Dynamic Modelling of Inter-Organizational Networks Using the Domain Knowledge and Big Data Analytics
Loading...
Paper Type
Complete
Abstract
Inter-organizational networks are becoming deeply rooted in the organization management’s practice and theory. Still, there is an evident lack of a data-driven, adaptive tool aiding managerial decision-making processes in the network context. The inter-disciplinary team of authors showed that modern approach including big data analytics and data science has a great potential to support this particularly sophisticated task. The article presented a novel approach of combining a domain model with big data analytics and machine learning and graph algorithms to forecast network events. Then, the model was verified against a selection of known and current managerial tasks in the inter-organizational context. The resulting concept of a decision support system presented an implementation of a human-machine environment in which the machine solved tasks of pattern recognition and the human (i.e. domain expert) interpreted the results on different levels of abstraction using the domain knowledge.
Recommended Citation
Śliwa, Piotr; Krzos, Grzegorz; and Pondel, Maciej, "Dynamic Modelling of Inter-Organizational Networks Using the Domain Knowledge and Big Data Analytics" (2020). AMCIS 2020 Proceedings. 8.
https://aisel.aisnet.org/amcis2020/data_science_analytics_for_decision_support/data_science_analytics_for_decision_support/8
Dynamic Modelling of Inter-Organizational Networks Using the Domain Knowledge and Big Data Analytics
Inter-organizational networks are becoming deeply rooted in the organization management’s practice and theory. Still, there is an evident lack of a data-driven, adaptive tool aiding managerial decision-making processes in the network context. The inter-disciplinary team of authors showed that modern approach including big data analytics and data science has a great potential to support this particularly sophisticated task. The article presented a novel approach of combining a domain model with big data analytics and machine learning and graph algorithms to forecast network events. Then, the model was verified against a selection of known and current managerial tasks in the inter-organizational context. The resulting concept of a decision support system presented an implementation of a human-machine environment in which the machine solved tasks of pattern recognition and the human (i.e. domain expert) interpreted the results on different levels of abstraction using the domain knowledge.
When commenting on articles, please be friendly, welcoming, respectful and abide by the AIS eLibrary Discussion Thread Code of Conduct posted here.