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This study aims to present the experimental and computational performance analysis in compact plate heat exchanger (PHE) using graphene oxide nanofluids at different concentrations and flow rate.

Field emission scanning electron microscope and X-ray diffraction were used to characterize graphene oxide nanoparticles. The nanofluid samples were prepared by varying volume concentration. Zeta potential test was done to check stability of samples. The thermophysical properties of samples have been experimentally measured. The experimental setup of PHE with 60° chevron angle has also been developed. The numerical analysis is done using computational fluid dynamics (CFD) model having similar geometry as of the actual plate. Distilled water at fixed temperature and flow rate is used in hot side tank. Nanofluid at fixed temperature with varying concentration and flow rate is used in cold side tank as coolant.

The numerical and experimental results were compared and found that both results were in good agreement. The results showed ∼13% improvement in thermal conductivity, ∼14% heat transfer rate (HTR), ∼9% in effectiveness and ∼10% in overall heat transfer coefficient at cost of pressure drop and pumping power using nanofluid. Exergy loss also decreased using nanofluid at optimum concentration of 1 Vol.%.

The CFD model can be significant to analyze temperature, pressure and flow distribution in heat exchanger which is impossible otherwise. This study gives ease to predict PHE performance with high accuracy without performing the experiment.

The study aims to use nanofluids as coolants for improving heat transfer peculiarities of plate heat exchangers (PHE). The experimental and numerical investigations are thoroughly performed using distilled water-based Al₂O₃, graphene nanoplatelet (GnP) and multi-walled carbon nanotubes (MWCNT) nanofluids.

The numerical simulation based on Single Phase Model (SPM) was performed on a realistic 3 D model of PHE having similar dimensions as of the actual plate. The standard k-epsilon turbulent model was used to solve the problem. The concentration and flow rate of nanofluids were ranging from 0.1 to 1 Vol.% and 1 to 5 lpm, respectively, at 30°C. Whereas, hot side fluid is distilled water at 2 lpm and 80°C. The heat transfer characteristics such as bulk cold outlet temperature, heat transfer rate (HTR), heat transfer coefficient (HTC), Nusselt number (Nu), pressure drop, pumping power, effectiveness and exergy loss were experimentally evaluated using nanofluids in a PHE.

The experimental results were then compared with the numerical model. The experimental results revealed maximum enhancement in an average heat transfer rate of 9.86, 14.86 and 17.27% using Al₂O₃, GnP and MWCNT nanofluids, respectively, at 1 Vol.%. The present computational fluid dynamics model accurately predicts HTR, and the results deviate <1.1% with experiments for all the cases. The temperature and flow distribution show promising results using nanofluids.

The study helps to visualise heat transfer and flow distribution in PHE using different nanofluids under different operating conditions.

The purpose of this study is to investigate the influence of mobile applications on investment decisions by retail investors in stocks and mutual funds. This study focuses on how mobile technologies are applied on mobile apps by retail investors for e-trading in emerging financial markets.

The study explored predictive relevance for the adoption behavior of retail investors under the Unified Theory of Acceptance and Use of Technology (UTAUT) framework. Further, goal contagion theory was applied to investigate the adoption behavior of investors towards e-trading. An adapted questionnaire was used to collect the date from April to June 2021 and data analysis was performed on 507 usable responses. The methodology adopted in this study is variance based partial least square structural equational modelling (PLS-SEM). Additionally, the study explains important and performing constructs based on the response of retail investors towards mobile app usage for investment decisions.

The study shows that effort expectancy, performance expectancy followed by perceived return were the primary determinants of behavioral intentions to use mobile applications by retail investors for e-trading. Further, habit of investors determined the adoption behavior of investors towards mobile apps. Additionally, the study revealed that perceived risk is not an important aspect for retail investors in comparison to perceived return.

The study in future can address to the aspect of personality traits of retail investors for technology adoption for investment decisions. Further investigation is required on addressing unobserved heterogeneity of retail investors towards technology adoption process in emerging financial markets.

The study provides theoretical and practical implications for retail investors, financial advisors and technology companies to understand the behavioral pattern and mobile apps adoption behavior of retail investors in emerging financial market. The findings in the study will help broking firms to sensitize their clients for effective use of their respective mobile apps for e-trading purposes. The study will strengthen the knowledge of financial advisors to understand investment behavior of retail investors in emerging financial markets.

This study unfolds a novel framework of research to understand the technology adoption pattern of retail investors for e-trading by mobile applications in emerging financial markets. The present study provides significant understanding in the domain of technology adoption by retail investors under behavioral finance environment.

