Showing papers in "Qme-quantitative Marketing and Economics in 2010"

What makes you click?—Mate preferences in online dating

Abstract: We estimate mate preferences using a novel data set from an online dating service. The data set contains detailed information on user attributes and the decision to contact a potential mate after viewing his or her profile. This decision provides the basis for our preference estimation approach. A potential problem arises if the site users strategically shade their true preferences. We provide a simple test and a bias correction method for strategic behavior. The main findings are (i) There is no evidence for strategic behavior. (ii) Men and women have a strong preference for similarity along many (but not all) attributes. (iii) In particular, the site users display strong same-race preferences. Race preferences do not differ across users with different age, income, or education levels in the case of women, and differ only slightly in the case of men. For men, but not for women, the revealed same-race preferences correspond to the same-race preference stated in the users’ profile. (iv) There are gender differences in mate preferences; in particular, women have a stronger preference than men for income over physical attributes.

Recording discrepancies in Nielsen Homescan data: Are they present and do they matter?

Abstract: We report results from a validation study of the Nielsen Homescan consumer panel data We use data from a large grocery retailer to match transactions that were recorded by the retailer (at the store) and by the Homescan panelist (at home) The matched data allow us to identify and document discrepancies between the two data sets in reported shopping trips, products, prices, and quantities We find that the discrepancies are largest for the price variable, and show that they are due to two effects: the first seems like standard recording errors (by Nielsen or the panelists), while the second is likely due to the way Nielsen imputes prices We present two simple applications to illustrate the impact of recording differences, and we use one of the applications to illustrate how the validation study can be used to adjust estimates obtained from Nielsen Homescan data The results suggest that while recording discrepancies are clearly present and potentially impact results, corrections, like the one we employ, can be adopted by users of Homescan to investigate the robustness of their results to such potential recording differences

Do private labels increase retailer bargaining power

Abstract: Like any new product, private label entry increases competition within a category leading to downward pressure on both wholesale and retail prices. But, given the higher margins for private labels and potential bargaining benefits for retailers, they have incentives to help private labels gain market share. The paper addresses two questions: First, do private labels enhance a retailer’s bargaining power with respect to manufacturers? Second, given the higher profitability and potential increase in bargaining power, does the retailer strategically set retail prices to favor and strengthen the private label? We find support for the “bargaining power” hypothesis, but qualified support for the “strategic retailer pricing” hypothesis. Retailers gain bargaining power through lower wholesale prices on imitated national brands. But the gain is greater in niche categories than in mass categories, suggesting that niche national brands with limited “pull” power lose greater bargaining power. In terms of strategic pricing, the retailer, on initially introducing the private label, strategically sets prices to help private labels gain market share in high volume mass market categories. But retail prices revert to the category profit maximizing price after a year when the private label gains a stable market share.

A nearly perfect market

Abstract: Internet shopbots allow consumers to almost instantly compare prices and other characteristics from dozens of sellers via a single website. We estimate the magnitude of consumer search costs and benefits using data from a major shopbot for books. For the median consumer, the estimated benefit from simply scrolling down to search lower screens is $6.55. This amounts to about 60% of the observed price dispersion and suggests that consumers face significant search costs, even in this “nearly-perfect” market. Price elasticities are relatively high compared to offline markets (−7 to −10 in our base model). Furthermore, contrary to the common assumption, search intensity is not correlated with greater price sensitivity. Instead, consumers who search multiple screens put relatively more weight on non-price factors like brand.

Switching costs, experience goods and dynamic price competition

Abstract: I analyze a dynamic duopoly with an infinite horizon where consumers are uncertain about their potential satisfaction from the products and face switching costs. I derive sufficient conditions for the existence of a Markov Perfect Equilibrium(MPE) where switching takes place each period. I show that when switching costs are sufficiently low, the prices in the steady state are lower than what they would have been when they are absent. This result is in contrast to those found in the literature. In the presence of low switching costs competition can be fiercer.

The effects of detailing on prescribing decisions under quality uncertainty

Abstract: 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.

Drivers of peak sales for pharmaceutical brands

Abstract: Peak sales are an important metric in the pharmaceutical industry. Specifically, managers are focused on the height-of-peak-sales and the time required achieving peak sales. We analyze how order of entry and quality affect the level of peak sales and the time-to-peak-sales of pharmaceutical brands. We develop a growth model that includes these two variables as well as control variables for own and competitive marketing activities. We find that early entrants achieve peak sales later, and they have higher peak-sales levels. High-quality brands achieve peak sales earlier, and their peak-sales levels are higher. In addition, quality has a moderating effect on the order of entry effect on time-to-peak-sales. Our results indicate that late entrants have longer expected time-to-peak-sales when they introduce a brand with high quality.

A simple test for distinguishing between internal reference price theories

Abstract: A large literature demonstrates the empirical importance of internal reference price effects. There are several theories regarding how and why these effects arise. We offer a simple test that distinguishes between the two leading theories based on economically rational behavior: price as a signal of quality and price as a predictor of future prices. Our test builds on differences in how past consumer purchases interact with internal reference prices. We first validate the reliability of our test by applying it to synthetic data. We then apply our test to purchases of ketchup and diapers and find: (1) quality signaling is the dominant mechanism behind reference price effects in both categories; (2) consistent with the quality-signaling theory, reference price effects diminish as various measures of consumer experience increase; but (3) in both categories there are many individuals for whom price-prediction effects dominate quality-signaling effects.

