The authors investigate whether and how pricing and promotional activities influence prescription choice behavior using a comprehensive panel of physicians and data on competitive price and promotional activities. The authors find that physicians are characterized by fairly limited price sensitivity, detailing and samples have a mostly informative effect on physicians, and physicians with a relatively large number of Medicare or health maintenance organization patients are less influenced by promotion than other physicians are.

We investigate the key determinants of the optimal direct mail policy in a dynamic environment where customers maximize utility and the direct mailer maximizes profits. We measure the sensitivity of the customers to receiving a catalog in the mail, while controlling for customer characteristics such as elapsed time in responses and number of purchases. We apply our model to a database from a national cataloger that markets nonseasonal products. We summarize the results of our model that are valid for these types of products. We find that the dynamic model significantly outperforms its single-period counterpart. We find that it is not optimal to mail to individuals at low recency levels because they are likely to buy anyway. It is better to save the mailing dollars for customers at higher recency levels. We find that it is optimal to mail to customers who have purchased only a small or a medium number of times to induce them to continue to buy from this catalog and not switch to others. It is not necessary to mail often to customers who have purchased many times before from the company unless they have high recency values. We find that under the optimal mailing policy the cataloguer enjoys higher profits than under the current mailing policy.Structural Models, Principle of Optimality, Catalogs, Mailing Policy

We examine the basic premise that consumers may anticipate future promotions and adjust their purchase behavior accordingly. We develop a structural model of households who make purchase decisions to minimize their expenditure over a finite period. The model allows for future expectations of promotions to enter the purchase decision. Households with adequate inventory of the product may face a trade-off of buying in the current period with a coupon or defer the purchase until next period, given their expectations of future promotions. Thus, we provide a framework for examining the impact of consumer expectations on choice behavior. The target audiences for our paper are (a) empirical researchers who intend to make structural models part of their applied research agenda; and (b) managers who value and seek to understand the impact of consumers' coupon expectations on current purchase behavior. Our research objective is to provide an empirical framework to examine whether and to what extent consumers anticipate future coupon promotions and adjust purchase behavior. The central premise of our approach is that a rational consumer minimizes the present discounted value of the cost of a purchase where cost in a single period consists of purchase price, inventory holding cost, gains from coupons, and potential stockout cost. We aim to test whether our hypotheses regarding the various elements of the cost structure are supported and that whether consumers take into account future discounted cost when making current purchase decisions. The research methodology we adopt is relatively new in econometrics and known as the estimable stochastic structural dynamic programming method. The methodology amounts to incorporating a maximum likelihood routine embedded in a dynamic programming problem. The dynamic programming problem is solved several times within a maximum likelihood iteration for each value of the state space elements and for each value of the parameters in the parameter set. The state space in our model consists of purchase and nonpurchase alternatives in each time period, coupon availability and no coupon availability in each time period, level of inventory in each time period for each household, and consumption rate of each household. We use scanner panel data on purchases in the disposable diaper product category and promotions. We estimate the inventory holding and stockout costs, brand-specific value of coupons, and consumers' expectations of future coupons. The key insights and lessons learned can be summarized as follows: (1) Our results are consistent with the notion that consumers hold beliefs about future coupons, and that such beliefs affect the purchase decision. We find that the dynamic optimization model performs significantly better than a single-period optimization model and a naive benchmark model. (2) We find a high and significant stockout cost, consistent with the essential nature of the product category. Our estimate of the holding cost yields a reasonable annualized percentage value when conver...

We offer a framework to specify and estimate various sources of heterogeneity in multinomial logit brand choice models. We let each brand-specific intercept and each parameter of the explanatory variable vector vary randomly across households. In addition, we distinguish loyal households from the rest. Our results suggest that incorporating multiple sources of heterogeneity improves the model fit and suggests higher impact of marketing mix elements on brand choice. We highlight the importance of incorporating multiple sources of heterogeneity. The model we implement yields valuable managerial insights.multinomial logit, heterogeneity, brand choice, random coefficients, loyalty

We develop a brand choice model with learning based on the Kalman filter methodology. The model enables us to separate the effects of contemporaneous marketing promotions from the impact of the perceived quality valuation accrued through product usage over time. We also account for idiosyncratic consumer learning and preferences. The results point to the presence of heterogeneity in the valuation carryover coefficients across consumers and brands. In contrast to our expectations, a higher price is not important for most of the consumers in the sample. The model enables us to compare brands in terms of their memorability, which determines brand salience on the next purchase occasion. Our findings suggest that price promotions may be deficient as a tool to increase market share in the studied product category. The proposed model is applicable to other consumer goods contingent on consumers' being sufficiently motivated to learn their own preferences via personal experience. Brand managers can use the model for comparative diagnostics and market performance simulation under different price and promotion scenarios. This paper is instructive to the application of a relatively new methodology; we illustrate the analytical potential of the model by demonstrating its inferential power in a specific marketing context.brand choice, buyer behavior, consumer learning, hierarchical Bayes analysis