This study aims to investigate the shopping behaviour of consumers, mainly in fashion apparels, and intends to understand consumer buying patterns in Indian context. The study was designed to determine the level of consumer's sense of belonging towards apparel shopping by applying the concept of self-congruence.

The study used variance-based partial least squares structural equational modelling (PLS-SEM) on a cross-sectional study conducted on 569 consumers. The study was conducted by using questionnaire to collect the responses from the central zone of India. The results support most of the projected hypotheses.

The study focused on the shopping behaviour of consumer such as self-congruence, impulse buying, hedonic values and consumer satisfaction. The results of the study highlight the association of constructs and analysed the mediation relation of hedonic and impulse buying constructs. The results revealed a positive association among the constructs and also found a partial mediation effect in their relation with constructs.

The findings are outcomes of an empirical study conducted in the fashion apparel industry of India based on the sample set of urban consumers. The study is restricted to the direct and indirect relationship of constructs. Further, research can examine by using moderating constructs like demographic factors (gender, age, income, etc.) and other shopping behaviours (like brand loyalty, brand love, brand attachment) for more clarity in results. Moreover, the study limited is with fashion apparel, whereas there are many categories in the fashion industry like accessories, perfumes, cosmetic products, footwear and also other products industry.

The study provided valuable inputs to the literature of marketing where self-congruence affects consumer shopping behaviour such as impulse buying, hedonic values and consumer satisfaction. The study proposes a practical approach that can help the marketing professionals and product developers to have a deep understanding about consumer shopping behaviour for facilitating consumer-oriented goods in the Indian fashion industry.

This is one of the first studies in the fashion industry to test the association of self-congruence with hedonic value and consumer satisfaction. This relation is not tested in context of fashion apparel. Additionally, this study also examined the mediating effect of hedonic value and impulse buying in relation with self-congruence and consumer satisfaction in the Indian context.

Celebrity endorsement is a preferred marketing communication strategy adopted by business firms. The present study suggests theoretical underpinnings for investigating the effect of celebrity endorsement on individual investors' intentions to invest in the shares of companies. The study integrates marketing communication and behavioural finance theories to understand investor behaviour in the stock market.

The study used a questionnaire based on a conjoint analysis technique. The retail investors from India filled out the questionnaire. The authors developed an orthogonal design to generate retail investors' investment intentions and applied the full-profile conjoint method.

The results reveal that investors prefer to invest in technology-related firms when they employ entertainment celebrities to endorse their products. Investors prefer that entertainment celebrities' personalities match the single brand only they are endorsing. Further, investors choose to invest during corrective market trends in emerging economies, such as India.

The study offers practical implications for corporate entities and marketing professionals by analysing retail investors' investment intentions in financial markets.

Purpose – The globally controversial genetically modified (GM) cotton has been adopted widely by Indian farmers. Claiming the adoption to be a success of the GM technology, the GM proponents call for a large-scale introduction of GM crops in Indian agriculture. Opposition to GM crops is largely constructed in terms of the environmental risks that GM technologies pose to crop and forest biodiversity. This chapter examines the economic and political context in which these seeds were adopted to see if adequate support mechanisms were available to farmers to facilitate adoption of the new technology.

Design/methodology/approach – A field study was conducted in Vidharbha, Eastern Maharashtra. In addition, government reports and newspaper articles were reviewed and interviews were conducted in Maharashtra and Delhi.

Findings – This chapetr finds that the problems faced by farmers are much deeper than what technology can solve or which have been addressed in the GM debate. Cotton farmers face persistent problems in the agricultural production process that increase their production costs. A spate of farmer's suicides in Vidharbha and other rain-fed regions of India epitomizes the dire conditions farmers are in. This chapter asserts that state-supported policies transformed India from a food importing to a food surplus country in the 1960s during the green revolution. However, GM cotton has been introduced without a supportive infrastructure for technology transfer in Maharashtra and most cotton-growing states. The lack of support makes the gain of cotton farmers in Vidharbha from the new technology highly uncertain.

Originality/value – This analysis shows the need to examine the role of government programs in helping farmers implement technological advances in agriculture.

Since the inception of the conjoint analysis technique in the year 1971, papers addressing the epistemological aspects of conjoint analysis are scant. Hence, this paper attempts to address the vacuum of qualitative discourse addressing the epistemological and methodological aspects of conjoint analysis including different issues, challenges, probable solutions, limitations and future direction of conjoint analysis in the recent decade.

For exploring the methodological and epistemological aspects of conjoint analysis, the seminal papers on conjoint analysis were reviewed. Moreover, the authors' experience for the state-of-art review was also taken into consideration.

