一类占线融资租赁问题的最优竞争策略与风险补偿模型

运用占线算法与竞争分析方法,研究了资产所有权在一定的租赁时间后转移给承租人的融资租赁问题的最优竞争策略与风险补偿模型。首先给出了该问题的最优离线解;然后,根据约定的租赁时限与购买价格及租赁费用的大小关系,分别给出了3种情形的占线策略及相应的竞争比分析;最后,在AL-BINALI提出的占线风险补偿分析框架下,给出了2种预期形式及相应最优占线收益策略。     

可退货在线租赁竞争分析及其风险回报模型

经典的在线租赁只考虑购买和租赁两种决策行为,当在线租赁方购买设备后,不允许退货。本文假设在线租赁方在选择购买设备后,如果觉得购买设备不划算,可以在任何时候花费一定的代价把设备退还给承租方。通过定义退货费用函数来刻画退货行为,本文提出了可退货在线租赁问题,它是经典在线租赁问题的扩展。利用传统的竞争分析方法设计了该问题的竞争策略,分析了策略的竞争性能,并证明该策略能达到竞争比下界(即是最优竞争策略)。同时,在风险回报竞争分析框架下,进一步讨论了上述问题,得到了给定预期和风险下收益最优的竞争策略。     

最优网上拍卖机制模型研究

最优拍卖机制设计问题是拍卖人通过合理的设计一系列规则使得自己的收益最大化的过程,这一过程显然是追求"卖方剩余"最大化的.实际上,在拍卖人追求收益最大化的同时,竞标人同样会通过最优策略的分析,使自己的收益最大化.这种双方博弈的结果自然导致一种均衡状态的出现,这种均衡状态是一种纳什均衡状态,这种状态下的社会资源配置也是最优的.本文试图从传统的网上拍卖模型入手,将原有模型进行扩展研究,得出拍卖品数量和拍卖价值离差等对网上拍卖的影响,从而提出一个现有电子商务环境下的最优拍卖机制模型.     

基于双边减排成本信息不对称的排污权二级交易市场拍卖机制研究

本文构建了一个基于双边减排成本信息不对称的排污权二级交易市场拍卖模型，分析了统一价格、歧视价格及混合拍卖机制下卖方收益、排污权价格波动及排污权供给量差异，在此基础上给出了排污权二级交易市场最优拍卖机制，并进一步讨论了相关参数对最优拍卖机制的影响。结果表明：从收益最大化角度来看，最优的拍卖机制为歧视价格拍卖机制，但考虑到价格波动及排污权供给量等其他因素，排污权二级市场交易应选用混合拍卖机制。风险偏好变化对混合拍卖机制下卖方收益及价格波动的影响存在不确定性，当风险偏好超过某一阈值时，随着风险偏好程度增大，需求隐蔽效应占主导，收益及价格波动增大；相反，当风险偏好小于某一阈值时，随着风险偏好程度增大，竞争效应占主导，收益及价格波动减小。价格变动的供给影响系数对卖方收益的影响随买方参与人数的不同而不同。当买方参与人数较小时，需求隐蔽效应占主导，竞争效应不明显，随着价格变动的供给影响系数增大，混合拍卖机制下卖方的收益不断增加；当买方参与人数较大时，卖方收益同时受到需求隐蔽和竞争效应影响，随着价格变动的供给影响系数增大，收益呈先增大后减小趋势。随着价格变动的供给影响系数增大，价格波动呈先增大后减小趋势。     

多阶段占线赁购问题与竞争分析

经典占线赁购决策是建立在设备使用寿命无限大的假设下进行竞争策略分析,是一种单阶段的占线决策问题。论文把设备使用寿命因素考虑进占线赁购问题,扩展单阶段占线赁购问题为多阶段占线赁购。给出了该问题的离线解;设计了等长赁购策略,证明该策略是唯一最优策略;给出了风险策略基本性质,为进一步研究多阶段占线赁购风险补偿模型奠定了基础。     

基于预期的占线特殊优惠卡问题与竞争分析

特殊优惠卡问题是租赁问题的一个推广.本文将风险补偿模型和市场利率引入了占线特殊优惠卡问题,使得该问题更贴近现实情况,得到以下结论:i)一般情形的占线特殊优惠卡问题的最优风险补偿收益为2-β/2-β(2-β)d;ii)考虑市场利率i,当(1-β)(1-αcr)小于和大于c(1-α)时,分别得出了两种情形下不同的最优风险补偿收益.最后,通过数值分析说明风险容忍度d和折扣率β对约束竞争比rA'和最优风险补偿收益的影响.     

