BUS601 Qualitative Research Methods in Business
BUS601 Qualitative Research Methods in Business
Syllabus | International University of Sarajevo - Last Update on Mar 03, 2026
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Department of Economics and Management
Hamza Smajić
Course Lecturer
Course Objectives
This course is designed to introduce students to qualitative research methods concepts and to provide tools in analyzing and solving qualitative research methods problems that students will face in the academic research and contemporary business world.
Learning Outcomes
After successful completion of the course, the student will be able to:
Course Materials
Required Textbook
Michael D. Myers (2013). Qualitative Research in Business & Management (2nd Ed). Sage Publications.
Additional Literature
De Sordi, J. O. (2024). Qualitative Research Methods in Business: Techniques for Data Collection and Analysis. Cham, Switzerland: Palgrave Macmillan. Denzin, N. K., & Lincoln, Y. S. (Eds.). (2017). The SAGE handbook of qualitative research (5th ed.). Thousand Oaks, CA: Sage Publications. Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). Sage Publications.Teaching Methods
Lecturers
Class discussions
Practical application of the learned theory.
Weekly Topics
| Week | Topic | Readings / References |
|---|---|---|
| 1 | Introduction to the course | |
| 2 | Introduction to Qualitative Research/Assignment | PART I |
| 3 | Assignment | PART II |
| 4 | Fundamental Concepts of Qualitative Research/Assignment | |
| 5 | Qualitative Research Methods/Assignment | PART III |
| 6 | Presentation of the Research Topic | |
| 7 | Research Proposal Discussion/Assignment | |
| 8 | Midterm Exam | |
| 9 | Research Proposal Submission | |
| 10 | Data Collection Techniques/Assignment | PART IV |
| 11 | Data Collection/Assignment | |
| 12 | Data Collection/Assignment | |
| 13 | Analyzing Qualitative Data | PART V |
| 14 | Writing Up and Publishing | PART VI |
| 15 | Final Paper Submission |
Course Schedule (All Sections)
| Section | Type | Day 1 | Venue 1 | Day 2 | Venue 2 |
|---|---|---|---|---|---|
| BUS601.1 | Course | Tuesday 17:00 - 19:50 | B F1.2 - Class/ECON Lab | - | - |
Office Hours & Room
| Day | Time | Office | Notes |
|---|---|---|---|
| Tuesday | 14:00 - 17:00 | B F1.7 | |
| Thursday | 13:00 - 15:00 | B F1.7 |
Assessment Methods and Criteria
Assessment Components
Final Paper
AI: Not AllowedAlignment with Learning Outcomes : 1 2 3 4 5
Research Proposal
AI: Not AllowedAlignment with Learning Outcomes : 1 2 3 4 5
Midterm Exam
AI: Not AllowedAlignment with Learning Outcomes : 1 2 3 4 5
Assignments
AI: Consult InstructorAlignment with Learning Outcomes : 1 2 3 4 5
IUS Grading System
| Grading Scale | IUS Grading System | IUS Coeff. | Letter (B&H) | Numerical (B&H) |
|---|---|---|---|---|
| 0 - 44 | F | 0 | F | 5 |
| 45 - 54 | E | 1 | ||
| 55 - 64 | C | 2 | E | 6 |
| 65 - 69 | C+ | 2.3 | D | 7 |
| 70 -74 | B- | 2.7 | ||
| 75 - 79 | B | 3 | C | 8 |
| 80 - 84 | B+ | 3.3 | ||
| 85 - 94 | A- | 3.7 | B | 9 |
| 95 - 100 | A | 4 | A | 10 |
Late Work Policy
Information about late submission policies will be shared during class and posted in this section. Please check back for official guidelines.
ECTS Credit Calculation
📚 Student Workload
This 6 ECTS credit course corresponds to 150 hours of total student workload, distributed as follows:
Reading
50 hours ⏳ (10 week × 5 h)
Collecting and analyzing data
24 hours ⏳ (2 week × 12 h)
Writing the research paper
60 hours ⏳ (12 week × 5 h)
Assignments
16 hours ⏳ (8 week × 2 h)
150 Total Workload Hours
6 ECTS Credits
Course Policies
Academic Integrity
All work submitted must be your own. Plagiarism, cheating, or any form of academic dishonesty will result in disciplinary action according to university policies. When in doubt about citation practices, consult the instructor.
Attendance Policy
Students are expected to adhere to the attendance requirements as outlined in the International University of Sarajevo Study Rules and Regulations. Excessive absences, whether excused or unexcused, may impact academic performance and eligibility for assessment. Mandatory sessions (e.g., labs, workshops) require attendance unless formally exempted. For detailed policies on absences, documentation, and penalties, please refer to the official university regulations.
Technology & AI Policy
Laptops/tablets may be used for note-taking only during lectures. Phones should be silenced and put away during all class sessions. Audio/video recording requires prior permission from the instructor.
