Disruption causes and disruption management in supply chains with Chinese suppliers

2017 ◽  
Vol 47 (9) ◽  
pp. 843-863 ◽  
Author(s):  
Christian F. Durach ◽  
Patrick C. Glasen ◽  
Frank Straube
Keyword(s):  
Risk Management ◽  
Supply Chain ◽  
Supply Chains ◽  
Cultural Differences ◽  
Mitigation Strategies ◽  
Nominal Group ◽  
Disruption Management ◽  
Chinese Market ◽  
Supply Chain Disruption ◽  
Content Type

Purpose The purpose of this paper is to identify and rank supply chain disruption causes for Western buying firms in the Chinese market; to identify supplier-relationship-specific mitigation strategies to avoid and resist such disruptions; and to develop and propose a framework of relational supply chain disruption management with Chinese suppliers. Design/methodology/approach Two group exercises with 42 representatives from Western manufacturing buying firms and nine in-depth interviews were conducted. The group exercises applied the nominal group technique. Findings The authors identified and ranked 22 disruption causes in China for Western buying firms. Evaluating the five most urgent causes, 43 mitigation strategies could be identified that build on implementing strategic relationships with Chinese suppliers. A framework of relational supply chain disruption management for Western buying firms was developed with six propositions on primary constructs, mediators, and moderators, highlighting guanxi as a fundamental construct of relations within the Chinese culture. Research limitations/implications The findings contribute to theory development at the intersection of risk management and culture. Quantitative testing of the proposed relationships in the framework is needed to derive more reliable conclusions. Practical implications The study depicts how cultural differences between Chinese suppliers and Western buyers influence relational supply chain disruption management strategies. Using the study findings, managers of Western buying firms are informed regarding the most pressing disruption causes in the Chinese market and the value and strategic use of Chinese-supplier relationships. Originality/value The study provides a valuable contribution to the scant body of literature on disruption management in supply chains with Chinese suppliers. It contributes to our understanding of a successful risk management in the presence of cultural differences.

Strategic action grids: a study on supply chain risk management in manufacturing industries in India

2018 ◽  
Vol 25 (8) ◽  
pp. 3045-3061 ◽  
Author(s):  
V. Viswanath Shenoi ◽  
T.N. Srikantha Dath ◽  
C. Rajendran ◽  
P. Shahabudeen
Keyword(s):  
Risk Management ◽  
Supply Chain ◽  
Mitigation Strategies ◽  
Manufacturing Industries ◽  
Supply Chain Risk Management ◽  
Supply Chain Risk ◽  
Strategic Action ◽  
Content Type ◽  
The Mean ◽  
Robust Supply Chain

Purpose The purpose of this paper is to provide strategic recommendations to supply chain managers of Indian manufacturing industries for a robust supply chain related to risk management by original equipment manufacturers (OEMs) and suppliers in manufacturing industries to ensure a robust supply chain risk management (SCRM). Design/methodology/approach Importance-performance analysis (IPA) is utilized to identify and provide strategic recommendations to manufacturing industries for improving their supply chain performance by attaching due importance to risk constructs and appropriately choosing mitigation strategies. Findings The investigation using the strategic action grids reveals that most of the means of risks are near the point of intersection of the grand means of the risk constructs and their impact on the supply chain, indicating that all the risks have the equal likelihood of occurrence. The mean importance of risk monitoring, risk avoidance (RA) and risk sharing surpass the mean performance for both OEMs and suppliers. Research limitations/implications The study is executed with following limitations: the study assumes that the manufacturing industries across different sectors perceive similar risk. The sectors considered are automotive, heavy engineering, general engineering and home appliances. The Southern States of India are considered because of the dominant presence of many industries, especially automotive industries. However, it should be noted that these States form the manufacturing hubs where the lead organizations are functioning along with their major suppliers. Practical implications By understanding the importance of SCRM dimensions and utilization of these dimensions, firms can mitigate the impact of risk on the supply chain. The detailed study of SCRM strategies highlights the importance attached to risk factors, mitigation strategies, and top management commitment. By the implementation of SCRM strategies, supply chain managers can improve the firm’s performance. Originality/value The study involves empirically validated data on SCRM dimensions. The IPA is performed on the SCRM dimensions to investigate the importance attached to the factors of the dimensions and their performance.

scholarly journals Reverse logistics risk management: identification, clustering and risk mitigation strategies

