DECISION SUPPORT SYSTEMS

Course Description

This course provides an in-depth study of Decision Support Systems (DSS) and their role in enhancing managerial decision-making. It explores the fundamental components of DSS, including mathematical models, databases, and user interfaces, and demonstrates how they support semi-structured problem-solving in business contexts. Students will learn methods of decision-making, reasoning, and inferencing, along with the application of operations research tools and optimization techniques. The course also introduces expert systems, knowledge acquisition, and model manipulation as part of DSS development. Through hands-on projects and practical case studies, students will design and implement DSS solutions, gaining both technical and managerial perspectives on improving organizational decision-making.

DECISION SUPPORT SYSTEMS

Evaluation Tools (Active Term)

No evaluation items have been defined.

Course outcomes

1. 01 The student should be able to identify the main concepts of decision support systems (DSS)
2. 02 The student should be able to recognize the components of DSS and the main participants in the decision-making process
3. 03 To be able to identify the the various models and their analysis
4. 04 To be able to develop DSS and its life cycle
5. 05 To recognize the role of intelligent systems in DSS

Course Syllabus

Reference Books & Course Materials

1. 01 George M. Markas, 2011, "Decision support systems in the 21st century", 2nd edition, Pearson education

Learning Outcomes

1. L01 The student should be able to identify the main concepts of decision support systems (DSS)
2. L02 The student should be able to recognize the components of DSS and the main participants in the decision-making process
3. L03 To be able to identify the the various models and their analysis
4. L04 To be able to develop DSS and its life cycle
5. L05 To recognize the role of intelligent systems in DSS

Program Outcomes

1. Demonstrate advanced knowledge of core concepts and theoretical frameworks in Management Information Systems, and apply them to develop innovative models that reflect current advancements in the field.
2. Analyze complex organizational problems and design integrated information systems solutions by applying advanced MIS knowledge and synthesizing multiple theoretical perspectives.
3. Develop and manage database systems and data-driven applications that ensure effective storage, retrieval, and use of organizational data in real-world contexts.
4. Utilize data analytics, business intelligence tools, and data visualization techniques to extract actionable insights and support strategic, data-driven decision-making.
5. Evaluate and apply emerging technologies such as AI, IoT, and Blockchain to drive digital transformation, enhance organizational performance, and formulate original research inquiries.
6. Conduct independent and collaborative research using appropriate methodologies, and communicate findings effectively through scholarly writing and presentations suited to diverse audiences.
7. dentify and address ethical, legal, and societal implications in the research, development, and use of information technologies, adhering to scientific and professional standards.
8. Collaborate effectively in multidisciplinary teams and demonstrate leadership in addressing complex technology-driven challenges.
9. Apply project management methodologies and tools to plan, execute, and monitor IT projects within organizational settings.
10. Develop and integrate information systems that align with organizational goals and strategies, supporting innovation and sustainable growth.
11. Perform comprehensive systems analysis and design, including requirements gathering, modeling, prototyping, and evaluating enterprise system architectures such as ERP, CRM, and SCM.
12. Assess and mitigate organizational information security risks by applying appropriate principles, technologies, and best practices in cybersecurity.

Po-Lo Matrix