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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.

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 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 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 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.

This comparative research examines the factors influencing individuals' purchase intention toward green housing. By examining these factors, this study provides fruitful insights into the purchase intentions and behaviors for greenhouses among individuals of different age groups in India.

Data were gathered from Generation (Gen) X (313) and Generation (Gen) Y (297) using self-administered questionnaires. The “partial least squares structural equation modeling” was used to test the hypotheses.

The outcome shows that attitude and green trust substantially impact the green purchase intention of Gen X and Y. More specifically, environmental knowledge insignificantly influences the green purchase intention of Gen X while significantly influencing Gen Y. However, perceived risk insignificantly affects the purchase intention of both Gen X and Y. Consequently, green purchase intention substantially impacts the green purchase behavior in both studies.

This research focuses primarily on India; future research may be conducted in different geographical contexts. This study could also be extended to all age groups individuals.

The findings of this article facilitate policymakers, real estate developers and professional bodies in formulating strategies for sustainable nations in the future.

The current article is the initial empirical attempt to examine the home-buying decisions of individuals in India. Moreover, the role of Generation X and Generation Y in green housing purchase decisions will provide fruitful insights into how different age groups impact the decision-making process of green housing.

Financial satisfaction is a potential ambition of individuals' lives that requires well-strategized economic behaviors. The authors examine the impact of various factors on the financial behavior (FB) and financial satisfaction (FIS) of individuals in India's National Capital Region (NCR).

Through a literature review, a survey questionnaire was formulated using existing scales on FIS. For more in-depth insights, data are obtained from 427 respondents in the NCR region using self-administered questionnaires. This article used “partial least square structural equation modeling (PLS-SEM)” to inspect the hypothesized model of individuals' FIS.

According to the study results, financial attitude (FA), financial self-efficacy (FSE), financial knowledge (FK) and demographic characteristics (DC) significantly influence FB. Conversely, financial stress (FS) negatively impacts FB. It also highlights that FA, FSE, FK and FB all significantly impact FIS. Nevertheless, FS and DC insignificantly influence FIS.

To the best knowledge of the authors, this article is an initial attempt to offer a novel perspective of individuals' FB and FIS in India. It would help the government and stakeholders by providing various pioneering economic schemes and making policies that help increase individuals' FIS.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-03-2023-0239

Phygital emerges as a promising phenomenon, as it uses innovative technologies to connect digital spaces and physical places that provide customers with an interactive and unique experience. Drawing the stimuli–organism–response (S-O-R) framework, the study aims to examine the phygital customer experience by using key drivers and their effect on customer engagement (CE), trust (TRU) and patronage intentions (PI).

Data were obtained by using convenience sampling from 389 respondents from northern parts of India between December 2022 and February 2023. After checking reliability and validity, “variance-based structural equation modeling” has been applied to obtain results.

The outcomes reported that stimuli constructs such as customer brand experience (CBE), service quality (SQ) and emotions during the service (EDS) significantly influence organism (CE). However, pain points (PP) have a statistically insignificant impact on CE. Further, the outcomes also reveal a positive relation between organism and response variables (i.e. CE, TRU and PI).

This study’s results offer strategic insights to enhance CE and PI, ultimately contributing to the advancement of the retail banking industry. The financial service provider must prudently interrelate digital and physical platforms to make the customer journey fruitful.

To the best of the authors’ knowledge, this study is the first to look at the effect of key drivers on the PI of active retail banking customers in national capital region, India by using the S-O-R framework.