Ishihara. Masakazu Ishihara. Toronto, ON M5S 3E6 Canada

Transcription

1 Masakazu September 2010 Phone: (416) Fax: (416) St. George Street Toronto, ON M5S 3E6 Canada Education Joseph L.,, ON, Canada (Sep present) Ph.D. in Marketing (In Progress, Expected May 2011) Dissertation: Dynamic Demand for New and Used Durable Goods without Physical Depreciation Thesis Committee: Andrew Ching (co-chair), Sridhar Moorthy (co-chair), Ron Borkovsky University of Wisconsin-Madison, WI, USA M.S. in Economics, May 2004 Fields: Empirical Industrial Organization, Game Theory University of Wisconsin-Madison, WI, USA B.S. in Economics-Mathematical Emphasis, Dec Research Interests Quantitative Marketing, Empirical Industrial Organization, Applied Econometrics, Marketing and Economics of Entertainment Industry and Pharmaceutical Industry Publications The Effects of Detailing on Prescribing Decisions under Quality Uncertainty (with Andrew Ching), Quantitative Marketing and Economics, vol. 8(2), pp , 2010 (lead article). Category Spanning, Naming Strategies and Performance Implications in the U.S. Film Industry with Eric Y.F. Zhao and Stan X. Li, 2008 Academy of Management Best Paper Proceedings (OMT) Working Papers Dynamic Demand for New and Used Durable Goods without Physical Depreciation: The Case of Japanese Video Games (Job Market Paper) Measuring the Informative and Persuasive Roles of Detailing on Prescribing Decisions (with Andrew Ching), under 2 nd round review at Management Science

2 A Guide to Bayesian Estimation of Dynamic Discrete Choice Models with an application to a Store-level Reward Program (with Andrew Ching, Susumu Imai, and Neelam Jain), under 2 nd round review at Quantitative Marketing and Economics (solicited by the editor) Work In Progress A Dynamic Model of Consumer Learning and Forgetting (with Andrew Ching, Susumu Imai, Neelam Jain) Patterns of Advertising and Distribution Strategies in the U.S. Motion Picture Industry (with Andrew Ching, Susumu Imai, and Sridhar Moorthy) Genre Spanning, Common Naming, and Compensatory Legitimation (with Eric Y.F. Zhao) The Origins and Performance Impact of Time-to-Market Capability: Evidence from the U.S. Video Game Industry (with Eric Y.F. Zhao) Conference Presentations Dynamic Demand for New and Used Durable Goods without Physical Depreciation: The Case of Japanese Video Games The 8 th Annual International Industrial Organization Conference, UBC, May 2010 Marketing Dynamics Conference, NYU, Aug A Guide to Bayesian Estimation of Dynamic Discrete Choice Models with an application to a Store-level Reward Program The 8 th Annual International Industrial Organization Conference, UBC, May 2010 UTD-FORMS Conference, University of Texas at Dallas, Feb Far East and South Asia Meeting of the Econometric Society, University of Tokyo, Aug Measuring the Informative and Persuasive Roles of Detailing on Prescribing Decisions Annual Meeting of the Canadian Health Economics Study Group, McGill University, May 2010 Marketing Science Conference, University of Michigan, Ann Arbor, Jun rd Annual Conference of the Canadian Economics Association,, May 2009 North American Summer Meeting of the Econometric Society, Carnegie Mellon University, Jun The Effects of Detailing on Prescribing Decisions under Quality Uncertainty Marketing Science Conference, Singapore Management University, Jun Fourth CEPR School on Applied Industrial Organization, Tarragona, Spain, May 2007

