UNDERGRADUATE PROGRAM · 4 YEARS

Business Administration (Ph.D. Turkish)

An undergraduate program equipped with an up-to-date curriculum, applied education and industry collaborations.

Language: Turkish
Degree: Doctorate
240 AKTS
Döşemealtı Campus

ABOUT THE DEPARTMENT

A strong undergraduate program in its field

The program combines a strong theoretical foundation with applied education and internship experience. Students acquire field-specific skills before graduation.

We prepare our graduates for their careers through internships, industry collaborations and international exchange programs.

CAREER OPPORTUNITIES

Broad career opportunities in the field

Our graduates can work in public institutions, the private sector, academia and international platforms, and also have the opportunity to start their own businesses through entrepreneurship.

WHY THIS DEPARTMENT?

Quality Education

We train competent graduates in their field with an up-to-date curriculum and an applied education approach.

Applied Learning

We strengthen the learning process with projects, internships and applied work that combine theory and practice.

Industry Collaborations

We prepare our students for professional life before graduation through internships, mentorship and industry partnerships.

International Experience

We offer global experience and career opportunities through Erasmus+ and exchange programs.

Year 1 · Fall 12 AKTS
Year 1 · Spring 8 AKTS
Year 2 · Fall 30 AKTS
Year 3 · Fall 30 AKTS
Year 3 · Spring 30 AKTS
Year 4 · Fall 30 AKTS
Year 4 · Spring 30 AKTS
ISD 893

Doktora Tezi-III

30.00 AKTS 0.00 Credits Turkish

Instructor: Prof. Dr. İbrahim Sani MERT

Course Objectives

The aim of this course is to enable doctoral students to advance their dissertation studies by conducting data collection, analysis, and interpretation processes in accordance with scientific standards. The course is designed to enhance students’ ability to integrate theoretical frameworks with empirical research, analyze research findings, and generate academic contributions.Additionally, the course aims to ensure that students make systematic progress toward completing their doctoral dissertations and are able to present their work at the level of academic publication quality.

Prerequisites / Corequisites

This course is designed for doctoral students who have advanced to the dissertation stage and whose dissertation proposals have been approved. Students are expected to have sufficient knowledge of research methods and statistical analysis.

Course Books / Materials / Recommended Resources

Main References:Creswell, J. W. – Research DesignHair, J. F. et al. – Multivariate Data AnalysisRecommended Readings:Recent academic journal articles in the fieldInternational peer-reviewed journalsResources on academic writing and publication processesThese materials are intended to support students in effectively conducting scientific research and producing academic contributions.

Academic Integrity and Artificial Intelligence

Full compliance with academic integrity principles is required. All academic work must be original, and all sources must be properly cited.Artificial intelligence tools may be used only for supportive purposes (e.g., literature review, data analysis support, writing suggestions). The direct use of AI-generated content without proper acknowledgment is considered a violation of academic ethics. Students are expected to clearly disclose the use of AI tools and assume full academic responsibility for their work.

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