scholarly journals A conceptual framework for improving effectiveness of risk management in supply networks

2020 ◽  
Vol 31 (1) ◽  
pp. 77-98 ◽  
Author(s):  
Atanu Chaudhuri ◽  
Abhijeet Ghadge ◽  
Barbara Gaudenzi ◽  
Samir Dani
Keyword(s):  
Risk Management ◽  
Supply Chain ◽  
Conceptual Framework ◽  
Negative Impact ◽  
Supply Network ◽  
Supply Networks ◽  
Content Type ◽  
Network Characteristics ◽  
Management Capabilities ◽  
Risk Planning

PurposeThe purpose of the paper is to develop a conceptual framework for improving the effectiveness of risk management in supply networks following a critical literature review.Design/methodology/approachA critical review of 91 scholarly journal articles published between 2000 and 2018 supports the development of an integrated conceptual framework.FindingsThe findings emphasize that supply chain integration (SCI) can have both a positive and negative impact on the effectiveness of risk management in supply networks. It is possible to have a positive effect when SCI can be used to develop competencies in joint risk planning within the organization and with wider supply network members and, in turn, to develop collaborative risk management capabilities. Supply network characteristics can influence whether and the extent to which SCI has a positive or negative impact on risk management effectiveness.Research implicationsThe conceptual framework can be used to empirically assess the role of SCI for effective risk management. Dynamic evaluation of the effectiveness of risk management and potential redesign of the supply network by considering other contingent factors are some future research avenues.Practical implicationsThere is a need for developing specific competencies in risk planning within organizations and joint risk planning with supply network members which, in turn, can help develop collaborative risk management capabilities to improve the effectiveness of risk management in supply networks. Network characteristics will influence whether and the extent to which SCI results in the effectiveness of risk management.Originality valueMoving beyond recent (systematic) reviews on supply chain risk management, this study develops a novel conceptual framework interlinking SCI and the effectiveness of risk management while considering network characteristics.

scholarly journals A supply network governance framework: a case study of the South Australian mining industry

2018 ◽  
Vol 11 (1) ◽  
pp. 55-78 ◽  
Author(s):  
Larissa Statsenko ◽  
Alex Gorod ◽  
Vernon Ireland
Keyword(s):  
Supply Chain ◽  
Conceptual Framework ◽  
Network Structure ◽  
Mining Industry ◽  
Network Governance ◽  
Supply Network ◽  
Supply Networks ◽  
Policy Makers ◽  
Content Type

Purpose The competitiveness of mining regions largely depends on the performance of the regional supply chains that provide services to mining companies. These local supply chains are often highly intertwined and represent a regional supply network for the industry. Individual companies often use supply chain strategies that are sub-optimal to overall supply network performance. To effectively respond to an uncertain business environment, policy-makers and supply chain participants would benefit by a governance framework that would allow to incentivise the formation of supply networks structures enabling effective operations. The purpose of this paper is to offer an empirically grounded conceptual framework based on Complex Adaptive Systems (CASs) governance principles, which links network governance mechanisms with supply network structure and operational performance to incentivise the formation of adaptive and resilient supply networks in the mining industry. Design/methodology/approach A mixed method research design and a case study of the South Australian mining sector were used to collect empirical data. Qualitative interviews and network analysis of the SA mining industry regional supply network structure were conducted. The relationships between network parameters were interpreted using CAS theory. Findings An empirically grounded conceptual framework based on CAS governance principles is developed. The case study revealed that supply chain strategies and governance mechanisms in the SA mining industry have led to the formation of a hierarchical, scale-free structure with insufficient horizontal connectivity which limits the adaptability, responsiveness and resilience of the regional supply network. Research limitations/implications The findings are drawn from a single case study. This limits generalisability of the findings and the proposed framework. Practical implications The proposed framework draws the attention of the policy-makers and supply chain participants towards the need for utilising CAS governance principles to facilitate the formation of adaptive, responsive and resilient regional supply networks in the mining industry. Originality value The proposed conceptual framework is an attempt to parameterise the governance of the regional supply networks in the mining industry.