3 Marketing Dynamics Conference, UCLA, Aug North American Summer Meeting of the Econometric Society, University of Minnesota, Twin Cities, Jun Honors and Awards Doctoral Scholarship,,, Sep present AMA-Sheth Doctoral Consortium Fellow, Texas Christian University, 2010 AIC Institute of Corporate Citizenship Research Grant (with Andrew Ching), 2010 Travel Grant, Far East and South Asia Meeting of the Econometric Society, 2009 ISMS Doctoral Consortium Fellow, Singapore Management University, 2007, University of Michigan, Ann Arbor 2009 Rotman Excellence in Teaching Awards, 2008 School of Graduate Studies Travel Grant,, 2008 Travel Grant, Forth CEPR School on Applied Industrial Organization, 2007 Travel Grant, Marketing Dynamics Conference, 2006 Distinguished Teaching Assistantship, University of Wisconsin-Madison, Spring 2003, Fall 2003 Mr. and Mrs. Harry A. Bullis Scholarship, University of Wisconsin-Madison, Sep May 2002 Walter Morton Memorial Scholarship, University of Wisconsin-Madison, Sep May 2002 Teaching Experience Instructor, Principles of Marketing,, Summer 2008 Received the Rotman Excellence in Teaching Awards (evaluation 6.0 / 7.0) Teaching Assistant for Pricing (MBA, undergraduate) and Principles of Marketing (undergraduate),, Teaching Assistant for Principles of Microeconomics and Intermediate Macroeconomics, University of Wisconsin-Madison, Received the Distinguished Teaching Assistant Award in two semesters Professional Experience Academic Research: Research Assistant for Prof. Andrew Ching,,, Visiting Scholar, Sophia University, Japan, Oct Project Assistant for Prof. Ananth Seshadri, University of Wisconsin-Madison, Sep May 2002

4 Industry Experience: Marketing Analyst in mobile e-commerce project, NetAge, Inc., Tokyo, Japan, Jan. Aug., 2005 Computer Skills LaTeX, MS-Word, MS-Excel (VBA), MS-PowerPoint, C, Fortran, Matlab, R, STATA, Maxima, Python References Andrew T. Ching Assistant Professor of Marketing Tel: (416) Ron N. Borkovsky Assistant Professor of Marketing Tel: (416) Sridhar Moorthy Manny Rotman Professor of Marketing Tel: (416) Susumu Imai Associate Professor of Economics Department of Economics Queen s University Tel: (613) imais@econ.queensu.ca

5 Abstract for Doctoral Dissertation Dynamic Demand for New and Used Durable Goods without Physical Depreciation: The Case of Japanese Video Games In product categories such as books, CDs/DVDs, and video games, the competition from used goods markets has been viewed as a serious problem by producers. These products share a common feature: the physical attributes of the products hardly depreciate but the consumption value to owners depreciates quickly due to satiation. The goal of this paper is to examine the substitutability between new and used goods for this type of product, and to study the impact of used goods markets on the profitability of new goods. To achieve this goal, I develop a new structural empirical framework. In my model, the demand for new goods and the demand for and the supply of used goods are generated by a dynamic discrete choice model of forward-looking consumers that incorporates (i) consumers new and used goods purchasing decisions, (ii) consumers used goods selling decision, (iii) consumer expectations about future prices of new and used goods and resale values of used goods, and (iv) the depreciation of both owners and potential buyers consumption values. I apply this framework to the Japanese video game software market in which used markets are mostly controlled by used-game retailers. A unique feature of my data set is that in addition to weekly sales and prices of new and used video games by game title, it contains weekly aggregate quantities sold by owners to retailers and the associated resale values, and weekly inventory levels of used games at retailers. The data on both consumers new and used goods purchasing decisions and used goods selling decisions allow me to separately identify the depreciation rates of consumption values to both owners and potential buyers. In addition, unlike previous studies that impose the market clearing condition in used-good trading, my data set allows me to make use of the excess supply information to control for the impact of the availability of used games on consumer purchasing decisions. To estimate my dynamic model using market-level data, I develop a new Bayesian Markov chain Monte Carlo (MCMC) algorithm that is applicable to a non-stationary dynamic discrete choice model with potential price endogeneity problems. The estimation results show that (1) the depreciation of consumption values to potential buyers from the release week to the 2nd week is about 5% in one consumer segment and 47% in another segment; and (2) the depreciation of consumption values to owners depends on product characteristics. In particular, I find that positive user ratings have a significant impact in reducing the depreciation rate. Using the parameter estimates, I examine three types of dynamic demand and supply elasticities that account for the inter-temporal substitution. They measure (a) the impact of used-game prices on new-game demand; (b) the impact of used-game inventory levels on new- and used-game demand; and (c) the impact of used-game resale values on used-game supply. The first type of elasticity is a standard measure for the substitutability, but previous works have not taken the inter-temporal substitution into account. The second and third types have never been examined in the previous literature, and they can provide important insights as to how an increase in the availability of used games affects new-game revenues. Furthermore, I quantify the impact of eliminating the used video game market on new-game revenues. I find that the elimination of the used video game market reduces the total revenue for a new game by 4% on average, if video game publishers do not adjust their pricing strategies. This is mainly because the elimination of the used market also eliminates the future selling opportunity for consumers and reduces the demand for new games, especially in the earlier periods. This suggests that the existence of the used video game market in Japan could be beneficial to video game publishers. Finally, I examine the optimality of the conventional flat-pricing strategy used by video game publishers in Japan. I simulate the model by marginally reducing the price of new games over time (as in the pricing-skimming strategy), and compare its profitability to that of the flat-pricing strategy. The result suggests that this marginal price-skimming strategy increases the total revenue for a new game by 0.5% on average.

