Evaluation of sustainable supply chain risk management using an integrated fuzzy TOPSIS- CRITIC approach

Rostamzadeh, Reza; Ghorabaee, Mehdi Keshavarz; Govindan, Kannan; Esmaeili, Ahmad; Nobar, Hossein Bodaghi Khajeh

doi:10.1016/j.jclepro.2017.12.071

Cited by 308 publications

(211 citation statements)

References 54 publications

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“…Manage risk and cost-related risk as well as environmental, technical, and market risk [48][49][50] Environmental risk, technology risk, management risk, and market risk [51,52] Technology risk, market risk, transportation capacity, competition risk, and policy risk [53,54] Risk characteristics Technology risk, management risk, and marketing risk [55,56] Technology risk, manufacturing risk, market risk, management risk, and financial risk [57,58] Technology risk, market risk, cooperative risk, financial risk, and institutional risk [59,60] Risk processes Development risk, manufacturing risk, and marketing risk [61,62] Research risk, manufacturing risk, and market service risk [63] Development risk, manufacturing risk, and market risk [64] The classification of the risk management process by the International Standards Association, American Project Management Organization, Australian And New Zealand Standards, and American Sponsor Committee is basically the same, including environmental analysis, risk identification, risk assessment, risk response, and risk internal control [65][66][67][68]. For identifying green innovation risk, the flowchart method, fault tree method, and scenario analysis method are usually used.…”

Section: Risk Sourcesmentioning

confidence: 99%

“…The green innovation risk of the manufacturing industry has the following characteristics [48][49][50][51][52][53][54][55][56][57][58][59][60][61][62][63][64]. (i) Each stage of green innovation in the manufacturing industry faces various risks.…”

Section: Process Of Green Innovation Risk Identificationmentioning

confidence: 99%

“…The risk of green innovation is defined as the possibility of the suspension, termination, or failure of green innovation activities due to the uncertainty of the external environment of green innovation and the lack of the strength of the enterprises implementing green innovation on the basis of R&D clean energy and development of energy-saving and emission reduction technologies, as well as the losses caused. R&D risks stem from changes in personnel, finance, technology, and green policies in the R&D process [51][52][53][54][55][56][57][58][59][60]. Manufacturing risk also involves personnel and financial risk, followed by production risk [55][56][57][58]61,62].…”

Section: Process Of Green Innovation Risk Identificationmentioning

confidence: 99%

“…R&D risks stem from changes in personnel, finance, technology, and green policies in the R&D process [51][52][53][54][55][56][57][58][59][60]. Manufacturing risk also involves personnel and financial risk, followed by production risk [55][56][57][58]61,62]. Marketing risk also involves human and financial risk and is affected by markets and low-carbon policies [55][56][57][58][59][60][61][62].…”

Section: Process Of Green Innovation Risk Identificationmentioning

confidence: 99%

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Measuring and Integrating Risk Management into Green Innovation Practices for Green Manufacturing under the Global Value Chain

Sun

Yin

2020

Sustainability

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How to solve the contradiction between economic growth and ecological environmental protection is a practical problem that should be solved urgently at present. The development of green technology in the manufacturing industry must rely on technology innovation. However, the process of implementing green innovation in the manufacturing industry is full of high uncertainty and risk. First, the green innovation risks were divided into global green R&D risk, global green manufacturing risk, global green marketing risk, and global green service risk from the perspective of the process. Then, this study established a management criteria system of green innovation risk identification in the manufacturing industry under the global value chain (GVC). Furthermore, three methods were applied to identify the green innovation risk of the manufacturing industry under the GVC. Finally, this paper put forward the countermeasures to the green innovation risk of the manufacturing industry under the GVC. The empirical research results of this paper are as follows: From the perspective of the green innovation process, four risks are classified in this study, namely, global green R&D risk, global green manufacturing risk, global green marketing risk, and global green service risk. Among the four stages of green innovation risk, green marketing risk is the highest, followed by green service risk, and green R&D risk and green manufacturing risk are the least. Global green service risk and green R&D risk can be reduced mainly through risk diversification and risk reduction. Global green manufacturing risk and green marketing risk can be reduced mainly through risk diversification and secondary through risk reduction.

