Literature on reference prices suggests that consumers carry a reference price for a brand in their memory, which they use to evaluate brands when making purchases. Further, research has shown that consumers respond more to losses (prices that are higher than reference prices) than to gains (lower prices). Many reference price models have been estimated using household purchase data in several product categories. A notable omission is that even though the reference price is an individual level construct, models have been estimated at the household level. In this study we examine whether an individual level reference price model for each member within a household provides different estimates and insights than the household level model. We seek to understand the magnitude of bias in the parameters of a brand choice model if one estimates the model at a household level. Further, we assess how firms will vary their targeted promotions if they use individual level estimates and how it affects their profits.We use a unique data set that identifies brand choices made by individual customers within a household to answer the above questions. We estimate two different reference price models using a random coefficients multinomial logit specification in three different product categories. Since frequent buyers are expected to have well-formed reference prices relative to infrequent buyers, we focus on the difference between these two groups. We find that customer level estimates are significantly different from those obtained at the household level and that frequent buyers are more price sensitive and respond differently to reference prices than infrequent buyers within the same household. We show that using individual customer level estimates to target households with a promotion, results in significantly higher profits and that ignoring reference price effects can lead to significantly reduced profits.

The over-the-top (OTT) subscription video streaming industry has witnessed significant growth and heightened competition in recent years, marked by the influx of new players. At the same time, competing services are forming new alliances that facilitate consumer multihoming. For instance, Amazon Prime Video has partnered with services such as HBO Max and Paramount+ to enhance the combined viewing experience for consumers through seamless integration. The authors build a game-theoretic model with horizontally differentiated services to examine how an alliance facilitating multihoming between two competing services affects price competition in the market. They find that the alliance's impact on price competition depends on the level of content differentiation in the market: Competition intensifies when differentiation is high but relaxes when differentiation is low. The alliance benefits the partnering services as long as the differentiation is not too high, and interestingly, it may increase the profitability of a third nonpartnering service when differentiation is sufficiently low. The authors show that consumer surplus increases under the alliance, even if price competition is relaxed. They also investigate a focal service's decision to partner with one of two competing services and find that it prefers to partner with a service that has high-quality content but a smaller loyal base. This research offers insights into the current landscape of the OTT video streaming market and provides implications for both managers and policymakers.

Much of the extant empirical work on consumers' grocery purchases employ models that are estimated on household scanner panel data. A known limitation of these models is that households may have multiple decision makers, and a decision maker may have brand preferences and marketing mix sensitivities that are distinct from other decision makers in the household. We seek to study whether models using individual customer data provide substantially different insights and managerial implications relative to models that use household data. This important issue has not been addressed in the literature, possibly due to limitations of scanner panel data. Using a unique data set that identifies choices made by individual customers within a household, we estimate multinomial choice models at the household level with and without incorporating intra-household heterogeneity using Markov Chain Monte Carlo (MCMC) procedures. We incorporate controls for unobserved heterogeneity by estimating random coefficients models which allows the brand preferences and the price sensitivity parameters to vary across households. We find that in each product category the estimates obtained at the customer level are significantly different from those obtained at the household level. Our findings imply that targeting promotions based on customer level estimates will result in outcomes that are significantly more profitable relative to targeting based on household level estimates.

Teachers at over 80% of all K–12 public and charter schools in the United States use online crowdfunding platforms to acquire classroom supplies, but they reach their goals only 75% of the time. Platforms such as DonorsChoose provide a framework through which teachers can reach potential donors using an essay that outlines their needs. Known as an appeal in fundraising language, this textual information provides a brief description of the students in a class, their needs, and how fundraising will influence their learning objectives. We study the role of stylistic aspects of an appeal that affect the success of fundraising and examine how framing information provided on crowdfunding platforms influences donor behaviors. We find that longer appeals attract lower donations and hurt funding success, but the effect is moderated by sentiment and sophistication. Sophistication of the appeal has a positive effect on fundraising and the amount donated. Providing information on the state of a project has a positive effect on donations made by subsequent donors, a result that corroborates reinforcement models of donor behavior; individuals share a burden when supporting charitable causes and donate at least as much as the minimum donated.

Managers, let stockpiling be but at a higher price—don’t hope to cut stockpiling by lopping off promotions.

