GOLD: Global organization alignment and decision - Towards the hierarchical integration of heterogeneous business models
The so-called fourth industrial revolution (Industry 4.0) is changing the landscape in the manufacturing industry. Although recognized as an essential factor to preserve competitiveness, organizations are still figuring out drivers, enablers and barriers as well as suitable business models to pave the way for innovations in fields such as highly customized products or exponential technologies. The central challenge for a successful adoption of Industry 4.0 is not primarily the required technology, but the emergence and aggregation of a common view and sound models focusing on paramount aspects like quality, customer perception and margins. We argue that available solutions for modeling business strategies fail at providing sufficient guidance for organizations in analyzing opportunities and driving innovations due to their narrow nature as well as missing combination and aggregation possibilities. In contrast, we outline a multi-perspective framework to support organizations in analyzing their context at multiple levels and discuss technological requirements as well as challenges for the development of modeling tools that support hierarchical integration of analyses and models as well as different perspectives to converge on an organization-wide aligned business strategy.
|Keywords||B-2-B market, Global organization alignment & decision framework, Global organization alignment & decision tool, Hierarchical integration of heterogeneous business models, Industry 4.0 context, Multi-level business modeling|
|Persistent URL||dx.doi.org/10.1007/978-3-030-03427-6_37, hdl.handle.net/1765/112182|
|Series||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
Steffen, B, & Boßelmann, S. (Steve). (2018). GOLD: Global organization alignment and decision - Towards the hierarchical integration of heterogeneous business models. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). doi:10.1007/978-3-030-03427-6_37