2020 ◽  
Vol 58 (7) ◽  
pp. 1449-1474 ◽  
Author(s):  
Hamidreza Panjehfouladgaran ◽  
Stanley Frederick W.T. Lim
Keyword(s):  
Risk Factors ◽  
Risk Management ◽  
Supply Chain ◽  
Reverse Logistics ◽  
Risk Mitigation ◽  
Mitigation Strategies ◽  
Supply Chain Risk Management ◽  
Supply Chain Risk ◽  
Content Type ◽  
Risk Mitigation Strategies

PurposeReverse logistics (RL), an inseparable aspect of supply chain management, returns used products to recovery processes with the aim of reducing waste generation. Enterprises, however, seem reluctant to apply RL due to various types of risks which are perceived as posing an economic threat to businesses. This paper draws on a synthesis of supply chain and risk management literature to identify and cluster RL risk factors and to recommend risk mitigation strategies for reducing the negative impact of risks on RL implementation.Design/methodology/approachThe authors identify and cluster risk factors in RL by using risk management theory. Experts in RL and supply chain risk management validated the risk factors via a questionnaire. An unsupervised data mining method, self-organising map, is utilised to cluster RL risk factors into homogeneous categories.FindingsA total of 41 risk factors in the context of RL were identified and clustered into three different groups: strategic, tactical and operational. Risk mitigation strategies are recommended to mitigate the RL risk factors by drawing on supply chain risk management approaches.Originality/valueThis paper studies risks in RL and recommends risk management strategies to control and mitigate risk factors to implement RL successfully.

Differences in security risk perceptions between logistics companies and cargo owners

2016 ◽  
Vol 27 (2) ◽  
pp. 418-437 ◽  
Author(s):  
Luca Urciuoli ◽  
Juha Hintsa
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Latin American ◽  
Risk Perceptions ◽  
Mitigation Strategies ◽  
Security Measures ◽  
Security Risk ◽  
Security Risks ◽  
Content Type ◽  
Perception Of Security

Purpose – Supply chain stakeholders may perceive security risks differently and thereby misalign mitigation strategies. Hence, causing weak spots in supply chains and thereby disruptions. The purpose of this paper is to determine whether supply chain companies actually perceive security risks and effectiveness of mitigation strategies differently. Design/methodology/approach – Two survey studies measuring perception of security risks and effectiveness of measures have been developed and used to collect data from European and Latin American companies, grouped as cargo owners and logistics companies. Findings – The findings of the surveys unveil that only two (out of six) security risks, namely, violation of customs non-fiscal regulations and illegal immigration, show significant differences between the two groups of companies. In addition, the surveys show that companies perceive equally the effectiveness of security measures. This study concludes that supply chains seem to have good visibility over the security risks of their partners. Hence, in terms of security, supply chain companies seem to have achieved a common understanding of risks and furthermore are able to act jointly to secure assets and operations. Originality/value – Previous research claim supply chain stakeholders may perceive risks differently and thereby may fail to correctly align mitigation strategies. Yet, to the authors knowledge, previous research has not empirically demonstrated these differences in perceptions of risks and mitigation strategies.

scholarly journals Collaborative risk management in decentralised multi-tier global food supply chains: an exploratory study

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shoufeng Cao ◽  
Kim Bryceson ◽  
Damian Hine
Keyword(s):  
Risk Management ◽  
Supply Chain ◽  
Supply Chains ◽  
Field Study ◽  
Food Supply ◽  
Risk Sharing ◽  
Fresh Produce ◽  
Supply Chain Risk Management ◽  
Content Type ◽  
Food Supply Chains

PurposeThe aim of this paper is to explore the value of collaborative risk management in a decentralised multi-tier global fresh produce supply chain.Design/methodology/approachThis study utilised a mixed methods approach. A qualitative field study was conducted to examine the need for collaborative risk management. The simulation experiments with industry datasets were conducted to assess whether risk-sharing contracts work in mitigating joint risks in parts of and across the supply chain.FindingsThe qualitative field study revealed risk propagation and the inefficiency of company-specific risk management strategies in value delivery. The simulation results indicated that risk-sharing contracts can incentivise various actors to absorb interrelated risks for value creation.Research limitations/implicationsThe research is limited to risks relevant to supply chain processes in the Australia–China table grrape supply chain and does not consider product-related risks and the risk-taking behaviours of supply chain actors.Practical implicationsCollaborative risk management can be deployed to mitigate systematic risks that disrupt global fresh produce supply chains. The results offer evidence-based knowledge to supply chain professionals in understanding the value of collaborative risk assessment and management and provide insights on how to conduct collaborative risk management for effective risk management.Originality/valueThe results contribute to the supply chain risk management literature by new collaborative forms for effective risk management and strategic competition of “supply chain to supply chain” in multi-tier food supply chains.

