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On-demand work applications (ODWAs), a type of digital platforms (DPs), are technology-enabled intermediaries for gig workers. In this paper, we study these platforms and their impact on women belonging to the low socio-economic section in a developing economy. These women act as primary unpaid workers while being expected to make an economic contribution. Hence, they suffer from time scarcity where they need to find mechanisms to generate economic success from the limited time they have, in a largely informal economy. We employed the theoretical lens of affordances to delineate the affordances that are provided by the various features of ODWAs and their impact on life satisfaction of women. We conducted a mixed method study using interviews of 20 female gig workers, supplemented by a survey of 927 workers on one of the largest ODWAs in India. Our analysis points to the sense of identity and individuality that these platforms provide as well as lowering the market boundaries for greater inclusion. Our research is significant from both, the information systems and inclusion research perspectives, as it contributes to the theoretical understanding of the impact of DPs on breaking societal structures and providing avenues to marginalised sections. [ABSTRACT FROM AUTHOR]

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]

This paper explores the different insider employee-led cyber frauds (IECF) based on the recent large-scale fraud events of prominent Indian banking institutions. Examining the different types of fraud and appropriate control measures will protect the banking industry from fraudsters. In this study, we identify and classify Cyber Fraud (CF), map the severity of the fraud on a scale of priority, test the mitigation effectiveness, and propose optimal mitigation measures. The identification and classification of CF losses were based on a literature review and focus group discussions with risk and vigilance officers and cyber cell experts. The CF was analyzed using secondary data. We predicted and prioritized CF based on machine learning-derived Random Forest (RF). An efficient fraud mitigation model was developed based on an offender-victim-centric approach. Mitigation is advised both before and after fraud occurs. Through the findings of this research, banks and fraud investigators can prevent CF by detecting it quickly and controlling it on time. This study proposes a structured, sustainable CF mitigation plan that protects banks, employees, regulators, customers, and the economy, thus saving time, resources, and money. Further, these mitigation measures will improve the reputation of the Indian banking industry and ensure its survival. [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]

The ability to exploit students' sentiments using different machine learning techniques is considered an important strategy for planning and manoeuvring in a collaborative educational environment. The advancement of machine learning technology is energised by the healthy growth of big data technologies. This helps the applications based on Sentiment Mining (SM) using big data to become a common platform for data mining activities. However, very little has been studied on the sentiment application using a huge amount of available educational data. Therefore, this paper has made an attempt to mine the academic data using different efficient machine learning algorithms. The contribution of this paper is two-fold: (i) studying the sentiment polarity (positive, negative and neutral) from students' data using machine learning techniques, and (ii) modelling and predicting students' emotions (Amused, Anxiety, Bored, Confused, Enthused, Excited, Frustrated, etc.) using the big data frameworks. The developed SM techniques using big data frameworks can be scaled and made adaptable for source variation, velocity and veracity to maximise value mining for the benefit of students, faculties and other stakeholders. [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]

A key agenda of policy-makers in both the developing and the developed worlds is to have an inclusive growth. Financial services have been recognised as one of the fundamental services that have the potential to achieve this objective and help move towards a more just and equitable society. This paper attempts to assess the impact of three information and communication technology-driven initiatives in the field of financial services by differentiating them on the basis of service design. This study goes beyond the stated objective of these services and uses Sen’s capability perspective to study their impact across three non-economic outcome variables viz. literacy, service-specific well-being and empowerment. The data for the study are collected from the urban poor across different locations in a large metropolitan city in South India where the three different services are being offered. The study follows a quasi-experimental design (field study) and ensures matching of the treatment and control groups through propensity score matching. The matched data are analysed using an independent samplet-test. The result of the analysis shows that service design plays a key role in increasing service literacy, improving service-specific well-being and empowering end users. The study suggests that the true challenge for providers (government and partner agencies) of these services is in designing a service that ensures a balance of structure and flexibility without constraining the choice of end users through innovative service blueprints. [ABSTRACT FROM AUTHOR]

Daily stand-up meetings (DSMs) are the most popular technique in agile methodologies and are deemed crucial for communication among the individual agile software developers to perform. Only a handful of studies in the past have shown the effect of the characteristics of DSMs on the attitude of agile developers. Little is known about how agile developers experience DSMs in their roles as junior/senior developers, and what feelings evoke these experiences. The purpose of this study was to describe and interpret agile developers' lived experiences with DSMs in their diverse roles. We conducted a hermeneutic phenomenological study with 19 professional agile developers. The lived experiences across the interviews revealed as an interaction between four categories: rationalising irrelevancy of DSMs, experiencing challenges with DSMs, conflicted opinion on the advantages of DSMs, and finding solutions. Developers experienced DSMs were too short to facilitate clear problem identification, or solve problems, or have a meaningful outcome. Senior developers experienced DSMs differently than junior developers in terms of sharing information, interest in other's work, monitoring progress, and facilitating decision making. Based on these findings, we discuss the theoretical contributions of our study, and offer recommendations for practitioners. [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]

