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完成時間(小時)

完成時間大約為14 小時

建議:6 hours/week...
可選語言

英語(English)

字幕:英語(English)
100% 在線

100% 在線

立即開始,按照自己的計劃學習。
可靈活調整截止日期

可靈活調整截止日期

根據您的日程表重置截止日期。
完成時間(小時)

完成時間大約為14 小時

建議:6 hours/week...
可選語言

英語(English)

字幕:英語(English)

教學大綱 - 您將從這門課程中學到什麼

1
完成時間(小時)
完成時間為 3 小時

THE INNOVATION DECISION

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....
Reading
14 個視頻 (總計 106 分鐘), 3 個閱讀材料, 1 個測驗
Video14 個視頻
Operation efficiency vs strategic efficiency3分鐘
What data can and cannot do4分鐘
Strategic efficiency4分鐘
What does the scientific approach do: the Galilean manager5分鐘
Inkdome case5分鐘
What is innovation7分鐘
The structure of the innovation decision15分鐘
Risk and Uncertainty11分鐘
Type I and type II errors in innovation decisions6分鐘
Interactive tour of the Museum of Failure3分鐘
The Building blocks: Theory, Hypotheses, Tests, Analysis12分鐘
Formulate and apply theories to managerial problems11分鐘
Tools: business model canvas and other tools8分鐘
Reading3 個閱讀材料
Readings & Videos10分鐘
Recap slides10分鐘
Background material (extended slides)10分鐘
Quiz1 個練習
Week 110分鐘
2
完成時間(小時)
完成時間為 4 小時

THEORY AND DATA FOR INNOVATION MANAGEMENT

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...
Reading
16 個視頻 (總計 140 分鐘), 3 個閱讀材料, 3 個測驗
Video16 個視頻
Conditional probabilities and the Bayes Theorem12分鐘
The scientific approach15分鐘
Using the organization to set the decision rule7分鐘
How to derive hypotheses from a theory6分鐘
Hypotheses and their context [p values don’t always matter]5分鐘
Cases4分鐘
Design and logic of hypothesis testing (download the attached datasets)12分鐘
The use of experiments in innovation management11分鐘
Randomized Control Trials7分鐘
Split and multivariate tests12分鐘
Quasi Experimental Design6分鐘
Innovation metrics11分鐘
Metrics validity and reliability5分鐘
Metrics validity7分鐘
Metrics reliability8分鐘
Reading3 個閱讀材料
Readings & Videos10分鐘
Recap slides10分鐘
Background material (extended slides)10分鐘
Quiz3 個練習
Exercise 115分鐘
Exercise 215分鐘
Week 210分鐘
3
完成時間(小時)
完成時間為 2 小時

DATA ANALYSIS

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....
Reading
6 個視頻 (總計 47 分鐘), 3 個閱讀材料, 1 個測驗
Video6 個視頻
Regression analysis: Theory11分鐘
Regression analysi: Application9分鐘
Using data to answer important questions at Google3分鐘
How firms and startups can gather and analyze data to test hypotheses6分鐘
Reflection critical evaluation5分鐘
Reading3 個閱讀材料
Readings & Videos10分鐘
Recap slides10分鐘
Background material (extended slides)10分鐘
Quiz1 個練習
Week 310分鐘
4
完成時間(小時)
完成時間為 2 小時

ADVANCED TOOLS FOR INNOVATION MANAGEMENT DECISIONS

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...
Reading
7 個視頻 (總計 53 分鐘), 3 個閱讀材料, 1 個測驗
Video7 個視頻
Difference-in-difference approach: Examples (download the attached datasets)9分鐘
Instrumental variables: Theory (download the attached datasets)9分鐘
Instrumental variables: Examples (download the attached datasets)5分鐘
Data science vs causal links4分鐘
Machine learning for innovation management decisions5分鐘
Summary, conclusions, limitations of the scientific approach8分鐘
Reading3 個閱讀材料
Readings & Videos10分鐘
Recap slides10分鐘
Background material (extended slides)10分鐘
Quiz1 個練習
Week 410分鐘

講師

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Alfonso Gambardella

Professor of Corporate Management
Management and Technology
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Arnaldo Camuffo

Professor of Business Organization
Management and Technology
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Chiara Spina

Lecturer and Ph.D. Candidate
Management and Technology

關於 博科尼大学

Our ambition is to develop students' potential and foster knowledge in Business, Economics and Law through innovative learning and research activities in a multicultural environment. Bocconi is a community that constantly innovates teaching and learning technologies and that strongly believes in the power of life-long learning and networking. Now available online....

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