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Section: Risk Sourcesmentioning

confidence: 99%

Section: Process Of Green Innovation Risk Identificationmentioning

confidence: 99%

Section: Process Of Green Innovation Risk Identificationmentioning

confidence: 99%

Section: Process Of Green Innovation Risk Identificationmentioning

confidence: 99%

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Measuring and Integrating Risk Management into Green Innovation Practices for Green Manufacturing under the Global Value Chain

Sun

Yin

2020

Sustainability

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“…Theory-based resilience management is increasingly becoming a major objective for both local and globally connected suppliers and buyers to respond to disruptive events [122]. The proactive attainment of resilience not only ensures absorptivity of and adaptability to sudden changes, but also offers a competitive advantage through a distinct level of the recovery and regrowth process [123,124]. SCRES practices improve the sustainability of traditional SC network systems by considering network relationships, environmental issues, and obtainable competitive advantages.…”

Section: Conclusion and Future Studiesmentioning

confidence: 99%

Evidence-Based Resilience Management for Supply Chain Sustainability: An Interpretive Structural Modelling Approach

Shin

Park

2019

Sustainability

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The purpose of this study is to systematically identify and design improvement planning for supply chain resilience (SCRES) for a higher level of sustainability and a competitive advantage. Literature-based interpretive structural modelling (ISM), a pairing of the systematic literature review (SLR) and ISM approaches, is proposed for investigating and identifying a set of key performance measures of resilience for supply chain (SC) management. In line with previous research, we identified and updated 13 key SC capabilities out of 24 as core performance measures of supply network resilience. Furthermore, our findings categorised each capability and element into one of four types of influential power variables (drivers, dependent, autonomous, or linkage). This study (i) lends support to and updates previous research that examined the core capabilities of SCRES and (ii) provides complementary classifications for the influential powers of SCRES capabilities and elements. The literature indicates that there has been no research that has integrated SLR as a basis to ISM for an effective way to utilize existing studies for increasing awareness and developing managerial guidelines to achieve SCRES.

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Analysing the risks of adopting circular economy initiatives in manufacturing supply chains

Ethirajan

Kandasamy

et al. 2020

Bus Strat Env

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The concept of circular economy (CE) has proven its worth due to the scarcity of natural resources and huge amounts of wastage which impacts the environment. Thus, the adoption of the CE concept in the supply chain becomes critical. However, due to the complex nature of processes/activities in the circular supply chain (CSC), managing risk has become a priority to avoid disruption. In current literature, no discussion has been conducted on how to analyse the risks in the context of CSC. Therefore, to fill this literature gap, this study concentrates on identifying and analysing the risks to promote effective circular initiatives in supply chains in the context of the manufacturing industry, thus minimising the negative environmental impact. A total of 31 risks were identified through an extensive literature review and discussions with experts. A grey‐based decision‐making trial and evaluation laboratory (DEMATEL) method is applied by incorporating the experts' knowledge to compute prominence and cause/effect scores to develop an interrelationship map. Finally, a vulnerability matrix for risk categories is developed using the average of prominence and cause/effect scores of risks. The results show that transparent process is the most prominent risk and branding is the least significant risk. By using the average prominence and cause/effect score, a risk category, namely, financial risk, is identified as most vulnerable to CSC. These findings will help industry managers not only to prepare business strategies in the adoption of CE initiatives in supply chains by eliminating risks but also in minimising negative environmental impact.

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Evaluation of sustainable supply chain risk management using an integrated fuzzy TOPSIS- CRITIC approach

Cited by 308 publications

References 54 publications

Measuring and Integrating Risk Management into Green Innovation Practices for Green Manufacturing under the Global Value Chain

Measuring and Integrating Risk Management into Green Innovation Practices for Green Manufacturing under the Global Value Chain

Evidence-Based Resilience Management for Supply Chain Sustainability: An Interpretive Structural Modelling Approach

Analysing the risks of adopting circular economy initiatives in manufacturing supply chains

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