R&D项目投资评价的实物期权方法

研究与开发(Research and Development，R＆D)是企业长期战略的重要组成部分，如何评价R＆D投资是R＆D管理中的一个重要课题。传统的NPV法未能充分考虑于确定性因素对投资价值的影响，不能客观地对R＆D项目做出正确的评价。R＆D项目不确定性反映了投资具有一定的期权特性，基于实物期权理论和方法，建立了R＆D项目的投资评价模型，并分析了非市场性的不确定因素(突发事件)对R＆D项目投资价值的影响。     

新产品R＆D项目综合风险评价的SPA方法研究

新产品的R＆D是企业可持续发展的根源，但对R＆D项目的投资却具有极高的风险。针对新产品R＆D项目的特征，建立了包含概率和项目目标三因素的风险评价指标体系；依据确立的指标体系，给出了基于集对分析的综合风险评价模型。最后，通过一个实例说明了集对分析在新产品R＆D项目综合风险评价中的应用。     

R＆D管理过程化的基本特点及其信息评价指标体系

本文通过调查发现我国多数企业R＆D管理滞后，R＆D过程控制欠缺。在此背景下，本文强调R＆D管理过程化是管理创新在R＆D管理中的应用，分析了R＆D管理过程化的基本特点；论述了R＆D管理过程化对R＆D绩效的意义；提出了R＆D管理过程化的信息评价指标体系     

高新技术项目风险评价指标体系及评价方法研究

高新技术项目具有涉及范围广、环节多、耗费资金巨大、研制和生产周期不确定性强、系统操作复杂、使用维护费用高等特点,这决定了其风险的高发性和复杂性,文章针对高新技术项目的特点,建立了高新技术项目风险评价指标体系;以模糊神经网络评价方法为基础,用遗传算法对神经网络进行训练,建立了高新技术风险评价方法。     

基于PCA-BP的PPP基础设施项目风险评价研究

PPP基础设施项目风险管理是参与方在进行项目管理时的瓶颈问题之一,如果不能在风险因素正确识别的基础上评价项目风险,则情况会变得更加复杂。鉴于此,文章在风险识别的基础上建立了PCA-BP风险评价方法,并在MATLAB 2010平台上进行实证分析。研究表明:基于PCA-BP的风险评价方法优于单一BP神经网络风险评价方法,其为PPP项目参与者精确评价项目风险提供了一定的参考价值。     

基于目标管理的R＆D人员绩效管理体系构建

企业R＆D（Research and Development）（研发）管理是一个完整的管理体系,主要由组织结构、项目管理、工作流程、绩效管理等内容构成基本构架。而R＆D人员的绩效管理是其中不可缺少的重要组成部分。在市场竞争日益激烈的今天,作为企业创新主体的R＆D人员越来越受到企业经营者的重视,目前R＆D管理工作的一个重点,是对其实施科学、合理、公正的评价。论文通过分析我国企业R＆D人员绩效管理工作上存在的一些问题,拟提出建立以目标管理理论为基础的R＆D人员绩效管理体系的思路,拟建立科学、合理的R＆D人员绩效管理体系。     

企业R＆D人员的激励机制设计与业绩评价指标

本文研究企业R＆D人员的激励机制设计和业绩评价体系。激励机制设计包括：R＆D人员的工资、劳务、职位、保险、失败后的宽容、充分自主权、声誉或荣誉激励，即物质到精神的七个方面。对于激励机制基础的业绩评价指标，本文从R＆D成果形成的组织内部指标、外部指标及其成果运用指标三方面加以展开分析。     

基于支持向量机的工程项目投资风险评价研究

提出一种工程项目投资风险评价的新方法—支持向量机评价法,由于支持向量机对样本数量的依赖性弱,通过学习有限的样本而建立的模型仍具有很强的泛化能力,具有比神经网络更好推广性能,因此在项目风险评价方面必然比神经网络具有更大的优势。实例研究也表明支持向量机方法更适合于投资项目风险评价的研究。     

基于FA-BP神经网络的养老地产PPP项目风险评价

为了解决养老地产PPP项目风险因素冗杂且普遍存在共线性问题,提出因子分析与BP神经网络相结合的风险评价模型.构建了养老地产PPP项目风险指标体系,运用SPSS软件对风险因素降维处理,结合MATLAB工具建立BP神经网络风险评价模型.选取9个相似工程项目数据作为学习样本,对模型进行训练并验证.结果表明,BP神经网络风险评...     

