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Numerous studies have captured the experiences of teachers teaching online, but the current 'emergency' to teach online is unprecedented and has been challenging. Grounded in the theory of cognitive dissonance, this paper attempts to recapitulate the experiences of university teachers and analyses whether they have developed the consonant cognitions to teach online during the pandemic period or would they prefer switching back to 'normal' teaching as soon as the circumstances permit. Technology-enabled teaching has been found to be complex as it mandates teaching in a computerised setting and lacks an element of social interaction, which is at the heart of face-to-face teaching. Using Structural Equation Modelling, this study presents the determining factors that motivate teachers to embrace technology-driven teaching more convincingly. The study finds that in the absence of adequate training imparted to the teachers for developing technological and pedagogical knowledge (TPK), high psychological capital and facilitating conditions are the two most important factors ensuring teaching proficiency, creating positive online experiences and a continued intention to teach online. [ABSTRACT FROM AUTHOR]

The paper examines the multi-dimensional nature of Internet Addiction (IA) and its influence on Well-Being (WB) amongst a representative sample of 320 young urban Indian internet users. Nine hypotheses are proposed through a conceptual model to assess the multi-dimensional nature of IA and its relationship with WB. Partial Least Squares – Structure Equation Modelling (PLS-SEM) was conducted to assess the hypothesised relationships. Of the proposed nine hypotheses, seven were accepted. The result indicated IA as a four-dimensional construct – Internet Control Disorder (ICD), Internet Craving (IC), Internet Obsession (IO), and Addictive Behaviour (AB). The findings supported that ICD positively and significantly influences IC. IC and AB both have a significant impact on IO. ICD and IC have a significant impact on the individual's AB. ICD and IO significantly influence WB. With respect to the dimensions IC, AB, and IO, the model is successful in explaining around 26%, 45%, and 33% of the variation. IA as a multi-dimensional phenomenon and its relationship with WB in a young-demographic nation like India has immense academic and societal value. The study provides critical actionable insights for users, educators, health counsellors, parents, and policymakers regarding interventions for controlling internet addiction. [ABSTRACT FROM AUTHOR]

Internet technology has flourished in India keeping pace with other developing countries. In keeping pace with this advancement, the Internet of Things (IoT) technology is also spreading in India. Government of India (GOI) has realised IoT's business prospect and published draft policy on IoT in 2015. To achieve a better result, the prospective users are required to be kept aware regarding the prospect of IoT and for this, social media is expected to play a pivotal role. Social media can highlight advantages of IoT and in turn, these advantages would be made known to other potential users through Word of Month (WOM). This would bring in projection of a new business paradigm as contemplated by GOI. The purpose of this paper is to identify the factors affecting actual use of IoT by the potential users of India and to develop a conceptual model. The model has been verified through survey with inputs from 208 participants identified from three metropolitan cities of India. The responses have been quantified through 5-Point Likert scale. The result shows the implication that social media and WOM almost equally influence Indians to use IoT. [ABSTRACT FROM AUTHOR]

This study aims to identify the critical factors influencing the user experience of contact tracing apps and the sentiments around them. For this purpose, we used Google play reviews of Aarogya Setu, a contact tracing app developed in India. First, we establish the relationship between review sentiment and review rating using regression between sentiment polarity and review rating. Then, we used a hybrid aspect-based sentiment analysis approach that uses unsupervised linguistic techniques to determine statistically significant concepts present in the review texts and cluster them into representative aspects that were then tagged under human supervision. Finally, supervised deep learning methods were applied for exhaustive extraction of the aspects and associated sentiments from the reviews. The final exercise of determining the key influencing factors was done by grouping these aspects under factors identified by marketing experts. A total of nine factors were identified, with the usefulness of the app being the most important factor. The findings of this study are essential for the development team and government to improve the application and increase adoption. [ABSTRACT FROM AUTHOR]

The purpose of this study is to investigate the factors underlying the adoption, completion and continuance of massive open online courses (MOOCs), using technology-user-environment (TUE) framework, MOOCs features and MOOCs qualities. The proposed model was empirically tested using longitudinal research design. The primary data was gathered at three time points through a survey of 197 students at an Indian university. Stepwise regression analysis was used to test the hypothesised relationships in the proposed model. The results demonstrate that technological characteristics, user characteristics and MOOCs features influence the students' decisions in all the stages of MOOCs acceptance including initial adoption, completion and continuance. Environmental factors determine the students' initial intentions to adopt MOOCs, whereas MOOCs qualities predict their intentions to complete and continue the usage of MOOCs in future. Moreover, the intention to adopt MOOCs significantly predicts the intention to complete MOOCs which in turn significantly determines the intention to continue using MOOCs. These findings will be helpful for MOOCs providers and other stakeholders. The MOOCs providers can focus on the technological characteristics, user characteristics and MOOCs features as they carry a sustained influence on the students' intentions to adopt, complete as well as continue using MOOCs. [ABSTRACT FROM AUTHOR]

The 'smartphone addiction' is a popular theme in media. It has number of clear behavioural changes in addicts' life and some of these aspects are yet to get due research attention. The present study identifies antecedents of smartphone addiction and its associated conflicts. The findings are based on data collected from adolescents, who are major targets for smartphone advertising and also vulnerable to addictions. The findings established 'loneliness' and 'self-regulation' as the main antecedents for smartphone addiction along with family, personal conflicts and poor academic performance as the significant negative consequences of its excessive use. The study findings would help to create awareness and offer insights for developing effective interventions for addressing smartphone addiction amongst adolescents. The planners, regulatory and administrative authorities will use the study findings to formulate measures that would promote positive coping mechanism to prevent smartphone addiction among adolescents. [ABSTRACT FROM AUTHOR]

We drew on the unified theory of acceptance and use of technology (UTAUT2) model, and perceived risk construct to propose an integrated model to explain continuance usage of mobile shopping applications. Espoused national cultural values of individualism/collectivism, masculinity/femininity, power distance, uncertainty avoidance, and long-term/short-term orientation act as moderators to examine the influence of within-culture variation on app usage. Findings reveal habit as the strongest predictor of both continuance intention and use behaviour, but interestingly perceived risk did not influence the post-acceptance behaviour of users significantly. Individualism/collectivism, masculinity/femininity, and long-term/short-term orientation espoused cultural values significantly moderated the relationships in the model. Noteworthy theoretical and managerial implications of the research are discussed further. [ABSTRACT FROM AUTHOR]

Business Management Education in India has shown an upward growth trend in the last couple of decades. Due to the diverse nature of the course, students from diverse academic backgrounds are being admitted to the course. Therefore, differences in students’ abilities and their learning styles have a significant effect on their learning outcomes. Meanwhile, with the development of learning technologies, learners can be provided a more effective learning environment to optimise their learning. The purpose of this study was to develop a model to automatically detect the students’ learning styles from their personal, academic and social media data and make recommendations for students, teachers, educators and administrators for overall improvement of learning outcomes. Data analysis in this research was represented using data collected from post-graduate business management students in India. A 10-fold cross-validation was used to create and test the models. The data were analysed by R and R-Studio. Classification accuracy, Precision, Recall, Kappa, ROC curve and F measure were observed. The results showed that the accuracy of classification by the C4.5 technique had the highest value at 95.7%, and it could be applied to develop Felder-Silverman’s learning style while taking into consideration students’ academic, personal information and social media preferences. [ABSTRACT FROM AUTHOR]