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The online learning environment is a function of dynamic market forces constantly restructuring the e-learning landscape’s complete ecosystemcape. This study aims to propose an e-learning framework by integrating the Technology Acceptance Model (TAM) and Theory of Planned Behaviour (TPB) to predict students’ Online Learning Readiness and Behaviour.

A structured questionnaire was used to collect data from 406 students through a survey. The data were analysed using two-stage structural equation modelling and artificial neural network (ANN).

The study’s results revealed that perceived ubiquity (PUB) positively influences perceived ease of use, usefulness and attitude. Similarly, perceived mobility significantly influences perceived ease of use and attitude. Furthermore, attitude, subjective norms, perceived behavioural control and perceived usefulness significantly influence readiness to learn online, which further influences students’ online learning behaviour. The root-mean-square error (RMSE) values obtained from the ANN analysis indicate the models’ predictive solid accuracy.

The study contributes to the existing literature by proposing an Online Learning Behaviour Model by integrating the TAM and the TPB frameworks in association with two additional constructs, PUB and Perceived Mobility. Secondly, this study proposes a unique triangulation framework of recommendations for learners, educators and policymakers.

Augmented Reality (AR) and Virtual Reality (VR) technologies possess the potential to transform the scenario of making real estate investment decisions through the immersive experience they offer. From the literature it was observed that the research in this domain is still emergent and there is a need to identify the latent variables that influence real estate investment decisions. Therefore, by examining the effects of these technologies on investment decision-making, the purpose of the study is to provide valuable insights into how AR and VR could be applied to enhance customers' property buying experiences and assist in their decision-making process.

From an extensive review of the literature four latent variables and their measure were identified, and based on these a survey instrument was developed. The survey was distributed online and received 300 responses from the respondents including home buyers, developers, AEC professionals and real estate agents. To validate the latent variables exploratory factor analysis was used whereas to establish their criticality second-order confirmatory factor analysis was used.

From the results, the four latent constructs were identified based on standard factor loadings (SFL) that is Confident Value Perception (CVP, SFL = 0.70), Innovative Investment Appeal (IIA, SFL = 0.60), Trusted Property Transactions (TPT, SFL = 0.58) and Effortless Property Engagement (EPE, SFL = 0.54), that significantly influence investor decision-making and property purchase experience.

This study contributes to the literature on real estate investment decisions by providing empirical evidence on the role of AR and VR technologies. The identified key variables provided practical guidelines for developers, investors and policymakers in understanding and leveraging the potential of AR and VR technologies in the real estate industry.

ChatGPT, a cutting-edge language model, stands as an unparalleled, unmatched conversational ally, showcasing novel versatility and intelligence in its responses. This research delves into the incorporation of ChatGPT, a powerful generative AI tool, into professional communication. This study utilizes the information system success model (ISSM) to examine the role of ChatGPTs in strengthening information quality (IQ), system quality (SQ) and service quality (SEQ) for improving customer usage intention (UI) and satisfaction (SAT). The study also investigates the moderating impact of perceived innovativeness between these relationships.

The research collected data from a sample of 400 customers through an online survey and validated the hypothesized relationships using structural equation modelling (SEM). Process Macros 4.1 in SPSS 22.0 is used to test the moderating role of perceived innovation between IQ, SQ and SEQ and UI and SAT.

The results of SEM analysis indicate that IQ, SQ and SEQ all positively support UI to use ChatGPT for professional communication with SAT. The result also establishes that perceived innovativeness positively moderates the relationship between IQ, SQ and SEQ and UI and SAT.

This research study offers novel contributions to the literature and body of knowledge by establishing the moderating role of perceived innovativeness in strengthening the relationship between IQ, SQ and SEQ and UI and SAT. Further, this study also proposes a 2*2 matrix to segment the UI and SAT of ChatGPT users in professional communication with varying degrees of perceived innovativeness.