Marketing Science

Desai, Preyas S.

doi: 10.1287/mksc.1120.0709pmid: N/A

No abstract available.

Tirunillai, Seshadri; Tellis, Gerard J.

doi: 10.1287/mksc.1110.0682pmid: N/A

This study examines whether user-generated content (UGC) is related to stock market performance, which metric of UGC has the strongest relationship, and what the dynamics of the relationship are. We aggregate UGC from multiple websites over a four-year period across 6 markets and 15 firms. We derive multiple metrics of UGC and use multivariate time-series models to assess the relationship between UGC and stock market performance.Volume of chatter significantly leads abnormal returns by a few days (supported by Granger causality tests). Of all the metrics of UGC, volume of chatter has the strongest positive effect on abnormal returns and trading volume. The effect of negative and positive metrics of UGC on abnormal returns is asymmetric. Whereas negative UGC has a significant negative effect on abnormal returns with a short wear-in and long wear-out, positive UGC has no significant effect on these metrics. The volume of chatter and negative chatter have a significant positive effect on trading volume. Idiosyncratic risk increases significantly with negative information in UGC. Positive information does not have much influence on the risk of the firm. An increase in off-line advertising significantly increases the volume of chatter and decreases negative chatter. These results have important implications for managers and investors.

Kopalle, Praveen K.; Sun, Yacheng; Neslin, Scott A.; Sun, Baohong; Swaminathan, Vanitha

doi: 10.1287/mksc.1110.0687pmid: N/A

We estimate the joint impact of the frequency reward and customer tier components of a loyalty program on customer behavior and resultant sales. We provide an integrated analysis of a loyalty program incorporating customers' purchase and cash-in decisions, points pressure and rewarded behavior effects, heterogeneity, and forward-looking behavior. We focus on four key research questions: (1) How important is it to combine both components in one model? (2) Does points pressure exist in the context of a two-component loyalty program? (3) How is the market segmented in its response to the combined program? (4) Do the programs complement each other in terms of the incremental sales they produce? Our most basic message is that the frequency reward and customer tier components of loyalty programs should be modeled jointly rather than in separate models. We find strong evidence for points pressure for both the customer tier and frequency reward components using both model-based and model-free evidence. We find a two-segment solution revealing a service-oriented segment that highly values cash-ins for room upgrades and staying in luxury hotels, and a price-oriented segment that is more price sensitive and highly values the frequency reward aspects of the loyalty program. Furthermore, we find that both components generate incremental sales. Also, there was slight synergy between the programs but not a huge amount. Overall, each component contributes to increased revenues and does not interfere with the other.

Ho, Teck-Hua; Li, Shan; Park, So-Eun; Shen, Zuo-Jun Max

doi: 10.1287/mksc.1110.0701pmid: N/A

When social influence plays a key role in the diffusion of new product, the value of a customer often goes beyond her own product purchase. We posit that a customer's value (CV) comes not only from her purchase value (PV) but also from her influence value (IV) (i.e., CV PV IV). Therefore, a customer's value can be far greater than her purchase value if she exerts a considerable influence on others. Building on a two-segment influentialimitator asymmetric influence model, we develop a model framework to derive closed-form expressions for PV, IV, and CV by customer segment as well as time of adoption, and we examine their comparative statics with respect to the diffusion parameters. A key parameter of our model framework is the social apportioning parameter, , which determines the credit a customer receives by influencing other potential adopters. We develop an endogenous method for determining as a function of the new product diffusion parameters. Our model framework allows us to investigate how a firm might accelerate product purchases by providing introductory discount offers to a targeted group of potential adopters at product launch. We find that purchase acceleration frequently leads to a significant increase in total customer value.

Godes, David

doi: 10.1287/mksc.1110.0695pmid: N/A

We investigate a business-to-business context and ask when and why a firm should announce a reference program that commits the firm to facilitating the flow of information about the efficacy of its products from early adopters to potential late adopters. We model a monopolist manufacturer with a new innovation that can be sold to two potential customers. We demonstrate here two benefits of a reference program that relate not to an increase in later adopters' willingness to pay but to an increase in the willingness to pay of the early adopters themselves. The impact on the early adopters' willingness to pay arises in two ways as a result of their observation of the firm's commitment to information transmission. First, in a model of symmetric uncertainty, we show that the announcement of a reference program facilitates dynamic pricing by the manufacturer in the sense that it allows the firm to provide temporary exclusive use of the technology to one of the customers. This creates more value, which the manufacturer can extract via a higher price. In this way, a reference program can serve as a partial substitute for an exclusive-use contract. In a model with asymmetric information, we demonstrate that under certain conditions, the firm is able to use the reference program as a signalagain, to the early adopting customerthat its technology is of high quality. However, such a signal requires significant discounts to early adopters to ensure separation. As a result, a pooling equilibrium dominates in which the manufacturer fosters references regardless of its quality. Finally, by allowing the firms' private information to be stochastic, we show that separation may be a dominant outcome.

Conitzer, Vincent; Taylor, Curtis R.; Wagman, Liad

doi: 10.1287/mksc.1110.0691pmid: N/A

When a firm can recognize its previous customers, it may use information about their past purchases to price discriminate. We study a model with a monopolist and a continuum of heterogeneous consumers, where consumers have the ability to maintain their anonymity and avoid being identified as past customers, possibly at a cost. When consumers can freely maintain their anonymity, they all individually choose to do so, which results in the highest profit for the monopolist. Increasing the cost of anonymity can benefit consumers but only up to a point, after which the effect is reversed. We show that if the monopolist or an independent third party controls the cost of anonymity, it often works to the detriment of consumers.