在线设备更新问题的竞争策略及其风险补偿模型

本文基于一种设备在线租赁的基础上,提出了在线设备更新问题。运用传统竞争比方法分别研究了两阶段设备更新问题在有无利率情形下的在线竞争策略,并建立了相应的风险补偿模型,从而在线投资者可以根据自己的风险容忍度和预期选择最优的更新策略。市场利率的引入使得在线设备更新模型更复杂但更贴近于现实中的设备更新问题。最后,通过具体实例进一步说明了市场利率下在线竞争比更小,而且竞争比关于市场利率递减;同时也说明了风险补偿模型中最优约束竞争比要小的多。因此,投资者若考虑到资金的收益及市场风险因素后将会采取更加谨慎稳健的投资策略。     

基于焦点的在线英式拍卖决策方法

在线拍卖打破了传统拍卖的时空限制,一口价允许竞拍者通过接受预先设置的特定价格即刻获得拍品,克服了在线拍卖时间成本高的问题,使其在电子商务平台得到广泛应用。针对固定一口价在线拍卖问题,在英式拍卖机制下,强调决定竞拍者能否赢得拍卖的是最高报价的事实,提出基于焦点的在线拍卖决策方法。焦点由赢得拍品的可能性和其对应的收益共同决定。参与者依据选定的焦点做出决策,不同类型的焦点用来直接反映参与者的决策偏好。基于焦点的决策方法得到英式拍卖下不同风险偏好竞拍者的最优策略和卖家一口价的定价区间,分析参与人数、估值等因素对焦点和参与者决策的影响。结合雅虎网站的竞拍现状,为在线拍卖参与者提供决策支持和为平台提供管理启示。     

基于竞争差分析的占线单向交易策略

针对交易者事先仅知道价格波动范围的占线单向交易问题,基于Savage后悔值准则提出了竞争差分析方法,通过引入一个假想的能够控制价格的“对手”将原来的单人决策问题转化为双人零和博弈问题.与竞争比分析相比,竞争差分析由于目标函数的数学形式更简单,因而可以直接采用逆向归纳法求解获得使最大后悔值(竞争差)最小化的稳健的占线交易策略,并找出对于交易者而言所有可能的最糟糕情况,而不必像竞争比分析那样需要事先猜测最优占线策略的特征;此外,数值模拟结果表明,基于竞争差分析的占线算法更节省计算时间,且在解决收益最大化问题时不像竞争比分析那样过于保守,一般具有更好的期望绩效.     

租金费用和购买价格连续可变的在线租赁竞争策略分析

本文运用竞争分析方法研究了占线金融租赁决策问题,已往的研究都是基于租赁设备的租用费用和购买价格不变的情形给出最优投资策略,本文给出了当价格在有界范围内连续可变时的占线投资策略,并对有无利率两种情形分析进行了竞争策略分析,分别给出了其竞争比的上下界。     

Managing Risks in Multiple Online Auctions: An Options Approach*

The scenario of established business sellers utilizing online auction markets to reach consumers and sell new products is becoming increasingly common. We propose a class of risk management tools, loosely based on the concept of financial options that can be employed by such sellers. While conceptually similar to options in financial markets, we empirically demonstrate that option instruments within auction markets cannot be developed employing similar methodologies, because the fundamental tenets of extant option pricing models do not hold within online auction markets. We provide a framework to analyze the value proposition of options to potential sellers, option‐holder behavior implications on auction processes, and seller strategies to write and price options that maximize potential revenues. We then develop an approach that enables a seller to assess the demand for options under different option price and volume scenarios. We compare option prices derived from our approach with those derived from the Black‐Scholes model ( Black & Scholes, 1973 ) and discuss the implications of the price differences. Experiments based on actual auction data suggest that options can provide significant benefits under a variety of option‐holder behavioral patterns.     

