Search results

This research aims to specialise in the investigation of risk management for service-oriented manufacturing supply chains via two stages, highlighting its differences from manufacturing. The research article is commenced by executing an encyclopedic review of earlier research to ascertain the distinctive traits of service-oriented manufacturing supply chains and identify prevalent risks. Secondly, an empirical study in the construction field, amongst the industry hardest struck in the mist of the COVID-19 epidemic, is conducted to thoroughly inspect the resonant effect of these risks on service-oriented manufacturing supply chain performance.

In this study, to validate the resonant effect mechanism, a thorough assessment is undertaken by juxtaposing theoretical model to a newly constructed comparative model that encompasses the single effects of risks on supply chain performance.

63% variance of service-oriented manufacturing supply chain performance was showcased by the resonant effect model, compared with 46.3% in the comparative model. Moreover, each risk exerts a more glaringly significant impact on supply chain performance, asserting the mechanism of the resonant influence. Another noteworthy result involves the demand risk possessing a low effect on supply chain performance, thus emphasising the superiority of service-oriented manufacturing supply chains.

Future research endeavours should hinge on the optimal “resonant” model explosion, thereby foreseeing and alleviating worst-case scenarios to guarantee the robustness and resilience of supply chain networks.

Indubitably, reducing the intensity of the resonant effect revolves around lowering the coefficient of “a,” thereby restricting/eliminating the link among risks. Therefore, the suggested resonant impact model might thus serve as “a road map”. In light of the aforementioned considerations, it is advisable that supply chain executives employ supply chain management tactics namely avoidance, prediction, and postponement, but only after meticulous consideration the costs and benefits of adopting such strategies.

The service-oriented manufacturing supply chain features and advantages have been analysed and explained throughout the article. The data gathered during the COVID-19 pandemic is a captivating and topical point of this paper.

Supply chains are among the most important, complex and risky systems in the modern world. Thus, managing risk is no longer an option, but a fundamental process in organizations. Given the lack of pathways that guide companies toward supply chain risk management (SCRM), the purpose of this study is to provide a conceptual reference, in the form of a maturity model, to support them in the evolution and improvement of this process.

The proposal covered a broad literature review, a survey and a multiple case study. The research was conducted in the aerospace industry and included companies from the supply chain of a leading aircraft manufacturer.

The model elaborated with the research results has eight attributes and four levels, addressing critical issues for SCRM to achieve its scope and purposes. The attributes include the structuring and scope of the SCRM process, the importance it receives within the organization, the resources used and the qualification of employees, the role of leadership and the inter-organizational collaboration.

Managing risk along supply chains is particularly challenging, demands resources and knowledge and requires a continuous effort. The proposed model offers a reference for improvement, helping to identify areas that need to be strengthened and practices to be implemented. Thus, it can guide the focus and efforts in a more efficient and systematic way, in addition to support evaluations and comparisons.

Although maturity models are abundant in different fields and several are available for risk management, models specifically developed for SCRM are scarce. This study broadens the understanding of SCRM with novel insights about how to improve this process in an evolutionary way. While many researchers focused their efforts on the SCRM process steps, this study identified critical issues that transcend these steps. The research was carried out in a sector with a long tradition in risk management and included companies belonging to a same supply chain, that is, using an approach still little explored in studies on SCRM or risk management maturity models.

Acknowledging, on the one hand, the increasing fragility of supply chains and the number of risks involved in supply chain operations and, on the other hand, the role of small- and medium-sized enterprises (SMEs) in supply chains and the high exposure of these firms to risks of different types, this study aims to examine the relationship between supply chain risk management (SCRM) and innovation performance in SMEs. Furthermore, the impact of technological turbulence on this relationship was studied to take into account recent technological changes.

Structural equation modelling was carried out on a sample of Turkish SMEs to test the hypotheses developed.

The findings presented allow the authors to better understand the link between SCRM and innovation performance in SMEs. More precisely, empirical evidence is provided about the impact of SCRM components such as maturity and ability on innovation performance. Furthermore, the findings show the impact of technological turbulence on both SCRM and innovation performance.

By focusing on SCRM in SMEs, this paper contributes to the body of knowledge with regard to SCRM in general and with regard to SMEs in particular; research on the latter has only started recently. Moreover, by having studied SMEs from a developing country (other than China), this paper helps to develop a broader and more diverse perspective of SCRM.

Due to the uniqueness of individual construction projects, identifying the dominant risk factors is needed for risk mitigation in ongoing and future projects. This study aims to identify the dominant construction supply chain risk (CSCR) factors, based on studies conducted between 2002 and 2022.

The study adopts the preferred reporting items for systematic reviews and meta-analysis (PRISMA) procedure to identify, screen and select relevant articles in order to provide a bibliography and annotation of the prevalent risks in the supply chains. A descriptive analysis of the findings then follows.

The study’s findings have highlighted the three most prevalent risks in the construction supply chain (poor communication across project teams, changes in foreign currency rate, unfavorable climate conditions) as reported in literature, that project teams need to pay closer attention to and take proactive steps to mitigate.

Due to limitations imposed by the chosen research methodology, tools, time frame and article availability, the study was unable to examine all CSCR-related papers.

The results will serve as a useful roadmap for risk/supply chain managers in the construction industry to take strategically proactive steps towards allocating resources for CSCR mitigation efforts.

Context-specific research on the impact of social and cultural risks on the construction supply chain would be beneficial, due to emerging social network risk factors and the complex socio-cultural settings.