This study investigates and compares the continuance intention of full-time business school students and faculty in India and Italy who moved from traditional pedagogy style to the digital classroom due to the COVID-19 pandemic. The study integrates the Expectation Confirmation Model (ECM) and Task-Technology Fit (TTF) to examine their continuance intention. Survey data was collected from 396 business school students and 130 faculty members from India and Italy and analysed using SmartPLS 3 software. The study found that perceived usefulness, satisfaction, and task-technology fit significantly impact the continuance intentions of students and faculty. Multigroup analysis of students indicates that Italian students are more driven by task-technology fit as compared to Indian students in their continuance intention; in comparison, Indian students rely more on gaining experience and knowhow on technology. Finally, the multigroup study of faculty suggests that Italian educators have a comparatively stronger orientation towards the fit between digital classroom technology and a portfolio of related tasks. In comparison, their Indian counterparts rely more on the perceived usefulness of technology. The strength of relationship between task-technology fit and continuance intention is comparatively lower for faculty as compared to students in both countries. Finally, implications for theory and practice are discussed. [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]

This study contributes to the literature that advocates the use of consumer segmentation by family life cycle (FLC) stages, which are found to have a greater influence on changes occurring in an individual’s life than age. It addresses the youth bias of most research on e-shopping adoption and the emergence of older e-shoppers as an attractive market segment by covering women of all age groups. It evaluated the effect of perceptions and attitudes towards e-shopping acceptance, as well as their variations across FLC stages, by using the technology acceptance model. The 10 FLC stages were selected by modifying the Duvall FLC classification system to reflect the Indian context. The results show that the different FLC stages have a significant impact on the e-shopping behaviour of women. While deals and discounts were found to influence all groups, time-saving and better decision-making through online shopping sites also significantly influenced e-shopping behaviour. Furthermore, the perceived usefulness and/or attitude were important factors that directly affected e-shopping technology adoption and usage patterns across a majority of the FLC stages. The study proved that FLC stages had greater power than age in explaining e-shopping adoption and e-retailers should not ignore them in designing e-marketing applications. [ABSTRACT FROM PUBLISHER]

Over the last few years there has been an increased emphasis on conceptualising, developing, and implementing virtual Learning initiatives across the Indian education sector. Effective and successful use of Virtual Learning Environments (VLEs) in academic setting requires identifying and solving many important social and behavioural issues. Without identifying and addressing these issues, their use can compound the mistakes of the past and leave the learner with a passive, un-engaging experience, leading to incomplete learning and low performance. Therefore, educators are required to recognise learner’s attitude, readiness, and learning style to take advantage of VLE. This study was conducted to find interrelationship of student attitude, readiness, and learning style towards the effective use of VLE. A total of 240 students who are using any form of VLE for their learning and research volunteered for the research, and the scales were filled via the convenience sampling method. The scales of learning readiness, attitude, and learning style were administered to the participants. The relationship among the variables of the research and the research hypotheses for the model were tested using different statistical tools like correlation,t-test and regression. The research result revealed that there is a correlation among learning readiness, attitude, and learning style, and each of these factors influence the effective use of VLE. [ABSTRACT FROM PUBLISHER]

‘Selfie’, the Oxford Dictionary’s word of the year in 2013, has been gaining popularity as a global phenomenon and its usage is growing with technological advancements in front-facing cameras and photo-editing software. Earlier studies hold a lopsided view of either criticising selfies as ‘vain’ and ‘narcissist’ or appreciate them as ‘feel good’ for ‘positive identity formation’. The current study intends to take a fresh look at the act and explores reasons and motivators of young college students in India, as they take selfies and traces the usage pattern and its likely relationship with the motivators of selfie-taking. Qualitative data were gathered through a focused group discussion conducted among graduate students with an average of 23.5 years who volunteered to participate in the discussion. Results show that male and female students have varying reasons for taking selfies and it is often an act of fun and assertion of one’s right to ‘self-depiction’. Selfies have a life-cycle which ends after they receive reviews on the social media platform. Results from the study can aid policy-makers in India and theoretically add to the nascent field of literature in the area. [ABSTRACT FROM AUTHOR]