Behavior In Online Auctions Research Articles

The Happiness Premium: The Impact of Emotion on Individuals’ Willingness to Pay in Online Auctions

Individuals' bidding behavior in online auctions has been the subject of research in multiple disciplines. Emotion has been shown to be an important factor affecting individual behavior and decision making but we know little about its effects on online bidding. A lab experiment was conducted to investigate the impact of positive emotion on individuals' willingness to pay in online auctions. We found that individuals with mildly positive emotion bid more than those with neutral emotion, that is, they paid a happiness premium of about 10%. The effect size is medium (Cohen's d=.41). This study contributes to electronic commerce literature by identifying emotion as an important factor affecting individual online auction behavior. The findings provide guidance to auction websites interface design. By incorporating emotion content, websites can increase bids by influencing consumers' positive emotion.

Brand Equity Effects on Bidding Strategies in an Online Environment

Internet auction bidders seldom have all the information resources upon which they have learned to comfortably rely. This raises the possibility that internet auction participants depend more on brand related knowledge and employ bidding strategies consistent with heightened valuations of brand related information. This study empirically examines how differences in brand equity affect consumer online auction behavior on eBay. Branded products with objective values (certified coins) are examined for differences in bidding behavior across auctions. The results indicate auction participants employ incremental bidding strategies for preferred brands that have higher prices except when those brands were for coins of the highest quality. Auctions that had sellers who were not power sellers or which did not take Paypal are more prone to attract late or last minute bidders.

Determinants of Individuals' Willingness to Continue Bidding in Online Auctions: From the Gambling Perspective

Given the unique features of bidding behaviors, such as the joy of finding items, the thrill of bidding, and the excitement of winning, it is likely that some bidders will engage in continued bidding behavior in online auctions, and this behavior might be explained from the gambling perspective. Accordingly, this study attempts to integrate the variables from TAM with cognitive absorption and the escalation of commitment from the gambling perspective in an effort to explain a bidder`s behavior. The results from 258 responses to the survey demonstrate that all the constructs in the study affect a bidder`s willingness to continue bidding in the online auction context. By constructing the proposed research model from the gambling perspective, this study can provide an alternative theoretical lens by which online bidders may be viewed, thus bolstering our current understanding of how willingness to continue bidding is driven-in service of this goal, this study applies several concepts, including cognitive absorption, TAM, and escalation of commitment. Furthermore, based on the findings, this study contributes to online auction sites which need to make their strategies to the bidders by examining an individual willingness to continue bidding.

Auction Fever: Exploring Informational Social Influences on Bidder Choices

Previous investigations of herd behavior have identified the importance of informational social influences in consumer decision making. This research presents three studies examining herd behavior in online auctions. The three studies addressed the influence on bidder online choices of herd cues frequently found in online auctions, including bid number, feedback ratings, and number of questions and answers. This research also investigated the effect of different levels of herd cues on bidder online choices under high and low brand awareness in online auctions. The experimental results demonstrated that bidders use online herd cues when making decisions in online auctions. Additionally, different levels of herd cues influence bidder online choices in both high and low brand awareness product situations.

Commentary—Bidders' Experience and Learning in Online Auctions: Issues and Implications

This study explores the implications of rejecting the sealed-bid abstraction proposed by Zeithammer and Adams [Zeithammer, R., C. Adams. 2010. The sealed-bid abstraction in online auctions. Marketing Sci. 29(6) 964–987]. Using a conditional order statistic model that relies on the joint distribution of the top two proxy bids of an auction, Zeithammer and Adams show that inexperienced bidders' reactive bidding is the main cause of the rejection of the sealed-bid abstraction. Their empirical study suggests that a large percentage of bidders reactively bid, and there is weak evolutionary pressure for bidders to converge to sealed bidding. We discuss theoretical implications of this rejection and the role of bidder experience, as well as inferences about bidder learning. Tracking an inexperienced bidder's bidding behavior over time, we show that bidders learn and their bidding strategy gravitates toward rational bidding. Potential biases in bidder experience measurement and bidder learning can be assessed using a cross-sectional, time-series data set that tracks a random sample of new eBay bidders. Learning speed is faster with their complete bidding history rather than feedback ratings or winning observations only. We highlight the importance of proper measures of bidder experience and its effect on bidding strategy evolutions, both of which play important roles in clarifying bidding behavior in online auctions.

The Sealed-Bid Abstraction in Online Auctions

This paper presents five empirical tests of the popular modeling abstraction that assumes bids from online auctions with proxy bidding can be analyzed “as if” they were bids from a second-price sealed-bid auction. The tests rely on observations of the magnitudes and timings of the top two proxy bids, with the different tests stemming from different regularity assumptions about the underlying distribution of valuation signals. We apply the tests to data from three eBay markets—MP3 players, DVDs, and used cars—and we reject the sealed-bid abstraction in all three data sets. A closer examination of these rejections suggests that they are driven by less experienced bidders. This consistent rejection casts doubt on several existing theories of online auction behavior and suggests some demand estimates based on the abstraction can be biased. To assess the direction and magnitude of this bias, we propose and estimate a new model in which some bidders conform to the abstraction while other bidders bid in a reactive fashion. Because reactive bidding can be at least partially detected from the data, we are able to estimate the underlying distribution of demand and compare it to what the sealed-bid abstraction implies. We find that our proposed model fits the data better, and our demand estimates reveal a large potential downward bias were we to assume the second-price sealed-bid model instead.

