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The current work investigates an unsteady squeezed flow of hybrid-nanofluid between two parallel plates in occurrence with a uniform transverse magnetic field. Water is used as base fluid mixed with Graphene Oxide (GO) and Copper (Cu) nanoparticles. The flow considered here is under slip boundary conditions.

The governing PDEs are transmuted into ODEs by applying an appropriate similarity transformation and then solved numerically using the 4th order R-K method with shooting technique. Graphical illustrations for velocity, temperature, entropy generation (NG), Bejan number (Be), streamline etc. are presented and discussed in detail from the physical point of view. The nature of the Nusselt number is also studied numerically through contour plots for different flow parameters.

There is no funding obtained for the research work.

This kind of study may be used in various fields including polymer processing, lubrication apparatus, compression including hydrodynamical machines compression, food processing etc.

It is observed that very little investigation has yet been made about the movement of hybrid nanofluid between two analogous plates.

This study aims to present the consequences of activation energy and the chemical reactions on the unsteady MHD squeezing flow of an incompressible ternary hybrid nanofluid (THN) comprising magnetite (FE₃O₄), multiwalled carbon nano-tubes (MWCNT) and copper (Cu) along with water (H2O) as the base fluid. This investigation is performed within the framework of two moving parallel plates under the influence of magnetic field and viscous dissipation.

Due to the complementary benefits of nanoparticles, THN is used to augment the heat transmit fluid’s efficacy. The flow situation is expressed as a system of dimensionless, nonlinear partial differential equations, which are reduced to a set of nonlinear ordinary differential equations (ODEs) by suitable similarity substitutions. These transformed ODEs are then solved through a semianalytical technique called differential transform method (DTM). The effects of several changing physical parameters on the flow, temperature, concentration and the substantial measures of interest have been deliberated through graphs. This study verifies the reliability of the results by performing a comparison analysis with prior researches.

The enhanced activation energy results in improved concentration distribution and declined Sherwood number. Enhancement in chemical reaction parameter causes disparities in concentration of the ternary nanofluid. When the Hartmann number is zero, value of skin friction is high, but Nusselt and Sherwood numbers values are small. Rising nanoparticles concentrations correspond to a boost in overall thermal conductivity, causing reduced temperature profile.

Due to its firm and simple nature, its implications are in various fields like chemical industry and medical industry for designing practical problems into mathematical models and experimental analysis.

Deployment of the squeezed flow of ternary nanofluid with activation energy has significant consideration in nuclear reactors, vehicles, manufacturing facilities and engineering environments.

This study would be contributing significantly in the field of medical technology for treating cancer through hyperthermia treatment, and in industrial processes like water desalination and purification.

In this problem, a semianalytical approach called DTM is adopted to explore the consequences of activation energy and chemical reactions on the squeezing flow of ternary nanofluid.

There has been considerable discussion about the utilization of social media effectively in tourist research. Still, there is a paucity of information about its usage for ecotourism destination selection. The study aims to determine critical factors influencing travelers' behavioral and electronic word-of-mouth (e-WOM) intentions to use Instagram reels to select an ecotourism destination.

This study is based on the motivated consumer innovativeness theory and technology acceptance model. Purposive sampling was applied to acquire data from Instagram users. Data were gathered from 445 respondents and 415 valid responses were analyzed using partial least square structural equational modeling.

The findings of the study confirmed the positive impact of perceived ease of use, socially motivated consumer innovativeness and hedonically motivated consumer innovativeness on travelers' attitude except for perceived usefulness. The outcomes also revealed a significant influence of travelers' attitude on behavioral and e-WOM intention.

The study's findings were intended to offer insights into traveler behavior to critical players in the tourism sector, including destination marketers, travel companies, the government and policymakers. They must comprehend how useful Instagram is for the tourist industry, which will help them better understand how to attract travelers through Instagram reels to market their destination.

The current investigation is the first attempt to investigate the travelers' behavioral and e-WOM intentions to use Instagram reels to select an ecotourism destination.

This chapter critically examines the unique challenges and opportunities faced by family-owned startups in emerging economies, a topic that has received limited attention in existing literature. Recognizing the high failure rate of startups, particularly in family firms, this study seeks to understand the factors contributing to their success or failure. Employing a qualitative analysis, the chapter explores various economic, legal, and cultural dimensions that influence these businesses. It provides a comparative perspective, drawing insights from various emerging economies to identify patterns and differences in the experiences of family-owned startups. The chapter aims to fill the knowledge gap by offering a comprehensive view of the success and failure dynamics in family-owned startups, with a focus on strategic, managerial, and operational aspects. This approach offers valuable insights for both academics and practitioners, aiming to guide future research and practical interventions to support the sustainability and growth of family firms in these dynamic markets.