Understanding the influence of lean and agile strategies on creating firms’ supply chain risk management capabilities

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Waqar Ahmed ◽  
Muhammad Zaki Rashdi
Keyword(s):  
Risk Management ◽  
Supply Chain ◽  
Empirical Evidence ◽  
Internal Control ◽  
Market Condition ◽  
Equation Modeling ◽  
Supply Chain Risk ◽  
Content Type ◽  
Management Capabilities ◽  
The Impact

Purpose Lean and agile strategies are two basic supply chain paradigms that strategist decouples based on their internal and external environment. This study aims to identify the influence of market orientation (MO) and quality management (QM) deployment on the supply chain strategies. Furthermore, this study also seeks empirical evidence of the impact of these core strategies on creating risk management capabilities. Design/methodology/approach Quantitative research technique is deployed to explain the phenomenon. The data was gathered through a structured scale questionnaire from supply chain professionals working at different manufacturing firms. Valid data of 134 respondents is then analyzed through partial least squares structural equation modeling for further empirical understanding. Findings The outcome of the research indicates that MO capability; as an external drive is a key to make an operational strategy. QM as an internal control is more prone to formulating a lean strategy (LS). Another important finding is that LS does not complement risk management capabilities especially in an uncertain market condition. Practical implications The study suggested concrete implications for risk management through the right mix of lean and agile supply chain strategies. There are some good insights for the supply chain policy-makers working in a developing country. Originality/value This study will provide empirical evidence for managing supply chain risk through an effective strategy making.

scholarly journals Catastrophic supply chain disruptions and supply network changes: a study of the 2011 Japanese earthquake

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Byung-Gak Son ◽  
Sangho Chae ◽  
Canan Kocabasoglu-Hillmer
Keyword(s):  
Supply Chain ◽  
Structural Changes ◽  
Network Density ◽  
Degree Centrality ◽  
Network Structures ◽  
Supply Network ◽  
The 2011 Tohoku Earthquake ◽  
Supply Chain Disruptions ◽  
Supply Networks ◽  
Content Type

PurposeCatastrophic supply chain disruptions can significantly damage the operational and financial performance of firms. While a growing body of literature on supply network structures has studied what influences supply networks' vulnerability to supply chain disruptions and capability to recover from them, it remains unclear how supply network structures change after major supply chain disruptions. We aim to provide an understanding of how these changes occur.Design/methodology/approachUsing a natural experiment approach and supply network data from Factset, this study investigates how firms' supply network structures change after experiencing the catastrophic supply chain disruptions caused by the 2011 Tohoku earthquake and tsunami in Japan. We capture post-earthquake supply network changes using the measures of degree centrality and ego network density.FindingsThe results of the analysis suggest that compared to unaffected firms, the affected firms experience changes in their supply network structures tending toward lower complexity measured by in-degree centrality, out-degree centrality and ego network density.Originality/valueThis study contributes to social network theory and the complex adaptive supply network literature by providing empirical evidence of structural changes in supply networks after catastrophic supply chain disruptions. A managerial contribution is made by providing a reflection on why these changes might be occurring and alert firms to the challenges of managing complexity in their supply networks.

Toward a supply chain risk identification and filtering framework using systems theory

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jianrong Hou ◽  
Xiaofeng Zhao
Keyword(s):  
Risk Management ◽  
Supply Chain ◽  
Conceptual Framework ◽  
Risk Identification ◽  
Supply Chain Risk Management ◽  
Supply Chain Risk ◽  
Supply Chain System ◽  
Content Type ◽  
The Hierarchical Structure ◽  
Supply Chain Risks

