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Analyzing Digital Data

Many phenomena that are of interest to management and organization scholars are captured in the form of rich digital (trace) data. Detailed work and navigation processes are captured in information systems and activity logs, product characteristics are described in textual product descriptions, gig platforms capture a wealth of data about workers, and CEOs manage the impression of their firms in video-recorded press conferences.

dr. Joey van Angeren

dr. Joey van Angeren

Find out more
JOEY VAN ANGEREN

dr. Hakan Ozalp

dr. Hakan Ozalp

His research focuses on platform-based ecosystems as he explores the impact of industrial and technological change (a) on the platform ecosystem, (b) on the firm, and (c) the antecedents of these changes.

View the profile of Hakan Ozalp

Course Description

The availability of such rich digital data provides novel opportunities for theorization and analysis. To this purpose, scholars of management and organization have turned to methods originally developed in computer science, to collect and work with digital data. A distinct feature of those methods is that they are applied in both qualitative and quantitative research, for purposes that range from data exploration, to theory development, and onto hypothesis testing.

Download the course manual here

Study Characteristics

  • Study period: April 2025 (Period 5)
  • Credits: 5 ECTS
  • Tuition fee: €1250 (20% discount for early bird registration)
  • Registration deadline: 17-03-2025 (early bird registration: 24-02-2025)
  • Prerequisite knowledge: This course is an advanced methods course that assumes prior knowledge of business and management or organization studies as well as a basic understanding of qualitative and/or quantitative research methods. Familiarity with programming in Python or R is also required (full proficiency in those programming languages is not necessary though).
  • Teaching methods: interactive sessions, Reading literature and other class preparation, Working on the group research assignment.
  • Assessment: Class participation (50%), Group research paper (50%).
  • The Analyzing Digital Data in Business and Management Research course is open to postdocs, PhD candidates, and research master students engaging in research in business and management or related fields such as organization studies. 
  • Course Description & Study Characteristics

    Course Description

    The availability of such rich digital data provides novel opportunities for theorization and analysis. To this purpose, scholars of management and organization have turned to methods originally developed in computer science, to collect and work with digital data. A distinct feature of those methods is that they are applied in both qualitative and quantitative research, for purposes that range from data exploration, to theory development, and onto hypothesis testing.

    Download the course manual here

    Study Characteristics

    • Study period: April 2025 (Period 5)
    • Credits: 5 ECTS
    • Tuition fee: €1250 (20% discount for early bird registration)
    • Registration deadline: 17-03-2025 (early bird registration: 24-02-2025)
    • Prerequisite knowledge: This course is an advanced methods course that assumes prior knowledge of business and management or organization studies as well as a basic understanding of qualitative and/or quantitative research methods. Familiarity with programming in Python or R is also required (full proficiency in those programming languages is not necessary though).
    • Teaching methods: interactive sessions, Reading literature and other class preparation, Working on the group research assignment.
    • Assessment: Class participation (50%), Group research paper (50%).
    • The Analyzing Digital Data in Business and Management Research course is open to postdocs, PhD candidates, and research master students engaging in research in business and management or related fields such as organization studies. 

Would you like to register or want to know more?

Please register with the Apply Now button at the top of this page. For more information please contact the course coordinator dr. Joey van Angeren:

joey.van.angeren@vu.nl

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