Agile supply chain capabilities: Determinants of competitive objectives

By Y. Yusuf, Angappa Gunasekaran, Ezekiel O. Adeleye, K. Sivayoganathan. European Journal of Operational Research, 2004

565 citations recorded by the source corpus.

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A mathematical programming approach to supply chain models with fuzzy parameters (2006, unknown): “…2000, Min and Zhou 2002, Smichi-Levi et al. 2003, Gunasekaran 2004, Gunasekaran and Chung 2004, Gunasekaran and Ngai 2004, Gunasekaran et al. 2004, Yusuf et al. 2004), and much effort has been expended in developing decision models for SCM (Cohen and Lee 1988, 1989, Cohen and Moon 1990, 1991,…”
Big data analytics capability in supply chain agility (2019, unknown): “Organizations with better organizational flexibility are more capable of coping with demand and supply uncertainties (Swafford et al. 2006) and gain competitive advantage (Yusuf et al. 2004, 2014).”
From Supply Chain Integration to Operational Performance: The Moderating Effect of Market Uncertainty (2018, methodology): “The factor scores are used to determine a measurement’s relative standing on the latent dimension (Yusuf et al. 2004; Brown 2015).”
Application of machine learning techniques for supply chain demand forecasting (2008, background): “Finally, with the advance of E-business there is an increasing tendency towards more ‘‘dynamic’’ (Vakharia, 2002) and ‘‘agile’’ (Gunasekaran and Ngai, 2004; Yusuf et al., 2004) supply chains.”