Getting real about Big Data: Applying critical realism to analyse Big Data hype

Stephen Fox, Tuan Do

Research output: Contribution to journalArticleScientificpeer-review

16 Citations (Scopus)

Abstract

Purpose: – An emerging application of Big Data is the addition of sensors and other micro‐electronic devices to engineer‐to‐order (ETO) goods such as one‐of‐a‐kind buildings and ships. The addition of micro‐electronic devices can enable the setting up and operation of smart buildings and smart ships. The purpose of this paper is to provide a critical realist analysis of Big Data hype. This is necessary to determine what challenges will need to be met before project businesses can achieve informational effects and transformational effects from Big Data technologies. Design/methodology/approach: – A critical realist study informed by reference to predictive theory and findings from action research. The predictive theory is concerned with the three different types of business effects that can come from information and communication technologies (ICTs): automational, informational, and transformational. Findings: – Critical realist analysis reveals that hype about Big Data underplays many challenges in achieving informational and transformational effects. Practical implications:
– Many inter‐related non‐trivial factors need to be taken into account when considering investing in Big Data initiatives. These factors range from the planning of data sampling rates, through the robust fixing of sensors, to the implementation of data mining algorithms and signal models. Originality/value:
– The originality of this paper is that critical realism is used in analysis of Big Data hype. The value of this paper is that it reveals a causal mechanism and causal context for project business Big Data application. This type of critical realist analysis can be applied to enable better understanding of necessary causal mechanisms and causal contexts for other ICT innovations.
Original languageEnglish
Pages (from-to)739-760
Number of pages21
JournalInternational Journal of Managing Projects in Business
Volume6
Issue number4
DOIs
Publication statusPublished - 2013
MoE publication typeA1 Journal article-refereed

Fingerprint

Critical realism
Project business
Information and communication technology
Factors
Ship
Microelectronics
Sensor
Technology innovation
Planning
Data mining
Design methodology
Sampling
Investing

Keywords

  • automational effects
  • Big Data
  • critical realism
  • hype
  • informational effects
  • transformational effects

Cite this

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Getting real about Big Data : Applying critical realism to analyse Big Data hype. / Fox, Stephen; Do, Tuan.

In: International Journal of Managing Projects in Business, Vol. 6, No. 4, 2013, p. 739-760.

Research output: Contribution to journalArticleScientificpeer-review

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