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The purpose of the study is to explore the various determinants of virtual communication technology (VCT) adoption among higher educational leaders by applying Unified Theory of Acceptance and Use of Technology 3 (UTAUT3) model. Further, this study ascertains the relationship among the various determinants and measure the effects of these determinants in adoption of VCT by educational leaders.

The study was conducted by using online survey method for data collection from 380 educational leaders of India through a convenience sampling procedure. The structural equation modelling technique was adopted to assess the dimensions of VCT adoption and test the proposed model and hypotheses.

The findings revealed that performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating conditions (FC) and personal innovativeness (PI) have positive and significant effects on intention to use VCT (ITUVCT) and actual use of VCT (AUVCT), i.e. e-leadership communication adoption. Besides this, there is also a significant and positive effect of ITUVCT on actual usage of VCT by the educational leaders.

This study makes its contribution to the literature related to technology adoption recommended in previous research for expanding the contexts through new studies and generalizing the UTAUT3 model, specifically in the teaching–learning and administrative perspectives. The results of the study will be further helpful for the researchers and practitioners to better understand the factors that influence higher educational leaders to adopt VCT.

The authors applied the UTAUT3 model and explored the factors determining the adoption intention of VCT among educational leaders. This study is the first study that adopts UTAUT3 model in Indian educational leaders’ context.

This study investigates the determinants of digital census for population and housing census (PHC) program through the lens of performance expectancy, technology readiness, self-efficacy and hedonic motivation for the upliftment of a national data collection exercise and development of human resource management.

A quantitative and qualitative research method was used to survey enumerators' responses from the PHC exercise during the COVID-19 period in Ghana. Based on the four determinants, a conceptual framework was developed consisting of eight proposed hypotheses tested through a structural equation model.

The findings of the study indicate that technological readiness, self-efficacy and hedonic motivation significantly influence behavioural intention to adopt digital technologies for PHC training and data collection. Importantly, the authors identified four key themes relating to digital technologies in PHC – personal enablers, general enablers, inherent affordances (inherent possibilities by the user in relation to what the technology offers in context) and personal inhibitors.

For research, this work systematizes antecedents from diverse research streams and validates their relative impact on government digital transformation for accurate data, thus providing a cohesive theoretical explanation of digital technologies in PHC. Due to the study's infancy in a developing country context, the findings provide a preliminary foundation and constructive insight for a digitalization plan conducive to people’s personality and technological readiness.

The authors aim to study a conceptual model based on behavioural theories (UTAUT-3 model) to evaluate the adoption, usage and recommendation for neobanking services in India.

The authors propose this model based on the UTAUT-3 integrated with perceived risk constructs. Hypotheses were developed to determine the relationships and empirically validated using the PLSs-SEM method. Using the survey method, 680 Delhi NCR respondents participated in the survey.

Empirical results suggested that behavioural intention (BI) to usage, adoption and recommendation affects neobanking adoption positively. The research observed that performance expectancy (PE), effort expectancy (EE), perceived privacy risk (PYR) and perceived performance risk (PPR) are the essential constructs influencing the adoption of neobanking services.

Limited by geographic and Covid-19 constraints, a cross-sectional study was conducted. It highlights the BI of neobanking users tested using the UTAUT-3 model during the Covid-19 period.

The study's outcome offers valuable insights into Indian Neobanking services that researchers have not studied earlier. These insights will help bank managers, risk professionals, IT Developers, regulators, financial intermediaries and Fintech companies planning to invest or develop similar neobanking services. Additionally, this research provides significant insight into how perceived risk determinants may impact adoption independently for the neobanking service.

The objective of this study was to analyse the effects of major determinants on VCT adoption intention among higher educational leaders. Also, this study aims to investigate how perceived risk and perceived benefits influence the educational leaders, VCT actual use intention.

The authors used the online survey method to collect the 440 responses through purposive sampling procedure. Structural equation modelling (SEM) technique and Multi Group Analysis procedure were used to test the proposed model and moderating effects.

The findings revealed that all the four determinants (PE, EE, SI and FC) based on UTAUT model have positive and significant effects on intention to use VCT. Besides this there is a significant and positive effect of intention to use VCT on actual usage of VCT by the educational leaders. The moderating effect of perceived risk and perceived benefits on actual usage of virtual communication also found significant.

This paper makes its contribution to the literature related to virtual communication technology adoption by including two moderator variables (perceived risk and benefits) that are expected to affect educational leaders' actual usage of VCT. The results can also help researchers and practitioners better understanding the factors that influence higher educational leaders to adopt VCT.

This study proposed a model incorporating the perceived risk and perceived benefits in the UTAUT model to predict the actual use of VCT. The study endeavours to investigate the moderating effects of perceived risk and perceived benefits between ITUVCT and AUVCT in Indian educational context.

This paper combines prospect theory (PT) and the technology acceptance model (TAM) proposing that technology anxiety (TA), risk averseness (RA), concern and resistance to use inhibit technology acceptance, while trust, social influence (SI) and compatibility are enablers to technology acceptance, particularly in the context of consumer adoption of retail technologies during crises.

A review of PT and TAM literature was conducted to develop a model which considers the impact of inhibitors and enablers on retail technology acceptance.

This investigation establishes a theoretical model of mid-crisis retail technology adoption behavior that can be tested quantitatively. Several propositions regarding relationships between proposed inhibitors, enablers and TAM are presented, as well as implications for future research.

This investigation further integrates PT and TAM, proposing that PT is an appropriate framework to investigate inhibitors and enablers of retail technology acceptance during crises.

The authors constructed an automatic essay scoring (AES) model in a discussion forum where the result was compared with scores given by human evaluators. This research proposes essay scoring, which is conducted through two parameters, semantic and keyword similarities, using a SentenceTransformers pre-trained model that can construct the highest vector embedding. Combining these models is used to optimize the model with increasing accuracy.

The development of the model in the study is divided into seven stages: (1) data collection, (2) pre-processing data, (3) selected pre-trained SentenceTransformers model, (4) semantic similarity (sentence pair), (5) keyword similarity, (6) calculate final score and (7) evaluating model.

The multilingual paraphrase-multilingual-MiniLM-L12-v2 and distilbert-base-multilingual-cased-v1 models got the highest scores from comparisons of 11 pre-trained multilingual models of SentenceTransformers with Indonesian data (Dhini and Girsang, 2023). Both multilingual models were adopted in this study. A combination of two parameters is obtained by comparing the response of the keyword extraction responses with the rubric keywords. Based on the experimental results, proposing a combination can increase the evaluation results by 0.2.

This study uses discussion forum data from the general biology course in online learning at the open university for the 2020.2 and 2021.2 semesters. Forum discussion ratings are still manual. In this survey, the authors created a model that automatically calculates the value of discussion forums, which are essays based on the lecturer's answers moreover rubrics.