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

More documents

Recommendations

Info

FC03 MARKETING SCIENCE CONFERENCE – 2011 ■ FC03 Legends Ballroom III Analytic Models of Online Behavior Cluster: Internet and Interactive Marketing Invited Session Chair: J. Miguel Villas-Boas, University of California-Berkeley, Berkeley-Haas, Berkeley, CA, 94720-1900, United States of America, villas@haas.berkeley.edu 1 - The Interplay between Sponsored Search and Display Advertising Kannan Srinivasan, Professor, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA, 15213, United States of America, kannans@cmu.edu, Kinshuk Jerath, Amin Sayedi An important decision for a firm is how to allocate its online advertising budget between sponsored search advertising and display advertising. An advantage of sponsored search advertising is that, since the firm advertises in response to a consumer-initiated search, the sales-conversion rate is typically higher than in display advertising. However, a disadvantage of sponsored search advertising is that, to “steal” the firm’s customers, its competitors can also bid on its keyword, therefore driving the advertising costs higher. Using a game theory model, we study the implications of these tradeoffs on the advertising decisions of competing firms, and on the design of the sponsored search auction by the search engine. We find that symmetric firms may follow asymmetric budget allocation and bidding strategies. Moreover, the search engine benefits from discouraging competition in sponsored search bidding by shielding firms from competitors’ bids. This explains the practice of employing “keyword relevance” measures, under which search engines such as Google, Yahoo! and Bing under-weight the bids of firms bidding on competitors’ keywords. We also obtain various other interesting insights on the interplay between sponsored search advertising and display advertising. 2 - Optimal “Last-minute” Selling by a Monopolist Facing Forwardlooking and Risk Averse Consumers Ori Marom, Erasmus University, Burgemeester Oudlaan 50, Rotterdam, 3062 PA, Netherlands, omarom@rsm.nl, Abraham Seidmann We characterize profit-maximizing strategies for a monopolist who sells to risk-averse buyers in two time periods and may deliberately randomize the occurrence of clearance sales. Our theoretical investigation shows that such a randomized strategy is optimal whenever the seller’s capacity exceeds a threshold value that is a decreasing function of the degree of the buyers’ risk-aversion. We show that with no loss of optimality the seller can restrict herself to strategies with a deterministic “sale” price. Contrary to intuition, we find that an increase in the buyers’ risk-aversion shifts supply toward randomized “last-minute” selling. 3 - Sampling Paid Content Florian Stahl, Assistant Professor, University of Zurich, Plattenstrasse 34, Zurich, 8032, Switzerland, florian.stahl@uzh.ch, Don Lehmann, Oded Koenigsberg, Daniel Halbheer This paper studies profit-maximizing sampling and pricing of paid content for online news publishers. The key feature of our model is the twofold role of free samples which allows publishers to generate advertising revenues and simultaneously disclose editorial quality to potential subscribers. Taking customers’ prior beliefs about article qualities into account and employing Bayesian updating, we derive the subscription demand and characterize the optimal number of articles offered for free as well as the subscription price for the content behind the paywall. Considering two cases where free sampling aims to persuade either all consumers to subscribe or only those with the highest willingness-to-pay, we find that is optimal for the publisher to offer a larger number of free samples when consumers underestimate product quality. 4 - Optimal Search for Product Information J. Miguel Villas-Boas, University of California-Berkeley, Berkeley-Haas, Berkeley, CA, 94720-1900, United States of America, villas@haas.berkeley.edu, Monic Sun, Fernando Branco Consumers often need to search for product information before making purchase decisions. We consider a parsimonious model in which consumers incur search costs to learn further product information, and update their expected utility of the product at each search occasion. We characterize the optimal stopping rules to either purchase, or not purchase, as a function of search costs and the informativeness of each attribute. The paper also characterizes how the likelihood of purchase changes with the ex-ante expected utility, search costs, and informativeness of each attribute. We discuss optimal pricing, the impact of consumer search on profits and social welfare, and how the seller chooses its price to strategically affect the extent of the consumers’ search behavior. We show that lower search costs can hurt the consumer because the seller may choose to then charge higher prices. The paper also considers the impact of searching for signals of the value of the product, of discounting, and of endogenizing the intensity of search. 