Taxonomy of a Fast Data Business Model in the Mobility Market

Inhaltsverzeichnis (Table of Contents)

• Introduction
  • Problem Statement
  • Motivation
  • Background
  • Methodology
  • Scope and Outline of this Thesis
• From Big to Fast Data
  • Defining Big Data
  • Big Data Related Challenges
  • Fast Data
• Decision Tree Algorithms
  • A Short Introduction to Decision Trees
  • Classification Trees
    • ID3
    • C4.5
    • CART
  • Decision Trees and Fast Data
    • Hoeffding Tree
    • VFDT
    • CVFDT
    • UCVFDT
• Preliminary Business Model
  • Brief Introduction to Open Innovation
  • Step-By-Step to the Business Model Concept
• Explorative Research
  • Case Studies
  • Expert Interviews
  • Interview - Oskar Dohrau
  • Interview - Jürgen Götzenauer
• Descriptive Research
• Business Model Adaption

Zielsetzung und Themenschwerpunkte (Objectives and Key Themes)

This bachelor thesis aims to develop a taxonomy of a business model for developing a new decision tree algorithm for the mobility market. It explores the application of Open Innovation within this business model concept.

• Data analysis processes for decision tree algorithms
• Fast data and its application in the mobility market
• Open Innovation model and its potential in the automotive industry
• Business model canvas for a decision tree algorithm development project
• Explorative research methodologies using case studies and expert interviews

Zusammenfassung der Kapitel (Chapter Summaries)

The thesis begins with an introduction to the problem statement, motivation, background, and methodology used. It then delves into the concept of Big and Fast Data, explaining its significance and challenges in the context of the mobility market. Chapter 3 focuses on decision tree algorithms, providing an overview of various classification trees and their application in fast data environments. The preliminary business model is discussed in Chapter 4, introducing the principles of Open Innovation and outlining the step-by-step development of the model concept. Explorative research methods, including case studies and expert interviews, are explored in Chapter 5. The thesis concludes with a detailed explanation of the business model adaption, which incorporates insights from the research conducted.

Schlüsselwörter (Keywords)

The thesis focuses on the following key concepts: decision tree algorithms, Open Innovation, business model canvas, fast data, serious gaming, and automotive industry. It utilizes these key concepts to explore the potential of a business model for developing a new decision tree algorithm for the mobility market.