Evidence-based Management (Autumn 2023)

Abstract

The course focuses on methodology and its practical application in relation to IT management. Through two seminars, students will be able to learn about and experiment with evidence-based decision-making, as well as evaluate which methods are most suitable under specific circumstances. A variety of methods and their applications will be introduced from an organizational perspective. Throughout the course, students will work with the course's methods in relation to generating and analyzing organizational knowledge within the field of IT management, and will additionally work on reporting the results, all of which can be applied to their final exam. The course also provides the necessary methodological tools for writing academic assignments.

Description

The first day of the course introduces evidence-based decision making and the fundamental elements of research methods and data gathering. The second day introduces specific methods and data gathering techniques, such as case studies, digital methods, organisational ethnography and design. The third day focuses on data analysis and compares the applicability of different methods and their strengths and weaknesses relative to different research goals and contexts. Students will also learn ways to visualise their data and get the opportunity to report on and explain their analytic findings. During the fourth day, students will be presented with the nuances of action research also through workshops and discussions.

Formal prerequisites

There are no formal prerequisites. 

(Students are encouraged to have thought of an organizational problem/ issue they would like to investigate).

Intended learning outcomes

After the course, the student should be able to:

• Identify and delineate an IT business problem that can be elucidated through analysis.
• Select and justify the choice of data sources according to both methodological considerations of validity and reliability, as well as business considerations.
• Select and justify the choice of analytical methods or a combination of these in relation to methodological and business considerations.
• Demonstrate basic skills in data analysis.
• Prioritize and present potential analysis results in a compelling way where business pointers are supported by well-documented analysis.
• Reflect on the strengths and weaknesses of the analysis in relation to answering research questions, and relate these to business implications.

Learning activities

LEARNING ACTIVITIES

The course is delivered as a combination of self-study, group work and weekend seminars.

There are two weekend seminars that last from Friday morning to Saturday afternoon. During the seminars, activities range from class teaching to group exercises and presentations.

In the exercises, participants will work on the formulation of research questions, as well as operationalization of research questions with the use of various methodological tools such as interview guides and questionnaires. In addition, the expected results will be discussed through a reflection on how they can be communicated to the rest of the organization/ other audiences.

Course literature

TBA

Student Activity Budget

Estimated distribution of learning activities for the typical student

• Preparation for lectures and exercises: 10%
• Lectures: 30%
• Exercises: 20%
• Assignments: 20%
• Project work, supervision included: 10%
• Exam with preparation: 10%

Ordinary exam

Exam type:
C: Submission of written work, External (7-point scale)
Exam variation:
C11: Submission of written work

reexam

Exam type:
C: Submission of written work, External (7-point scale)
Exam variation:
C11: Submission of written work

Time and date

Ordinary Exam - submission Fri, 12 Jan 2024, 08:00 - 14:00