How big data analytics can help manufacturing companies strengthen supply chain resilience in the context of the COVID-19 pandemic

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Surajit Bag ◽  
Pavitra Dhamija ◽  
Sunil Luthra ◽  
Donald Huisingh
Keyword(s):  
Risk Management ◽  
Big Data ◽  
Supply Chain ◽  
Supply Chains ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Hypothetical Model ◽  
Content Type ◽  
Supply Chain Resilience ◽  
Management Capabilities

PurposeIn this paper, the authors emphasize that COVID-19 pandemic is a serious pandemic as it continues to cause deaths and long-term health effects, followed by the most prolonged crisis in the 21st century and has disrupted supply chains globally. This study questions “can technological inputs such as big data analytics help to restore strength and resilience to supply chains post COVID-19 pandemic?”; toward which authors identified risks associated with purchasing and supply chain management by using a hypothetical model to achieve supply chain resilience through big data analytics.Design/methodology/approachThe hypothetical model is tested by using the partial least squares structural equation modeling (PLS-SEM) technique on the primary data collected from the manufacturing industries.FindingsIt is found that big data analytics tools can be used to help to restore and to increase resilience to supply chains. Internal risk management capabilities were developed during the COVID-19 pandemic that increased the company's external risk management capabilities.Practical implicationsThe findings provide valuable insights in ways to achieve improved competitive advantage and to build internal and external capabilities and competencies for developing more resilient and viable supply chains.Originality/valueTo the best of authors' knowledge, the model is unique and this work advances literature on supply chain resilience.

Towards more balanced sourcing strategies – are supply chain risks caused by the COVID-19 pandemic driving reshoring considerations?

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Remko van Hoek ◽  
David Dobrzykowski
Keyword(s):  
Decision Making ◽  
Risk Management ◽  
Supply Chain ◽  
Supply Chains ◽  
Research Process ◽  
Manufacturing Companies ◽  
Content Type ◽  
Management Techniques ◽  
The Many ◽  
The Impact

Purpose Reshoring is one of the supply chain risk management techniques suggested in literature. However, literature suggests that the decision-making involved in reshoring is complex and not fully understood. In the context of the COVID-19 pandemic, reshoring may represent a way to reduce reliance on global sources and improve resilience of their supply chains. This paper aims to explore if the pandemic is driving reshoring decisions and if the pandemic will actually lead to companies reshoring parts of their supply chain. Design/methodology/approach This paper critically engages with senior(-most) supply chain managers from three manufacturing companies as they proceed through reshoring decision-making. This enables to develop experiential knowledge about reshoring decision-making processes and their context, as well as insights into the relevance of existing knowledge about reshoring. While not a full multiple case study, the opportunity to engage directly with senior(-most) supply chain managers as they consider reshoring, enables near real-time learning. Not only is reshoring a very timely topic literature has also called for more event-based empirical research. Further to that, it is hoped that this can complement this special issue and support, in a timely manner, the many researchers that are actively studying the impact of the pandemic on supply chains. Findings Reshoring was being actively considered by all three companies during the research process in Q3 and Q4 of 2020. During this period the pandemic has not yet led to substantial implementation of reshoring, at least by the companies studied in this paper. In response to tariffs on Chinese imports, companies had been diversifying their supply base away from China, but doing so by developing alternative, global sources. Additionally, companies are using alternative risk management techniques, such as supplier collaboration, in the short to medium term. Reshoring decision-making is indeed found to be complex and requires a longer-term time horizon for decision-making and implementation. Logistical challenges and growth in demand do drive a willingness of consumers to pay a premium for locally sourced products. However, when supply normalizes these considerations might lose relevance well before reshoring decision-making and implementation can be completed. Originality/value This paper studies reshoring in a real-world setting, learning directly from insights from industry as they emerge. This paper develops four extensions to existing knowledge, develop these in frameworks and hope that this will support ongoing consideration in industry and support the many researchers that are active in this domain today. This paper also suggests several directions for further research.

