互斥方案比选时NPV与NPVR指标优劣对比

NPV与NPVR是进行技术经济评价时最常用的两个基本指标。在进行单方案(独立方案)比选时两指标的评价结果是一致的,然而在互斥方案比选时,应该选用NPV指标而非NPVR指标,但这一点在许多资料里甚至教科书里被笼统的认为两指标在任何情况下评价结果都是一致的。运用管理经济学的基本原理对两指标进行分析,从而清晰界定两指标的使用情况与范围。     

基于NPVR或N/K的互斥型投资方案的选优

在互斥型投资方案的无资格方案的选优方法中,传统的方法是采用静态数据来淘汰无资格方案的,此方法仅仅适用于特殊的现金流的情况,不能解决所有类型互斥方案的选优问题.针对这一缺陷,改进了无资格方案的概念,提出基于净现值率(NPVR)或者投资净收益率(N/K)的动态数据淘汰无资格方案的新方法,此方法可以适用于任何类型的互斥方案的选优问题.同时此方法与互斥型方案选优的环比法的结论是完全一致的,可以保证所选方案为最优方案.     

关于互斥型投资方案的分析评价问题

简单就互斥型投资方案的分析、评价、比较和选择问题，辨证地分析了所采用的方法和指标之间的关系以及多种方法和多种指标存在的必要性和合理性，特别就使用环比差量法进行项目选择的一些观点进行了辨析。     

成败型产品的Bayes鉴定试验方案研究

利用可靠性增长模型给出了成败型产品鉴定试验的一种Bayes方法，提出了Bayes鉴定试验的最大后验风险准则，利用这种准则制定的鉴定试验方案综合了产品研制过程中的先验信息，在确保产品质量的前提下．与传统的鉴定试验方案相比，将大大节省试验时间。     

带交易费用组合证券投资的minimax模型

交易费用对投资者的投资绩效具有直接影响.本文研究了在具有交易费用的情形下,资产投资上限有界以及不允许卖空的证券投资组合优化问题.模型以最小化最大个人风险的minimax准则作为风险度量方法.利用凸规划的Lagrange乘子法与KuhnTucker条件,得到了投资者最优投资策略的显式表达式.最后,利用数值例子阐述了该风险控制模型的投资策略,从而为投资者提供决策依据.     

基于最大间距MFA的鉴别分析

针对边界Fisher分析(MFA)所面临的小样本问题,本文基于最大间距准则(MMC),提出了一种基于最大间距的边界Fisher分析(MMMFA)算法.该方法利用描述类间数据可分性的相似度矩阵与描述类内数据紧致性的相似度矩阵之差作为鉴别准则,从而避免了MFA鉴别分析所遇到的小样本问题.然后探讨了本文算法与传统的线性降维算...     

科视将为嘉禾深圳影城最大的影院安装胶片电影放映机

2004年9月20日，DLP Cinema^TM放映领域的领先厂商科视宣布，在嘉禾娱乐事业(集团)有限公司(GH)设在中国深圳市华润中心万象城的第一个多厅电影院里，将安装7台Christie P35GPSLAT 35mm无齿轮胶片电影放映机。嘉禾深圳耗资513万美元，是深圳最大的电影院，也是嘉禾集团在中国最大的投资项目。     

DVD租赁问题的模型设计及求解

本文讨论了DVD在线租赁的服务供应商可能遇到的问题与其解决方案。模型Ⅱ解决了在已知订单与各种DVD数量的情况下，如何分配DVD使得满意的人数最多，且总的满意度最大。模型Ⅲ解决了在已知订单的情况下，在一定的满意率与总满意度最大的约束下，如何以最小的成本购买各种DVD，并确定分配方案。模型Ⅴ对原问题作了更深入的推广，解决了在DVD数量有限且租赁费用与租赁时间成正比的条件下如何选择性地出租DVD以获得最大收入的问题。本文所讨论的问题均为最优化问题，但是各题的约束条件均不相同，本文对各个问题建立不同的网络模型，经过严密的理论论证，并用统一的费用流算法在微机上实现，充分利用了网络流模型适用面广，结果精确，计算简单的优点，对DVD租赁的现实问题提供了高效的解决方案。     

考虑生产商风险规避的农产品绿色投资策略演化研究

针对农户与生产商绿色投资策略的选择问题，构建以农户为主导的Stackelberg博弈模型，得到双方在不同策略组合下的支付矩阵。以此为依据，运用演化博弈理论，研究农户与风险规避生产商两类异质群体绿色投资策略选择的演化过程，推演不同条件下系统的演化稳定策略，探讨双方绿色投资策略选择的演化路径及其影响因素。结果表明，面对具有绿色农产品消费偏好的消费者时，农户与生产商至少有一方会选择绿色投资策略，当双方选择合作并分担绿色投资成本时市场需求最大。此时，成本分担比例及生产商风险规避程度对两群体的策略选择演化速度、绩效水平具有显著影响。     

某超高层建筑空调冷热源配置浅探

以某超高层建筑为例，比较了不同的冷热源配置方案，就初投资和运行费用进行了分析，并最终选择了合理的冷热源配置方式。     

Integrating carbon market uncertainties into a sustainable manufacturing investment decision: a Bayesian NPV approach

Net present value (NPV) is a widely used technique in capital budgeting. In this paper, we develop a Bayesian NPV framework using a Gibbs sampler. This approach allows decision-makers to integrate their knowledge, past experience, and uncertain and volatile cash flows from carbon emissions credits into decisions dealing with energy efficient, sustainable manufacturing equipment. The results indicate NPV is highly dependent on the nature of volatility and uncertainty of the cash flows. Without inclusion of this information through the Bayesian framework results, NPV becomes overstated, and thus it may provide biased guidance for the investment. The results developed in this paper further show that the frequency of very high and low cash flows and to a lesser degree their variability adversely impacts NPV. The results may also explain reasons for the economic phenomenon known as the energy efficiency gap.     

