energy flow estimates.

This chapter takes on the role of the metaverse in skill development, such as skilling, reskilling, and upskilling in the digital age. Metaverse is instrumental in revolutionizing skill development in the digital age and bringing the paradigm shift in learning. This chapter will cover the capability of the metaverse to transform the ways of learning and developing skills in the evolving digital landscape. Individuals can be part of tailor-made solutions for their needs through innovative methodologies and interactive experiences. This chapter takes through real cases to get deeper insights about conventional methods that transform how an individual experiences learning to acquire skills to get exposed to the rapidly changing digital world, allowing people to customize their learning experiences to adapt their unique requirements through cutting-edge methodologies and digitally responsive encounters. It then deliberates the importance of the metaverse in the individual-led industry in a manner that allows people to reach their potential. Individuals succeed in the evolution of the metaverse dynamic by continually upskilling granted to them.

The concept of a heat function is introduced to visualize the path of heat flow in a buoyancy‐driven turbulent flow heated vertical flat plate. The velocities and the temperature field near the vertical plate are predicted numerically, using an algebraic flux model of turbulent heat transport. As an accurate prediction of the turbulent heat flux is required in order to predict the heat function in the flow field, the use of an algebraic flux model for the turbulent heat transport θu_i, is made as compared with a simple eddy diffusivity hypothesis. The algebraic flux expression was closed with a low‐Re‐number‐k‐ε — θ² —_θ model. The solution ofthe 4 equation low‐Re‐number‐k‐ε — θ² — ε_θ model predicts very well the local Nusselt number along the plate height as well as the velocity and the temperature field near the wall when compared with the experiments. Then the partial differential equation for the heat function is numerically solved to show the true path of heat flow in the buoyancy‐driven turbulent flow field near a heated vertical plate.

The Navier‐Stokes equation and the species continuity equation have been solved numerically in a boundary fitted coordinate system comprising the geometry of a large scale industrial size tundish. The solution of the species continuity equation predicts the time evolution of the concentration of a tracer at the outlets of a six strand billet caster tundish. The numerical prediction of the tracer concentration has been made with six different turbulence models (the standard k‐ε, the k‐ε RNG, the Low Re number Lam‐Bremhorst model, the Chen‐Kim high Re number model (CK), the Chen‐Kim low Re number model (CKL) and the simplest constant effective viscosity model (CEV)) which favorably compares with that of the experimental observation for a single strand bare tundish. It has been found that the overall comparison of the k‐ε model, the RNG, the Lam‐Bremhorst and the CK model is much better than the CKL model and the CEV model as far as gross quantities like the mean residence time and the ratio of mixed to dead volume are concerned. However, the k‐ε model predicts the closest value to the experimental observation compared to all other models. The prediction of the transient behavior of the tracer is best done by the Lam‐Bremhorst model and then by the RNG model, but these models do not predict the gross quantities that accurately like the k‐ε model for a single strand bare tundish. With the help of the above six turbulence models mixing parameters such as the ratio of mix to dead volume and the mean residence time were computed for the six strand tundish for different outlet positions, height of advanced pouring box (APB) and shroud immersion depth. It was found that three turbulence models show a peak value in the ratio of mix to dead volume when the outlets were placed at 200 mm away from the wall. An APB was put on the bottom of the tundish surrounding the inlet jet when the outlets were kept at 200 mm away from the wall. It was also found that there exists an optimum height of the APB where the ratio of mix to dead volume and the mean residence time attain further peak values signifying better mixing in the tundish. At this optimum height of the APB, the shroud immersion depth was made to change from 0 to 400 mm. It was also observed that there exists an optimum immersion depth of the shroud where the ratio of mix to dead volume still attains another peak signifying still better mixing. However, all the turbulence models do not predict the same optimum height of the APB and the same shroud immersion depth as the optimum depth. The optimum height of the APB and the shroud immersion depth were decided when two or more turbulence models predict the same values.

