The Effect of Competition on R&D Portfolio Investments

Although project portfolio management has been an active research area over the past 50 years, budget allocation models that consider competition are sparse. Faced with the competition, firms contemplating budget allocation for their project portfolio cannot limit their attention to the returns from their projects' target markets, as is the case for monopoly firms, but must also anticipate the competitive effects on these returns. Assuming firms allocate their budgets between projects offering incremental innovation targeting a mature market and projects offering radical innovation targeting an emerging market, we show that while the monopoly firm bases its budget allocation decision solely on the marginal returns of the markets, competing firms—as they take into account their counterparts' investment decisions—need to also consider the projects' average returns from their respective markets. This drives competing firms into incrementalism: faced with competition, firms invest larger portions of their budgets into projects targeting mature markets. This effect is amplified as the number of competing firms increases and firms allocate an even greater share of their budget into projects targeting a mature market. We further demonstrate the effects that changes to firms' individual budgets, as well as to market characteristics, have on firms' budget allocation decision.     

Application of the knapsack model for budgeting

The budget problem of selecting projects (or activities) with known values (or payoffs) and associated costs, subject to a prescribed maximum budget, is akin to the knapsack problem, which is well documented in the literature. The optimal solution to maximise the total value of selected projects for a given budget constraint can readily be obtained. In practice, budgets are often somewhat flexible, or subject to possible changes, so that an optimal solution for a given budget value may not remain optimal when the budget is modified. It is, therefore, sensible in many situations to consider a budget range, instead of a single budget value. In addition to their original objective of maximising the total value of selected projects, decision makers are often concerned to get ‘value for money’, indicated by the ratio of payoff to cost. This paper examines how these questions can be tackled through the introduction of a stability index, to guide project selection within a defined budget range, and the use of a portfolio diagram, to help in the ranking of projects with respect to the stated twin objectives.     

资源约束下可打断项目组合选择模型研究

首先,本文在已有可打断项目组合选择模型的基础上,引入了消耗性资源和可更新资源约束,构建了一个更符合实际的新模型;其次,为了达到模型简化的目的,本文给出了资金约束的现值表示,并给出了理论证明;最后,利用GAMS对模型进行了算例分析。数值实验结果表明：1）资源约束下的项目打断有时可以给企业带来积极效益,这有别于已有的研究;2）在考虑资源约束的情况下,资源消耗少且同时收益高的项目应优先执行;3）当资源的供给量较少时,资源约束是决定项目选择的关键因素。此外,通过企业实际的案例对数值实验结果进行了验证。     

Incorporating balance concerns in resource allocation decisions: A bi-criteria modelling approach

We consider resource allocation problems where inputs are allocated to different entities such as activities, projects or departments. In such problems a common goal is achieving a desired balance in the allocation over different categories of the entities. We propose a bi-criteria framework for trading balance off against efficiency. We define and categorise indicators based on balance distribution and propose formulations and solution algorithms which provide insight into the balance-efficiency tradeoff. We illustrate our models by applying them to the data of a portfolio selection problem faced by a science funding agency and to randomly generated large-sized problem instances to demonstrate computational feasibility.     

Estimation of Downside Risks in Project Portfolio Selection

In project portfolio selection, the aim is to choose projects which are expected to offer most value and satisfy relevant risk and other constraints. In this study, we show that uncertainties about how much value the projects will offer, combined with the fact that only a subset of the proposed projects will be selected, lead to inaccurate risk estimates about the aggregate value provided by the selected project portfolio. In particular, when downside risks are measured in terms of lower percentiles of the distribution of portfolio value, these risk estimates will exhibit a systematic bias. For deriving unbiased risk estimates, we present a calibration framework in which the required calibration can be presented in closed‐form in some cases or, more generally, derived by using Monte Carlo simulation to study a large number of project selection decisions. We also show that when the decision must comply with risk constraints, the introduction of tighter (more demanding) risk constraints can counterintuitively aggravate the underestimation of risks. Finally, we present how the calibrated risk estimates can be employed to align the portfolio with the decision maker's risk preferences while eliminating systematic biases in risk estimates.     

