University of Twente Student Theses
Detecting emerging technological trends by patent text mining for the automotive industry.
Lagrand, S. (2023) Detecting emerging technological trends by patent text mining for the automotive industry.
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| Abstract: | In a VUCA world, firms are forced to become more dynamic. Quickly responding to new innovations is required to maintain a firm’s competitive advantage. By being able to detect emerging patterns, firms can more effectively manage their R&D portfolio. This research addresses the problem of improving firms’ ability to detect emerging technological trends, thereby improving their competitiveness and innovative capabilities. The findings contribute to the understanding of R&D portfolio management by detecting persistent, emerging, and fading patterns in the automotive industry. These patterns are identified by using patent text mining on the R&D portfolios of the top-5 firms over time. The study is relevant, since it assists firms in navigating through the dynamic and quickly evolving environment of the automotive industry by providing guidelines for firms’ R&D strategies. |
| Item Type: | Essay (Bachelor) |
| Faculty: | BMS: Behavioural, Management and Social Sciences |
| Subject: | 83 economics, 85 business administration, organizational science |
| Programme: | International Business Administration BSc (50952) |
| Link to this item: | https://purl.utwente.nl/essays/95448 |
| Export this item as: | BibTeX EndNote HTML Citation Reference Manager |
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