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2020/2021  BA-BSOCV2013U  Digital Society D. Analyzing corporate networks using digital methods

English Title
Digital Society D. Analyzing corporate networks using digital methods

Course information

Language English
Course ECTS 7.5 ECTS
Type Elective
Level Bachelor
Duration One Quarter
Start time of the course Second Quarter
Timetable Course schedule will be posted at calendar.cbs.dk
Max. participants 60
Study board
Study Board for BSc in Business Administration and Sociology
Course coordinator
  • Christoph Houman Ellersgaard - Department of Organization (IOA)
Main academic disciplines
  • Organisation
  • Sociology
  • Strategy
Teaching methods
  • Blended learning
Last updated on 07-02-2020

Relevant links

Learning objectives
The course will aim at giving student digital tools to collect and analyze data on corporate networks. Furthermore, we aim to give students the necessary theoretical background to understand and analyze networks.
The course aims to provide the students with the ability to
  • Use and critically reflect on digital methods to gain access to data on corporate networks
  • Understand and use tools for collecting digital data online
  • Be capable of cleaning data and use other procedures to enhance data quality
  • Account for different understandings of corporate strategies in a network perspective
  • Analyze intra- or interorganizational networks using theory and methods from network analysis
  • Communicate findings from network analysis both in text and through data visualization
Course prerequisites
The course intends to introduce students to statistical programming, but having some prior experience working with research design and quantitative methods will be an advantage.
Analyzing corporate networks using digital methods:
Exam ECTS 7,5
Examination form Home assignment - written product
Individual or group exam Group exam
Please note the rules in the Programme Regulations about identification of individual contributions.
Number of people in the group 2-3
Size of written product Max. 15 pages
Assignment type Essay
Duration Written product to be submitted on specified date and time.
Grading scale 7-point grading scale
Examiner(s) One internal examiner
Exam period Winter
Make-up exam/re-exam
Same examination form as the ordinary exam
Course content, structure and pedagogical approach

Understanding how a firm is connected – both to its environment and internally – is key to identify strengths and weaknesses in the strategy of the firm. Digital methods can give access to the types of data that allow us to understand these connections through network analysis. Understanding how to get access to and analyze these data will be a key driver for organizational innovations in the future.
The course will give an introduction to corporate strategies in a network perspective and provide students with tools to use digital methods to get access to network data. This will include both learning to scrape data online and to use statistical programming to manage these data and produce analysis of relevance to understand and implement corporate strategies. Using corporate networks as a theoretical framework, the course aim at not only providing students with technical analytical skills, but also to show how these skills can be applied


Three main elements of the course will be:


1. Conceptual-theoretical framework in which network theories about corporate strategies are presented


2. Technical component which includes teaching techniques for scraping data and tools for statistical programming of networks analysis


3. Critical sociological reflections on how to analyse and interpret the data of corporate network analysed.


Description of the teaching methods
The teaching is based on lectures complemented by plenum discussions, blended learning and other methods designed to facilitate as much active class participation as possible.

Exercises will give the students the chance to work with the digital methods and get feedback on their work and their progression during the course.

The course leads towards a group project prepared by students, which they will work on continuously and will serve as the basis of their exam paper.

Lecture slides, literature and presentations will be accessible on Canvas.

The students are expected to read the literature for each class and participate actively in the sessions.

The course will include blending learning by using video tutorials for statistical programming and collaborative learning in statistical programming. Adding to this, peer-grading will be used as a feedback form.

We will use the R-programming language as basis for work in the course. No prior experience with rather is needed, as the exercises will also include introduction to the R-language.
Feedback during the teaching period
The groups will present their work continuously through exercises by presenting mini-cases and receive peer feedback from the teacher and other students. The student will get feedback on work presented in each exercise from fellow students and teachers.
Student workload
Lectures 20 hours
Exercises 16 hours
Preparation, exam 170 hours
Expected literature
  1. Burt, R. (1983). Corporate Profits and Cooptation: Networks of Market Constraint and Directorate Ties in the American Economy. New York: Academic Press.
  2. Burt, R. (1992). Structural Holes: The Social Structure of Competition. Cambridge, MA: Harvard University Press.
  3. Davis, G. F., Yoo, M., & Baker, W. E. (2003). “The small world of the American corporate elite, 1982-2001.” Strategic Organization, 1(3), 301–26.
  4. Fligstein, N. (2001). The Architecture of Markets. Princeton: Princeton University Press. 
  5. Granovetter, M. (1985). “Economic Action and Social Structure: The Problem of Embeddedness.” American Journal of Sociology, 91(3), 481–510.
  6. Podolny, J. (1993). “A Status-Based Model of Market Competition.” American Journal of Sociology, 98(4), 829–72.
  7. Powell, W., Koput, K. W., & Smith-Doerr, L. (1996). “Interorganizational collaboration and the locus of innovation: Networks of learning in biotechnology.” Administrative science quarterly, 41(1), 116–145.
  8. Vedres, D., & Stark, D. (2010). “Structural Folds: Generative Disruption in Overlapping Groups.” American Journal of Sociology, 115(4), 1150–90.
  9. Vitali, S., Glattfelder, J. B., & Battiston, S. (2011). “The network of global corporate control.” PLoSONE, 6(10). General Finance; Physics and Society. 
  10. Wasserman, Stanley, and Katherine Faust. Social Network Analysis: Methods and Applications. Cambridge: Cambridge University Press, 1994.
  11. Westphal, J. D. (1999). “Collaboration in the boardroom: The consequences of social ties in the CEO/board relationship.” Academy of Management Journal, 42(1), 7–24.
  12. White, H. (1981). “Where Do Markets Come From?” American Journal of Sociology, 87(3), 517–47.
  13. Uzzi, B. (1997). “Social Structure and Competition in Inter-Firm Networks: The Paradox of Embeddedness.” Administrative Science Quarterly, 42(1), 35–67.
  14. Uzzi, B., & Spiro, J. (2005). “Collaboration and Creativity: The Small World Problem.” American Journal of Sociology, 111(2), 447–504.
Last updated on 07-02-2020