Conference Sessions - Jesse H. Jones Graduate School of ...

More documents

Recommendations

Info

FC07 4 - Price Competition in the Spanish Nondurable Retail Industry Jaime Romero, Associate Professor, University Autonoma Madrid, Fac. CC. Economicas, Avda. Tomas y Valiente, 5, Madrid, 28049, Spain, jaime.romero@uam.es, Daniel Klapper, Martin Natter In this paper we develop a model of spatial competition between retailers. In particular we study price competition between a very large and representative sample of Spanish retailers. These retailers offer a wide variety of products including packed food, fresh meat, seafood, fruits and vegetables and drugstore articles. They all provide non durable products. As many retail markets across the world the Spanish retail market for food products has experienced the exit of small and the entry of large retail corporations. However there still exists a mixture of different store types, ranking from small independently and family owned operated stores to large chain stores. Based on the model of retail competition and an application of the difference in difference estimator we study the extent of price competition that is affected by different store types and regional effects. Regional effects are driven by local economic effects such as real estate prices or discretionary income and the density of competition between retailers which is measured e.g. by the distance between retailers or assortments. Our results show that the differences in prices across retailers and markets are strongly affected by regional effects. Local differentiation between retailers limits the competitive threat and allows smaller retailers to survive even in the presence of large and chain wide operated retail stores. ■ FC07 Founders I New Directions in Word of Mouth Cluster: Special Sessions Invited Session Chair: Jonah Berger, University of Pennsylvania, PA, United States of America, jberger@wharton.upenn.edu Co-Chair: Andrew Stephen, INSEAD, Fontainebleau, France, andrew.stephen@INSEAD.edu 1 - How the Frequency and Pattern of Social Influence Over Time Shape Product Adoption Raghu Iyengar, University of Pennsylvania, 3730 Walnut Street, 700 Jon M Huntsman Hall, Philadelphia, PA, United States of America, riyengar@wharton.upenn.edu, Jeffrey Cai, Jonah Berger Social influence shapes diffusion and new product adoption. But how does the quantity of social influence (e.g., number of doses) and its distribution over time impact new product adoption? Does hearing about a product from multiple social contacts increase adoption, and if so, is it better to have such doses concentrated over a short period or spread out over time? We test whether multiple doses of social influence boost adoption, and further, whether influence decays over time and is increased by concentration. Analysis of the adoption of both a new website and hundreds of academic papers indicates that (1) people are more likely to adopt a product if they have received multiple doses of social influence. Importantly, however, (2) the impact of influence decays over time and (3) there is little evidence of concentration. While hearing about a product today has a stronger impact on behavior than a dose a month ago, the relationship between dose concentration and adoption is concave such that multiple doses in a short period has little added effect. That said, the relative importance of decay versus concentration suggests that concentrating two doses in a given period will increase adoption rather than spreading them out. Overall these results provide insight into the mechanisms behind new product adoption and have important managerial implications for getting new products to catch on. 2 - The Complementary Roles of Traditional and Social Media Publicity in Driving Marketing Performance Andrew Stephen, INSEAD, Fontainebleau, France, andrew.stephen@INSEAD.edu, Jeff Galak The media landscape has dramatically changed, with traditional media (e.g., newspapers, television) now supplemented by social media (e.g., blogs, online communities). This situation is not well understood with respect to the relative impacts of these media types on marketing performance (e.g., sales), and how they influence each other. These issues are examined using 14 months of daily count data for sales and media activity for a micro-lending website. Multivariate time series count data pose a number of statistical challenges, which are overcome using a copula-based multivariate autoregressive count model. The authors find that both traditional and social media affect sales, directly and indirectly through effects on each other. While the unit sales impact for traditional media is larger than for social media, the greater frequency of social media activity results in it having a comparable effect to traditional media in the case of blogs, and a larger effect in the case of online communities. Overall, the results emphasize the critical role that interactive, conversational online social media plays in