This chapter explores how perceived product innovation influences brand loyalty among UK Apple users, extending the technology acceptance model. Using a quantitative approach, data were collected from 101 respondents via an online survey and analysed using SPSS. Objectives included examining the mediating role of perceived product usefulness and ease of use, exploring the relationship between product/brand attitudes and brand loyalty and assessing gender's impact on loyalty perceptions. Findings reveal a significant positive relationship among variables, with perceived product usefulness and ease of use jointly mediating the link between product innovation and attitude, affecting brand loyalty. Gender was found to have no moderating effect. The research contributes by highlighting these mediating effects and deepening understanding of product innovation's impact on loyalty. Managerially, prioritising innovation, usefulness and ease of use can enhance satisfaction and loyalty. Future research could explore additional variables to enrich understanding further.

This study conducts a systematic literature review and bibliometric analysis to explore the overarching trends, growth trajectories, key themes, significant contributors and scope of research concerning the interplay between foreign capital inflows, institutional quality and the dynamics of financial development.

Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines have been followed to identify the articles. A thorough literature review was then conducted, supplemented by a bibliometric analysis using the Biblioshiny software within the RStudio platform.

Empirical research consistently demonstrates a strong correlation between foreign capital inflows, institutional quality and financial development. The bibliometric analysis indicates a 5.56% annual growth rate in this area, alongside a steady increase in scientific output. Regarding country-specific scientific production, China, Malaysia and the United States rank among the world’s top 10 most prolific nations. Thematic map analysis further reveals that the keywords “institutional quality,” “financial development” and “foreign direct investment” are categorized as “basic themes,” highlighting their significant potential for future research.

The analysis relies on Biblioshiny software; future studies could incorporate other methods such as cluster analysis, citation and co-citation analysis using VOSviewer. Additionally, a more comprehensive meta-analysis covering a longer time span can be considered for future research.

This study shall assist researchers in identifying recent advancements in the components of foreign capital and their direct and indirect effects on financial development through the lens of institutional quality. It provides valuable insights for scholars, aiding in recognizing emerging trends and patterns in the field. Additionally, it highlights key contributors, including leading authors, journals and countries, thereby fostering global academic collaboration.

This research offers policymakers a clear framework for formulating policies to effectively leverage foreign capital inflows for financial development. It also emphasizes the importance of a strong institutional environment in the relationship between foreign capital inflow and financial market development.

The study uncovers key gaps in the multidimensional aspects of financial development and the heterogeneity of foreign direct investment (FDI), thereby deepening scholars' understanding of trends, growth rates and potential future directions in the field.

In this study, we investigate the effects of an extended ternary hybrid Tiwari and Das nanofluid model on ethylene glycol flow, with a focus on heat transfer. Using the Cross non-Newtonian fluid model, we explore the heat transfer characteristics of this unique fluid in various applications such as pharmaceutical solvents, vaccine preservatives, and medical imaging techniques.

Our investigation reveals that the flow of this ternary hybrid nanofluid follows a laminar Cross model flow pattern, influenced by heat radiation and occurring around a stretched cylinder in a porous medium. We apply a non-similarity transformation to the nonlinear partial differential equations, converting them into non-dimensional PDEs. These equations are subsequently solved as ordinary differential equations (ODEs) using MATLAB’s bvp4c tools. In addition, the magnetic number in this study spans from 0 to 5, volume fraction of nanoparticles varies from 5% to 10%, and Prandtl number for EG as 204. This approach allows us to examine the impact of temperature on heat transfer and distribution within the fluid.

Graphical depictions illustrate the effects of parameters such as the Weissenberg number, porous parameter, Schmidt number, thermal conductivity parameter, Soret number, magnetic parameter, Eckert number, Lewis number, and Peclet number on velocity, temperature, concentration, and microorganism profiles. Our results highlight the significant influence of thermal radiation and ohmic heating on heat transmission, particularly in relation to magnetic and Darcy parameters. A higher Lewis number corresponds to faster heat diffusion compared to mass diffusion, while increases in the Soret number are associated with higher concentration profiles. Additionally, rapid temperature dissipation inhibits microbial development, reducing the microbial profile.

The numerical analysis of skin friction coefficients and Nusselt numbers in tabular form further validates our approach. Overall, our findings demonstrate the effectiveness of our numerical technique in providing a comprehensive understanding of flow and heat transfer processes in ternary hybrid nanofluids, offering valuable insights for various practical applications.

The purpose of this study is to provide a review of the existing research landscape on work-life balance and women’s career motivation. It examines the relationship between work-life balance and career motivation in the context of Indian women. Specifically, it explores how the work-life balance of women influences the motivational aspects of their careers.

The research uses a systematic literature review to identify and analyze relevant literature on work-life balance and women’s career motivation among Indian women from the Scopus database.

The study uncovers critical insights into the connection between work-life balance and women’s career decisions. It gives insight on how work-life balance significantly impacts women’s career choices. The SLR reveals a notable and consistent upward trend in the domains of work-life balance and career motivation among women.

