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Service Operations Management MHR105

Course description for study year 2021-2022. Please note that changes may occur.

Course code




Credits (ECTS)


Semester tution start


Number of semesters


Exam semester


Language of instruction


Learning outcome

A candidate who has completed the course should have the following learning outcomes defined in terms of knowledge, skills, and competence:


After completing this course, the student has:

  • advanced knowledge of literature and research in operation management in service organizations, based on a stochastic understanding of data.
  • in-depth knowledge of the organization of management information flows during operation.
  • in-depth knowledge of structuring information flows according to organizational level as well as the horizon of planning.
  • Thorough knowledge of how to build large database structures on service business operational data to enable organizational learning, both nationally and internationally.
  • training on how to build professional decision support systems according to a changing service business framework in a contemporary international context.


After completing this course, the student can:

  • analyze existing theories in order to construct modern service management tools to be applied to middle large service company stuctures, tools that are compatible to national as well as international service management practice.
  • apply business model analysis, modelling, formulatiion and simulation, identify performance parameters identification.
  • carry out a plan for stochastic formulated variable based on estalished data structures, and construct dynamic reporting frameworks.

General Competence:

After completing this course, the student can:

  • apply the principles of integrated database construction and machine learning models, and computer added learning.
  • apply his/her knowledge and skills in new areas in order to carry out advanced assignments and projects.

Students investigate and analyse business systems, systems parameter identification, systems formulation and modelling. The working mechanisms of different models are tested using integrated stochastic simulation and variance analysis; formulating the planned actions for future management cycles. Performance registration and measuring systems are integrated into this, especially the link between control measures and the model variables and parameters. An essential part in these processes are the information distribution methods, distribution tools and the speed of the management processes.

Data recording systems, integrated database construction, operations and query are important parts in these operations. This goes for computer aided learning, machine learning models and prediction methods, as well. Risk management in service operations are an important part of business service performance. Reporting framework, output and structure are integrated into the management models.

Parts of the content are communicated using computational essays. These essays gives a succinct representation of high-level abstract ideas in service operations expressed as human computational thinking. Computers are used for actual precise computation and transfer for knowledge. In parallel lectures, workshops and training in writing, and reading computer code in the Wolfram Language and application of Mathematica are offered.

Required prerequisite knowledge
Recommended prerequisites
Knowlegde in business economics equivalent to bachelor level is preferred.

Home exams and written exam

Form of assessment Weight Duration Marks Aid
Home exams 3/10 A - F
Written exam 7/10 4 Hours A - F

3 individual test arranged are given as home exams during the semester accounting for  30% of the final grade. Grading A-F. The individual home exams has a duration for 7 days for each home exam. Written 4 hour school exam accounts for 70% of the final grade. Grading A-F.            

Course teacher(s)
Course coordinator: Dag Osmundsen
Method of work
This course adopts student-centered learning based on lectures, case-studies and discussions. Concepts are explained by using computational essays. 
Course assessment
The course will be assessed and evaluated according to the University of Stavanger' administrative quality system.
Overlapping courses
Course Reduction (SP)
Service Management Models (MHR290) 10
The syllabus can be found in Leganto