Supply chain disruption risk management through strategic information acquisition and sharing and risk-sharing contracts

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How researchers see this paper

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Quantifying risks in a supply chain through integration of fuzzy AHP and fuzzy TOPSIS (2013, methodology): “Moreover, the research information available on this topic is mainly qualitative in nature (Thun et al. 2011, Simangunsong et al. 2012) and only recently has a quantitative approach been adopted (Hillman and Keltz 2007, Wakolbinger and Cruz 2011, Diabat et al. 2012).”
Supply chain disruption propagation: a systemic risk and normal accident theory perspective (2018, result): “This is consistent with the literature (Lau, Huang, and Mak 2002; Kleindorfer and Saad 2005; Wakolbinger and Cruz 2011) and is an example of a risk being both cyclical and counterparty risk.”
Supply Chain Risk Management: Present and Future Scope (2012, unknown): “Most of the previous research has focussed on different SC contracts in the context of price and demand fluctuations (Wakolbinger and Cruz, 2011) but, long term contracts for disruption management are lacking in the literature.”
A critical review on supply chain risk – Definition, measure and modeling ☆ (2015, methodology): “Deviation-based measures, like variance, standard deviation, expected or absolute values of deviation are applied by [4,6,7,55, 62,79,87,102,123,134,153,156,157].”