Hai Che

Bounded Rationality in Pricing Under State-Dependent Demand: Do Firms Look Ahead, and if So, How Far?

The authors propose an empirical procedure to investigate the pricing behavior of manufacturers and retailers in the presence of state-dependent demand. Rather than assuming that firms are perfectly forward looking and therefore solving accordingly for dynamic equilibriums that would arise in the presence of state dependence, the authors systematically evaluate whether boundedly rational firms indeed look ahead when they set prices and, if so, to what extent. They illustrate the procedure using household-level scanner-panel data on breakfast cereals and replicate the substantive results using data on ketchup. The authors find that (1) omission of state dependence in demand biases inference of firm behavior (i.e., tacit collusion is erroneously inferred when firms are competitive); (2) observed retail prices are consistent with a pricing model in which both manufacturers and retailers are forward looking (i.e., they incorporate the effects of their current prices on their future profits), but firms have short time horizons when setting prices (i.e., they look ahead by only one period, suggesting that firms are boundedly rational in their dynamic pricing behavior); and (3) even a myopic pricing model of firms that accounts for state dependence in demand is a reasonable approximation of the observed prices in the market.

Price Competition in Markets with Consumer Variety Seeking

We investigate price competition between firms in markets characterized by consumer variety seeking. While previous research has addressed the effect of consumer inertia on prices, there exists no research on the effects of variety seeking on price competition. Our study fills this gap in the literature. Using a two-period duopoly framework as in Klemperers analysis of inertial markets, we show that the noncooperative pricing equilibrium in a market with consumer variety seeking may be the same as the collusive outcome in an otherwise identical market without variety seeking. Specifically, our variety-seeking model implies tacit collusion between firms in both periods, unlike the inertia model of Klemperer that implies tacit collusion between firms only in the second period but implies fierce price competition in the first period. When consumers are assumed to have rational expectations about future prices, the implied first-period prices increase further, which is consistent with what Klemperer finds in an inertial market. To summarize, while our variety-seeking analyses support two key results (pertaining to second-period prices and rational expectations) previously derived for inertial markets by Klemperer, they depart from one key result (pertaining to first-period prices).

The Economic Value of Online Reviews

This paper investigates the economic value of online reviews for consumers and restaurants. We use a data set from Dianping.com , a leading Chinese website providing user-generated reviews, to study how consumers learn, from reading online reviews, the quality and cost of restaurant dining. We propose a learning model with three novel features: 1 different reviews offer different informational value to different types of consumers; 2 consumers learn their own preferences, and not the distribution of preferences among the entire population, for multiple product attributes; and 3 consumers update not only the expectation but also the variance of their preferences. Based on estimation results, we conduct a series of counterfactual experiments and find that the value from Dianping is about 7 CNY for each user, and about 8.6 CNY from each user for the reviewed restaurants in this study. The majority of the value comes from reviews on restaurant quality, and contextual comments are more valuable than numerical ratings in reviews.

“Speed of Replacement”: Modeling Brand Loyalty Using Last-Move Data

The authors study brand loyalties for durable goods using automobile survey data that are peculiarly censored and track only elapsed times since transitions but not the transition times themselves. This censoring problem is typical of commercially available durable goods survey data. However, little attention has been paid to such “last-move” data in the statistics or marketing literature on the analysis of transition times. The authors propose a multistate, continuous-time, nonstationary Markov model with a parsimonious brand loyalty structure and also propose an estimation approach to recover the parameters of the proposed model using the automobile survey data. The proposed model fits observed brand choice outcomes even better than a model with a fully unrestricted (and, therefore, highly parameterized) transition structure. The authors also obtain several substantive findings. For example, Chrysler is significantly “weaker” than General Motors and Ford insofar as it has the lowest brand loyalty during the study period. The authors illustrate the managerial implications by predicting time-varying market shares of brands in periods subsequent to the period of analysis.