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Safety or no safety in numbers? Governments, big data and public policy formulation

Amankwah-Amoah, J. (2015) Safety or no safety in numbers? Governments, big data and public policy formulation. Industrial Management and Data Systems, 115 (9). pp. 1596-1603. ISSN 0263-5577. (doi:10.1108/IMDS-04-2015-0158) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:57752)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL:
http://dx.doi.org/10.1108/IMDS-04-2015-0158

Abstract

Purpose

– Although big data have emerged at the cornerstone of business and management research, past studies have failed to offer explanations and classifications of different levels of capacity and expertise possessed by different countries in utilising big data. The purpose of this paper is to examine the different capacities of governments in utilising big data.

Design/methodology/approach

– The paper is based on a comprehensive synopsis of the literature on big data and the role of governments in utilising and harnessing big data.

Findings

– The study provides an array of explanations to account for why some countries are adept at using big data to solve social problems, while others often faltered.

Research limitations/implications

– The study offers a range of explanations and suggestions, which include skills upgrading, to help countries improve their capabilities in data collection and data analysis.

Originality/value

– In this paper, data collection-data analysis matrix was developed to characterise the role of governments in data collection and analysis.

Item Type: Article
DOI/Identification number: 10.1108/IMDS-04-2015-0158
Uncontrolled keywords: Capabilities, Public policy, Big data, Data
Subjects: H Social Sciences
Divisions: Divisions > Kent Business School - Division > Department of Marketing, Entrepreneurship and International Business
Depositing User: Joseph Amankwah-Amoah
Date Deposited: 06 Oct 2016 11:43 UTC
Last Modified: 17 Aug 2022 11:01 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/57752 (The current URI for this page, for reference purposes)

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