Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/196465 
Year of Publication: 
2018
Citation: 
[Journal:] Amfiteatru Economic Journal [ISSN:] 2247-9104 [Volume:] 20 [Issue:] 49 [Publisher:] The Bucharest University of Economic Studies [Place:] Bucharest [Year:] 2018 [Pages:] 805-819
Publisher: 
The Bucharest University of Economic Studies, Bucharest
Abstract: 
The purpose of the paper is to contribute to the development of best practices at emerging factories of the future, i.e. smart factories of Industry 4.0. Smart factories need to develop effective managerial early warning systems to identify and respond to subtle threats or opportunities, i.e. weak signals, in order to adapt to an ever-changing environment in a timely manner and thus gain or maintain a competitive advantage on the market. These factories need to develop and implement a several-stage early warning system that is specific to their industry. The aim of our study is, with the help of semi-structured group interviews, to examine which stages of a managerial early warning system are present in the case of a global innovative supplier in the automotive industry. As such, a four-stage managerial early warning system model for a knowledge-based automotive smart factory is proposed, in which aggregate activities and management decision-making strategies are defined for each stage, with the importance of intuition being taken into consideration. We found that managers rely on intuition and extensive analysis for satisficing strategies and teamwork for optimizing strategies, when using their managerial early warning system.
Subjects: 
managerial early warning system
best practice
Industry 4.0
smart factories
satisficing and optimizing
Slovenia
JEL: 
D81
D91
O33
L60
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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