The findings suggest that conjoint analysis that roots back since 1971 has not seen much exploration in Asian regions and is mainly used for new product development in the field of marketing or allied areas. Moreover, the reliability and validity of conjoint analysis is always a matter of concern for the researchers that hinders this technique's wider adaptability. Thus, the paper presents some probable solutions to address the focal issues useful for improved reliability and validity of the conjoint analysis technique.

This paper attempts to familiarize the researchers with epistemological and methodological aspects of conjoint analysis with certain solutions to evolve beyond existing conjoint analysis dimensions in terms of improved validity, reliability, epistemological and methodological aspects of conjoint analysis (CA). Moreover, it acts as a call for research in different research domains, especially in the Asian continent.

There exist certain seminal research papers on epistemological aspects of conjoint analysis. However, there is a dearth of such attempt in the recent decade addressing the application issues of conjoint analysis incorporating the recent issues as well. Therefore, this paper is an attempt to usher the future researcher to understand the methodological aspects of conjoint analysis. It may prevent them from violating the basic assumptions and methodological threshold. This research technique is preferred equally by academicians and practitioners, thus making it imperative to have clarity beforehand for improved research rigor.

This study aims to investigate the antecedents of social interaction among Indian retail investors and fund managers to understand how these factors influence investment decisions. By identifying and examining these antecedents, the study aims to shed light on the social dynamics that shape investment behavior in the Indian financial market.

The researchers have mainly adopted an interpretive strategy for the present study. Qualitative data elicited through semistructured interviews with six retail investors and two fund managers were subjected to qualitative thematic analysis.

Our research found several factors that make Indian retail investors and fund managers connect and make financial decisions. Peers can improve a person’s investing performance through social facilitation, and discussing investment suggestions and lessons learned can affect a group’s investment behavior. Social norms also influenced investors’ financial decisions, demonstrating compliance. Investor closeness increased information sharing. Finally, the fear of missing out (FOMO), a psychological phenomenon where people fear missing out on rewarding experiences, encouraged social engagement as investors sought appealing prospects.

The researchers interviewed eight carefully selected interviewees across the divide between retail investors and fund managers. Adopting other grouping criteria, conducting a focus group discussion with more respondents or adopting a mixed-methods approach may increase our understanding of the investment decision behaviors of Indian retail investors and fund managers.

The findings have far-reaching consequences, from deepening our knowledge of investors’ motivations and actions to directing individual savers, informing the development of financial literacy initiatives, influencing fund management practices and inspiring additional research in this study area.

This research, including retail investors and fund managers, significantly contributes to the literature on investment decisions and behavioral finance, particularly in the context of Indian investors and managers. This study’s unique perspective and comprehensive approach make it a valuable addition to the field, sparking interest and further exploration among academics, practitioners and investors alike.

The purpose of this study is to investigate the factors affecting behaviour intention (BI) to use and actual usages of investment-related FinTech services among the zoomers (Gen Z) and millennials (Gen M) retail investors of India.

The study explores the predictive relevance of actual adoption behaviour among the two different age categories of Indian retail investors. It uses the Unified Theory of Acceptance and Use of Technology-2 and the prospect theory framework as guiding frameworks. Data has been collected from 294 retail investors, actively engaged in the investment-related FinTech services. The multi-group analysis using variance-based partial least square structured equation modelling has been used to compare the two groups. The invariance between the two groups was achieved through measurement invariance assessment.

The study reveals distinct factors significantly affecting BI to use investment-related FinTech services among Gen Z and Gen M retail investors are performance expectancy (PE) to BI, perceived risk (PR) to BI, price value (PV) to BI and PR to service trust (ST).

This study provides insights for financial providers and policymakers, emphasizing different factors influencing BI to use investment-related FinTech services in both age groups. Notably, habit emerges as a common factor influencing the actual usage of investment-related FinTech services across Gen M and Gen Z retail investors in India.

This study explores the heterogeneous behaviour of the heterogenous population in the domain of technological adoption of investment-related FinTech services in India.

This research aims to identify the factors that influence the investment intention of retail investors in Indian REITs. The study incorporates the theory of planned behavior and innovation diffusion theory as the research framework, with perceived risk and mass media influence as additional constructs.

Primary data were collected using self-administered questionnaires from 534 potential investors in India. The data were analyzed using partial least square structural equation modeling.

The study showed that factors such as relative advantage, compatibility, attitude, subjective norms, perceived behavioral control and mass media significantly and positively influence investment intention in Indian REITs. However, perceived risk was found to have a negative and significant influence, while complexity did not affect investment intention.

This is the first quantitative investigation into determining the factors influencing the investment intention of Indian retail investors on Indian REITs.