Code: DT305
ECTS: 6
Semester: 3rd
School: School of Engineering [UA]
Academic Unit: Department of Product & Systems Design Engineering, University of the Aegean [UA]
Responsible Institution: UA
This course delves into the field of network economics, exploring how the structure of relationships and connections between individuals, firms, or even countries influences economic outcomes. We will analyse how social and economic networks affect behaviours, decisions, and ultimately, market dynamics.
Key concepts and topics covered include:
- Fundamentals of Network Theory: We’ll introduce the basic concepts of graph theory and social network analysis, including network topology, centrality measures, and network formation models.
- Network Effects: Explore the economic implications of network effects, where the value of a good or service increases with the number of users. Analyse direct and indirect network effects, network externalities, and their impact on market competition.
- Game Theory on Networks: Study how strategic interactions are influenced by network structures. Learn about concepts like network games, diffusion of information and innovation, and the role of social influence in decision-making.
- Information Economics in Networks: Examine how information flows through networks and affects economic outcomes and analyse information asymmetry.
- Market Competition and Network Structure: Explore how market competition is shaped by the underlying network structure. Analyse models of competition in industries with network effects, platform markets, and the role of network centrality in determining market power.
- Applications of Network Economics: Apply the theoretical framework to real-world scenarios, including social media platforms, telecommunications networks, financial markets, and innovation diffusion.
Design Studio 2 develops and evaluates a digital transformation solution and examines how it could be implemented in its intended setting. It combines supervised development, evaluation and management planning, building on the project framing and concept work coordinated with DT304 during the same semester.
Development planning: review of the project brief and evidence; prioritisation of functionality; selection of architecture, tools and data; task allocation and iteration planning. The chosen fidelity must enable the main design claims to be examined within the course workload.
Prototype implementation: integration of interaction, content, data and relevant intelligent or other digital technologies; version and decision records; attention to accessibility, privacy, security and intellectual property.
Evaluation: definition of questions and success criteria; selection of appropriate user, expert, technical or organisational evaluation methods; ethical collection of evidence; analysis of results; identification of limitations and iterative improvement.
Implementation and management: resource and skills needs, stakeholder engagement, adoption and change management, deployment and maintenance considerations, risks, sustainability and indicators of expected value. Cost estimates and claims about benefits are justified and their assumptions are stated.
Studio practice: supervised critiques, an intensive integration and review workshop, peer feedback and a final demonstration. Students submit a project portfolio combining the solution, evaluation evidence, implementation plan and individual reflection.
DT305 assesses development, evaluation and implementation planning. A project shared with DT304 retains separate milestones, assessment criteria and evidence for each course.
- Search, analysis and synthesis of information using appropriate technology.
- Independent work and collaboration in interdisciplinary and international teams.
- Problem framing, creative thinking and evidence-based decision-making.
- Project planning, documentation and management of time and resources.
- Respect for diversity, accessibility and different stakeholder perspectives.
- Social, professional and ethical responsibility, including responsible use of data and AI.
- Constructive criticism, self-criticism and reflection on design decisions.
Upon successful completion of the course, students will be able to:
Knowledge
- Explain the relationship between a design proposal, a working prototype and an implementation plan for digital transformation.
- Compare methods for evaluating the usability, usefulness, technical performance and organisational feasibility of a digital solution.
- Identify requirements for deployment, maintenance, adoption and responsible use of the proposed solution.
Skills
- Develop and document a prototype or demonstrator at an appropriate level of technical fidelity using justified tools and methods.
- Design and conduct an evaluation suited to the project, analyse the evidence and use the findings to refine the solution.
- Develop an implementation plan addressing stakeholders, resources, milestones, risks and indicators of expected value.
- Present and defend the final solution and its limitations through a demonstration and a documented project portfolio.
Competences
- Integrate design, technical and management decisions in an accountable development process.
- Manage collaboration and individual responsibilities, incorporating feedback and documenting the evolution of the project.
- Exercise critical judgement about claims of effectiveness, innovation and impact in light of the available evidence.
