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A core aim of the course is to help students develop intuition about the necessary skills and knowledge to identify research problem, develop and use an actionable research proposal. This course utilizes both theoretical and practical exercises to develop student’s skills for conducting field research for business entities. These skills include developing and defining research problem statements; developing research objectives; utilizing the appropriate design; the use of secondary and primary data collection and instruments. Collecting original qualitative and quantitative data; sampling design and methods; hypotheses testing; data analysis and interpretation.At the end of the course students should be able to: • Learn the overall research process from inception to report • Use theory and previous research to create research questions and hypotheses • Understand ethical issues in business and management research • Identify, explain, and apply the basic concepts of research, such as variables, sampling, reliability, and validity • Identify primary characteristics of quantitative research and qualitative research • Construct a coherent research proposal • Interpret research findings

WEEK 1: Introduction to Scientific Research WEEK 2: Research Approaches and Data Collection Methods WEEK 3: Research Approaches and Data Collection Methods(cont) WEEK 4a: Research Ideas to Hypothesis Formulation and Data Type 4b: Ethics in Scientific Research WEEK 5: Measurement Techniques and Sampling Methods WEEK 6: The Survey as Non-Experimental Research WEEK 7: Qualitative and Mixed Methods Research WEEK 8: Midterm Exam WEEK 9: Quantitative Research Data- Descriptive Statistics WEEK 10: Quantitative Research Data- Inferential Statistics WEEK 11: Quantitative Research Data- Structural equation modeling WEEK 12: Practical’s with JAMOVI and SmartPLS software packages WEEK 13: Practical’s with JAMOVI and SmartPLS software packages WEEK 14: Practical’s with JAMOVI and SmartPLS software package

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Research Methods, Design, and Analysis by Larry B Christensen, Lisa A. Turner, and R. Burke Johnson. 12th International Edition (Pearson)

·        Plagiarism will not be tolerated under any circumstances.·        No late submissions will be accepted, except in very rare cases (e.g., illness withmedical report, legal etc.).·        Students who are absent on an exam day must provide a legitimate excuse before the exam. Failure to do so will result in a penalty of a grade of 0·        Any form of academic dishonesty (e.g., plagiarism, intellectual property theft – including materials taken from the Internet, having others do your assignments, failing to participate in group work, etc.) will result in a penalty.·        Students are expected to uphold the highest standards of academic integrity when using artificial intelligence (AI) tools. While AI resources may be used to support learning, all submitted work must reflect the student’s own understanding and effort.·        Unauthorized use of AI to generate or complete assignments, or failure to properly acknowledge such use when permitted, constitutes academic misconduct.