投资抵免政策在空分项目中的应用分析

根据企业所得税投资抵免优惠政策,以一具体空分设备投资项目为例,通过EXCEL软件计算,得出不同方案的净现值和内含报酬率,从而说明国产空分设备的经济性优势。     

A framework for decision-making in investment alternatives selection

Investment alternatives selection involves a variety of criteria that should be evaluated to provide a solid basis for decision-making. Some prior research has proposed methodologies and frameworks to support such alternatives selection. However, many of them present intrinsic limitations related to their applicability and complexity. Thus, this paper presents a framework for decision-making concerning investment alternatives that are usually related to equipment selection for a manufacturing process, technology selection for product development, product portfolio selection, and production strategy selection, among others. The framework is based on a multi-criteria approach that considers three main criteria: (i) strategy, which considers company market competitiveness; (ii) quality, which considers client requirements; and (iii) economic aspects, considering the overall financial benefits of the investment. These criteria are evaluated with the support of well-known tools from traditional management engineering such as SWOT, QFD, NPV and Payback. The results obtained through the use of these tools are rated using the MAUT method. Two major contributions are offered by this framework: (i) the integration of three key criteria for decision-making that enables to obtain a balanced analysis of the investment alternatives and (ii) the intrinsic easy-to-implement characteristic of the framework – based on the use of traditional tools. The proposed framework was applied in a tailor-made furniture company to support a make-or-buy decision, and the obtained results are discussed.     

A continuous‐time Markov chain model for redundancy allocation problem: An economic analysis

Reliability of an engineering system can be improved by investing on redundant (spare) parts. However, the cost‐efficiency of such an investment is a significant concern that needs to be taken into consideration in practice. To do so, a continuous‐time Markov chain (CTMC) model is presented in this paper to analyze the system's reliability by allocating redundant components. The developed model can also capture the system's repair and failure conditions by defining appropriate states in CTMC. Subsequently, the net present value (NPV) approach is utilized for a variety of scenarios to investigate the effectiveness of investment on spare parts using the break‐even point (BEP) analysis. Afterwards, a comprehensive analysis is carried out to examine the impact of input parameters including interest rate, initial cost of investment, and periodic profit on the decision making process to find the optimal number of spare parts.     

Independent component analysis by wavelets

This paper introduces a new approach in solving the ICA problem using a method that fits in the contrast and minimize paradigm, mostly found in the ICA literature. In our case, the contrast is a L ₂ norm dependence measure, which constitutes an alternative to the usual criteria, based on mutual information. We propose a non parametric evaluation of the L ₂ contrast, using a wavelet projection estimator. The mean square error of the procedure is bounded under Besov assumptions. Finally, we provide a set of simulations to show how the method performs in practice.     

Technology investment effects in performance-based maintenance contracts

This work analyses the effects of a fixed initial investment in technology or infrastructure on performance-based maintenance contracts. We present a mathematical expression which reflects the trade-off between an upfront technology investment by the vendor and the cost of required future interventions. We develop a mathematical model of a performance-based maintenance contract that uses this technology trade-off expression and determines the value of the contract for each party. Contractually, the client indicates the duration of the contract and the optimal number of maintenance interventions to maximise asset availability; the vendor quotes the cost for the requested interventions. We study how the initial investment and the contract parameters affect the net present value for each party and the supply chain, demonstrating the existence of an optimal relation between the number of preventive maintenance interventions and level of investment. We derive the optimal contract parameters for the client, vendor and chain and show lack of coordination between the parties. To achieve coordination, we present a revenue sharing mechanism which maximises the value for the chain. Finally, an industry study case with data from the mining sector is presented. Results indicate that by investing and coordinating, the entire supply chain can improve the contract NPV by 149.7%.     

One-side value-added service investment and pricing strategies for a two-sided platform

To widen user participation and increase profit, two-sided platforms may invest on value-added services (VASs) for users. Due to the cross-market network externality, the investment for one side would affect the utility of users on two sides, thus affect the demand and profit of the platform. In this paper, we investigate one-side VAS investment and pricing strategies for a two-sided platform. It is revealed that it is optimal to invest at the maximum level for any marginal investing cost below a certain threshold, and to decrease the investment when the marginal investing cost increases above the threshold. We find that compared with the case of no investment, the invested user side will always be priced higher, while the uninvested user side may either be priced higher or lower, depending on the relative magnitude of mutual cross-market network externalities. If both sides are priced higher after the investment, the price increment for uninvested user side could be larger than that for invested user side.     

A quantitative model for ERP investment decision: considering revenue and costs under uncertainty

This paper evaluates ERP investment under uncertainty using a model based on the Real Options theory. We expand the Dixit and Pindyck (Dixit, A.K. and Pindyck, R.S., 1994. Investment under uncertainty. Princeton: Princeton University Press) model, which considers a single source of uncertainty, and apply it to the problem of ERP investment decision. Revenue and costs are well documented in the literature as uncertain and critical factors. We developed a quantitative model using the concept of dynamic programming, which takes into account multiple uncertain factors, to determine the optimal threshold ratio of revenue to cost, as a means to evaluate investment in ERP. In addition, we performed sensitivity analysis on the effects various parameters have on the value of ERP projects. In contrast to conventional wisdom, we showed that the evaluation of ERP based on Real Options theory differs from that of NPV and captures a more realistic valuation of investment in ERP. This paper contributes to the literature by taking both uncertain revenue and costs into account, and makes up for the lack of tools required to quantify investments in ERP under uncertainty.