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The oil and gas industry is a crucial economic sector for both developed and developing economies. Delays in extraction and refining of these resources would adversely affect industrial players, including that of the host countries. Supplier selection is one of the most important decisions taken by managers of this industry that affect their supply chain operations. However, determining suitable suppliers to work with has become a phenomenon faced by these managers and their organizations. Furthermore, identifying relevant, critical and important criteria needed to guide these managers and their organizations for supplier selection decisions has become even more complicated due to various criteria that need to be taken into consideration. With limited works in the current literature of supplier selection in the oil and gas industry having major methodological drawbacks, the purpose of this paper is to develop an integrated approach for supplier selection in the oil and gas industry.

To address this problem, this paper proposes a new uncertain decision framework. A grey-Delphi approach is first applied to aid in the evaluation and refinement of these various available criteria to obtain the most important and relevant criteria for the oil and gas industry. The grey systems theoretic concept is adopted to address the subjectivity and uncertainty in human judgments. The grey-Shannon entropy approach is used to determine the criteria weights, and finally, the grey-EDAS (evaluation based on distance from average solution) method is utilized for determining the ranking of the suppliers.

To exemplify the applicability and robustness of the proposed approach, this study uses the oil and gas industry of Iran as a case in point. From the literature review, 21 criteria were established and using the grey-Delphi approach, 16 were finally considered. The four top-ranked criteria, using grey-Shannon entropy, include warranty level and experience time, relationship closeness, supplier’s technical level and risks which are considered as the most critical and influential criteria for supplier evaluation in the Iranian oil and gas industry. The ranking of the suppliers is obtained, and the best and worst suppliers are also identified. Sensitivity analysis indicates that the results using the proposed methodology are robust.

The proposed approach would assist supply chain practicing managers, including purchasing managers, procurement managers and supply chain managers in the oil and gas and other industries, to effectively select suitable suppliers for cooperation. It can also be used for other multi-criteria decision-making (MCDM) applications. Future works on applying other MCDM methods and comparing them with the results of this study can be addressed. Finally, broader and more empirical works are required in the oil and gas industry.

This study is among the first few studies of supplier selection in the oil and gas industry from an emerging economy perspective and sets the stage for future research. The proposed integrated grey-based MCDM approach provides robust results in supplier evaluation and can be used for future domain applications.

Circular supply chain management (CSCM) has the potential to compensate for the drawbacks of the linear supply chain model. Therefore, the objective of this study is to identify and prioritise the significant enablers related to the effective management of the circular supply chain (CSC).

The significant enablers of CSCM are identified through a two-step process of literature review and grey-Delphi approach. Further, an integrated grey-based Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is applied to prioritise these enablers.

This study proposes a grey-based framework to identify and evaluate the enablers associated with CSCM. A total of 12 significant CSCM enablers are finalised per the proposed framework. The findings suggest that the top three enablers are "long-term planning", "development of CE culture" and "alignment of CE goals with strategic objectives". These enablers require the attention of the top management and supply chain partner on priority.

This study identifies 12 enablers through the literature review, so there is a possibility to overlook some significant enablers. However, the expert's input is used to finalise and analyse the enablers, which can be biased towards their working level.

This study proposes a grey-based framework to identify and analyse the CSC enablers rarely investigated in the contemporary literature. The paper is strong in methodological contributions and gives practitioners and researchers a better framework for CSCM.

Consumers, governments and regulatory agencies are concerned about the social and environmental aspect that pushes firms to move towards the circular economy. The transformation of the existing linear model into a circular model depends on several circular economy practices. Therefore, the purpose of this study is to identify and analyse the critical factors that are responsible for the adoption of circular practices.

In total, 15 critical factors are identified through the literature review and 12 are finalised with the grey Delphi method. Further, these critical factors are prioritised using the weighted aggregated sum/product assessment (WASPAS) method. A sensitivity analysis is also conducted to test the robustness of the ranking of critical factors obtained from WASPAS.

The finding of this study show that “top management participation,” “market for recovered products” and “circular economy oriented R&D activities promotion” are the most significant factors for circular practice adoption. These factors need to address on the highest priority by the stakeholders.

