2020
DOI: 10.1016/j.resourpol.2020.101701
|View full text |Cite
|
Sign up to set email alerts
|

Financial and operational efficiencies of national and international oil companies: An empirical investigation

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
7
0
2

Year Published

2021
2021
2024
2024

Publication Types

Select...
5
1

Relationship

0
6

Authors

Journals

citations
Cited by 16 publications
(9 citation statements)
references
References 21 publications
0
7
0
2
Order By: Relevance
“…Many studies have emerged analyzing the differences in ownership, efficiency, and environmental behavior between IOCs and NOCs (Al‐Mana et al, 2020; Al‐Obaidan & Scully, 1992; Cabrales et al, 2017; Gong, 2018, 2020; Ohene‐Asare et al, 2017; Sueyoshi & Goto, 2012; Wolf, 2009). However, the distinction between IOCs and NOCs is not straightforward over time.…”
Section: Diversified Companies Within Different Statesmentioning
confidence: 99%
“…Many studies have emerged analyzing the differences in ownership, efficiency, and environmental behavior between IOCs and NOCs (Al‐Mana et al, 2020; Al‐Obaidan & Scully, 1992; Cabrales et al, 2017; Gong, 2018, 2020; Ohene‐Asare et al, 2017; Sueyoshi & Goto, 2012; Wolf, 2009). However, the distinction between IOCs and NOCs is not straightforward over time.…”
Section: Diversified Companies Within Different Statesmentioning
confidence: 99%
“…Their findings revealed that the different objectives of IOCs and NOCs influenced the companies' efficiency. Moreover, in order to reach a consensus with regards to the effectiveness of a given ownership model in comparison to the other by estimating the operational and financial efficiency differentials of NOCs and IOCs, Al‐Mana, Nawaz, Kamal, and Koҫ (2020) used 10 indicators (three financial and seven operational) to perform four analyses (financial analysis, operational analysis, SFA and DEA) for a sample consists of 50 firms (composed of 16 NOCs and 34 IOCs) during 2002–2016. Their results suggest that, in general, IOCs perform better than NOCs but the role of privatisation on the performance and efficiency of NOCs remains contentious because some NOCs perform as well as the best IOCs.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Nevertheless, on average, it is safe to imply that privatisation may lead to improved performance and efficiency because shareholder-owned firms, generally, perform better than the national players. For that matter, even some partially privatised firms show evidence of better performance in comparison to NOCs (Al-Mana et al, 2020). Due to the specifics of the petroleum sector, the companies tend to be large and have a significant direct and indirect influence on the oil industry as a whole (Filimonova, Komarova, Provornaya, Dzyuba, & Link, 2020).…”
Section: Efficiency Of Oil and Gas Companiesmentioning
confidence: 99%
“…To the best of our knowledge, the MPI studies under uncertainty are hedged in the DEA literature and received insufficient attention from both theoretical and practical viewpoints. There are also a few studies in which uncertain inputs and outputs data are assumed to be involved in the applications associated with the oil industry (Sueyoshi 2000 ; Eller et al 2011 ; Tavana et al 2019 ; Al-Mana et al 2020 ). Sueyoshi ( 2000 ) presented a stochastic DEA model to plan the restructuring strategy of a Japanese petroleum company.…”
Section: Introductionmentioning
confidence: 99%
“…Tavana et al ( 2019 ) introduced a novel fuzzy multi-objective multi-period network DEA model that was aimed to assess the dynamic efficiency of oil refineries when undesirable outputs are available. To compare the efficiency of NOCs and IOCs, Al-Mana et al ( 2020 ) employed an integrated framework containing four methods: SFA, DEA, financial, and operational analysis to ensure the validity of the obtained results as well as providing managerial implications. Table 1 shows a summary of those papers in the oil industry using DEA and MPI to measure economic efficiency and productivity in the presence of uncertainty.…”
Section: Introductionmentioning
confidence: 99%