基于支持向量机的R&D项目中止决策算法

提出了一种基于支持向量机的R&D项目的中止决策算法,该算法根据以往同类R&D项目失败或成功的经验作为学习样本,来识别未知性质的R&D项目的类别,从而做出中止还是继续研究的决策.算法不存在困扰神经网络算法的局部极小值问题.为解决项目各指标权重及合理阈值难以确定的R&D项目中止决策提供了一种有效的途径.最后用一个实例验证了该算法的可行性和有效性.     

改进的Hamming神经网络在R＆D项目中止决策中的应用

针对 Ham ming网络的匹配网络中输出节点的阈值 ,采用一种既能反映模式向量又能反映输入向量的调整方式 ,使改进的 Hamm ing网络能够测度基于欧氏距离的向量间的贴近度。探讨了改进的Hamming网络在 R& D项目中止决策领域应用的可行性 ,同时对改进的 Hamm ing神经网络算法迭代的收敛性给出了证明。案例研究表明 ,改进后的 Ham ming神经网络能有效地对 R& D项目实施中止决策     

改进的Hamming 神经网络在R&D项目中止决策中的应用

针对Hamming网络的匹配网络中输出节点的阈值,采用一种既能反映模式向量又能反映输入向量的调整方式,使改进的Hamming网络能够测度基于欧氏距离的向量间的贴近度.探讨了改进的Hamming网络在R&D项目中止决策领域应用的可行性,同时对改进的Hamming神经网络算法迭代的收敛性给出了证明.案例研究表明,改进后的Hamming神经网络能有效地对R&D项目实施中止决策.     

基于．NET的国防R＆D项目绩效评估系统

利用人工神经网络方法构建了国防R＆D项目绩效评估体系和模型，基于C／S和B／S混合模式给出了国防R＆D项目绩效评估系统的解决方案，最后说明了该系统主要功能的实现过程以及安全措施。     

R&D项目进展评估及决策选择模型

在分析R＆D项目技术和市场不确定性分布特征的基础上,提出多步骤四项式期权定价模型,用于R＆D项目进展评估.探讨了当出现不可预见信息时,对采取的多个管理决策的选择问题.实例分析表明,多步骤四项式模型能灵敏地监测项目的单因素变化引起的项目投资价值的变化,对管理的灵活性和不确定性能进行量化处理,在很大程度上提高了R＆D中期投资决策的准确性.     

后金融危机时代R＆D税收激励政策的国际实践与启示

研究与开发活动（R＆D）作为持续创新的坚实物质基础,决定着创新能力的高低。本文基于R＆D税收激励政策的角度,通过介绍各国实施R＆D税收激励政策的概况以及比较分析部分国家R＆D税收激励政策的优惠力度,得出以下五点结论：正确认识中国R＆D税收激励政策;重视R＆D税收激励政策对技术创新的推动作用;综合运用各种政策手段和工具吸引R＆D投资;适时调整R＆D税收激励政策;增强R＆D税收激励政策的可操作性。     

基于Hamming神经网络的R&D项目中止决策方法

提出了适用于R&D项目中止决策的Hamming神经网络方法,用初等数学知识证明了 Hamming神经网络算法迭代的收敛性,并论述了该方法对正在实施的R&D项目进行模式识别 的可行性.最后用一个实例验证了本文所提方法的有效性.     

基于R2-MOEA/D算法的顶板支护决策模型

现有的顶板支护决策方法或片面分析安全因素,或对指标客观赋予权重,未能有效分配权重系数,不能满足高维多目标顶板案例决策的需求。针对该问题,对顶板来压指标进行分析,提出了一种基于R2指标的差分高维多目标进化(R2-MOEA/D)算法的顶板支护决策模型。首先针对来压状态定义指标属性,建立顶板指标知识库,利用层次分析法和熵值法对知识库中的条件指标进行计算,得到指标的主观权重和客观权重;然后在确定主观、客观权重的基础上引入权重矩阵,构建基于R2-MOEA/D算法的顶板多目标决策模型;最后基于R2-MOEA/D算法将多目标问题分解成多个子问题,利用切比雪夫函数作为R2指标排序标准进行个体选择,得到收敛性和多样性较好的Pareto最优解,即相似度最高的条件指标顶板案例,其对应的结果属性为事故案例的决策提供了支护方案。实验结果表明:R2-MOEA/D算法与NSGA2算法、NSGA3算法、RVEA算法相比,在数据集的收敛性和分布性上整体效果最优,改善了高维空间中的搜索能力。通过山西霍州三交河煤矿2-6011巷道和10-4151巷道对基于R2-MOEA/D算法的顶板支护决策模型进行可行性评定,结果表明:由R2-MOEA/D算法检索出的解决方案符合该矿的实际支护情况。     

