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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]

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]

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 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]