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on Marketing |
| By: | Yongmin Chen (University of Colorado at Boulder); Chuan He (University of Colorado at Boulder) |
| Abstract: | Paid placement, where advertisers bid payments to a search engine to have their products appear next to keyword search results, has emerged as a predominant form of advertising on the Internet. This paper studies a product-di¤erentiation model where consumers are initially uncertain about the desirability of and valuation for di¤erent sellers? products, and can learn about a seller?s product through a costly search. In equilibrium, a seller bids more for placement when his product is more relevant for a given keyword, and the paid placement of sellers by the search engine reveals information about the relevance of their products. This results in e¢ cient (sequential) search by consumers and increases total output. |
| Keywords: | Paid placement, Advertising, Auction, E-commerce, Search |
| Date: | 2006–09 |
| URL: | http://d.repec.org/n?u=RePEc:net:wpaper:0602&r=mkt |
| By: | Anja Lambrecht (UCLA Anderson School of Management); Katja Seim (The Wharton School, University of Pennsylvania) |
| Abstract: | The availability and variety of online services has increased dramatically in recent years. Many questions remain, however, regarding patterns of online service use, consumer preferences when using online services, and how consumers substitute between equivalent online and offline services. Using an extensive data set of consumer adoption and usage of the online banking service of a major German bank, this paper analyzes consumers’ adoption and usage of online banking over the period August 2001 to July 2003, including the effect of demographics and branch banking on usage of online banking. We also examine the relationship between Internet availability and channel choice as well as usage. Finally, we analyze the effect of channel usage on customer level and product-specific revenues earned by the bank and derive revenue implications of online banking. |
| Date: | 2006–10 |
| URL: | http://d.repec.org/n?u=RePEc:net:wpaper:0627&r=mkt |
| By: | Chris Forman (Tepper School of Business); Anindya Ghose (Stern School of Business, New York University); Avi Goldfarb (Rotman School of Management, University of Toronto) |
| Abstract: | We develop a formal model of online-offline substitution to identify three factors that drive consumers to purchase online: convenience, selection, and price. This model builds hypotheses on how features of offline retail supply impact online purchasing. We then examine how the local availability of offline retail options drives use of the online channel and consequently how the convenience, selection, and price advantages of the online channel may vary by geographic location. In particular, we examine the effect of local store openings on online book purchases in that location. We explore this problem using data from Amazon on the top selling books for 1501 unique locations in the US for 10 months ending in January 2006. In addition to this data, we use information on changes in local retail competition as measured by openings of large specialty bookstores such as Borders or Barnes & Noble and discount stores such as Wal-Mart or Target. We show that even controlling for product-specific preferences by location, changes in local retail options have substantial effects on online purchases. We demonstrate how the convenience, selection, and price benefits of the Internet are different for customers in different types of locations. More generally, we show that geography significantly impacts the benefit that consumers derive from electronic markets. |
| Date: | 2006–09 |
| URL: | http://d.repec.org/n?u=RePEc:net:wpaper:0615&r=mkt |
| By: | Anirban Sengupta (Texas A&M University); Steven Wiggins (Texas A&M University) |
| Abstract: | This paper uses a unique individual transactions data set to investigate the effects of internet purchase on the prices paid for individual airline tickets. The analysis also investigates the effects of changes in the percentage of online transactions on both online and offline prices and on overall price dispersion. The analysis also uses these unique data to provide a more complete analysis of the factors affecting airline price levels and price dispersion, contributing more generally to our understanding of airline pricing. Our novel data set includes detailed transaction level data the includes ticket characteristics and restrictions, carrier, estimated flight level load factors, date of issue, departure date, other hedonic factors affecting prices, whether the ticket was purchased online or offline, and the share of online purchases for the citypair. Controlling for numerous observed ticket characteristics, as well as carrier and route effects, the results show that online prices average about 13 percent less than the offline prices. The analysis also shows that a ten percent increase in the online share of tickets sold on a route decreases average prices by an additional 5 percent, with more of this effect coming in the form of lower offline prices. The results also suggest that the potential savings to the consumers from buying online in markets with lower share of internet purchases are higher than in markets where the online share is larger. The paper also finds evidence that an increase in online shares decrease price dispersion. The paper also uses these unique data to investigate the effects of hub dominance and high route shares on pricing. Due to data limitations previous investigations of these issues could not control for important ticket characteristics, load factors, and time of purchase in measuring the effects of concentration on price levels and dispersion. Our analysis controls for these factors while investigating the impact of market concentration on price levels and dispersion. |
