Use of control charts with regression analysis for autocorrelated data in the context of logistic financial budgeting

Jorge Pérez-Rave*, Leandro Muñoz-Giraldo, Juan Carlos Correa-Morales

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

The aim of this paper is to explore whether the use of control charts with regression analysis is an effective way to evaluate financial budget requests (autocorrelated data) in the transport logistics sector. First, the variables are selected. Second, a regression analysis is performed to model the financial variables. Third, three types of traditional control charts are tested (individuals, CUSUM and EWMA), using simulation to monitor the regression scaled residuals. The results show that the individual control chart of 2.7-sigma offers an appropriate performance for the context of this study. This paper provides new evidence regarding a type of variable and context not reported in the literature. In addition, it proposes a control chart approach of scaled regression residuals, with two differentiators: (1) residuals offer better practical interpretation and (2) regressions do not incorporate the time variable, as traditionally occurs, but a missionary process variable (loading units) and a control one.

Original languageEnglish
Pages (from-to)71-83
Number of pages13
JournalComputers and Industrial Engineering
Volume112
DOIs
Publication statusPublished - Oct 2017
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2017 Elsevier Ltd

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • General Engineering

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