A good knowledge in Statistics/ Econometrics
The aims of the course are: i) to make the students familiar with the radically new technologies such as robotics, artificial intelligence, machine learning, additive manufacturing, and internet of things that characterises the digital transformation; ii) to deepen the knowledge about the sources of the digital transformation highlighting how changes in techno-economics paradigms take place; iii) to provide the students an in-depth knowledge of the mechanisms behind the industrial change caused by the digital transformation, and of the impacts of such radical change on the organization of production, the labour market, the economic policies and the organisation of the market. Indeed, unlike in previous industrial revolutions, automation extends to cognitive and mental tasks, which redefines the balance between job-destruction and job-creation and the skill-bias of automation; iv) to provide the knowledge base necessary for independent qualified analyses – and economic/management implementation - of processes and strategies related to industrial and technical change on different systems levels (at the level of firms, industrial sectors, and the economic system as a whole). The new paradigm calls for a new set of conditions for firms to survive, compete and succeed, calling for a similar rethinking of our common approach to industrial organisation and dynamics. Institutions have a central role in directing and ruling this new industrial paradigm with policies that sometimes have to face completely new aspects (for example the use and the governance of Data).
The course is constituted by lectures and group discussions on specific topics treated in the required literature. The main topics are: *Introduction. What is Digital Trasformation, and why it is important to study such a topic. *Digital Trasformation as technology: an introduction to radical and revolutionary innovation. *A basic coverage of the economics of digitalisation. *Digital Transformations and Platforms. *Governing Digital Transformations. *Addressing Dominance, and the Digital Policies .*Artificial Intelligence and the use and governance of Data
The course is held partly in the form of formal lectures given by the professor, and partly in the form of students’ presentations and joint discussion of some assignments on topics of interest and possibly on data analysis concerning such topics. Student’s assignments are done by groups of normally 2, maximum 3 persons. The teaching includes the training to team and individual work practices for the preparation and the communication of the papers and data analysis. The students are trained to use bibliographic references and quotations, to search for relevant sources, to search for real data on public reliable datasets and to check unclear content. Students are also asked to answer theoretical and applied research questions using real data and statistics/econometrics techniques. Class presentations challenge the students to confront the communication dynamics, both as actors and as spectators, taking the chance to evaluate the strength and the weaknesses of the performances.
The final evaluation is given by:
1.The evaluation of some assignments done by groups of 2 (maximum 3) students and their presentation in class.
Assignments’ evaluation asses the students’ capabilities of: *using properly real data at the firm level; *understanding correctly the research questions; *positioning the topic in the correct strand of the literature; *using the correct statistical/econometrics techniques to answer the research question.
Students' presentations assess: *The correct understanding of the topic. *The identification of the key issues and of the priority order. *The capacity to summarise the relevant content. *The strength and systematic storytelling; *The effectiveness of the slides.
The evaluation of students’ presentations and assignments counts the 50% of the final grade and it takes into consideration the active participation of the student during the lectures and other students’ presentations.
2. The written exam at the end of the course concerns the contents of the lectures and the required readings. It counts 50% of the final grade. The written exam consists of open questions and/or multiple-choice questions. The written exam assesses: *The correct learning of the concepts of the programme's topics. *The accuracy of the answers and the capacity of summarising the relevant concepts. *The capacity of understanding and explaining complex issues. *The effectiveness of the written exposition. Students should get a sufficient grade (18/30) in order to pass the exam.
The students who are not able to give the class presentation/assignments should prepare for the exam more articles than those assigned to students that are able to present their team work in class. They will be evaluated according to the written exam (see above point 2), and an oral exam, which will follow straight on in the same session if the students get a sufficient grade (55% correct) in the written exam. The oral exam focuses on the standard programme and on the additional readings.
If teaching is given in mixed or remote (on-line) mode, some changes may be introduced compared to what was stated in the syllabus to make the course and exams fit also according to these modalities.
The students are invited to enroll in the course on the e-learning platform, Moodle, where the slide, the supplementary material and all the up-dates will be published.