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«submitted by Daniel Philipp Stadel from Germany Approved on the application of Prof. Dr. Andreas Herrmann and Prof. Dr. Torsten Tomczak Dissertation ...»

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Advanced Statistical Models for

Pricing, Mass Customization and Forecasting

- A Bayesian Approach DISSERTATION

of the University of St. Gallen,

School of Management,

Economics, Law, Social Sciences

and International Affairs

to obtain the title of

Doctor of Philosophy in Management

submitted by

Daniel Philipp Stadel

from

Germany

Approved on the application of

Prof. Dr. Andreas Herrmann

and

Prof. Dr. Torsten Tomczak

Dissertation no. 3937

Difo-Druck GmbH, Bamberg 2011

The University of St. Gallen, School of Management, Economics, Law, Social Sciences and International Affairs hereby consents to the printing of the present dissertation, without hereby expressing any opinion on the views herein expressed.

St. Gallen, May 13, 2011

The President:

Prof. Dr. Thomas Bieger To my family V Acknowledgment This cumulative dissertation has been a very challenging and interesting endeavor, which would not have been possible without the contributions of a number of persons. Therefore, I would like to thank all the people who supported me throughout this ambitious project.

First of all, I would like to thank my primary advisor, Professor Andreas Herrmann, and my secondary advisor, Professor Torsten Tomczak, for their guidance, encouragement, and supervision. They have provided vital support for my study and research. I am also indebted to numerous individuals at the University of St. Gallen. Particularly, I would like to thank Dr. Julia Stefanides, Antonia Erz, Christian Hildebrand and Christian Purucker for their ongoing willingness to discuss issues related to my dissertation project, their valuable comments and the great working atmosphere. I also would like to thank my coauthors Professor Florian Stahl, Professor Raghuram Iyengar, Professor Benedict Dellaert and Dr. Jan Landwehr for their support and effort in completing the papers.

Sustaining me throughout has been the ever present support and understanding of my family and friends. Therefore, I would like to thank my friends for their comprehension and patience and my family for their continuous encouragement and support. Without them, the completion of this dissertation would not have been possible.

St. Gallen, May 2011 Daniel P. Stadel VII Table of Contents A. Summary - Zusammenfassung B. Article I Stahl, F., Stadel, D. P., Iyengar, R., and Herrmann, A. (in preparation for submission). Subscriptions Pricing and Intertemporal Tradeoffs. Management Science.

C. Article II Stadel, D. P., Dellaert, B. G. C., Herrmann, A., and Landwehr, J. R. (submitted). Locked-In To Luxury: First- and Second-Order Default Effects in Mass Customization. Marketing Science.

D. Article III Stadel, D. P. (submitted). Online Data: Predictive Power or Obscure Delusion?

International Journal of Research in Marketing.

–  –  –

Summary In many fields of business studies such as finance, econometrics and quantitative marketing the importance of advanced statistical methods steadily increases as the problems gain complexity. With faster computers and new sources for vast amounts of data, statistical approaches are challenged to cope with these aspects, and must therefore be improved. For quantitative marketing, the information gained by complex models, and the insights given by new advanced methods strengthen the ability of companies to faster react to their customers’ needs. This dissertation discusses the application of advanced statistical methods to a variety of research objectives, such as tariff design, mass customization profitability, and forecasting.

The first essay broaches the issue of consumers’ intertemporal tradeoffs among subscription plans and the respective consequences for its optimal pricing. Subject of further investigation is the individual’s discounting behavior which has a significant influence on the perceived value for the customer. We augment a general discount function by an additional parameter to account for flexibility preferences in the individual’s discounting behavior. Such behavior has a tremendous influence on optimal pricing strategies for service providers.

The second essay investigates default-based upselling potentials in mass customization systems such as online car configurators. We study whether companies can start their customers off on a high-margin decision path based on a few high-end default selections early on in the configuration process. We analyze whether default attribute levels within the customization process can increase consumers’ choices for high-margin attribute levels (first-order default effects) and whether these effects help or hurt margins on later subsequent attribute level choices (second-order default effects). We offer a conceptual framework to managerially guide default selection to accommodate these two effects. The third essay provides an analysis of online data from a car configurator and web search queries to assess its usefulness as input for forecasting models. Due to large amounts of data available online, companies can benefit from proper analX yses of such data pools. Therefore, time series methods are applied to the data.

