Real R&D options and optimal activation of two-dimensional random controls

We value investments under uncertainty with embedded optional costly controls (impulse-type with uncertain outcome) that capture managerial intervention for value enhancement and/or information acquisition (exploration, R&D, advertising, marketing research, etc). Implementing real option models but neglecting such embedded managerial actions can severely underestimate investment opportunities and lead to erroneous investment decisions. Optimal decisions are solutions to a maximization problem where the trade-off between the control's cost and the value added by such actions is explicitly taken into consideration. In this paper, we generalize such a methodology from one dealing with the special case of actions affecting only one state-variable, to one with actions that affect several. Asset values follow geometric Brownian motion or jump-diffusion processes with multiple generating sources of jumps. The Markov-chain numerical methodology we provide can handle sequential controls. Although we report the results with open-loop policies, the approach can be readily extended to accommodate dependency among the controls.     

Technology lock-in with horizontal and vertical innovations through limited R&D spending

In this paper we analyze an inter-temporal optimization problem of a representative firm that invests in horizontal and vertical innovations and that faces a constraint with respect to total R&D spending. We find that there can exist two different steady-states of the economy when the amount of research spending falls short of an endogenously determined threshold: one with higher productivities and less new technologies being developed, and the other with more technologies being created and lower productivities. But, for a higher amount of R&D spending the steady-state becomes unique and the firm produces the whole spectrum of available technologies. Thus, a lock-in effect may arise that, however, can be overcome by raising R&D spending sufficiently.     

A comparison between the robust risk-aware and risk-seeking managers in R&D portfolio management

In this paper, we analyze two mathematical modeling frameworks that reflect different managerial attitudes toward upside risk in the context of R&D portfolio selection. The manager seeks to allocate a development budget between low-risk, low-reward projects, called incremental projects, and high-risk, high-reward projects, called innovational projects. Because of their highly uncertain nature and significant probability of failure, the expected value of the innovational projects is smaller than that of their incremental projects’ counterpart, but the long-term financial health of a company necessitates to take risk in order to maintain growth. We study the differences in strategy and portfolio’s risk profile that arise between a risk-aware manager, who takes upside risk because he has to for the long-term competitive advantage of his company, and a risk-seeking manager, who will take as big a bet as allowed by the model. To the best of our knowledge, this is the first paper to consider upside risk management using a robust-optimization-like methodology.     

Effects of asymmetric knowledge spillovers on the stability of horizontal and vertical R&D cooperation

In order to investigate the role of asymmetric spillovers in the stability of R&D cooperation, this paper distinguishes two different types of cooperative partners, and uses a game theory approach to reveal the relationship between asymmetric spillovers and R&D investment in the horizontally and vertically related R&D cooperation. In the horizontal R&D cooperation, higher incoming spillovers and lower outgoing spillovers induce firms to invest on R&D efforts as agreed. However, it is the contradiction between horizontal firms’ attitudes towards asymmetric spillovers that leads to the inherent instability of the cooperation. In the vertical R&D cooperation, our results question the usually held opinion about the effects of asymmetric spillovers on the decision of R&D investment. The incoming spillovers are less important in the innovation process for vertically related R&D cooperation. A firm tends to under-invest on the arranged level of R&D efforts when its incoming spillovers increase. Our results also show that efficient mechanisms to restrain firms’ non-cooperative behavior are essential to improve the stability of horizontal and vertical R&D cooperation.     

Planning and Control of R & D Activities

Despite the success of network techniques for planning maintenance and construction projects there has been little application in R & D. Extensions to network planning techniques to allow their use in R & D are described and potential areas of cost and benefit stemming from their use identified. Some applications of planning methods in R & D are considered and conclusions are drawn concerning the difficulties to be faced, and the strategies to be adopted, in their implementation.     

The impact of delaying an investment decision on R&D projects in real option game

In a research and development (R&D) investment, the cost and the project value of such an investment are usually uncertain, which thus increases its complexity. Correspondingly, the NPV (Net Present Value) rule fails to evaluate the value of this project exactly, because this method does not take into account the market uncertainty, irreversibility of investment and ability of delay entry. In this paper, we employ the real option theory to evaluate the project value of a R&D investment. Since the cost of a R&D investment is very high and the flow of the information is crowded, an investor cannot make an immediate decision every time. So, the proposed real option model is an exchange option. At the same time, combining the real option and the game theory, we can find the Nash equilibrium which is the optimal strategy. Moreover, we also study how the delayed time influences the price of the project investment and how the different delayed times effect the choice of the optimal strategies.     