This study is beneficial for the managers to formulate their strategies for the adoption of circular practices. The prioritisation of critical factors supports the managers and professionals to optimise their effort and resources to adopt the circular practice.

This study explores and analyses the critical factor for circular economy practice adoption in the supply chain in the context of emerging economies.

The study aims to identify and analyse the drivers of resilient healthcare supply chain (HCSC) preparedness in emergency health outbreaks to prevent disruption in healthcare services delivery in the context of India.

The present study has opted for the grey clustering method to identify and analyse the drivers of resilient HCSC preparedness during health outbreaks into high, moderate and low important grey classes based on Grey-Delphi, analytic hierarchy process (AHP) and Shannon's information entropy (IE) theory.

The drivers of the resilient HCSC are scrutinised using the Grey-Delphi technique. By implementing AHP and Shannon's IE theory and depending upon structure, process and outcome measures of HCSC, eleven drivers of a resilient HCSC preparedness are clustered as highly important, three drivers into moderately important, and two drivers into a low important group.

The analysis and insights developed in the present study would help to plan and execute a viable, resilient emergency HCSC preparedness during the emergence of any health outbreak along with the stakeholders' coordination. The results of the study offer information, rationality, constructiveness, and universality that enable the wider application of AHP-IE/Grey clustering analysis to HCSC resilience in the wake of pandemics.

This paper aims to explore the drivers of sustainable healthcare supply chain (SHCSC) performance measurement through extensive literature review and experts' opinions. The drivers are then scrutinized and their priority vector is calculated to provide quality and cost-effective healthcare supply chain (HCSC) services.

The drivers of the SHCSC performance measurement are validated using the grey-Delphi technique. After validating the drivers, they are prioritized using the grey-analytic hierarchy process (G-AHP), a multi-criteria decision-making tool.

The findings of the study highlight the prioritized drivers based on the preferences given by the experts. The findings of the study highlight the most prioritized drivers of healthcare (HC) by-product management system, coordinating and facilitating green suppliers in the HCSC and green packaging of pharmaceutical as well as other essential items.

The HCSC managers should coordinate with all the stakeholders across the supply chain and involve them in the decision-making process to make products and services greener and become complicit in complying with the sustainable policy guidelines. The study highlights the strategic policy and managerial implications for implementing sustainability in the HCSC.

The validation and prioritization of the drivers of SHCSC in developing nations' contexts is the key contribution of the study. Grey-AHP enables a practical approach towards enhancing the sustainability of the HCSC and opening the doors for generalizing the study for future research works.

The statistical report published by the Iranian Social Security Organization in 2012 showed that, of all industries, the construction industry is associated with the highest number of work-related accidents. Furthermore, as this sector contains a large human workforce, identification of the factors contributing to the occurrence of such accidents is vital. The paper aims to discuss these issues.

Furthermore, as this sector contains a large human workforce, identification of the factors contributing to the occurrence of such accidents is vital. In the present study, such factors were initially identified, after which the most important of these, managerial factors, were selected. Subsequently, the identification of the causes of the managerial factors was carried out with the use of the fault tree analysis (FTA) method and application of OR and AND entries.

Since it is difficult to determine the probability of occurrence of events in this industry with certainty, and because gray numbers (numbers of which the exact value is unknown, and which represent uncertain information) have a strong relationship with human expressions, the probability of occurrence of the main undesired events was also evaluated using the gray numbers as input entries, in addition to ranking the probability of occurrence of intermediate events.

The findings revealed that FTA using gray numbers is a useful and effective tool in risk assessment.

The proposed model was capable of being used in both promoting safety performance level and evaluating and ranking safety units. The paper aims to discuss these issues.

Managers must be able to determine positive impacts of safety programmes on the organisation and level of goal achievement and information access about performance of safety units. Since uncertain judgements of decision makers can be hardly estimated by numerical values, in this paper, based on grey system theory, a method was proposed for evaluating performance of safety units which was done using qualitative criteria of safety performance in an uncertain environment by one of the newest developed theory. This method used concept of grey theory to convert verbal variables into interval grey numbers; in the quantitative method, degree of grey possibility was imported.