54 ■ FC04 Legends Ballroom V Structural Models I Contributed Session Chair: Wenbo Wang, PhD Candidate, New York University, 40 West 4th Street, Room 921, New York, NY, 10012, United States of America, wwang2@stern.nyu.edu 1 - A Dynamic Model of Consumers’ Optimal Default on Financial Products: A Case of Subprime Mortgages Minjung Park, Assistant Professor, University of California-Berkeley, Haas, 545 Student Services Bldg #1900, Berkeley, CA, 94720, United States of America, mpark@haas.berkeley.edu, Patrick Bajari, Sean Chu, Denis Nekipelov The increase in defaults in the subprime mortgage market is widely held to be one of the causes behind the recent financial turmoil. Key issues of policy concern include identifying the main drivers behind the wave of defaults and predicting the effects of various policy instruments designed to mitigate default. To address these questions, we estimate and simulate a dynamic structural model of subprime borrowers’ default behavior. In each period, a borrower takes one of three possible actions: defaulting, prepaying, or continuing to make regularly scheduled payments. Dynamics are generated by the fact that defaulting results in an immediate payoff as well as the loss of future option value from keeping the mortgage alive into the future. Key determinants of optimal borrower behavior include the level of net equity as well as expectations about future home prices. Our model also allows for defaults to be driven by binding credit constraints. We use our model to simulate how borrowers’ default decisions would change under various counterfactual scenarios. The simulation exercises allow us to quantify the importance of home price declines versus loosened underwriting standards in explaining the recent increase in subprime defaults. Furthermore, we use simulations to assess the effects of foreclosure mitigation policies, such as principal write-downs, on the behavior of various subsets of borrowers. 2 - Modeling Consumer Learning of Attribute-specific Preferences Jihong Min, PhD Student, Purdue University, Rm 460 Krannert Building, W. State Street, West Lafayette, IN, 47909-2065, United States of America, min1@purdue.edu, Subramanian Balachander Most extant consumer learning models allow for learning about alternative-specific preference such as brand preference in a brand choice model. However, there exist product categories which offer many varieties of products with different attributes. In such cases, it is important to model consumer learning of attribute-specific preferences rather than simply modeling alternative-specific preferences in order to more accurately and parsimoniously describe consumer behavior. In this paper, we propose a structural model of consumer’s Bayesian learning of attribute-specific preference, using scanner panel data. We show that the proposed model and empirical results can enable marketing researchers to identify whether a certain attribute is characterized by significant consumer learning, and to capture the possible separate learning processes of preferences for multiple attributes. Moreover, the model results provide a snapshot of the segmentation of consumers’ learning of different attributes and this snapshot can provide insights into market structure. We conduct policy evaluations such as the introduction of a new flavor for a brand and obtain interesting implications for managers. 3 - Studying the Switching Behavior of Electricians: Assessing the Impact of a Loyalty Program Madhu Viswanathan, University of Minnesota, 321 Nineteenth Avenue South, Suite 3-150, Minneapolis, MN, 55455, United States of America, viswa022@umn.edu, Ranjan Banerjee, Om Narasimhan Despite the popularity of reward programs, the ability of these programs to create brand loyalty has been questionable. Existing empirical work has found mixed results and focused largely on a single “lock-in” parameter that rationalizes the observed response to a reward (Lewis 2004, Rossi 2008, Hartmann and Viard 2008). In this paper, we identify and estimate the impact of reward programs when these programs create both financial and non-financial costs for the consumer. By financial costs, we refer to all those costs that involve the loss of financially quantifiable resources, like not meeting the target for a reward program. Non-financial costs could be procedural (related to learning about the features and appropriate usage) or emotional (psychological or emotional discomfort due to loss of identity/breaking of bonds). We estimate these two kinds of costs by using a unique dataset that tracks electricians’ purchase behavior during a reward program offered by a switchgear manufacturer in India. In general, estimation of such costs is made difficult by the need to account for forward-looking behavior of consumers, and separating the “lock-in” effect from consumer heterogeneity. Accordingly, we develop and estimate a structural dynamic model of consumer choice and incidence across different consumer segments. We find that behavior differs across segments based on the intensity of usage; financial rewards are the main drivers of purchase behavior for frequent and infrequent consumers of the brand, while both non-financial and financial rewards matter for average users of the brand.
