A meta-analysis on the effects of online auction design options: The moderating effect of value uncertainty

Online auction design options (the public reserve price, secret reserve option and buy-out option) are critical in determining auction outcomes (the number of bids, the probability of sale and auction price). However, previous studies about the impacts of online auction design options on auction outcomes have generated inconsistent or even contradictory results. To synthesize the inconsistencies and reach more substantive conclusions, we conduct this meta-analysis study. Furthermore, to explain the inconsistencies, we identify the value uncertainty of auction items as a key moderator on the impacts of auction design options on auction outcomes, and verify the moderating effects using meta-analysis methods.This study has three main findings: (i) the public reserve price has a positive effect on the auction price, and this effect is stronger when the value uncertainty of auction items is higher; (ii) the secret reserve option has a positive effect on the auction price when auction items are of low value uncertainty, but the magnitude of this effect decreases when the value uncertainty increases; (iii) the buy-out option has positive effects on both the probability of sale and the auction price when auction items are of low value uncertainty, but has negative effects on these two auction outcomes when auction items are of high value uncertainty.     

Is that deal worth my money? The effect of relative and referent thinking on starting price under different promotion programs using hotel coupons in online auctions

Developments in information technology have made shopping at home much easier and have created a so-called “Otaku economy” that is an increasing focus for tourism and hotel business managers. A related development is the increase in the popularity and value of online auction channels. Scholars thus argue that it is important to examine what factors influence consumers’ bidding behavior in this new context. One issue is what initial bidding price and a promotion program must offer to attract customers to join an auction when they will be using a complex online auction mechanism. This study used a 2 × 2 between-subjects design and the principles of relative and referent thinking to examine the influence of the starting price (whether the starting price deviates from the reference price) and the promotion program (price vs. non-price) on consumers’ online bidding for hotel coupons. The results of the analysis indicate the following. First, starting price is positively related to end price. Second, the relative thinking effect holds when the actual price is the same as the sellers’ reference price (i.e., when the starting price is higher). In this context, consumers prefer price promotion programs, and hence, their willingness to pay through bidding will increase. Finally, the referent thinking effect holds when the actual price deviates from the seller’s reference price (i.e., when the starting price is low). In this context, consumers prefer non-price promotion programs, and their willingness to pay through bidding will increase. The academic and managerial implications of this research are discussed in the conclusion.     

Consumer adoption of group-buying auctions: an experimental study

Internet-based group-buying auctions enable consumers to obtain volume discounts, but they face risk and trust issues that are not present in other e-retailing formats, which affects their adoption by consumers. Bidders experience uncertainty about the final auction price, and the risk of whether the auction will be completed. We evaluate textual comments and the number of bids made in an auction as drivers of a consumer’s perceived financial and psychological risks toward the group-buying auction mechanism and trust in the auction initiator. We use an Internet-based experimental test bed for online group-buying auctions and will report on one experiment that we conducted. Our results indicate that textual comments made by the participants about sellers in past auctions and existing bids affected a consumer’s perceived trust in the auction initiator and the financial risk of the mechanism. Positive textual comments and more bids appear to enhance perceived trust in the auction initiator and reduce financial risk, and other consumers are more willing to make bids as a result. Consumers continued to express concerns about the uncertainty of the final group-buying auction price though.     

基于拍卖博弈的电子商务自动协商

为提高电子商务自动协商系统效率,本文以拍卖博弈理论为基础,提出并实现了一种基于拍卖博弈的自动协商Agent模型,并在此基础上实现了一个基于拍卖博弈的电子商务自动协商原型系统,应用于一个企业敏捷供应链管理系统中实现自动协商交易。     

Interplay between Buy-It-Now price and last minute bidding on online bidding strategies

Sellers and buyers on online auction sites like eBay have the option of setting and executing auction parameters such as auction length, Buy-It-Now price, starting price, reserve price, etc. Understanding why bidders choose to execute the Buy-It-Now price as opposed to submitting a bid at the last minute of an auction helps managers better choose auction parameters and generate more revenue. In this paper, we first study online bidder behavior pertaining to the execution of the Buy-It-Now option as opposed to the last minute bidding strategy on eBay. Consequently, we study the seller’s decision to set a Buy-It-Now option and the amount of it. Our main finding is that a dominant strategy for the seller is to offer a Buy-It-Now option at the beginning of the auction. An early bidder arriving at the auction site is indifferent in choosing threshold Buy-It-Now prices or moving onto the auction and under particular circumstances strategically waiting for the last minutes of the auction to submit a bid. We also provide conditions on the existence of a set of equilibria which predicts the outcome of the game of executing the Buy-It-Now option versus last-minute bidding on eBay.     

基于拍卖的多智能体任务分配算法

任务分配是多智能体系统协作关键问题,对此提出一种基于拍卖的多智能体任务分配算法.在限定时间内,利用拍卖算法综合考虑完成任务的效益及各智能体完成任务需付出的代价,得到接近最优的任务分配方案.动态的环境会造成方案滞后,通过动态调整,重要任务可吸引到更多智能体.为减轻动态调整过程的通信负担,引入令牌的概念,由令牌控制智能体发送信息的权利.通过在机器人救援仿真系统中的成功应用,验证了本算法的有效性.     