基于信号博弈的卖方欺诈行为分析

本文主要基于信号博弈的卖方欺诈行为进行研究，假设拍卖中可能存在欺诈型和诚实型两种卖家，其中欺诈行为有概率发生在第二价格拍卖中：欺诈型卖方冒充竞拍者递交仅次于最高价的报价从而获得额外收益。两种卖家根据各自效用选择拍卖形式：第一价格或者第二价格。而竞买者将卖者的选择作为信号，更新对卖方类型的判断，然后制定报价策略。这是一个买卖方信号交叉影响的过程。考虑到拍卖过程中买方价值相关性，本文在建立模型中参考了关联价值原理。针对该模型进行分析，得出了不同情况下的买卖方策略，并且研究了买方报价、买方判断、卖方收益三者之间的关系。文中利用贝叶斯公式对双方的策略选择问题进行预测，与单纯的概率分布方法相比，更具实践价值。     

双边市场中平台企业搭售行为分析

搭售是现实中双边平台企业常用的促销策略之一。通过构建一个两阶段完全信息动态博弈模型,将买方分为搭售喜好型和搭售无差异型,从垄断和竞争两种情形研究了双边平台企业采取搭售策略时,具有不同搭售偏好的买方对最优均衡解的影响以及相应的社会福利变化。研究发现:不论是垄断情形还是竞争情形,搭售对买卖双方均衡进入价格的影响都不确定,而搭售产品的定价则按照传统单边市场的定价方式制定;垄断情形下,搭售能增加买方数量、卖方数量及双边平台企业的利润,而竞争情形下,搭售产品成本较小的双边平台企业将获得较大买方数量、卖方数量及利润。在两种情形下的买方总效用、卖方总效用以及社会总福利均随搭售喜好型买方数量的增加而增加。     

Toward a Strategic Foundation for Rational Expectations Equilibrium

A step toward a strategic foundation for rational expectations equilibrium is taken by considering a double auction with n buyers and m sellers with interdependent values and affiliated private information. If there are sufficiently many buyers and sellers, and their bids are restricted to a sufficiently fine discrete set of prices, then, generically, there is an equilibrium in nondecreasing bidding functions that is arbitrarily close to the unique fully revealing rational expectations equilibrium of the limit market with unrestricted bids and a continuum of agents. In particular, the large double‐auction equilibrium is almost efficient and almost fully aggregates the agents' information.     

基于“柠檬”理论的在线信誉反馈系统有效性研究

信任问题是困扰在线拍卖市场发展的瓶颈之一.在线信誉反馈系统在消除信息不对称性,解决在线拍卖市场逆向选择问题中发挥着重要的作用.首先分析在线拍卖市场中逆向选择问题产生的原因,而后基于"柠檬"理论,从更换交易对手的重复博弈角度分析在线信誉反馈系统中信誉运行模型,对在线拍卖市场的信誉运行机理进行分析.研究指出在线信誉反馈系统能激励卖家诚信交易,一定程度上降低逆向选择问题,为我国在线拍卖网站和网络卖家更好地实施网络声誉战略提供一个思路.     

Reverse Auctions with Multiple Reinforcement Learning Agents*

Reverse auctions in business‐to‐business (B2B) exchanges provide numerous benefits to participants. Arguably the most notable benefit is that of lowered prices driven by increased competition in such auctions. The competition between sellers in reverse auctions has been analyzed using a game‐theoretic framework and equilibria have been established for several scenarios. One finding of note is that, in a setting in which sellers can meet total demand with the highest‐bidding seller being able to sell only a fraction of the total capacity, the sellers resort to a mixed‐strategy equilibrium. Although price randomization in industrial bidding is an accepted norm, one might argue that in reality managers do not utilize advanced game theory calculations in placing bids. More likely, managers adopt simple learning strategies. In this situation, it remains an open question as to whether the bid prices converge to the theoretical equilibrium over time. To address this question, we model reverse‐auction bidding behavior by artificial agents as both two‐player and n‐player games in a simulation environment. The agents begin the game with a minimal understanding of the environment but over time analyze wins and losses for use in determining future bids. To test for convergence, the agents explore the price space and exploit prices where profits are higher, given varying cost and capacity scenarios. In the two‐player case, the agents do indeed converge toward the theoretical equilibrium. The n‐player case provides results that reinforce our understanding of the theoretical equilibria. These results are promising enough to further consider the use of artificial learning mechanisms in reverse auctions and other electronic market transactions, especially as more sophisticated mechanisms are developed to tackle real‐life complexities. We also develop the analytical results when one agent does not behave strategically while the other agent does and show that our simulations for this environment also result in convergence toward the theoretical equilibrium. Because the nature of the best response in the new setting is very different (pure strategy as opposed to mixed), it indicates the robustness of the devised algorithm. The use of artificial agents can also overcome the limitations in rationality demonstrated by human managers. The results thus have interesting implications for designing artificial agents in automating bid responses for large numbers of bids where human intervention might not always be possible.     

