Development of a Pre-Competitive Business Model for AI-Based Autonomous Technology Scouting

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Leachu, S.; Clemens, F.; Stich, V.: Development of a Pre-Competitive Business Model for AI-Based Autonomous Technology Scouting. In: Herberger, D.; Hübner, M. (Eds.): Proceedings of the Conference on Production Systems and Logistics: CPSL 2022. Hannover : publish-Ing., 2022, S. 612-621. DOI: https://doi.org/10.15488/12163

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Sum total of downloads: 266




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Abstract: 
Technology management can significantly influence the strategic decisions of a company and thus cause success or failure. Basic templates for technology management are technology radars as well as the determination of the technology readiness level (TRL) to be able to evaluate the maturity of newly deployed technologies (e.g., newcomer vs. established). The radars, as well as the TRL, are identified in time- consuming, manual research by subject matter experts from external consultancies. This process is often repeated due to the further development and new development of technologies so that the necessary research becomes an ongoing task. The TechRad research project, therefore, aims to automate the identification of the TRL as well as technology radars using web crawling and Natural Language Processing (NLP). To commercialize the pre-competitive prototype, the development of a pre-competitive business model is the goal of this paper. Based on customer analyses, a target group definition is created. Based on user interviews, the precompetitive business model will be detailed in a four-step approach using a business model canvas and a value proposition canvas.
License of this version: CC BY 3.0 DE
Document Type: BookPart
Publishing status: publishedVersion
Issue Date: 2022
Appears in Collections:Proceedings CPSL 2022
Proceedings CPSL 2022

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downloads by country:

pos. country downloads
total perc.
1 image of flag of Germany Germany 107 40.23%
2 image of flag of United States United States 30 11.28%
3 image of flag of Iran, Islamic Republic of Iran, Islamic Republic of 9 3.38%
4 image of flag of Korea, Republic of Korea, Republic of 8 3.01%
5 image of flag of Italy Italy 8 3.01%
6 image of flag of Hungary Hungary 8 3.01%
7 image of flag of Taiwan Taiwan 7 2.63%
8 image of flag of Sweden Sweden 7 2.63%
9 image of flag of India India 6 2.26%
10 image of flag of Austria Austria 6 2.26%
    other countries 70 26.32%

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