A Decision Framework to Mitigate Supply Chain Risks: An Application in the Offshore-Wind Industry

Mogre, Riccardo; Talluri, Srinivas; D’Amico, Federico

doi:10.1109/tem.2016.2567539

Cited by 40 publications

(11 citation statements)

References 29 publications

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“…While this is understandable, it means a holistic approach to studying the full SCRM process is missing (Gap 1). Such an approach is important in understanding the adoption of some Decision Support Systems (DSS) that benefit from a holistic approach to managing SCRs (Mogre et al, 2016). For work that is to focus on a particular SCRM stage, two key directions are identified.…”

Section: Discussion: Gaps In Scrm Researchmentioning

confidence: 99%

A review of supply chain risk management: definition, theory, and research agenda

Fan

Stevenson

2018

IJPDLM

401

351

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Purpose: To review the extant literature on supply chain risk management (SCRM, including risk identification, assessment, treatment, and monitoring), developing a comprehensive definition and conceptual framework; to evaluate prior theory use; and to identify future research directions. Design/methodology/approach: A systematic literature review of 354 articles (published 2000-2016) based on descriptive, thematic, and content analysis.Findings: There has been a considerable focus on identifying risk types and proposing risk mitigation strategies. Research has emphasised organisational responses to supply chain risks and made only limited use of theory. Ten key future research directions are identified. Research implications:A broad, contemporary understanding of SCRM is provided; and a new, comprehensive definition is presented covering the process, pathway, and objectives of SCRM, leading to a conceptual framework. The research agenda guides future work towards maturation of the discipline. Practical implications:Managers are encouraged to adopt a holistic approach to SCRM.Guidance is provided on how to select appropriate risk treatment actions according to the probability and impact of a risk.Originality/value: The first review to consider theory use in SCRM research and to use four SCRM stages to structure the review.

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Section: Discussion: Gaps In Scrm Researchmentioning

confidence: 99%

A review of supply chain risk management: definition, theory, and research agenda

Fan

Stevenson

2018

IJPDLM

401

351

View full text Add to dashboard Cite

show abstract

“…Although a higher value of inconsistency criteria requires a revaluation of pair wise comparisons, decisions obtained in certain cases can also be taken as the best alternative. AHP is widely used for decision-making problems like evaluation of renewable energy project (Malik et al, 2014), energy-aware decision-making (Benedicenti, 2016), project quality evaluation in construction engineering (Shao and Fu, 2015), power system (Bhonsle and Junghare, 2015), and wind energy (Mogre et al, 2016).…”

Section: Methods Appliedmentioning

confidence: 99%

Application of AHP-VIKOR and GMDH framework to develop an indicator to identify utilisation potential of wave energy converter with respect to location

Chakraborty

Majumder

Khare

2019

IJSTDS

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The potential of analytical hierarchy process (AHP)-rough number based compromise ranking method (also known as VIKOR) multi-criteria decision-making (MCDM) and group method of data handling (GMDH) multimodal predictive method was analysed for smart representation of 'utilisation potential' of wave energy converters from specific locations. The significant parameters were identified by considering different case studies and their influence on converter efficiency. The soft-computation methods like AHP-VIKOR and GMDH were used for the first time to find the relative priority values of the parameters. The results from the multi-method estimation model were validated with the help of multi linear regression equation and certain real-time case analysis. With an accuracy of above, 99% the ensemble MCDM-ANN model depicted reliability, which ensures the author of its wide application for real benefits like cost reduction and efficiency maximisation of converters in the utilisation of the potential wave energy of locations.

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“…While the risk assessment topic is largely theoretical in the scope of the matched articles, the research clustered under the risk forecasting topic (Topic 19) is quite applied. Mogre et al (2016) proposes a decision support system-based framework to mitigate risk. Their approach encompasses identification, estimation, assessment, and decision making for risks.…”

Section: Risk Management Topicsmentioning

confidence: 99%

Machine Learning and Finance

Khatib¹

2021

Int J Innov Educ Res

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The aim of this paper is provide a first comprehensive structuring of the literature applying machine learning to finance. We use a probabilistic topic modelling approach to make sense of this diverse body of research spanning across the disciplines of finance, economics, computer sciences, and decision sciences. Through the topic modelling approach, a Latent Dirichlet Allocation Technique (LDA), we can extract the 14 coherent research topics that are the focus of the 6,148 academic articles during the years 1990-2019 analysed. We first describe and structure these topics, and then further show how the topic focus has evolved over the last two decades. Our study thus provides a structured topography for finance researchers seeking to integrate machine learning research approaches in their exploration of finance phenomena. We also showcase the benefits to finance researchers of the method of probabilistic modelling of topics for deep comprehension of a body of literature, especially when that literature has diverse multi-disciplinary actors.

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A Decision Framework to Mitigate Supply Chain Risks: An Application in the Offshore-Wind Industry

Cited by 40 publications

References 29 publications

A review of supply chain risk management: definition, theory, and research agenda

A review of supply chain risk management: definition, theory, and research agenda

Application of AHP-VIKOR and GMDH framework to develop an indicator to identify utilisation potential of wave energy converter with respect to location

Machine Learning and Finance

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