Big data analytics capabilities: a systematic literature review and research agenda

By Patrick Mikalef, Ilias O. Pappas, John Krogstie, Michail N. Giannakos. Information Systems and E-Business Management, 2017

768 citations recorded by the source corpus.

Subfields: Management Information Systems, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/3ca7f49ce3554ea9366744c54413d8f5e401f48d

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In Management Information Systems

In Strategy and Management

Citations in the corpus

Big Data Analytics Capabilities and Innovation: The Mediating Role of Dynamic Capabilities and Moderating Effect of the Environment (2019, positive): “…definition in the literature regards big data analytics as “a new generation of technologies and architectures, designed to economically extract value from very large volumes of a wide variety of data, by enabling high velocity capture, discovery and/or analysis” (Mikalef, Pappas, et al., 2017).”
Prescriptive analytics: Literature review and research challenges (2020, neutral): “To this end, business analytics has evolved beyond a simple raw data analysis on large datasets with the aim to provide organizations a competitive advantage (Mikalef, Pappas, Krogstie, & Giannakos, 2018; Vidgen, Shaw, & Grant, 2017).”
Big data analytics adoption: Determinants and performances among small to medium-sized enterprises (2020, background): “Therefore, to address this issue, the term of BDAC has taken place as it makes firm able to successfully implement big data and take advantage of its business values (Mikalef et al., 2018).”
Algorithmic bias: review, synthesis, and future research directions (2021, methodology): “We employed a well-established systematic review methodology to analyse and synthesise the existing literature on algorithmic bias and propose a theoretical model accordingly (Mikalef et al., 2018; Webster & Watson, 2002).”
A survey towards an integration of big data analytics to big insights for value-creation (2018, background): “Facebook and Netflix, Borders and many other businesses (Mithas & Lucas, 2010).”
Exploring the relationship between big data analytics capability and competitive performance: The mediating roles of dynamic and operational capabilities (2020, background): “Recent studies argue that effects of BDACs on competitive performance are indirect and are mediated by changes in firm’s organizational capabilities [8,13,20].”
The smart circular economy: A digital-enabled circular strategies framework for manufacturing companies (2020, background): “This includes both tangible and intangible organizational resources such as data governance, existence of a data-driven culture, presence of suitable managerial and technical skills, and processes for data-driven organizational learning (Mikalef, Pappas, Krogstie, & Giannakos, 2018).”
Artificial intelligence and big data analytics for supply chain resilience: a systematic literature review (2022, methodology): “Similarly, we approach BDA as the portfolio of technologies, techniques, and organisational resources that allow a company to analyse large-scale and complex datasets, so as to improve their performance and develop actionable insights from big data (Mikalef et al., 2018).”