4 - Green Lifestyle Adoption: Shopping Without Plastic Bags Wenbo Wang, PhD Candidate, New York University, 40 West 4th Street, Room 921, New York, NY, 10012, United States of America, wwang2@stern.nyu.edu, Yuxin Chen This research develops a structural model of consumer lifestyle adoption. The model captures two behavioral features —- forward looking and accessibility contingency — - that are shared by many lifestyles. Lifestyle adoption often involves a deliberate trade-off between long-term benefit and extra effort at the initial stage, and therefore motivates consumers to look forward in adoption decisions. Moreover, the forward looking adoption is contingent on accessibility of the optimal lifestyle choice. For instance, even though one intends to lives a healthy lifestyle, he may accidentally forget to bring sneakers from time to time. In this case, the gym exercise lifestyle choice is not accessible to him at the decision moment. Inaccessibility can occur due to, for example, memory limitations or cognitive constraints. We estimate the model with a panel data of a green lifestyle adoption of urban shoppers under the plastic bag ban in China. The ban is lifestyle-changing to the consumers because they now have to either bring own shopping bags or pay for plastic bags. This research sheds light on the following questions: 1) How does accessibility contingency interplay with forward looking in the green lifestyle adoption? 2) What is the role of state dependence on the lifestyle adoption? 3) How long does it take a shopper to stabilize on the new green lifestyle and where is the no-return point for this lifestyle? 4) How can marketing mix decisions facilitate the adoption? ■ FC05 Legends Ballroom VI Game Theory II: Market Entry Contributed Session Chair: Matthew Selove, Assistant Professor of Marketing, USC Marshall School of Business, 3660 Trousdale Parkway, ACC 306E, Los Angeles, CA, 90089, United States of America, selove@marshall.usc.edu 1 - Cross-market Experience and Market Entry Dai Yao, PhD Student, INSEAD, PhD Room (2nd floor), 1 Ayer Rajah Avenue, INSEAD, Singapore, 138676, Singapore, dai.yao@insead.edu, Yakov Bart Cross-market experience externality arises when a firm may choose to provide products or services in one market in order to gain experience that could benefit launching products or services in another market. Examples of industries with such externality include IT outsourcing market vs. IT consulting market and PC components market vs. PC market.Multi-market environments that exhibit such cross-market experience externalities are structurally different from industries in which multiple markets are related to each other through characteristics of goods. We propose a game-theoretic model toprovide explanations to different patterns in regards to optimal entry time for market entrants and optimal defending strategies for market incumbents in such multi-market environments.Our analysis characterizes the impact of cross-market experience externalities on firms’ optimal market entry decisions and competitive interactions. 2 - The Benefit of Increased Competition David Soberman, Canadian National Chair in Strategic Marketing, Rotman School of Management, University of Toronto, 105 St. George Street, Toronto, Ontario, Canada, david.soberman@rotman.utoronto.ca, Amit Pazgal We consider a fundamental question regarding the need for incumbents to protect their turf and foreclose entry to their industry. This has been a fundamental issue of industrial organization for more than 50 years (Bain 1956) and numerous studies have demonstrated how barriers to entry are used to protect and increase profits. But are there times when a new entrant can be beneficial for incumbent firms? Sometimes late entrants learn from incumbents and are able to improve on existing offerings. However, late entrants are also known to offer stripped down versions of products that have reduced functionality. Using a spatial model, we demonstrate that a stripped down new entrant can lead to higher (and not lower) incumbent profits by capturing a quality insensitive/price sensitive segment of consumers that are the source of intense competition between incumbents. This can create a win-win situation for all competitors including the entrant. Our analysis identifies the precise conditions where this occurs and also conditions where incumbents should seek to blockade the potential entrant. 3 - A Dynamic Model of Competitive Entry Response Matthew Selove, Assistant Professor of Marketing, USC Marshall School of Business, 3660 Trousdale Parkway, ACC 306E, Los Angeles, CA, 90089, United States of America, selove@marshall.usc.edu This paper develops a model in which competing firms invest in various business formats. For example, they could implement full service or “no-frills” airline models. I derive conditions in which each firm specializes in a single format, and conditions in which both firms adopt both formats. In some cases, increased difficulty of implementing a format increases the likelihood that firms attack each other by investing in each other’s format. This is because barriers to entry also serve as barriers to retaliation, allowing firms to attack without fear of swift punishment. MARKETING SCIENCE CONFERENCE – 2011 FC06 55 ■ FC06 Legends Ballroom VII Channels III: Competition Contributed Session Chair: Jaime Romero, Associate Professor, University Autonoma Madrid, Fac. CC. Económicas, Avda. Tomas y Valiente, 5, Madrid, 28049, Spain, jaime.romero@uam.es 1 - When and How Do Coordinating Contracts Improve Channel Efficiency? Ernan Haruvy, Associate Professor, Universiy of Texas at Dallas, 800 West