driving sales. MARKETING SCIENCE CONFERENCE – 2011 56 3 - Promotional Reviews Yaniv Dover, Yale University, New Haven, CT, 06520, United States of America, Yaniv.Dover@yale.edu, Dina Mayzlin In recent years, we have witnessed the proliferation of online consumer reviews of products and services. Researchers have studied the impact of reviews on sales as well as the dynamics of reviews that arise from social factors. While reviews are clearly popular and impactful, there have always been concerns about the authenticity of reviews since firms can manufacture positive reviews for their products (see Mayzlin 2006 and Delarocas 2006). Here we propose an empirical method for detecting the existence of manipulation of reviews that differs from current work (see, for example, Kornish 2009). We then apply this method to investigate under which conditions we expect to see the greatest amount of manipulation. In particular, we show that the amount of competition affects the rate of the manipulation behavior as well as the dynamics of the manipulation process. 4 - Multichannel Word of Mouth: The Effect of Brand Characteristics Renana Peres, Assistant Professor, Hebrew University of Jerusalem, Jerusalem, Israel, peresren@huji.ac.il, Ron Shachar Although word-of-mouth has been receiving an increasing attention, our understanding of it is still too one-dimensional and does not recognize the richness of the phenomenon. Specifically: (i) it is based on a single conversation channel; (ii) it is based almost exclusively on online measures, in spite of evidence suggesting that offline WOM might have a higher effect on consumption, and (iii) it does not account for the role of brands characteristics which is a central ingredient of marketing. The only way to address these concerns is by creating a comprehensive data set and analyzing it. We conducted a massive data search on 700 US brands from 16 different categories. For each of these brands we collected data on the perceived brand characteristics (collaborating with Decipher Inc. and the Brand Asset Valuator of Young and Rubicam), the offline word of mouth through face-to-face and phone conversations (from the Keller Fay Group), and the online word of mouth through blogs, user forums, and Twitter messages (using the Buzzmetrics tool of Nielsen online). Our preliminary analysis finds that while different online channels are similar to each other, online and offline WOM are quite different. Thus, online WOM cannot act as a good proxy for offline activities. We also find that brand characteristics play an important role in generating WOM and that their role is different between the online and offline channels. While newness of the brand, the brand equity and its visibility/observability are important for both online and offline WOM, the effect of the Aaker’s brand personality variables (excitement and competence) on WOM is significant for the online channels, but they are not significant for the offline channel. ■ FC08 Founders II Dynamic Models in Marketing Cluster: Special Sessions Invited Session Chair: Paul Ellickson, University of Rochester, Simon School of Business, Rochester, NY, United States of America, paul.ellickson@simon.rochester.edu 1 - Learning About Entertainment Products: A Dynamic Consumer Decision Model with Learning About Changing Match-Values Mitch Lovett, University of Rochester, Simon School of Business, Rochester, NY, United States of America, mitch.lovett@simon.rochester.edu, William Boulding, Richard Staelin How do consumers decide whether to continue watching a TV show week after week? We study consumer learning and decisions when engaging in an entertainment product repeatedly and seek to understand both how consumers use new information to learn about the product as well as what trades are most important in the decision to continue engaging. We develop a model for how consumers learn about products when the match-value for those products could be changing from one experience to the next. For entertainment products, the plot and characters may change with each new experience, potentially altering how much the consumer likes the show in a persistent way. We model this changing nature of the product and the way consumers adjust their beliefs about the product. These beliefs, in turn, are central to our explanation of how consumers decide whether to continue engaging in the product. To test and calibrate this theory, we both conduct a laboratory experiment and collected data in which consumers have multiple experiences with products. We collect measures of viewing behaviors, experienced liking, and subjective expectations for the next experience. We present an approach to estimate how each individual learns about the product as the product itself is changing and incorporate this estimation into a dynamic consumer choice model. Through this research, we extend understanding of how to model consumer learning as well as how consumers behave in repeated interactions with entertainment products.
