Please use this identifier to cite or link to this item: http://hdl.handle.net/10125/41479

Barriers to Predictive Analytics Use for Policy Decision-Making Effectiveness in Turbulent Times: A Case Study of Fukushima Nuclear Accident

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Title: Barriers to Predictive Analytics Use for Policy Decision-Making Effectiveness in Turbulent Times: A Case Study of Fukushima Nuclear Accident
Authors: Chatfield, Akemi Takeoka
Reddick, Christopher
Keywords: Predictive analytics
analytical capabilities
government decision making effectiveness
evacuation policy
Issue Date: 04 Jan 2017
Abstract: Predictive analytics are data-driven software tools that draw on confirmed relationships between variables to predict future outcomes. Hence they may provide government with new analytical capabilities for enhancing policy decision-making effectiveness in turbulent environments. However, predictive analytics system use research is still lacking. Therefore, this study adapts the existing model of strategic decision-making effectiveness to examine government use of predictive analytics in turbulent times and to identify barriers to using information effectively in enhancing policy decision making effectiveness. We use a case study research to address two research questions in the context of the 2011 Fukushima nuclear accident. Our study found varying levels of proactive use of SPEEDI predictive analytics system during the escalating nuclear reactor meltdowns between Japan’s central government agencies and between the central and the state government levels. Using the model, we argue that procedural rationality and political behavior can be used to explain some observed variations.
Pages/Duration: 10 pages
URI/DOI: http://hdl.handle.net/10125/41479
ISBN: 978-0-9981331-0-2
DOI: 10.24251/HICSS.2017.323
Rights: Attribution-NonCommercial-NoDerivatives 4.0 International
Appears in Collections:Open Data, Information Processing, and Datification in Government Minitrack



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