DIGITAL TRANSFORMATION AND ARTIFICIAL INTELLIGENCE APPLICATIONS IN LOGISTICS PROGRAMME COURSE DESCRIPTION

Code	Name of the Course Unit	Semester	In-Class Hours (T+P)	Credit	ECTS Credit
ILT440	DIGITAL TRANSFORMATION AND ARTIFICIAL INTELLIGENCE APPLICATIONS IN LOGISTICS	7	3	3	7

GENERAL INFORMATION
Language of Instruction :	English
Level of the Course Unit :	BACHELOR'S DEGREE, TYY: + 6.Level, EQF-LLL: 6.Level, QF-EHEA: First Cycle
Type of the Course :	Compulsory
Mode of Delivery of the Course Unit	-
Coordinator of the Course Unit	Assist.Prof. KADİR MERSİN
Instructor(s) of the Course Unit	Assist.Prof. CAN BURAK NALBANTOĞLU
Course Prerequisite	No

OBJECTIVES AND CONTENTS
Objectives of the Course Unit:	This course aims to introduce the fundamental concepts of digital transformation and artificial intelligence applications in the logistics sector. By learning about digital technologies used in logistics processes, students will gain insights into implementing current AI solutions into logistics operations.
Contents of the Course Unit:	Basic concepts cover the importance of digital transformation in logistics, basic digital technologies and their use in logistics, big data, artificial intelligence, machine learning, smart planning, security and future trends.

KEY LEARNING OUTCOMES OF THE COURSE UNIT (On successful completion of this course unit, students/learners will or will be able to)
Define the basic concepts of digital transformation and artificial intelligence in the context of logistics.
Explain the role and importance of digital technologies in modern logistics systems.
Analyze how big data, IoT, and blockchain technologies improve supply chain visibility and efficiency.
Apply artificial intelligence and machine learning techniques to logistics problems such as demand forecasting and inventory management.
Evaluate the impact of digital transformation on logistics costs, operational efficiency, and sustainability.
Interpret real-world examples and case studies of successful digital transformation in logistics.
Develop an integrated perspective on how AI-driven tools can optimize logistics and transportation processes.

WEEKLY COURSE CONTENTS AND STUDY MATERIALS FOR PRELIMINARY & FURTHER STUDY
Week	Preparatory	Topics(Subjects)	Method
1	Reading	ntroduction to the Course – Overview of Digital Transformation and Artificial Intelligence	Lecture, Q&A
2	Reading	Importance of Digitalization in Logistics and Fundamental Concepts	Lecture, Q&A
3	Reading	Big Data and Its Applications in Logistics	Lecture, Q&A
4	Reading	Internet of Things (IoT) and Smart Logistics Applications	Lecture, Q&A
5	Reading	Blockchain Technology and Supply Chain Management	Lecture, Q&A
6	Reading	Fundamentals of Artificial Intelligence and Machine Learning	Lecture, Q&A
7	Reading	Applications of Artificial Intelligence in Demand Forecasting and Inventory Management	Lecture, Q&A
8	Reading	Automation and Robotics Technologies in Warehouse Management	Lecture, Q&A
9	Reading	Route Optimization and AI Applications in Transportation	Lecture, Q&A
10	-	MID-TERM EXAM	-
11	Reading	Autonomous Vehicles and Drone-based Transportation	Lecture, Q&A
12	Reading	Impacts of Digital Transformation on Logistics Costs and Efficiency	Lecture, Q&A
13	Reading	Artificial Intelligence Solutions for Sustainable Logistics	Lecture, Q&A
14	Reading	Case Studies: Successful Examples of Digital Transformation	Lecture, Q&A, Problem Solving
15	Reading	General Review	Problem Solving
16	-	FINAL EXAM	-
17	-	FINAL EXAM	-

SOURCE MATERIALS & RECOMMENDED READING
Tao, F., Gadekallu, T. R., Kumar, V., Akberdina, V., & Kuzmin, E. (2025). Artificial Intelligence and Digital Transformation. Springer.
Alok, S. (2025). AI-Driven Digital Transformation in Logistics and Supply Chain. Notion Press

ASSESSMENT
Assessment & Grading of In-Term Activities	Number of Activities	Degree of Contribution (%)	Description	Examination Method
Mid-Term Exam	1	30		Classical Exam
Short Exam	1	20
Final Exam	1	50		Classical Exam
TOTAL	3	100

Level of Contribution
0	1	2	3	4	5

KNOWLEDGE
Theoretical
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	To explain the basic concepts and theories associated with the field of Logistics Management						5

KNOWLEDGE
Factual
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	To relate concepts and cases in the field of Logistics Management with other fields in Social Sciences					4
2	To make scientific and interdisciplinary research about the cases in the field					4

SKILLS
Cognitive
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	To draw conceptual and theoretical connections between past and present trade and logistics – transportation procedures and to make forecasts for the future.						5

SKILLS
Practical
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	To make literature review for analyzing cases in the field of Logistics Management and to use this information for personal studies.						5
2	To use the latest technology for making descriptive and exploratory research and to use this information for personal studies.						5

OCCUPATIONAL
Autonomy & Responsibility
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	To conduct a field-specific study individually and to complete it with discipline and responsibility.					4
2	To assume duties and responsibilities in a team work as leader or team member and to fulfil them flawlessly.						5

OCCUPATIONAL
Learning to Learn
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	To analyze data and findings in the field of Logistics Management with respect to cause-effect relations and critical perspective.						5
2	To identify gaps in the theory and practice of Logistics Management and to offer solutions for each.					4
3	To develop ideas as to how to use the information related to the field of Logistics Management in professional life.						5

OCCUPATIONAL
Communication & Social
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	To convey information related with the field of Logistics Management by using effective presentation and communication techniques.						5
2	To use field-specific information for creation of various projects, activities and social responsibility programmes in the field of Logistics Management.					4
3	To conduct literature review, follow the recent developments and produce written and oral works in a foreign language.						5

OCCUPATIONAL
Occupational and/or Vocational
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	To respect social, cultural, scientific and ethical norms and values in the processing and dissemination of data.						5
2	To follow latest developments in the field and direct personal studies accordingly within the framework of the lifelong learning principle.						5

WORKLOAD & ECTS CREDITS OF THE COURSE UNIT
Workload for Learning & Teaching Activities
Type of the Learning Activites	Learning Activities (# of week)	Duration (hours, h)	Workload (h)
Lecture & In-Class Activities	14	3	42
Preliminary & Further Study	13	3	39
Land Surveying	0	0	0
Group Work	0	0	0
Laboratory	0	0	0
Reading	0	0	0
Assignment (Homework)	0	0	0
Project Work	0	0	0
Seminar	0	0	0
Internship	0	0	0
Technical Visit	0	0	0
Web Based Learning	0	0	0
Implementation/Application/Practice	0	0	0
Practice at a workplace	0	0	0
Occupational Activity	0	0	0
Social Activity	0	0	0
Thesis Work	0	0	0
Field Study	0	0	0
Report Writing	0	0	0
Final Exam	1	1	1
Preparation for the Final Exam	7	8	56
Mid-Term Exam	1	1	1
Preparation for the Mid-Term Exam	5	7	35
Short Exam	0	0	0
Preparation for the Short Exam	0	0	0
TOTAL	41	0	174