Soysal, Gonca P.; Krishnamurthi, Lakshman

doi: 10.1287/mksc.1110.0693pmid: N/A

This study develops and estimates a dynamic model of consumer choice behavior in markets for seasonal goods, where products are sold over a finite season and availability is limited. In these markets, retailers often use dynamic markdown policies in which an initial retail price is announced at the beginning of the season and the price is subsequently marked down as the season progresses. Strategic consumers face a trade-off between purchasing early in the season, when prices are higher but goods are available, and purchasing later, when prices are lower but the stockout risk is higher. If the good starts providing utility as soon as it is purchased (e.g., apparel), consumers purchasing earlier in the season can also get more use from the product compared to those purchasing later. Our structural model incorporates three features essential for modeling the demand for seasonal goods: changing prices, limited availability, and possible dependence of total consumption utility on the time of purchase. In this model, heterogeneous consumers have expectations about future prices and product availability, and they strategically time their purchases. We estimate the model using aggregate sales and inventory data from a fashion goods retailer. The results indicate that, in the fashion goods context, ignoring consumers' expectations about future availability or the change in total consumption utility over the season can lead to biased demand estimates. We find that strategic consumers delay their purchases to take advantage of markdowns and that these strategic delays hurt the retailer's revenues. Retailer revenues facing strategic consumers are 9 lower than they would have been facing myopic consumers. Limited availability, on the other hand, reduces the extent of strategic delays by motivating consumers to purchase earlier. We find that the impact of strategic delays on retailer revenues would have been as high as 35 if there were no stockout risk. By means of counterfactual experiments, we show that the highest retailer profits are achieved by offering small markdowns early in the season. On the other hand, given current markdown percentages, the retailer can improve profits by carrying less stock as consumers accelerate purchases and purchase at higher prices when they anticipate scarcity in future periods. As long as the reduction in availability is not great, the profit gain from earlier higher-priced sales can overcome the loss resulting from the reduction in overall sales.

Shachat, Jason; Wei, Lijia

doi: 10.1287/mksc.1120.0704pmid: N/A

We use laboratory experiments to examine the relative performance of the English auction (EA) and the first-price sealed-bid auction (FPA) when procuring a commodity. The mean and variance of prices are lower in the FPA than in the EA. Bids and prices in the EA agree with game-theoretic predictions, but they do not agree in the FPA. To resolve these deviations found in the FPA, we introduce a mixture model with three bidding rules: constant absolute markup, constant percentage markup, and strategic best response. A dynamic specification in which bidders can switch strategies as they gain experience is estimated as a hidden Markov model. Initially, about three quarters of the subjects are strategic bidders, but over time, the number of strategic bidders falls to below 65. There is a corresponding growth in those who use the constant absolute markup rule.

Iyengar, Raghuram; Jedidi, Kamel

doi: 10.1287/mksc.1110.0702pmid: N/A

Quantity discount pricing is a common practice used by business-to-business and business-to-consumer companies. A key characteristic of quantity discount pricing is that the marginal price declines with higher purchase quantities. In this paper, we propose a choice-based conjoint model for estimating consumer-level willingness to pay (WTP) for varying quantities of a product and for designing optimal quantity discount pricing schemes. Our model can handle large quantity values and produces WTP estimates that are positive and increasing in quantity at a diminishing rate. In particular, we propose a tractable WTP function that depends on both product attributes and product quantity and that captures diminishing marginal WTP. We show how such a function embeds standard WTP functions in the quantity discount literature as special cases. We also demonstrate how to use the model to estimate the consumer value potential, which is the product of the premium a consumer is willing to pay and her volume potential. Finally, we propose a parsimonious experimental design approach for implementation.We illustrate the model using data from a conjoint study of online movie rental services. The empirical results show that the proposed model has good fit and predictive validity. In addition, we find that marginal WTP in this category decays rapidly with quantity. We also find that the standard choice-based conjoint model results in anomalous WTP distributions with negative WTP values and nondiminishing marginal willingness-to-pay curves. Finally, we identify four segments of consumers that differ in terms of magnitude of WTP and volume potential, and we derive optimal quantity discount schemes for a monopolist and a new entrant in a competitive market.

Peers, Yuri; Fok, Dennis; Franses, Philip Hans

doi: 10.1287/mksc.1110.0696pmid: N/A

We propose a method to include seasonality in any diffusion model that has a closed-form solution. The resulting diffusion model captures seasonality in a way that naturally matches the original diffusion model's pattern. The method assumes that additional sales at seasonal peaks are drawn from previous or future periods. This implies that the seasonal pattern does not influence the underlying diffusion pattern. The model is compared with alternative approaches through simulations and empirical examples. As alternatives, we consider the standard Generalized Bass Model (GBM) and the basic Bass Model, which ignores seasonality. One of the main findings is that modeling seasonality in a GBM generates good predictions but gives biased estimates. In particular, the market potential parameter is underestimated. Ignoring seasonality in cases where data of the entire diffusion period are available gives unbiased parameter estimates in most relevant scenarios. However, ignoring seasonality leads to biased parameter estimates and predictions when only part of the diffusion period is available. We demonstrate that our model gives correct estimates and predictions even if the full diffusion process is not yet available.