::: Research Affiliates of the CRC 649 "Economic Risk"
Professor, DPolSc. Timo Teräsvirta
Timo Teräsvirta is Professor Emeritus at Aarhus University and a member of the Centre for Research in Econometric Analysis of Time Series (CREATES) in that university.
He is also Professor Emeritus at Stockholm School of Economics, where he served as Professor of Economic Statistics 1994-2006 before joining CREATES and Aarhus University.
Teräsvirta is elected member of the International Institute of Statistics, Societas Scientiarum Fennica (Helsinki) and the Royal Academy of Sciences (Stockholm).
He is honorary member of the Finnish Statistical Society and Fellow of both the International Institute of Forecasters and the Society for Financial Econometrics.
Teräsvirta has co-authored two books (with Clive W.J. Granger and Dag Tjøstheim) on nonlinear economic modelling and models.
He has published articles in international journals and volumes and is Fellow of Journal of Econometrics and Distinguished Author of Journal of Applied Econometrics.
His research interests include nonlinear time series models, smooth transition regressions in particular, and modelling nonlinear series.
He is currently also doing work on volatility models and modelling.
Prof. Dr. Stefan Wagner, ESMT European School of Management and Technology
Digitalization transforms virtually every step in the value chain of
almost every industry. It is most visible in consumer software such as
video games and in content-related industries, including publishing of
texts, music and movies. The availability of high-speed Internet
connections and powerful mobile devices have been enablers of this
development, which has led to the creation of new pricing schemes
and entirely new business models. One of the most striking features
of the “app economy” is a hybrid pricing model combining free and
paid features of a product. This so-called freemium pricing model is
now the new standard in news publishing, music streaming, consumer
software and also video gaming − all industries in which traditionally
customers were expected to pay upfront before using a product.
Despite the widespread use of freemium pricing models, it needs to
be stressed that to date many companies are still struggling in
optimizing freemium pricing schemes.
An initial project is rooted in the mobile gaming industry which is a
fast growing market and in which developers collect 90% of their
revenues on application stores through freemium business models.
Analyzing fine-grained data of one of the largest German publishers of
mobile games (www.wooga.com) allows close tracking of individual
user-behavior, linking it to their purchase decisions, and showing how
it is influenced by various design parameters of the freemium pricing
scheme. Due to the size of the data set and the richness of the
information contained in it, advanced econometric models can be
applied to identify causal relations between freemium parameters
and purchase decisions.
Prof. Francis de Véricourt, PhD, ESMT European School of Management and Technology
We explore the interplay between organizations’ capability to extract
rich data about their environment and the way these organizations
are managed. To that end, we follow a modeling and analytical
approach, mostly grounded in Operations Research and Decision
First, we develop theoretical guidelines on how organizations can
leverage rich flows of information to improve and sometimes radically
transform their processes. This may also lead to process innovations
or new business models. For instance, new information technologies
allow firms to elicit in real time very detailed information about their
customers, products or production facilities. We develop innovative
supply chain management or pricing strategies that exploit flows of
information such as these.
Second, and conversely, we explore which new processes
organizations should follow to elicit important hidden data and
information. For example, we study how a firm can uncover possible
environmental hazards at one of its suppliers or within its own