The Electronic Journal of Information Systems Evaluation provides critical perspectives on topics relevant to Information Systems Evaluation, with an emphasis on the organisational and management implications
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Journal Article

Privacy Lost ‑ and Found? The information value chain as a model to meet citizens concerns  pp200-210

John van de Pas, Geert-Jan van Bussel

© Sep 2015 Volume 18 Issue 2, The special issue from ECIME 2014, Editor: Jan Devos, pp93 - 210

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Abstract

Abstract: In this paper we explore the extent to which privacy enhancing technologies (PETs) could be effective in providing privacy to citizens. Rapid development of ubiquitous computing and the internet of things are leading to Big Data and the appl ication of Predictive Analytics, effectively merging the real world with cyberspace. The power of information technology is increasingly used to provide personalised services to citizens, leading to the availability of huge amounts of sensitive data about individuals, with potential and actual privacy‑eroding effects. To protect the private sphere, deemed essential in a state of law, information and communication systems (ICTs) should meet the requirements laid down in numerous privacy regulations. Sens itive personal information may be captured by organizations, provided that the person providing the information consents to the information being gathered, and may only be used for the express purpose the information was gathered for. Any other use of in formation about persons without their consent is prohibited by law; notwithstanding legal exceptions. If regulations are properly translated into written code, they will be part of the outcomes of an ICT, and that ICT will therefore be privacy compliant. We conclude that privacy compliance in the technological sense cannot meet citizens concerns completely, and should therefore be augmented by a conceptual model to make privacy impact assessments at the level of citizens lives possible.

 

Keywords: Keywords: privacy, privacy enhancing technology, digital archiving, information value chain, big data, information management

 

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Journal Article

Considerations for the Adoption of Cloud‑based Big Data Analytics in Small Business Enterprises  pp63-79

Ajimoko Olufemi

© Nov 2018 Volume 21 Issue 2, Editor: Prof Shaun Pather, pp63 - 130

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Abstract

This study explores the various adoption criteria that may guide the information technology (IT) professionals in small business enterprises (SBEs) in their decision to adopt cloud‑based big data analytics (CBBDA). The research was guided by three major theories of technology adoption, which were: diffusion of innovation, theory of technology acceptance model, and the theory of technology‑organization‑environment framework. The study was based on a sample of 20 IT professionals from10 SBEs in the state of New Jersey in the United States. The exploratory qualitative research used semi‑structure questionnaires to conduct one‑on‑one interviews with the participants. The results were coded to identify the emergent themes. The study found two categories of CBBDA adoption criteria; they were: (a) internal technology adoption criteria, which were found to be unique to each SBE and (b) external technology adoption criteria, which were found to be uniform to all the SBEs. The internal criteria consisted of technological and organizational factors, while the external criteria consisted of vendor‑related and environmental factors. Further, the study found that some of the prominent internal factors played a dominant role in CBBDA adoption in SBEs. They were: (a) technology/organization alignment and fit; (b) SBE data environment and need; (c) SBE financial standing and (d) SBE owner/top management support. It was also found that no matter how useful the innovation, the lack of SBE owner/top management support can easily obstruct the adoption of CBBDA and other similar future technology.

 

Keywords: big data analytics, cloud computing, cloud-based big data analytics, small business enterprise

 

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Journal Issue

Volume 21 Issue 2 / Nov 2018  pp63‑130

Editor: Prof Shaun Pather

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Keywords: Acceptance of Open Learning Resources, Self-efficacy, MOOCs and OERs in India, Technology acceptance, Informal online-learning, Open educational content and higher education, big data analytics, cloud computing, cloud-based big data analytics, small business enterprise

 

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