2 - Determining Consumers’ Discount Rates with Field Studies Song Yao, Northwestern University, Kellogg School of Management, Evanston, IL, United States of America, s-yao@kellogg.northwestern.edu, Carl Mela, Jeongwen Chiang, Yuxin Chen Because utility/profits, state transitions and discount rates are confounded in dynamic models, discount rates are typically fixed to estimate the other two factors. Yet these rate choices, if misspecified, generate poor forecasts and policy prescriptions. Using a field study wherein cellphone users transitioned from a linear to three-part tariff pricing plan, we estimate a dynamic structural model of minute usage and obtain discount factors that would normally be unidentifiable. The identification rests upon imputing the utility under linear pricing plans without dynamic structure; then using these utilities to identify discount rates when consumers were switched to a threepart tariff where dynamics became material. We find that the estimated segment-level weekly discount factors (0.86 and 0.91) are much lower than the value typically assumed in empirical research (0.995). When using a standard 0.995 discount rate, we find the price coefficients are underestimated by 23%. Moreover, the predicted intertemporal substitution pattern and demand elasticities are biased, leading to a 27% deterioration in model fit; and sub-optimal pricing recommendations that would lower potential revenue gains by 74-88%. 3 - Does AMD Spur Intel to Innovate More? Ronald Goettler, University of Chicago, Booth School of Business, Chicago, IL, United States of America, ronald.goettler@chicagobooth.edu, Brett Gordon We propose and estimate a model of dynamic oligopoly with durable goods and endogenous innovation to examine the relationship between market structure and the evolution of quality. Firms make dynamic pricing and investment decisions while taking into account the dynamic behavior of consumers who anticipate the product improvements and price declines. The distribution of currently owned products is a state variable that affects current demand and evolves endogenously as consumers make replacement purchases. Our work extends the dynamic oligopoly framework of Ericson and Pakes~(1995) to incorporate durable goods. We propose an alternative approach to bounding the state space that is less restrictive of frontier firms and yields an endogenous long-run rate of innovation. We estimate the model for the PC microprocessor industry and perform counterfactual simulations to measure the benefits of competition. Consumer surplus is 2.8 percent higher ($2.8 billion per year) with AMD than if Intel were a monopolist. Innovation, however, would be higher without AMD present. Counterfactuals reveal that consumer surplus can actually increase as the market moves toward monopoly, which suggests policymakers ought to consider the dynamic trade-off lower current consumer surplus from higher prices for higher future surplus from more innovation. Comparative statics reveal that competition does induce higher innovation if consumers have su¢ ciently high preferences for quality and low price sensitivity or if depreciation of the durable good reduces the degree to which a monopolist competes with itself over time. 4 - Dynamics of Pricing Strategy and Repositioning Costs Paul Ellickson, University of Rochester, Simon School of Business, Rochester, NY, United States of America, paul.ellickson@simon.rochester.edu, Sanjog Misra, Harikesh Nair We measure the cost to retailers of changing pricing formats in oligopolistic retail markets. The choice of pricing strategy is a signficant, but to our knowledge, unquantified, determinant of price-stickiness. For example, adopting an Everyday Low Pricing (EDLP) strategy could have significant effects on long-run market structure, as these firms tend to stick to an initially chosen pricing format for years, if not decades, to avoid incurring adjustment costs. This could be an important source of price rigidity. We exploit a unique dataset containing the pricing-format decisions of all supermarkets in the U.S to measure format-switching costs. The data contain the format-change decisions of supermarkets in response to a large shock to their local market positions: the entry of WalMart. We exploit the price-format responses of supermarkets to WalMart’s entry and infer the repositioning cost using a “revealedpreference” argument similar to the spirit of Breshnahan & Reiss (1990). The interaction between players in a market is modeled as a dynamic discrete game. We find evidence that suggests that the entry patterns of WalMart had a significant impact on the costs and incidence of switching pricing strategy. Our results add to the marketing literature on the organization of retail markets, and to a new literature that discusses implications of marketing pricing decisions for macroeconomic policy. MARKETING SCIENCE CONFERENCE – 2011 FC09 57 ■ FC09 Founders III Retailing IV: