What the programme entails
Webinar on Urban Digital Transformation & Innovation
Learn more about the master track content directly from Dr Sofia Pagliarin and Dr Beatriz Calzada — the programme coordinators themselves! Watch this video to discover more about the programme content, and how digital innovation and transformation impact urban socio-economic development and governance.
The master track provides participants with the expertise to become urban managers specialising in the economics and governance of urban digital transformation and innovation.
The Urban Digital Transformation & Innovation: Governance and Economics of Cities programme is a master track within the MSc in Urban Management and Development. The master track focusses on digital innovation and transformation and their impact on urban economic development and governance. Organised in three modules, the programme draws on the fields of economics, technology and innovation, governance and development, socio-technology and technological transitions, social and economic geography, and urban planning.
Across the three modules, students discuss both socio-economic and socio-technological transformation. The participants will learn how to critically evaluate the concept of ‘smart cities’ and analyse the opportunities and challenges that the current global digitalisation trends create in the domains of industrial production, employment, and sustainability. Basics on useful skills, such as big data analytics and machine learning, will be taught. The effects of digital transformations on governance and economics are illustrated with examples of smart and micro-mobility, smart grids, new forms of production and energy transition, future-proof public transportation, and labour markets, among others. The programme pays equal attention to the complex process of governing digital innovation, and its role in creating or reducing inequalities in cities. Students will also have the opportunity to focus further on both overarching topics of the track: economic development or algorithmic governance.
Students in the economic development group will focus on economic geography, knowledge hubs, technological diffusion, territorial development, agglomeration economics, entrepreneurship, and labour markets.
Students in the algorithmic governance group will focus on opportunities and disruptions caused by digitalization and how governments may respond to this: digital infrastructure and algorithmic governance, big data, and how this impacts more traditional forms of governance.
It is important to note that the programme does not have a technical orientation but focuses on governance and economics. It will introduce students to those techniques and exemplify their use in the context of governance and economics of digital transformations.
How is your year organized?
The first block shares courses on urban complexity, governance & participation, and data analytics with the other master tracks. In the second block, most courses will be track-specific and you will be working more closely with your master track peers. The third and last block will be entirely dedicated to your thesis. It will further guide you in writing your thesis proposal on a topic relevant to your master track.
Exam Regulations
2024-2025
Academic Calendar
2024-2025
Programme Curriculum
Block 1 - September to January
The students will explore key concepts in urban governance, corruption, planning, participation, and urban finances through a blend of theoretical and practical learning. Through an interdisciplinary lens, and by discussing case studies from both the Global North and the Global South, in this course students will explore theoretical/conceptual frameworks, indicators, and strategies aimed at fostering inclusive, participatory governance in urban settings.
With over half of the population living in urban areas, rising to 70% in 2050, it is of ever-increasing importance to understand how cities work and evolve. Complex and interrelated economic, social, physical, and environmental processes constantly transform cities. Students will learn to view cities as Complex Adaptive Systems, providing insights into their dynamic, self-organizing nature and varying development paths.
With over half of the world's population now living in urban areas, cities are growing larger and more complex. This course addresses this complexity through two modules:
- Quantitative Data Analysis: Students will learn to manage, visualize, and analyze various urban data sources to address research questions and make informed decisions.
- Qualitative Data Collection and Analysis: Students will gain skills in collecting and interpreting in-depth qualitative data to understand the intricate dynamics and experiences within urban environments.
Blocks 2 - January to April
The module on governance focusses on analytical approaches that describe and explain how technological innovations exit the controlled environment of ‘labs’ to become (at times) the mainstream technologies we use in our everyday life. The module will present and discuss the various factors and actors that contribute to the development and selection of technology that can affect its widespread adoption. Students will also critically evaluate the concept of ‘smart cities’ and the challenges and opportunities of digitalisation for the governance of cities. Particular attention will be given to the opportunities and challenges of big and open data usage in urban decision-making in different cities and regions (i.e., algorithmic governance).
