Cargando…

Robust productivity growth and efficiency measurement with undesirable outputs: evidence from the oil industry

This paper aims to contribute to the contemporary and imperative research on the performance and productivity growth of the oil industry. Among cutting edge methods, frontier analysis is a successful approach that has been widely used to assess the efficiency and productivity of entities with multip...

Descripción completa

Detalles Bibliográficos
Autores principales: Hatami-Marbini, Adel, Arabmaldar, Aliasghar, Asu, John Otu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9125358/
https://www.ncbi.nlm.nih.gov/pubmed/35645438
http://dx.doi.org/10.1007/s00291-022-00683-y
_version_ 1784711932791488512
author Hatami-Marbini, Adel
Arabmaldar, Aliasghar
Asu, John Otu
author_facet Hatami-Marbini, Adel
Arabmaldar, Aliasghar
Asu, John Otu
author_sort Hatami-Marbini, Adel
collection PubMed
description This paper aims to contribute to the contemporary and imperative research on the performance and productivity growth of the oil industry. Among cutting edge methods, frontier analysis is a successful approach that has been widely used to assess the efficiency and productivity of entities with multiple resources and multiple outputs. This study first develops a unique framework based upon data envelopment analysis (DEA) to measure efficiency and productivity in the way that it tackles the uncertainty in data and undesirable outputs and, in turn, provides useful information to decision-makers. An adaptive robust optimisation is utilised to combat uncertain data whose distributions are unknown and consider the nexus between the level of conservatism and decision-makers’ risk preference. The key advantage of the proposed robust DEA approach is that the results remain relatively unchanged when uncertain conditions exist in the problem. An empirical study on the oil refinery is presented in situations of data uncertainty along with considering CO(2) emissions as the undesirable output to conduct environmental efficiency and productivity analysis of the 25 countries over the period 2000–2018. The empirical results obtained from the proposed approach give some imperative implications. First, results show that the price of robustness does not affect identically for varying technologies when assessing productivity in a global oil market, and the USA oil industry is observed as the highest productivity growth in all cases confirming its efforts for the rapid rise in oil extraction and production at low costs. There may be practical lessons for other nations to learn from the USA oil industry to improve productivity. Findings also support a considerable regress during the 2008 Global Financial Crisis in the oil industry compared to the rest of the periods in question, and due to monetary and fiscal stimulus, there is a sharp productivity growth from 2009 to 2011. The other implication that can be drawn is that the GDP growth rate and technology innovation can more effectively improve the productivity of the oil industry across the globe. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00291-022-00683-y.
format Online
Article
Text
id pubmed-9125358
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Springer Berlin Heidelberg
record_format MEDLINE/PubMed
spelling pubmed-91253582022-05-23 Robust productivity growth and efficiency measurement with undesirable outputs: evidence from the oil industry Hatami-Marbini, Adel Arabmaldar, Aliasghar Asu, John Otu OR Spectr Original Article This paper aims to contribute to the contemporary and imperative research on the performance and productivity growth of the oil industry. Among cutting edge methods, frontier analysis is a successful approach that has been widely used to assess the efficiency and productivity of entities with multiple resources and multiple outputs. This study first develops a unique framework based upon data envelopment analysis (DEA) to measure efficiency and productivity in the way that it tackles the uncertainty in data and undesirable outputs and, in turn, provides useful information to decision-makers. An adaptive robust optimisation is utilised to combat uncertain data whose distributions are unknown and consider the nexus between the level of conservatism and decision-makers’ risk preference. The key advantage of the proposed robust DEA approach is that the results remain relatively unchanged when uncertain conditions exist in the problem. An empirical study on the oil refinery is presented in situations of data uncertainty along with considering CO(2) emissions as the undesirable output to conduct environmental efficiency and productivity analysis of the 25 countries over the period 2000–2018. The empirical results obtained from the proposed approach give some imperative implications. First, results show that the price of robustness does not affect identically for varying technologies when assessing productivity in a global oil market, and the USA oil industry is observed as the highest productivity growth in all cases confirming its efforts for the rapid rise in oil extraction and production at low costs. There may be practical lessons for other nations to learn from the USA oil industry to improve productivity. Findings also support a considerable regress during the 2008 Global Financial Crisis in the oil industry compared to the rest of the periods in question, and due to monetary and fiscal stimulus, there is a sharp productivity growth from 2009 to 2011. The other implication that can be drawn is that the GDP growth rate and technology innovation can more effectively improve the productivity of the oil industry across the globe. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00291-022-00683-y. Springer Berlin Heidelberg 2022-05-23 2022 /pmc/articles/PMC9125358/ /pubmed/35645438 http://dx.doi.org/10.1007/s00291-022-00683-y Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Original Article
Hatami-Marbini, Adel
Arabmaldar, Aliasghar
Asu, John Otu
Robust productivity growth and efficiency measurement with undesirable outputs: evidence from the oil industry
title Robust productivity growth and efficiency measurement with undesirable outputs: evidence from the oil industry
title_full Robust productivity growth and efficiency measurement with undesirable outputs: evidence from the oil industry
title_fullStr Robust productivity growth and efficiency measurement with undesirable outputs: evidence from the oil industry
title_full_unstemmed Robust productivity growth and efficiency measurement with undesirable outputs: evidence from the oil industry
title_short Robust productivity growth and efficiency measurement with undesirable outputs: evidence from the oil industry
title_sort robust productivity growth and efficiency measurement with undesirable outputs: evidence from the oil industry
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9125358/
https://www.ncbi.nlm.nih.gov/pubmed/35645438
http://dx.doi.org/10.1007/s00291-022-00683-y
work_keys_str_mv AT hatamimarbiniadel robustproductivitygrowthandefficiencymeasurementwithundesirableoutputsevidencefromtheoilindustry
AT arabmaldaraliasghar robustproductivitygrowthandefficiencymeasurementwithundesirableoutputsevidencefromtheoilindustry
AT asujohnotu robustproductivitygrowthandefficiencymeasurementwithundesirableoutputsevidencefromtheoilindustry