6 Abstracts for Selected Published and Working Papers 1) The Effects of Detailing on Prescribing Decisions under Quality Uncertainty (with Andrew Ching), Quantitative Marketing and Economics, vol. 8(2), pp , 2010 (lead article). Motivated by recent empirical findings on the relationship between new clinical evidence and the effectiveness of detailing, this paper develops a new structural model of detailing and prescribing decisions under the environment where both manufacturers and physicians are uncertain about drug qualities. Our model assumes (1) a representative opinion leader is responsible for updating the prior belief about the quality of drugs via consumption experiences and clinical trial outcomes, and (2) manufacturers use detailing as a means to build/maintain the measure of physicians who are informed of the current information sets. Unlike previous learning models with informative detailing, our model directly links the effectiveness of detailing to the current information sets and the measures of well-informed physicians. To illustrate the empirical implications of the new model, we estimate our model using a product level panel data on sales volume, prices, detailing minutes, and clinical trial outcomes for ACE-inhibitors with diuretics in Canada. Using our estimates, we demonstrate how the effectiveness of detailing depends on the information sets and the measures of well-informed physicians. Furthermore, we conduct a policy experiment to examine how a public awareness campaign, which encourages physicians/patients to report their drug experiences, would affect managerial incentives to detail. The results demonstrate that the empirical and managerial implications of our model can be very different from those of previous models. We argue that our results point out the importance of developing a structural model that captures the mechanism of how detailing/advertising conveys information in the market under study. 2) Measuring the Informative and Persuasive Roles of Detailing on Prescribing Decisions (with Andrew Ching), under 2 nd round review at Management Science. In the pharmaceutical industry, measuring the importance of informative and persuasive roles of detailing is crucial for both drug manufacturers and policy makers. However, little progress has been made in disentangling these two roles of detailing in empirical research. In this paper, we provide a new identification strategy to address this problem. Our key identification assumptions are that the informative component of detailing is chemical specific while the persuasive component is brand specific. Our strategy is to focus on markets where some drug manufacturers engage in a co-marketing agreement, under which two companies market the same chemical using two different brand-names. With our identification assumptions, the variations in the relative market shares of these two brands, together with their brand specific detailing efforts, would allow us to measure the persuasive component of detailing. The variations in the market shares of chemicals, and the detailing efforts summed across brands made of the same chemical, would allow us to measure the informative component of detailing. Using the data for ACE-inhibitor with diuretic in Canada, we find evidence that our identification strategy can help identify these two effects. Although both effects are statistically significant, we find that the persuasive function of detailing plays a very minor role in determining the demand at the chemical level - the informative role of detailing is mainly responsible for the diffusion patterns of chemicals. In contrast, the persuasive role of detailing plays a crucial role in determining the demand for brands which co-market the same chemical. We also find that patients could be worse off if the government bans detailing for ACE-inhibitor with diuretic.

7 3) A Guide to Bayesian Estimation of Dynamic Discrete Choice Models with an application to a Store-level Reward Program (with Andrew Ching, Susumu Imai, and Neelam Jain), under 2 nd round review at Quantitative Marketing and Economics. This paper provides a step-by-step guide to estimating infinite horizon discrete choice dynamic programming (DDP) models using a new Bayesian estimation algorithm (Imai, Jain and Ching, Econometrica 77: , 2009) (IJC). In the conventional nested fixed point algorithm, most of the information obtained in the past iterations remains unused in the current iteration. In contrast, the IJC algorithm extensively uses the computational results obtained from the past iterations to help solve the DDP model at the current iterated parameter values. Consequently, it has the potential to significantly alleviate the computational burden of estimating DDP models. To illustrate this new estimation method, we use a simple dynamic store choice model where stores offer frequent-buyer type reward programs. We show that the parameters of this model, including the discount factor, are well-identified. Our Monte Carlo results demonstrate that the IJC method is able to recover the true parameter values of this model quite precisely. We also show that the IJC method could reduce the estimation time significantly when estimating DDP models with unobserved heterogeneity, especially when the discount factor is close to 1.