Competition Contributed Session Chair: Aharon Hibshoosh, Professor, San Jose State University and Lincoln University, One Washington Square, San Jose CA 95192, 401 15th Street, Oakland, CA 94612, Oakland, CA, 94612, United States of America, rhibshoosh@gmail.com 1 - Product Variety Decision: When Specialty Stores Meet with Big-box Retailers Jiong Sun, Assistant Professor, Illinois Institute of Technology, 565 W Adams St., Chicago, IL, 60661, United States of America, jiongs@gmail.com, Tao Chen Specialty stores carry more varieties in a particular category, while big-box retailers carry fewer varieties with price advantages. When consumers are unsure about their taste about different varieties, visiting specialty stores offers consumers an opportunity to inspect the varieties and resolve their uncertainty. Offering more varieties may encourage more low-valuation consumers to evaluate and buy the product from the specialty store, but may also intensify the price competition with the big box retailer which enjoys high cost efficiency. In this paper, we examine product variety decisions of specialty stores when facing competition from big-box retailers. We find that consumers’ transaction cost and valuation heterogeneity play an important role. 2 - Variety and Cost Pass-through Among Supermarket Retailers Timothy Richards, Morrison Professor, Arizona State University, 7171 E Sonoran Arroyo Mall, Mesa, AZ, 85212, United States of America, trichards@asu.edu, Stephen Hamilton, William Allender The extent to which wholesale price changes are reflected in retail prices is an issue of critical importance to manufacturers. Theoretical models of cost pass-through in both the marketing (Tyagi, 1999; Moorthy, 2005) and economics (Bulow and Pfeiderer, 1983; Nakamura and Zerom, 2010) literatures show that competitive, single-product retailers will pass a rise in costs along to consumers on a one-to-one basis if they face perfectly elastic demand. Imperfectly competitive retailers, however, will absorb some of the change in costs depending upon the curvature of demand, the competitiveness of local markets, and the structure of retailing costs. Hamilton (2009) shows that over-shifting, or passing through costs on a more than one-to-one basis, can occur among imperfectly competitive, multi-product retailers because rising input costs cause retailers to reduce the number of products they sell, which softens price competition. We fail to reject this hypothesis using store-level data on breakfast cereal sales from a large sample of U.S. grocery retailers. Our contribution lies in explaining the phenomenon of over-shifting in response to changes in wholesale prices, extending the empirical literature on retail pass-through to multi-product environments, and documenting the extent to which changes in wholesale prices are passed through to consumer food prices. 3 - Pricing, Package Size, Advertising and Trade Areas in Spatial Competition of Retail Warehouse Clubs Aharon Hibshoosh, Professor, San Jose State University and Lincoln University, One Washington Square, San Jose CA 95192, 401 15th Street, Oakland, CA 94612, Oakland, CA, 94612, United States of America, rhibshoosh@gmail.com Using game theoretical framework, we model intrinsic short run spatial competition among profit-maximizing Retail Warehouse Clubs RWCs). Traditional modeling of spatial competition has location and price as the key decision variables of the marketing mix of each competitor and typically assumes an instantaneously consumed single product. However, our models assumes that, in the short run store locations are fixed, and more realistically that besides price, RWCs distinctively compete on package size and store advertising while offering many products. We further assume that package size is directly related to RWC’s cost savings due to economics of scale in purchasing, transportation and inventory management. Consumer patronage and purchase decisions are complex, as every consumer minimizes his total purchasing, transportation and holding cost of a portfolio of products. Usually RWCs do not locate near consumers, as convenience stores do, so that consumers encounter time constraints and overall transportation costs. Hence, consumer store visit frequency and average product quantity demanded per visit are often institutionally dependent. Distinctively, the package size offered by an RWC is typically large and the consumer incurs high inventory carrying cost when purchasing non-instantaneously consumed products. The indivisibility of package size raises non-trivial technical and substantive consequences. Specifically, for inventory path valuation, we employ continued fractions and the classical Euclidean Algorithm. The competition is modeled as a sequential game where package size equilibrium is determined prior to price equilibrium. We derive explicit parametric game equilibria solutions for price, package size, store advertising, trading area and profit.