The diffusion of a new service: Combining service consideration and brand choice

Abstract: We propose an individual-level model of a two-stage service diffusion process. In the first stage, customers decide whether to “consider” joining the service. This (Consideration) stage is modeled by a hazard model. Customers who decide to consider the service move on to the Choice stage, wherein they choose among the service alternatives and an outside No Choice option. This stage is modeled by a conditional Multinomial Logit model. The service provider does not observe the transition in the first stage of potential customers who have yet to choose a brand. Such potential customers may have started to consider joining the service, yet chose the outside alternative in each period thereafter. One of the main contributions of the model is its ability to distinguish between these two non-adopter types. We estimated the model using data on the adoption process of newly introduced service plans offered by a commercial bank. We employed the hierarchical Bayes Monte Carlo Markov Chain procedure to estimate individual as well as population parameters. The empirical results indicate that the model outperforms competing models in breadth of analysis, model fit, and prediction accuracy.

Who should practice price discrimination using rebates in an asymmetric duopoly

Abstract: Price discrimination is generally thought to improve firm profits by allowing firms to extract more consumer surplus. In competition, however, price discrimination may also be costly to the firm because restrictive incentive compatibility conditions may allow the competing firm to gain market share at the discriminating firm’s expense. Therefore, with asymmetric competition, it may be the case that one firm would let the other firm assume the burden of price discrimination. We investigate optimal segmentation in a market with two asymmetric firms and two heterogeneous consumer segments that differ in the importance of price and product attributes. In particular, we investigate second-degree price discrimination under competition with explicit incentive compatibility constraints thus extending prior work in marketing and economics. Focusing on the managerial implications, we explore whether it would be profitable for either or both firms to pursue a segmentation strategy using rebates as a mechanism. We identify conditions under which one or both firms would want to pursue such segmentation. We find that segmentation lessens competition for the less price-sensitive consumer segment and that this results in higher profits to both firms. A key to understanding this result is that segmentation leads to consumer remixing. We establish the key result that if firms are asymmetric in their attractiveness to consumers, the disadvantaged firm in our model is more likely to pursue a segmentation strategy than its rival in equilibrium. We then ask whether this result prevails in practice. To this end, we explore competitive segmentation empirically and are able to verify that disadvantaged firms indeed pursue segmentation through rebates with greater likelihood.

Modeling strategic group dynamics: A hidden Markov approach

Abstract: With competition playing a critical role in market-based strategic planning and implementation, identifying and understanding competiton and competitive dynamics has become critical. In this vein, the strategic groups perspective has emerged as a powerful means to understand such competitive phenomena. Empirical approaches to model competitive dynamics within the strategic groups framework, however, have been piece meal as researchers typically resort to distinct sequential analysis by time period. To overcome the limitations of these simplistic approaches, we develop a hidden Markov model to study strategic group (competitive) dynamics. In this approach, we explicitly account for competitive dynamics over time by modeling strategic group memberships as latent states that follow a first-order Markov process. Thus, we explictly model the notion that firms adopt their strategy for the next time period based on their current strategy and respective outcomes. We illustrate the model with longitudinal data from COMPUSTAT on 63 public banks from the tri-state region of NY-OH-PA. The results show the proposed model to be superior to a number of viable alternative approaches that have been suggested in the literature. We find the existence of three strategic groups: the leveraged group has low current assets compared to current liabilities, high debt to equity, and high total borrowing to assets. The lending group consists of the largest banks that focus on lending with high ratios of gross loans to securities and gross loans to deposits. The balanced group has the largest number of banks where the values of the financial and product ratios are intermediate compared to the leveraged and lending groups. The asymmetries in the switching probabilites are also evident as there seems to be a higher probability of switching into the balanced group than switching out of this group. The switching probabilites are symmetric between the the leveraged and lending groups.

Competitive price-matching guarantees under imperfect store availability

Abstract: This paper analyzes the role of verification of product availability in the context of competitive price-matching guarantees (PMGs). PMGs involve a retailer matching any lower price offered by competition for an identical item. Until now, researchers focused on the scenario where customers can receive the lower price with a simple proof (e.g., weekly flyers). However, in reality, retailers reserve the right to verify the availability at the competitor location; if the product is not available there, then the price-match request might be declined. We develop a price competition model to investigate the effects of verification of availability on price decisions and profit levels of competing retailers. In our model, demand is driven by the availability levels of retailers as well as the price-search cost and store-switching cost incurred by customers. Price-search cost leads to two customer segments: uninformed ones who have no knowledge about prices, and informed ones who are knowledgeable about prices. On the other hand, store-switching cost determines how many customers search for the product at an alternative location because of high price or unavailability at their preferred retailers. Our analysis reveals, among others, that the outcome of availability verification is linked to three factors: price-search cost, store-switching cost, and the reservation prices of customer segments. Verification of availability allows retailers to price discriminate customers who could not be discriminated otherwise, specifically those belonging to the informed customer segment. Furthermore, it is a significant profit-enhancing mechanism only if there are switching customers in the market. Interestingly, even though customers view the verification of availability as a hassle, it can actually result in them paying lower retail prices by increasing the level of retail price competition.

