Search results

Digital transformation misalignment refers to disparities in digital transformation levels between suppliers and buyers across the production and operation process. It has negatively affected supply chain stability. However, the existing research concerning the economic consequences has not been adequately addressed. Therefore, this paper aims to investigate whether such digital transformation misalignment increases supplier financial risk and to identify the factors influencing this relationship.

This paper examines binary combinations of suppliers and buyers listed on China’s A-share market between 2011 and 2021. This group constitutes a sample to empirically test the influence of digital transformation misalignment on the supplier’s financial risk, as well as the moderating effect of the geographical and organizational distances.

The paper’s findings demonstrate that digital transformation misalignment has indeed a significant increase in the supplier’s financial risk. Moreover, the impact is more intense when the geographical or organizational distance between the supplier and the buyer is relatively large.

The existing literature rarely explores the potential risks arising from digital transformation misalignment between supply chain partners. Therefore, this paper fills a notable gap as it is the first to study the impact of digital transformation misalignment on the supplier’s financial risk and the specific applied mechanisms. The contribution significantly improves the field of corporate digital transformation, particularly, within the context of supply chain management.

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.

This paper is motivated by the need to assess the risk profiles associated with the substantial number of items within military supply chains. The scale of supply chain management processes creates difficulties in both the complexity of the analysis and in performing risk assessments that are based on the manual (human analyst) assessment methods. Thus, analysts require methods that can be automated and that can incorporate on-going operational data on a regular basis.

The approach taken to address the identification of supply chain risk within an operational setting is based on aspects of multiobjective decision analysis (MODA). The approach constructs a risk and importance index for supply chain elements based on operational data. These indices are commensurate in value, leading to interpretable measures for decision-making.

Risk and importance indices were developed for the analysis of items within an example supply chain. Using the data on items, individual MODA models were formed and demonstrated using a prototype tool.

To better prepare risk mitigation strategies, analysts require the ability to identify potential sources of risk, especially in times of disruption such as natural disasters.

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 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.

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.

Drawing on the dynamic capability view (DCV), this research determines the suitable configurations of resilience strategies for sustainable tourism supply chain performance amidst “extreme” disruptive events affecting the entire supply chain.

This research applies a multi-study and multi-method approach. Study 1 utilizes in-depth interviews to identify a list of tourism supply chain sustainability risks and resilience strategies. Study 2, using quality function deployment (QFD) technique, determines the most important resilience strategies corresponding to highly significant risks. Study 3, on the other hand, adopts a fuzzy set qualitative comparative analysis (fsQCA) to determine the best recipe of resilience strategies and risks to make the tourism supply chain performance sustainable.

The findings reveal that sustainable tourism performance during an extreme disruptive event (e.g. COVID-19 health crisis) depends on the combined effect of tourism resilience strategies and risks instead of their individual effect.

The research findings offer significant managerial implications. Managers may experiment with multiple causal conditions of risks and resilience strategies to engender the expected outcome.

This research extends current knowledge on tourism supply chain and offers insights for managers to mitigate the risks and ensures sustainable performance in the context of extreme disruptive events.

In the last few years, environmental issues have become a matter of survival. In this sense, e-waste management is among the major problems since it may be a way of mitigating mineral depletion. In this context, the literature lacks e-waste supply chain studies that systematically map supply chain challenges and risks concerning material recovery.

Given this context, the authors' paper conducted a systematic literature review (SLR) to build a framework to identify the constructs of e-waste supply chain risk management.

The paper revealed the theoretical relationship between important variables to achieve e-waste supply chain risk management via a circular economy (CE) framework. These variables include reverse logistics (RL), closed-loop supply chains (CLSC), supply chain risk management, supply chain resilience and smart cities.

The literature contributions of this paper are as follows: (1) a complete list of the risks of the e-waste supply chains, (2) the techniques being used to identify, assess and mitigate e-waste supply chain risks and (3) the constructs that form the theoretical framework of e-waste supply chain risk management. In addition, the authors' results address important literature gaps identified by researchers and serve as a guide to implementation.

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.