Buy-It Now: One Dollar Auction Attractive?

This paper discusses factors affecting the buy-it-now (BIN) market behavior in online auctions. The study includes performing a probit analysis — using a collected data set to find out how the independent variables affect the BIN behavior. Three most critical factors, starting price, BIN price and seller's reputation, were identified by the probit model for studying whether a BIN option was used or not. Then, the study uses a factorial design to identify impacts of important factors. The key findings are that the BIN price plays an important role in affecting the final price formation (47.6%) and a seller's reputation is critical to affect the performance of the bid duration (74.9%). These observations can help the predictions of the final price formation and bid duration in the future and further improve the efficiency of the BIN institution. Sellers should use an attractable BIN price to increase their revenue rate and keep an excellent reputation to reduce the bid duration. Since the starting price has only minor effects, the seller needs not to put much effort on that and the so-called “one dollar auction” seems to be a good idea.

The Sealed-Bid Abstraction in Online Auctions

This paper presents five empirical tests of the popular modeling abstraction that assumes bids from online auctions with proxy bidding can be analyzed “as if” they were bids from a second price sealed-bid auction. The tests rely on observations of the magnitudes and timings of the top two proxy bids, with the different tests stemming from different regularity assumptions about the underlying distribution of valuation signals. We apply the tests to data from three eBay markets - MP3 players, DVDs, and used cars - and we reject the sealed-bid abstraction in all three datasets. A closer examination of these rejections suggests they are driven by less experienced bidders. This consistent rejection casts doubt on several existing theories of online auction behavior and suggests some demand estimates based on the abstraction can be biased. To assess the direction and magnitude of this bias, we propose and estimate a new model in which some bidders conform to the abstraction while other bidders bid in a reactive fashion. Since reactive bidding can be at least partially detected from the data, we are able to estimate the underlying distribution of demand and compare it to what the sealed-bid abstraction implies. We find that our proposed model fits the data better, and our demand estimates reveal a large potential downward bias were we to assume the second-price sealed-bid model instead.

Reactivity based model to study online auctions dynamics

Online auctions have challenged many assumptions and results from the traditional economic auction theory. Observed bidder behavior in online auctions often deviates from equilibrium strategies postulated by economic theory. In this research, we consider an online auction as an information system that provides a long-duration, information-rich, dynamic application environment in which users (bidders) interact with the system in a feedback loop, in what we term reactivity. Bidders react to the observed conditions of the auction and events triggered by actions of other bidders. In this work we propose a new characterization model with the purpose of isolating the segments of the auction in which users react to the auction conditions and events. Through this model, it is possible to enrich the auction characterization. Despite the existence of other bidding characterization models, none of them is enough for understanding the factors that characterize and explain the auction dynamics. We present results which demonstrate the advantages of applying our methodology. The final objective is to gain an understanding of what drives the dynamics of online auctions, the role of reactivity in the auction dynamics, and how the outcome of the auction is affected by the particular dynamics of the system.

Factors influencing online auction repurchase intention

PurposeThe purpose of this study is to integrate expectancy disconfirmation theory (EDT) to explore cognitive beliefs and affect influencing an individual's intention to repurchase in online marketplaces.Design/methodology/approachThe paper used EDT to conduct an empirical study and data were collected from a total of 303 bidders of online auctions. A structural equation modeling (SEM) was used to assess the relationships of the research model.FindingsThe findings show that bidders' disconfirmation of online auctions is positively associated with their satisfaction, which in turn is positively associated with their repurchase intentions.Practical implicationsBoth bidders' expectation of policy and auctioneers' performance of policy are important determinants of disconfirmation. Auctioneers need to recognize the distinctive roles of information policy in selling and bidding rules. Besides, neither bidders' expectation of sellers' reputation nor their expectation of service quality has a significant relationship with disconfirmation. This finding implies that in a mature e‐commerce environment bidders pay more attention to the sellers' performance than their prior expectation.Originality/valueThis study, which aims to shed light on bidder behavior in online auctions, is the first study that has applied an EDT‐based model to investigate the determinants of repurchase intention in online auctions.

User Heterogeneity and Its Impact on Electronic Auction Market Design: An Empirical Exploration

While traditional information systems research emphasizes understanding of end users from perspectives such as cognitive fit and technology acceptance, it fails to consider the economic dimensions of their interactions with a system. When viewed as economic agents who participate in electronic markets, it is easy to see that users' preferences, behaviors, personalities, and ultimately their economic welfare are intricately linked to the design of information systems. We use a data-driven, inductive approach to develop a taxonomy of bidding behavior in online auctions. Our analysis indicates significant heterogeneity exists in the user base of these representative electronic markets. Using online auction data from 1999 and 2000, we find a stable taxonomy of bidder behavior containing five types of bidding strategies. Bidders pursue different bidding strategies that, in aggregate, realize different winning likelihoods and consumer surplus. We find that technological evolution has an impact on bidders' strategies. We demonstrate how the taxonomy of bidder behavior can be used to enhance the design of some types of information systems. These enhancements include developing user-centric bidding agents, inferring bidders' underlying valuations to facilitate real-time auction calibration, and creating low-risk computational platforms for decision making.