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Author: Guojie Wang
Publisher:
ISBN:
Category : Electronic Dissertations
Languages : en
Pages : 69
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Book Description
This dissertation consists of three essays. The first essay adopts the survival analysis to empirically analyze a new auction format, pay-per-bid auction, in which a fee occurs to the bidder when a new bid is submitted. This auction mechanism attracted many theoretical studies and empirical testing in recent years. However, analyzing the pay-per-bid auction under the survival framework provides a novel path to reflect this new auction format as well as involved bidder and seller behaviors. By considering the arrival of bids as a necessary condition for a pay-per-bid auction to survive, survival analysis tools such as Kaplan-Meier (KM) estimate and Accelerated Failure Time (AFT) models are applied to the data set collected from a leading pay-per-bid auction site Swoopo. Cox Proportional Hazard (PH) model is also discussed. Some equilibrium behaviors are confirmed but also some equilibrium deviated behaviors are detected. The second essay models the last-minute bidding behaviors in eBay's hard close auction design using non-parametric analysis. For comparison purpose, the auctions in Amazon with soft close auction design are combined to carry out analysis. The data is selected from eBay and Amazon and a large difference in bid timing is found between auction sites. Density estimation of bid timing confirms the existence of such difference. Mixed additive model is applied to explore the nonparametric relationship between bid timing and parameters of bidding environment. And generalized response model with logistic link function is used to model the probability of a late bidding occurs conditioned on interested covariates. The third essay proposes, from a non-parametric Bayesian aspect, using Dirichlet Processes (DP) with normal mixtures to estimate underlying valuations in second-price ascending auctions under the independent-private-values paradigm. I illustrate how a second-price ascending auction is similar in mechanism to its sealed counterpart and consequently bidders' valuations can be extracted if bidders are identifiable. Compared to classical methods, to provide more flexible and reliable inferences, DP density estimation is strongly motivated and represents an advance. As a non-parametric Bayesian method, DP can accommodate non-nomality through normal mixtures and develop Bayesian inference on model parameters. Due to the complex nature of posteriors, MCMC simulation is used to approximate posteriors as well as density predictions. To test the validity of this method, a Monte Carlo experiment is conducted with similar sample size to our eBay data. In the last section, I reanalyze a data set from eBay auctions and apply our method to estimate the valuations.
Author: Guojie Wang
Publisher:
ISBN:
Category : Electronic Dissertations
Languages : en
Pages : 69
Get Book Here
Book Description
This dissertation consists of three essays. The first essay adopts the survival analysis to empirically analyze a new auction format, pay-per-bid auction, in which a fee occurs to the bidder when a new bid is submitted. This auction mechanism attracted many theoretical studies and empirical testing in recent years. However, analyzing the pay-per-bid auction under the survival framework provides a novel path to reflect this new auction format as well as involved bidder and seller behaviors. By considering the arrival of bids as a necessary condition for a pay-per-bid auction to survive, survival analysis tools such as Kaplan-Meier (KM) estimate and Accelerated Failure Time (AFT) models are applied to the data set collected from a leading pay-per-bid auction site Swoopo. Cox Proportional Hazard (PH) model is also discussed. Some equilibrium behaviors are confirmed but also some equilibrium deviated behaviors are detected. The second essay models the last-minute bidding behaviors in eBay's hard close auction design using non-parametric analysis. For comparison purpose, the auctions in Amazon with soft close auction design are combined to carry out analysis. The data is selected from eBay and Amazon and a large difference in bid timing is found between auction sites. Density estimation of bid timing confirms the existence of such difference. Mixed additive model is applied to explore the nonparametric relationship between bid timing and parameters of bidding environment. And generalized response model with logistic link function is used to model the probability of a late bidding occurs conditioned on interested covariates. The third essay proposes, from a non-parametric Bayesian aspect, using Dirichlet Processes (DP) with normal mixtures to estimate underlying valuations in second-price ascending auctions under the independent-private-values paradigm. I illustrate how a second-price ascending auction is similar in mechanism to its sealed counterpart and consequently bidders' valuations can be extracted if bidders are identifiable. Compared to classical methods, to provide more flexible and reliable inferences, DP density estimation is strongly motivated and represents an advance. As a non-parametric Bayesian method, DP can accommodate non-nomality through normal mixtures and develop Bayesian inference on model parameters. Due to the complex nature of posteriors, MCMC simulation is used to approximate posteriors as well as density predictions. To test the validity of this method, a Monte Carlo experiment is conducted with similar sample size to our eBay data. In the last section, I reanalyze a data set from eBay auctions and apply our method to estimate the valuations.
