Paulo Albuquerque

Mapping Online Consumer Search

In this paper, we propose a method to visualize online consumer search in so-called product search maps. Manufacturers can use these maps to understand how consumers search for competing products prior to choice, including how information acquisition and product search is organized along brand-, product attributes-, and/or price related search strategies. The product search maps also inform manufacturers about the competitive structure in the industry and about the contents of consumer consideration sets. Our proposed method first defines a product search network, consisting of the products and links that designate if a product is searched conditional on searching other products. We next model this network using a stochastic, hierarchical and asymmetric multidimensional scaling framework and decompose the product locations as well as the product-level influences using product attributes. The advantages of the approach are two-fold. First, we simultaneously visualize the positions of products and the direction of consumer search over products in a perceptual map of “search proximity.�? Second, we explain and relate the dimensions of the map using observed product attributes. We empirically apply our approach to consumer search for digital camcorders at Amazon.com and provide a number of managerial implications.

Selection and Ordering of Linear Online Video Ads

This paper studies the selection and ordering of in-stream ads in videos shown in online content publishers. We propose an allocation algorithm that uses a collective measure of price and quality for each ad and factors in slot-specific continuation probabilities to maximize publisher revenue. The algorithm is based on cascade models and uses a dynamic programming method to assign linear (video) ads to slots in an online video. The approach accounts for the negative externality created by lower quality ads placed in a video, leading to viewer exit and thereby preventing the publisher from showing the subsequent ads scheduled in that session. Our algorithm is scalable and suited for real-time applications. A large log of viewer activity from a video ad platform is used to empirically test the algorithm. A series of simulations show that our algorithm, when compared to other algorithms currently practiced in industry, generates more revenue for the publisher and increases viewer retention.

The Impact of Innovation on Product Usage: A Dynamic Model with Progression in Content Consumption

We propose a dynamic model to explain product usage in categories characterized by frequent updates and progression of consumer involvement. In our setting, product updates introduce additional content that, to be fully enjoyed, requires increasing consumer experience and involvement with the product. Consumers gain experience through recurrent product usage and content consumption. Examples of such categories include TV series, computer games, mobile apps, books, movies, and educational products. Our modeling approach builds on theory from experiential products to define the product usage utility as a function of intrinsic consumer preferences, satiation, social interactions, and future usage. We use data on consumer participation from the online computer game World of Warcraft to empirically test our model. We show that the success of product updates strongly depends on consumer heterogeneity, on the rate of content consumption, and on the social interaction of consumers. Using our approach, we are able to quantify the value of a product update for the firm. We also provide managerial recommendations to improve scheduling of product innovation and offer insights about consumer segmentation and targeting to increase product usage.

A Continuous Time Model of Product Usage: Measuring the Effect of Product Design and Rewards in Online Games

The paper proposes a demand model of product usage in continuous time. Our setting is flexible enough to simultaneously explain usage frequency, duration of usage, and consumer response to product features and firm’s actions. Based on product usage literature, we define the main components of our model to include intrinsic motivations, product characteristics, external rewards provided by the firm, and past consumption. In our model, the influence of past consumer choices on decisions takes the form of a cue-based habit formation mechanism. The model is estimated on a novel dataset of online game usage where we observe the usage decisions of a large sample of individuals with a periodicity of 10 minutes. We provide managerial insights on product design and reward systems by testing different product configurations and measuring shirk with changes in reward frequency and product complexity. The proposed model can be applicable to a large number of product categories characterized by repeated product usage or content consumption.

The Probit Choice Model under Sequential Search with an Application to Online Retailing

We develop a probit choice model under optimal sequential search and apply it to the study of aggregate demand of consumer durable goods. In our joint model of search and choice, we derive a semi-closed form expression for the probability of choice that obeys the full set of restrictions imposed by optimal sequential search. Our joint model leads to a partial simulation-based estimation that avoids high-dimensional integrations in the evaluation of choice probabilities and that is particularly attractive when search sets are large. We illustrate the advantages of our approach using aggregate search and choice data from the camcorder product category at Amazon.com. We show that the joint use of search and choice data provides better performance in terms of inferences and predictions than using search data alone and leads to realistic estimates of consumer substitution patterns.

Applying structural models in a public policy context: Methods and Applications in Marketing Management, Public Policy, and Litigation Support

We present an illustration of how marketing and structural models can be applied in a public policy context. We describe the demand model in Albuquerque and Bronnenberg (2012) to evaluate the impact of the 2009 federal policy measure known as the “Car Allowance Rebate System” program (or “Cash for Clunkers”) on prices and demand in the auto sector.

Evaluating the Impact of Fat Taxes: The Need to Account for Purchases for In-Home and Out-Of-Home Consumption

To tackle rising obesity rates, countries such as UK, Mexico, France, Hungary, as well as some states of the United States, have introduced taxes on snacks with high-sugar content. These are commonly known as “sugar taxes”. A large part of consumption of the snacks targeted by these taxes, such as chocolates and sugar-sweetened soft drinks, takes place away fromhome. Hence, it is crucial for policy makers to understand the impact of “sugar taxes” on purchases made at away-from-home locations, in addition to the traditional evaluation of purchases at grocery stores for consumption at home. Using a unique data set that tracks weekly household purchase of chocolates in both channels, for at-home and for away-from-home consumption, we estimate separate price elasticities, and find consumers are less price sensitive for away-from-home purchases compared to at-home purchases and also find evidence of cross-channel effects. We simulate the impact of price increases ranging from +5% to +10%. We find that including only at-home purchase data leads us to underestimate the impact of the tax by 15% when compared to the scenario where we include purchases made both at-home and away-from-home.

Competition and Firm Service Reliability Decisions: A Study of the Airline Industry

To understand the impact of strategic competition on organizational service reliability decisions, this study investigates if firms in the airline industry consider competitors’ actions when making their service reliability decisions.We apply two methods – a seemingly unrelated regression and a discrete game among airlines – to analyze data from the U.S. Bureau of Transportation Statistics on flight cancellations rates and duration of flight delays. We find that competitive effects lead firms to differentiate themselves on the levels (low vs. high) and dimensions (cancellation vs. delay) of service reliability.In counterfactual analyses, we show that commitment by a firm to low cancellation rates leads to improved service reliability in the overall market. Internal programs to improve service reliability, such as on-time bonuses, can significantly improve service reliability, however, ignoring competitive interactions can lead to the over-estimation of the impact of these programs on service reliability by more than 10%.