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2024/2025  KAN-CDSCV2401U  Innovation and Strategy in the Digital Economy

English Title
Innovation and Strategy in the Digital Economy

Course information

Language English
Course ECTS 7.5 ECTS
Type Elective
Level Full Degree Master
Duration One Quarter
Start time of the course Second Quarter
Timetable Course schedule will be posted at calendar.cbs.dk
Max. participants 120
Study board
Master of Science (MSc) in Business Administration and Data Science
Course coordinator
  • Lars Bo Jeppesen - Department of Strategy and Innovation (SI)
Main academic disciplines
  • Innovation
  • Organisation
  • Strategy
Teaching methods
  • Blended learning
Last updated on 23-01-2024

Relevant links

Learning objectives
After successfully completing the course, the student should be able to:
  • Understand the current debates around innovation in the digital economy, strategy, as it relates to digital economy and data.
  • Explain how digital changes and the availability of data transform the business landscape.
  • Discuss relevant theories and explain their assumptions, causal dynamics and processes.
  • Assess the role of data in business innovation and specify success and failure factors
  • Understand central concepts around management in the context of digital businesses.
  • Discuss ethical issues of the digital economy and organizations’ use of data.
Examination
Innovation and Strategy in the Digital Economy:
Exam ECTS 7,5
Examination form Written sit-in exam on CBS' computers
Individual or group exam Individual exam
Assignment type Written assignment
Duration 4 hours
Grading scale 7-point grading scale
Examiner(s) One internal examiner
Exam period Winter
Aids Open book: all written and electronic aids, including internet access
Read more here about which exam aids the students are allowed to bring and will be given access to : Exam aids and IT application package
Make-up exam/re-exam
Same examination form as the ordinary exam
The number of registered candidates for the make-up examination/re-take examination may warrant that it most appropriately be held as an oral examination. The programme office will inform the students if the make-up examination/re-take examination instead is held as an oral examination including a second examiner or external examiner.
Course content, structure and pedagogical approach

This course will give students an introduction to central issues of innovation and strategy in the digital economy. It forms the background for the study of data in the business context. The growth of the digital economy is predicting a data rich future and a transformation of the business landscape with implications for existing firm, entrepreneurial ventures, and individual workers. In some of the most dynamic sectors of the modern economy, such as, apps for smartphones, video games, scientific and technical problems solving, Internet of Things, artificial intellegence (AI) technologies, companies’ overall performance already rely on data, setting requiring a whole new set of skills and organizational capabilities. The course will develop the conceptual foundations, frameworks and methods for analyzing the relationships between firms, crowds, AI, platforms and data. It introduces student to the process of digital transformation. The course gives students a systematic basis for assessing the economic potential of different sorts of data and organizational imperatives to unlocking this potential. The first part of the course introduces business models of the digital economy. The latter part will focus on organizing for innovation in a data rich business context. From this point of departure, the course will develop the conceptual foundations, frameworks, and methods for analyzing the relationships between innovation, strategy, and data in a digital context. The focus will be on how to manage and strategize, how existing organizations adapt to increasing digitization of business and development models. Topics will include:

 

  • Digital economy and innovation
  • Digital business models and strategy
  • Internet of Things
  • The role of crowds in generating innovation and predictions.
  • Crowdsourcing, collaborative innovation
  • Digital platforms, platform markets and platform disruption 
  • Managing organizations in a data rich future
  • Data networks and markets

 

Description of the teaching methods
The course will employ a variety of teaching forms, including lectures, interactive case based sessions, hands-on exercises, and guest lectures by practitioners. Some sessions will be face-to-face and some will be online.
Feedback during the teaching period
During sessions there will be an opportunity for feedback from professors and peers.
Student workload
Teaching 30 hours
Preparation 93 hours
Exam and preparation for exam 83 hours
Total 206 hours
Further Information
  • There may be an overlap between Innovation and Strategy in the Digital Economy and the course Digital Strategy and Innovation.

 

  • Part of minoren Data and Business.
Expected literature

The literature can be changed before the semester starts. Students are advised to find the final literature on canvas before they buy any material.

 

Boudreau K., Jeppesen, LB., 2015, Unpaid Crowd Complementors: The Platform Network Effect Mirage, Strategic Management Journal

 

Boudreau, K., & Lakhani, K. (2009). How to manage outside innovation. MIT Sloan management review, 50(4), 69.

 

Chesbrough, H. W., & Appleyard, M. M. (2007). Open innovation and strategy. California Management review, 50(1), 57-76.

 

Dahlander Jeppesen Piezunka 2019 Define, Broadcast, Attract and Select: A Framework for Crowdsourcing, INSEAD Knowledge

 

Davenport, T. H. (2009). How to design smart business experiments. Harvard business review, 87(2), 68-76.

 

Goldfarb, Avi and Tucker, Catherine E., Digital Economics (August 2017). NBER Working Paper No. w23684.

 

Hagui, Andrei & Julian Wright (2020): When data creates competitive advantage… and when it doesn’t. Harvard Business Review, January-February 2020, pp. 94-101.

 

Iansiti, M., & Lakhani, K. (2020): Competing in the Age of AI. Harvard Business Review. January-February 2020, pp. 3-9.

 

Lambrecht, A. & Tucker, C. (2015): Can Big Data Protect a Firm from Competition? Available at SSRN: https:/​/​ssrn.com/​abstract=2705530

 

Laursen, K., & Salter, A. (2006). Open for innovation: the role of openness in explaining innovation performance among UK manufacturing firms. Strategic management journal, 27(2), 131-150.

 

Mazzei, M. J., & Noble, D. (2017). Big data dreams: A framework for corporate strategy. Business Horizons, 60(3), 405-414.

 

Parker, van Alstyne and Choudary, 2016, Platform Revolution. Norton &Company, pp: 1-34

 

Thomke, Stefan, and Jim Manzi. "The Discipline of Business Experimentation." Harvard Business Review 92, no. 12 (December 2014): 70–79.

 

von Hippel, E. (2005) Democratizing Innovation Chapter 1. MIT Press, Introduction and Overview, in Democratizing Innovation, Cambridge MA: MIT Press: 1-18

 

von Hippel, E., & Kaulartz, S. (2021). Next-generation consumer innovation search: Identifying early-stage need-solution pairs on the web. Research Policy, 50(8), 104056.

 

Last updated on 23-01-2024