Bundling is the practice of selling two or more products together, often at a discounted price. In this article, we extend the concept of bundling to a wide variety of choice settings. We argue that bundle choice covers consumer decision scenarios, which differ with respect to three key dimensions: the number of product categories in the bundle, the party in the distribution system who constructs the bundles, and the time frame of the bundle choice decision. These situational differences are important, from the standpoint of constructing an appropriate choice model and developing an appropriate framework for managerial decision-making. We describe five research perspectives prevalent in bundle choice research (i.e., economic, attribute-based, psychological, multi-category choice, and bundle dynamics). We provide detailed discussion of several areas of current interest: and identify unresolved issues in bundling research: understanding the multiple rationales behind bundling strategies, specification and calibration of bundle choice models, and impact of Big Data, and optimal bundle design. We conclude that bundle choice research provides rich opportunities for collaboration among economists, psychologists, and choice theory experts in marketing science.

Price-matching guarantees PMGs are offered in a wide array of product categories in retail markets. PMGs offer consumers the assurance that, should they find a lower price elsewhere within a specified period after purchase the retailer will match that price and refund the price difference. The goal of this study is to explain the following stylized facts: 1 many retailers that operate both online and offline implement PMG offline but not online; 2 the practices of PMG vary considerably across retail categories; and 3 some retailers launch specialized websites that automatically check competitors' prices for consumers after purchase. To this end, we build a sequential search model that endogenizes consumers' pre-and postpurchase search decisions. We find that PMG expands retail demand but intensifies price competition on two dimensions. PMG drives retailers to offer deeper promotions because it increases the overall extent of consumer search, which we call the primary competition-intensifying effect. We also find a new secondary competition-intensifying effect, which results from endogenous consumer search. As deeper promotions incentivize consumers to continue price search, retailers are forced to lower the "regular" price to deter consumers from searching. The strength of the secondary competition-intensifying effect increases with the ratio of product valuation to search cost, which explains the variation in PMG practices online versus offline and across retail categories. We show that an asymmetric equilibrium exists such that one retailer offers PMG while the other does not. In this equilibrium, the PMG retailer may benefit from launching a price check website to facilitate consumers' postpurchase search.This paper was accepted by J. Miguel Villas-Boas, marketing.

Many products have different attributes which appeal to the different segments of the market. We investigate how firms should position their products in a multi-attribute product market where consumers are heterogeneous in (1) the product attributes that they care about, and (2) their willingness to pay for product quality. We develop a duopoly model where each firm offers a product which has three attributes. There are two customer segments in the market; each segment values only two attributes of the product but not the third one. We assume that customers are heterogeneous in their willingness to pay for the quality of product attributes. In a two-stage model, where firms first simultaneously set the level of product attributes and then price the product, we find four types of positioning equilibrium, all of which are of Min-Max kind. If the range of common attribute (the attribute that both customer segments appreciate) is high enough, firm only differentiate in this attribute and agglomerate on unique attributes (the attributes that only one segment appreciate). If the range of common attribute is low enough, firms differentiate only on unique attributes. The differentiation is never enough on only one of the unique attributes, and is never necessary on all three attributes. Our results have managerial implication for segmentation, targeting and positioning in a competitive market.

Product lines are ubiquitous. For example, Marriott International manages high-end ultra-luxury hotels e.g., Ritz-Carlton and low-end economy hotels e.g., Fairfield Inn. Firms often bundle core products with ancillary services or add-ons. Interestingly, empirical observations reveal that industries with ostensibly similar characteristics e.g., customer types, costs, competition, distribution channels, etc. employ different bundling strategies. For example, airlines bundle high-end first class with ancillary services e.g., breakfast, entertainment while hotel chains bundle ancillary services e.g., breakfast, entertainment at the low-end. We observe, unlike hotel lines that are highly differentiated at different geographic locations, airlines suffer low core differentiation because all passengers first-class and economy are at the same location i.e., same plane, weather, delays, cancellations, etc.. In general, we find product lines with low core differentiation e.g., airlines, amusement parks routinely bundle high-end while product lines with highly differentiated cores e.g., hotels, restaurants routinely bundle low-end. High-end bundling makes the high-end more attractive, increasing line differentiation less intraline competition while low-end bundling decreases line differentiation. Therefore, bundling allows optimal differentiation given a differentiation constraint complex costs. Last, firms may use strategic bundling for targeting in their core products; e.g., low-end hotels bundle targeted add-ons unattractive to high-end consumers such as lower-quality breakfasts and slower Internet.Data, as supplemental material, are available at https://doi.org/10.1287/mksc.2016.1004.

