Innovative Supply Risk Management

PurposeManaging supply risk is gaining in importance in the tightly interconnected global economy. Identifying the relevant risks is the foundation of any risk management process. Therefore, the purpose of this paper first is to provide a short introduction to supply risk management, before focussing on the identification of such risks in more detail. A holistic framework of the identified supply risks, which distinguishes between risk dimensions and risk factors in manufacturing upstream supply networks, is proposed.Design/methodology/approachThis study applies a mixed methods research approach. Data are collected based on a structured literature review in combination with the analysis of company-specific documents and semi-structured expert interviews. Subsequently, a deductive content analysis is carried out to derive a holistic framework of supply risks, adapted to the manufacturing industry. For the external validation of the conceptual supply risk framework, additional experts from several manufacturing companies were consulted.FindingsBased on the definition and delimitation of supply risk, a categorization of supply risks is developed. The relevant literature, as well as expert interviews, lead to the distinction of six supply risk dimensions: quality, delivery, collaboration, economic, ambience and compliance. A total of 27 risk factors can be assigned to these dimensions. A holistic foundation for the management of supply risk is thus created.Originality/valueThis study provides a holistic framework of relevant supply risks in the context of the manufacturing industry. This overview of identified risks offers a novel perspective on risk in manufacturing supply networks that can be helpful in researching assessment and mitigation strategies. Despite the high relevance and popularity of this field of research, such an overview with a focus on manufacturing had not yet been made available in the literature. Building thereon, management approaches can now be developed to handle the risk arising from the upstream of the supply network.

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Supply risk management under imperfect competition ? Empirical applications to the Swedish pulp and paper industry

Empirical Economics ◽

10.1007/bf01206039 ◽

1991 ◽

Vol 16 (4) ◽

pp. 447-464 ◽

Cited By ~ 3

Author(s):

M. Bergman ◽

K. G. L�fgren

Keyword(s):

Risk Management ◽

Imperfect Competition ◽

Paper Industry ◽

Pulp And Paper Industry ◽

Pulp And Paper ◽

Supply Risk

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Supply risk management vs supplier selection to manage the supply risk in the EPC supply chain

Management Research News ◽

10.1108/01409170810913042 ◽

2008 ◽

Vol 31 (11) ◽

pp. 846-866 ◽

Cited By ~ 34

Author(s):

Guido J.L. Micheli ◽

Enrico Cagno ◽

Marta Zorzini

Keyword(s):

Risk Management ◽

Supply Chain ◽

Supplier Selection ◽

Supply Risk

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Responsible buying practices in supply risk management

International Journal of Integrated Supply Management ◽

10.1504/ijism.2016.10002259 ◽

2016 ◽

Vol 10 (3/4) ◽

pp. 309

Author(s):

Jukka Hallikas ◽

Pietro Evangelista ◽

Katrina Lintukangas ◽

Anni Kaisa Kähkönen

Keyword(s):

Risk Management ◽

Supply Risk

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Collaborative Forecasting, Inventory Hedging and Contract Coordination in Dynamic Supply Risk Management

SSRN Electronic Journal ◽

10.2139/ssrn.2199986 ◽

2013 ◽

Cited By ~ 2

Author(s):

Long Gao

Keyword(s):

Risk Management ◽

Supply Risk

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Responsive contingency planning in supply risk management by considering congestion effects

Omega ◽

10.1016/j.omega.2014.03.002 ◽

2014 ◽

Vol 48 ◽

pp. 19-35 ◽

Cited By ~ 17

Author(s):

Alireza Ebrahim Nejad ◽

Iman Niroomand ◽

Onur Kuzgunkaya

Keyword(s):

Risk Management ◽

Contingency Planning ◽

Supply Risk ◽

Congestion Effects

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Bayesian Belief Network Approach for Supply Risk Modelling

International Journal of Information Systems and Supply Chain Management ◽

10.4018/ijisscm.2022010102 ◽

2022 ◽

Vol 15 (1) ◽

pp. 0-0

Keyword(s):

Risk Management ◽

Supply Chain ◽

Risk Model ◽

Management Strategies ◽

Bayesian Belief Network ◽

Supply Chain Risk Management ◽

Supply Risk ◽

Belief Network ◽

Transportation Risk ◽

Price Risks

Today’s global and complex world increased the vulnerability to risks exponentially and organizations are compelled to develop effective risk management strategies for its mitigation. The prime focus of research is to design a supply risk model using Bayesian Belief Network bear in mind the tie-in of risk factors (i.e. objective and subjective) those are critical to a supply chain network. The proposed model can be re-engineered as per new information available at disclosure, so risk analysis will be current and relevant along the timeline as so situation is strained. The top three factors which influenced profitability were transportation risk and price risks. Netica is the platform used for designing and running simultaneous simulations on the Bayesian Network. The proposed methodology is demonstrated through a case study conducted in an Indian manufacturing supply chain taking inputs from supply chain/risk management experts. .

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