基于移动Agent技术的自动拍卖模拟研究

自动拍卖的基本思想是用某种代理机制——Agent代替人监控整个拍卖过程。提出分阶段第二价格封标拍卖模式，设计了多Agent网上自动拍卖协议，和多Agent拍卖系统体系结构。提出三种拍卖策略模型：平稳加价型策略、跳跃型策略和保密型策略。利用移动Agent开发平台Aglet实现了一个模拟系统，并进行了多次仿真模拟实验，对实验数据进行了详细分析。实验结果表明该模拟系统基本达到设计目的，并为进一步研究自动拍卖相关策略、协议提供了一个实验平台。     

基于歧视性的第二价格拍卖算法的激励机制

在基于对等网(P2P)的大数据实时应用中,针对如何遏制视频点播(VOD)系统中的节点搭便车行为,提出了基于歧视性的第二价格拍卖算法的激励机制。节点之间以分布式动态拍卖的方式获取各自所需视频数据块,拍卖中,拍卖节点首先根据歧视性原则判断竞标节点的预算是否足以参与竞标,并根据允许参与竞标的节点数目设置上传带宽;然后根据竞标节点的出价确定赢得竞标的节点;最后竞标节点在接收到数据块后根据第二价格方案支付拍卖节点仅次于拍卖最高价格的第二高价格的要价作为节点的收益。分析节点的收益、节点带宽的利用率以及贡献节点/自私节点的比例,表明该方案能有效地激励节点积极地参与视频数据块的共享,同时高效地利用节点的上传带宽。     

遗传算法在电子商务协商优化问题中的应用

本文提出了一种基于智能体和"多维拍卖"机制的电子商务谈判协商模型,并利用改进的遗传算法实现了交易方案的自动生成.实验表明,上述方法可以对offer不断优化,高效、快速地生成使参与自动协商的Agent双赢的交易方案.     

Auction-based distributed efficient economic operations of microgrid systems

This paper studies the economic operations of the microgrid in a distributed way such that the operational schedule of each of the units, like generators, load units, storage units, etc., in a microgrid system, is implemented by autonomous agents. We apply and generalise the progressive second price (PSP) auction mechanism which was proposed by Lazar and Semret to efficiently allocate the divisible network resources. Considering the economic operation for the microgrid systems, the generators play as sellers to supply energy and the load units play as the buyers to consume energy, while a storage unit, like battery, super capacitor, etc., may transit between buyer and seller, such that it is a buyer when it charges and becomes a seller when it discharges. Furthermore in a connected mode, each individual unit competes against not only the other individual units in the microgrid but also the exogenous main grid possessing fixed electricity price and infinite trade capacity; that is to say, the auctioneer assigns the electricity among all individual units and the main grid with respect to the submitted bid strategies of all individual units in the microgrid in an economic way. Due to these distinct characteristics, the underlying auction games are distinct from those studied in the literature. We show that under mild conditions, the efficient economic operation strategy is a Nash equilibrium (NE) for the PSP auction games, and propose a distributed algorithm under which the system can converge to an NE. We also show that the performance of worst NE can be bounded with respect to the system parameters, say the energy trading price with the main grid, and based upon that, the implemented NE is unique and efficient under some conditions.     

Autonomous Adaptive Agents for Single Seller Sealed Bid Auctions

In developing open, heterogeneous and distributed multi-agent systems researchers often face a problem of facilitating negotiation and bargaining amongst agents. It is increasingly common to use auction mechanisms for negotiation in multi-agent systems. The choice of auction mechanism and the bidding strategy of an agent are of central importance to the success of the agent model. Our aim is to determine the best agent learning algorithm for bidding in a variety of single seller auction structures in both static environments where a known optimal strategy exists and in complex environments where the optimal strategy may be constantly changing. In this paper we present a model of single seller auctions and describe three adaptive agent algorithms to learn strategies through repeated competition. We experiment in a range of auction environments of increasing complexity to determine how well each agent performs, in relation to an optimal strategy in cases where one can be deduced, or in relation to each other in other cases. We find that, with a uniform value distribution, a purely reactive agent based on Cliff’s ZIP algorithm for continuous double auctions (CDA) performs well, although is outperformed in some cases by a memory based agent based on the Gjerstad Dickhaut agent for CDA.     

