sustainability-09-02217-v3.pdf - sustainability Article...

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sustainability Article Analyzing Supply Chain Uncertainty to Deliver Sustainable Operational Performance: Symmetrical and Asymmetrical Modeling Approaches Mohammad Asif Salam 1, * ID , Murad Ali 1 and Konan Anderson Seny Kan 2 1 Faculty of Economics and Business Administration, King Abdulaziz University, P.O. Box 80201, Jeddah 21589, Saudi Arabia; [email protected] 2 Toulouse Business School, University of Toulouse, 20, bd Lascrosses, BP 7010, 31068, Toulouse CEDEX 7, France; [email protected] * Correspondence: [email protected]; Tel.: +96-65-4094-9461 Received: 31 October 2017; Accepted: 22 November 2017; Published: 30 November 2017 Abstract: The purpose of this study is to analyze different types of supply chain uncertainties and suggest strategies to deal with unexpected contingencies to deliver superior operational performance (OP) using symmetrical and asymmetrical modeling approaches. The data were collected through a survey given to 146 supply chain managers within the fast moving consumer goods industry in Thailand. Symmetrical modeling is applied via partial least squares structural equation modeling (PLS-SEM) in order to assess the theoretical relationships among the latent variables, while asymmetrical modeling is applied via fuzzy set qualitative comparative analysis (fsQCA) to emphasize their combinatory causal relation. The empirical results support the theory by highlighting the mediating effect of supply chain strategy (SCS) in the relation between supply chain uncertainty (SCU) and firms’ OP and, hence, deliver business sustainability for the firms, demonstrating that the choice of SCS should not be an “either-or” decision. This research contributes by providing an illustration of a PLS-SEM and fsQCA based estimation for the rapidly emerging field of sustainable supply chain management. This study provides empirical support for resource dependence theory (RDT) in explaining the relation between SCU and SCS, which leads to sustainable OP. From a methodological standpoint, this study also illustrates predictive validation testing of models using holdout samples and testing for causal asymmetry. Keywords: supply chain uncertainty; supply chain strategy; operational performance; resource dependence theory; business sustainability; PLS-SEM; and fsQCA 1. Introduction In recent years, the nature of competition has increasingly shifted toward one supply chain competing against another supply chain [ 1 ]. Bromiley and Rau and Breton-Miller and Miller have raised the question that why, under uncertainty, some firms outperform others [ 2 , 3 ]. Typically, supply chains serve the strategic goals through inter-reliant value-adding processes. Hult et al. have argued that the “strategic supply chain management” role is not merely moving products where they need to be, but is also a tool to enhance key outcomes [ 4 , 5 ]. By nature, supply chain entities are interdependent through sequential, parallel, and network structures, and collaboratively transform raw materials into finished products which can be highly vulnerable to uncertain risks and disruptions [
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