Model-based adjustment for conditional benchmarking
File(s)
Published version
Author(s)
Graham, Daniel J
Singh, Ramandeep
Type
Journal Article
Abstract
Quantitative benchmarking is widely used in the industry to compare relative performance across a sample of organizations. A key analytical challenge lies in obtaining accurate measures of intrinsic organizational performance net of contextual or exogenous influences. In this paper, we propose a model-based adjustment approach for comparative benchmarking that allows the analyst to recover targeted metrics for specific aspects of innate performance. We outline the statistical theory underpinning our method, provide simulations to demonstrate its properties and describe practical examples for computation. The managerial relevance of the method is demonstrated via two real-world transport industry applications: adjusting for economies of scale and density in benchmarking average costs of urban metros and for service characteristics in benchmarking metro journey times.
Date Issued
2022-07
Date Acceptance
2021-05-28
Citation
IMA Journal of Management Mathematics, 2022, 33 (3), pp.381-393
ISSN
1471-678X
Publisher
Oxford University Press (OUP)
Start Page
381
End Page
393
Journal / Book Title
IMA Journal of Management Mathematics
Volume
33
Issue
3
Copyright Statement
© The Author(s) 2021. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
License URL
Identifier
https://academic.oup.com/imaman/advance-article/doi/10.1093/imaman/dpab021/6308195
Subjects
Social Sciences
Science & Technology
Technology
Physical Sciences
Management
Operations Research & Management Science
Mathematics, Interdisciplinary Applications
Social Sciences, Mathematical Methods
Business & Economics
Mathematics
Mathematical Methods In Social Sciences
benchmarking
model
performance
conditional
unconditional
NONPARAMETRIC FRONTIER MODELS
EFFICIENCY
PERFORMANCE
0102 Applied Mathematics
1502 Banking, Finance and Investment
Publication Status
Published
Date Publish Online
2021-06-28