Page 1 and 2:
How to Navigate the Contributed Ses
Page 3 and 4:
address a target group. i.e., shoul
Page 5 and 6: ole that prior distributions play i
Page 7 and 8: 4 - Understanding Customers` Substi
Page 9 and 10: shift in the demand curve. Most of
Page 11 and 12: marketers may predict future custom
Page 13 and 14: ■ TB06 Legends Ballroom VII Compe
Page 15 and 16: 3 - The Impact of Free-trial Promot
Page 17 and 18: 3 - Cross-cultural Differences in B
Page 19 and 20: of the sequence of evaluation, a pa
Page 21 and 22: ■ TC06 Legends Ballroom VII Compe
Page 23 and 24: and on the transaction utility they
Page 25 and 26: een developed would help marketers
Page 27 and 28: Thursday, 3:30pm - 5:00pm ■ TD01
Page 29 and 30: interest. To evaluate the performan
Page 31 and 32: 2 - What You Don’t Know Can’t H
Page 33 and 34: ■ TD12 Champions Center II Biddin
Page 35 and 36: while maintaining market growth rat
Page 37 and 38: knowledge. However, buyers with a h
Page 39 and 40: ■ FA07 Founders I Panel Session:
Page 41 and 42: ecoming more acceptable, the dilemm
Page 43 and 44: 2 - Choosing the Right Plan? Asymme
Page 45 and 46: 4 - A Framework for Unifying Differ
Page 47 and 48: ■ FB06 Legends Ballroom VII Chann
Page 49 and 50: 3 - Money-back Guarantees: The Grea
Page 51 and 52: 2 - The Impact of Consulting on Buy
Page 53 and 54: 2 - Data or Structure? Using a Fiel
Page 55: 4 - Green Lifestyle Adoption: Shopp
Page 59 and 60: 3 - Investigating Salespeople Turno
Page 61 and 62: 2 - One-stop Shopping: A Double Edg
Page 63 and 64: 3 - Which Link to Click - Sponsored
Page 65 and 66: valuation of the high-end consumers
Page 67 and 68: 2 - A Machine Learning Approach to
Page 69 and 70: 4 - Social Ties and User Generated
Page 71 and 72: ■ SA02 Legends Ballroom II Twitte
Page 73 and 74: ■ SA05 Legends Ballroom VI Game T
Page 75 and 76: differ depending on their respectiv
Page 77 and 78: 2 - The Impact of Online Referrals
Page 79 and 80: Saturday, 10:30am - 12:00pm ■ SB0
Page 81 and 82: 2 - R&D Spillover and Product Diffe
Page 83 and 84: 2 - The Advertising Role of Profess
Page 85 and 86: 4- Optimal Allocation of Marketing
Page 87 and 88: 3 - Information Communities: The Ne
Page 89 and 90: ■ SC06 Legends Ballroom VII Consu
Page 91 and 92: and context is unclear. The current
Page 93 and 94: A Agarwal, Nipun SB14 Alexandrov, A
Page 95 and 96: F Fan, Tingting FC10 Fang, Eric TA0
Page 97 and 98: Schweidel, David TC07, FA02, FB02,
Page 99: Friday, 1:30pm - 3:00pm FC01 Choice
show all

Conference Sessions - Jesse H. Jones Graduate School of ...

Create successful ePaper yourself

Delete template?

Save as template?