Bidding Experience Research Articles

The Economic, Municipal, And Social Impact of Major Sporting Events on Host Countries – The World Cup as Examples

The full name of the World Cup is the FIFA World Cup, which is participated by the world's national football teams, symbolizing the highest level of football, the highest honor, and the greatest influence. If a country wants to host the World Cup, it first needs to be a member of international football. The second is to submit an application to the national FIFA (which can be hosted by two or even three countries), and then voted by all FIFA member states. So the World Cup venue is very strict because the World Cup has always been a significant sporting event which will bring many benefits to the local area. Of course, there are many disadvantages. This paper analyzes the bidding experience and risk assessment of hosting the World Cup over the years, analyzes and puts forward relevant risks by identifying the Qatar World Cup, summarizes the hidden dangers and problems existing after the World Cup, provides effective concepts and solutions for the construction of risk response strategies, and puts forward specific measures for future World Cups for the problems raised.

The effect of experienced regret based on gender differences in auction

This study aims to show how experiencedregret influences the decisions made by bidders of differentgenders in an auction. - In this paper, the data is collected through a real-time recorded tv show about English auctions. In previous studies, female participants tend to be more risk-sensitive and rational than male bidders. Based on this trend, we hypothesized that female bidders would make quick decisions compared to male bidders after the bidder experience regret.

High‐Temperature Exposure and Land Transactions in China

AbstractWe estimate the relationship between high‐temperature exposure and land transaction using daily transaction data from 2013 to 2018 in China. Standard hedonic price method is used to perform multidimensional fixed effects regression on 458,564 transaction samples. This study shows that each additional day of the extremely high temperature increases the average bid price by 0.6%, which is equivalent to an additional annual increase of 15.018 billion yuan in land transaction costs. The effect of high temperature on land prices is considerably stronger for residential and commercial lands. We further find that high‐temperature‐induced changes of mood and cognition play a role. Extreme gradient boosting (XGBoost) algorithm is used to calculate price deviation, which overcome missing eigenvalues and reduce nonlinear measurement error. Our findings indicate that heat can make investors more aggressive, which occurs when bidders continue to raise prices to win. The number of bidding behavior will not drop due to the hidden costs of land transactions. Specially, bidding experience offsets the cognitive output bias. This study contributes to the behavioral finance and decision‐making literature, helps investors make better investment management decisions, and alleviates the negative effect of land transaction premium on the real estate market.

Data-driven online interactive bidding strategy for demand response

Demand response (DR), as one of the important energy resources in the future’s grid, provides the services of peak shaving, enhancing the efficiency of renewable energy utilization with a short response period, and low cost. Various categories of DR are established, e.g. automated DR, incentive DR, emergency DR, and demand bidding. However, with the practical issue of the unawareness of residential and commercial consumers’ utility models, the researches about demand bidding aggregator involved in the electricity market are just at the beginning stage. For this issue, the bidding price and bidding quantity are two required decision variables while considering the uncertainties due to the market and participants. In this paper, we determine the bidding and purchasing strategy simultaneously employing the smart meter data and functions. A two-agent deep deterministic policy gradient method is developed to optimize the decisions through learning historical bidding experiences. The online learning further utilizes the daily newest bidding experience attained to ensure trend tracing and self-adaptation. Two environment simulators are adopted for testifying the robustness of the model. The results prove that when facing diverse situations the proposed model can earn the optimal profit via off/online learning the bidding rules and robustly making the proper bid.

When Good Things Turn Bad: Evidence from G-7 Serial Acquirer Bidding

This study investigates the impact of acquirer bidding experience on acquiring abnormal returns based on empirical evidence from a large sample of 10,880 bidders making 23,852 deals from G-7 countries. Both event study and regressions analysis have been used to examine the impact of acquirer bidding experience on acquirer returns. The findings show that “single acquirers” achieve higher returns, with a cumulative average abnormal return (CAAR) of 3.354%, but this number tends to decrease with increasing numbers of previous bids. In addition, the results of the bivariate analysis demonstrate that a single acquisition alone generates greater abnormal returns than those which are part of a series of acquisitions, with very robust results even after accounting for additional heterogeneity in payment method, target status and country/industry diversification. The findings of the multivariate analysis also confirm that serial acquirers are associated with significantly lower abnormal returns. This evidence conflicts with the notion that more experience with mergers and acquisitions (M&As) will correspond to improve target valuation and thus lead to more profitable agreements. In contrast, my findings imply that shareholder wealth is destroyed by serial acquirers, which suggests that the goal of maximising firm value is not always the sole motivation for engaging in M&A activities.

