Evaluation of external forces affecting supply chain sustainability in oil and gas industry using Best Worst Method

Sadaghiani, Saman; Ahmad, Karimah W.; Rezaei, Jafar; Tavasszy, Lóránt

doi:10.1109/medgo.2015.7330322

Cited by 26 publications

(12 citation statements)

References 6 publications

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“…Vanalle et al (2017) investigated green pressures, practices, and performance within the Brazilian automotive supply chain. Kusi-Sarpong et al, (2016) developed a framework for green supply chain practices in the Ghanaian mining industry, while Sadaghiani et al (2015) evaluated the external forces affecting supply chain sustainability in the oil and gas industry. Recent studies also show that in the next couple of decades, most Asian manufacturers will have to face several environmental and social issues (Mangla et al, 2017).…”

Section: Motivation and Contributionmentioning

confidence: 99%

Modeling the interrelationships among barriers to sustainable supply chain management in leather industry

Moktadir

Ali

Rajesh

et al. 2018

Journal of Cleaner Production

197

103

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The leather industry of Bangladesh is facing considerable amounts of pressure to adopt sustainable supply chain management (SSCM). While there are some studies that have examined barriers to SSCM practices in developed and developing countries in various domains, these are not necessarily applicable to the Bangladeshi leather industry. To bridge this gap, it is crucial to identify most influential barriers to SSCM practices, particularly in the context of developing economies. Therefore, this study identifies such barriers and examines the causal relationships between them with an aim to facilitate the effective implementation of SSCM in the Bangladeshi leather processing industry. Thirty-five barriers to SSCM implementation were identified through a detailed literature review and a survey of leather processing industry experts. Among them, the most common 20 barriers were selected with the help of industry experts. Then, a blended, grey-based Decision Making Trial and Evaluation Laboratory (DEMATEL) approach was utilized to examine their interrelationships. The results demonstrate that nine barriers could be classified as "causal" and eleven as "influenced". 'Lack of awareness of local customers in green products' and 'lack of commitment from top management' took high priority in the causal group. 'Lack of reverse logistics practices' and 'Outdated machineries' were the most influenced barriers. This research uses a leather processing company as a case study for demonstrating the proposed model. The findings aim to support the leather processing industry in a structural way, so that industrial managers can identify the most influential barriers and work to eliminate them. This study may be useful to stakeholders to achieve sustainable development.

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Section: Motivation and Contributionmentioning

confidence: 99%

Modeling the interrelationships among barriers to sustainable supply chain management in leather industry

Moktadir

Ali

Rajesh

et al. 2018

Journal of Cleaner Production

197

103

View full text Add to dashboard Cite

show abstract

“…The SCM in Oil and Gas in measured by the number of groups involved in the development of the Oil and Gas Resources. The Oil and Gas industry contains national and global transportation, ordering, import, export, and information (Sadaghiani et al, 2015). Accordingly, it has a long supply chain network operating on a global scale.…”

Section: Literature Reviewmentioning

confidence: 99%

“…This paper focuses on the SCM practices in the oil and gas sector. The main purpose of every Oil and Gas Company is to find and create oil, gas, or Oil and Gas derived products (Sadaghiani et al, 2015). The operations in this industry have become more challenging for the Oil and Gas companies in respects to the environments, locations, and the trade paths during last decade.…”

Section: Introductionmentioning

confidence: 99%

A uniform supply chain management framework for oil and gas sector: A preliminary review

Alhosani¹,

Zabri

2018

Int. j. adv. appl. sci.

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The multidisciplinary nature of the oil and gas sector makes Supply Chain Management (SCM) practices in this sector more complex. Moreover, lack of generic model/framework results in lack of sharing knowledge, training, proper model or framework, and add additional complexities to SCM in oil and gas sector. Furthermore, the SCM knowledge of oil and gas sector is scattered in internet, books, thesis, journals papers, conference's papers, online database, and organizations. It lacks the obvious structure to unify, facilitate, reuse, and manage that scattered knowledge. Thus, it receives little attention from researchers. Current researchers have not focused on fundamental and essential guidelines to establish a baseline for SCM in oil and gas sector. This paper identifies and proposes common SCM practices concepts in oil and gas sector to unify the view of SCM practices in the form of a conceptual framework that can be seen as a baseline for this domain. The framework will be validated and refined to assist as a representational layer to unify, facilitate, and expedite the access to SCM practices in oil and gas sector. The specific aims are to facilitate knowledge sharing, combining and matching different SCM activities according to the different situations.

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“…Both P-CNP and BWM have been proved to be effective and been applied in some real world applications [22,[25][26][27][28][29][30][31][32][33][34]. However, to the best of our knowledge, there has not been a pairwise comparison based MADM method that has the two aspects of advantages possessed by P-CNP and BWM at the same time.…”

Section: ⋅ ⋅ ⋅mentioning

confidence: 99%

Cognitive Best Worst Method for Multiattribute Decision‐Making

Zhang

Yin

et al. 2017

Mathematical Problems in Engineering

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Pairwise comparison based multiattribute decision-making (MADM) methods are widely used and studied in recent years. However, the perception and cognition towards the semantic representation for the linguistic rating scale and the way in which the pairwise comparisons are executed are still open to discuss. The commonly used ratio scale is likely to produce misapplications and the matrix based comparison style needs too many comparisons and is not able to guarantee the consistency of the matrix when the number of objects involved is large. This research proposes a new MADM method CBWM (Cognitive Best Worst Method) which adopts interval scale to represent the pairwise difference and only compares each object to the best object and the worst object rather than all the other objects. CBWM is a vector based method which only needs 2n-3 pairwise comparisons and is more likely to generate consistent comparisons and reliable results. The theoretical analysis and a real world application demonstrate the effectiveness of CBWM.

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Evaluation of external forces affecting supply chain sustainability in oil and gas industry using Best Worst Method

Cited by 26 publications

References 6 publications

Modeling the interrelationships among barriers to sustainable supply chain management in leather industry

Modeling the interrelationships among barriers to sustainable supply chain management in leather industry

A uniform supply chain management framework for oil and gas sector: A preliminary review

Cognitive Best Worst Method for Multiattribute Decision‐Making

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