工程量清单计价模式下的投标报价决策研究
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摘要
我国自2003年起推行工程量清单计价,市场化的价格机制在建设领域逐步形成,给各个参与投标的建筑施工企业提供了一个更加公平的竞争环境,投标人报价的自由度大大增加。然而,由于绝大多数施工单位没有建立本企业的内部定额,没有系统的成本测算资料,缺乏投标报价的决策技术,难以适应工程量清单计价的市场化要求。在这种形势下,尽快完善与工程量清单计价模式相适应的投标报价工作,是施工企业取得竞争优势、保持持久生存发展能力的关键所在。
鉴于我国目前工程量清单计价发展仍不成熟的现状,本文对工程量清单计价模式下投标报价的形成机理进行了系统研究,将投标报价分为工程成本和标高金两个部分,所界定的工程成本包括直接成本和间接成本,标高金包括利润和风险费用。工程成本是投标报价的主要部分,其影响因素众多,本文将这些因素划分为工程项目特征因素和工程项目管理因素两类,分别进行详尽分析,并界定了投标报价中工程成本的变动区间:其上限由招标控制价决定,下限则取决于企业自身的成本水平,可以根据以往的成本数据资料,运用量本利分析的原理建立数学模型进行测算。
工程项目风险的来源包括工程项目外风险和工程项目内风险两方面,施工承包方所承担的风险包括决策失误风险、合同缔约风险、合同履约风险、项目管理风险和不可抗力风险。投标报价风险受合同计价方式的影响,与工程项目所处的市场环境和适用的合同体系相关。论文结合工程实践,对我国目前的工程量清单计价模式下,由于市场环境不尽规范、标准施工合同文本不配套而导致的投标报价中的潜在风险进行了剖析。
企业定额完善与否是成本测算关键,也是提高企业投标报价竞争力的重要基础性工作。论文分析了企业定额的特性,提出了企业定额体系的框架结构,并对定额指标的编制方法进行了研究。作为另一项投标报价的基础性工作,论文对企业投标管理信息化建设的状况进行了剖析,对企业工程成本数据库和工程价格信息库建设提出了建议。
投标报价决策是在成本测算的基础上,进一步分析项目可能出现的问题或潜在的风险,明确投标环境,判断自身所处的地位,以制定应对的投标策略,最终确定投标报价的过程。传统的投标环境分析仅限于定性分析,本文将SWOT分析法与模糊综合评判法相结合,构造了SWOT分析模型,通过提供定量化的数据来对企业的投标态势进行分析,为投标策略的选择提供依据。针对标高金决策的特点,在充分研究国内外投标报价决策模型的基础上,本文选择RBF神经网络来解决标高率决策问题。在吸收前人经验与研究成果的基础上,确定了影响标高率的18个主要因素,通过MATLAB神经网络工具箱,建立了用于投标报价中标高率决策的RBF神经网络模型。
Our country has promoted valuation with bill quantity from 2003.The price mechanism of the market is gradually forming in the construction field,which provided a more fair competition environment to every construction enterprise that participates the bidding and the freedom degree of the bidders' bidding consumedly increased.Then,it is hard to adapt to the request for majority construction enterprises,because they have never established internal norms,have no systematic data for cost accounting,and lack decision technology for bidding and pricing.Under this kind of situation,perfecting the work of bidding and pricing to adapt to valuation with bill quantity is the key for construction enterprises to obtain competitive advantage and keep long time existence and development abilities.
Owing to the present situation that valuation with bill quantity is still not mature in our nation,this paper systematic exposits the formation mechanism of bidding and pricing based on the mode of valuation with bill quantity,which divides bidding and pricing into two part of engineering cost and mark-up.The engineering cost for definition includes direct cost and indirect cost and the mark-up includes the profits and risk expenses.The engineering cost which has many influencing factors is the main part of the bidding.This paper divides these influencing factors into two types:the characteristic factor and the management factor of the engineering project,and carries on respectively detailed analysis,which defines the fluctuation interval of engineering cost in bidding:the upper limit is decided by bids control price,then the lower limit is decided by the cost level of business enterprises themselves.Based on the former cost datas,the fluctuation interval can be calculated by using mathematics model established by quality cost and profit analysis principle.
The source of engineering project risks includes the engineering risks outside the project and risks inside the project,as while as the risks contractors undertake include decision fault risk,contracting risk,contract fulfill risk,project management risk and force majeure risk. Bidding and pricing risk is influenced by the pricing way of contracts and is related to market environment of the project and the contract system which applies to.Combining engineering practice,the latent risk in Bidding and pricing is analyzed in this paper,which is cause of the irregular market environment and the imperfect standard construction contract text.
Whether the business enterprises'norms perfect or not is the key for cost calculation,and it's also the important fundamental work to improve the competitiveness of bidding.The paper analyzes the characteristic of the business enterprises'norms,establishes the frame structure of the business enterprises'norms system,and studies the formulation method of norm indexes. As another fundamental work,the establishment of the business enterprises'bidding management information is analyzed,and suggestion to the construction of business enterprise engineering cost database and price information database is put forward.
Bidding and pricing decision is a process that based on the cost accounting,further analysis problems possibility emergence or latent risk,explicit bid environment,judge the position of oneself,establish fight reply of bid strategy,and then determine bid offer.Different from traditional bid environment analysis which only be limited by qualitative analysis,this paper combines SWOT analysis method and fuzzy comprehensive evaluation method together to structure SWOT analysis model,by which we can provide basis for choosing of bidding strategy according to provide quantitative data to carry on analysis to the bid of business enterprise situation.Aiming at the characteristics of the mark-up decision,the mark-up rate decision problem is solved by RBF neural network in this paper.By absorbing the previous experiences and research results and using the MATLAB neural network toolbox,this paper defines 18 main factors which can influent mark-up rate,and establishes RBF neural network model used for mark-up rate decision in bidding and pricing.
