MSE Master of Science in Engineering

The Swiss engineering master's degree

Ogni modulo equivale a 3 crediti ECTS. È possibile scegliere un totale di 10 moduli/30 ECTS nelle seguenti categorie: 

  • 12-15 crediti ECTS in moduli tecnico-scientifici (TSM)
    I moduli TSM trasmettono competenze tecniche specifiche del profilo e si integrano ai moduli di approfondimento decentralizzati.
  • 9-12 crediti ECTS in basi teoriche ampliate (FTP)
    I moduli FTP trattano principalmente basi teoriche come la matematica, la fisica, la teoria dell’informazione, la chimica ecc. I moduli ampliano la competenza scientifica dello studente e contribuiscono a creare un importante sinergia tra i concetti astratti e l’applicazione fondamentale per l’innovazione 
  • 6-9 crediti ECTS in moduli di contesto (CM)
    I moduli CM trasmettono competenze supplementari in settori quali gestione delle tecnologie, economia aziendale, comunicazione, gestione dei progetti, diritto dei brevetti, diritto contrattuale ecc.

La descrizione del modulo (scarica il pdf)riporta le informazioni linguistiche per ogni modulo, suddivise nelle seguenti categorie:

  • Insegnamento
  • Documentazione
  • Esame
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

Requisiti

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)

Obiettivi di apprendimento

  • 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.

Categoria modulo

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

Metodologie di insegnamento e apprendimento

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

Bibliografia

  • 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.

Scarica il descrittivo completo del modulo

Indietro