Horizontal Integration Through Knowledge Sharing in the Supply Chain Under Uncertainty

Abstract

A robust knowledge-sharing network is designed for horizontal integration under disruption risks and epistemic uncertainties by introducing a novel optimization model using a fuzzy robust possibilistic programming approach to optimize knowledge sharing among supply chain members with varying knowledge levels. In this article, we aim to identify an efficient knowledge-sharing network, thereby reducing costs and enhancing suppliers' knowledge levels. By challenging the common assumption that companies with higher knowledge levels are always the primary contributors and have more added value for cooperation, this study highlights their potential inefficiencies and higher sharing costs. The proposed model promotes the integration of diverse knowledge sources within the supply chain, emphasizing the importance of horizontal integration. It advocates for comprehensive knowledge sharing among suppliers and organizations to enhance supply chain efficiency, collaboration, and performance while reducing costs. Quantitative analysis demonstrates that knowledge sharing significantly increases supply chain integration, and the study endorses the use of multiobjective mathematical programming for optimal decision making in scheduling. The results emphasize the value of collaborating with closely aligned companies to minimize knowledge-sharing costs and enhance broader organizational collaboration. Furthermore, the introduced model proposes practical execution scheduling and knowledge-sharing processes, as evidenced by a case study, leading to effective execution scheduling, reduced costs, improved communication, strengthened collaboration, and increased supply chain efficiency. Overall, this article contributes to research in supply chain management and knowledge-sharing models, enabling them to navigate constraints and market dynamics to improve supply chain performance through effective knowledge sharing and collaboration.

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