IEEE Transactions on Engineering Management · 2021 · 67 citations · 63 references
ManagementOperations ManagementSupply Chain ManagementDigital TransformationSupply Chain Performance ManagementSupply Chain StrategyOrganizational ResilienceSupply Chain DigitalizationSupply Chain DigitizationSupply Chain Performance MeasurementSupply Chain ResilienceSupply ChainsCritical Success FactorsDigital Supply Chain ManagementInterpretive Structural ModelingOrganizational Performance AssessmentProcess ResilienceResilienceResilient Supply ChainsSupply Chain Resilience Capabilities
Technological advancement is redefining supply‑chain processes, making traditional management approaches ineffective and prompting a shift toward digital supply chains to sustain competitive performance. The study aims to identify the critical factors that enable organizations to transition from traditional supply chains to digital supply chains and thereby improve performance. Interpretive structural modeling was employed to map relationships among the critical factors and determine their driving and dependency powers. Fifteen critical factors were identified, with SC resilience and proactive prevention showing the strongest dependency power and integration and advanced operational models the strongest driving power, offering managers a framework for adopting digital supply chains.
Technological advancement is redefining supply chains (SCs) processes and soon traditional ways of managing SCs will no more be feasible and effective. Due to recent advancement in technology, digitalization has become an emerging topic among decision-makers and researchers. To cope-up with this emerging trend in customer behavior and remain competitive, organizations must move from their traditional ways of managing their SCs to digital supply chains (DSCs) for improved organizational performance. Therefore, the purpose of this article is in two folds: First, to identify critical factors of DSCs that are essential for transitioning traditional SCs to DSCs to improve organizational performance. Second, interpretive structural modeling is used to establish the relationship among critical factors and (matriced’ impacts croise´s multiplication applique´e a´un classement used to identify the driving and dependency power of the critical factors. Thus, this article identified fifteen DSC critical factors and established their direct and indirect effect on DSCs. The results show that “SC resilience”, and “proactive prevention” have the highest dependency power factors whilst “integration” and “advanced operational models” have the highest driving power factors. This article can help SC managers and decision-makers to understand the critical factors essential in adopting DSCs for improving organizational performance.
63
Digital Supply Chain Transformation toward Blockchain Integration
Kari Korpela, Jukka Hallikas, Tomi Dahlberg · Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences · 2017 · 850 citations · Full text
Management, Information Systems, Supply Chain Management +17