Evolutionary positioning of outsourcing in the local public administration
Abstract
Purpose: This work intends to establish a new methodology to quantitatively measure the initial position and evolution of outsourcing in a public administration.
Design/methodology: Product of the generalization of a methodological tool based on the fuzzy set theory "index of maximum and minimum level," a method is designed to evaluate the evolution of the positioning of outsourcing in a public administration.
Contributions/results: The proposed model that is presented opens up the possibility to study the evolution of public administration in terms of the actions that have been taken to reach an ideal outsourcing position, which would allow managers to create points of control at various stages to ensure the success of the actions taken.
Limitations: The limitations to the proposed method are directly related to the cases established in the fuzzy set theory. As an example, having to choose a specific value for the ideal values in an outsourcing strategy implies a regression to the concept of certainty. The work shows no examples of how to overcome these problems, although it does offer some ideas on how to minimize them.
Practical implications: This work offers a tool to help determine the degree to which the objectives have been reached that are established within a public administration with regard to actions associated with outsourcing.
Social implications: The ability to establish a distance from an ideal value means that citizens can numerically analyze whether the actions taken by the management team have improved or worsened the position of the public administration in terms of its outsourcing actions.
Originality/added value: The work offers two original proposals. First, it offers an expansion of an index customarily used to calculate the distance from an ideal position. Second, it offers a context in which to demonstrate the usefulness of the index.
Keywords
DOI: https://doi.org/10.3926/ic.1352
This work is licensed under a Creative Commons Attribution 4.0 International License
Intangible Capital, 2004-2024
Online ISSN: 1697-9818; Print ISSN: 2014-3214; DL: B-33375-2004
Publisher: OmniaScience