在线拍卖商品最终成交价格预测

在线拍卖产生了大量的电子数据，充分利用这些数据，无论对于卖者、买者还是站点管理员，都会产生极大的作用。卖者通过预测最终的成交价格可以优化自己拍卖商品的拍卖价格。在线拍卖中的大量属性是动态变化的，以至于不能直接运用机器学习算法对最终成交价格进行预测。为了解决这个问题，收集了大量的在线拍卖成交数据，提取和构造了维度固定的特征列表，运用BP算法进行最终成交价格的预测，并对预测结果进行了分析。     

基于移动Agent的智能拍卖系统研究

该文基于买方为主的拍卖结构,提出了一种基于移动Agent技术的多属性拍卖系统。采用Skyline算法实现招标的选优,协同过滤技术实现投标的推荐,利用移动Agent技术优势完成多属性拍卖过程的自动化处理。分析表明该系统是一种较为有效,智能化的系统。     

An artificial negotiating agent modeling approach embedding dynamic offer generating and cognitive layer

In this paper, a dynamic offer generating unit and cognitive layer are suggested for artificial agents based negotiation systems. For this purpose, first, adaptive time and behavior dependent tactics are developed taking advantages from time continuity and dynamics aspects (features) integrated in their modeling. Then, a negotiation strategy (bilateral over single issue) based on these two tactics is suggested. Second, a cognitive negotiation model for a negotiator agent is developed using Win-Lose and Win-Win orientations which will be formed based on personality factors. Afterwards, an experimental validation is conducted for testing applicability of time dependent tactics, the effect of offering time, and the effect of cognitive orientations (Win-Lose and Win-Win) on final negotiation outcomes. The results prove the applicability of the suggested time and behavior dependent tactics as well as the proposed cognitive negotiation model.     

MoCAAS: auction agent system using a collaborative mobile agent in electronic commerce

To get the items that a buyer wants in an Internet auction, he must search for the items through several auction sites. When the bidding starts, the buyer needs to connect to these auction sites frequently so that he can monitor the bid states and re-bid. A reserve-price auction reduces the number of connections, but this limits the user's bidding strategy. Another problem is equity between the buyer and the seller. Both the buyer and the seller should profit within proper limits. In this paper, we propose an auction agent system using a collaborative mobile agent and a brokering mechanism called MoCAAS (Mobile collaborative auction agent system), which mediates between the buyer and the seller and executes bidding asynchronously and autonomously. This reduces the network load more than with other auction-agents, offers more intelligent bidding, and increases the clear ratio.     

LEARNING OLIGOPOLISTIC COMPETITION IN ELECTRICITY AUCTIONS

This paper addresses the problem of auction markets efficiency within the context of recently liberalized electricity markets. Two different auction mechanisms, i.e., the uniform and the discriminatory price setting rules, have been employed worldwide in designing electricity markets. In this paper, we study the relative efficiency of the two auction mechanisms in the framework of the learning-in-games approach. The behavior of electricity suppliers are modeled by means of an adaptive learning algorithm and the demand is assumed to be constant and inelastic, according to a common hypothesis in electricity market modeling. Computational experiments results are interpreted according game theoretical solutions, i.e., Nash equilibria and Pareto optima. Different economic scenarios corresponding to a duopoly and a tripoly competition with different level of demand are considered. Results show that in the proposed conditions, sellers learn to play competitive strategies, which correspond to Nash equilibria. Finally, this study establishes that, in the presented computational setting and economic scenarios, the discriminatory auction mechanism results more efficient than the uniform auction one.     

基于拍卖机制的改进合同网协商策略

在现有合同网协议的研究基础上，引入经济学中的拍卖理论，提出一种基于拍卖机制的改进合同网协商策略，通过Agent间的自主竞争来实现任务的动态分配，从而降低管理者获取和更新其他Agent知识的难度，间接支持Agent能力动态变化，减少Agent间通讯量和评标时间。     

An agent-based English auction protocol using Elliptic Curve Cryptosystem for mobile commerce

Rapid development of the Internet and the extensive use of mobile phones have increased demand for mobile devices in Internet auctions. This trend is acting as an incentive to develop an auction model for mobile-based environment. Recently, Kuo-Hsuan Huang proposed a mobile auction agent model (MoAAM), which allows the bidders to participate in online auctions through a mobile agent. He used modular exponentiation operations in his method. As a result, the processing time for key generation, bidding, and verification were long. Thus, we propose to add the concept of Elliptic Curve Cryptosystem (ECC) onto MoAAM, because ECC has low computation amount and small key size, both of which will aid to increase the speed in generating keys, bidding, and verification. In terms of reduction of computation load on mobile devices and auction-manager server, the proposed method will make online auction system more efficient as well as more convenient to use. This paper mainly uses the English auction protocol as the key auction protocol. The protocol consists of four entities: Registration Manager (RM), Agent House (AH), Auction House (AUH), and Bidders (B). The Registration Manager registers and verifies Bidder identity. The Agent House manages the agents and assigns public transaction keys to Bidders. The Auction House provides a place for auction and maintains all necessary operations for a smooth online auction. Bidders are buyers who are interested in purchasing items at the auction. Our proposed method conforms to the requirements of an online auction protocol in terms of anonymity, traceability, no framing, unforgetability, non-repudiation, fairness, public verifiability, unlinkability among various auction rounds, linkability within a single auction round, efficiency of bidding, one-time registration, and easy revocation.