The forecasting performance is compared to models without incorporating the online data. It is shown that such data can significantly improve the forecasting performance and, hence, companies should face the challenge to cope with the task of utilizing available online data.





The intended research projects, and therefore the resulting essays show applications of advanced statistical tools to cover complex but important issues among the economic interaction of companies and their customers. Based on these methods, I am able to conduct several analyses to draw conclusions of high importance and relevance for managerial implications.

XI

Zusammenfassung

In den unterschiedlichsten Teilgebieten der Wirtschaftswissenschaften efreuen sich statistische Methoden aufgrund der stetig steigenden Komplexität der Fragestellungen immer größerer Beliebtheit. In der Disziplin des quantitativen Marketings können hochentwickelte Methoden den nötigen Wissensvorsprung liefern, um bestmöglichst auf sich ändernde Kundenanforderungen zu reagieren. Die vorliegende Dissertation diskutiert statistische Modelle für Anwendungen in den Bereichen Tarifdesign, Konfigurator-Optimierung und Prognoserechnung.

Der erste Aufsatz diskutiert die Gestaltung von Abo-Tarifen bezüglich Laufzeit und Preis unter Berücksichtigung des individuellen Planungshorizonts der Kunden. Der Fokus liegt dabei auf dem individuellen Diskontierungsverhalten der Konsumenten. Der zweite Beitrag untersucht das Upselling-Potential mittels Produktkonfiguratoren am Beispiel eines Car-Konfigurators. Es wird analysiert, wie Konsumenten auf voreingestellte Optionen innerhalb des Kongurationsprozesses reagieren (Effekt 1. Ordnung), und ob diese Auswirkungen auf spätere Entscheidungen innerhalb des selben Konfigurationsprozesses (Effekt 2. Ordnung) haben. Wir erarbeiten ein konzeptionelles Gerüst für die optimale Auswahl von Defaults unter Berücksichtigung beider Effekte. Der letzte Artikel befasst sich mit der Prognose von Verkaufsmengen. Für zwei Pkw-Modelle werden mittels Online-Daten und einem statistischen ZeitreihenModell zukünftige Bestellungen vorhergesagt. Es wird gezeigt, dass sich, unter Berücksichtigung der Online-Daten, die Prognose-Güte signifikant verbessern lässt, und den Herstellern somit eine weitere zuverlässige Datenquelle für Prognosemodelle gegeben ist.

Die wissenschaftlichen Ausführungen zeigen die Anwendung statistischer Methoden zur Bearbeitung und Lösung komplexer Fragestellungen im Zusammenhang der wirtschaftlichen Interaktion zwischen Unternehmen und ihren Kunden. Basierend auf diesen Methoden und deren Ergebnisse, können Implikationen und Empfehlungen von großer Bedeutung für Management-relevante Entscheidungen abgeleitet werden.

Article I

–  –  –

∗ Florian Stahl (stahl@isu.uzh.ch) is Assistant Professor of Marketing at the University of Zurich, 8032 Zurich, Switzerland.

† Daniel P. Stadel (daniel.stadel@unisg.ch) is Ph.D. candidate at the University of St. Gallen, 9000 St. Gallen, Switzerland.

‡ Raghuram Iyengar (riyengar@wharton.upenn.edu) is Assistant Professor of Marketing at the The Wharton School, Philadelphia, PA - 19104.

§ Andreas Herrmann (andreas.herrmann@unisg.ch) is Professor of Marketing at the University of St. Gallen, 9000 St. Gallen, Switzerland.

