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2026/2027  BA-BHAAV2626U  Introduction to Data Analytics for Innovation, Technology, and Markets

English Title
Introduction to Data Analytics for Innovation, Technology, and Markets

Course information
Language English
Course ECTS 7.5 ECTS
Type Elective
Level Bachelor
Duration One Semester
Start time of the course Autumn
Timetable Course schedule will be posted at calendar.cbs.dk
Max. participants 80
Study board
Study Board for General Management
Programme Bachelor of Science in Economics and Business Administration
Course coordinator
  • Marek Giebel - Department of Economics (ECON)
Main academic disciplines
  • Innovation
  • Statistics and quantitative methods
  • Economics
Teaching methods
  • Face-to-face teaching
Last updated on 30-01-2026

Relevant links
Learning objectives
The course has multiple objectives. After having participated in this course, students should be able to:
  • Identify and apply appropriate theories to analyze the effects of innovation
  • Argue and critically assess how an empirical analysis relates to theories about the impact of innovations on firms, markets, and society
  • Interpret and critically assess estimation results
  • Set empirical results in the context of the broader debate on the impact of innovations on organizations and society
Course prerequisites
Basic knowledge of microeconomics, descriptive statistics, and linear regression models.
Examination
Introduction to Data Analytics for Innovation, Technology, and Markets:
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 Limited aids, see the list below:
The student is allowed to bring
  • Any calculator
  • Language dictionaries in paper format
The student will have access to
  • Advanced 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 is a hands-on, data-oriented course that combines theory with econometric and statistical tools to analyze the determinants and effects of innovation and new technologies on firms, markets, and society. Innovation and new technologies are central to today’s fast-changing economy. Managers, entrepreneurs, and policymakers need to decide which technologies to support, how to organize innovation, and how to evaluate their impacts. This course integrates perspectives from economics, finance, and management to explore the connection between theory and empirical evidence. We will study how new ideas and technologies influence firms, markets, and society. 

 

A central component of the course is an introduction to the analysis of innovation-related datasets (e.g., firm-level, patent, or labor-market data) using statistical software and to the basics of interpreting regression results. We will adopt an integrated approach, discussing key topics in innovation through theory and related empirical studies. Core topics include innovation incentives and competition, innovation policy, intellectual property rights and strategy, and innovation financing and valuation. We will also examine how innovation, automation, and artificial intelligence impact economic growth, financial markets, labor markets, firms, and society. Throughout the course, we will analyze relevant innovation questions with empirical studies and real-world data. Additionally, we will introduce econometric tools and data analysis techniques to evaluate and discuss the societal impacts of innovation. The course will also teach you how to interpret and communicate results that inform strategic decisions and policy design. 
Research-based teaching
CBS’ programmes and teaching are research-based. The following types of research-based knowledge and research-like activities are included in this course:
Research-based knowledge
  • Classic and basic theory
  • New theory
  • Teacher’s own research
  • Methodology
  • Models
Research-like activities
  • Development of research questions
  • Data collection
  • Analysis
  • Discussion, critical reflection, modelling
  • Activities that contribute to new or existing research projects
Description of the teaching methods
The course follows the structure of a three-hour per week class. Teaching includes lecture-style classes, in-class workshops, and practical computer exercises. Students are encouraged to present and actively participate in discussions. Blended learning instances will help the students deepen their understanding of the statistical software, empirical methods, and empirical applications.
Feedback during the teaching period
The course follows the structure of a three-hour per week class. Teaching includes lecture-style classes, in-class workshops, and practical computer exercises. Students are encouraged to present and actively participate in discussions.
Student workload
Preparation 106 hours
Classes 30 hours
Exam 70 hours
Expected literature

Core reading includes selected chapters from:

  • Bryan, K.A. and Williams, H.L. (2021). Innovation: market failures and public policies. In Handbook of Industrial Organization (Vol. 5, No. 1, pp. 281-388). Elsevier.
  • Pepall, L., Richards, D.J. and Norman, G. (2014). Industrial organization: Contemporary theory and empirical applications. Wiley.
  • Scotchmer, S. (2004). Innovation and incentives. Cambridge, Mass.: MIT Press.
  • Békés, G., & Kézdi, G. (2021). Data analysis for business, economics, and policy. Cambridge University Press.
  • Cunningham, S. (2021). Causal inference: The mixtape. Yale university press.

 

More literature will be announced in the syllabus.

Last updated on 30-01-2026