Author: Wolfgang Jank
Publisher: John Wiley & Sons
ISBN: 1118031865
Category : Mathematics
Languages : en
Pages : 321
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Book Description
Explore cutting-edge statistical methodologies for collecting, analyzing, and modeling online auction data Online auctions are an increasingly important marketplace, as the new mechanisms and formats underlying these auctions have enabled the capturing and recording of large amounts of bidding data that are used to make important business decisions. As a result, new statistical ideas and innovation are needed to understand bidders, sellers, and prices. Combining methodologies from the fields of statistics, data mining, information systems, and economics, Modeling Online Auctions introduces a new approach to identifying obstacles and asking new questions using online auction data. The authors draw upon their extensive experience to introduce the latest methods for extracting new knowledge from online auction data. Rather than approach the topic from the traditional game-theoretic perspective, the book treats the online auction mechanism as a data generator, outlining methods to collect, explore, model, and forecast data. Topics covered include: Data collection methods for online auctions and related issues that arise in drawing data samples from a Web site Models for bidder and bid arrivals, treating the different approaches for exploring bidder-seller networks Data exploration, such as integration of time series and cross-sectional information; curve clustering; semi-continuous data structures; and data hierarchies The use of functional regression as well as functional differential equation models, spatial models, and stochastic models for capturing relationships in auction data Specialized methods and models for forecasting auction prices and their applications in automated bidding decision rule systems Throughout the book, R and MATLAB software are used for illustrating the discussed techniques. In addition, a related Web site features many of the book's datasets and R and MATLAB code that allow readers to replicate the analyses and learn new methods to apply to their own research. Modeling Online Auctions is a valuable book for graduate-level courses on data mining and applied regression analysis. It is also a one-of-a-kind reference for researchers in the fields of statistics, information systems, business, and marketing who work with electronic data and are looking for new approaches for understanding online auctions and processes. Visit this book's companion website by clicking here
Author: Yu Zhang
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
This dissertation, which consists of three essays, studies online auctions both theoretically and empirically. The first essay studies a special online auction format used by eBay, "Buy-It- Now" (BIN) auctions, in which bidders are allowed to buy the item at a fixed BIN price set by the seller and end the auction immediately. I construct a two-stage model in which the BIN price is only available to one group of bidders. I find that bidders cutoff is lower in this model, which means, bidders are more likely to accept the BIN option, compared with the models assuming all bidders are offered the BIN. The results explain the high frequency of bidders accepting BIN price, and may also help explain the popularity of temporary BIN auctions in online auction sites, such as eBay, where BIN option is only offered to early bidders. In the second essay, I study how bidders' risk attitude and time preference affect their behavior in Buy-It-Now auctions. I consider two cases, when both bidders enter the auction at the same time (homogenous bidders) thus BIN option is offered to both of them, and when two bidders enter the auction at two different stages (heterogenous bidders) thus the BIN option is only offered to the early bidder. Bidders' optimal strategies are derived explicitly in both cases. In particular, given bidders' risk attitude and time preference, the cutoff valuation, such that a bidder will accept BIN if his valuation is higher than the cutoff valuation and reject it otherwise, is calculated. I find that the cutoff valuation in the case of heterogenous bidders is lower than that in the case of homogenous bidders. The third essay focuses on the empirical modeling of the price processes of online auctions. I generalize the monotone series estimator to model the pooled price processes. Then I apply the model and the estimator to eBay auction data of a palm PDA. The results are shown to capture closely the overall pattern of observed price dynamics. In particular, early bidding, mid-auction draught, and sniping are well approximated by the estimated price curve.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
This thesis provides a discussion on some analytical and empirical models of online auctions. The objective is to provide an alternative framework for analyzing online auctions, and to characterize the distribution of intermediate prices. Chapter 1 provides a mathematical formulation of the eBay auction format and background to the data used in the empirical analysis. Chapter 2 analyzes policies for optimally disposing inventory using online auctions. It is assumed a seller has a fixed number of items to sell using a sequence of, possibly overlapping, single-item auctions. The decision the seller must make is when to start each auction. The decision involves a trade-off between a holding cost for each period an item remains unsold, and a cannibalization effect among competing auctions. Consequently the seller must trade-off the expected marginal gain for the ongoing auctions with the expected marginal cost of the unreleased items by further deferring their release. The problem is formulated as a discrete time Markov Decision Problem. Conditions are derived to ensure that the optimal release policy is a control limit policy in the current price of the ongoing auctions. Chapter 2 focuses on the two item case which has sufficient complexity to raise challenging questions. An underlying assumption in Chapter 2 is that the auction dynamics can be captured by a set of transition probabilities. Chapter 3 shows with two fixed bidding strategies how the transition probabilities can be derived for a given auction format and bidder arrival process. The two specific bidding strategies analyzed are when bidders bid: 1) a minimal increment, and 2) their true valuation. Chapters 4 and 5 provides empirical analyzes of 4,000 eBay auctions conducted by Dell. Chapter 4 provides a statistical model where over discrete time periods, prices of online auctions follow a zero-inflated gamma distribution. Chapter 5 provides an analysis of the 44,000 bids placed in the auctions, based on bids.
