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This research aims to forecast university students' intentions to contribute to sustainable entrepreneurship (SE) in an emerging market. The study observed the factors influencing students’ sustainable entrepreneurial intentions (SEI) using an extended theory of planned behaviour (TPB).

A survey was conducted utilising an online questionnaire with a total of 332 college students in Gujarat, India. Partial least squares-structural equation modelling (PLS-SEM) was used to analyse the data.

The outcome of the present research sanctions that university support strongly impacts perceived behavioural control (PBC) and negatively affects attitudes towards sustainable entrepreneurship (ATT). The findings revealed that environmental concern positively influences students' attitudes and perceived behavioural control towards sustainable entrepreneurship. Whereas sustainable development goals knowledge (SDGK) negatively impacts attitude and PBC. Out of the three key factors of TPB used in the study, only the subjective norm negatively affects SEI among the respondents.

This research may be valuable to academicians and environmental strategists in determining the most essential elements that drive students to create sustainable firms. The findings of this study back up the assumption that TPB adaptation is required when assessing entrepreneurship-specific intents.

The current research aimed to regulate students' entrepreneurial intention (EI) in Gujarat, India, concerning a sustainable enterprise. This research appears to be one of the extremely scarce studies that utilise the extended TPB model to investigate the effect of university support (US), environmental concern (EC) and SDGK in the context of India.

The purpose of this paper is to understand the market for various e-learning platforms existing globally. The global pandemic transformed the traditional education sector into an e-learning industry and impacted the digital education sector proportionally. The wide impact on people to maintain a social distance shortened the space and enhanced student engagement with digital screens. The merchandise of electronic gadgets and e-learning platforms boosted global revenues ever before.

A digital data analytical tool retrieved the data for e-learning companies. While screening companies, the authors came up with more than 150 and later narrowed it to 71. Furthermore, revenues and market capitalisation data were collected from open-source websites of respective e-learning platforms at national and international stock exchanges. The data from the year 2018 to 2021 was used to predict the compound annual growth rate (CAGR) of the 2022–2027 market value of e-learning companies. The demographics of the statistical data were plotted using GraphPad Prism and Python Plotly. Also, the study attempted to underpin the association of annual revenue with market capitalisation for e-learning companies using Statistical Package for the Social Sciences (SPSS).

The financials of the e-learning platforms were compared from 2018 to 2021 based on the stock market exchange, which showed a gradual increase in revenues and influenced the market capitalisation by the 2022 financial year. Also, simultaneously validating the CAGR of 13.16%, the expected revenues from 2022 to 2027 were $830bn. The data plotted on the atlas choropleth exhibiting the e-learning users increased globally by 2022. The Web traffic data validated by the browsing gadget helped to validate the increase in revenues of the electronic gadget companies.

To the best of the authors’ knowledge, this is one of the pioneer studies postulating the study of e-learning demographics comparing the e-learning influence on the global digital market, Web user traffic and the education sector. The demographics of e-learning users by age, gender and gadget distribution validate the e-learning induction globally.

This study aims to identify factors affecting Generation Z (Gen-Z)’s online learning (OL) behavioural intention (BI) using the extended technology acceptance model by investigating gender differences in the BI of Indian students to adopt OL.

The proposed model was tested on 284 students from a higher education institution (HEI) in Gujarat, India, using the partial least square–structural equation modelling. Further, the subgroup analysis was conducted using Statistical Package for Social Sciences (SPSS) to determine male and female OL adoption variances.

Based on the research findings, all the constructs positively influence the BI of Gen-Z to adopt OL, except the influence of information technology infrastructure (INF) on perceived usefulness (PU). However, no substantial difference was observed in the BI adoption of OL amongst males and females. Also, when gender was kept as a moderator between computer self-efficacy (CSE) and PU, and INF and perceived ease of use (PEU), no substantial difference was observed in the OL of Gen-Z.

The study will benefit HEIs and associated government departments from a deeper understanding of Gen-Z’s BI to speed up deployment and consider key elements essential while considering OL.

This article found major determinants of Gen-Z’s BI to adopt the OL in HEI. To the best of the author’s understanding, this is amongst the few studies to explore these ideas in the context of India. The uniqueness of the topic has been brought to light by the fact that “gender” has been employed as a moderator between attitude and BI, INF and PEU, and CSE and PU.

The study aims to shed light on the role of university support (US), environmental concern (EC) and Sustainable Development Goal knowledge (SDGK) in forming students' intention (SI) to engage in sustainability-driven entrepreneurship. The authors attempted to blend the theory of planned behaviour (TPB) and social cognitive career theory (SCCT) as a potentially useful theoretical base for sustainability-driven entrepreneurial intention (SDEI) development.

The responses were collected from university students in India using a self-administered questionnaire. Confirmatory factor analysis (CFA) and partial least squares structured equation modelling (PLS-SEM) are used to examine the data.

The university support strongly influences students' attitudes towards sustainable entrepreneurship (ATT) and outcome expectations (OEs). Also, the degree of understanding about SDGs among students was alarmingly low, which has crucial negative consequences for future SDG achievement.

The findings of this study may assist academicians and environmental strategists in deciding the crucial factors influencing SI to start a sustainable business. The study highlights the importance of universities in promoting entrepreneurial sustainability decisions.

This research will add value to the prevailing literature in the area of sustainable entrepreneurship as it explores the effects of environmental concern, SDGK and the role of US on sustainable entrepreneurial intention (EI) among Indian engineering students.