M11 - Production ManagementReturn

This study explores how supply chain management (SCM) information system (IS) capabilities can lead to superior business performance, and what are the detailed capabilities and methods to master volatility and uncertainties in business environments. Key concepts in SC modelling have been identified for decreasing SC complexity and increasing SC agility and key methods for supply network planning and synchronisation for optimising business performance and objectives that are often contradicting at the same time. The study developed a best practice recommendation for profit-optimised SCM for companies with capital intensive and capacity constrained resources such as in the steel companies and others of the industry, and for managing their integration between SC domains and between technological and organisations' needs simultaneously. Finally, the study shows how Industry 4.0 innovations such as Smart Services and blockchain technology can provide new value potentials such as cross-organisational network effects and increased autonomy in SC ecosystems, and concludes with suggestions for further research in needed rules and semantics for SC ecosystem collaboration.

A model for managing strategic alignment and dynamic capabilities (DC) of Supply Chain Management (SCM) information systems (IS) has been developed and applied to a traditional German steel company and a highly innovative Austrian steel company. Different concepts of leading researchers have been combined to get a holistic and detailed view of IS capabilities' impact on strategic fit. The model enables companies to identify ideal levels to strategic fit needed from SC integration and its antecedents for predefining architectural artefacts as sources for dynamic capabilities. The study contributes to new insights into the IT productivity paradox, where possibilities from IS investments remain unused. Essential concepts for optimising SC performance by reducing SC complexity and increasing SC agility have been identified and integrated. The study highlights value enabler and Artificial Intelligence (AI) methods of digital SC models and how the model's ontology can be used to increase alignment autonomy. Finally, the approach supports organisational learning and development of cognitive profiles through collective assimilation and sensemaking effects.