Probability of mergers and acquisitions deal failure

Purpose The purpose of this paper is to investigate whether the probability of deal success/failure in mergers and acquisitions (M&As) transactions is influenced by a range of deal, firm and country-specific characteristics which tend to affect acquirers’ shareholder returns. The specific hypotheses under investigation relate to the method of payment (cash versus stock), target status (listed versus non-listed), diversification (domestic versus cross-border and industry-wide) and acquirers’ prior bidding experience. Additionally, the authors also investigate whether announced deals reflect an expectation about likelihood of deal completion. Design/methodology/approach The authors analyse the probability of deal success/failure in M&As by combining event study and probit regression-based methods. The authors use the standard event study methodology to calculate acquirers’ abnormal returns for up to 10 days before and after the announcement date. In the probit model, the dependent variable is the probability of deal i being failure depending on four sets of explanatory variables: method of payment, target status, diversification and acquirer bidding experience, along with a set of control variables. Findings The findings from event study confirm that market reaction is indifferent to whether announced deals are likely to be successfully completed or not, consistent with the efficient markets hypothesis. However, the results from cross-sectional, cross-country regressions confirm that the aforementioned deal characteristics, as well as certain firm and country level attributes do influence the likelihood of whether an announced deal is subsequently completed or terminated. Originality/value In examining whether the specific characteristics affecting the likelihood that M&A transactions, once announced, will ultimately succeed or fail, it seems natural to ask whether the market reaction at the time of deal announcement reflects an expectation regarding deal completion. This could be associated with specific deal or firm-level characteristics influencing shareholder returns or risk, and represents a unique contribution of this study, over and above the use of a global sample of M&A data. The empirical analysis investigates these issues by using an extensive, global sample of 46,758 M&A transactions from 180 countries and 80 industries, which took place between the years 1977 and 2012.

Modeling Advertisers' Willingness to Pay in TV Commercial Slot Auctions

Auctions are receiving increasing attention from both practitioners and researchers in the TV advertising market. This paper studies advertisers' willingness to pay (WTP) in Hong Kong television commercial slot auctions, defined as overlapped, multiple-winner auctions with discrete, ascending, semi-sealed bids. We specify advertisers' WTP as a parametric function of their valuations of slot-specific attributes and the valuations that depend on the context of the focal auction and on the competition from other auctions of similar commercial slots. We extend the two “no-regret” bidding principles (first proposed by Haile and Tamer 2003) to obtain informative boundary conditions for asymptotical identification. The estimation results suggest that advertisers' WTP increases with the TV rating of the program in which the advertisement is embedded and decreases with the bidder's bidding experience and the number of similar slot options available. The WTP also depends on the number of bidders classified into the same product category, as two directly competing advertisers are not allowed to advertise in the same commercial break. In the current practice, advertisers submit discrete bids using price levels set by the TV station. Based on the recovered bidder's WTP, we investigate how the TV station can set adjacent price levels and examine the resulting revenue implications.

Market Information and Bidder Heterogeneity in Secondary Market Online B2B Auctions

Online auction environments provide several sources of information that can be used by bidders to form their bids. The impact of this information on bidding is likely to be higher when ambiguously specified products are auctioned. The secondary market represents one such environment, where used and returned items from big-box retailers are auctioned off to other business buyers. Using a proprietary data set of secondary market auctions hosted on an online business-to-business platform, we study how market pricing information from other auctions for comparable products affects the bidding behavior of the first bidder. First bidders are shown to be influenced by two sets of pricing information: prices from their own historical bidding behavior and concurrent prices, formed from other open and just-finished auctions relative to the focal auction. We also study how the impact of this market pricing information is moderated by bidder heterogeneity, captured by bidder experience and cross-bidding activity on the platform across comparable concurrent auctions. Finally, we show that the first bid is significantly associated with the auction’s final price, contingent on the type of first bidder. Auctions are increasingly being used for the sale of ill-defined and idiosyncratic products; our work thus provides managerial implications for how auctioneers may design and manage the flow of relevant information to different classes of bidders on their sites in order to enhance their yields. This paper was accepted by Lorin Hitt, information systems.

Comparative study between two market clearing schemes in wind dominant electricity markets

High price volatility and excessive price reduction are introduced as two emerging problems in wind dominant electricity markets. In this study, an agent-based simulation methodology is employed to investigate the impact of two pricing mechanisms, uniform and pay-as-bid, on the mentioned problems. According to the proposed agent-based approach, electricity market agents (here generation units) learn from their previous bidding experience to obtain maximum financial. A comparative study is then conducted to investigate the impact of mentioned pricing schemes on price volatility and average price level. It is shown that these two pricing mechanisms cause different bidding behaviours for the generation units. This study suggests that this change in market agent behaviour, modifies the overall price volatility and system average price. The results indicate that a pay-as-bid pricing mechanism can alleviate policy maker's concerns regarding mentioned emerging problems in power systems with extremely high percentage of wind power penetration. It is also shown that market efficiency is lower under pay-as-bid scheme. The validity of the proposed methodology is investigated using IEEE 24-bus test system with 33 generation units.

