MBA581 Advanced Business Research Methods
Syllabus | International University of Sarajevo - Last Update on Jan 01, 2026
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Management
Emil Knezović
Course Lecturer
Course Objectives
This course is designed to provide students with in-depth knowledge and skills regarding research methods in the business where students will develop skills needed to plan, organize, and undertake a business research project by using both quantitative and qualitative research methods.
Learning Outcomes
After successful completion of the course, the student will be able to:
Course Materials
Required Textbook
Hair, Jr., J. F., Page, M., & Brunsveld, N. (2020). Business Research Methods. Routledge.
Additional Literature
Saunders, M., Lewis, P., and Thornhill, A. (2019). Research Methods for Business Students. Pearson. Creswell, J.W. (2015). Educational Research: Planning, Conducting, and Evaluating Quantitative and Qualitative Research. Pearson. Any of the above-mentioned books is useful for this course. Besides, earlier versions are applicable.Teaching Methods
The methods include lectures (which may involve power point presentation
Video and audio aids)
Student presentations
Projects and class discussions.
Weekly Topics
| Week | Topic | Readings / References |
|---|---|---|
| 1 | The research process | Chapters 1 and 2 |
| 2 | Problem, literature, and purpose of the study | Chapters 4 and 5 |
| 3 | Research design: a qualitative approach | Chapters 6-10 |
| 4 | Research design: a quantitative approach | Chapters 6-10 |
| 5 | Presenting a research topic | |
| 6 | Interim exam 1 | |
| 7 | Qualitative data analysis: content, thematic, and narrative approaches | Chapter 11 |
| 8 | Research proposal | |
| 9 | Sharpening the proposal: Peer dialogue and feedback | |
| 10 | Quantitative data analysis: Understanding the data | Chapter 12 |
| 11 | Quantitative data analysis: Pre-testing and data validation | Special readings |
| 12 | Quantitative data analysis: Hypothesis testing and interpretation | Chapters 13 and 14 |
| 13 | Quantitative data analysis: Key findings and final insights | Special readings |
| 14 | Reporting and presenting research | |
| 15 | Interim exam 2 | Chapter 16 |
Course Schedule (All Sections)
| Section | Type | Day 1 | Venue 1 | Day 2 | Venue 2 |
|---|---|---|---|---|---|
| MBA581.1 | Course | Wednesday 17:00 - 19:50 | B F1.35 FBA Conference Room | Monday 17:00 - 20:50 | B F1.25 Computer Lab |
Office Hours & Room
| Day | Time | Office | Notes |
|---|---|---|---|
| Wednesday | 12:00 - 17:00 | B F1.28 |
Assessment Methods and Criteria
Assessment Components
Final paper
AI: Not AllowedAlignment with Learning Outcomes : 1 2 3 4 5 6
Research proposal
AI: Not AllowedAlignment with Learning Outcomes : 1 2 3
Interim exam
AI: Not AllowedAlignment with Learning Outcomes : 1 2 3 4 5 6
Classwork
AI: Not AllowedAlignment with Learning Outcomes : 1 2 3 4 5 6
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:
Lecture Hours
45 hours ⏳ (15 week × 3 h)
Home Study
15 hours ⏳ (15 week × 1 h)
Assignments
32 hours ⏳ (8 week × 4 h)
Research proposal
10 hours ⏳ (1 week × 10 h)
Interim exam
18 hours ⏳ (2 week × 9 h)
Final paper
30 hours ⏳ (1 week × 30 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 [MBA581] 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 Jan 01, 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 | |||||||||
| MBA581 | Advanced Business Research Methods | 3 | 0 | 6 | Wednesday 17:00-19:50 | |||||
| Prerequisite | None | It is a prerequisite to | - | |||||||
| Lecturer | Emil Knezović | Office Hours / Room / Phone | Wednesday: 12:00-17:00 |
|||||||
| eknezovic@ius.edu.ba | ||||||||||
| Assistant | Assistant E-mail | |||||||||
| Course Objectives | This course is designed to provide students with in-depth knowledge and skills regarding research methods in the business where students will develop skills needed to plan, organize, and undertake a business research project by using both quantitative and qualitative research methods. | |||||||||
| Textbook | Hair, Jr., J. F., Page, M., & Brunsveld, N. (2020). Business Research Methods. Routledge. | |||||||||
| Additional Literature |
|
|||||||||
| Learning Outcomes | After successful completion of the course, the student will be able to: | |||||||||
|
||||||||||
| Teaching Methods | The methods include lectures (which may involve power point presentation, video and audio aids), student presentations, projects and class discussions. | |||||||||
| Teaching Method Delivery | Face-to-face | Teaching Method Delivery Notes | ||||||||
| WEEK | TOPIC | REFERENCE | ||||||||
| Week 1 | The research process | Chapters 1 and 2 | ||||||||
| Week 2 | Problem, literature, and purpose of the study | Chapters 4 and 5 | ||||||||
| Week 3 | Research design: a qualitative approach | Chapters 6-10 | ||||||||
| Week 4 | Research design: a quantitative approach | Chapters 6-10 | ||||||||
| Week 5 | Presenting a research topic | |||||||||
| Week 6 | Interim exam 1 | |||||||||
| Week 7 | Qualitative data analysis: content, thematic, and narrative approaches | Chapter 11 | ||||||||
| Week 8 | Research proposal | |||||||||
| Week 9 | Sharpening the proposal: Peer dialogue and feedback | |||||||||
| Week 10 | Quantitative data analysis: Understanding the data | Chapter 12 | ||||||||
| Week 11 | Quantitative data analysis: Pre-testing and data validation | Special readings | ||||||||
| Week 12 | Quantitative data analysis: Hypothesis testing and interpretation | Chapters 13 and 14 | ||||||||
| Week 13 | Quantitative data analysis: Key findings and final insights | Special readings | ||||||||
| Week 14 | Reporting and presenting research | |||||||||
| Week 15 | Interim exam 2 | Chapter 16 | ||||||||
| Assessment Methods and Criteria | Evaluation Tool | Quantity | Weight | Alignment with LOs | AI Usage |
| Final paper | 1 | 35 | 1-6 | Not Allowed | |
| Semester Evaluation Components | |||||
| Research proposal | 1 | 15 | 1-3 | Not Allowed | |
| Interim exam | 2 | 30 | 1-6 | Not Allowed | |
| Classwork | 1 | 20 | 1-6 | Not Allowed | |
| *** ECTS Credit Calculation *** | |||||
| Activity | Hours | Weeks | Student Workload Hours | Activity | Hours | Weeks | Student Workload Hours | |||
| Lecture Hours | 3 | 15 | 45 | Home Study | 1 | 15 | 15 | |||
| Assignments | 4 | 8 | 32 | Research proposal | 10 | 1 | 10 | |||
| Interim exam | 9 | 2 | 18 | Final paper | 30 | 1 | 30 | |||
| Total Workload Hours = | 150 | |||||||||
| *T= Teaching, P= Practice | ECTS Credit = | 6 | ||||||||
| Course Academic Quality Assurance: Semester Student Survey | Last Update Date: 29/01/2026 | |||||||||