Course 2025-2026 a.y.

The seminar explores these challenges:

• how to design decision-making processes that can overcome obstacles when introducing innovations to solve collective problems;
• how to make strategic decisions in uncertain situations characterized by scarce information and high complexity.

To involve participants in a close-to-earth experience and support the debate, after a theoretical introduction, an educational digital game (P-Cube).

Following these objectives, the seminar will be divided into two parts.

In the first part, students will:

• Receive a theoretical introduction, providing a framework for analyzing policy decision-making processes.
• Apply this framework to real scenarios by engaging in missions within the P-Cube educational digital game.
• Participate in a debriefing session to discuss the learning objectives of the P-Cube missions. 

In the second part of the course, students will explore the Theory-Based framework, emphasizing its practical relevance in tackling complex policymaking and business challenges. This section is structured as follows:

1. Theoretical Foundations: students will examine the cognitive and perceptual foundations of strategic decisions, differentiating theory-based approaches from traditional methods. Key concepts such as attributes, models, and the theory development process will be introduced, along with experimental strategies to test theories. 
2. Case Studies in Theory-Based Decisions: real world cases, including Stockholm’s congestion pricing and Singapore’s housing policies, will be analysed to illustrate how theories are developed, tested, and adapted in diverse strategic contexts.
3. Integration and Application: students will engage in comparative case analysis and participate in a theory development workshop, applying the framework to strategic scenarios.  

• Understand the different models of policy decision-making, their key concepts, and the criticisms to the rational-comprehensive model. 
• Analyze policy decision-making processes using specific theoretical frameworks, knowing how to assess whether and how a causal link can be established between two attributes of a problem. 
• Apply a scientific approach to solving real-world problems.
• Identify the strategies useful to cope with the complexity of decision-making processes and to overcome the barriers to policy innovations. 

• Recognize the characteristics of the real, empirical contexts in which policies are designed and decided. 
• Understand the complexity of policy decision-making in the real world and why incremental solutions are in general the results of these processes.  
• Select the strategies useful to overcome decisional stalemates and problems among actors in empirical decisional processes to reach non-incremental decisions. 
• Develop well-founded, robust theories for a given problem, then test and compare them to identify the most effective course of action. 

• Lectures
• Practical Exercises
• Interaction/Gamification

• Cases will be discussed to identify theoretical concepts from real-life situations and to introduce the missions of the digital serious game.
• The missions of the educational digital game have the goal to introduce students to real-life situations and to apply theoretical concepts in these contexts. 
• The participant will be asked to put him/herself in the shoes of a policy innovator who tries to steer a proposal through the complexities of public policy making. In this journey he/she will meet a large number of characters who in some cases will fight against innovation and in others will help. He/she will be confronted with a series of choices between different alternatives to complete the different missions.
• The seminar aims to offer a learning experience that does not try to simplify the complexities of public policy making, nor to provide ready-to-use solutions to decisional problems. On the contrary it will stimulate the participants to analyze every single case and to derive first-hand experience of the different elements which compose the conceptual framework developed by literature and that represents the more realistic description of how public policies and innovative services come about. 

The seminar provides for in-person participation only.

Full attendance counts as a passed exam.

To be considered attending student you must attend at least 75% of the scheduled classes. Failing to do so will entail an integrative test or an exam. 

• Partial attendance (between 50-74% of the hours) implies an integrative test.
• Complete absence (-50% of the hours) implies an exam (closed-ended and open ended questions).
• For students that need to do the test or the exam, me and prof. Pandey will provide the materials after the seminar.

Students will be required to form groups to discuss cases and participate in playing the missions of the education digital game P-Cube, including the debriefing phases.

Assessment of non-attending students is entirely based on an individual written test. The exam probes the student’s understanding of the concepts inherent to policy decision-making and the student’s ability to apply the learned framework through the analysis of case studies based on real policy decision-making processes.

• Slides used during the course. 

• Bruno Dente. 2014. Understanding Policy Decision. Cham: Springer. 

• Giancarlo Vecchi. 2021. “Public Policy and Decision-Making Processes. Introducing the Rationale of the P-Cube Digital Educational Game.” In https://www.p-cube-project.eu/literature-reviews/ 
• Camuffo, Gambardella & Pignataro (2024) "Theory-Driven Strategic Management Decisions".
• Camuffo et al (2026): "Beyond Blackboxes: Designing and Testing Agentic AI Systems for Strategy"
• Eliasson (2014) "The Stockholm Congestion Charges: An Overview".
• Börjesson et al. (2012) "The Stockholm Congestion Charges—5 Years On".
• Phang (2007) "The Singapore Model of Housing and the Welfare State". 
• World Bank (2016) "The Singapore Success Story". 
• Other material will be assigned at course inception. 

• Bruno Dente. 2014. Understanding Policy Decision. Cham: Springer. 

• Giancarlo Vecchi. 2021. “Public Policy and Decision-Making Processes. Introducing the Rationale of the P-Cube Digital Educational Game.” In https://www.p-cube-project.eu/literature-reviews/ 
• Slides used during the seminar
• Felin & Zenger (2017) "The Theory-Based View: Economic Actors as Theorists".
• Camuffo, Gambardella & Pignataro (2024) "Theory-Driven Strategic Management Decisions".
• Camuffo et al (2026): "Beyond Blackboxes: Designing and Testing Agentic AI Systems for Strategy"
• Eliasson (2014) "The Stockholm Congestion Charges: An Overview".
• Börjesson et al. (2012) "The Stockholm Congestion Charges—5 Years On".
• Phang (2007) "The Singapore Model of Housing and the Welfare State".
• World Bank (2016) "The Singapore Success Story".