上市公司R＆D效率评价研究——医药行业实践

本文以医药行业上市公司2004～2005年财务数据为研究对象，采用数据包络分析方法（DEA），对医药行业上市公司R＆D的投入产出效率进行了分析。研究发现，医药上市公司R＆D效率之间存在较大的差距，大部分公司R＆D经费投入产出效率较高，人员投入的使用效率存在较多浪费，R＆D效率与企业规模存在一定的联系，R＆D效率不高和R＆D投入规模较小，仍然是制约医药企业快速发展的因素。     

基于层次分析法的风险投资项目评价与决策

层次分析法应用多目标评价决策，是一种十分有效的定性分析与定量分析有机结合的方法，对于风险投资项目而言，其评价决策也是一个多目标，多层次，结构复杂，因素众多的大系统，因而运用层次分析法进行此类项目的评价与决策是合适的，文中对如何应用层次分析法分析风险投资项目的评价决策进行了说明与探讨。     

R&D项目投资评估的实物期权方法初探

本文分析了传统的NPV法在R&D项目投资评估中的缺陷,指出R&D项目投资本质上所具有的期权特性。在此基础上引入了实物期权方法,包括Black-Scholes期权定价方法和Geske期权定价模型。     

知识经济下的研究开发支出的会计处理

现有的资产计量和报告模式,仍然以有形资产的计量为核心,而无形资产不同于有形资产的经济特征———非竞争性、部分独占、固有风险、不可交易,决定了不能把有形资产的规则强加于无形资产。本文试图在对我国上市公司研究开发支出会计处理和信息披露状况的分析的基础上,结合相关的基本理论,思考我国研究开发支出会计处理“前方的路”。     

风险投资项目筛选与价值评估的重要因素及其评价指标体系分析

风险投资固有的高风险特征,使得初始投资决策十分重要。研究项目筛选和价值评估机理的目的,正是为了正确认识风险投资项目在价值形成、影响因素等方面的内在规律性,为投资者正确评估风险项目,作出正确的投资决策奠定基础。本文通过对风险投资项目特征、价值形成及影响风险投资项目筛选和价值评估的重要因素进行分析,建立了风险投资项目筛选和价值评估的指标体系。     

基于实物期权法对R&D项目价值评估的研究——对布莱克-舒尔斯定价模型的改进

针对R&D项目投资的特点,探讨了采用布莱克一舒尔斯期权定价模型对R&D项目价值评估可能存在的缺陷,并提出一种改进方法,即将决策树和布莱克一舒尔斯定价模型结合运用,因为决策树能够模拟研发项目的阶段性决策过程,考虑到多个离散型不确定性因素的相关性,模拟并计算出对决策路径依赖的现金流,因此能克服纯粹使用布莱克一舒尔斯公式的不足,在考虑多个不确定性因素的影响下,实现对多阶段R&D项目价值的评估,作出正确的投资决策。     

Using the fuzzy associative memory (FAM) computation to explore the R&;D project performance

This study found out there were nonlinear relationships between the R&D project performance and its determinants—R&D project manager’s skills, quality of project environment, and teamwork effectiveness—by using the Fuzzy Associative Memory (FAM) technique in the IC design industry of Taiwan. The results showed that R&D project manager’s skills and quality of project environment had significantly inverse U-shaped effects on the R&D project performance, while teamwork effectiveness had almost monotonic positive influence upon it. Therefore, there were optimal values for R&D project manager’s skills and quality of project environment for the R&D project performance in the Taiwanese IC design companies, although they can raise teamwork effectiveness as much as possible.     