基于项目网络支配和扩散关系的研发项目组合选择

项目组合包含多项目且项目间存在相互作用和依赖关系,针对传统项目组合评价方法忽略了各项目间依赖关系的不足,本文采用复杂网络理论和PageRank算法,提出一种新的项目优先级排序方法（PPRM）。首先,本文建立研发项目多属性评价准则,分析了项目间的支配关系以及技术和经验在项目间的扩散关系。然后,以项目为节点、以支配和扩散关系为边,分别构建了项目支配和扩散网络,进一步,采用设计结构矩阵（DSM）和K-shell方法建立了基于支配网络的项目影响力模型,并建立了考虑项目之间多次扩散传播的综合扩散概率模型。综合项目节点影响力和扩散关系,本文构建了基于PageRank算法的研发项目优先级排序模型。最后,以某研发项目组合选择为例,验证了本文所建立的模型和算法可有效分析项目组合中的排序问题。     

受弹性时间段和价值波动双重影响的项目组合选择问题研究

许多现有的项目组合模型都认为项目集合可以在固定的计划期完成,但是在实际的项目执行过程中,决策者为了使得高收益的项目纳入项目集合中或者放弃风险高的项目来释放更多的资金,会选择对项目组合固定的计划期进行灵活性调整。同时,考虑到项目未来价值的不确定性,本文利用实物期权的二叉树模型给出了价值波动的公式,进而建立了同时受弹性时间段和价值波动影响的项目组合选择的新模型,对传统的计算项目价值的净现值法进行补充。通过GAMS/BARON对算例进行求解,验证了模型的合理性和有效性。结果表明：考虑弹性时间段和价值波动的影响会给更符合企业长期的发展战略,给企业带来更大的收益,该模型也为处理不确定情况下的项目组合问题提供了新思路和新方法。     

Linear solution schemes for Mean-SemiVariance Project portfolio selection problems: An application in the oil and gas industry

We study the Mean-SemiVariance Project (MSVP) portfolio selection problem, where the objective is to obtain the optimal risk-reward portfolio of non-divisible projects when the risk is measured by the semivariance of the portfolio׳s Net-Present Value (NPV) and the reward is measured by the portfolio׳s expected NPV. Similar to the well-known Mean-Variance portfolio selection problem, when integer variables are present (e.g., due to transaction costs, cardinality constraints, or asset illiquidity), the MSVP problem can be solved using Mixed-Integer Quadratic Programming (MIQP) techniques. However, conventional MIQP solvers may be unable to solve large-scale MSVP problem instances in a reasonable amount of time. In this paper, we propose two linear solution schemes to solve the MSVP problem; that is, the proposed schemes avoid the use of MIQP solvers and only require the use of Mixed-Integer Linear Programming (MILP) techniques. In particular, we show that the solution of a class of real-world MSVP problems, in which project returns are positively correlated, can be accurately approximated by solving a single MILP problem. In general, we show that the MSVP problem can be effectively solved by a sequence of MILP problems, which allow us to solve large-scale MSVP problem instances faster than using MIQP solvers. We illustrate our solution schemes by solving a real MSVP problem arising in a Latin American oil and gas company. Also, we solve instances of the MSVP problem that are constructed using data from the PSPLIB library of project scheduling problems.     

Allocation of research and development funds: A zero-one goal programming approach

The research and development project selection process is one of the most difficult and important problems faced by management. It is typically complicated by indivisibility of projects and multiple and conflicting objectives, in addition to limitations on funding, facilities, and qualified researchers. In this paper a case example involving a high technology electrical equipment manufacturer is developed to illustrate this problem using zero—one goal programming to accommodate indivisibility of projects in addition to multiple and conflicting goals. The model presented is an attempt to provide managers with a robust tool for allocating scarce resources among research and development projects.     

