ENBIS-19 Pre-Conference Event: Joint ECAS-ENBIS 1-Day Summer Course1 September 2019; 09:30 – 18:30
This 1-day course is a joint initiative from ENBIS and ECAS (ecas.fenstats.eu), which provides courses since 1987 in special areas of statistics both for researchers and teachers for universities and professionals in the industry.
New Product Growth Models: Theory, Practice, and a Look to the Future.
Sunday, 1st September 2019, 9:30-13:30, Room Dudich
Mariangela Guidolin, Department of Statistical Sciences, University of Padua, Italy
google scholar: https://scholar.google.it/citations?user=tOh7UTUAAAAJ&hl=it
General aim of the course
Main puropose of this tutorial is to provide an introduction to the most known new product growth models (also called innovation diffusion models), used to describe and forecast the evolution in time of sales of new products. In most cases, commercial products are characterized by a finite life cycle, which follows a nonlinear path, namely birth, growth, maturity, and decline. In this context, traditional time series framework such as ARIMA models do not prove a satisfactory choice. Quantitative marketing has played a central role in the development of new product diffusion models. The statistical techniques involved in model estimation combine time series analysis with nonlinear regression techniques.
The key objectives of the course are:
- to describe the main mathematical features of the models, illustrating the meaning of the parameters from the marketing point of view;
- to present and discuss the statistical aspects involved in model estimation and selection;
- to show and discuss forecasting and explanatory ability of the proposed models with real-data applications in several industrial and commercial sectors;
- to propose some ideas for future achievements in research and commercial practice.
- New product forecasting: marketing problems and quantitative models.
- New product life cycle as an empirical generalization: the Bass model.
- Accounting for marketing mix actions: the Generalized Bass model.
- Accounting for the strength of word-of-mouth, seasonality and competition: some advanced models.
- Statistical inference for nonlinear models.
- Forecasting for new product growth models.
- Model selection and evaluation.
Causality: A Half Day Workshop
Sunday, 1st September 2019, 14:30-18:30, Room Dudich
Ron S. Kenett
KPA Ltd and the Samuel Neaman Institute, Technion, Israel
Judea Pearl, the 2011 Turing Award winner who developed Bayesian networks and causality networks, recently published a bestselling book: The Book of Why. In that book he calls for a “causality revolution”. Causality has been treated by statisticians for many years, since the work of R. A. Fisher at Rothamsted agricultural station on designed experiments. The gold standard for determining causality has been the randomized controlled trial (RCT). A general framework for handling causality has been the Neyman-Rubin potential outcomes approach and the propensity score methods developed by Donald Rubin. This workshop will review basic tools for identifying causality variables, such as the fishbone diagram, present the versatile Bayesian network tool, discuss the critical role of randomization in designed experiments and introduce the methods proposed by Pearl and Rubin to assess causality relationships. Applications of these methods to personalized medicine, condition-based maintenance (CBM) and Industry 4.0 will also be discussed.
- Background on causality in science and statistics
- Fishbone cause and effect diagrams
- Bayesian networks
- Randomization in experimental designs
- Propensity scores in observational data
- Counterfactuals and do calculus
- Personalized medicine, condition-based maintenance and Industry 4.0
- Future research areas
Professor Ron Kenett, Chairman of the KPA Group, Senior Research Fellow, Samuel Neaman Institute, Technion and Visiting Professor, Institute for Drug Development, Hebrew University of Jerusalem, Israel. He is Past President of the Israel Statistical Association (ISA) and of the European Network for Business and Industrial Statistics (ENBIS). Ron authored and co-authored over 250 papers and 14 books on topics ranging from industrial statistics, biostatistics, customer surveys, multivariate quality control, risk management and statistical methods in healthcare. He held academic positions at the University of Wisconsin-Madison, the State University of New York, Binghamton, Tel Aviv University and Bell Laboratories in New Jersey, He was awarded the 2013 Greenfield Medal by the Royal Statistical Society (RSS) in recognition for excellence in contributions to the applications of Statistics and the 2018 George Box Medal by the European Network for Business and Industrial Statistics (ENBIS) for outstanding contributions to the application of statistical methods in European business and industry. He is editor in chief of the Wiley’s StatsRef electronic Encyclopedia and associate editor of ASMBI, Dynamic Relationships Management Journal, Electronic Journal of Applied Statistical Analysis and Transactions on Machine Learning and Data Mining. The methods he developed are incorporated in the arules and mistat R packages available from CRAN. For more details on Ron and his publications, see: https://www.neaman.org.il/EN/Ron-Kenett