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This study aims to examine the mediating role of green finance in the relationship between green banking practices and the sustainability performance of banking institutions in developing economies.

The authors performed an empirical investigation by applying the “partial least squares structural equation modeling (PLS-SEM)” based on a representative sample of 414 bank employees working in the National Capital Region, India.

The study’s outcome confirms that employee, top-management, operation and policy related practices substantially influence green finance and banks’ sustainability performance. On the contrary, customer related practices insignificantly influence banks’ sustainability performance. Further, green finance substantially influences the sustainability performance of banking institutions.

This study shed light on green banking practices that can assist in achieving the vision of the “Clean India Mission” of the Indian government. In addition, it encourages policymakers and bank managers to fulfill their social responsibility by engaging employees and customers in cleaner operations to promote banks’ sustainability performance.

This is ground-breaking research that enriches the understanding of green banking practices and green finance by providing a novel theoretical framework concerning the sustainability performance of banking institutions. Theoretically, this paper also broadens the scope of corporate social responsibility literature by applying the resource-based view theory in finance and banking.

ChatGPT is an advanced artificial intelligence (AI) form that can generate human-like text based on large amounts of data. This paper aims to empirically examine the ChatGPT adoption level among Indian individuals by considering the key factors in determining individuals’ attitudes and intentions toward newly emerged AI tools.

This paper used “partial least square structural equation modeling” (PLS-SEM) to investigate the relation among several latent factors by applying a representative sample of 351 individuals.

This study found that trialability, performance expectancy and personal innovativeness significantly influence individuals' attitudes, while compatibility and effort expectancy do not significantly impact attitudes. Additionally, trialability, performance expectancy, effort expectancy, personal innovativeness and attitude significantly influence behavioral intentions. However, compatibility has an insignificant impact on behavioral intention. Moreover, the research highlights that attitude and behavioral intention directly correlate with actual use. Specifically, the absence of compatibility makes people hesitate to use technology that does not meet their specific needs.

These unique findings provide valuable insights for technology service providers and government entities. They can use this information to shape their policies, deliver timely and relevant updates and enhance their strategies to boost the adoption of ChatGPT.

This paper is one of the pioneering attempts to exhibit the research stream to understand the individual acceptance of ChatGPT in an emerging country. Moreover, it gained significant attention from individuals for delivering a unique experience and promising solutions.

Intellectual capital has recently gained significant attention for achieving a competitive advantage for firms. Accordingly, this study aims to examines the impact of intellectual capital on small and medium enterprises (SMEs) innovation performance. Additionally, it also examines the mediating role of firm’s attractiveness (FATR) and knowledge sharing (KS) in small enterprises of India’s National Capital Region (NCR).

Data was gathered from 395 owners and managers of the NCR region through a self-administered survey questionnaire. The author applied a “variance-based structural equation modeling” to examine the outcomes.

The outcomes exhibited that relational capital (RC) significantly influences the FATR, while human capital (HC) and structural capital (SC) insignificantly influences the FATR. Furthermore, HC, RC and SC substantially influence KS. Interestingly, the outcomes also reveal that a FATR and KS substantially influence innovation performance.

This research provides valuable opportunities to expand the study of intellectual capital and innovation performance in SMEs across different countries, paving the way for future comparative analyses in diverse international contexts.

The results assist policymakers and practitioners in assessing an organization’s ability to transform data into intellectual capital within the context of “Industrial Revolution 4.0” to strengthen its sustainability and innovation performance.

The current paper delivers a more affluent and novel understanding of Indian SMEs by examining the interplay between intellectual capital and innovation performance mediating by a FATR and KS behavior. Furthermore, the proposed model has not been previously addressed in the academic literature, which signifies advancement in scientific knowledge.

This paper aims to examine how fear of missing out (FOMO) and investment intention mediate the relationship between behavioral biases and investment decisions of retail investors in the Indian stock market.

The present research comprises two cross-sectional quantitative studies, where Study A involves data from 405 self-employed and Study B involves 393 salaried investors. Data was attained through questionnaires – the partial least squares structural equation modeling was used for data analysis.