鉴于我国目前工程量清单计价发展仍不成熟的现状,本文对工程量清单计价模式下投标报价的形成机理进行了系统研究,将投标报价分为工程成本和标高金两个部分,所界定的工程成本包括直接成本和间接成本,标高金包括利润和风险费用。工程成本是投标报价的主要部分,其影响因素众多,本文将这些因素划分为工程项目特征因素和工程项目管理因素两类,分别进行详尽分析,并界定了投标报价中工程成本的变动区间:其上限由招标控制价决定,下限则取决于企业自身的成本水平,可以根据以往的成本数据资料,运用量本利分析的原理建立数学模型进行测算。
工程项目风险的来源包括工程项目外风险和工程项目内风险两方面,施工承包方所承担的风险包括决策失误风险、合同缔约风险、合同履约风险、项目管理风险和不可抗力风险。投标报价风险受合同计价方式的影响,与工程项目所处的市场环境和适用的合同体系相关。论文结合工程实践,对我国目前的工程量清单计价模式下,由于市场环境不尽规范、标准施工合同文本不配套而导致的投标报价中的潜在风险进行了剖析。
企业定额完善与否是成本测算关键,也是提高企业投标报价竞争力的重要基础性工作。论文分析了企业定额的特性,提出了企业定额体系的框架结构,并对定额指标的编制方法进行了研究。作为另一项投标报价的基础性工作,论文对企业投标管理信息化建设的状况进行了剖析,对企业工程成本数据库和工程价格信息库建设提出了建议。
投标报价决策是在成本测算的基础上,进一步分析项目可能出现的问题或潜在的风险,明确投标环境,判断自身所处的地位,以制定应对的投标策略,最终确定投标报价的过程。传统的投标环境分析仅限于定性分析,本文将SWOT分析法与模糊综合评判法相结合,构造了SWOT分析模型,通过提供定量化的数据来对企业的投标态势进行分析,为投标策略的选择提供依据。针对标高金决策的特点,在充分研究国内外投标报价决策模型的基础上,本文选择RBF神经网络来解决标高率决策问题。在吸收前人经验与研究成果的基础上,确定了影响标高率的18个主要因素,通过MATLAB神经网络工具箱,建立了用于投标报价中标高率决策的RBF神经网络模型。
Our country has promoted valuation with bill quantity from 2003.The price mechanism of the market is gradually forming in the construction field,which provided a more fair competition environment to every construction enterprise that participates the bidding and the freedom degree of the bidders' bidding consumedly increased.Then,it is hard to adapt to the request for majority construction enterprises,because they have never established internal norms,have no systematic data for cost accounting,and lack decision technology for bidding and pricing.Under this kind of situation,perfecting the work of bidding and pricing to adapt to valuation with bill quantity is the key for construction enterprises to obtain competitive advantage and keep long time existence and development abilities.
Owing to the present situation that valuation with bill quantity is still not mature in our nation,this paper systematic exposits the formation mechanism of bidding and pricing based on the mode of valuation with bill quantity,which divides bidding and pricing into two part of engineering cost and mark-up.The engineering cost for definition includes direct cost and indirect cost and the mark-up includes the profits and risk expenses.The engineering cost which has many influencing factors is the main part of the bidding.This paper divides these influencing factors into two types:the characteristic factor and the management factor of the engineering project,and carries on respectively detailed analysis,which defines the fluctuation interval of engineering cost in bidding:the upper limit is decided by bids control price,then the lower limit is decided by the cost level of business enterprises themselves.Based on the former cost datas,the fluctuation interval can be calculated by using mathematics model established by quality cost and profit analysis principle.
The source of engineering project risks includes the engineering risks outside the project and risks inside the project,as while as the risks contractors undertake include decision fault risk,contracting risk,contract fulfill risk,project management risk and force majeure risk. Bidding and pricing risk is influenced by the pricing way of contracts and is related to market environment of the project and the contract system which applies to.Combining engineering practice,the latent risk in Bidding and pricing is analyzed in this paper,which is cause of the irregular market environment and the imperfect standard construction contract text.
Whether the business enterprises'norms perfect or not is the key for cost calculation,and it's also the important fundamental work to improve the competitiveness of bidding.The paper analyzes the characteristic of the business enterprises'norms,establishes the frame structure of the business enterprises'norms system,and studies the formulation method of norm indexes. As another fundamental work,the establishment of the business enterprises'bidding management information is analyzed,and suggestion to the construction of business enterprise engineering cost database and price information database is put forward.
Bidding and pricing decision is a process that based on the cost accounting,further analysis problems possibility emergence or latent risk,explicit bid environment,judge the position of oneself,establish fight reply of bid strategy,and then determine bid offer.Different from traditional bid environment analysis which only be limited by qualitative analysis,this paper combines SWOT analysis method and fuzzy comprehensive evaluation method together to structure SWOT analysis model,by which we can provide basis for choosing of bidding strategy according to provide quantitative data to carry on analysis to the bid of business enterprise situation.Aiming at the characteristics of the mark-up decision,the mark-up rate decision problem is solved by RBF neural network in this paper.By absorbing the previous experiences and research results and using the MATLAB neural network toolbox,this paper defines 18 main factors which can influent mark-up rate,and establishes RBF neural network model used for mark-up rate decision in bidding and pricing.
引文
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