Demand planning as a tamer and trigger of operational risk disruptions: evidence from the European supply chains

2019 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Artur Swierczek ◽  
Natalia Szozda
Keyword(s):  
Risk Management ◽  
Supply Chain ◽  
Supply Chains ◽  
Planning Process ◽  
Operational Risk ◽  
Negative Consequences ◽  
Content Type ◽  
Demand Planning ◽  
Operational Risks ◽  
And Control

Purpose The purpose of this paper is to explore the effects of demand planning practices on the disruptions induced by operational risk. The study reveals whether the negative consequences of operational risk factors (covering demand, supply, control and process risks) can be absorbed or amplified through the application of specific demand planning practices in supply chains. Design/methodology/approach The study involves the partial least squares path model procedure. Likewise, the items of the constructs in the outer model were subjected to a purification process by principal component analysis with the orthogonal (varimax) and oblique (Promax) methods of rotation. Findings The findings suggest that although one may not observe uniformity and standardization in the role of demand planning in alleviating the negative effects of operational risks, still some regularities can be obtained. Having said that some demand planning practices tend to mitigate or reinforce disruptions driven by operational risk, whereas the other practices simultaneously absorb and amplify disruptions driven by operational risk. Practical implications The study shows that different managerial instruments, which are not inherently dedicated to risk management, when appropriately applied, may have an indirect impact on the mitigation of supply chain risk. In particular, the concept of demand planning might be very helpful for managers when dealing with demand and control risks. Originality/value The study simultaneously examines a more detailed bundle of practices forming the demand planning process. The research attempts to investigate the link between the demand planning process and operational risk consequences, derived from all sources (supply, demand, process and control). The paper shows that risk management is not a sole tool to mitigate disruptions. Among the concepts, which contribute to decrease risks is the demand planning process. The study demonstrates that the demand planning process when applied as a component of supply chain management, may contribute to mitigate certain operational risks.

Investigating the role of demand planning as a higher-order construct in mitigating disruptions in the European supply chains

2020 ◽  
Vol 31 (3) ◽  
pp. 665-696 ◽  
Author(s):  
Artur Swierczek
Keyword(s):  
Supply Chains ◽  
Planning Process ◽  
Contextual Factors ◽  
Higher Order ◽  
Dynamic Capability ◽  
Content Type ◽  
Demand Planning ◽  
Operational Risks ◽  
Order Construct ◽  
The Impact

PurposeThe goal of the paper is twofold. First, it aims to empirically conceptualize whether a wide array of fragmented demand planning activities, performed in supply chains, can be logically categorized into actionable sets of practices, which then form a broader conceptualization of the demand planning process. Second, regarding certain contextual factors, our research seeks to investigate the contribution of demand planning, as a higher-order construct, to mitigating disruptions induced by operational risks in supply chains.Design/methodology/approachIn this study, PLS-SEM was used to estimate the reflective-formative nature of the model. The results of PLS-SEM were additionally complemented by the assessment of the predictive power of our model. Finally, to reveal possible contingency effects, the multigroup analysis (MGA) was conducted.FindingsThe study suggests that demand planning process (DPP) is a second-order construct that is composed of four sets of practices, including goal setting, data gathering, demand forecasting, communicating the demand predictions and synchronizing supply with demand. The study also reveals that the demand planning practices, only when considered together, as a higher-order factor, significantly contribute to mitigating disruptions driven by operational risks. Finally, the research shows that the strength of the impact of demand planning on disruptions is contextually dependent.Research limitations/implicationsWhile the study makes some important contributions, the obtained findings ought to be considered within the context of limitations. First, the study only investigates disruptions driven by operational risks, ignoring the negative consequences of environmental risks (terrorist attacks, natural disasters, etc.), which may have a far more negative impact on supply chains. Second, the sample is mostly composed of medium and large companies, not necessarily representative of demand planning performed by the entire spectrum of companies operating in the market.Practical implicationsThe study shows that to effectively mitigate disruptions induced by operational risks, the demand planning practices should be integrated into a higher-order construct. Likewise, our research demonstrates that the intensity of demand planning process is contingent upon a number of contextual factors, including firm size, demand variability and demand volume.Social implicationsThe study indicates that to mitigate disruptions of operational risk, demand planning as a higher-order dynamic capability can be referred to the concept of organizational learning, which contributes to forming a critical common ground, ensuring the balance between formal and informal dynamic routines.Originality/valueThe paper depicts that to fully deal with disruptions, the demand planning practices need to be integrated and categorized into the dedicated higher-order. This may lead to forming demand planning as a higher-order dynamic capability that provides a more rapid and efficient rebuttal to any disruptions triggered by operational risks.

