Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Public administration, public leadership and the construction of public value in the age of the algorithm and ‘big data’

Andrews, Leighton ORCID: 2019. Public administration, public leadership and the construction of public value in the age of the algorithm and ‘big data’. Public Administration 97 (2) , pp. 296-310. 10.1111/padm.12534

[thumbnail of Andrews-2018-Public_Administration.pdf]
PDF - Published Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (1MB) | Preview


Public administration scholarship has to a significant degree neglected technological change. The age of the algorithm and ‘big data’ is throwing up new challenges for public leadership, which are already being confronted by public leaders in different jurisdictions. Algorithms may be perceived as presenting new kinds of ‘wicked problems’ for public authorities. The article offers a tentative overview of the kind of algorithmic challenges facing public leaders in an environment where the discursive context is shaped by corporate technology companies. Public value theory is assessed as an analytical framework to examine how public leaders are seeking to address the ethical and public value issues affecting governance and regulation, drawing on recent UK experience in particular. The article suggests that this is a fruitful area for future research.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Business (Including Economics)
Additional Information: This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
Publisher: Wiley
ISSN: 0033-3298
Date of First Compliant Deposit: 21 June 2018
Date of Acceptance: 3 June 2018
Last Modified: 05 May 2023 02:37

Citation Data

Cited 57 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item


Downloads per month over past year

View more statistics