The results showed that the most important performance indicator in the field of safety in inter-urban transportation management included specialized safety training, safety auditing, hazard identification and risk evaluation, employees’ health monitoring, solid waste management and management review.

This model could be extended for the whole safety issues and can be used as a simple and efficient method to evaluate performance of safety units in metro company of all the cities in order to determine their weaknesses and introduce the applied control strategies.

The purpose of this paper is to construct a novel grey incidence evaluation model to investigate a scientific and effective evaluation system of regional road traffic safety.

To provide a method for the evaluation of regional road traffic safety, the grey incidence feature vector method is employed to construct the evaluation index system for regional road traffic safety and then the index weights are calculated with Shannon entropy method. In this paper, the grey incidence feature vector method and grey incidence analysis are utilised to construct evaluation index systems for regional road traffic safety and determine the index weights. Then a grey incidence-ideal point method is used to establish a novel evaluation model for regional road traffic safety. To thoroughly investigate the road traffic safety in one region, the data of 13 cities in Jiangsu province is gathered, using the grey clustering and grey incidence-ideal point method to obtain the ranking results of the 13 cities.

The results provide a basic analysis of the present situation and show the differences for these regions based on the proposed model, according to which several solutions are proposed, aiming to improve regional road traffic safety situation.

The method exposed in the paper can be used to deal with the problems of the evaluation of regional road traffic safety.

The paper succeeds in understanding the status quo and implementing effective road traffic safety management based on the proposed model.

In a globalised environment, market volatility makes risk management an essential component of the supply chain. Similar to conventional supply chains, a Halal supply chain (HSC) is also affected by several factors making it vulnerable to risks. Therefore, the purpose of this study is to identify and analyse the elements of Halal supply chain management (HSCM) and their significant risk dimensions.

In total, 72 risk elements of HSCM are identified through a review of contemporary scientific literature along with news items and official websites related to risk management of conventional supply chain management, HSC and sustainable supply chain. Further, 42 risk elements are finalised using fuzzy Delphi and then these risk elements are categorised into 7 dimensions. The interrelationships among the risk dimensions as well as risk elements are developed using fuzzy DEMATEL.

Results suggest that production, planning, logistic & outsourcing and information technology-related risk are prominent risk dimensions. The causal relationships among the significant risk dimensions and elements related to the HSCM may help managers and policy planners.

This study faces a challenge due to inadequate availability of the literature related to risk management in the area of HSCM. Further, this study has used inputs from experts, which can be biased.

To the best of the author's knowledge, it is the first comprehensive study towards investigating the interrelationships among the risks in the context of the HSCM.

This paper intends to explore and appraise the humanitarian supply chain management enablers (HSCMEs) for efficient and effective humanitarian operations. This research aims to analyze the interaction of enablers for humanitarian supply chain management (HSCM) using a proposed hybrid framework consists of fuzzy Delphi (FD), interpretive structural modeling (ISM)–matriced impacts croises multiplication appliquee a un classement (MICMAC) and revised Simos approach.

This research is deliberate to identify 28 HSCMEs through a literature review and experts' opinions; out of which 20 HSCMEs are selected using FD. ISM is applied to know contextual relationship among the selected HSCMEs for developing a hierarchical model. The MICMAC analysis classifies the HSCMEs based on driving power and dependence power to validate the developed hierarchical ISM structure. The revised Simos technique is used to prioritize the HSCMEs to access its relative significance in humanitarian operations.

The finding of the analysis suggests that government policy and leadership support obtained the highest priority, having high driving power and low dependence power is significantly strategic and emerged as the leading driver for the HSCM implementation.

ISM model presents an insight into interrelationship among HSCMEs, but this cannot quantify the impact of each HSCMEs.

Disaster relief aid agencies and stakeholders may focus on the enablers having high driving power and higher weight in designing and executing an effective and efficient humanitarian supply chain and to improve their activities and strategies of HSCM.

This research helps humanitarian logisticians and humanitarian organizations to make better decisions to improve their operational performance in pre and postdisaster phases.

This paper explores the application of proposed hybrid framework to analyze the HSCMEs that can be considered as the original contribution.