A fuzzy set approach for R&D portfolio selection using a real options valuation model

Making R&D portfolio decision is difficult, because long lead times of R&D and market and technology dynamics lead to unavailable and unreliable collected data for portfolio management. The objective of this research is to develop a fuzzy R&D portfolio selection model to hedge against the R&D uncertainty. Fuzzy set theory is applied to model uncertain and flexible project information. Since traditional project valuation methods often underestimate the risky project, a fuzzy compound-options model is used to evaluate the value of each R&D project. The R&D portfolio selection problem is formulated as a fuzzy zero–one integer programming model that can handle both uncertain and flexible parameters to determine the optimal project portfolio. A new transformation method based on qualitative possibility theory is developed to convert the fuzzy portfolio selection model into a crisp mathematical model from the risk-averse perspective. The transformed model can be solved by an optimization technique. An example is used to illustrate the proposed approach. We conclude that the proposed approach can assist decision makers in selecting suitable R&D portfolios, while there is a lack of reliable project information.     

Roy’s Safety‐First Portfolio Principle in Financial Risk Management of Disastrous Events

Roy pioneers the concept and practice of risk management of disastrous events via his safety‐first principle for portfolio selection. More specifically, his safety‐first principle advocates an optimal portfolio strategy generated from minimizing the disaster probability, while subject to the budget constraint and the mean constraint that the expected final wealth is not less than a preselected disaster level. This article studies the dynamic safety‐first principle in continuous time and its application in asset and liability management. We reveal that the distortion resulting from dropping the mean constraint, as a common practice to approximate the original Roy’s setting, either leads to a trivial case or changes the problem nature completely to a target‐reaching problem, which produces a highly leveraged trading strategy. Recognizing the ill‐posed nature of the corresponding Lagrangian method when retaining the mean constraint, we invoke a wisdom observed from a limited funding‐level regulation of pension funds and modify the original safety‐first formulation accordingly by imposing an upper bound on the funding level. This model revision enables us to solve completely the safety‐first asset‐liability problem by a martingale approach and to derive an optimal policy that follows faithfully the spirit of the safety‐first principle and demonstrates a prominent nature of fighting for the best and preventing disaster from happening.     

Measuring dynamic efficiency of highway maintenance operations

In this paper we discuss a dynamic efficiency measurement model for evaluating the performance of highway maintenance policies where the inter-temporal dependencies between consumption of inputs (i.e., maintenance budget) and realization of outputs (i.e., improvement in road condition) are explicitly captured. We build on a micro representation of pavement deterioration and renewal processes and study the impact of the allocation of scarce maintenance budgets over time. We provide a measure of efficiency that contrasts the optimized budget allocations to the actual ones. The developed model is then applied to an empirical dataset of pavement condition and maintenance expenditures over the years 2002 to 2008 corresponding to seventeen miles of interstate highway that lay in one of the counties in the state of Virginia, USA. The policies that were found through optimization showed that road authorities should give higher priorities to preventive maintenance than corrective maintenance. In essence, by applying preventive maintenance, the road authorities can effectively decrease the need for future corrective maintenance while spending less overall.     

Financial planning for new products: Part I—Basis for model formulation

In a previous paper the author presented a staged approach methodology for the evaluation and selection of R & D projects. The present paper is intended to serve as its complement.The aim is the formulation of a matching overall long range budget planning policy which will attempt to answer the questions of “how many projects to prove” and “how much to fund” on the basis of satisfying the company growth objective.To achieve the above purpose, a staged budget planning model has been developed which recognizes and utilizes the specific attributes of the various R & D stages. Tje project stage survival rate and project stage cost ratio concepts are discussed. A steady flow of projects through the various R & D stage is maintained. The aim of the program is to produce periodically a planned number of new products fro commercial investment.This methodology may apply to R & D program with a sufficient number of moderately sized projects that justify the use of survival rate and cost ratio values. It should be constructed as a tentative effort for possible use within the staged limitations.     

