COURSE UNIT TITLE

: TRADE INTELLIGENCE MANAGEMENT

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
DIŞ 5038 TRADE INTELLIGENCE MANAGEMENT ELECTIVE 3 0 0 4

Offered By

Foreign Trade (English)

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR CANAN MADRAN

Offered to

Foreign Trade (English)

Course Objective

The course aims to provide students with a solid background in business intelligence by considering theoretical concepts and practical applications for trading.

Learning Outcomes of the Course Unit

1   Have a knowledge understanding of the conditions, tendencies, and applications of information systems and technologies.
2   Have a knowledge understanding of the new web technologies and various applications of intelligent agents for trading.
3   Understand the basic definitions, concepts and processes used in developing and managing data warehouses and datamarts
4   Describe major business analytics methods and tools such as artificial intelligence, online analytical processing (OLAP) and data mining.
5   Describe how computer systems facilitate groupwork, communication and collaboration in intraorganizations and interorganizations.
6   Use computer applications to apply trade intelligence for making decision in a competitive international trade environment with a focus on overseas operations.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to the emerging field of intelligence management Understand the need for computerized support of managerial decision making, Describe the trade intelligence methodology and concepts and relate them to DSS, Understand the major issues in implementing trade intelligence.
2 Business information systems and trade intelligence Transaction Processing systems, Management Information Systems, Decision support systems, Group Decision Support system, Executive Support systems, Enterprise systems, Knowledge management systems, Expert systems, Customer relationship management systems, Supply chain management systems, integration of information systems and trade intelligence.
3 Describe business analytics and its importance to organizations, major business analytics methods and tools, Understand the basic definitions and concepts of data warehouses and datamarts, Describe the processes used in developing and managing data warehouses and datamarts, Explain data warehousing operations, Explain the role of data warehouses in decision support.
4 Data analysis to discover the intelligence Describe How online analytical processing (OLAP), data visualization, and multidimensionality can improve decision making.
5 Data analysis to discover the intelligence Describe data mining and list its objectives and benefits, Understand different purposes and applications of data mining, Data mining concepts and applications (data,text,web), Data mining techniques and tools, Operation research and optimization, Dashboards as a user interface.
6 Mid-Term
7 Understand the concept and evolution of artificial intelligence, Understand the importance of knowledge in decision support, Describe the concept and evolution of rule-based expert systems (ES), Understand machine-learning concepts, Developing neural network-based systems, Learn the concepts and applications of case-based systems,
8 Understand the concept and power of intelligent agents and Web intelligence. The concept of representing semantic knowledge over the Internet. Various applications of intelligent agents for trading (info agents, buyer agents, seller agents, intermediary agents.....). Learn the concept of recommendation systems over the Internet.
9 Understand the basic concepts and processes of groupwork, communication, and collaboration. Describe how computer systems facilitate communication and collaboration in intraorganizations and interorganizations. (SOAP, SaaS, UDDI, WSML). E-negotiation systems, Negotiation Support Systems, Negotiation Decision Support Systems
10 Defining/distinguishing personalization and customization, Empowering personalization and customization in B2B transaction with information, Modelling for personalization and customization, e-catalogue aggregators, intermediary firms providing e-catalogues, Semantic web, XML standards to exchange data among different database systems based on e-catalogues.
11 Web page design issues, Tracking Cookies and clickstream behaviour, Adware Spyware and privacy issues, mobile services to track customers behaviours, Geographical information systems, Collaboration with other business partners, Institutions, banks, credit card associations and so on.
12 Implementation Project Presentations
13 Implementation Project Presentations
14 Genel Review

Recomended or Required Reading

Business Intelligence: A Managerial Approach. Efraim Turban, Ramesh Sharda, Jay E. Aronson, and David King. 2007, Prentice Hall.

Planned Learning Activities and Teaching Methods

The course consists of lectures, class discussions, computer applications and implementation projects.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 STT TERM WORK (SEMESTER)
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE MTE * 0.30 + STT * 0.30 + FIN* 0.40
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + STT * 0.30 + RST* 0.40


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

1. Exams will measure the ability to identify and apply business intelligence in the context of trading operations ve problems. Each exam will cover course materials and include questions on lecture materials, and additional items covered in class meetings.

2. Students are required to complete an Implementation Project which allows them to apply the information systems and business intelligence to a topic of personal or professional interest in competitive international trade environment.

3. The implementation project will be graded by the instructor. Project will be evaluated for such factors as apparent understanding of the topic, originality of treatment and discussion, accuracy of results, comprehensiveness of the report s content and depth of the analysis, clarity and mechanics of presentation such as organization, format, punctuation, grammar, and quality of exhibits and charts.

4. By completing the project, students will improve analytical and communication skills through identifying and applying information systems and business intelligence to facilitate the real trade operations and problems. Project reports and presentations will enable students improve their competency using the language of information technologies to communicate the results.

Language of Instruction

English

Course Policies and Rules

1. It is obligatory to attend at least 70% of the classes.
2. Violations of Plagiarism of any kind will result in disciplinary steps being taken.
3. Absence will not be considered an excuse for submitting homework assignments late.
4. Delayed project reports will suffer grade decay equivalent to one letter grade per day late.

Contact Details for the Lecturer(s)

ferkan.kaplanseren@deu.edu.tr, aysun.kapucugil@deu.edu.tr

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 13 3 39
Preparations before/after weekly lectures 13 2 26
Preparation for midterm exam 1 10 10
Preparation for final exam 1 15 15
Preparing assignments 1 10 10
Midterm 1 1,5 2
Final 1 1,5 2
TOTAL WORKLOAD (hours) 104

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.1555
LO.25555
LO.3555
LO.4555
LO.5555
LO.6555

CONTACT INFORMATION
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Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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