Step by step. The benefits of stage-based R&D licensing contracts

We examine how a licensor can optimally design licensing contracts for multi-phase R&D projects when he does not know the licensee’s project valuation, leading to adverse selection, and cannot enforce the licensee’s effort level, resulting in moral hazard. We focus on the effect of the phased nature typical of such projects, and compare single-phase and multi-phase contracts. We determine the optimal values for the upfront payment, milestone payments and royalties, and the optimal timing for outlicensing. Including multiple milestones and accompanying payments can be an effective way of discriminating between licensees holding different valuations, without having to manipulate the royalty rate, which induces licensees to invest less, resulting in lower project values and socially suboptimal solutions. Interestingly, we also find that multiple milestone payments are beneficial even when the licensor is risk-averse, contrary to standard contract theory results, which recommend that only an upfront payment should be used. In terms of licensing timing, we show that the optimal time depends on the licensor’s risk aversion, the characteristics of the licensee and the project value.     

Multi-criteria decision analysis as an aid to the strategic planning of Energy R&D

This paper demonstrates the use of multi-criteria decision analysis to assist an advisory council in selecting areas of interest for government-financed Energy R&D, subject to a budget constraint. The benefits of Energy R&D may be difficult to value in monetary terms. A different way of comparing the anticipated impacts of Energy R&D in various technological areas based on the opinions of the council members given a number of judgment criteria is described, followed by maximizing the overall impact of an Energy R&D programme for a given level of expenditure. Since the council members have different backgrounds, their opinions may diverge and so may the solutions to the optimization problem. The decision model can be used as a discussion model highlighting the points of agreement and disagreement amongst them, so that they can concentrate on the latter in order to reach a vindicated compromise.     

A model of R&D valuation and the design of research incentives

We develop a real options model of R&D valuation that takes into account the uncertainty in the quality (or efficacy) of the research output, the time and cost to completion, and the market demand for the R&D output. The model is then applied to study the problem of pharmaceutical under-investment in R&D for vaccines to treat diseases affecting the developing regions of the world. To address this issue, world organizations and private foundations are willing to sponsor vaccine R&D, but there is no consensus on how to administer the sponsorship effectively. Different research incentive contracts are examined using our valuation model. Their effectiveness is measured in the following five dimensions: expected cost to the sponsor, probability of development success, consumer surplus generated, expected number of successful vaccinations and expected cost per person successfully vaccinated. We find that, in general, purchase commitment plans (pull subsidies) are more effective than cost subsidy plans (push subsidies). Moreover, we find that a hybrid subsidy plan constructed from a purchase commitment combined with a sponsor research cost-sharing subsidy is the most effective.     

A model of R&D valuation and the design of research incentives

We develop a real options model of R&D valuation that takes into account the uncertainty in the quality (or efficacy) of the research output, the time and cost to completion, and the market demand for the R&D output. The model is then applied to study the problem of pharmaceutical under-investment in R&D for vaccines to treat diseases affecting the developing regions of the world. To address this issue, world organizations and private foundations are willing to sponsor vaccine R&D, but there is no consensus on how to administer the sponsorship effectively. Different research incentive contracts are examined using our valuation model. Their effectiveness is measured in the following five dimensions: expected cost to the sponsor, probability of development success, consumer surplus generated, expected number of successful vaccinations and expected cost per person successfully vaccinated. We find that, in general, purchase commitment plans (pull subsidies) are more effective than cost subsidy plans (push subsidies). Moreover, we find that a hybrid subsidy plan constructed from a purchase commitment combined with a sponsor research cost-sharing subsidy is the most effective.     

Expenditure patterns and timing of patent protection in a competitive R&D environment

In this paper we consider a stochastic R&D decision model for a single firm operating in a competitive environment. The study focuses on the firm's optimal policy which maximizes the expected discounted net return from the project. The firm's policy is composed of two ingredients: a stopping time which determines when the developed technology should be introduced and protected by a patent, and an investment strategy which specifies the expenditure rate throughout the R&D program. The main findings of the study are:

• (a) 

  Under a constant expenditure rate strategy, the optimal stopping time of the project is a control limit policy of the following form: stop whenever the project's state exceeds a fixed critical value, or when a similar technology is introduced and protected by one of the firm's rivals, whichever occurs first.

• (b) 

  For a R&D race model in which the winner-takes-all competition and the loser's return is zero, we show that the firm's optimal expenditure rate throughout the R&D program increases monotonically as a function of the project's state.

In order to gain a better insight regarding optimal R&D programs in competitive markets we examine the effect of key economic parameters on the firm's optimal policy.     

