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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 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.

Financial technology (FinTech) is experiencing transformation because artificial intelligence has become the new norm to enrich the experiences of individuals in this modern era of technological advancement. The article utilizes the stimuli-organism-response (SOR) framework to investigate how individual attitudes and behavioral intentions influence the adoption of FinTech, particularly in mobile banking.

433 respondents participated in the self-administered survey to answer questions related to demographic profiles and items to assess the variables adopted in the conceptual framework. The study applied “partial least squares structural equation modeling” PLS-SEM to analyze the data.

A structural equation model indicates that perceived usefulness and ease of use significantly affect attitude and behavioral intention. Moreover, the outcomes show that perceived value and social influence significantly influence, while perceived risks and performance expectancy insignificantly affect behavioral intention. Further, the outcomes also confirm that attitude and behavioral intention substantially influence mobile banking adoption.

The article provides insights for practitioners to improve and assess the quality of mobile banking services by using proposed antecedents that may increase the actual use of FinTech services, which serves as a valuable resource for stakeholders.

The new research model adds to the existing literature by offering empirical evidence of mobile banking adoption by considering three theories. Further, the study builds upon the S-O-R framework that incorporates FinTech attributes to explain the antecedents of the actual use of FinTech towards mobile banking adoption.

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.