Development of a decision support system for assessing the supply chain risk mitigation strategies: an application in Indian petroleum supply chain

Tarei, Pradeep Kumar; Thakkar, Jitesh J.; Nag, Barnali

doi:10.1108/jmtm-02-2020-0035

Cited by 14 publications

(7 citation statements)

References 80 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A combination of plans, processes, and activities capable of reducing accidents and their ensuing consequences and sufficient preparedness for dealing with any event can all boost safety resilience in an industry [20][21][22]. Moreover, given nature and unique characteristics of the chemical industry with its critical process parameters, chemical companies are constantly exposed to different types of threats, negative consequences, and vulnerabilities.…”

Section: The Results Of Using the Semi-quantitative Methods Of Safety...mentioning

confidence: 99%

Analyzing Resilience in Chemical Industry: A Cross-Sectional in a Process Industry

Amouei

Tehrani²,

Jozi³

et al. 2022

J. Hum. Environ. Health Promot

View full text Add to dashboard Cite

Background: This study aimed at developing and using a semi-quantitative method for analyzing safety resilience in the chemical industry. This cross-sectional, descriptiveanalytical study aimed to develop a semi-quantitative method for analyzing resilience. Methods: This study was carried out based on the Delphi method including 18 experts in chemical and process engineering as well as the health, safety and environment (HSE) engineering in 2018-2020. Results:The development of the semi-quantitative method for analyzing safety resilience took place after three rounds of the Delphi study. In this Delphi study, all the members of the experts' panel approved the three components of preparedness, likelihood, and severity with an 80% acceptance level. The results of the field study revealed 131 hazardous elements. The maximum and minimum values of resilience were found to be 500 and 100 belonging to failure in utility and failure in the distributed control system, respectively. Conclusion:The developed semi-quantitative method has acceptable reliability for the analysis of safety resilience in the chemical industry. Therefore, the analysis in the chemical industry can be considered an effective, necessary decision-making instrument for predicting and preventing dangers threatening the process, manpower, and nature of the chemical industry.

show abstract

Section: The Results Of Using the Semi-quantitative Methods Of Safety...mentioning

confidence: 99%

Analyzing Resilience in Chemical Industry: A Cross-Sectional in a Process Industry

Amouei

Tehrani²,

Jozi³

et al. 2022

J. Hum. Environ. Health Promot

View full text Add to dashboard Cite

show abstract

“…Besides, Guo et al (2021) proposed a machine learning method based on the C5.0 decision tree model and K‐means clustering algorithm to generate a regional landslide susceptibility map. Tarei et al (2021) developed a decision support system to help supply chain risk management strategies and accelerate the implementation of corresponding risk management drivers. The relationship between risk management strategies and drivers was explored by identifying potential factors between them, which can be further used to build decision support systems.…”

Section: Literature Reviewmentioning

confidence: 99%

Supply chain risk management of badminton supplies company using decision tree model assisted by fuzzy comprehensive evaluation

2023

View full text Add to dashboard Cite

Supply chain risk management is crucial for the management of sports goods companies, which can help enterprises better complete the transparent and efficient management of the whole process from production to sales. However, there are inevitably some potential risks. Thereby, to study the supply chain risk management of badminton supplies companies in the general environment, the supply chain risk evaluation index system of badminton supplies companies is established in this study by studying the connotation of supply chain risk management and combining the steps of fuzzy comprehensive evaluation (FCE) method. Then, according to these evaluation indexes, the modelling process of the classification and regression tree (CART) algorithm in the corporate overall supply chain risk decision tree is proposed. Moreover, the corporate overall supply chain risk decision tree is established. Moreover, the financial data of 10 A‐share listed companies of badminton and other sports goods listed on the Shanghai Stock Exchange in 2020 are selected as the sample dataset for model training and testing. The potential risks of badminton enterprises are predicted. The results show that the scale of badminton enterprises has been increasing gradually since 2018, but the return on total assets has steadily decreased with the increase of years. It shows that the badminton supplies enterprise's input and output assets are unbalanced, and the overall asset operation effect is relatively poor. However, the growth rate of total assets shows a significant upward trend from 2018 to 2020, rising from 4% to 12.69%. It indicates that the corporate investment and domestic and foreign investment expansion in recent years are high‐speed. The FCE method is employed to obtain the maximum eigenvalue of the enterprise, which is 5.4698. Then, the C.I value is 0.1205, the R.I value is 1.12, and the consistency ratio value is 0.0958 < 0.1, indicating that the judgement matrix is acceptable. It suggests that under the influence of the macro environment and economic situation, the sales situation of the badminton supplies company is subtly affected by the macro environment, and there is a great business risk.

show abstract

“…In response to supply chain challenges, gradually, a field of supply chain risk management (SCRM) has been introduced. According to Tarei et al (2020), SCRM has been defined as "a process that encompasses the collaborative and coordinated efforts of all parties involved in a supply chain to reduce vulnerability and increase robustness and resilience of the supply chain, ensuring profitability and continuity." From this definition, the risk hedging strategy is one of the SCRM approaches corresponding to the differing conditions of supply and demand risk environments (Manuj et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Aligning the risk hedging strategy with supplier collaboration and manufacturing competitiveness: a resource-based and contingency approach

Myamba

Nguni

2022

IJPPM

View full text Add to dashboard Cite

PurposeThe purpose of this study is to examine the alignment between the risk hedging strategy and supplier collaboration and its effect on manufacturing competitiveness.Design/methodology/approachBuilding on the resource-based view (RBV) and contingency theory (CT), this study is guided by a positivist philosophy and employs a survey strategy to investigate both the direct relationship between the risk hedging strategy and manufacturing competitiveness and the moderating role of supplier collaboration using data collected from 397 respondents of manufacturing firms. Partial least squares structural equation modeling (PLS-SEM) technique is used to analyze collected data and to present the research findings.FindingsConsistent with the RBV and CT, study findings indicate that a significant positive relationship exists between the risk hedging strategy and manufacturing competitiveness and that this relationship becomes stronger when supplier collaboration is interactively aligned. Study findings provide important insights on the role of the risk hedging strategy in promoting manufacturing competitiveness. Furthermore, supplier collaboration as a moderator accounts for a significant proportion of the relationship between the risk hedging strategy and manufacturing competitiveness.Research limitations/implicationsInternal resources provide an explanation of the competitive differences among firms employing the risk hedging strategy. However, the environment presents opportunities for firms to acquire additional resources to fulfil the unique collaborative requirements of the risk hedging strategy. This study has used the moderation perspective to explain the interaction between the risk hedging strategy and supplier collaboration and its effect on manufacturing competitiveness. Future studies could incorporate other alignment concepts such as mediation and systems approach and compare the results to improve the theory.Originality/valueThis study can be considered as its kind in the supply chain management literature and both practitioners and researchers can benefit from the experience of resource-based and contingency analysis research and the results of aligning the risk hedging strategy with supplier collaboration for higher levels of manufacturing competitiveness.

show abstract

Development of a decision support system for assessing the supply chain risk mitigation strategies: an application in Indian petroleum supply chain

Cited by 14 publications

References 80 publications

Analyzing Resilience in Chemical Industry: A Cross-Sectional in a Process Industry

Analyzing Resilience in Chemical Industry: A Cross-Sectional in a Process Industry

Supply chain risk management of badminton supplies company using decision tree model assisted by fuzzy comprehensive evaluation

Aligning the risk hedging strategy with supplier collaboration and manufacturing competitiveness: a resource-based and contingency approach

Contact Info

Product

Resources

About