| Keywords: | search cost, online, offline, price dispersion |
| JEL: | L8 L93 |
| Date: | 2006–09 |
| URL: | http://d.repec.org/n?u=RePEc:net:wpaper:0607&r=mkt |
| By: | Anindya Ghose (Stern School of Business, New York University); Bin Gu (McCombs School of Business, University of Texas at Austin) |
| Abstract: | It is well known that the Internet has significantly reduced consumers’ search costs online. But relatively little is known about how search costs affect consumer demand structure in online markets. In this paper, we identify the impact of search costs on firm competition and market structure by exploring a unique theoretical insight that search costs create a kink in aggregate demand when firms change prices. The significance of the kink reflects the magnitude of online search costs and the kinked demand function provides information on how search costs affect competition in the online market. Using a dataset collected from Amazon and Barnes & Noble, we find that search costs vary significantly across online retailers. Consumers face low search costs for price information from Amazon.com. It leads to a higher price elasticity when the firm reduces prices than when it increases prices, increasing Amazon’s incentive to engage in price competition. On the other hand, consumers face relatively higher search costs for price information from Barnes & Noble. This leads to a lower price elasticity when Barnes & Noble reduces prices than when it increases prices, reducing Barnes & Noble’s incentive to engage in price competition. We also find that search costs decrease with the passage of time as the information about price changes dissipates among consumers, leading to increased price elasticity over time. Finally, we highlight that search costs are lower for popular books compared to rare and unpopular books. These findings have implications for the impact of the Internet on the Long Tail phenomenon. |
| Keywords: | Electronic Markets, Search Costs, Kinked Demand Curve, Price Elasticity, Price Competition, Long Tail |
| Date: | 2006–10 |
| URL: | http://d.repec.org/n?u=RePEc:net:wpaper:0619&r=mkt |
| By: | K. COUSSEMENT; D. VAN DEN POEL |
| Abstract: | CRM gains increasing importance due to intensive competition and saturated markets. With the purpose of retaining customers, academics as well as practitioners find it crucial to build a churn prediction model that is as accurate as possible. This study applies support vector machines in a newspaper subscription context in order to construct a churn model with a higher predictive performance. Moreover, a comparison is made between two parameter-selection techniques, needed to implement support vector machines. Both techniques are based on grid search and cross-validation. Afterwards, the predictive performance of both kinds of support vector machine models is benchmarked to logistic regression and random forests. Our study shows that support vector machines show good generalization performance when applied to noisy marketing data. Nevertheless, the parameter optimization procedure plays an important role in the predictive performance. We show that only when the optimal parameter selection procedure is applied, support vector machines outperform traditional logistic regression, whereas random forests outperform both kinds of support vector machines. As a substantive contribution, an overview of the most important churn drivers is given. Unlike ample research, monetary value and frequency do not play an important role in explaining churn in this subscription-services application. Even though most important churn predictors belong to the category of variables describing the subscription, the influence of several client/company-interaction variables can not be neglected. |
| Keywords: | data mining, churn prediction, subscription services, support vector machines, parameter-selection technique |
| Date: | 2006–09 |
| URL: | http://d.repec.org/n?u=RePEc:rug:rugwps:06/412&r=mkt |
| By: | Ke-Wei Huang (Leonard N. Stern School of Business, New York University); Arun Sundararajan (Leonard N. Stern School of Business, New York University) |
