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International Journal of Big Data Management (4 papers in press)
A mapping of the factors related to self-disclosure on social network sites by Mahamadou Kante Abstract: Privacy is a critical concern in big data era. Users share their personal data to informal communities such as social media. Despite the evident benefits of social network sites and users concerns about privacy, people disclose personal information. Albeit users know the conceivable risks of sharing personal information, more users are doing so. It is important to identify the factors affecting self-disclosure on social network sites. In this paper, the audience is informed about these factors. Using a systematic approach, models/theories used in self-disclosure researches on social network sites were identified. It was observed that the convenience of building and maintaining relationships, social ties and norms, and expected outcomes are positively affecting while privacy concerns are negatively affecting. It was also found that the level of trust, perceived control and perceived similarity can affect online behaviour towards self-disclosure. The paper closes by proposing future line of inquiries. Keywords: big data; privacy paradox; self-disclosure; social network services; SNSs; social network sites. DOI: 10.1504/IJBDM.2020.10034496
Big Data Analytics Capability for Digital Transformation in the Insurance Sector by CHRISTOPHER MOTURI, Vincent O. Okemwa, Ochieng Daniel Abstract: In order for organisations to generate competitive advantages from big data investments, they need to acquire a unique blend of technology, human skills, financial resources and a data-driven culture. Organisations need to measure their big data analytics capability in order to yield competitive performance. This study sought to examine the relationship between a firms big data analytics capability (BDAC) and competitive performance through mediating role of dynamic and operational capabilities. To test the proposed research model, we used survey data from 110 employees across 54 insurance companies in Kenya. Using partial least squares structural equation modelling, the results provide evidence that BDAC leads to superior firm performance. Various resources that form big data analytics (BDA) capability have been identified and an instrument to measure BDAC proposed. The findings from this study provides a roadmap strategy for implementing BDA projects. Keywords: big data; big data analytics; BDA; big data analytics capability; BDAC; dynamic capabilities; operational capabilities; competitive performance. DOI: 10.1504/IJBDM.2020.10034709
Blockchain Law by Antonios Maniatis Abstract: Very few studies have been made on the question of normativity relevant to the blockchain technology, initiated with the proposal for the cryptocurrency bitcoin (BTC). The purpose of the current study is to examine the status of norms relevant to blockchain, emphasising the question whether it is about a field of law. In the short period of its existence, blockchain has already enacted an important role, in both aspects of legality and illegality. The current research takes an approach to some cases of criminality being relevant to blockchain and to mainstreaming applications of this technology, by analysing particularly the literature on the matter. The outcome of this paper consists not only in the view that a field of law has emerged, called blockchain law, against the generic branch of internet law, but also in the finding that in a parallel way traditional institutions and legal branches are in motion, towards new rights and institutions. Keywords: automation; blockchain law; bitcoin; BTC/XBT; distributed ledger technology; DLT; contract law; cryptocurrency; OneCoin; silk road; smart contracts. DOI: 10.1504/IJBDM.2020.10034867
Leveraging Big Data Analytics by CHRISTOPHER MOTURI, Esther Karuga, Ochieng Daniel Abstract: This paper sought to study the extent to which telecoms within Kenya have adopted Big Data analytics to gain richer and deeper insights into their business dynamics in order to facilitate evidence decision making. A descriptive research design was employed and data was collected from ten leading telecoms using semi-structured questionnaires. The study found that Big Data could stimulate the economic growth, advance the productivity and competitiveness of the telecoms, as well as generate enormous benefits for customers. The factors with the highest significant effect on the adoption of Big Data analytics were identified. The practical implication of this paper is an increased understanding on what elements can promote Big Data adoption by large telecom companies. The study is beneficial to telecoms companies and any other organisations that would be looking at adopting data driven decision making to sustain competitiveness within the present uncertain setting. Keywords: Big Data; Big Data analytics; data-driven decision making; telecoms; technology; organisation and environment; TOE. DOI: 10.1504/IJBDM.2021.10036720