The module on economics will present the main theoretical approaches to analyse the emergence and impacts of digital transformation and innovation at different spatial levels, from neighbourhoods to cities and cities to countries. The module on economics will also introduce and analyse the opportunities and challenges that the current global digitalisation trends create in the domains of industrial production, employment, and sustainability. These opportunities and challenges will be specifically analysed in the context of urban and regional settings.
This module introduces students to methodological skills that are highly sought after in urban professionals. These methodological skills prepare students to analyse and evaluate digital technologies and innovation in cities and regions. In understanding the basics of key methodological techniques, students will not only be able to correctly apply them but also to choose the most suitable approach to adopt for carrying out a meaningful analysis according to the specific issue at hand.
The module includes an introduction to selected quantitative methods and offers students a good starting point to develop these skills further. The master track covers the following skills:
- Econometrics
- Big data analytics and machine learning
- Causality and its link to policy evaluation
The Master's programme at IHS includes a significant focus on designing and implementing academic research in urban studies. The Research Design (RD) course is essential for guiding students in creating academic research within the social sciences and independently developing their Master’s thesis. Alongside the two Urban Data Analytics courses (UDA 1: quantitative and UDA 2: qualitative), the RD course equips students with the necessary skills and knowledge to design, implement, and compose a research project that meets the standards of a Master’s thesis.
Geographic Information Systems, or GIS, allow to capture and analyze geographic data and spatial information easily and efficiently. Already decades ago their usefulness and popularity prompted companies as well as the open source community to develop high-level GIS software solutions, applicable to many disciplines and publicly accessible (QGIS is ahigh-level open-source tool, used in this course). GIS tools include plenty of possibilities to process, analyze and visualize quantitative as well as qualitative information typically used in research in the social sciences. This course will explain frequently used GIS techniques and demonstrate their applicability across typical cases covered in the UMD program. With lectures, examples and point-and-click instructions, you will learn how to create new insights for your research by solving geographic problems with GIS tools.
Effective urban resilience depends on strategically aligning city capacities with risks, and community needs through a comprehensive resilience strategy. This hands-on workshop equips future urban planners, policymakers, and stakeholders with practical skills to navigate the complexities in resilience strategy development, fostering sustainable urban development and proactive resilience-building efforts.
This workshop comprises two sessions based on the City Resilience Framework of the Resilient Cities Network. In the first session, participants will work on assessing urban risks (acute shocks and chronic stresses) in a selected city. They will prioritize short-term and long-term threats and categorize them by severity of impact and likelihood of occurrence. In the second session, participants will develop a resilience diagnosis based on the 12 guiding principles, drivers, and actions of the “Resilience Wheel”. The diagnostic helps identify the city’s existing resources or strengths to tackle the identified threats. Participants will then develop specific strategies that tackle the most threats with the least actions and investment. Participants will work in teams, and present their processes, strategies, and conclusions at the end of the workshop.
Block 3 - April to August
The research proposal is linked and complementary to the Research Design (RD) course. In the RD course participants are guided to design academic research within the social sciences and to develop their research proposal.
The RD course will teach participants how to develop the problem statement, research questions, research objectives their theoretical framework.
Designing and implementing academic research in the field of urban studies is a major component of the master's programme at IHS. During this period students will write their master thesis on their chosen topic guided by a supervisor.
Learning objectives
- Understand the innovative and disruptive aspects of technologies in societies, economies, and cities
- Apply key theories to concrete case studies to explain the process of socio-technological development, selection, and diffusion, with a focus on socio-technological transitions
- Critically evaluate ‘smart cities’ and other digital innovations by identifying socio-economic opportunities and challenges in cities and regions
- Analyse the opportunities and challenges of (big) data usage in urban decision-making in different cities and regions
- Analyse the opportunities and challenges presented by the global digitalization trend in the context of production, employment, and sustainability faced by different urban and regional settings
- Apply fundamental economic theory principles in the analysis of digital transformation and innovation on various scales: from neighbourhoods to cities and from cities to countries
- Apply theories and concepts from contemporary literature to practical examples
- Apply selected quantitative, qualitative, and comparative methods for analysing and evaluating digital technologies and innovation in cities and regions
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Enrolment Office
- Email address
- courseinquiries@ihs.nl