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Identifying and prioritizing supply chain risk is significant from any product’s quality and reliability perspective. Under an input-process-output workflow, conventional risk prioritization uses a risk priority number (RPN) aligned to the risk analysis. Imprecise information coupled with a lack of dealing with hesitancy margins enlarges the scope, leading to improper assessment of risks. This significantly affects monitoring quality and performance. Against the backdrop, a methodology that identifies and prioritizes the operational supply chain risk factors signifies better risk assessment.

The study proposes a multi-criteria model for risk prioritization involving multiple decision-makers (DMs). The methodology offers a robust, hybrid system based on the Intuitionistic Fuzzy (IF) Set merged with the “Technique for Order Performance by Similarity to Ideal Solution.” The nature of the model is robust. The same is shown by applying fuzzy concepts under multi-criteria decision-making (MCDM) to prioritize the identified business risks for better assessment.

The proposed IF Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) for risk prioritization model can improve the decisions within organizations that make up the chains, thus guaranteeing a “better quality in risk management.” Establishing an efficient representation of uncertain information related to traditional failure mode and effects analysis (FMEA) treatment involving multiple DMs means identifying potential risks in advance and providing better supply chain control.

In a company’s supply chain, blockchain allows data storage and transparent transmission of flows with traceability, privacy, security and transparency (Roy et al., 2022). They asserted that blockchain technology has great potential for traceability. Since risk assessment in supply chain operations can be treated as a traceability problem, further research is needed to use blockchain technologies. Lastly, issues like risk will be better assessed if predicted well; further research demands the suitability of applying predictive analysis on risk.

The study proposes a hybrid framework based on the generic risk assessment and MCDM methodologies under a fuzzy environment system. By this, the authors try to address the supply chain risk assessment and mitigation framework better than the conventional one. To the best of their knowledge, no study is found in existing literature attempting to explore the efficacy of the proposed hybrid approach over the traditional RPN system in prime sectors like steel (with production planning data). The validation experiment indicates the effectiveness of the results obtained from the proposed IF TOPSIS Approach to Risk Prioritization methodology is more practical and resembles the actual scenario compared to those obtained using the traditional RPN system (Kim et al., 2018; Kumar et al., 2018).

This study provides mathematical models to simulate the supply chain risk assessment, thus helping the manufacturer rank the risk level. In the end, the authors apply this model in a big-sized organization to validate its accuracy. The authors validate the proposed approach to an integrated steel plant impacting the production planning process. The model’s outcome substantially adds value to the current risk assessment and prioritization, significantly affecting better risk management quality.

Businesses are increasingly vulnerable and exposed to physical climate change risks, which can cascade through local, national and international supply chains. Currently, few methodologies can capture how physical risks impact businesses via the supply chains, yet outside the business literature, methodologies such as sustainability assessments can assess cascading impacts.

Adopting a scoping review framework by Arksey and O'Malley (2005) and the PRISMA extension for scoping reviews (PRISMA-ScR), this paper reviews 27 articles that assess climate risk in supply chains.

The literature on supply chain risks of climate change using quantitative techniques is limited. Our review confirms that no research adopts sustainability assessment methods to assess climate risk at a business-level.

Alongside the need to quantify physical risks to businesses is the growing awareness that climate change impacts traverse global supply chains. We review the state of the literature on methodological approaches and identify the opportunities for researchers to use sustainability assessment methods to assess climate risk in the supply chains of an individual business.

The purpose of this paper is to develop a model for upstream supply chain risk management linking risk identification, risk assessment and risk mitigation to risk performance and validate the model empirically. The effect of a continuous improvement process on identification, assessment, and mitigation is also included in the model.

A literature review is undertaken to derive the hypotheses and operationalize the included constructs. The paper then tests the path analytical model using partial least squares analyses on survey data from 162 large and mid‐sized manufacturing companies located in Germany.

All items load high on their respective constructs and the data provides robust support to all hypothesized relationships. Superior risk identification supports the subsequent risk assessment and this in turn leads to better risk mitigation. The model explains 46 percent of the variance observed in risk performance.

This study empirically validates the sequential effect of the three risk management steps on risk performance as well as the influence of continuous improvement activities. Limitations of this study can be seen in the use of perceptional data from single informants and the focus on manufacturing firms in a single country.

The detailed operationalization of the constructs sheds further light on the problem of measuring risk management efforts. Clear evidence of the performance effect of risk management provides managers with a business case to invest in such initiatives.

This is one of the first large‐scale, empirical studies on the process dimensions of upstream supply chain risk management.

