This paper develops a procedure for assessing both supply chain processes and strategic criteria in the context of platform-based supply chains, addressing the problem that organizations often invest in digital platforms without a clear understanding of how process effectiveness, process dysfunction, and strategic platform priorities jointly influence implementation success. The main research objective is to evaluate how effective and dysfunctional supply chain processes, together with prioritized strategic platform criteria, shape performance, productivity, and resilience outcomes in platform-based supply chain integration. The paper further discusses how identified dysfunctional processes and prioritized strategic criteria relate to operational vulnerabilities and resilience-building measures. The research adopts a multi-criteria decision-making (MCDM) approach to address the challenges of digital transformation and platform integration. An exploratory study was conducted applying the analytic hierarchy process (AHP) to evaluate functional and dysfunctional processes, complemented by the best worst method (BWM) to prioritize critical strategic criteria. The combined assessment highlights effective and dysfunctional processes while also identifying the most influential factors driving platform-based adoption and their potential implications for operational vulnerability and resilience. The results demonstrate how platform integration contributes to performance improvement, process alignment, and productivity gains across supply chain operations. The study contributes to both theory and practice by integrating MCDM techniques to support structured decision-making, enhancing responsiveness, resilience, and alignment with platform-oriented strategies. The primary contribution lies in providing a dual-level framework that enables supply chain managers to diagnose weaknesses, leverage strengths, and strategically guide the transition toward platform-based supply chain operations, with a measurable impact on organizational performance and productivity development.
TRAMARICO et al. (Sun,) studied this question.