Course Topics
The course proposes an approach to understand different phenomena using a "complexity" lens and understand how current behaviors and patterns emerge. The course tackles the complexity of adaptive systems in the context of business (e.g., innovation and entrepreneurship). The lecturer will introduce the students to ABM thinking and to NetLogo as a simulation environment to describe and analyze open innovation phenomena.

Teaching format
In-Person "Mixed" sessions with theoretical tractation and laboratory applications of the topics covered

Educational objectives
Knowledge and understanding The student acquires advanced knowledge and understanding of models for new product development and innovation management within companies. I/we acquire advanced knowledge and understanding of business analysis tools and solutions for the development of innovations and organisational knowledge I/we acquire advanced knowledge and understanding of innovation economics models and systems for regional innovation development The student acquires knowledge of quantitative models for the formulation of forecasts necessary to guide management decisions and to predict the life cycle of a product and a sector Ability to apply knowledge and understanding ability to acquire and select relevant information to frame cases of innovation (product, service, social, managerial organisational), also different from the contexts studied ability to assess the potential of an innovation within existing enterprises, with respect to the creation of a new enterprise (e.g. intrapreneurship, open innovation, etc.). Autonomy of judgement Acquire the ability to analyse complex entrepreneurial issues, such as the elaboration and evaluation of a business project (business plan) or the development of a new product. Acquire the ability to make predictions, such as analysing the future consequences of entrepreneurial, managerial and operational choices. Autonomy of judgement is developed in the training activities carried out for the preparation of the thesis, as well as in the exercises that accompany the lectures and that involve group discussions and the comparison of individual analyses carried out by students in preparation for the lecture. Communication skills Acquire the ability to describe and communicate in an intercultural context, in a clear and precise manner, problematic situations typical of the management of a new enterprise and the development of innovation, such as, for example, the conditions for the validation of a problem or solution, the prospects and risks associated with a business model or an innovation project. The development of communication competences assumes heterogeneous situations such as, for example, the presence of internal stakeholders (e.g. colleagues, managers, owners), or external stakeholders (e.g. potential investors, suppliers and other business partners) and the ability to sustain an adversarial process. The achievement of these objectives is assessed in the course of the training activities already mentioned, as well as in the discussion of the final thesis. Learning ability Acquire the ability to study independently, to prepare summaries. Acquire the ability to identify thematic connections and to establish relationships between different cases and contexts of analysis Acquire the ability to frame a new problem systematically and to generate appropriate taxonomies. Acquire the ability to develop general models from the phenomena studied.

Additional educational objectives and learning outcomes
This course will provide knowledge and understanding of complex adaptive systems and their properties, and how patterns are emerging in systems. In the context of innovation and entrepreneurship, emerging patterns are related to innovation. Students will be introduced to agent-based modeling via the NetLogo program, which is a widely used, arguably easy software with which they can further simulate and explore complex adaptive systems.

Assessment
Written exam with three “open-answer questions about the topics covered during the course.

Evaluation criteria
The written exam will consist of three open-answer questions and aims at checking the knowledge of the topic and of the models covered in the course. Clarity of the exposition is also evaluated.

Required readings

·      Wilensky, U., Rand W. (2015). An Introduction to Agent-Based Modeling: Modeling Natural, Social, and Engineered Complex Systems with Netlogo. The MIT Press. (selected chapters);

Supplementary readings

Optional readings:

·      Holland, J.H., 2014. Complexity: A very short introduction. Oxford;

·      Mitchell, M., 2009. Complexity: A guided tour. Oxford University Press.

Further information
No exam for non-attending students.