Evaluating Process Efficiency with Data Envelopment Analysis: A Case in the Automotive Industry

Rutger Kerkhof*, Luís Ferreira Pires, Renata Guizzardi - Silva Souza

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

64 Downloads (Pure)

Abstract

In some industries, small improvements to processes and profit margins may lead to a significant change in profit, and this holds especially in the automotive industry. A popular approach to achieving process improvement is benchmarking, in which the execution of a process is measured and compared between different work units so that improvement opportunities can be identified. This paper reports on our efforts to improve car dealership benchmarking by designing a benchmarking tool for the automotive workshop department, such that it calculates the efficiency of its main process, which we call the Standard Service Process (SSP) in this paper. We achieved this by designing a Data Envelopment Analysis (DEA) Network Slacks-Based Measure (NSBM) model and used this model to measure the SSP efficiency for each workshop by considering its sub-processes. This model was programmed using R, after which it was verified and extended based on the literature, and the results of the verified model were validated using a real case. In this paper, we show that this has enabled a more insightful assessment of the workshops so that suggestions for improvement can be automated. In this way, we demonstrate that our approach is appropriate to rank the efficiency of work units that perform a certain process.

Original languageEnglish
Title of host publicationResearch Challenges in Information Science
Subtitle of host publicationInformation Science and the Connected World - 17th International Conference, RCIS 2023, Proceedings
EditorsSelmin Nurcan, Andreas L. Opdahl, Haralambos Mouratidis, Aggeliki Tsohou
Place of PublicationCham, Switzerland
PublisherSpringer Nature
Pages291-307
Number of pages17
ISBN (Electronic)978-3-031-33080-3
ISBN (Print)978-3-031-33079-7
DOIs
Publication statusPublished - 23 May 2023
Event17th International Conference on Research Challenges in Information Science, RCIS 2023 - Corfu, Greece
Duration: 23 May 202326 Aug 2023
Conference number: 17
https://www.rcis-conf.com/rcis2023/

Publication series

NameLecture Notes in Business Information Processing
PublisherSpringer
Volume476
ISSN (Print)1865-1348
ISSN (Electronic)1865-1356

Conference

Conference17th International Conference on Research Challenges in Information Science, RCIS 2023
Abbreviated titleRCIS 2023
Country/TerritoryGreece
CityCorfu
Period23/05/2326/08/23
Internet address

Keywords

  • Car dealerships
  • Data envelopment analysis
  • Process efficiency

Fingerprint

Dive into the research topics of 'Evaluating Process Efficiency with Data Envelopment Analysis: A Case in the Automotive Industry'. Together they form a unique fingerprint.

Cite this