Sriram Venkataraman

The Effects of Online User Reviews on Movie Box Office Performance: Accounting for Sequential Rollout and Aggregation Across Local Markets

Our objective in this paper is to measure the impact (valence, volume, and variance) of national online user reviews on designated market area (DMA)-level local geographic box office performance of movies. We account for three complications with analyses that use national-level aggregate box office data: (i) aggregation across heterogeneous markets (spatial aggregation), (ii) serial correlation as a result of sequential release of movies (endogenous rollout), and (iii) serial correlation as a result of other unobserved components that could affect inferences regarding the impact of user reviews. We use daily box office ticket sales data for 148 movies released in the United States during a 16-month period (out of the 874 movies released) along with user review data from the Yahoo! Movies website. The analysis also controls for other possible box office drivers. Our identification strategy rests on our ability to identify plausible instruments for user ratings by exploiting the sequential release of movies across markets---because user reviews can only come from markets where the movie has previously been released, exogenous variables from previous markets would be appropriate instruments in subsequent markets. In contrast with previous studies that have found that the main driver of box office performance is the volume of reviews, we find that it is the valence that seems to matter and not the volume. Furthermore, ignoring the endogenous rollout decision does not seem to have a big impact on the results from our DMA-level analysis. When we carry out our analysis with aggregated national data, we obtain the same results as those from previous studies, i.e., that volume matters but not the valence. Using various market-level controls in the national data model, we attempt to identify the source of this difference. By conducting our empirical analysis at the DMA level and accounting for prerelease advertising, we can classify DMAs based on their responsiveness to firm-initiated marketing effort (advertising) and consumer-generated marketing (online word of mouth). A unique feature of our study is that it allows marketing managers to assess a DMAs responsiveness along these two dimensions. The substantive insights can help studios and distributors evaluate their future product rollout strategies. Although our empirical analysis is conducted using motion picture industry data, our approach to addressing the endogeneity of reviews is generalizable to other industry settings where products are sequentially rolled out.

Blogs, Advertising, and Local-Market Movie Box Office Performance

We measure the effects of pre-and postrelease blog volume, blog valence, and advertising on the performance of 75 movies in 208 geographic markets in the United States. We attribute the variation in blog effects across markets to differences in demographic characteristics of markets combined with differences across demographic groups in their access and exposure to blogs as well as their responsiveness conditional on access. We study the effects of prerelease factors on opening day box office performance and of pre-and postrelease factors on box office performance one month after release. Our estimation accounts for confounding factors in the measurement of these effects via the use of instrumental variables. We find considerable heterogeneity in the effects across consumer-and firm-generated media and across geographic markets, with gender, income, race, and age driving across-market differences. Release day performance is impacted most by prerelease blog volume and advertising, whereas postrelease performance is influenced by postrelease blog valence and advertising. Across markets, there is more variance in advertising and blog valence postrelease elasticities than there is in blog volume prerelease elasticities. We identify the top 20 markets in terms of their elasticities to each of these three instruments. Further, we classify markets in terms of their sensitivities across these three instruments to identify the most sensitive markets that studios can target with their limited release strategies. Finally, we characterize the extent to which studios could have improved their limited release strategies by identifying the overlap between the actual release markets and the most responsive ones. We find that at the time of first-release studios cover only 53% of the most responsive advertising markets and 44% of the most responsive markets to prerelease blog volume in their limited release strategies, implying considerable room for improvement if these were the only metrics to assess those strategies. This paper was accepted by Gerard P. Cachon, marketing.

An Empirical Model of Drug Detailing: Dynamic Competition and Policy Implications

The practice of detailing in the marketing of prescription drugs is undergoing significant changes. For instance, in September 2013, the Physician Payment Sunshine Act went into full effect. The accompanying transparency requirements have prompted physician practices and hospitals to severely restrict pharmaceutical sales representatives’ direct access to their physicians. Despite all the attention in the popular press, scant scholarly research has investigated how these restrictions on physician access impact physician prescription behavior and competitive detailing to physicians. To analyze the impact of these restrictions, we develop a structural model of how pharmaceutical firms compete dynamically to schedule detailing to physicians. Detailing activities are known to have significant carryover effects that are captured in a first-stage model of physicians’ demand for prescription drugs. We also specify detailing policy functions that describe each firm’s observed detailing actions. In a second stage, we estimate a model that describes costs of detailing, assuming that the observed detailing levels are consistent with a Markov perfect Nash equilibrium. The estimated structural model is used to examine the implications of restrictions on the amount of detailing via counterfactual simulations. We find that restriction policies would increase the market share of a nondrug-treatment-only option but impact firms asymmetrically; firms that are strong in detailing and/or rely more on detailing would be hurt more. Unexpectedly, a policy that imposes a ceiling on detailing frequency could significantly reduce detailing of all firms in the market, including those firms with average detailing levels below the ceiling, and effectively would soften competition between firms and enhance their profits. This paper was accepted by J. Miguel Villas-Boas, marketing .

Price Reactions to Rivals' Local Channel Exits

In this paper, we study the effect of a firm’s local channel exits on prices charged by incumbents remaining in the marketplace. Exits could result in higher prices due to tempered competition or lower prices due to reduced colocation or agglomeration benefits. The net effect of these two countervailing forces remains unknown. In addition, little is known about how this effect could change depending on incumbents’ geographic locations. We address this research gap by examining new car price reactions by incumbent multiproduct automobile dealerships who experience the exit of a Chrysler dealership in their local markets. We find evidence that the competition effect exceeds the colocation effect: prices increase by about 1% (

Predicting the Consequences of Marketing Policy Changes: A New Data Enrichment Method with Competitive Reactions

318) following an exit relative to the price change in the absence of an exit. More important, we find that the price increase is lower at dealerships more proximate to the exiting dealership than dealerships farther away for the same set of cars available across these locations. This finding suggests differences in the extent of the two forces (competition and agglomeration) at different distances from the closed dealership. We assess the generalizability of our results by looking at the impact of GM’s closure of Pontiac dealerships. Taken together, our results inform consumers, firms, and policymakers about possible implications of an exit.Data, as supplemental material, are available at http://dx.doi.org/10.1287/mksc.2015.0952.

The Debate on Influencing Doctors' Decisions: Are Drug Characteristics the Missing Link?

This article introduces a new data enrichment method that combines revealed data on consumer demand and competitive reactions with stated data on competitive reactions to yet-to-be-enacted, unprecedented marketing policy changes. The authors extend the data enrichment literature to include stated competitive reactions, collected from subject-matter experts through a conjoint experiment. The authors apply their method to investigate hypothetical and unprecedented sales force policy changes of pharmaceutical companies. The results from the data enrichment method have high face validity and lead to various unique insights compared with using revealed data only. The authors find that only a very large sales force decrease initiated by the market leader triggers all competitors to decrease their sales force as well, leading to substantial profit increases for each firm. With respect to sales force allocation, when competitors decrease their sales force, they mainly decrease the reach of detailing across doctors, rather than decreasing the number of details to the most-visited doctors. The proposed data enrichment method provides managers with a powerful tool to, ex ante, predict the consequences of unprecedented marketing policy changes.