Quantitative Methods for Innovation Research
This NORSI core course is organized in collaboration between University of Stavanger and Lund University (CIRCLE). The Course gives 5 ECTS, and is administered and held at The University in Stavanger in December 2022.
ECTS credits: 5
Level of course: Ph.D. course
Type of course: Elective for students in business or other social science disciplines studying entrepreneurship and innovation for their PhD.
We are planning for an in-person class at The University of Stavanger in Norway. The course will include lectures and computer lab sessions in relation to the methods.
Registration deadline: TBA!
Course Responsible & Faculty
Professor Tom Brökel , University of Stavanger Business School
Professor Torben Schubert, CIRCLE, Lund University and Fraunhofer Institute for Systems and Innovation Research ISI
This course is part of the Nordic Research School in Innovation and entreprenurship (NORSI) and introduces students to the quantitative analysis part of the common course in research methods under the NORSI program. The course will exclusively be offered as a part of NORSI common courses. The course will survey the most commonly used quantitative analysis techniques in the social sciences such as an introduction to R, data reduction techniques, regression and correlation analysis, and social network analysis. Students will learn about these techniques as applied in the field of innovation studies.
Students will have an basic overview of quantitative analysis techniques and their application in innovation research.
Students will be able to evaluate the use of methods and the main data sources relevant for innovation research.
Students will be able to develop new knowledge and new theories on innovation using quantitative methods.
Students will be able to conduct innovation research at a basic level using quantitative methods, including factor analysis, regression and correlation analysis, and social network analysis.
Students will be able to formulate new research questions and conduct innovation research using quantitative methods.
Students will be able to handle the statistical software R.
Students will be able to assess when and how to use quantitative research methods.
Students will be able to discuss academic analyses in the field at a basic level. Students will be able to assess research using quantitative methods.
Registration and registration form: To registered for the course please send an email to Nadya Sandsmark <email@example.com> together with UiS application form for PhD courses.
Registration deadline: TBA!
Course assessment and requirement
Assessment: To obtain 5 ECTS point requires active participation during the course as well as an accepted paper of 3.000-4.000 words demonstrating competence in using quantitative methods. The paper should be based on the topic of the PhD thesis and reflect literature used in the course. If quantitative methods will not be used in the thesis a paper answering given tasks could substitute a normal paper. However, the concrete form of the written delivery can be further discussed during the course.
Exam: Term paper – appr. 3.000-4.000 words. The paper will be assessed as a pass/fail. Active class room participation required.
All students have to bring their own PC with installations of R and R-Studio.
How to get to Stavanger
The best way to come to The University of Stavanger if you come from abroad is my plane, directely to Sola Airport or via Oslo, Gardermoen Lufthavn to Sola Airport. It is also possible to take a bus from Oslo to Stavanger.
The University of Stavanger is located approximately 25 minutes by buss, from Stavanger city center at Kjell Arholms gate 41, 4021 Stavanger.
We ask kindly that all students make their own travel arrangements (economy).
NORSI Travel Reimbursement
As this is a NORSI course all travel expenses etc. will be covered for NORSI students and teaching faculty.
Please see NORSI Travel Policy for more information.
PhD students registered for the course that are not part of NORSI will have to cover their own expensens.