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Resource allocation in local government with facilitated portfolio decision analysis

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posted on 2021-04-30, 12:39 authored by Gilberto Montibeller, Luis Alberto FrancoLuis Alberto Franco
Resource allocation in local government imposes several challenges for public managers, such as substantial pressures for more efficiency in public spending, frequent changes in levels of income for public organisations, steadily growing demand for public services, and higher public expectations and increased scrutiny. In order to tackle these challenges effectively public managers and policy makers are focusing on changing old ways of working, with a view to creating and delivering public value in an ever increasingly “wicked” context. One area of concern relates to improving decision-making processes and the accountability of decisions, particularly within the context of resource allocation in local government. In this chapter, we review our experience of using facilitated portfolio decision analysis to help local government teams assess the value of a range of public services or projects. Our discussion is focused primarily on the British local government context, and illustrated with several case studies drawn from our own research and practical interventions. The approach and experience discussed here, however, can be easily translated to similar contexts in other countries.

History

School

  • Business and Economics

Department

  • Business

Published in

Portfolio Decision Analysis: Improved Methods for Resource Allocation

Pages

259 - 281

Publisher

Springer

Version

  • AM (Accepted Manuscript)

Rights holder

© Springer Science+Business Media, LLC

Publisher statement

This book chapter was published in the book Portfolio Decision Analysis: Improved Methods for Resource Allocation [© Springer Science+Business Media, LLC]. The definitive published version is available at https://doi.org/10.1007/978-1-4419-9943-6_12.

Publication date

2011-06-29

Copyright date

2011

ISBN

9781441999429; 9781441999436

Book series

International Series in Operations Research & Management Science; 162

Language

  • en

Editor(s)

Ahti Salo; Jeffrey Keisler; Alec Morton

Depositor

Prof Alberto Franco. Deposit date: 29 April 2021

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