The findings of this study can inform organizations in tailoring policies that foster women’s career growth while simultaneously supporting a healthy work-life balance. In addition, the research can empower women to make informed decisions about their careers and personal lives. Ultimately, it contributes to creating a more inclusive and gender-equitable work environment, promoting both women’s career aspirations and their overall well-being.

This research stands out in its examination of the relationship between work-life balance and women’s career motivation, particularly in the unique context of Indian women. While previous studies have explored these topics individually, this research bridges the gap by investigating their interplay. Moreover, the application of a systematic literature review approach to these variables in the context of Indian women represents a novel contribution.

This study aims to determine experimentally factors affecting the satisfaction of retail stock investors with various investor protection regulatory measures implemented by the Government of India and Securities and Exchange Board of India (SEBI). Also, an effort has been made to gauge the level of satisfaction of retail equities investors with the laws and guidelines developed by the Indian Government and SEBI for their invested funds.

To accomplish the study’s goals, a well-structured questionnaire was created with the help of a literature review, and copies of it were filled by Punjabi retail equities investors with the aid of stockbrokers, i.e. intermediaries. Amritsar, Jalandhar, Ludhiana and Mohali-area intermediaries were chosen using a random selection procedure. Xerox copies of the questionnaire were given to the intermediaries, who were then asked to collect responses from their clients. Some intermediaries requested the researcher to sit in their offices to collect responses from their clients. Only 373 questionnaires out of 1,000 questionnaires that were provided had been received back. Only 328 copies were correctly filled by the equity investors. To conduct the analysis, 328 copies, which were fully completed, were used as data. The appropriate approaches, such as descriptives, factor analysis and ordinal regression analysis, were used to study the data.

With the aid of factor analysis, four factors have been identified that influence investors’ satisfaction with various investor protection regulatory measures implemented by government and SEBI regulations, including regulations addressing primary and secondary market dealings, rules for investor awareness and protection, rules to prevent company malpractices and laws for corporate governance and investor protection. The impact of these four components on investor satisfaction has been investigated using ordinal regression analysis. The pseudo-R-square statistics for the ordinal regression model demonstrated the model’s capacity for the explanation. The findings suggested that a significant amount of the overall satisfaction score about the various investor protection measures implemented by the government/SEBI has been explained by the regression model.

A study could be conducted to analyse the perspective of various stakeholders towards the disclosures made and norms followed by corporate houses. The current study may be expanded to cover the entire nation because it is only at the state level currently. It might be conceivable to examine how investments made in the retail capital market affect investors in rural areas. The influence of reforms on the functioning of stock markets could potentially be examined through another study. It could be possible to undertake a study on female investors’ knowledge about retail investment trends. The effect of digital stock trading could be examined in India. The effect of technological innovations on capital markets can be studied.

This research would be extremely useful to regulators in developing policies to protect retail equities investors. Investors are required to be safeguarded and protected to deal freely in the securities market, so they should be given more freedom in terms of investor protection measures. Stock exchanges should have the potential to bring about technological advancements in trading to protect investors from any kind of financial loss. Since the government has the power to create rules and regulations to strengthen investor protection. So, this research will be extremely useful to the government.

This work has societal ramifications. Because when adequate rules and regulations are in place to safeguard investors, they will be able to invest freely. Companies will use capital wisely and profitably. Companies should undertake tasks towards corporate social responsibility out of profits because corporate houses are part and parcel of society only.

Many investors may lack the necessary expertise to make sound financial judgments. They might not be aware of the entire risk-reward profile of various investment options. However, they must know various investor protection measures taken by the Government of India & Securities and Exchange Board of India (SEBI) to safeguard their interests. Investors must be well-informed on the precautions to take while dealing with market intermediaries, as well as in the stock market.

This study aims to assess support vector machine (SVM) models' predictive ability to estimate half-cell potential (HCP) values from input parameters by using Bayesian optimization, grid search and random search.

A data set with 1,134 rows and 6 columns is used for principal component analysis (PCA) to minimize dimensionality and preserve 95% of explained variance. HCP is output from temperature, age, relative humidity, X and Y lengths. Root mean square error (RMSE), R-squared, mean squared error (MSE), mean absolute error, prediction speed and training time are used to measure model effectiveness. SHAPLEY analysis is also executed.

The study reveals variations in predictive performance across different optimization methods, with RMSE values ranging from 18.365 to 30.205 and R-squared values spanning from 0.88 to 0.96. Additionally, differences in training times, prediction speeds and model complexities are observed, highlighting the trade-offs between model accuracy and computational efficiency.

This study contributes to the understanding of SVM model efficacy in HCP prediction, emphasizing the importance of optimization techniques, model complexity and dimensionality reduction methods such as PCA.