Overbidding in electronic auctions: factors influencing the propensity to overbid and the magnitude of overbidding

This research investigates the buyer and seller characteristics that impact overbidding in electronic auctions. Specifically, the empirical analysis shows that customers with more total experience are less likely to overbid and that overbidding is less frequent for auction items with higher face values. When bidder experience pertains to the same product category, the frequency and magnitude of overbids are further reduced. This research also finds that consumers are more likely to overbid as the bidding environment becomes more competitive. Furthermore, auction item attributes, such as starting price, day/time of the auction, and shipping fees, are shown to impact the propensity to overbid and the magnitude of overbidding. The empirical results have important implications for understanding bidder behavior and for assisting online sellers in formulating more profitable selling strategies.

Show Me The Goods

Consumers using online auction websites face the challenge of appraising products at a distance. Sellers and buyers in online auctions navigate this challenge by displaying and evaluating various cues, a critical one being use of photographs. Warranting theory predicts that cues less subject to control and manipulation by the presenter will be more influential in impression formation. Therefore, user-generated photographs which display the actual item should be more effective in generating successful auctions, more bidders, more bids, and higher prices, compared with stock photographs. A field experiment tested this prediction by systematically manipulating photographs for eBay auctions. User-generated photographs were found to have a positive effect on likelihood of selling and the number of auction bidders. Findings indicate that attracting more bidders is a possible mechanism for higher sale prices and also show a moderating role of bidder experience.

Reference Prices and Bidder Heterogeneity in Secondary Market Online B2B Auctions

Online auction environments provide several sources of information that can be used by bidders to form their bids. One such information set that has been relatively understudied in the literature pertains to reference prices available to the bidder from other concurrent and comparable auctions. In this paper, we study how reference prices from such auctions affect bidding behavior on the focal auction. We also study how the impact of these reference prices is moderated by bidder heterogeneity. Bidders are shown to be influenced by two sets of references prices: internal reference prices from their own historical bidding behavior and external reference prices, formed from other open and just-finished auctions relative to the focal auction. We measure bidder heterogeneity using bidder experience and level of participation in concurrent auctions. Our results show that external reference prices are significantly moderated by bidder heterogeneity. In a departure from current work, we use longitudinal data on auctions and bids in the B2B secondary markets, where goods represent salvage or returned items from big-box retailers and bidders are business buyers. The dataset comprises over 4000 auctions collected from a large liquidator firm in North America and is unique in its comprehensiveness. Our work provides theoretical insights that are complementary to the current set of results from B2C auctions as well as managerial implications for auctioneers in the B2B space.

Reference Prices and Bidder Heterogeneity in Secondary Market Online B2B Auctions

Online auction environments provide several sources of information that can be used by bidders to form their bids. The impact of this information on bidding is likely to be higher when ambiguously specifi ed products are auctioned. The secondary market represents one such environment, where used and returned items from big-box retailers are auctioned off to other business buyers. Using a proprietary dataset of secondary market auctions hosted on an online B2B platform, we study how market pricing information from other auctions for comparable products a ffects the bidding behavior of the first bidder. First bidders are shown to be influenced by two sets of pricing information: prices from their own historical bidding behavior and concurrent prices, formed from other open and just-finished auctions relative to the focal auction. We also study how the impact of these market pricing information are moderated by bidder heterogeneity, captured by bidder experience and cross bidding activity on the platform across comparable concurrent auctions. Finally, we show the fi rst bid is signi cantly associated with the auction's nal price, contingent on the type of first bidder. Auctions are increasingly being used for the sale of ill-defi ned and idiosyncratic products; our work thus provides managerial implications for how auctioneers may design and manage the flow of relevant information to di erent classes of bidders on their sites in order to enhance their yields.

Bidder Experience In Online Auctions: Effects On Bidding Choices And Revenue

<p class="MsoNormal" style="text-justify: inter-ideograph; text-align: justify; margin: 0in 0.5in 0pt; mso-pagination: none;"><span style="mso-bidi-font-style: italic;"><span style="font-size: x-small;"><span style="font-family: Times New Roman;">This paper describes research to determine the effects of bidder experience on performance in online auctions. Choice of bid type, the timing of bids, and the price paid are all examined for very experienced and very inexperienced bidders.<span style="mso-spacerun: yes;">  </span>The <span style="mso-spacerun: yes;"> </span>study draws on information systems empirical research, traditional auction theory, the results of lab experiments involving "live" auctions not mediated by computers, and existing research on online auctions.<span style="mso-spacerun: yes;">  </span>The results indicate that bidder experience is related to timing of bids and choice of bid type, but not to revenue realized. These findings have implications for bidders and researchers.</span></span></span></p>

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.

