Università Bocconi
A Scientific Approach to Innovation Management
Università Bocconi

A Scientific Approach to Innovation Management

Taught in English

Some content may not be translated

8,120 already enrolled

Course

Gain insight into a topic and learn the fundamentals

Alfonso Gambardella
Arnaldo Camuffo
Chiara Spina

Instructors: Alfonso Gambardella

4.6

(70 reviews)

13 hours to complete
3 weeks at 4 hours a week
Flexible schedule
Learn at your own pace

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Assessments

6 quizzes

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There are 5 modules in this course

We provide a general discussion of innovation as problem-solving and we link the discuss the building blocks of the scientific approach to innovation decisions – from how to formulate the problem, to how to formulate the hypotheses and the theory, and how to test them. The whole discussion will be framed and applied to concrete managerial problems, including a discussion of the specific managerial tools that facilitate the application of a scientific approach to innovation management.

What's included

15 videos3 readings1 quiz1 discussion prompt

We provide more details about the scientific approach and we introduce probabilities to understand how and why certain decisions lead to some outcomes instead of others and how to make better decisions. We also focus on how to formulate and test hypotheses in practice, and how to interpret these tests. We finally discuss how to design and run experiments. NB: some videos may contain a downloadable database; please, download it and follow the in-video instructions

What's included

17 videos3 readings3 quizzes1 discussion prompt

We cover the basics of data analysis, beginning with the distinction between correlation and causality in the analysis of data. We also teach how to make predictions using regression analysis and link these methods to the scientific approach, showing what role these analyses play, how they help to make scientific decisions and why. We complement this with real examples of companies using data to make innovation decisions. We close by discussing how to interpret these analyses and results critically to make sure we understand what we really learn from the analyses and when, how and why we should interpret our results cautiously and critically.

What's included

8 videos3 readings1 quiz1 discussion prompt

This is s a more advanced part in which we discuss causality and provide the students with some broad exposure to big data and machine learning, and we discuss what they can do for managerial decisions.We provide a general wrap-up and conclusion of the course, including a discussion of when the scientific approach is most appropriate or has limitations. This helps to see when to apply it, or when to apply other approaches, including our own gut feelings. NB: some videos may contain a downloadable database; please, download it and follow the in-video instructions

What's included

7 videos3 readings1 quiz1 discussion prompt

What's included

1 peer review

Instructors

Instructor ratings
4.6 (18 ratings)
Alfonso Gambardella
Università Bocconi
1 Course8,120 learners
Arnaldo Camuffo
Università Bocconi
1 Course8,120 learners

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4.6

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5

Reviewed on May 13, 2024

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