The theoretical basis for studying the phenomenon of Global Software Development (GSD) draws upon one of the key research streams, that is, the Organizational Behavior (OB) research. The focus of this study has led to two research problems: partnership quality and service climate aspects are addressed which have given an insight into the OB research on GSD teams. Moreover, this study classifies results from the partnership quality and service climate aspects into one integrated framework, which covers 18 attributes to explore the GSD outcome factors perceived by GSD teams in OB research phenomenon. To evaluate partnership quality and team service climate aspects with reference to the GSD project outcome, we have integrated the fuzzy Decision-Making Trial and Evaluation Laboratory Model (DEMATEL) and the Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) approach, which is more appropriate to find the significance of criteria. The empirical application of this hybrid approach for evaluating GSD project outcome factors has been tested in Indian software organizations. Consequently, the results of this study provide a vivid picture and facilitate the organization to reveal the importance of OB research on GSD teams.

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The technology-driven era has encouraged Malaysians to use e-Wallet rather than paper money in their daily transactions. Numerous e-Wallet applications have been developed, such as GrabPay, Touch 'n Go eWallet, and Boost. Erstwhile, Malaysians perceived that using e-Wallets is troublesome and worthless. However, the COVID-19 outbreak has reframed the buyers' perceptions otherwise. This study investigates the impact of Covid-19 on consumer behavior towards the intention to use e-Wallet in Malaysia. A sample of 100 Malaysians has voluntarily participated in this survey. Data were assembled through an electronic survey questionnaire. Contrary to popular belief, the findings depicted that the behavioral intention to use e-Wallets among Malaysians had further accelerated due to the convenience perceptions, facilitating conditions, and perceived safety.

It is known that big data has penetrated several if not all spheres of life. In higher education, the ability to take these large amounts of data and process it into something meaningful for academic decision making is commonly referred to as learning analytics. This chapter provides an overview of learning analytics and its importance, as well as identifying academic data sources, techniques used for learning analytics and prediction, and data visualisation techniques used to present analysis for better understanding and eventual decision making. It also includes a discussion of learning analytics frameworks for research and some identified research challenges.

Aim/Purpose: The paper’s objective is to examine the challenges of using the mobile phone to mine location data for effective contact tracing of symptomatic, pre-symptomatic, and asymptomatic individuals and the implications of this technology for public health governance. Background: The COVID-19 crisis has created an unprecedented need for contact tracing across South Africa, requiring thousands of people to be traced and their details captured in government health databases as part of public health efforts aimed at breaking the chains of transmission. Contact tracing for COVID-19 requires the identification of persons who may have been exposed to the virus and following them up daily for 14 days from the last point of exposure. Mining mobile phone location data can play a critical role in locating people from the time they were identified as contacts to the time they access medical assistance. In this case, it aids data flow to various databases designated for COVID-19 work. Methodology: The researchers conducted a review of the available literature on this subject drawing from academic articles published in peer-reviewed journals, research reports, and other relevant national and international government documents reporting on public health and COVID-19. Document analysis was used as the primary research method, drawing on the case studies. Contribution: Contact tracing remains a critical strategy in curbing the deadly COVID-19 pandemic in South Africa and elsewhere in the world. However, given increasing concern regarding its invasive nature and possible infringement of individual liberties, it is imperative to interrogate the challenges related to its implementation to ensure a balance with public governance. The research findings can thus be used to inform policies and practices associated with contact tracing in South Africa. Findings: The study found that contact tracing using mobile phone location data mining can be used to enforce quarantine measures such as lockdowns aimed at mitigating a public health emergency such as COVID-19. However, the use of technology can expose the public to criminal activities by exposing their locations. From a public governance point of view, any exposure of the public to social ills is highly undesirable. Recommendations for Practitioners: In using contact tracing apps to provide pertinent data location caution needs to be exercised to ensure that sensitive private information is not made public to the extent that it compromises citizens’ safety and security. The study recommends the development and implementation of data use protocols to support the use of this technology, in order to mitigate against infringement of individual privacy and other civil liberties. Recommendation for Researchers: Researchers should explore ways of improving digital applications in order to improve the acceptability of the use of contact tracing technology to manage pandemics such as COVID-19, paying attention to ethical considerations. Impact on Society: Since contact tracing has implications for privacy and confidentiality it must be conducted with caution. This research highlights the challenges that the authorities must address to ensure that the right to privacy and confidentiality is upheld. Future Research: Future research could focus on collecting primary data to provide insight on contact tracing through mining mobile phone location data. Research could also be conducted on how app-based technology can enhance the effectiveness of contact tracing in order to optimize testing and tracing coverage. This has the potential to minimize transmission whilst also minimizing tracing delays. Moreover, it is important to develop contact tracing apps that are universally inter-operable and privacy-preserving.