Increased sales due to promotions could be at the expense of competitors: such sales come from consumers with relatively weak brand preferences. However, increased sales from brand loyal consumers could well cannibalize sales of the promoted brand. An unintended consequence of promotions is that loyal consumers who otherwise would be willing to pay high prices may strategically stockpile at low prices to reduce their cost. What is its impact on firms’ profits? How should firms adapt their pricing to consumer stockpiling? To answer these questions we analyze an infinite horizon dynamic model of competition under duopoly and derive the Markov Perfect Equilibrium pricing strategies.Contrary to intuition we find that strategic stockpiling by loyal consumers at low prices does not reduce firms’ long-run profits if (i) initial consumer inventory is zero and (ii) firms employ the Nash equilibrium strategies that maximize the present value of future profits. Managers’ perception of losses probably reflects the fact that they encounter situations in which consumers have stockpiled in the past. We then analytically derive an upper bound on the losses after consumer stockpiling and show that it is relatively small. We derive the mixed strategy equilibrium that serves as a guide for managers on how to adapt pricing strategies to meet the challenge of stockpiling by loyal consumers. A particularly novel aspect of these strategies is that firms’ equilibrium pricing distributions can have a mass point in the interior of the support. Further, when the equilibrium pricing is compared to the situation with no stockpiling, we find that firms move away from frequently promoting below the stockpiling threshold, and moreover the probability of charging the reservation price increases. Finally, a prediction of our model is a positive inter-temporal correlation in prices implying, somewhat counter-intuitively, that in equilibrium deep promotions are followed by deep promotions.

An examination of brand prices in several categories reveals that the distribution of prices is multimodal, with firms offering shallow and deep discounts. Another interesting feature of these distributions is that they may have holes in the interior of the support. These pricing distributions do not occur in extant theoretical models of price promotions. We develop a dynamic model of competition in which some price-sensitive consumers stockpile during periods of deep discounts. A game-theoretic analysis of our model generates a multimodal pricing distribution with a hole in the interior of the support. Consumer stockpiling in our model also gives rise to negative serial correlation in prices. This is consistent with our empirical observation of the pricing distribution of several brands across multiple categories in the IRI marketing data set. We generate several interesting insights into firms' optimal promotional strategies and their interplay with the clientele mix, market structure, and other market factors. We find that, in equilibrium, stockpiling by price-sensitive consumers neither harms nor benefits firms when they adopt equilibrium strategies. Interestingly, when price-sensitive consumers stockpile, even increased consumption as a result of stockpiling does not lead to higher profits for firms.

We consider a publisher that earns advertising revenue while providing content to serve a heterogeneous population of consumers. The consumers derive benefit from consuming content but suffer from delivery delays. A publisher's content provision strategy comprises two decisions: (a) the content quality (affecting consumption benefit) and (b) the content distribution delay (affecting consumption cost). The focus here is on how a publisher should choose the content provision strategy in the presence of a content pirate such as a peer-to-peer (P2P) network. Our study sheds light on how a publisher could leverage a pirate's presence to increase profits, even though the pirate essentially encroaches on the demand for the publisher's content. We find that a publisher should sometimes decrease the delivery speed but increase quality in the presence of a pirate (a quality focused strategy). At other times, a distribution focused strategy is better; namely, increase delivery speed, but lower quality. In most cases, however, we show that the publisher should improve at least one dimension of content provision (quality or delay) in the presence of a pirate.

Online advertising has transformed the advertising industry with its measurability and accountability. Online software and services supported by online advertising is becoming a reality as evidenced by the success of Google and its initiatives. Therefore, the choice of a pricing model for advertising becomes a critical issue for these firms. We present a formal model of pricing models in online advertising using the principal–agent framework to study the two most popular pricing models: input-based cost per thousand impressions (CPM) and performance-based cost per click-through (CPC). We identify four important factors that affect the preference of CPM to the CPC model, and vice versa. In particular, we highlight the interplay between uncertainty in the decision environment, value of advertising, cost of mistargeting advertisements, and alignment of incentives. These factors shed light on the preferred online-advertising pricing model for publishers and advertisers under different market conditions.

We model a supply chain consisting of a national brand manufacturer and an independent manufacturer, both of whom are potential suppliers of store brand to a single retailer. The retailer serves two customer segments—a quality sensitive segment (high type) and a price sensitive (low type) segment. The retailer serves these two segments by targeting the national and store brands to the quality and price sensitive segments, respectively. When the national brand manufacturer supplies the store brand he internalizes the effect of store brand quality on the national brand's retail prices. This leads the national brand manufacturer to choose a lower store brand quality than the independent manufacturer. This decrease in store brand quality has the benefit of increased revenues from the high type customers along with an associated cost of decreased revenues from the low type customers. Thus, when the benefit outweighs the cost the retailer chooses the national brand manufacturer to supply the store brand. We show that the retailer will choose the national brand manufacturer to supply the store brand when (a) the size of the high type customer segment is large relative to the low type customer segment, (b) the valuations of the high type customer segment is large relative to the low type customer segment, and (c) the retailer's margin requirement on the store brand is not very high. Overall, these results suggest that retailers who serve a bigger sized quality (price) sensitive clientele would have the national brand (independent) manufacturer supply the store brand.