2 ARTICLE I

Abstract

A common form of subscriptions to many services (e.g., health clubs, Internet access) is characterized by duration that a consumer has access to a service and a one-time flat fee for unlimited use. A key aspect of such subscriptions is that the price per-time unit declines with longer durations. Such a pricing mechanism forces consumers to face a tradeoff in their choice among plans - a short membership plan gives the flexibility to switch plans or providers while a long one provides a price discount. For consumers, such decisions involve the flat fee, discounting of future service benefits and their valuation of flexibility. For a firm offering a subscription-based service, it is important to understand how consumers discount future benefits as it impacts their willingness-to-pay. Using experimental data, we find that consumers’ discounting pattern is inverse N-shaped (decrease-increase-decrease) with respect to membership duration. We also show that a key driver of this pattern is the maximum contract duration that consumers typically subscribe to a service. To determine the implications of our findings for managerial decisions, we parameterize the observed discounting pattern and incorporate it within a model of consumer choice among plans. The model is estimated using experimental data on consumers’ willingness-to-pay for membership plans for a health club. We compare the optimal menu of plans predicted from our model with those based on an alternative model, which assumes only hyperbolic discounting. Our results show that firms would give much smaller price discounts to customers for longer membership durations if they ignore the inverse N-shaped discounting pattern. Translated in terms of profitability, the failure to account for the observed discounting leads to a reduction of 19% in firm profit.

–  –  –

Subscriptions are a popular pricing practice used by many business-to-consumer companies. A common form of such subscriptions is a membership plan, which is characterized by the length of time a customer can access a service (membership duration) and a one-time flat fee (membership fee) for its unlimited use.

For example, an online newspaper, Radiance Weekly, charges a one-time fee of $85, $125, $175 and $225 for unlimited access to articles for 1, 2, 3 and 5 years, respectively (see radianceweekly.com). Similarly, Greyhound bus service charges $239, $439 and $539 for unlimited rides for 7, 30 and 60 days, respectively as part of their Discovery package (see discoverypass.com). Such flat rate plans are becoming increasingly popular as compared to usage-based pricing for a variety of services such as Internet access, fixed-line telephone and access to many online services (OECD 2009). A key aspect of such subscriptions is that the price per-time unit declines with a longer subscription period. For example, customers pay only $45 per year to Radiance Weekly if they subscribe for 5 years as opposed to $85 for a one year subscription.1 With such type of plans, consumers face a tradeoff in their choice among them - a membership plan of short duration has a high price per-time unit but gives consumers the flexibility to switch plans or providers. With a long membership plan, customers lose their flexibility but benefit from the lower price per-time unit. For consumers, a choice of a plan involves consideration of immediate costs (flat fee), future benefits from use of service and their valuation of flexibility (DellaVigna and Malmendier 2006). How consumers discount future benefits in this context has an impact on their willingness-to-pay (WTP) for subscriptions of differing lengths and, consequently, for the optimal design of subscriptions.

A rich stream of past literature on consumers’ intertemporal preferences has shown that individuals discount future utility according to a hyperbolic function (Ariely and Loewenstein 2000, Ariely and Zauberman 2000, Laibson 1997, Loewenstein and Prelec 1992, Thaler 1981). A majority of this work has foThere are other types of subscriptions in which consumers are charged for both access and usage using either a two-part tariff (Danaher 2002, Essegaier et al. 2002) or multi-part tariff (Iyengar et al. 2007, 2008). In this paper, we focus on a popular pricing plan used by many types of services, where there is a one-time access fee charged for giving consumers unlimited usage for a given time duration.

4 ARTICLE I cused on consumers discounting of utility at discrete future time points. More recent literature has considered the impact of “duration” and “intervals” on individuals’ discount patterns (Ariely and Loewenstein 2000, LeBoeuf 2006, Overton and MacFadyen 1998, Read et al. 2005, Scholten and Read 2006, 2009).

However, such investigations have been in the context of how far future outcomes are removed from the present, how far these outcomes are removed from one another and its effect on the evaluation of a sequence of outcomes. Please see Berns et al. (2007) and Frederick et al. (2002) for a more detailed discussion of past work about intertemporal discounting, and DellaVigna and Malmendier (2006) for a discussion of consumers’ discounting of future benefits from product usage. As described above, subscriptions are also characterized by a time duration for which customers have access to a service. However, in the case of subscriptions, consumers have to discount future benefits from a service over a continuous duration (length of membership) rather than at discrete future time points. While it is plausible that consumers may discount such future benets still using a hyperbolic function, it is not obvious how their valuation for flexibility would impact their discounting pattern.



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