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Subject Description Form Subject Code ISE5010 Subject Title Decision Support Modeling for Courier and Freight Management Credit Value 3 Level 5 Pre-requisite/Corequisite/Exclusion Nil Objectives This subject provides students with Intended Learning Outcomes Subject Synopsis/ Indicative Syllabus 1. the concepts and experience in various modern decision support models with applications in courier and freight management; 2. the knowledge of scenario articulation values, strategy formulation, and case examples. Upon completion of the subject, students will be able to a. apply the basic skills and concepts of various decision support models in business and logistics environments; b. recognize scenario articulation values, strategy formulation and implementation; c. solve logistics problems using tools and methodologies associated with decision support theories and applications. 1. Introduction to Decision Support Models Decision support models compared with other intelligent expert systems; Pivot tables and expert systems with applications; Multidimensional database and data analysis approaches; Online analytical processing; Architecture and components of knowledge-based systems; Rule-based reasoning principles and applications. 2. Development of Organizational Strategies Organizational strategies for supporting ES, KBS, and DSS; Management involvement in DSS; Executive information system to support decision making; Tools for DSS. 3. Case Studies of Decision Support Systems Application systems in courier and freight forwarding activities; Production scheduling; Optimization examples in business and logistics settings. 18.11.2013 Teaching/Learning Methodology A mixture of lectures, tutorial exercises, and case studies are used to deliver the various topics in this subject, some of which are covered in a problem-based format where the learning objectives are enhanced. Other topics are covered through directed study to enhance the students’ “learning to learn” ability. Some case studies, largely based on consultancy experience, are used to integrate these topics and thus demonstrate to students how the various techniques are interrelated and how they apply in real-life situations. Teaching/Learning Methodologies Lecture Assessment Methods in Alignment with Intended Learning Outcomes Intended Subject Learning Outcomes to be assessed a b c Case Study Project Specific assessment methods/tasks % weighting Intended subject learning outcomes to be assessed a b 1. Assignments 20% 2. Project 30% 3. Case studies 20% 4. Test 30% Total 100% c The test and project are designed to measure students' depth of knowledge on the issues of decision support modeling for courier and freight management. Assignments are designed to reflect students' understanding of the concepts and skills taught on various decision support models in business and logistics environments. Case studies are designed to appraise students' recommendations in applying the skills taught, tools, and methodologies associated with decision support theories and applications to solve logistics problems. Student Study Effort Expected Class contact: Lecture 18 Hrs. Case studies/Seminars 12 Hrs. Laboratory/Tutorial 9 Hrs. Other student study effort: 18.11.2013 Preparation for case studies and assignments 33 Hrs. Self-revision for project and test Total student study effort Reading List and References 18.11.2013 34 Hrs. 106 Hrs. 1. Akerkar, R, A and Sajja, P, S. 2010, Knowledge-Based Systems, Jones and Bartlett, Priti Srinivas 2. Turban, Efraim and Aronson, and JE. 2009, Decision Support Systems and Intelligent Systems, Prentice Hall, Upper Saddle River, N.J. 3. Lewis, J. 2008, Mastering Project Management: Applying Advanced Concepts to Systems Thinking, Control & Evaluation, Resource Allocation, 2nd edn, McGraw-Hill, New York 4. Phillips-Wren, G, Ichalkaranje, Nikhil and Lakhmi, C, J. 2008, Intelligent Decision Making: An AI-Based Approach, Springer-Verlag, Berlin, Heidelberg 5. Turban, E and Aronson, J, E. 2005, Decision Support Systems and Intelligent Systems, 7th edn, Pearson Education, Upper Saddle River, N.J. 6. Moore, J, H and Weatherford, L, R. 2001, Decision Modeling with Microsoft Excel, 6th edn, Prentice Hall, Upper Saddle River, N.J.