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A Scientific Approach to Innovation Management
Coursera
Course
Unknown

A Scientific Approach to Innovation Management

Università Bocconi

Learn to assess feasibility of innovative ideas through problem-framing and rigorous data analysis, aiding entrepreneurs and managers in strategic decision-making.

Unknown5 weeksEnglish11,041 enrolled

About this Course

How can innovators understand if their idea is worth developing and pursuing? In this course, we lay out a systematic process to make strategic decisions about innovative product or services that will help entrepreneurs, managers and innovators to avoid common pitfalls. We teach students to assess the feasibility of an innovative idea through problem-framing techniques and rigorous data analysis labelled ‘a scientific approach’. The course is highly interactive and includes exercises and real-world applications. We will also show the implications of a scientific approach to innovation management through a wide range of examples and case studies. This video is part of a project that has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Grant agreement No. 101021061)

What You'll Learn

  • Assess feasibility of innovative ideas using problem-framing techniques
  • Apply rigorous data analysis for strategic decision-making
  • Use scientific approach in innovation management to avoid common pitfalls

Prerequisites

  • No prerequisite required. Basic notions of probability and statistics might facilitate learning

Instructors

A

Alfonso Gambardella

Professor of Corporate Management

A

Arnaldo Camuffo

Professor of Business Organization

C

Chiara Spina

Assistant Professor

Topics

Business Strategy
Business
Data Analysis
Data Science
Statistical Analysis
Correlation Analysis
Probability
Regression Analysis
Data-Driven Decision-Making
Machine Learning

Course Info

PlatformCoursera
LevelUnknown
PacingUnknown
PriceFree

Skills

استراتيجية الأعمال
الأعمال
تحليل البيانات
علوم البيانات
التحليل الإحصائي
تحليل الترابط
الاحتمالات
تحليل الانحدار
Data-Driven Decision-Making
Machine Learning

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