Taxonomy of a Fast Data Business Model in the Mobility Market

Andreas Landgraf

2020-ж. июн. · GRIN Verlag

Учкай маалымат

Bachelor Thesis from the year 2016 in the subject Business economics - Business Management, Corporate Governance, grade: 1,00, Campus02 University of Applied Sciences Graz, language: English, abstract: Today, the market around mobility is under heavy change. The industry is preparing the change from fossil fuels to their alternatives. Large funds are raised to build new products based on electricity, either with rechargeable battery packs or solar energy. Another field of research and development is autonomous driving. Google and Tesla are prominent examples of companies developing technologies and prototypes of future autonomous cars. The information technology used in such cars is using data analysis and artificial intelligence to observe, measure, predict and control traffic situations. This technology is influenced by one of the trending technologies of the early 21th century, Big Data. The basic research in data analysis had its crucial test in many Big Data related projects and products, like Facebook and Twitter. A part of the data analysis process are classification algorithms used to classify the input data for targeted further processing. Decision trees are one of the algorithms of classification. They are very precisely, but tend to overflow. This thesis will introduce the taxonomy of a business model, related to Open Innovation, for developing a new decision tree algorithm for the mobility market. Therefore, the data analysis process up to classification algorithms are introduced. The major decision tree algorithms are discussed in detail to build up the characteristics of the new decision tree algorithm. Furthermore, the Open Innovation model is introduced to carve out the assets and drawbacks of this model. Based on that theoretical information, the taxonomy of a preliminary business model is developed and visualized using the business model canvas. To prove this concept, expert interviews and questionnaires were used to gather feedback and new ideas. The collected information is used to modify the taxonomy of the business model. The resulting business model canvas shows the possibility of implementation.