一种R＆D项目选择的人工智能方法

针对目前Ｒ＆Ｄ项目选择方法中存在的种种不足，提出了一种人工智能方法。该方法分为两部分：第一部分采用信息树方法来帮助决策者提高对Ｒ＆Ｄ项目选择过程的认识，说明了Ｒ＆Ｄ项目选择信息树模型实际上是一个认知图模型；第二部分采用前馈式神经网络的方法来进行Ｒ＆Ｄ项目选择中的多准则决策。     

中国高校R＆D投入对产出和区域经济增长的影响研究：基于2005年-201O年省际面板数据

通过我国31个省市6年的面板数据进行分析,考察了高校R＆D投入与产出的关系,以及高校R＆D投入对区域经济增长的影响。研究结果表明,（1）高校R＆D的经费投入与区域经济之间存在正相关的关系,高校R＆D投入的全时人员与区域经济关系不显著。（2）科研成果无法及时转化成技术产品,促进区域经济的增长。（3）各地区的高校之间缺少交流,在高校R＆D产出方面存在很大的差异。     

Fuzzy R&D portfolio selection of interdependent projects

Global competition of markets has forced firms to invest in targeted R&D projects so that resources can be focused on successful outcomes. A number of options are encountered to select the most appropriate projects in an R&D project portfolio selection problem. The selection is complicated by many factors, such as uncertainty, interdependences between projects, risk and long lead time, that are difficult to measure. Our main concern is how to deal with the uncertainty and interdependences in project portfolio selection when evaluating or estimating future cash flows. This paper presents a fuzzy multi-objective programming approach to facilitate decision making in the selection of R&D projects. Here, we present a fuzzy tri-objective R&D portfolio selection problem which maximizes the outcome and minimizes the cost and risk involved in the problem under the constraints on resources, budget, interdependences, outcome, projects occurring only once, and discuss how our methodology can be used to make decision support tools for optimal R&D project selection in a corporate environment. A case study is provided to illustrate the proposed method where the solution is done by genetic algorithm (GA) as well as by multiple objective genetic algorithm (MOGA).     

A Lack of Insight: An Experimental Analysis of R&D Managers’ Decision Making in Innovation Portfolio Management

This study analyses the decision to exploit an innovation project and investigates differences in individuals’ evaluations of project attributes in the context of innovation project portfolio management. A conjoint field experiment was used to collect data on exploitation decisions made by 126 research and development (R&D) managers to test how managers evaluate specific project attributes in the context of innovation project portfolio management. I analyse the relative power and popularity of profitability, strategy, uncertainty and social dimensions of the portfolio while R&D managers exploit an innovation project. Moreover, using social judgement theory, I analyse actual exploitation processes (i.e., the innovation attributes an R&D manager considers while he or she is making an exploitation decision) and self‐reported decision‐making attributes (i.e., managers’ self‐reported data). The data underline that R&D managers value specific project attributes more and others less, and therefore find disparities in innovation project portfolio decision making. Based on this study's results, decision makers are better able to reflect and understand the influence of specific project attributes. Therefore, they should investigate established decision‐making processes which can help them to improve portfolio performance.     

Fuzzy multiattribute evaluation of R&D projects using a real options valuation model

R&D project selection decision is very important in two ways. First, in many organizations, R&D budget represents huge investment. Project selection decisions could be thought with the strategic objectives and plans of the firm. Second, R&D projects' organizational returns are multidimensional in nature and risky in terms of projected outcome. Real options approach helps to calculate this risky side of the selection process. This paper considers that multidimensional side of the R&D project selection process. Another consideration is the vagueness in the evaluation process. The fuzzy analytic hierarchy process, which takes monetary (fuzzy real option value) and nonmonetary (capability, success probability, trends, etc.) criteria into account, is used to make this selection among alternative R&D projects. A real case study is given to illustrate the application of the proposed approach. © 2008 Wiley Periodicals, Inc.     