The outcomes show that herding, overconfidence and loss aversion bias significantly impact investment intention and FOMO on both studies. Furthermore, the outcomes also indicate that herding and loss aversion bias significantly influence investment decisions in studies (A and B); however, overconfidence bias insignificantly affects the investment decisions in Study A. Besides, the results also reveal a substantial relationship between FOMO, investment intention and investment decision.

The findings of this paper assist practitioners (financial analysts and retail investors) in considering the various ways of analyzing investment decision outcomes by considering the joint effect of several biases.

This paper is an initial attempt to propose a new theoretical framework and empirically examine the impact of behavioral biases on investment decisions by considering the FOMO and investment intention among self-employed and salaried investors. This study also contributes to the behavioral finance literature; other researchers may find it valuable to attain their goals.

This study aims to examine the cryptocurrency adoption (CA) level among Indian retail investors who use cryptocurrency as an investment and mode of transaction.

Through self-administered survey questionnaires, data is collected from 397 retail investors of Haryana (India). This study adopted a quantitative method using partial least squares structural equation modeling (PLS-SEM).

This paper offered a robust model with a high explanatory value for CA in which four of the five proposed factors of diffusion of innovation theory (trialability, compatibility, complexity and observability) and one of the two proposed factors of consumer behavioral theory (perceived value) significantly influences CA. More specifically, the absence of regulatory support is a barrier to the broad adoption of cryptocurrencies, as its regulations are necessary to mitigate or minimize uncertain outcomes.

This research primarily focuses on CA in India. Thus, it can be extended to cover diverse other countries for more precise results.

The results provide insights to the government to design the policies, better regulate and make investment strategies that can ultimately enhance CA. In addition, the study’s results also inform financial educators, policymakers, employers and academicians about the significance of several variables affecting CA in India.

From a social standpoint, this study is an advance that directs central banks and governments to develop, regulate and manage digital currencies and implement a digital currency ecosystem. Moreover, the results assist in understanding investors’ perceptions and decision-making perspectives toward cryptocurrencies through the country’s digitalization.

This paper fills the study gap to assist policymakers and cryptocurrency experts in broadening their knowledge base and recognizing prioritized intentions. Additionally, this study provides a theoretical model with the latent variable for a present and pertinent matter.

This study aims to empirically examine and analyze the factors that influence the adoption of blockchain technology, particularly within small and medium-sized enterprises (SMEs). The study also predicts how adopting blockchain technology may affect SMEs’ market and financial performance.

The research is grounded in the theoretical frameworks of the “technology–organization–environment (TOE) framework” and the “resource-based view (RBV)” perspective. The researchers collected 407 responses from a survey conducted on SMEs in India. The statistical package for social science, followed by the “partial least square structural equation modeling (PLS-SEM)” technique, was applied for the data analysis.

This paper offered a robust research framework for blockchain technology adoption in which one of the two proposed technological factors (relative advantage), one organizational factor (top management support) and two environmental factors (competitive pressure and market dynamics) significantly influence blockchain technology adoption. Similarly, there is a substantial association between blockchain technology adoption and both market and financial performance. More specifically, the complexity and perceived investment cost have been recognized as barriers to SMEs adopting blockchain technology.

The primary focus of this research lies in examining the adoption of blockchain technology among SMEs in India. Consequently, there exists an opportunity to broaden the scope of this study to include various other countries. Such an expansion holds the potential to yield more precise and comprehensive results, enabling a comparative analysis across diverse international contexts.

The outcomes have practical significance for SMEs as they navigate their strategies for adopting blockchain technology. Moreover, policymakers and practitioners can use these findings to enact specific measures targeting barriers, fostering the adoption of blockchain in Indian SMEs and creating a more supportive environment for technological integration and growth.

This study introduces a novel theoretical framework focusing on the impact of blockchain adoption on SMEs. Its distinctive contribution lies in investigating the mediating role of blockchain adoption in the relationship between market and financial performance, specifically within emerging economies. By addressing this gap, the study enhances the understanding of how blockchain adoption shapes SME performance in evolving economic landscapes.

This paper aims to identify the factors influencing the adoption of financial technology (FinTech) services among Indian residents. Moreover, it compares the awareness levels among both male and female users to offer a comprehensive insight into FinTech adoption.