Supply chain risk management dimensions in Indian automobile industry

2014 ◽  
Vol 21 (6) ◽  
pp. 1023-1040 ◽  
Author(s):  
Satyendra Kumar Sharma ◽  
Anil Bhat
Keyword(s):  
Risk Management ◽  
Supply Chain ◽  
Automobile Industry ◽  
Control Strategies ◽  
Supplier Development ◽  
Supply Chain Risk Management ◽  
Supply Chain Risk ◽  
Negative Effects ◽  
Content Type ◽  
And Control

Purpose – Globalization and outsourcing have rendered Indian automotive companies more vulnerable to supply chain (SC) risks. Consequently, companies adopt different supply chain risk management (SCRM) strategies to mitigate SC risks. The purpose of this paper is to explore SCRM strategies in Indian automobile industry and to classify automobile firms based on SCRM dimensions. Design/methodology/approach – A survey instrument on SCRM dimensions was designed and data were collected from 79 automobile firms. Principle component analysis (PCA) was performed on the collected data to derive the factors underlying SCRM dimensions. Further, cluster analysis using extracted factors as a clustering variate was performed to identify strategic groups from the given set of firms. Findings – PCA derived seven factors, namely: avoidance, supplier development, flexibility, risk pooling, redundancy, integration and control strategies. The surveyed firms were classified into two clusters as low and high SCRM level. Research limitations/implications – A limitation of this study is that data were collected from a single industry and in a single country. Practical implications – Understanding of SCRM dimensions shall increase the use of these dimensions and firms can mitigate negative effects of SC risks. The detailed operationalization of SCRM strategies highlights the importance of three strategies: avoidance, integration and supplier development. Managers’ understanding of SCRM strategies will improve the firm's performance and business excellence. Originality/value – This research empirically validates SCRM strategies and investigates how these create differences among firms.

The “snowball effect” in the transmission of disruptions in supply chains

2016 ◽  
Vol 27 (3) ◽  
pp. 1002-1038 ◽  
Author(s):  
Artur Swierczek
Keyword(s):  
Risk Factors ◽  
Supply Chain ◽  
Supply Chains ◽  
Chain Structure ◽  
Supply Chain Integration ◽  
Negative Consequences ◽  
Content Type ◽  
External Risk ◽  
Supply Chain Structure ◽  
Snowball Effect