scholarly journals Big data and connectivity in long-linked supply chains

2018 ◽  
Vol 33 (8) ◽  
pp. 1201-1208 ◽  
Author(s):  
Per Engelseth ◽  
Hao Wang
Keyword(s):  
Risk Management ◽  
Big Data ◽  
Supply Chain ◽  
Supply Chains ◽  
Technology Use ◽  
Future Research ◽  
Alternative View ◽  
Research Approach ◽  
Ongoing Research ◽  
Content Type

Purpose This study aims to consider the developing of strategic use of big data in association with long-linked physical goods supply focusing on risk management. Design/methodology/approach Analysis is grounded on a case study of organizing the import of machine parts from Shanghai, China, to Norway. An analytical framework is developed through a literature review on long linked supply chains, big data and risk management. Findings Analysis reveals that big data use in this scenario encompasses mainly around handling risks associated with transformations in the supply chain, a data-driven approach. Complexity is founded in transformation – the flows of goods and information. Supply chain dynamics represent an important source for data acquisition for big data analytics. Research limitations/implications The qualitative nature of the study limits the aim of generalization. An alternative view of big data as process is discussed and proposed, adapted to supply chain management and industrial marketing functionality. Originality/value This is the first part in an ongoing research project aimed at developing a research approach to study information technology use in the inherently complex setting and scope of a long linked supply network. This scope of investigation enhances big data associated with operations dynamics providing foundation for future research on how to use big data to mitigate risk in long linked supply chains.

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

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Pradeep Kumar Tarei ◽  
Jitesh J. Thakkar ◽  
Barnali Nag
Keyword(s):  
Risk Management ◽  
Supply Chain ◽  
Decision Support ◽  
Support System ◽  
Risk Sharing ◽  
Risk Mitigation ◽  
Mitigation Strategies ◽  
Supply Chain Risk ◽  
Content Type ◽  
Risk Mitigation Strategies

PurposeThe purpose of this paper is to develop a decision support system (DSS) to assist supply chain (SC) risk managers to select a suitable risk management (RM) strategy and expedite the implementation of corresponding RM enablers. The relationship between RM strategies and RM enablers is explored by identifying the underlying factors between them, which is further used to build the DSS.Design/methodology/approachThe DSS is built by integrating heterogeneous techniques. A systematic review approach is employed to explore both proactive and reactive RM enablers, and they are further mapped to various RM strategies by using correspondence analysis (CA). An in-depth interview is conducted to develop the rules for constructing the decision system. A rule-based fuzzy inference system (FIS) is utilized to counteract the uncertainty involved in the decision variables. The efficacy of the proposed DSS is demonstrated by considering two conjectural scenarios in the case of Indian petroleum SC (IPSC).FindingsThe results reveal three primary underlying factors between the risk mitigation strategies viz. SC managers' preparedness to face risk, organization's resource capability to deal with risk and the sophistication of the implementation of the RM enablers; with explained variances of 37%, 29% and 22%, respectively. Risk avoidance strategy comprises of RM enablers such as supplier evaluation, technology adaption, information security, etc. Whereas, the risk-sharing strategy includes revenue sharing, insurance, collaboration, public-private-partnership, etc. as essential RM enablers. The DSS recommends risk-mitigation and risk-sharing as effective RM strategies for the IPSC under the considered scenarios.Research limitations/implicationsThis paper develops a decision support framework for recommending an effective risk mitigation strategy and outranking the corresponding enablers. The study explicitly focuses on the risk mitigation step of the supply chain risk management (SCRM) process. Pre- and post-risk mitigation steps of the SCRM process, such as risk assessment and risk monitoring are beyond the scope of this research.Originality/valueThe operational procedure of the proposed DSS is explained by considering a real-life case of petroleum SC in the Indian scenario. The unique contributions of this study are presented as theoretical implications and managerial propositions in the context of a developing country.

