Showing papers by "Stefan Stremersch published in 2011"

Multihoming in Two-Sided Markets: An Empirical Inquiry in the Video Game Console Industry

Abstract: Two-sided markets are composed of platform owners and two distinct user networks that either buy or sell applications for the platform. The authors focus on multihoming—the choice of an agent in a user network to use more than one platform. In the context of the video game console industry, they examine the conditions affecting seller-level multihoming decisions on a given platform. Furthermore, they investigate how platform-level multihoming of applications affects the sales of the platform. The authors show that increased platform-level multihoming of applications hurts platform sales, a finding consistent with literature on brand differentiation, but they also show that this effect vanishes as platforms mature or gain market share. The authors find that platform-level multihoming of applications affects platform sales more strongly than the number of applications. Furthermore, among mature platforms, an increasing market share leads to more seller-level multihoming, while among nascent platfor...

Predictably Non-Bayesian: Quantifying salience effects in physician learning about drug quality

Abstract: textExperimental and survey-based research suggests that consumers often rely on their intuition and cognitive shortcuts to make decisions. Intuition and cognitive shortcuts can lead to suboptimal decisions and, especially in high-stakes decisions, to legitimate welfare concerns. In this paper, we propose an extension of a Bayesian learning model that allows us to quantify the impact of salience-the fact that some pieces of information are easier to retrieve from memory than others-on physician learning. We show, using data on actual prescriptions for real patients, that physicians' belief formation is strongly influenced by salience effects. Feedback from switching patients-the ones the physician decided to switch to a clinically equivalent treatment-receives considerably more weight than feedback from other patients. In the category we study, salience effects slowed down physicians' speed of learning and the adoption of a new treatment, which raises welfare concerns. For managers, our findings suggest that firms that are able to eliminate, or at least reduce, salience effects to a greater extent than their competitors can speed up the adoption of new treatments. We explore the implications of these results and suggest alternative applications of our model that are relevant for policy makers and managers.

Predictably Non-Bayesian: Quantifying Salience Effects in Physician Learning About Drug Quality

Abstract: Experimental and survey-based research suggests that consumers often rely on their intuition and cognitive shortcuts to make decisions. Intuition and cognitive shortcuts can lead to suboptimal decisions and, especially in high-stakes decisions, to legitimate welfare concerns. In this paper, we propose an extension of a Bayesian learning model that allows us to quantify the impact of salience---the fact that some pieces of information are easier to retrieve from memory than others---on physician learning. We show, using data on actual prescriptions for real patients, that physicians' belief formation is strongly influenced by salience effects. Feedback from switching patients---the ones the physician decided to switch to a clinically equivalent treatment---receives considerably more weight than feedback from other patients. In the category we study, salience effects slowed down physicians' speed of learning and the adoption of a new treatment, which raises welfare concerns. For managers, our findings suggest that firms that are able to eliminate, or at least reduce, salience effects to a greater extent than their competitors can speed up the adoption of new treatments. We explore the implications of these results and suggest alternative applications of our model that are relevant for policy makers and managers.

The Global Entry of New Pharmaceuticals: A Joint Investigation of Launch Window and Price

Abstract: Research on the launch of new products in the international realm is scarce. The present paper is the first to document how launch window (difference in months between the first worldwide launch and the subsequent launch in a specific country) and launch price are interrelated and how regulation influences both launch window and launch price. The research context is the global - 50 countries worldwide - launch of 58 new ethical drugs across 29 therapeutic areas. We show that the fastest launch occurs when the launch price is moderately high and the highest launch price occurs at a launch window of 85 months. We find that the health regulator acts strategically in that the extent to which it delays the launch of a new drug increases with the price of the new drug. We also find that regulation overall increases the launch window, except for patent protection. Surprisingly, regulation does not directly impact launch price. The descriptive information on average launch window and launch price and the interconnection between launch window and launch price allows managers in ethical drug companies to build more informed decisions for international market entry. This study also provides public policy analysts with more quantitative evidence regarding launch window and launch price on a broad sample of countries and categories.

Dynamics in International Market Segmentation of New Product Growth

Abstract: Prior international segmentation studies are static, i.e., they identify segments that are stable over time. This paper shows that country segments in new product growth are intrinsically dynamic. We propose a semiparametric hidden Markov model to dynamically segment countries based on the observed penetration pattern of new product categories. The methodology allows countries to switch between segments over the new product's life cycle, with time-varying transition probabilities. Our approach is based on penalized splines and can thus be flexibly applied to any non-stationary phenomenon, beyond the new product growth context.For the penetration of six new product categories in 79 countries, we recover each country’s dynamic membership to segments over the life cycle. Our findings reveal substantial dynamics in international market segmentation, in particular at the beginning of the product life. Finally, we exploit the dynamic segments to predict the national penetration patterns of a new product before its launch and show that our forecasts outperform forecasts derived from alternate parametric and/or static methods. Our results encourage multinational corporations to adopt dynamic segmentation methods instead of static ones.