PurposeThe purpose of the paper is to develop a methodological framework for supply chain risk management using the hierarchical holographic modeling approach. It analyses supply chain risks in a systematic manner and develops a hierarchical methodology for identifying, prioritizing and managing the potential supply chain risks.Design/methodology/approachThis research reviews supply chain risk management literature and develops a conceptual framework, which outlines general principles and guidelines for managing risks in a systematic manner. Through decomposition, the complexity of supply chain risk can be identified by analyzing smaller subsystems.FindingsThe paper provides a conceptual framework to identify supply chain risks from multiple overlapping perspectives. The structured filtering and ranking procedure enables decision-makers to focus on the most critical risks. The research shows that the supply chain risks associated with the sub-systems within the hierarchical structure contribute to and ultimately determine the risks of the overall supply chain system.Research limitations/implicationsThe risks associated with each sub system within the hierarchical structure can contribute to and determine the risks of the overall supply chain system. Further applications in various companies and industry sectors would benefit supply chain managers on a case-by-case basis.Practical implicationsThe hierarchical risk identification framework can serve as guidance for applications to specific supply chain systems and processes. The framework from a holistic overlapping perspective can efficiently and effectively help supply chain managers identify supply chain risks and facilitate the evaluation of the subsystem risks.Originality/valueThe paper applies system thinking in supply chain management and presents an efficient and practical framework for supply chain risk identification and evaluation.

How “smart cities” will change supply chain management

2015 ◽  
Vol 20 (3) ◽  
pp. 237-248 ◽  
Author(s):  
Elcio M. Tachizawa ◽  
María J. Alvarez-Gil ◽  
María J. Montes-Sancho
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Network Structure ◽  
Smart Cities ◽  
Supply Network ◽  
Supply Networks ◽  
Chain Management ◽  
Content Type ◽  
Integrative Framework

Purpose – The purpose of this paper is to analyze the impact of smart city initiatives and big data on supply chain management (SCM). More specifically, the connections between smart cities, big data and supply network characteristics (supply network structure and governance mechanisms) are investigated. Design/methodology/approach – An integrative framework is proposed, grounded on a literature review on smart cities, big data and supply networks. Then, the relationships between these constructs are analyzed, using the proposed integrative framework. Findings – Smart cities have different implications to network structure (complexity, density and centralization) and governance mechanisms (formal vs informal). Moreover, this work highlights and discusses the future research directions relating to smart cities and SCM. Research limitations/implications – The relationships between smart cities, big data and supply networks cannot be described simply by using a linear, cause-and-effect framework. Accordingly, an integrative framework that can be used in future empirical studies to analyze smart cities and big data implications on SCM has been proposed. Practical implications – Smart cities and big data alone have limited capacity of improving SCM processes, but combined they can support improvement initiatives. Nevertheless, smart cities and big data can also suppose some novel obstacles to effective SCM. Originality/value – Several studies have analyzed information technology innovation adoption in supply chains, but, to the best of our knowledge, no study has focused on smart cities.

Developing supply chain risk management capabilities by aligning strategies: integrating Triple-A model

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Waqar Ahmed ◽  
Muhammad Zaki Rashidi
Keyword(s):  
Risk Management ◽  
Supply Chain ◽  
Structural Equation ◽  
Statistical Technique ◽  
Equation Modeling ◽  
Original Research ◽  
Supply Chain Risk Management ◽  
Content Type ◽  
The Right ◽  
Management Capabilities

Purpose Risk is primarily managed by developing the right strategies. Effective alignment of lean and agile strategies is always challenging for practitioners to create firm’s competitiveness. The purpose of this study is to comprehend the behavior of these fundamental supply chain (SC) strategies by using the Triple-A framework. Design/methodology/approach Sample data is collected from 257 SC professionals serving in manufacturing firms through a self-administered structured questionnaire. The statistical technique used to perform hypotheses testing is structural equation modeling. Findings This study discloses a few critical attributes of lean and agile strategies while attempting to create strategic alignment and gain maximum benefits out of it. One of the key findings is that a lean strategy finds it challenging to create adaptability. However, better alignment among the market priorities and operational capabilities may improve risk management capabilities. Practical implications This study posits various vital insights for strategy-makers. For instance, it is advised to the operations managers that lean resources are usually never capable of adopting change but can be aligned with the market changes to create a SC risk management capability for the firm. Originality/value This is an original research with various useful insights for SC operations strategy-makers and academic researchers as it reveals a key empirical evidence of past vital concepts.