基于实物期权的研发项目动态投资决策模型

本文基于实物期权理论,针对研发项目阶段性特点,结合博弈论的思想,分析了多个研发项目组成的投资状态组合,构建了研发项目动态选择模型。首先,根据研发项目多阶段的特征,利用孪生证券的思想,基于实物期权理论,建立了项目中止决策准则;在此基础上分析研发项目的投资决策状态,建立了二十五个状态的切换场景;然后通过实际算例对模型进行验证和分析,得出了研发项目投资的影响范围概念图,最终实现两个项目的最优投资决策目标。     

Managing a Portfolio of Product Development Projects under Resource Constraints

Managers of product development (PD) project portfolios face difficult decisions in allocating limited resources to minimize project or portfolio delay. Although PD projects are highly iterative (cyclical), almost all of the vast literature on project scheduling assumes that projects are acyclical. This article addresses this gap with a comprehensive analysis of 31 priority rules (PRs) on 18,480 portfolios containing 55,440 iterative projects. We find that the best PRs for iterative project portfolios differ significantly from those for acyclical ones, and that the best PRs at the project level differ from those at the portfolio level. The best PR depends on project and portfolio characteristics such as network density, iteration intensity, resource loading profile, and amount of resource contention. In particular, by amplifying the effects of iteration, high‐density networks hold dramatically different implications for iterative projects. Moreover, the best PR also differs depending on whether the objective is to minimize the average delay to all projects or to minimize delay to the overall portfolio. Thus, a project or portfolio manager who uses the same PR on all occasions will exhibit unnecessarily poor performance in most cases.     

PORTFOLIOS OF RISKY PROJECTS

The problem of selecting a portfolio from a set of independent risky business ventures is formulated in terms of maximization of the risk-adjusted (certainty-equivalent) profit of the portfolio, based upon the exponential utility function. Objects of investment include fractional participation (risk sharing) in projects with other firms, where costs and returns are shared in the same proportion. The method assumes that project costs are certain. Project revenues are uncertain, and any probability function for revenue can be used.     

建设项目的费用控制以及项目费用管理系统的需求

对于许多项目而言,费用严重超支、交付成果低劣的现象更凸显了需要对项目管理流程进行有效的管理和控制。本文叙述了项目从概念设计阶段到完工整个生命周期的有效费用控制,并介绍了进行这种控制所需要的项目费用管理系统在大型建设项目上的应用。     

A short term forecasting model for R & D expenditures

Whenever budget requests for individual R & D projects contain a built-in contingency then this will result in inefficient use of scarce resources. At the end of the year the annual budget may have been fully allocated but not necessarily fully utilized. This can result in delays or even complete cancellation of other proposed R & D projects because of an apparent lack of funding.The objective of the study was to forecast monthly R & D expenditures with a better accuracy than available from the subjective estimates of individual project leaders. The method described in this paper proved to be successful in practice.     

具有模糊收益的项目投资组合优化方法

基于可能性理论,研究了投资项目具有模糊收益的多项目投资组合的决策问题。在假设投资项目各年净现金流为三角模糊数的条件下,运用可能性均值和方差,建立了基于现值指数法的单投资项目模糊收益指标和模糊风险评价指标,同时,在此基础上建立了基于模糊可能性均值与方差的多项目投资组合优化模型,提出了最优项目投资组合的算法。最后,给出实际算例说明了方法的可行性和有效性。     

基于突变的项目组合共享资源竞争拥挤研究

对于以项目方式进行管理或生产的企业来说,共享资源在多项目、特别是项目组合(project portfolio,PP)中的合理配置是企业运营所需要解决的重要问题,对企业实现可持续发展起着关键的支撑作用。本文将突变理论引入项目组合管理问题中,在类比交通系统中车辆对交通资源竞争的基础上,提出了项目组合系统共享资源竞争拥挤概念,并对其基础变量进行了详细分析;其次,本文分析了项目组合共享资源竞争拥挤势函数和竞争稳定性,构建了以系统效率最大化为决策目标的项目组合共享资源竞争拥挤模型;最后,通过HD集团的案例分析对项目组合共享资源竞争拥挤模型的可实践性进行了验证,并以此为基础,针对项目组合管理提出了共享资源的改进管理方案。