Companies are increasingly challenged by sustainability-related supply chain risks. Research has developed linking supply chain sustainability priorities, practices and triple bottom line performance; however, risk is rarely included in these models. The purpose of this paper is to understand the link between sustainable supply chain strategies, practices and performance, and to test the importance of risk management practices in this relationship focusing on the product category level.

The paper includes a survey of supply managers in four countries with 305 responses, with a focus on upstream supply chain strategies at the product category level.

The environmental and social sustainability strategies lead to sustainable supply sustainable performance, through focused practices in either area, but the effect on operational and cost performance is not significant. Social supply chain strategies positively impact environmental and cost performance when mediated by risk assessment practices.

This paper shows a more nuanced view of the impact of supply chain practices on the strategy–performance link. It is one of the first papers to empirically test the role of risk practices in sustainable supply chain management and emphasize the importance of alignment across the main dimensions of sustainability to achieve positive sustainable performance outcomes, but not necessarily cost and operational performance. Unlike other studies, social sustainability priorities may positively impact environmental and social performance and is linked to cost advantage when implemented with risk assessment practices.

The purpose of this study is to identify the risks that exist in halal meat supply chain activities and to carry out a risk assessment using the fuzzy best-worst method (FBWM) along with mitigating risks using the risk mitigation number (RMN).

The method used is to collect several literature reviews related to the halal meat supply chain, which has information relevant to the risks of the meat industry in Indonesia. Then, a focus group discussion was held with several experts who play a role in the meat industry in Indonesia, and 33 identified risks were identified in halal meat supply chain activities. The proposed methodology uses FBWM and RMN in conducting risk assessment and mitigation in the meat industry in Indonesia.

The analysis reveals that priority risk is obtained by using the global weight value on the FBWM, and then risk mitigation is carried out with RMN. Priority mitigation strategies can mitigate some of the risks to the meat industry in Indonesia. The proposed mitigation strategy is designed to be more effective and efficient in preventing risks that can interfere with product halalness in halal meat supply chain activities in the Indonesian meat industry.

The implications of this study highlight the need for collaboration among stakeholders, improved risk assessment methodologies and the expansion of research into other halal supply chains. By addressing these implications, the halal industry can enhance its integrity, consumer confidence and overall contribution to the global market.

This research provides an integrated approach to identifying, analyzing, assessing and mitigating risks to the meat industry in Indonesia.

Halal integrity assurance is the primary objective of Halal supply chain management. Several halal-related risks are present that have the potential to breach halal integrity. Therefore, this study aims to develop the framework for the assessment of halal-related risk from a supply chain perspective.

Risk related to halal is identified through the combined approach of the systematic literature review and experts’ input. Further, these risks are assessed using the integrated approach of intuitionistic fuzzy number (IFN) and D-number based on their severity score. This integrated approach can handle fuzziness, inconsistency and incomplete information that are present in the expert’s input.

Eighteen significant risks related to halal are identified and grouped into four categories. These risks are further prioritised based on their severity score and classified as “high priority risk” or “low priority risks”. The findings of the study suggests that raw material status, processing methods, the wholesomeness of raw materials and common facilities for halal and non-halal products are more severe risks.

This study only focusses on halal-related risks and does not capture the other types of risks occurring in the supply chain. Risks related to halal supply chain management are not considered in this study. Prioritisation of the risks is based on the expert’s input which can be biased to the experts' background.

The proposed risk assessment framework is beneficial for risk managers to assess the halal related risks and develop their mitigation strategies accordingly. Furthermore, the prioritisation of the risks also assists managers in the optimal utilisation of resources to mitigate high-priority risks.

This study provides significant risks related to halal integrity, therefore helping in a better understanding of the halal supply chain. To the best of the authors' knowledge, this is the first comprehensive study for developing a risk assessment model for the halal supply chain.

The purpose of this paper is to provide a reliable and accurate instrument to assess the supply chain risk of similar comparable industries. This enables the firms which fall in this category of industry to identify and incorporate suitable risk sources under various risk constructs. This paper also provides a framework to the top management to prioritize the various risk constructs.

A systematic approach is used to develop and validate an instrument for assessing overall risk of supply chain. This includes specifying the domain and dimensionality of a construct, generation of initial pool of items, refinement of the initial items by the expert group, assessment of content validity, evaluation of reliability and construct validity of the scale items. Also a higher order measurement model of structural equation modeling is used to prioritize the various risk constructs.

The process yielded a robust instrument to assess overall risk of the supply chain. Through empirical verification, this instrument is shown to exhibit high levels of reliability and validity. The framework for prioritization of risk constructs revealed the importance of various supply chain risk constructs.