The Navier‐Stokes equation and the species continuity equation have been solved numerically in a boundary fitted coordinate system comprising the geometry of a single strand bare tundish. The solution of the species continuity equation predicts the time evolution of the concentration of a tracer at the outlet of the tundish. The numerical prediction of the tracer concentration has been made with nine different turbulence models and has been compared with the experimental observation for the tundish. It has been found that the prediction from the standard k‐ε model, the k‐ε Chen‐Kim (ck) and the standard k‐ε with Yap correction (k‐ε Yap), matches well with that of the experiment compared to the other turbulence models as far as gross quantities like the mean residence time and the ratio of mixed to dead volume are concerned. It has been found that the initial transient development of the tracer concentration is best predicted by the low Reynolds number Lam‐Bremhorst model (LB model) and then by the k‐ε RNG model, while these two models under predict the mean residence time as well as the ratio of mixed to dead volume. The Chen‐Kim low Reynolds number (CK low Re) model (with and without Yap correction) as well as the constant effective viscosity model over predict the mixing parameters, i.e. the mean residence time and the ratio of mixed to dead volume. Taking the solution of the k‐ε model as a starting guess for the large eddy simulation (LES), a solution for the LES could be arrived after adopting a local refinement of the cells twice so that the near wall y⁺ could be set lower than 1. Such a refined grid gave a time‐independent solution for the LES which was used to solve the species continuity equation. The LES solution slightly over predicted the mean residence time but could predict fairly well the mixed volume. However, the LES could not predict both the peaks in the tracer concentration like the k‐ε, RNG and the Lam‐Bremhorst model. An analysis of the tracer concentration on the bottom plane of the tundish could help to understand the presence of plug and mixed flow in it.

The conception of a heat function, just like the stream function used in a laminar two dimensional incompressible flow field visualization, has been introduced to visualize the convective heat transfer or the flow of energy around a sphere when the sphere is either being cooled or heated by a stream of fluid flowing around it. The heat function is developed in a spherical polar coordinate and is used to generate the heat lines around the sphere. The heat lines essentially show the magnitude and direction of energy transfer around the sphere with and without the existence of a finite radial velocity at the surface. The steady state hydrodynamic field around the sphere is numerically obtained up to a maximum Reynolds number of 100 and the corresponding thermal field has been obtained by solving the steady state energy equation. The field properties thus obtained are utilized to form the heat function, which becomes an effective tool for visualization of convective heat transfer.

This paper intends to contribute to the evolving understanding of Indian adolescents as consumers by examining their unique relationships with food brands, focusing specifically on brand love. It further investigates the key drivers that cultivate brand love among adolescents and explores the resulting outcomes of brand love.

About 37 in-depth interviews, including three exercises, were conducted with adolescents aged 11–16. The first and second exercises used projective techniques to explore respondents’ culture-bound love relationships with their favorite brands. Using the laddering technique, the third exercise investigated the critical drivers of respondents’ brand love.

The study reveals that adolescents derive value through attribute-benefit-value linkages from the consumption experience, leading to brand love. The customer value–brand love dynamics result in adolescents’ customer engagement behavior. Additionally, Indian adolescent customers seek brand consumption as a medium to instate their social identity and achieve hedonic pleasure from the experience. The study highlights the role of socialization and attitudinal autonomy in shaping adolescent–brand interactions.

The study could be relevant for both academicians and practitioners as they unveil the consumer psychology of contemporary adolescents in emerging countries like India and how similar or different they are from adult consumers. Also, there are very few adolescent–brand relationship studies in the past that have been deliberated in the context of food brands. Brand managers may design their product development and communication appeals around higher levels of abstraction in the attribute-benefit-value linkages discovered by this study.

This paper aims at studying numerically the entropy generation of nanofluid flowing over an inclined sheet in the presence of external magnetic field, heat source/sink, chemical reaction along with slip boundary conditions imposed on an impermeable wall.

A suitable similarity transformation technique has been used to convert the coupled nonlinear partial differential equations to ordinary differential equations (ODEs). The ODEs are then solved simultaneously using the finite difference method implemented through an in-house computer program. The effects of different controlling parameters such as magnetic parameter, radiation parameter, Brownian motion parameter, thermophoresis parameter, chemical reaction parameter, Reynolds number, Brinkmann number, Prandtl number, velocity slip parameter, temperature slip parameter and the concentration slip parameter on the entropy generation and Bejan number have been discussed comprehensively through the relevant physical insights for the first time.

The relative strengths of the irreversibilities due to heat transfer, fluid friction and the mass diffusion arising due to the change in each of the controlling variables have been delineated both in the near-wall and far-away-wall regions, which may be helpful for a better understanding of the thermo-fluid dynamics of nanofluid in boundary layer flows. The numerical results obtained from the present study have also been validated with results published in open literature.

The effects of different controlling parameters such as magnetic parameter, radiation parameter, Brownian motion parameter, thermophoresis parameter, chemical reaction parameter, Reynolds number, Brinkmann number, Prandtl number, velocity slip parameter, temperature slip parameter and the concentration slip parameter on the entropy generation and Bejan number have been discussed comprehensively through the relevant physical insights for the first time.