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2025/2026  BA-BSEMO2583U  Managing Coding in Service Management

English Title
Managing Coding in Service Management

Course information
Language English
Course ECTS 7.5 ECTS
Type Mandatory
Level Bachelor
Duration One Quarter
Start time of the course Third Quarter
Timetable Course schedule will be posted at calendar.cbs.dk
Study board
Study Board for Service and Markets
Course coordinator
  • Søren Henning Jensen - Department of Business Humanities and Law (BHL)
Main academic disciplines
  • Information technology
  • Innovation
  • Strategy
Teaching methods
  • Blended learning
Last updated on 26-06-2025

Relevant links
Learning objectives
After completing this course, students should be able to:
  • • Select and apply relevant theories and models to analyze managing coding in service management.
  • • Demonstrate an understanding of coding languages and their role in digital services.
  • • Analyze the impact of coding on digital service management, including flexibility, competition, and security.
  • • Identify historical developments and recent trends in coding for digital services.
Examination
Managing Coding in Service Management:
Exam ECTS 7,5
Examination form Active participation

The completion of this course is based on active student participation in class. The course will be considered as passed if the students participation - based on an overall assessment - in the class activities fulfill the learning objectives of the course. The individual student’s participation is assessed by the teacher.
The student must participate in A combination of assignment and presentation
Individual or group exam Individual exam
Grading scale Pass / Fail
Examiner(s) Assessed solely by the teacher
Exam period Spring
Make-up exam/re-exam Home assignment - written product
Size of written product: Max. 10 pages
Assignment type: Written assignment
Duration: Written product to be submitted on specified date and time.
Description of activities
A combination of assignment and presentation: The students will prepare and present an assignment in class. The presentation will form the basis of a class discussion and students will receive critique and feedback from the teacher.
Course content, structure and pedagogical approach

All digital services originate in coding. Understanding coding and what it does is central to managing digital services. This course provides an overview of the most used coding languages (e.g., Python, Java and JavaScript, C/C++) and how and where coding is used in creating digital services. We will look into the history of coding, recent developments, and the challenges in both creating and managing coding to make it flexible and protect it from competitors and hacking.

The idea is for the students to understand the basics of coding and how it affects managing digital services, not to become experts in coding. While some hands-on coding will be a part of the course, emphasis is on the managerial aspects of coding.

 

 

The course will cover:

  • The history of coding and its evolution to present day.
  • Recent developments in coding languages and their implications for service management.
  • Challenges in coding management, including flexibility, security, competition, and hacking risks.
  • Challenges and opportunities in managing coding in service management

 

 

By the end of the course, students will:

  1. Develop an awareness of coding fundamentals relevant to digital service management.
  2. Learn how coding affects strategic decision-making in digital services.
  3. Apply theories and frameworks to analyze and manage coding processes.

Understand the importance of coding in creating and managing digital services
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
  • Models
Research-like activities
  • Analysis
  • Discussion, critical reflection, modelling
Description of the teaching methods
The course includes lectures, case discussions, presentations and exercises.
• Lectures, physical or pre-recorded will cover coding fundamentals, historical context, and theoretical models.
• Exercises will focus on discussions, case studies, and applications of coding in digital service management.
• Students will work in groups to analyze coding-related case studies and receive feedback.
• Group activities will encourage participation and real-world problem-solving.
Feedback during the teaching period
Feedback During the Teaching Period:
Students will receive feedback in multiple ways:
• During lectures, through interaction with the teacher.
• During exercises, including Q&A sessions about the lecture.
• From case presentation feedback during exercises.
Student workload
Regular class sessions 38 hours
Readings (approx. 550 pages of literature) 127 hours
Other preparation before class 20 hours
Preparation for and participation in the exam: 30 hours
Expected literature

Wirtz, J., Kunz, W. H., & Paluch, S. (2021). "The far-reaching impact of transformative technologies on service management: The role of AI and robotics." Journal of Service Research, 24(4), 514–532.

 

Holmlund, M., Van Vaerenbergh, Y., Ciuchita, R., & Yrjölä, M. (2020). "Digital platforms as service ecosystems: A relational view." Journal of Business Research, 115, 278–288.

 

Rha, J. S., & Lee, J. (2022). "Digital transformation trends in service industries." Service Business, 16(4), 1105–1137.

 

Sjödin, D., Parida, V., Kohtamäki, M., & Wincent, J. (2020). "An agile co-creation process for digital servitization: A micro-service innovation approach." Journal of Business Research, 112, 478–491.

 

Boudreau, K. J., & Lakhani, K. R. (2016). Innovation experiments: Researching technical advance, knowledge production, and the design of supporting institutions. Management Science, 62(6), 1505–1518.

 

Mithas, S., Tafti, A., & Mitchell, W. (2015). How a firm’s competitive environment and digital strategic posture influence digital business strategy. MIS Quarterly, 39(2), 511–536.

 

Lee, G., & Xia, W. (2016). Toward agile: An integrated analysis of quantitative and qualitative field data on software development agility. MIS Quarterly, 40(1), 87–114.

 

Gemino, A., Reich, B. H., & Sauer, C. (2015). A temporal model of information technology project performance. Journal of Management Information Systems, 32(3), 174–207.

 

Wamba, S. F., Akter, S., Edwards, A., Chopin, G., & Gnanzou, D. (2015). How ‘big data’ can make big impact: Findings from a systematic review and a longitudinal case study. International Journal of Production Economics, 165, 234–246.

 

Wirtz, B. W., Weyerer, J. C., & Sturm, B. J. (2020). The impact of digital transformation on service management: Insights from the public sector. Journal of Service Management, 31(4), 637–657.

 

Piccarozzi, M., Aquilani, B., & Gatti, C. (2018). Industry 4.0 in management studies: A systematic literature review. Sustainability, 10(10), 3821.

 

Mittelstadt, B. D., Allo, P., Taddeo, M., Wachter, S., & Floridi, L. (2016). The ethics of algorithms: Mapping the debate. Big Data & Society, 3(2), 1–21.
Last updated on 26-06-2025