There is presently no study that has reviewed extant studies to identify and compile the dominant risk factors (DRFs) associated with the supply chain of construction projects for ranking in the supply chain risk management process.

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.

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.

This study aims to investigate the contribution of blockchain technology to supply chain risk management and its impact on performance among Indian manufacturing companies.

Drawing on a resource-based view, dynamic capability and system of systems theory, this study examines the direct relationships between blockchain, supply chain risk management and supply chain performance. The authors validate the mediating effects of three supply chain risk management components, namely supply risk management, demand risk management and cyber security management, on financial transaction reliability and information reliability. Data were collected from 204 Indian manufacturing companies that have adopted blockchain technology.

The results demonstrate that companies adopting blockchain technology have experienced positive outcomes in managing supply chain-related risks, financial transaction reliability and information reliability. These findings provide valuable guidance to managers, highlighting blockchain as a competitive advantage for supply chain management.

To the best of the authors’ knowledge, no previous research on blockchain-based risk management capabilities has been conducted.

Globalisation, trade barriers, unprecedented health crises and geo-political crises have forced organisations to revisit their performance measurement systems (PMS) to better prepare their supply chain against the risk and improve performance in times of crisis. This study aims to review the supply chain operation reference (SCOR)-based PMS and propose a dynamic SCOR-based PMS for supply chain risk management (SCRM).

Due to the need for multi-stakeholder perspectives on SCOR-based PMS for the SCRM, the authors aimed to develop a theory rather than to elaborate upon or test the theory. Hence, the authors adopted an inductive theory-building approach to build research propositions. The authors also gathered 12 semi-structured interviews with knowledgeable managers from B2B international companies.

The findings of the study highlight the challenges faced by the organisations during the implementation of the SCOR-based performance indicators and the positive impacts they have on decision-making and on the continuous improvement strategy of organisations to tackle supply chain risks and improve performance. The findings suggest that the effects of these indicators are more felt during risk management and risk monitoring stages.

Like any other study, this study has some rules, and, thus, the authors caution the readers that they must interpret the findings of the research considering these limitations. The study is based on semi-structured qualitative interviews. The interviews were conducted with 12 knowledgeable managers from France; thus, the insights drawn from the study cannot be generalised to other settings. Furthermore, the samples represent something other than small and medium enterprises. In the future, the samples from small and medium firms can offer a nuanced understanding of the performance indicators for SCRM.

To the best of the authors’ knowledge, this is one of the few studies which has attempted to revisit the SCOR-based PMS in the B2B supply chain for risk management. The study’s findings help expand the SCOR-based PMS literature and offer numerous insights to the management and consultants facing challenges in SCOR implementation.

The fresh food supply chain industry faces significant challenges in risk management because of the complexity, immature development and unpredictable external environment of imported fresh food supply chains (IFFSCs). This study aims to identify specific risk factors in IFFSCs, demonstrate how these risks are transmitted within the system and provide an analytical framework for managing these risks.

A total of 15 risk factors for IFFSCs through extensive literature review and expert consultation are identified and classified into seven levels using interpretive structural modeling (ISM) to demonstrate the risk transmission path. Fuzzy Matrice d’Impacts Croises-Multiplication Appliance Classement (MICMAC) analysis is then used to analyze the role of each factor.

The interactions of the 15 identified risk factors of IFFSCs, classified into seven levels, are visualized using ISM. The fuzzy MICMAC analysis classifies the factors into four groups, namely, dependent, independent, linkage and autonomous factors, and identifies the relatively critical risk factors in the system.

The findings of this research provide a clear framework for enterprises operating in IFFSCs to understand the specific risks they may face and how these risks interact within the system. The fuzzy MICMAC analysis also classifies and highlights critical risk factors in the system to facilitate the formulation of appropriate mitigation measures.

This study provides enterprises in IFFSCs with a comprehensive understanding of how the risks can be effectively managed and a basis for further exploration. The theoretical model constructed is also a new effort to address the issues of risk in IFFSCs. The ISM and the fuzzy MICMAC analysis offer clear insights for researchers and enterprises to grasp complex concepts.

Supply chains must rebuild for resilience to respond to challenges posed by systemwide disruptions. Unlike past disruptions that were narrow in impact and short-term in duration, the Covid pandemic presented a systemic disruption and revealed shortcomings in responses. This study outlines an approach to rebuilding supply chains for resilience, integrating innovation in areas critical to supply chain management.

The study is based on extensive debates among the authors and their peers. The authors focus on three areas deemed fundamental to supply chain resilience: (1) forecasting, the starting point of supply chain planning, (2) the practices of supply chain risk management and (3) product design, the starting point of supply chain design. The authors’ debated and pooled their viewpoints to outline key changes to these areas in response to systemwide disruptions, supported by a narrative literature review of the evolving research, to identify research opportunities.

All three areas have evolved in response to the changed perspective on supply chain risk instigated by the pandemic and resulting in systemwide disruptions. Forecasting, or prediction generally, is evolving from statistical and time-series methods to human-augmented forecasting supplemented with visual analytics. Risk management has transitioned from enterprise to supply chain risk management to tackling systemic risk. Finally, product design principles have evolved from design-for-manufacturability to design-for-adaptability. All three approaches must work together.

The authors outline the evolution in research directions for forecasting, risk management and product design and present innovative research opportunities for building supply chain resilience against systemwide disruptions.