In this section
@article{Graham:2022:imaman/dpab021,
author = {Graham, DJ and Singh, R},
doi = {imaman/dpab021},
journal = {IMA Journal of Management Mathematics},
pages = {381--393},
title = {Model-based adjustment for conditional benchmarking},
url = {http://dx.doi.org/10.1093/imaman/dpab021},
volume = {33},
year = {2022}
}
TY - JOUR
AB - 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.
AU - Graham,DJ
AU - Singh,R
DO - imaman/dpab021
EP - 393
PY - 2022///
SN - 1471-678X
SP - 381
TI - Model-based adjustment for conditional benchmarking
T2 - IMA Journal of Management Mathematics
UR - http://dx.doi.org/10.1093/imaman/dpab021
UR - https://academic.oup.com/imaman/advance-article/doi/10.1093/imaman/dpab021/6308195
UR - http://hdl.handle.net/10044/1/90007
VL - 33
ER -
Transport Strategy Centre
Department of Civil and Environmental Engineering
South Kensington Campus
Imperial College London
London SW7 2AZ - UK
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