Technological, Organizational and Environmental Security and Privacy Issues of Big Data: A Literature Review

Salleh, Khairulliza Ahmad; Janczewski, Lech J.

doi:10.1016/j.procs.2016.09.119

Cited by 49 publications

(32 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Hence, housing data and doing the analytics in-house enhances data security, integrity, and can give energy firms an edge. Earlier research has also supported this argument [167,168]. However, this can only be realized with the appropriate human capital which is Industry 4.0 ready.…”

Section: Implications For Managersmentioning

confidence: 93%

Big Data Analytics Capabilities and Eco-Innovation: A Study of Energy Companies

Munodawafa

Johl

2019

Sustainability

View full text Add to dashboard Cite

Increased greenhouse gas (GHG) emissions in the past decades have created concerns about the environment. To stymie global warming and the deterioration of the natural environment, global CO2 emissions need to reach approximately 1.3 tons per capita by 2050. However, in Malaysia, CO2 output per capita—driven by fossil fuel consumption and energy production—is expected to reach approximately 12.1 tons by the year 2020. GHG mitigation strategies are needed to address these challenges. Cleaner production, through eco-innovation, has the potential to arrest CO2 emissions and buttress sustainable development. However, the cleaner production process has been hampered by lack of complete data to support decision making. Therefore, using the resource-based view, a preliminary study consisting of energy and utility firms is undertaken to understand the impact of big data analytics towards eco-innovation. Linear regression through SPSS Version 24 reveals that big data analytics could become a strong predictor of eco-innovation. This paper concludes that information and data are key inputs, and big data technology provides firms the opportunity to obtain information, which could influence its production process—and possibly help arrest increasing CO2 emissions.

show abstract

Section: Implications For Managersmentioning

confidence: 93%

Big Data Analytics Capabilities and Eco-Innovation: A Study of Energy Companies

Munodawafa

Johl

2019

Sustainability

View full text Add to dashboard Cite

show abstract

“…The impacts of this emerging innovation in providing relevant business insights to organizations such as Google, Amazon, Microsoft, EMC, Oracle, IBM and Facebook has led to its subsequent adoption in various industries, as well as society and government (Yang et al 2017). This is further driven by the fact that e-commerce firms that use big data analytics (BDA) in their value chains experience 5-6% higher productivity than their competitors (McAfee and Brynjolfsson 2012; cited by Salleh and Janczewski 2016). More importantly, the supply chain shocks and adaptations amid the covid-19 pandemic and post-pandemic recoveries provided indisputable evidence for the urgent needs of digital techniques for mapping supply chain networks and ensuring visibility (Ivanov and Dolgui 2020).…”

Section: Introductionmentioning

confidence: 99%

“…Also most of the supply chain data is not useful because of its raw state and the fact that it is often held captive inside organizational silos. Moreover, big data due to its complex and diverse functions in organizations and individuals' life, has the potential of introducing far greater security, ethical and privacy risks to customers (Salleh and Janczewski 2016). There is also a growing but limited number of SCMfocussed papers despite the increasing relevance of big data analytics across businesses and research community (Barbosa et al 2018).…”

Section: Introductionmentioning

confidence: 99%

Big data supply chain analytics: ethical, privacy and security challenges posed to business, industries and society

Ogbuke

Yusuf

Kovvuri

et al. 2020

Production Planning & Control

113

View full text Add to dashboard Cite

This study conducted a comprehensive review of big data supply chain analytics (BDSCA). The paper explored the application of big data in supply chain management and its benefits for organisations and society. The paper also examined the ethical, security, privacy and operational challenges of big data techniques, as well as the potential reputational damages to businesses. The review outlined four principal facets, namely: Big data analytics, applications, ethics and privacy issues, and how organizations employed this emerging tool to anticipate and even predict the future and direct their operations. These principle facets are built across the multiple levels and unique conceptual standpoints indicated by 7 themes and 14 sub-themes. These themes were generated based on 120 articles (2005À2020) drawn mainly from leading academic journals. Overall, there is a considerable consensus across current literature that big data analytics extend far beyond just reinventing the supply chain. It has the potential to support more responsive next-generation of global companies who are operating in an increasingly challenging and uncertain environment.

show abstract

“…In the academia area, the bulk of research on privacy issues in mHealth systems is mainly focused on organizational and technological solutions [ 11 ]. However, these types of solutions are no longer sufficient.…”

Section: Introductionmentioning

confidence: 99%

An Evolutionary Game-Theoretic Approach for Assessing Privacy Protection in mHealth Systems

Zhu

Liu

Feng

2018

IJERPH

View full text Add to dashboard Cite

With the rapid deployment of mobile technologies and their applications in the healthcare domain, privacy concerns have emerged as one of the most critical issues. Traditional technical and organizational approaches used to address privacy issues ignore economic factors, which are increasingly important in the investment strategy of those responsible for ensuring privacy protection. Taking the mHealth system as the context, this article builds an evolutionary game to model three types of entities (including system providers, hospitals and governments) under the conditions of incomplete information and bounded rationality. Given that the various participating entities are often unable to accurately estimate their own profits or costs, we propose a quantified approach to analyzing the optimal strategy of privacy investment and regulation. Numerical examples are provided for illustration and simulation purpose. Based upon these examples, several countermeasures and suggestions for privacy protection are proposed. Our analytical results show that governmental regulation and auditing has a significant impact on the strategic choice of the other two entities involved. In addition, the strategic choices of system providers and hospitals are not only correlated with profits and investment costs, but they are also significantly affected by free riding. If the profit growth coefficients increase to a critical level, mHealth system providers and hospitals will invest in privacy protection even without the imposition of regulations. However, the critical level is dependent on the values of the parameters (variables) in each case of investment and profits.

show abstract

Technological, Organizational and Environmental Security and Privacy Issues of Big Data: A Literature Review

Cited by 49 publications

References 24 publications

Big Data Analytics Capabilities and Eco-Innovation: A Study of Energy Companies

Big Data Analytics Capabilities and Eco-Innovation: A Study of Energy Companies

Big data supply chain analytics: ethical, privacy and security challenges posed to business, industries and society

An Evolutionary Game-Theoretic Approach for Assessing Privacy Protection in mHealth Systems

Contact Info

Product

Resources

About