Campbell Rd, Richardson, TX, 75080, United States of America, eharuvy@utdallas.edu A growing literature shows that coordinating contracts may not improve efficiency in the laboratory to the extent prescribed by theory. We show that this result is largely due to offer rejection where the bargaining procedure is structured as an ultimatum offer, which is the only structure studied in the lab hitherto in relation to coordinating contracts. We show that a less restrictive procedure does not involve this feature and allows coordinating contracts to coordinate. Specifically, we look at three contract formats – wholesale price, two-part-tariff and minimum order quantity. The wholesale price leads to loss of firm surplus because of double marginalization. The other two contracts – the coordinating contracts – allow the manufacturer to coordinate the channel, either by pricing at cost and extracting surplus through a lump sum payment (two part tariff) or through announcing a minimum order quantity which is equal to the efficient quantity and extracting the surplus through price (minimum order quantity contract). Even though for fully rational players these two coordinating contracts are equivalent, these two contracts are different under mild bounded rationality assumptions. Proposals in the minimum order quantity treatment are far more efficient than two-part-tariff proposals in terms of the overall surplus they imply. But in the ultimatum context such efficient proposals tend to get rejected, leading to lower ex-post efficiency. With structured negotiations bargaining, however, rejection rate drastically falls leading to a more direct relationship between proposal efficiency and ex-post efficiency. 2 - Channel Structure and Performance under Co-marketing Alliance Xiao Zuhui, The Hong Kong Polytechnic University, Room 409, New East Ocean Centre, 9 Science Museum Road, Honghum, Hong Kong, Hong Kong - PRC, zuhuixiao@msn.com, Liu Liming, Zhang Xubing A growing number of companies are seeking cooperation to better serve their clients. Among various types of cooperative strategies, lateral relationships between firms at the same level in the value chain, are popular in both good and service markets. In these relations, downstream firms jointly market the products or provide value add service for upstream suppliers to increase profit and promote sales. Although introducing marketing effort from a third party has become more common in business life, this type of cooperation receives little continuing attention in the literature. Motivated by real business cases, we aim to provide a better understanding on how these cooperative activities create values for partnering firms and their common clients. We construct models for marketing and channel decisions of alliance partners under different scenarios. Our modeling analysis focuses on the following issues: (1) how the firms involved make their individual decisions in equilibrium; (2) how different cooperation structures influence the performance of firms involved; (3) how market conditions, i.e., demand uncertainty and asymmetric information, influence the firms’ performance. We characterize the different scenarios in these settings, providing conditions under which the cooperation structure will benefit the partnering firms. We show that, under certain market conditions, the partnering firms and even total channel may be better off under these cooperative activities. 3 - Should be Close to or Away from Your Competitors? Store Location Choice by Gravity Model Wei-Jhih Yang, PhD Candidate, National Taiwan University, No.1, Sec. 4, Roosevelt Rd., Taipei City, Taiwan - ROC, flieryang@gmail.com, Jesheng Huang, Lichung Jen Agglomeration among competing firms in store location cluster may enlarge consumer demand, but may also create more brand competitive intensity in consumer’s mind spontaneously. From managerial perspective, it is hard to identify who made much more efforts and who should gain more if the economies of agglomeration exist; likewise, it’s also difficult to examine who would threat others and who won’t if the diseconomies of agglomeration exist. More specifically, for channel strategy, a firm’s store should be close to or away from the agglomeration of its competitors? And for brand positioning strategy, how a firm can get a good location in consumer’s mind to avoid the points of parity. Therefore, how to address this kind of dual competitive intensities is the focus of this article. Based on the concept of gravity model from physics, the authors propose a location gravity model to analyze why a firm should close to or away from its competitors. The authors firstly use consumers’ brand perceptual mapping to measure the cognitive distance of the competing brands in an agglomeration through MDS; then, the results of cognitive distance among competing brands will be applied to location gravity model, in order to calculate distribution intensity in the spatial cluster formed by a firm and the agglomeration of its competitors. Based on the proposed model which combining both considerations of dual competition intensities , the authors suggest how a firm can choose the optimal store location which may avoid the exiting competition from the cluster of store locations and get the best position in consumers’ mind. Finally the authors discuss the managerial implications of this model for the blue ocean strategy.
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: 2 - Data or Structure? Using a Fiel
Page 57 and 58: 2 - Determining Consumers’ Discou
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 ...

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?