单价类不完备合同视角下工程项目投标决策研究

发布时间：2018-01-11 10:33

本文关键词：单价类不完备合同视角下工程项目投标决策研究　出处：《天津大学》2014年博士论文　论文类型：学位论文

【摘要】：随着建筑市场招标投标制度的规范和成熟,投标人在招投标过程中的竞争日益激烈,造成我国建筑施工企业利润普遍低下。究其原因,在单价类合同投标报价过程中,投标人一方面担心过高的投标报价会丧失中标机会,另一方面过低的投标报价又将大幅压缩企业的利润空间。上述问题的存在导致投标人陷入投标决策困境。其根本原因在于,投标人未形成一套合理的投标策略体系,而是一味试图降低投标报价调解上述矛盾。最终导致企业发展陷入恶性循环,且不利于整个建筑市场的可持续发展。因此,如何构建一套科学的投标决策流程与方法,指导施工企业在承发包双方信息不对称且合同不完备条件下,提高自身中标概率并实现创收,已成为亟待解决的科学问题。基于对科学问题的解构,形成以下关键问题的研究内容:(1)投标人中标概率影响因素实证分析首先,应用文献综述法识别出影响投标人中标概率的主要因素;其次,使用聚类分析法将识别出的因素归纳为商务指标、技术指标和管理指标三个维度;再次,运用主成分分析的方法,对识别出的变量进行逐次筛选,将特征值最小的变量所对应的特征向量中最大分量所对应的变量剔除。经过3次变量筛选,对剩余变量的总方差贡献率进行比较,结果表明,在剩余变量中,投标报价贡献率达到50.021%,且其特征值大于1,是贡献率最高的指标维度,即此为第一主成分,也是影响投标人中标概率的最主要因素。(2)投标人中标概率最大化策略研究基于对现有商务标的评价方法的研究发现,随机复合型标底条件下当投标人的投标报价满足扣分最小原则时中标概率最大,由此分解为两个关键问题,即对于业主标底权重及下浮率的预测以及对于投标中竞争对手的平均报价水平的预测。首先,采用蒙特卡洛模拟的方法确定了业主标底权重及下浮率最可能的取值区间;其次,构建基于不完全信息静态博弈的投标竞争对手平均报价预测模型,预测随机性复合标底条件下投标中竞争对手的平均报价水平;最后,通过实证分析对本文构建的基于随机性复合标底条件下投标人实现中标概率最大化的投标报价模型进行了验证。(3)中标概率最大化下投标人不平衡报价策略研究本研究在保证中标概率最大化的前提下,基于对企业创收的考量,投标人可以利用不完备合同的漏洞,预测未来可能发生的变更,并据此制定相应的不平衡报价策略。一方面,运用事故树分析法和案例分析法,从清单特征描述不完备和地质勘查资料不完备两方面对可能存在的变更机会点进行分析、识别、归类,提炼出投标人可控的变更机会点。另一方面,对于不平衡报价策略的实施,采用线性规划模型,讨论不平衡报价方案的最优解,为投标人在报价方案选择上提供借鉴。
[Abstract]:With the standardization and maturity of the bidding system in the construction market, the competition of bidders in the bidding process is becoming increasingly fierce, resulting in the low profits of construction enterprises in our country. In the bidding process of unit price contract, the bidder on the one hand is worried that the excessive bid will lose the chance of winning the bid. On the other hand, too low bidding price will greatly reduce the profit space of the enterprise. The existence of the above problem leads the bidders into the bidding decision-making dilemma. The fundamental reason is that. Instead of forming a set of reasonable bidding strategy system, bidders blindly try to reduce the bidding price to mediate the above-mentioned contradictions, and ultimately lead to a vicious circle of enterprise development. And is not conducive to the sustainable development of the entire construction market. Therefore, how to build a set of scientific bidding decision-making process and method to guide construction enterprises under the condition of asymmetric information and incomplete contract. To improve the probability of winning bid and to achieve income generation has become a scientific problem to be solved urgently based on the deconstruction of scientific problems. Empirical Analysis on the influencing factors of bidder's winning probability. Firstly, the main factors that influence the bidder's winning probability are identified by the literature review method. Secondly, the identified factors are classified into three dimensions: business index, technical index and management index. Thirdly, the method of principal component analysis is used to screen the identified variables one by one, and the variables corresponding to the largest component in the eigenvector corresponding to the smallest eigenvalue are eliminated. By comparing the total variance contribution rate of the remaining variables, the results show that, in the remaining variables, the bidding price contribution rate reaches 50.021, and its characteristic value is more than 1, which is the highest index dimension of the contribution rate. This is the first principal component, which is also the most important factor that affects the bidder's winning probability.) the study of the maximization strategy of the bidder's winning probability is based on the research of the evaluation method of the existing commercial bid. When the bidder's bid price meets the minimum principle of deduction, the probability of winning the bid is the largest under the condition of stochastic compound bid, which is decomposed into two key problems. That is to say, the forecast of owner's bottom weight and floatation rate, as well as the forecast of the average bidding level of the competitors in the bidding. The method of Monte Carlo simulation is used to determine the most probable value interval of owner's bottom weight and floatation rate. Secondly, the paper constructs a prediction model of bidding competitors' average quotation based on incomplete information static game, and forecasts the average bidding level of the competitors in the bidding under the condition of stochastic compound bid. Finally. Based on the empirical analysis, this paper verifies the bidding quotation model based on the stochastic compound bid base condition, which is based on the maximization of the winning probability of the bidder. Research on the unbalanced bidding Strategy of bidders under the maximization of the winning probability; this study is based on the premise of maximizing the probability of winning the bid. Based on the consideration of enterprise income generation, bidders can make use of the loopholes of incomplete contracts to predict the possible future changes, and accordingly formulate the corresponding unbalanced quotation strategy. On the one hand. By means of accident tree analysis and case analysis, the possible change opportunity points are analyzed, identified and classified from two aspects: incomplete description of inventory characteristics and incomplete geological exploration data. On the other hand, for the implementation of unbalanced quotation strategy, linear programming model is used to discuss the optimal solution of unbalanced bidding scheme. To provide reference for bidders in the selection of quotation options.
【学位授予单位】：天津大学
【学位级别】：博士
【学位授予年份】：2014
【分类号】：TU723.2

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