Purpose The purpose of this paper is to explore the link between interorganizational integration with respect to its intensity and span, as well as the propagation and amplification of disruptions alongside a supply chain. Design/methodology/approach The paper opted for an exploratory study using a survey of companies. In order to extract the constructs manifesting the span and intensity of integration between companies in supply chains, the principal component analysis was employed. The obtained factor scores were then used as classification criteria in the cluster analysis. It enabled to include similar organizations in terms of intensity and span of supply chain integration. In order to validate the obtained results, the analysis of variance (ANOVA) was conducted and regression models were developed. Findings The findings of the study show that there is a relationship between the intensity and span of supply chain integration and the “snowball effect” in the transmission of disruptions. The obtained findings show that the span of supply chain integration is negatively associated with the strength of the “snowball effect” in the transmission of disruptions. In addition, the results suggest that more intense supply chain integration contributes to the “snowball effect” in material flows in the forward and backward transmission of disruptions. Research limitations/implications Although the current study investigates the intensity and span of integration within the basic, extended and ultimate supply chain structure, it still lacks the broader analysis of the “snowball effect” in the transmission of disruptions. The study investigates this phenomenon only within the basic supply chain structure, constituted by the primary members. Another challenge is to examine if the effects of external risk factors (e.g. natural disasters) may also be transferred to other links in the supply chain structure, and what are the similarities and differences (if any) between the mechanism of propagation and amplification of disruptions elicited by internal and external risk factors. Another future direction of study is to define other ways of identification and measurement of the “snowball effect” in order to make cross-industrial and international comparisons of disruptions amplified in the transmission more standardized and objective. In the current study, the phenomenon of the “snowball effect” is anchored in the subjective opinions of managers who may view the problem from different angles. Consequently, the study is limited to individual perceptions of the strength of disruptions affecting the solicited company, its customers and suppliers. Practical implications In practical terms, the findings provide crucial information for the framework of supply chain risk management and therefore enable its more efficient and effective implementation. The better the managers understand the nature of the “snowball effect” in the transmission of disruptions, the easier it is for them to allocate resources and apply necessary managerial tools to mitigate the negative consequences of risk more effectively. The deliverables of the study also confirm that the interorganizational exchange of information accompanying the supply chain integration enables to mitigate the strength of the “snowball effect” in the transmission of disruptions. Another important implication is the broadening of practical expertise concerning the use of integration not only as a means of obtaining and sustaining supply chain effectiveness and efficiency, but also as the way to mitigate the “snowball effect” in the transmission of disruptions. Therefore, nowadays the supply chain managers are facing another challenging task – namely, how to balance supply chain integration in terms of span and intensity to ensure profits from integration and mitigate the negative risk consequences transmitted among the links in supply chains. Originality/value The paper elaborates on the underestimated issue of the “snowball effect” in the transmission of disruptions and its drivers. In particular, the paper attempts at filling the gap in empirical studies concerning the relationships between the “snowball effect” in the transmission of disruptions and supply chain integration.

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.

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.

On uncertainty in supply chain risk management

2014 ◽  
Vol 25 (1) ◽  
pp. 3-19 ◽  
Author(s):  
Jyri Vilko ◽  
Paavo Ritala ◽  
Jan Edelmann
Keyword(s):  
Risk Management ◽  
Supply Chain ◽  
Supply Chains ◽  
Conceptual Framework ◽  
Logistics Management ◽  
Supply Chain Risk Management ◽  
Supply Chain Risk ◽  
Content Type ◽  
Holistic Understanding ◽  
Efficiency And Effectiveness

Purpose – The concept of uncertainty is a relevant yet little understood area within supply chain risk management. Risk is often associated with uncertainty, but in reality uncertainty is a much more elaborate concept and deserves more in-depth scrutiny. To bridge this gap, the purpose of this paper is to propose a conceptual framework for assessing the levels and nature of uncertainty in this context. Design/methodology/approach – The aim of the study is to link established theories of uncertainty to the management of risk in supply chains, to gain a holistic understanding of its levels and nature. The proposed conceptual model concerns the role of certainty and uncertainty in this context. Illustrative examples show the applicability of the model. Findings – The study describes in detail a way of analysing the levels and nature of uncertainty in supply chains. Such analysis could provide crucial information enabling more efficient and effective implementation of supply chain risk management. Practical implications – The study enhances understanding of the nature of the uncertainties faced in supply chains. Thus it should be possible to improve existing measures and analyses of risk, which could increase the efficiency and effectiveness of supply chain and logistics management. Originality/value – The proposed conceptual framework of uncertainty types in the supply chain context is novel, and therefore could enhance understanding of uncertainty and risk in supply and logistics management and make it easier to categorise, as well as initiate further research in the field.

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