Author: Ernan Haruvy
Publisher: Now Publishers Inc
ISBN: 1601983328
Category : Business & Economics
Languages : en
Pages : 87
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Book Description
Internet Auctions reviews recent empirical and theoretical works on internet auctions with a focus on internet auction design, formats, and features that are currently debated in the marketing literature.
Author: Wei Guo
Publisher:
ISBN:
Category :
Languages : en
Pages : 12
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Book Description
There has been substantial work exploring strategies, both theoretical and empirical, for selling and buying in online auctions. However, much of this work has considered single auctions in isolation, partially because it is hard to examine multiple simultaneous auctions using traditional math modeling approaches. In reality, many auctions occur simultaneously, so there is competition not just among bidders, but also among auctions. In this paper, we use simulation to explore bidders' switching behavior between auctions for similar products. Using an empirical dataset, we first examine the distribution of switching and associated bidding behavior in real auctions. We use this data to create an agent-based model that reproduces the price process observed in the empirical data. Using this model we then explore the effects of: (1) different switching distributions, (2) the switching rule, i.e., which auction to switch to, and (3) different auction start rates. In the end, we show that in order to maximize the final price and to minimize the price disparity, auction platforms should encourage users to switch to a low-price auction that is ending soon.
Author: Kanghyun Yoon
Publisher:
ISBN:
Category : Consumer behavior
Languages : en
Pages : 248
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Book Description
Author: Saumyanil Deb
Publisher:
ISBN:
Category :
Languages : en
Pages : 214
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Book Description
This dissertation investigates the seller's decision on whether or not to reveal bidder information in online auctions. It makes a novel contribution to the literature by investigating the relationship between bidder information asymmetry and bidder experience level. Bidder information is a signal about the experience level of bidder. Bidder experience affects the strategic decisions of both buyers and sellers. Using data from 500 Egyptian antique auctions (a common value auction) and 500 laptop auctions (a private value auction), following main results are identified. First, sellers reveal bidder information more often in private value auctions than in common value auctions. Second, in common value auctions, sellers earn higher average prices when they conceal bidder information. In private value auctions, sellers generate higher average prices when proportionally more inexperienced bidders are present, regardless of whether or not they reveal bidder information. Then, in common value auctions, late bidding is observed more frequently when bidder information is revealed. Late bidding is relatively less common in private value auctions than in the common value auctions, regardless of whether or not sellers reveal bidder information.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 218
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Book Description
The first chapter studies identification and estimation of first-price auctions if the bidders face ambiguity about the distribution of valuations. Ambiguity is modeled using Gilboa and Schmeidler's (1989) Maxmin Expected Utility preferences. We exploit variation in the number of bidders to identify the essential primitives of the model. The identification result yields a closed form for the inverse bid function, which suggests a two-step estimation procedure. We study asymptotic and finite sample properties of the estimators. We find evidence of ambiguity in USFS timber auctions which leads to aggressive bidding for bidders with high valuations and has important implications for auction design. The second chapter proposes a procedure to test restrictions on infinite-dimensional parameters (partially) identified by unconditional or conditional moment equalities. Our new method allows us to test restrictions involving a continuum of inequalities. Examples of such restrictions include weakly increasing, concavity and first-order stochastic dominance. We show that our testing procedure controls size uniformly and has power approaching 1 against fixed alternatives. We conduct Monte Carlo Experiments to study the finite sample properties of our procedure. The third chapter studies the inference problem of bidders' risk attitudes in Independent Private Value (IPV) first-price auctions with multiplicative auction-level unobserved heterogeneity. Bidders are assumed to have Constant Relative Risk Aversion. Under the exclusion restriction that bidders randomly select themselves into auctions given the auction-level unobserved heterogeneity, bidders' CRRA coefficient is point-identified from bid data of auctions with at least two different number of active bidders. Our exclusion restriction is consistent with a variety of models with endogenous entry. Empirical application to USFS timber auctions shows that we will conclude that timber firms are risk averse if we ignoring the unobserved heterogeneity. But once we take the unobserved heterogeneity into account, risk neutrality is consistent with the data.
Author: Barbora Máková
Publisher: LAP Lambert Academic Publishing
ISBN: 9783659399855
Category :
Languages : en
Pages : 112
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Book Description
This book presents an empirical analysis of price determinants and bidders' behavior in online auctions eBay.de and Aukro.cz. We focus on the effect of sellers' feedback rating score and the phenomenon of sniping. Buyers in online auctions cannot personally inspect the quality of the product, so they have to rely on seller's honesty. In this setting, seller's rating may significantly contribute to the final price formation. Sniping is a bidding strategy, whereby a bidder waits until the last moment of the bidding period to place her bid. The impact of sniping on the final price and parameters affecting the probability of sniping are examined in this paper. The empirical results for both auction web sites show that seller's feedback rating score has significant impact on the final price. The tests regarding sniping provided significant results only for the eBay auction. The effect of sniping on final price is not clear since we obtain different results for different specifications, but we found out that the experience of a bidder increases the probability of placing snipe bid. The study should be especially useful to all users of internet auction portals.
