<span>Innovation Diffusion Models</span><p><span>Understand innovation diffusion models and their role in business success</span></p><p><span>Innovation diffusion models are statistical models that predict the medium- and long-term sales performance of new products on a market. They account for nume
Innovation Diffusion Models: Theory and Practice
โ Scribed by Mariangela Guidolin
- Publisher
- Wiley
- Year
- 2023
- Tongue
- English
- Leaves
- 207
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
Innovation Diffusion Models
Understand innovation diffusion models and their role in business success
Innovation diffusion models are statistical models that predict the medium- and long-term sales performance of new products on a market. They account for numerous factors that contribute to the life cycle of a new product and are subject to continuous reassessment as markets transform and the business world becomes more complex. In a modern market environment where product life cycles are becoming ever shorter, the latest innovation diffusion models are essential for businesses looking to perfect their decision-making processes.
Innovation Diffusion Models: Theory and Practice provides a comprehensive and up-to-date guide to these models and their potential to impact product development. It focuses on the latest product diffusion models, which combine time series analysis with nonlinear regression techniques to create increasingly refined predictions. Its combination of mathematical theory and business practice makes it an indispensable tool across many sectors of industry and commerce.
Innovation Diffusion Models readers will also find:
- Real-world examples demonstrating the kinds of data sets generated by new product growth models and their potential applications
- Discussion of the factors underlying the decision to select a given growth model for a particular product
- Clear, detailed explanation of each model's explanatory ability
Innovation Diffusion Models is an essential volume for practitioners in any field of industry or commerce, as well as for graduate students and researchers in business and finance.
โฆ Table of Contents
fmatter
Title Page
Copyright
Contents
List of Figures
List of Tables
About the Author
Preface
Acknowledgments
Acronyms
About the Companion Website
Introduction
ch1
1.1 Basic Concepts and Definitions
1.1.1 Innovation
1.1.2 Innovation Diffusion
1.1.3 Innovation Diffusion Models
References
ch2
2.1 Introduction
2.2 Bass Model: Theory
2.2.1 ClosedโForm Solution
2.3 Model Estimation
2.3.1 Goodness of Fit
2.4 The Bass Model: Case Studies
2.4.1 Model Fit
2.4.2 Apple iPhone
2.4.3 RIM Blackberry
2.4.4 Wind Energy Consumption in Denmark
2.5 Recap
References
ch3
3.1 Introduction
3.2 Generalized Bass Model: Theory
3.2.1 ClosedโForm Solution
3.2.2 Structured Shocks
3.2.2.1 Exponential Shock
3.2.2.2 Rectangular Shock
3.2.2.3 More Complex Shocks
3.3 Generalized Bass Model: Case Studies
3.3.1 Model Fit
3.3.2 Apple iPhone
3.3.3 Apple Mac
3.4 Recap
References
ch4
4.1 Introduction
4.2 Dynamic Market Potential: Theory
4.2.1 ClosedโForm Solution
4.3 GGM
4.3.1 Specification of m(t) in the GGM
4.3.2 Communication and Adoption in the GGM
4.4 Generalizations of the GGM
4.4.1 GGM with Structured Shocks
4.4.2 GGM with Deterministic Seasonality
4.5 A Dynamic Market Potential Model with Network Externalities
4.6 GGM: Case Studies
4.6.1 Model Fit
4.6.2 Apple iPhone
4.6.3 Apple iPod
4.6.4 Samsung Smartphones
4.7 Recap
References
ch5
5.1 Introduction
5.2 ARMAX Refinement: Theory
5.2.1 ARMAX Models
5.3 ARMAX Refinement: Case Studies
5.3.1 Netflix Subscriptions
5.3.2 Apple iPod
5.4 Recap
References
ch6
6.1 Introduction
6.2 UCRCD Model: Theory
6.2.1 More General Models in Competition
6.2.1.1 LotkaโVolterra with Churn Model, LVch
6.2.1.2 Competition Dynamic Market Potential
6.2.1.3 Competition Between Three Products, UCTT
6.3 UCRCD Model: Case Studies
6.3.1 Model Fit
6.3.2 Denmark
6.3.3 Australia
6.4 Recap
References
ch7
7.1 Introduction
7.2 Nonlinear Least Squares
7.2.1 GaussโNewton Method
7.2.2 LevenbergโMarquardt Method
7.3 Confidence Intervals and Hypothesis Testing
7.3.1 Exact Inference
7.3.2 Asymptotic Inference and Linear Approximations
7.3.2.1 Prediction Intervals
References
ch8
8.1 Introduction
8.2 Sales of Smartphones
8.2.1 Recap
8.3 Music Industry in the US
8.3.1 Recap
8.4 Revenues of a Company
8.4.1 Recap
8.5 The Life Cycle of Tablets
8.5.1 Recap
8.6 Energy Transition in Germany
8.6.1 Coal
8.6.2 Gas
8.6.3 Nuclear
8.6.4 Renewables
8.6.5 Nuclear and Renewables
8.6.6 Coal, Nuclear, and Renewables
8.6.7 Recap
8.7 Growth of Video Conferencing
8.7.1 Share Price
8.7.2 Google Searches
8.7.3 Recap
8.8 Diffusion of a Scientific Paper
8.8.1 Recap
8.9 Diffusion of Internet Usage
8.9.1 Recap
References
ch9
9.1 Statistical Modeling
9.2 To Explain or to Predict
9.2.1 To Explain
9.2.2 To Predict
9.3 Conclusion
References
ref
index
๐ SIMILAR VOLUMES
<p><p>Effective knowing and learning for vocational purposes must take account of the wide range of variables that impact on knowledge formation and that promote learning. In light of those many variables, the formal sector of technical and vocational education and training (TVET) must constantly as
<p><p>Effective knowing and learning for vocational purposes must take account of the wide range of variables that impact on knowledge formation and that promote learning. In light of those many variables, the formal sector of technical and vocational education and training (TVET) must constantly as