The Six Sigma framework improves the awareness and management of supply-chain risk

2020 ◽  
Vol 32 (5) ◽  
pp. 1021-1037
Author(s):  
Roy Andersson ◽  
Yinef Pardillo-Baez
Keyword(s):  
Risk Management ◽  
Supply Chain ◽  
Supply Chains ◽  
Six Sigma ◽  
Lean Six Sigma ◽  
Supply Chain Risk ◽  
Holistic View ◽  
Content Type ◽  
Management Culture ◽  
Training Structure

PurposeModern supply chains are at risk as a result of increasing disturbance. The use of Lean and Six Sigma’'s values, methods and tools can be one option to analyze, prevent and mitigate risks. The purpose of this study is to investigate whether a combined Lean Six Sigma philosophy can support the awareness and management of supply-chain risk.Design/methodology/approachThe methodology followed in the study is based on a literature review and multiple case study, performed by means of qualitative methods of data collection, such as observations on-site, face-to-face interviews and document analysis. Case selection includes the results of research conducted in seven large Swedish companies.FindingsIt has been indicated that Lean and Six Sigma values, methods and tools can be very effective in companies’ efforts to control the supply-chain risks and that they improve the companies’ ability to handle variability and risk management. Lean Six Sigma supports a risk-management culture in the focal companies, but they must involve customers and companies in the supply chain if they wish to create a risk-management culture in the entire supply chain. In order to do this, they can use the Six Sigma training structure, but they need to include more risk tools and methods developed for the supply chain management. It has also been indicated in the literature that if more people involve in 6S projects, the financial results will be better, and the innovation of processes will increase.Research limitations/implicationsThese include suggestions for how the companies can use the Six sigma training structure to collaborate in the supply chain.Practical implicationsThis study gives practical suggestions for how the companies in supply chain can collaborate and use the Six Sigma training structure for creating a more holistic view of supply chain, which also decrease risks in supply chain.Originality/valueThis study indicates that Lean Six Sigma supports risk awareness and management in the focal companies of the supply chains, which improves companies’ ability to handle variability and risk management. It has also been demonstrated that the companies should use the Six Sigma framework, especially training, as a foundation, and they should create common projects for better collaboration in the supply chain, which will decrease the risks in the entire supply chain.

scholarly journals Risk interaction identification in international supply chain logistics

2018 ◽  
Vol 38 (2) ◽  
pp. 372-389 ◽  
Author(s):  
Dong-Wook Kwak ◽  
Vasco Sanchez Rodrigues ◽  
Robert Mason ◽  
Stephen Pettit ◽  
Anthony Beresford
Keyword(s):  
Risk Management ◽  
Supply Chain ◽  
Risk Analysis ◽  
Supply Chains ◽  
Analysis Model ◽  
Content Type ◽  
Risk Elements ◽  
Supply Chain Logistics ◽  
Holistic Understanding ◽  
Level 2

Purpose International supply chains can be severely disrupted by failures in international logistics processes. Therefore, an understanding of international logistics risks, or causes of failure, how these may interact with each other and how they can be mitigated are imperatives for the smooth operation of international supply chains. The purpose of this paper is to specifically investigate the interactions between international logistics risks within the prevailing structures of international supply chains and highlights how these risks may be inter-connected and amplified. A new dynamic supply chain logistics risk analysis model is proposed which is novel as it provides a holistic understanding of the risk event interactivity. Design/methodology/approach The paper applies interpretive structural modelling to data collected from a survey of leading supply chain practitioners, in order to analyse their perspectives of risk elements and interactions. The risk elements and their contextual relationship were derived empirically through the use of focus groups and subsequent Delphi study. The two stages of the research rely on experts’ views on risk events and clusters and the level of interactions among those clusters. Findings A key finding of this research is that supply chain practitioner’s perception of risk consists of inter-connected four levels: value streams risks; information and relationship risks; risks in international supply chain activities; and external environment. In particular, since level 2 risk creates feedback loops of risks, risk management at level 2 can dampen the amplification effect and the strength of the interactions. Practical implications Several managerial implications are drawn. First, the research guides managers in the identification and evaluation of risk events which can impact the performance of their international logistics supply chain operations. Second, evidence is presented that supports the proposition that the relationships with trading partners and LSPs, and the degree of logistics information exchange, are critical to prevent, or at least mitigate, logistics risks which can substantially affect the responsiveness of the international supply chain. Originality/value The main contribution to knowledge that this study offers to the literature on supply chain risk management is the development of a supply chain logistics risk analysis model which includes both risk elements and interactions. The research demonstrates the importance of taking into account risk interactions in the process of identification and evaluation of risk events.

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