基于支持向量机的工程项目风险预测研究

风险预测是工程项目风险管理的重要基础,本文在介绍支持向量机(SVM)基本原理的基础上,探讨了基于支持向量机的项目风险预测算法,根据以往同类工程项目的数据作为学习样本,来识别待研究项目的风险类别,从而做出项目风险水平的预测。本文同时也说明了Libsvm软件在项目风险预测方面的应用。     

Leadership in R&D Projects

This article describes the results of an empirical study regarding a suitable style of R&D project leadership, especially what tasks project leaders should perform by themselves and what tasks they should delegate, what personal characteristics they should be endowed with and what kind of relationships they should have with their team. Fifty interviews were held in German institutions short‐listed for an award for their innovative products by the Saxon government. In contrast to the assumption of the Social Identity Theory, in these institutions good R&D project leaders are not the ‘prototype’ of their team, but successfully balance the interests of the company and the R&D project team.     

Modeling and analysis of project team formation factors in a project-oriented virtual organization (ProVO)

In this era of rapid changes in the project-oriented R&D organization’s environment, some are actively pursuing joint research to gain a leading edge over other R&D organizations. The condition for joint research is the knowledge that an organization needs from other organizations and the capability of collaboration. This study presents a ProVO model using the concept of virtual organization and project team formation based on knowledge and collaboration. In this model, VO is represented by the capability of carrying out a project and the cost of employment. Capability consists of knowledge competence (KC) and collaboration competence (CC). KC, in turn, consists of individual knowledge and collective knowledge from social network, while CC consists of density, degree centrality, and closeness centrality. To verify the presented model, we conducted a case study on a research institute. The analysis results show that all five project team formation factors of KC and CC are statistically significant. A prototype was also developed for selecting project team members using the binary logistics regression model. The proposed ProVO model can assist quantitative decision making on the selection of project team members by a project-oriented R&D organization from the aspects of knowledge and collaboration.     

A new approach for selecting portfolio of new product development projects

The most decisive factor that survives enterprises under stiff competition is the development of new product (NPD), and when entering the product development stage after the fuzzy front end, a best project portfolio should be finalized in order to potentially create expected revenue and competitive advantage. However, even it reaches the end of the fuzzy front stage; the NPD project is still significantly involved with uncertainties, complexities and fuzziness. To assist R&D managers making decision in this environment, this study proposes a new approach which combines fuzzy set theory and multi-criteria group decision making method into a NPD project portfolio selection model. This model takes into account project performance, project delivery and project risk, and formulates the selection decision of NPD project portfolio as a fuzzy linear programming problem. The illustrative example shows that the model proposed can generate projects with the highest success rate under limited resources and manpower.     

基于序贯博弈的装备制造业复杂产品研发补贴和关税决策

增大国内装备制造业的研发投入和引入国外产品带来的研发溢出可提升国内装备制造业科技水平,但同时带来了企业的研发成本负担和国外产品抢占国内市场的问题,因此政府在其中的研发补贴和关税政策调控显得尤为迫切.探究政府研发补贴和关税政策对存在研发溢出的国外装备制造商和国内装备制造商进行序贯博弈时的市场份额、利润和研发水平的影响问题.进一步分析政府以社会福利最大为目标时,政府的最优决策并对关键因素进行敏感性分析.最后通过数值扩展验证结论的稳健性.研究发现:研发补贴系数或关税增大都会提高(降低)国内制造商(国外制造商)的产量、利润和研发水平;政府以社会福利最大进行决策时,随着两种产品竞争强度的增大,总的研发补贴会减小,而单位研发补贴先减后增,关税先增后减.研发成本系数越高,关税和单位研发补贴会越高,但总的研发补贴会减少.     

Pricing real abandonment options on several R&;D investment projects

Much previous research has shown that the R&D investments can be evaluated by real growth options approach. But few studies have been done on real abandonment options for R&D projects which may not succeed. The contribution of this paper is not only to derive a more general closed-form solution for evaluating real abandonment options, but to put backup project consideration into our model for reality. We show that both Black-Scholes’s and Stulz’s models are special cases of our model under some specifications of parameters. From the simulation results, we explore that the higher the percentage of recovering salvage value, the more investment projects should be carried out. We hope that the results in this study could provide a useful reference for the manager, to make better decisions regarding backup projects.