| Abstract: | We develop and analyze a model of pricing for digital products with discontinuous supply functions. This characterizes a number of information technology-based products and services for which variable increases in demand are fulfilled by the addition of "blocks" of computing or network infrastructure. Examples include internet service, telephony, online trading, on-demand software, digital music, streamed video-on-demand and grid computing. These goods are often modeled as information goods with variable costs of zero, although their actual cost structure features a mixture of positive periodic fixed costs, and zero marginal costs. The pricing of such goods is further complicated by the fact that rapid advances in semiconductor and networking technology lead to sustained rapid declines in the cost of new infrastructure over time. Furthermore, this infrastructure is often shared across multiple goods and services in distinct markets. The main contribution of this paper is a general solution for the optimal nonlinear pricing of such digital goods and services. We show that this can be formulated as a finite series of more conventional constrained pricing problems. We then establish that the optimal nonlinear pricing schedule with discontinuous supply functions coincides with the solution to one specific constrained problem, reduce the former to a problem of identifying the optimal number of "blocks" of demand that the seller will fulfil under their optimal pricing schedule, and show how to identify this optimal number using a simple and intuitive rule (which is analogous to "balancing" the marginal revenue with average "marginal cost"). We discuss the extent to which using "information-goods" pricing schedules rather than those that are optimal reduce profits for sellers of digital goods. A first extension includes the rapidly declining infrastructure costs associated with Moore’s Law to provide insight into the relationship between the magnitude of cost declines, infrastructure planning and pricing strategy. A second extension examines multi-market pricing of a set of digital goods and services whose supply is fulfilled by a shared infrastructure. Our paper provides a new pricing model which is widely applicable to IT, network and electronic commerce products. It also makes an independent contribution to the theory of second-degree price discrimination, by providing the first solution of monopoly screening when costs are discontinuous, and when costs incurred can only be associated with the total demand fulfilled, rather than demand from individual customers. |
| Keywords: | digital goods, price discrimination, nonlinear pricing, screening, discontinuous costs, shared infrastructure, Moore’s Law |
| JEL: | D41 D82 L1 |
| Date: | 2006–09 |
| URL: | http://d.repec.org/n?u=RePEc:net:wpaper:0611&r=mkt |
| By: | James E. Prieger (Pepperdine University); Wei-Min Hu (University of California, Davis) |
| Abstract: | We explore the indirect network effect in the market for home video games. We examine the video game console makers’ strategic choice between increasing demand by lowering console price and by encouraging the growth of software variety. We also explore the existence of an applications barrier to entry in the console market, and find that there is little evidence for such a barrier. Finally, we assess the applicability of the model to out-of-sample situations, to look at whether our model and previous similar models can generalize to other markets for purposes of marketing or antitrust inquiry. We find that the model generalizes reasonably well to the Japanese market for the same generation of gaming systems, but poorly to previous generations in the US market. |
| Date: | 2006–10 |
| URL: | http://d.repec.org/n?u=RePEc:net:wpaper:0625&r=mkt |
| By: | Jay Pil Choi (Michigan State University) |
| Abstract: | This paper analyzes the effects of tying arrangements on market competition and social welfare in two-sided markets when economic agents can engage in multi-homing, that is, they can participate in multiple platforms in order to reap maximal network benefits. The model shows that tying induces more consumers to multi-home and makes platform-specific exclusive content available to more consumers, which is also beneficial to content providers. As a result, tying can be welfare-enhancing if multi-homing is allowed, even in cases where its welfare impacts are negative in the absence of multi-homing. The analysis thus can have important implications for recent antitrust cases in industries where multi-homing is prevalent. |
| Keywords: | tying, two-sided markets, (indirect) network effects, multi-homing. |
| JEL: | L1 L4 |
| Date: | 2006–09 |
| URL: | http://d.repec.org/n?u=RePEc:net:wpaper:0604&r=mkt |
| By: | Jennifer Zhang (University of Toledo); Abraham Seidmann (University of Rochester) |
| Abstract: | Previous studies suggested that a monopoly durable goods seller can use leasing to effectively avoid the time-inconsistent problem raised by Coase Conjecture. This paper extends those previous works by examining the monopoly seller’s selling and leasing strategy for a special type of durable good --- software. We look at a software vendor that can sell (at a posted price) or lease his product where as a lesser he guarantees that the lessees will always have the latest version of the software. We address some of the specific issues of implementing the selling and/or leasing policies at the packaged software market, including the impact of network externality, upgrade compatibility, and commitment on pricing in a dynamic environment. We show that by properly defining their pricing structure, software vendors can segment the market and second-degree price discriminate the consumers. We also demonstrate how software vendors can manage the trade-offs of selling and leasing to achieve a higher profit as well as the corresponding welfare effect on the consumers. |
| Keywords: | Software licensing, Coarse Conjecture, Price discrimination, Network externality, Commitment, Upgrade, Compatibility, Risk. |
| Date: | 2006–09 |
| URL: | http://d.repec.org/n?u=RePEc:net:wpaper:0613&r=mkt |