Rejoinder—Causes and Implications of Some Bidders Not Conforming to the Sealed-Bid Abstraction

This paper presents the authors' rejoinder to Zeithammer and Adams [Zeithammer, R., C. Adams. 2010. The sealed-bid abstraction in online auctions. Marketing Sci. 29(6) 964–987]. This rejoinder clarifies and qualifies conclusions of the original paper and makes suggestions for fruitful areas of future research. In particular, the original paper shows that bidding style can make a big difference in managerial decisions, but a structural model would be necessary to make confident predictions under different reserve prices. The rejoinder also clarifies the interpretation of feedback as a measure of bidder experience, and the relationship between bidder experience and bidding style.

The effect of experience on Internet auction bidding dynamics

On the basis of the bidding history of a panel of new eBay bidders, we examine the impact of different types of experiences on bidding behavior evolution. Accounting for unobserved bidder heterogeneity, the results indicate that losing experiences make the bidders’ bidding behavior evolve toward the normative predictions of auction theory, in that they submit fewer bids and bid later. Winning experiences, however, do not have such an effect. Moreover, the experience effect pertains to the bidder’s entire previous bidding experience regardless of product categories. We also assess the potential bias introduced by using feedback ratings (compared with actual participation) as experience measures.

Consumer Surplus in Online Auctions

Despite the growing research interest in Internet auctions, particularly those on eBay, little is known about quantifiable consumer surplus levels in such mechanisms. Using an ongoing novel field experiment that involves real bidders participating in real auctions, and voting with real dollars, we collect and examine a unique dataset to empirically quantify and understand determinants of consumer surplus in eBay auctions. The estimation procedure for private value auctions relies mainly on knowing the highest bid, which is not disclosed by eBay, but is available to us from our experiment. For common value auctions, where bidders bid strategically to avoid winner's curse, we develop an estimation procedure that infers the bidders' signals from their bids, and subsequently infers the item's common value and resulting surplus, from the signals. Our analysis, based on a sample of 4514 eBay auctions, indicates that the average surplus level per eBay auction is $15.59, which roughly translates to $6.5 billion in accrued consumer surplus for the year 2003 alone. We find that consumer surplus is significantly different across currencies and item categories, negatively influenced by seller experience, auction duration and competition, and positively influenced by bidder experience, bidder aggressiveness and item price.

Willingness to Pay and Competition in Online Auctions

The authors model how to measure consumer willingness to pay (WTP) using an English, or ascending first-price, auction based on two general bidding premises: No bidder bids more than his or her WTP, and no bidder allows a rival bidder to win at a price that he or she is willing to beat. In other words, the authors propose a “no-regret” rule in bidding. They impose no other restrictive assumptions on “maximands” or the bidders' behaviors in a competitive auction context. The authors model WTP as having two components: a pure product feature component and one based on the auction market environment. The latter includes bidder experience, seller reputation, and measures for competition among bidders and items. The proposed model is general enough to include a “buy-it-now” (equivalent to a posted price) auction mechanism. The authors use data on notebook auctions from one of the largest Internet auction sites in Korea. They find that most product characteristics matter in the expected ways. There are two additional primary findings: First, WTP declines as more similar items are concurrently listed with the focal item; there is an additional effect if these similar items also belong to the same brand. Therefore, market thickness matters for consumer WTP. Second, more extensive site surfing and bidding histories lead to lower WTP, implying that search costs and experience matter in bidding. As specific substantive benefits, the authors demonstrate how sellers can calculate changes in WTP and, thus, the expected revenue as the number of concurrently available similar items varies.

Auction hosting site pricing and market equilibrium with endogenous bidder and seller participation

This paper characterizes the payoffs and pricing policies of auction hosting sites when both the bidders’ and the sellers’ participation is endogenous. Sellers have heterogeneous opportunity costs and make a listing decision depending on the listing fee and the expected revenue from the sale. On the other side of the market, factors such as facility in navigating an interface layout and prior bidding experience result in bidder heterogeneity with respect to participation costs. Bidders participate if their ex ante expected payoff from searching the site exceeds their participation costs. The auction site earns revenue by setting positive listing fees, trading off the increased revenue per seller resulting from a higher fee with the revenue reduction from the loss of sellers. Though this appears to be a classic monopoly problem, there are important differences. The reduction in the number of sellers participating in a site has feedback effects, as it affects the number of bidders who choose to visit that site, which in turn again affects the attractiveness of the site to sellers, and thus further reduces seller participation. In this environment the monopolist’s ability to extract rents is severely limited, even if one considers rent extraction from the seller side of the market only. It is demonstrated that the inverse demand curve is flatter than the demand curve obtained from the (inverse) distribution of seller costs. Moreover, the inverse demand curve has at least one and possibly multiple flat segments, leading to discontinuities in the profit function. Thus, small changes in the environment can lead to large changes in the optimal fee and market participation.