Buch, Englisch, 488 Seiten, Format (B × H): 156 mm x 234 mm
Models and Advanced Quantitative Techniques for Product Pricing
Buch, Englisch, 488 Seiten, Format (B × H): 156 mm x 234 mm
ISBN: 978-1-041-19810-9
Verlag: Taylor & Francis Ltd
This updated and expanded second edition has the same theme as the first: the price, the number, someone puts on a product to help consumers decide to buy that product, comes from statistically modeling data.
Five new chapters provide a wider perspective on pricing analytics to more effectively develop elasticities and pricing strategies. This book gives readers the statistical modeling tools needed to get the number to put on a product, based on economic and statistical principles and theory. It covers elasticities, methodologies for analyzing customer choices including conjoint analysis, pricing segmentation, big data and econometric models—now with improved explanations and developments. The second edition adds discussion of three important and advanced topics: simulations for testing strategies under different conditions such as scenario analysis, AI applications for elasticity estimation and dynamic pricing, and the impacts of tariffs.
A comprehensive and essential resource for analysts—economists, statisticians, or market researchers—who must estimate the optimal price for a product or service, this book is also a helpful guide for upper-level students in analytics disciplines.
Zielgruppe
Postgraduate and Professional Practice & Development
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
- Wirtschaftswissenschaften Betriebswirtschaft Management Entscheidungsfindung
- Wirtschaftswissenschaften Betriebswirtschaft Marktforschung
- Wirtschaftswissenschaften Volkswirtschaftslehre Volkswirtschaftslehre Allgemein Ökonometrie
Weitere Infos & Material
Acknowledgements. Preface. Part I Background. 1 Introduction. 2 Elasticities – Background and Concept. 3 Elasticities – Their Use in Pricing. Part II Stated Preference Models. 4 Conjoint Analysis. 5 Discrete Choice Models. 6 MaxDiff Models. 7 Other Stated Preference Methods. Part III Price Segmentation. 8 Price Segmentation: Basic Models. 9 Price Segmentation: Advanced Models. Part IV Big Data and Econometric Models. 10 Working with Big Data. 11 Big Data Pricing Models. 12 Big Data and Nonlinear Prices. Part V Simulations and Pricing Analytics. 13 Introduction to Simulations and Pricing Analytics. 14 Stochastic Simulation Technicalities. 15 Pricing Analytics Simulations: Case Studies. Part VI Specialized Topics. 16 Tariffs and Pricing Analytics. 17 AI and Pricing Analytics. Part VII References. Part VIII Biography.