Dynamic Matching,Two‐Sided Incomplete Information,and Participation Costs: Existence and Convergence to Perfect Competition

Consider a decentralized, dynamic market with an infinite horizon and participation costs in which both buyers and sellers have private information concerning their values for the indivisible traded good. Time is discrete, each period has length δ, and, each unit of time, continuums of new buyers and sellers consider entry. Traders whose expected utility is negative choose not to enter. Within a period each buyer is matched anonymously with a seller and each seller is matched with zero, one, or more buyers. Every seller runs a first price auction with a reservation price and, if trade occurs, both the seller and the winning buyer exit the market with their realized utility. Traders who fail to trade continue in the market to be rematched. We characterize the steady‐state equilibria that are perfect Bayesian. We show that, as δ converges to zero, equilibrium prices at which trades occur converge to the Walrasian price and the realized allocations converge to the competitive allocation. We also show the existence of equilibria for δ sufficiently small, provided the discount rate is small relative to the participation costs.     

不同质量权重评分规则下的多维招标机制设计

本文主要研究包括价格变量及非价格变量(质量)的多维招标机制设计,在Che模型评分规则的基础上引入新的参数,研究了赋予质量不同权重的第一高分和第二高分招标机制的均衡情况。研究发现,不管新参数如何变化,第一高分招标和第二高分招标是等价的。在该评分规则下,买方还可以灵活根据自己的质量偏好、设定质量门槛筛选企业。如果买方和中标企业在中标后有协调机制,则能实现共赢、社会福利的最大化。     

基于可变供给量的可分离物品拍卖及其应用

本文对统一价格下可分离物品的拍卖问题进行了研究。首先,在买者报价连续、买者和卖者风险中立、卖者采取可变供给量(将供给量看成价格的函数)的策略下,设计了一个新的基于可变供给量的可分离物品统一价格拍卖机制,研究了其信息激励性和分配的有效性,给出了卖者的最佳供给策略和买者的均衡报价策略。然后,将拍卖机制推广到风险中立、风险爱好和风险厌恶三类风险买者共存的情形,并给出了相应的均衡结论,该结论与现有的一些成果相比更具一般性。最后,给出了拍卖机制在环境规划中应用。具体地,结合"十一五"期间获得的"1+8武汉城市圈"环境规划中有关污染物允许排放总量分配数据和统计申报资料,利用拍卖模型来分析和评价了免费分配方案的有效性程度,并据此给出了关于目前排污申报制度和免费分配方法的若干结论和建议。     

A Study of Online Auction Sellers’ Intention to Switch Platform: The Case of Yahoo!Kimo Versus Ruten_eBay*

The study of consumers’ switching from one service provider to another has a long tradition in economics, information systems, and marketing. The emergence of electronic commerce presents new challenges in understanding consumers’ switching intentions in the context of e‐commerce in general and online auctions in particular. With the abundance of literature on online auctions, there is a surprising lack of research on auction sellers’ intentions to switch from one online auction platform to another. Using the competition between Yahoo!Kimo and Ruten_eBay, two leading auction platforms in Taiwan, as the backdrop, we developed a research model and collected empirical data based on this real case to study what factors influence auction sellers to switch to a competing service provider. We find that the higher the procedural switching costs, financial switching costs, relational switching costs, site design quality, or interaction quality, the lower the intention of an auction seller to switch to a competing auction service provider. A higher perceived transaction fee, however, leads to a higher switching intention.