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Digital Business Innovation Studio

Reference number
Coordinator INTERNATIONELLA HANDELSHÖGSKOLAN I JÖNKÖPING AB
Funding from Vinnova SEK 1 199 341
Project duration December 2016 - June 2020
Status Completed

Important results from the project

This project has developed personalization and automation solutions that strengthen news media. The core of the project was to understand the digital transformation challenges that industries face, and the increasing susceptibility with automatization, machine learning. This project applied the approach of make-to-learn to link new AI opportunities and organizational capabilities. The results give them insights on how companies can change their product offerings and processes, the consequences of AI for employees, customers and society at large.

Expected long term effects

The results included technical developments and innovation capability development. The technical developments solutions have potential to broaden digital content production and personalize the selection of news. The capability renewal refers to new processes that focus on technical development, exploring mechanisms of re-skilling professionals and building new digital competences (machine learning). Industrial digitalization affects professional practices which might become obsolete when these do not bridge new organizational or technical boundaries.

Approach and implementation

This project developed methods to build innovation capabilities for digital transformation. Enabled by the project-specific activities, participants developed AI capabilities to be implemented in new process in media management. During the implementation, we learnt that AI capability building can occur through external acquisition which leads to platform dependence and university-industry collaborations are ideal for technology exploration, and internal capability development for technology deployment.

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 27 August 2020

Reference number 2016-04527