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

Rutger Kerkhof; Luís Ferreira Pires; Renata Guizzardi - Silva Souza

doi:10.1007/978-3-031-33080-3_18

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 proceeding › Conference contribution › Academic › peer-review

1 Citation (Scopus)

151 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 language	English
Title of host publication	Research Challenges in Information Science
Subtitle of host publication	Information Science and the Connected World - 17th International Conference, RCIS 2023, Proceedings
Editors	Selmin Nurcan, Andreas L. Opdahl, Haralambos Mouratidis, Aggeliki Tsohou
Place of Publication	Cham, Switzerland
Publisher	Springer
Pages	291-307
Number of pages	17
ISBN (Electronic)	978-3-031-33080-3
ISBN (Print)	978-3-031-33079-7
DOIs	https://doi.org/10.1007/978-3-031-33080-3_18
Publication status	Published - 23 May 2023
Event	17th International Conference on Research Challenges in Information Science, RCIS 2023 - Corfu, Greece Duration: 23 May 2023 → 26 Aug 2023 Conference number: 17 https://www.rcis-conf.com/rcis2023/

Publication series

Name	Lecture Notes in Business Information Processing
Publisher	Springer
Volume	476
ISSN (Print)	1865-1348
ISSN (Electronic)	1865-1356

Conference

Conference	17th International Conference on Research Challenges in Information Science, RCIS 2023
Abbreviated title	RCIS 2023
Country/Territory	Greece
City	Corfu
Period	23/05/23 → 26/08/23
Internet address	https://www.rcis-conf.com/rcis2023/

Keywords

Car dealerships
Data envelopment analysis
Process efficiency

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10.1007/978-3-031-33080-3_18Licence: CC BY

ArticleFinal published version, 1.39 MBLicence: CC BY

Cite this

Kerkhof, R., Pires, L. F., & Guizzardi - Silva Souza, R. (2023). Evaluating Process Efficiency with Data Envelopment Analysis: A Case in the Automotive Industry. In S. Nurcan, A. L. Opdahl, H. Mouratidis, & A. Tsohou (Eds.), Research Challenges in Information Science: Information Science and the Connected World - 17th International Conference, RCIS 2023, Proceedings (pp. 291-307). (Lecture Notes in Business Information Processing; Vol. 476). Springer. https://doi.org/10.1007/978-3-031-33080-3_18

Kerkhof, Rutger ; Pires, Luís Ferreira ; Guizzardi - Silva Souza, Renata. / Evaluating Process Efficiency with Data Envelopment Analysis : A Case in the Automotive Industry. Research Challenges in Information Science: Information Science and the Connected World - 17th International Conference, RCIS 2023, Proceedings. editor / Selmin Nurcan ; Andreas L. Opdahl ; Haralambos Mouratidis ; Aggeliki Tsohou. Cham, Switzerland : Springer, 2023. pp. 291-307 (Lecture Notes in Business Information Processing).

@inproceedings{b9581e92b1a844489d6a7cddba90b4ab,

title = "Evaluating Process Efficiency with Data Envelopment Analysis: A Case in the Automotive Industry",

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.",

keywords = "Car dealerships, Data envelopment analysis, Process efficiency",

author = "Rutger Kerkhof and Pires, \{Lu{\'i}s Ferreira\} and \{Guizzardi - Silva Souza\}, Renata",

note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 17th International Conference on Research Challenges in Information Science, RCIS 2023, RCIS 2023 ; Conference date: 23-05-2023 Through 26-08-2023",

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Kerkhof, R, Pires, LF & Guizzardi - Silva Souza, R 2023, Evaluating Process Efficiency with Data Envelopment Analysis: A Case in the Automotive Industry. in S Nurcan, AL Opdahl, H Mouratidis & A Tsohou (eds), Research Challenges in Information Science: Information Science and the Connected World - 17th International Conference, RCIS 2023, Proceedings. Lecture Notes in Business Information Processing, vol. 476, Springer, Cham, Switzerland, pp. 291-307, 17th International Conference on Research Challenges in Information Science, RCIS 2023, Corfu, Greece, 23/05/23. https://doi.org/10.1007/978-3-031-33080-3_18

Evaluating Process Efficiency with Data Envelopment Analysis: A Case in the Automotive Industry. / Kerkhof, Rutger; Pires, Luís Ferreira ; Guizzardi - Silva Souza, Renata.
Research Challenges in Information Science: Information Science and the Connected World - 17th International Conference, RCIS 2023, Proceedings. ed. / Selmin Nurcan; Andreas L. Opdahl; Haralambos Mouratidis; Aggeliki Tsohou. Cham, Switzerland: Springer, 2023. p. 291-307 (Lecture Notes in Business Information Processing; Vol. 476).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Evaluating Process Efficiency with Data Envelopment Analysis

T2 - 17th International Conference on Research Challenges in Information Science, RCIS 2023

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AU - Pires, Luís Ferreira

AU - Guizzardi - Silva Souza, Renata

N1 - Conference code: 17

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N2 - 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.

AB - 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.

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KW - Data envelopment analysis

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BT - Research Challenges in Information Science

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PB - Springer

CY - Cham, Switzerland

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Kerkhof R, Pires LF , Guizzardi - Silva Souza R. Evaluating Process Efficiency with Data Envelopment Analysis: A Case in the Automotive Industry. In Nurcan S, Opdahl AL, Mouratidis H, Tsohou A, editors, Research Challenges in Information Science: Information Science and the Connected World - 17th International Conference, RCIS 2023, Proceedings. Cham, Switzerland: Springer. 2023. p. 291-307. (Lecture Notes in Business Information Processing). doi: 10.1007/978-3-031-33080-3_18

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

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