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Fine Tuning a Bayesian Network and Fairly Allocating Resources to Improve Procurement Performance

  • Mohammad Hassan AbolbashariEmail author
  • Omar Khadeer Hussain
  • Morteza Saberi
  • Elizabeth Chang
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 8)

Abstract

Procurement is one of the most important activities in any organization. Hence it is vital for an organization to track procurement practices. Through performance measurement, the organization will have a clear understanding on how it’s performing as well as the effect of any action that it makes towards improvement. In our previous work, we proposed a Bayesian Network (BN) model to measure the level of procurement performance in an organization. This paper extends that model in two ways. First it uses the Best-Worst Method (BWM) to adjust the impact of each KPI on the procurement performance according to its importance to the overall business strategy. Second is by using the relative importance of the KPIs, it demonstrates how procurement can be improved by re-allocating the available resources among the KPIs in a fair way.

Keywords

Procurement performance management Fair resource allocation Bayesian network 

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Mohammad Hassan Abolbashari
    • 1
    Email author
  • Omar Khadeer Hussain
    • 1
  • Morteza Saberi
    • 1
  • Elizabeth Chang
    • 1
  1. 1.School of BusinessUniversity of New South WalesCanberraAustralia

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