The research comprises two cross-sectional surveys utilizing self-administered questionnaires: Study A involves 411 male participants and Study B involves 473 female users in FinTech adoption. This article used a “Statistical Package for Social Science (SPSS) followed by partial least squares-structural equation modeling (PLS-SEM)” for data analysis.

The exciting finding reveals that attitude and personal innovativeness have a significant impact, while technology anxiety shows a statistically insignificant impact on awareness in both studies. Surprisingly, the socio-demographic factor significantly impacts awareness (in Study A) and has an insignificant impact on awareness in Study B. Moreover, both studies reveal that awareness significantly impacts perceived usefulness and ease of use. Additionally, the outcomes confirm a positive relation between awareness, perceived usefulness, ease of use and FinTech adoption in both studies.

The present research will offer valuable insights to all FinTech service providers and stakeholders, aiding them in planning and designing relevant policies.

As far as the researchers are aware, this study stands as the initial survey into FinTech that specifically examines the impact of gender on technology adoption. The divergence in awareness and adoption rates between males and females and the authors’ insightful findings illuminate the context's uniqueness. Moreover, this article offers a robust model for using FinTech services from the perspective of a developing economy.

The purpose of this paper is to investigate millennials’ purchase behaviours towards green housing in India. This paper also examines the mediating effect of purchase intention between determinants of buying green housing and purchase behaviour in the real estate industry.

A cross-sectional research design was applied to collect data from 393 rural and 388 urban millennials. This study used “partial least squares structural equation modelling” to verify the framed hypotheses.

The outcomes indicate that attitude, environmental concern and green trust substantially influence the purchase intention and purchase behaviour towards green housing in rural and urban studies. However, perceived risk has an insignificant effect on purchase intention and purchase behaviour towards green housing in both studies. Likewise, innovativeness insignificantly impacts the purchase intention in study rural while substantially impacting the purchase behaviour in both studies. Additionally, a favourable relationship between purchase intention and purchase behaviour towards green housing in both rural and urban contexts.

This study provides fruitful evidence for practitioners, marketers and academicians about the drivers of purchase behaviour toward green housing. The results of this study also enable regulatory bodies to design appropriate strategies and tactics to foster the sustainable growth of nations.

This paper is a preliminary attempt to explore the decision to buy green housing in India. Furthermore, the authors targeted a specific age group, especially millennials, to gain a valuable understanding of how different factors affect green housing decisions in different areas, that is, rural and urban areas.

This study aims to investigate the factors that impact the solo travel intentions of millennial women in rural and urban areas. By exploring these factors, this research also sheds light on the similarities and differences in travel behaviors and motivations of women in different geographical contexts within India.

Crowdfunding has emerged as an alternative financing tool and recently gained attention to foster entrepreneurial dynamism and innovation. The current research has identified the determinants impacting the behavioral intentions of entrepreneurs to use crowdfunding for financing their small and medium-sized enterprises (SMEs).

The current article is based on a cross-sectional research design. This research collected the data of 422 owners and managers of SMEs through self-administered questionnaires in the Indian National Capital Region (NCR). The responses were collected from July 17 to October 27, 2022. This article used “partial least squares structural equation modeling” (PLS-SEM) for data analysis.

This article offered a robust model with a high explanatory value of 66% of behavioral intention and 62.1% variance in crowdfunding use behavior. The finding also highlighted that performance expectancy, social influence, facilitating conditions, trialability and perceived value significantly impact behavioral intention. However, effort expectancy and perceived risk insignificantly influence behavioral intention. Notably, facilitating conditions, trialability and behavioral intention positively impact use behavior.

The results of this study will bridge the gap in empirical research on crowdfunding adoption, shedding light on why entrepreneurs hesitate to adopt crowdfunding for financing. Moreover, these results will offer strategic insights for crowdfunding managers and policymakers, aiding them in making informed decisions.

To the best of the authors' knowledge, this pioneering study built the theoretical framework using three credible technology determinant models. The authors examined crowdfunding-specific contextual factors to improve understanding of the positive effect of technological orientation. This addition assists in strategically arranging entrepreneurs' fundraising conversations more efficiently.