Empirical examination of the pricing policies of brands in several categories reveals that the pricing distribution is multi-modal with firms offering shallow and deep discounts with varying frequencies. Another interesting feature of these pricing distributions is that the modes are in the interior of the support. However, extant theory on price promotions predicts that the equilibrium pricing density will be bi-modal and the modes will be at the ends of the support of the distribution. In this study, we develop a dynamic game-theoretic model which allows for inter-temporal shifts in demand that may result from some consumers’ stockpiling at promotional prices. We examine how such behavior affects firms’ pricing strategy in a setting where firms and consumers interact repeatedly over an infinite horizon. The pricing distributions predicted by our theory are remarkably consistent with the pricing patterns observed in practice. The model allows us to generate many new and interesting insights on the optimal promotional strategies of firms and its interplay with the clientele mix, market structure and other market factors. Interestingly, we find that the stockpiling threshold is decreasing in the consumer’s willingness to stockpile. The model also highlights whether or not the stockpiling occurs in equilibrium depends on the market structure, mix of price sensitive, price insensitive and opportunistic consumers and discount rate.

Extant theoretical models suggest that greater consumer loyalty increases a firm’s market power and leads to higher prices and fewer price promotions (Klemperer, Quarterly Journal of Economics 102(2):375–394, 1987a, Economic Journal 97(0):99–177, 1987b, Review of Economic Studies 62(4):515–539, 1995; Padilla, Journal of Economic Theory 67(2):520–530, 1995). However, in some markets large, national brands that are able to generate more consumer loyalty than their rivals offer lower prices and promote more frequently. In this paper, we develop a two-period game-theoretic, asymmetric duopoly model in which firms differ in their ability to retain repeat, loyal buyers. In this market, we demonstrate that it is optimal for a firm that generates more loyalty to offer a lower average price and promote more frequently than a weaker competitor. Numerical analysis of a more general infinite period version of this asymmetric model leads to three additional results. First, we show that there is an inverted-U relationship between a weak firm’s ability to attract repeat, loyal consumers and strong firm profits. Second, we show that the relative ability of firms to attract repeat buyers affects whether serial and contemporaneous price correlations are positive or negative. Finally, we highlight the effect of dynamics on firms’ expected prices and profits.

Why is it that in some markets only a few firms find it optimal to complement their retail channels with a direct Internet channel while other firms do not?

How can supermarkets use the vast data they have to design strategies to compete for large-basket shoppers, potentially their most profitable customers? We say, analyze the data to glean basket composition of heterogeneous consumers. Of theoretical and practical interest is the question, will our suggestion improve supermarket profits, and if so, by what pricing strategies? By answering this we can also answer the question, do results of extant research on single-product marketing that using such information intensifies competition and lowers profits, generalize to multiproduct marketing by supermarkets that carry several products, and whose patrons purchase multiple items? We derive equilibrium data-based intelligent pricing strategies that also produce increased supermarket profits. What is more interesting is our result that data analysis is profitable whether or not a competitor undertakes data analysis. If not too costly, implementing data analysis is a dominant strategy. Moreover, with comprehensive data analysis connecting basket information and household data, stores can increase profits further by targeting rewards at individual households, thereby segmenting the market more completely. In contrast to past research findings, we show that for supermarkets, even under competition, use of information on past purchases enables intelligent pricing, better segmentation, and higher profits.

In this study, we examine firms' incentive to offer customized products in addition to their standard products in a competitive environment. We offer several key insights. First, we delineate market conditions in which firms will (will not) offer customized products in addition to their standard products. Surprisingly, we find that when firms offer customized products they are able to not only expand demand, but can also increase the prices of their standard products relative to when they do not. Second, we find that when a firm offers customized products it is a dominant strategy for it to also offer its standard product. This result highlights the role of standard products and the importance of retaining them when firms offer customized products. Third, we identify market conditions under which ex ante symmetric firms will adopt symmetric or asymmetric customization strategies. Fourth, we highlight how the degree of customization offered in equilibrium is affected by market parameters. We find that the degree of customization is lower when both firms offer customized products relative to the case when only one firm offers customized products. Finally, we show that customizing products under competition does not lead to a prisoner's dilemma.