The last two decades of designing large-scale engineering systems have demonstrated that the even higher complexity of problems requires entirely new solution approaches. Transdisciplinary engineering (TE) is a means to overcome the limits of inter- or multi- disciplinary approaches. For such challenges, transdisciplinary research and processes are focused on solving ill-defined and society-relevant problems, like sustainability and environmental problems. It has still not received much attention, in particular, when the decision-making is difficult due to the lack of a suitable analytical basis. TE requires extensive IT support to manage and control the large amount of data and knowledge produced and used in TE processes. It is implemented through the follow- ing processes (Wognum et al., in press).

Peruzzini, M., Stjepandić, J. (2018). Editorial to the special issue “Transdisciplinary analytics in supply chain management”. JOURNAL OF MANAGEMENT ANALYTICS, 5(2), 75-80 [10.1080/23270012.2018.1443405].

Editorial to the special issue “Transdisciplinary analytics in supply chain management”

Peruzzini, Margherita;
2018

Abstract

The last two decades of designing large-scale engineering systems have demonstrated that the even higher complexity of problems requires entirely new solution approaches. Transdisciplinary engineering (TE) is a means to overcome the limits of inter- or multi- disciplinary approaches. For such challenges, transdisciplinary research and processes are focused on solving ill-defined and society-relevant problems, like sustainability and environmental problems. It has still not received much attention, in particular, when the decision-making is difficult due to the lack of a suitable analytical basis. TE requires extensive IT support to manage and control the large amount of data and knowledge produced and used in TE processes. It is implemented through the follow- ing processes (Wognum et al., in press).
2018
Peruzzini, M., Stjepandić, J. (2018). Editorial to the special issue “Transdisciplinary analytics in supply chain management”. JOURNAL OF MANAGEMENT ANALYTICS, 5(2), 75-80 [10.1080/23270012.2018.1443405].
Peruzzini, Margherita; Stjepandić, Josip
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/952221
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