The framework is intended to be useful in practice for assessment of overall risk of heavy engineering industries supply chain. The procedure will be extended for development of risk assessment instrument for other industries which shares a common risk profile. Prioritization of various risk constructs with respect to the overall risk enables the top management to focus their attention to plan and manage the supply chain risks based on their relative importance.

This paper fulfils an identified need for the development of an empirically validated instrument by identifying the significant supply chain risk sources under major supply chain risk constructs for assessing the supply chain risk of industries which are similar in their risk profiles. Also provides a higher order model to identify the most influential risk constructs.

This paper aims to address how to systematically address vulnerability in a maritime transportation system using a formal vulnerability assessment approach, create quantitative measures of disruption risk and test the effect of mitigating measures. These quantitative data are prerequisites for cost efficiency calculations, and may be obtained without requiring excessive resources.

Supply chain simulation using heuristics‐based planning tools offers an approach to quantify the impact of disruption scenarios and mitigating measures. This is used to enrich a risk‐based approach to maritime supply chain vulnerability assessment. Monte Carlo simulation is used to simulate a stochastic nature of disruptions.

The exemplary assessment of a maritime liquefied natural gas (LNG) transportation system illustrates the potential for providing quantitative data about the cost of disruptions and the effects of mitigating measures, which are foundations for more precise cost efficiency estimates.

This simulation was done on a simplified version of a real transportation system. For resource reasons, several simplifications were made, both with regards to modeling the transportation system and with the implementation of the formal vulnerability assessment framework. Nevertheless, the authors believe the paper serves to illustrate the approach and potential outcome.

Practitioners are provided with an approach to get more precise quantitative data on disruption costs and cost/efficiency of mitigating measures, providing background data for decisions on investing in reduction of supply chain vulnerability.

The combination of risk assessment methods and inventory routing simulation of maritime supply chain problems is a novelty. Quantifying vulnerability, effects of disruptions and effects of mitigating measures in maritime transportation systems contributes to a little‐researched area.

This research aims to develop a supplier risk assessment methodology for measuring, tracking, and analyzing supplier and part specific risk over time for an automotive manufacturer.

Supply chain risk literature is analyzed and used in conjunction with interviews from the automotive manufacturer to identify risks in the supply base. These risks are incorporated into the development of a temporal risk assessment and monitoring system.

A framework of risk factors important to the auto manufacturer is presented. A multi‐criteria scoring procedure is developed to calculate part and supplier risk indices. These indices are used in the development of a risk assessment and monitoring system that allows the indices to be tracked over time to identify trends towards higher risk levels.

There are a number of operational issues identified in the paper that could be investigated in future research. One such issue is the development of alternative risk assessment methods that would increase the sensitivity of the risk analysis.

The framework is implementable in firms interested in understanding and controlling risk in their supply base. The research stems from an industry project with an automotive manufacturer. The method is designed to be practical and easy to implement and maintain. The system also has a visual reporting mechanism designed to provide early warning signals for potential problems in the supply base and to show temporal changes in risk.

This paper presents a dynamic risk analysis methodology that analyzes and monitors supplier risk levels over time.

In response to multiple disruptions, the purchasing supply management (PSM) function in construction supply chain management (CSCM) has gained prominence due to stakeholder pressures, dynamic market conditions and the need to adhere to complex sustainability, safety and health regulations and standards. However, there is a noticeable absence of empirical research on measuring and mitigating PSM vulnerabilities, especially considering the distinct challenges faced by large engineer-to-order project-oriented manufacturers. To address these issues, the purpose of this study is to develop and test a novel method to assist companies in construction supply chains in assessing and managing risks associated with sustainable procuring and sourcing materials.

Grounded in the literature gaps on construction PSM and a real case supply chain, the research uses the design science research (DSR) approach to develop an integrated method for assessing PSM strategies in this sector. The method integrates three essential purchasing dimensions: supply risks, profit impact and sustainability risks of materials, supported by nine subdimensions. Empirical validation took place within a multinational European construction company based in Denmark.

Findings from the supplier–buyer relationships confirmed that the developed method allows for the identification of the key components that significantly impact supplier–buyer relationships, profitability and sustainability. The research further suggests that construction supply chain managers and purchasing practitioners can use the proposed method to evaluate PSM, thus enabling them to make more informed decisions.

Through the utilization of the proposed artifact, construction companies can take a more proactive approach to address PSM uncertainties, thereby enhancing their competitiveness in dynamic construction supply chains.

The research contributes to bridging the theory and practice, providing valuable assistance for construction companies assessing and managing the PSM and supply risks within global construction value chains. This paper provides original insights for the CSCM, aiding in adopting competitive PSM strategies to improve overall supply chain performance.