Artificial Intelligence (AI) Usage: The use of AI tools (e.g., ChatGPT, Copilot, Gemini) varies by assessment component. Please refer to the AI usage indicator next to each assessment item in the Assessment Methods and Criteria section above. Submitting AI-generated content as your own work, where AI is not explicitly allowed, constitutes an academic integrity violation.
Communication Policy
All course-related communication should occur through official university channels (institutional email or SIS). Emails should include [BUS601] in the subject line.
Academic Quality Assurance Policy
Course Academic Quality Assurance is achieved through Semester Student Survey. At the end of each academic year, the institution of higher education is obliged to evaluate work of the academic staff, or the success of realization of the curricula.
Learning Tips
Be prepared to contribute thoughtfully during class discussions, labs, or collaborative work. Active participation deepens understanding and encourages critical thinking.
Complete assigned readings or prep materials before class. Take notes, highlight key ideas, and jot down questions. Aim to grasp core concepts and their applications—not just facts.
Use course frameworks or methodologies to analyze problems, case studies, or projects. Begin early to allow time for reflection and refinement. Seek feedback to improve your work.
Don’t hesitate to reach out when something is unclear. Use office hours, discussion boards, or peer networks to clarify concepts and stay on track.
Syllabus Last Updated on Mar 03, 2026 | International University of Sarajevo
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Referencing Curricula Print this page
| Course Code | Course Title | Weekly Hours* | ECTS | Weekly Class Schedule | ||||||
| T | P | |||||||||
| BUS601 | Qualitative Research Methods in Business | 3 | 0 | 6 | Tue 17:00 - 19:50 | |||||
| Prerequisite | None | It is a prerequisite to | - | |||||||
| Lecturer | Hamza Smajić | Office Hours / Room / Phone | Tuesday: 14:00-17:00 Thursday: 13:00-15:00 |
|||||||
| hsmajic@ius.edu.ba | ||||||||||
| Assistant | Assistant E-mail | |||||||||
| Course Objectives | This course is designed to introduce students to qualitative research methods concepts and to provide tools in analyzing and solving qualitative research methods problems that students will face in the academic research and contemporary business world. |
|||||||||
| Textbook | Michael D. Myers (2013). Qualitative Research in Business & Management (2nd Ed). Sage Publications. | |||||||||
| Additional Literature |
|
|||||||||
| Learning Outcomes | After successful completion of the course, the student will be able to: | |||||||||
|
||||||||||
| Teaching Methods | Lecturers, class discussions, practical application of the learned theory. | |||||||||
| Teaching Method Delivery | Face-to-face | Teaching Method Delivery Notes | ||||||||
| WEEK | TOPIC | REFERENCE | ||||||||
| Week 1 | Introduction to the course | |||||||||
| Week 2 | Introduction to Qualitative Research/Assignment | PART I | ||||||||
| Week 3 | Assignment | PART II | ||||||||
| Week 4 | Fundamental Concepts of Qualitative Research/Assignment | |||||||||
| Week 5 | Qualitative Research Methods/Assignment | PART III | ||||||||
| Week 6 | Presentation of the Research Topic | |||||||||
| Week 7 | Research Proposal Discussion/Assignment | |||||||||
| Week 8 | Midterm Exam | |||||||||
| Week 9 | Research Proposal Submission | |||||||||
| Week 10 | Data Collection Techniques/Assignment | PART IV | ||||||||
| Week 11 | Data Collection/Assignment | |||||||||
| Week 12 | Data Collection/Assignment | |||||||||
| Week 13 | Analyzing Qualitative Data | PART V | ||||||||
| Week 14 | Writing Up and Publishing | PART VI | ||||||||
| Week 15 | Final Paper Submission | |||||||||
| Assessment Methods and Criteria | Evaluation Tool | Quantity | Weight | Alignment with LOs | AI Usage |
| Final Paper | 1 | 30 | 1-5 | Not Allowed | |
| Semester Evaluation Components | |||||
| Research Proposal | 1 | 20 | 1-5 | Not Allowed | |
| Midterm Exam | 1 | 20 | 1-5 | Not Allowed | |
| Assignments | 8 | 30 | 1-5 | Consult Instructor | |
| *** ECTS Credit Calculation *** | |||||
| Activity | Hours | Weeks | Student Workload Hours | Activity | Hours | Weeks | Student Workload Hours | |||
| Reading | 5 | 10 | 50 | Collecting and analyzing data | 12 | 2 | 24 | |||
| Writing the research paper | 5 | 12 | 60 | Assignments | 2 | 8 | 16 | |||
| Total Workload Hours = | 150 | |||||||||
| *T= Teaching, P= Practice | ECTS Credit = | 6 | ||||||||
| Course Academic Quality Assurance: Semester Student Survey | Last Update Date: 03/03/2026 | |||||||||