Ownership coordination in a channel: Incentives, returns, and negotiations

Abstract: In many industries firms have to make quantity decisions before knowing the exact state of demand. In such cases, channel members have to decide which firm will own the units until demand uncertainty is resolved. The decision about who should retain ownership depends on the balance of benefit and risk to each member. Ownership, after all, is costly. Whichever member owns the units accepts the risk of loss if more units are produced than can be sold. But ownership also grants firms the flexibility to respond to demand once it becomes known by adjusting price. In this study, we analyze ownership decisions in distribution channels and how those decisions are affected by demand uncertainty. We model demand based on micro-modeling of consumer utility functions and capture demand uncertainty related to market size and price sensitivity. This study shows that as long as the degree of uncertainty about market size is intermediate, the retailer and the manufacturer both benefit when the manufacturer maintains ownership of the units. But when there is substantial uncertainty about market size, the retailer and the channel are better off if the retailer takes ownership but the manufacturer still prefers to maintain ownership. Thus, there is potential for channel conflict regarding ownership under high levels of uncertainty. We show that, using product returns, the manufacturer can achieve the same outcome under retailer ownership as under manufacturer ownership. This provides an additional new rationale for the prevalence of product returns. The first-best outcome (from the perspective of total channel profit), however, is under retailer ownership without product returns when uncertainty is high (i.e., product returns reduce the total channel profit). Negotiations between the manufacturer and the retailer can lead to the first-best outcome but only under quite restrictive constraints that include direct side payments by the retailer to the manufacturer and the retailer being pessimistic about its outside option (when an agreement cannot be reached) during the negotiation.

Leveraging uncertainty through backorder

Abstract: Business models based on postponement are being increasingly adopted by firms in categories ranging from consumer electronics and information technology to automobiles. Backorder is one example of this system wherein firm produces the product after receiving an order from the customer and they represent a stark contrast to the traditional Make-to-stock (MTS) system where firm anticipates demand and satisfies it from finished inventory. The popularity of postponement is primarily attributed to the operational efficiencies that it can generate for a firm in dealing with highly uncertain and dynamic demand environments. Our focus in this paper is on understanding the implications of the interaction of demand uncertainty and consumer heterogeneity for the optimality of these different systems. We show that the combination of these two forces requires the firm to use both backorder and MTS simultaneously. The optimality of backorder depends on the extent of demand uncertainty—products that exhibit relatively higher demand volatility are better candidates for backorder. Importantly, the combination of the two systems has significant implications for the firm’s product line decision (in terms of product qualities) and pricing.

Setting price or quantity: Depends on what the seller is more uncertain about

Abstract: We consider a seller with uncertain demand for its product. If the demand curve were certain, then setting price and setting quantity would be equivalent ways to frame the seller’s problem of choosing a profit-maximizing point on its demand curve. With uncertain demand, these become distinct sales mechanisms. We distinguish between uncertainty about the market size and uncertainty about the consumers’ valuations. Our main results are that (i) for a given marginal cost, an increase in uncertainty about valuations favors setting quantity whereas an increase in uncertainty about market size favors setting price; (ii) keeping demand uncertainty fixed, there is a nonmonotonic relationship between marginal costs and the optimal selling mechanism (setting price or quantity); and (iii) in a bilateral monopoly channel setting, coordination occurs except for a conflict zone in which the retailer’s choice of a selling mechanism deviates from the coordinated channel selling mechanism.

Erratum to: Competitive price-matching guarantees under imperfect store availability

Abstract: This paper analyzes the role of verification of product availability in the context of competitive price-matching guarantees (PMGs). PMGs involve a retailer matching any lower price offered by competition for an identical item. Until now, researchers focused on the scenario where customers can receive the lower price with a simple proof (e.g., weekly flyers). However, in reality, retailers reserve the right to verify the availability at the competitor location; if the product is not available there, then the price-match request might be declined. We develop a price competition model to investigate the effects of verification of availability on price decisions and profit levels of competing retailers. In our model, demand is driven by the availability levels of retailers as well as the price-search cost and store-switching cost incurred by customers. Price-search cost leads to two customer segments: uninformed ones who have no knowledge about prices, and informed ones who are knowledgeable about prices. On the other hand, store-switching cost determines how many Electronic supplementary material The online version of this article (doi:10.1007/s11129-010-9080-1) contains supplementary material, which is available to authorized users. A. Nalca (B) School of Business, Queen’s University, Kingston, ON, K7L 3N6, Canada e-mail: arcan.nalca@business.queensu.ca T. Boyaci · S. Ray Desautels Faculty of Management, McGill University, Montreal, QC, H3A 1G5, Canada T. Boyaci e-mail: tamer.boyaci@mcgill.ca S. Ray e-mail: saibal.ray@mcgill.ca