Selecting balanced portfolios of R&D projects with interdependencies: A Cross-Entropy based methodology

The intensive growth of technology makes firms rely on research and development (R&D) activities in order to adapt to technology changes in an ever-changing and uncertain environment. Due to R&D budget constraints and limited resources, firms are often forced to select a subset of all candidate projects by means of project portfolio selection techniques mitigating the corresponding risks and enhancing the overall value of portfolio. Projects' interdependencies and types were rarely considered in existing models of R&D portfolio selection that may result in selecting wrong projects. This flaw hinders the projects alignment with corporate objectives and strategy and leads to excessive risk and missing the promised values. In this paper, a balanced set of R&D project evaluation criteria was proposed. Next, to construct R&D project portfolio, a 0–1 nonlinear mathematical programming method for balancing portfolio values and risks was proposed, in which research projects' interdependencies, types and other constraints were all considered. Finally, a Cross-Entropy algorithm was developed to solve the proposed model and results were reported. The algorithm proved to be very effective in terms of solution quality and computational time. The proposed algorithm especially suits large scale instances while exact approaches are doomed to fail.     

Stratified network mapping decision making technique based decision support framework for R&D budget allocation in South Korea

In this research work, we proposed and developed a stratified network mapping (SNM) decision making method and used it to improve the industry–university specialization in R&D in each region selected in this study. The proposed method considers the influence of criteria on and their priority in alternatives performance evaluation process. By analyzing the influence of these criteria on decision-making, we can easily improve the performance of alternatives. The SNM gives a clear understanding of each alternatives performance efficiency level. It explores possible and inefficient states and high-level influence states in inefficient states. Narrowly using multi-criteria decision-making methods to rank alternatives does not improve the performance of alternatives. The proposed method helps rank alternatives and improve the performance level of alternatives in each state. We analyzed the R&D investment of central and local governments of South Korea. It is an attempt to invigorate and facilitate R&D collaboration using a decision support model. We analyzed industry–academia research networks and enhanced the efficiency of the research.     

Credit constraints and R&D over the boom and bust: Firm-level evidence from Central and Eastern Europe

This paper studies the effect of credit constraints on R&D over the recent boom and bust episode in Central and Eastern European countries (CEECs). Given that financial and venture capital markets in CEECs are thin in comparison to those in high-income economies, it is proposed that credit constraints have a significant adverse effect on R&D activity in these countries. The paper uses three waves of Business Environment and Enterprise Performance Survey (BEEPS) data between 2005 and 2013 on manufacturing firms from ten CEECs. We find that credit constraints have a substantial effect on R&D engagement, as the probability of credit constrained firms undertaking R&D activities is around 30 % lower than for other firms. The adverse effect of credit constraints for R&D emerges during the years of fast economic growth.     

A performance-oriented risk management framework for innovative R&D projects

Uncertainty is one of the major inherent difficulties in developing innovative products, due to their highly dynamic markets and technologies. The presence of a large degree of uncertainty leads to high R&D risks, resulting in many R&D failures. Therefore, it is important to manage R&D risks through all R&D stages to improve R&D project success rates. This paper proposes a new risk management framework that aligns project risk management with corporate strategy and a performance measurement system to increase success rates of R&D projects and to accomplish corporate strategic goals. The balanced scorecard is used to identify major performance measures of an R&D organization based on the firm vision and strategy. Quality function deployment is adapted to transform organizational performance measures into project performance measures and a systematic procedure is developed for risk identification, assessment, response planning, and control. The proposed risk management framework enables an R&D project to be focused on achieving the corporate goals and provides a more effective way to identify, assess, analyze, and monitor R&D risks along the project cycle. The proposed methodology is illustrated with a drug development project.