MSE Master of Science in Engineering

The Swiss engineering master's degree

Jedes Modul umfasst 3 ECTS. Sie wählen insgesamt 10 Module/30 ECTS in den folgenden Modulkategorien:

  • ​​​​12-15 ECTS in Technisch-wissenschaftlichen Modulen (TSM)
    TSM-Module vermitteln Ihnen profilspezifische Fachkompetenz und ergänzen die dezentralen Vertiefungsmodule.
  • 9-12 ECTS in Erweiterten theoretischen Grundlagen (FTP)
    FTP-Module behandeln theoretische Grundlagen wie die höhere Mathematik, Physik, Informationstheorie, Chemie usw. Sie erweitern Ihre abstrakte, wissenschaftliche Tiefe und tragen dazu bei, den für die Innovation wichtigen Bogen zwischen Abstraktion und Anwendung spannen zu können.
  • 6-9 ECTS in Kontextmodulen (CM)
    CM-Module vermitteln Ihnen Zusatzkompetenzen aus Bereichen wie Technologiemanagement, Betriebswirtschaft, Kommunikation, Projektmanagement, Patentrecht, Vertragsrecht usw.

In der Modulbeschreibung (siehe: Herunterladen der vollständigen Modulbeschreibung) finden Sie die kompletten Sprachangaben je Modul, unterteilt in die folgenden Kategorien:

  • Unterricht
  • Dokumentation
  • Prüfung
Smart services (CM_SmartSer)

 

Smart Service Design and Engineering - Value Creation:

  • Basics of Smart Service Design (Customer insight, customer journey, value proposition design, use of data insights)
  • Selected topics of Service Science and Service Dominant Logic
  • Service blueprinting as a relevant step in the service engineering process
  • Characteristics of Data Services and Data Products
  • Use of data in the smart service design process and in the services themselves - Smart Data
  • data sources
  • Iterative improvement up to product maturity
  • Discussion of applications in the industrial and the sector
  • Discussion of real-life cases

Smart Business Model Design - Value Capturing:

  • Fundamentals for Engineering Value Flows in Service Ecosystems and Service Business Models
  • From Service Blueprint to Business Model
  • Quantification of service business models
  • Basics Business Model Design and Business Model Canvas
  • Service Ecosystem Design
  • Quantification of the business model
  • Discussion of real-life cases

Data Protection, Data Security, Data Ethics:

  • Fundamentals of data protection and data security
  • Relevant aspects for Data Product Design
  • Legal aspects vs. ethics
  • Discussion of real-life cases

Eintrittskompetenzen

Prior to joining the module, the students should have an understanding of business process modeling and engineering, e.g., terms like process charts, swimlanes, process models, resources, value chain etc. (see, e.g., the paper of John Krogstie: Introduction to Business Processes and Business Process Modeling, https://link.springer.com/chapter/10.1007/978-3-319-42512-2_1)

Lernziele

  • Understand and apply the essential principles of Smart Service Design and Engineering - i.e. the development of intelligent services on the basis of data (comprehensive methods for the development of novel data-driven services, for their operation as well as their improvement in operations).
  • Able to integrate the data specific aspects into their service design.
  • Apply the methods of data-driven service engineering in practical case studies primarily in industrial envi-ronments (B2B), but also in consumer areas (B2C)
  • Know and understand the relevant basics of Service Business Model Design including the types of industrial Service Models.
  • Evaluate these business models quantitatively. To weigh up variants and draw conclusions about the engineering process with the aim of achieving an opera-tionally and economically balanced model.
  • Understand the design of service ecosystems.
  • Able to understand the essential principles of data protection, data security, and data ethics.

Modulinhalt

Smart Service Design and Engineering - Value Creation: 40%
Smart Business Model Design - Value Capturing: 40%
Data Protection, Data Security, Data Ethics: 20%

Lehr- und Lernmethoden

  • Lectures
  • Group work, presentation and discussion of case studies
  • Self study of papers and analysis of business case studies

Bibliografie

  • A. Wierse, T. Riedel: Smart Data Analytics, Walter de Gruyter, 2017.
  • A. Polaine, L. Løvlie, B. Reason, Service Design: From Insight to Implementation, Rosenfeld, 2013.
  • A. Osterwalder, Y. Pigneur et al., Value Proposition Design: How to Create Products and Services Customers Want, Wiley, 2014.
  • E. Siegel, Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, Wiley, 2016.
  • F. Provost, T. Fawcett, Data Science for Business: What you need to know about data mining and data-analytic thinking, O'Reilly, 2013.
  • A. Osterwalder, Y. Pigneur, Business Model Generation, Wiley, 2010.
  • C. Kowalkowski, W. Ulaga: Service strategy in action: a practical guide for growing your B2B service and solution business, Service Strategy Press, 2017.
  • O. Gassmann, K. Frankenberger, M. Csik:  Business Model Navigator: 55 Models That Will Revolutionise Your Business, Harlow Pearson, 2014.
  • D. S. Evans, R. Schmalensee, Matchmakers, Matchmakers: The New Economics of Multisided Platforms, Harvard Business Review Press, 2016.
  • W. Stallings, Cryptography and Network Security: Principles and Practice (7th Edition), Pearson, 2016.
  • N. Passadelis et al., Datenschutzrecht, Beraten in Privatwirtschaft und öffentlicher Verwaltung, Basel 2015.

  • Stickdorn, Marc, Markus Edgar Hormess, Adam Lawrence, and Jakob Schneider 2018: This Is Service Design Doing: Applying Service Design Thinking in the Real World. O’Reilly Media, Inc.

Vollständige Modulbeschreibung herunterladen

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