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.

scholarly journals Investigating the relationship between supply chain innovation, risk management capabilities and competitive advantage in global supply chains

2018 ◽  
Vol 38 (1) ◽  
pp. 2-21 ◽  
Author(s):  
Dong-Wook Kwak ◽  
Young-Joon Seo ◽  
Robert Mason
Keyword(s):  
Risk Management ◽  
Supply Chain ◽  
Theoretical Model ◽  
Competitive Advantage ◽  
Structural Equation ◽  
Large Scale ◽  
Positive Influence ◽  
Content Type ◽  
Management Capability ◽  
Management Capabilities

Purpose The purpose of this paper is to propose and validate a theoretical model to investigate whether supply chain (SC) innovation positively affects risk management capabilities, such as robustness and resilience in global SC operations, and to examine how these capabilities may improve competitive advantage. Design/methodology/approach A theoretical model was developed from extant studies and assessed through the development of a large-scale questionnaire survey conducted with South Korean manufacturers and logistics intermediaries involved in global SC operations. The data were analysed using confirmatory factor analysis and structural equation modelling to validate the suggested model. Findings It was found that innovative SCs have a discernible positive influence on all dimensions of risk management capability, which in turn has a significant impact on enhancing competitive advantage. Therefore, this work provides evidence for the importance of SC innovation and risk management capability in supporting competitive advantage. Research limitations/implications This study contributes to providing an empirical understanding of the strategic retention of SC innovation and risk management capabilities in the SC management discipline. Furthermore, it confirms and expands existing theories about innovation and competitive advantage. Practical implications The finding provides firm grounds for managerial decisions on investment in technology innovation and process innovation. Originality/value This research is the first of its kind to empirically validate the relationships between SC innovation, risk management capabilities and competitive advantage.

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.

Product deletion and supply chain repercussions: risk management using FMEA

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Qingyun Zhu ◽  
Seyedehfatemeh Golrizgashti ◽  
Joseph Sarkis
Keyword(s):  
Decision Making ◽  
Risk Management ◽  
Supply Chain ◽  
Supply Chains ◽  
Portfolio Management ◽  
Failure Modes ◽  
Negative Impact ◽  
Product Portfolio ◽  
Content Type ◽  
Managerial Implications

PurposeProduct portfolio management is a strategic concern. Product portfolio management includes decisions associated with adding new products, maintaining existing products and deleting or phasing out problematic products. This paper first introduces a framework to identify risks of product deletion along supply chain activities. It utilizes failure mode and effects analysis (FMEA) to identify, analyse and evaluate product deletion risks on supply chains and proposes managerial implications for risk management in dynamic business scenarios. It is meant to build upon and address a gap in the product deletion and supply chain linkage literature.Design/methodology/approachFMEA is utilized in this study to structure and manage potential risks in product deletion decision-making on supply chains. FMEA is based on an analysis of severity, occurrence and detectability of failure modes. FMEA provides methods to help identify managerial preventive solutions to avoid and mitigate risk consequences of such decisions.FindingsTen top product deletion risks are identified in this study; discussions of their negative impact on supply chain performance, and possible managerial recommendations are followed for risk control, monitor and elimination.Practical implicationsFindings help managers to predict, avoid and mitigate risk consequences of product deletion decisions; especially those related to the supply chain. A framework to structure various risks of product deletion in the supply chain can be useful to both practitioners and researchers.Originality/valueThis study advances product portfolio management through enhanced understanding of product deletion decision-making in organizations; and especially contributes to a broader investigation of such decisions in supply chain management. It also structures the factors that play a role in identifying risks.

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