The role of feedback dynamics in disruption and delay on the nature of disruption and delay (D&D) in major projects

The idea that small disruptions and delays can cause serious consequences to the life of a major project, well beyond that which might be easily attributed to their direct impact, is well established. Nevertheless, the nature of this ‘delay and disruption’ is still not fully understood. This paper discusses some of the issues and difficulties in gaining a full understanding. In particular it presents the variety of ways in which disruptions occur, and the variety of consequences that may unfold. It also focuses attention on a number of issues that arise when ‘normal’ methods of analysis of complex projects might be used, for example, the analysis and costing of change orders and the use of network analysis. The role of dynamic feedback and the ‘portfolio effect’ is introduced, particularly with reference to project acceleration and changing productivity.     

A generalized real option pricing method of R&D investments: jump diffusion and external competition

ABSTRACT

Numerous studies have assessed Research and Development (R&D) investment using the real option pricing approach. This paper proposes a more general real option pricing method that both considers the specificity of R&D investment (such as uncertainty) and the R&D investment opportunity of a business in a market environment with external competitors. Specifically, we adopt a jump diffusion model to evaluate R&D investments that incorporate the uncertainties of these activities. The model values a pioneer's R&D investment opportunity allowing the chance that competitors may enter the market and the project value may vary with time. By construction and analysis of the model, we then analyse the optimal timing to realize profit on an investment. Overall, this model should facilitate a more comprehensive evaluation for R&D investments.     

考虑双参照点和Choquet积分的新型研发机构绩效评估方法及应用

针对新型研发机构绩效评估值不确定、指标间存在关联、投资主体多元且有风险偏好、指标集权重未知等绩效问题,提出基于双参照点和Choquet积分的绩效评估方法。首先,结合新型研发机构的特点,构建绩效评估指标体系;其次,基于累积前景理论设计同行-期望双参照点;然后,构建指标间直接关联矩阵,依据K-可加模糊测度和平均边际贡献Banzhaf值优化求解指标集权重,代入Choquet积分方法和参照点权重公式计算各新型研发机构的综合绩效评估值,从而实现机构排序和问题分析。该方法考虑了新型研发机构的特点、数据不确定性、指标关联性、风险偏好性、权重未知性等因素,更加符合实际情况,案例验证了方法的有效性和实用性。     

Constructing and evaluating balanced portfolios of R&D projects with interactions: A DEA based methodology

We propose and demonstrate a methodology for the construction and analysis of efficient, effective and balanced portfolios of R&D projects with interactions. The methodology is based on an extended data envelopment analysis (DEA) model that quantifies some the qualitative concepts embedded in the balanced scorecard (BSC) approach. The methodology includes a resource allocation scheme, an evaluation of individual projects, screening of projects based on their relative values and on portfolio requirements, and finally a construction and evaluation of portfolios. The DEA–BSC model is employed in two versions, first to evaluate individual R&D projects, and then to evaluate alternative R&D portfolios. To generate portfolio alternatives, we apply a branch-and-bound algorithm, and use an accumulation function that accounts for possible interactions among projects. The entire methodology is illustrated via an example in the context of a governmental agency charged with selecting technological projects.     

The Influence of an Internet‐Based Formative Assessment Tool on Primary Grades Students’ Number Sense Achievement

This study examined primary grades students’ achievement on number sense tasks administered through an Internet‐based formative assessment tool, Assessing Math Concepts Anywhere. Data were analyzed from 2,357 students in teachers’ classrooms who had participated in a year‐long professional development program on mathematics formative assessment, 1,427 students from teachers who had participated in the program in the year prior, and 9,783 students whose teachers had not participated at all. Analyses indicated that all students in the treatment group demonstrated growth, and that student achievement was influenced by the number of times the assessment was used to collect data and make instructional decisions. Further, there was a relationship between districts’ socioeconomic status and growth, meaning students from impoverished backgrounds grew more than their peers.     

Generalized Entropy Numbers and Gelfand Numbers – an Approach to the Entropy Behaviour of Certain Integral Operators

The present paper is devoted to the study of a theorem of Pachl and some of its consequences. This theorem states that every supermodular increasing set function defined on a lattice of sets is dominated by a tight set function.     

The 3D index of an ideal triangulation and angle structures

The 3D index of Dimofte–Gaiotto–Gukov is a partially defined function on the set of ideal triangulations of 3-manifolds with r tori boundary components. For a fixed 2r tuple of integers, the index takes values in the set of q-series with integer coefficients. Our goal is to give an axiomatic definition of the tetrahedron index and a proof that the domain of the 3D index consists precisely of the set of ideal triangulations that support an index structure. The latter is a generalization of a strict angle structure. We also prove that the 3D index is invariant under 3–2 moves, but not in general under 2–3 moves.     

Mixed finite element approximation of an MHD problem involving conducting and insulating regions: The 3D case

In this paper we extend in 3D a 2D Lagrange finite element technique proposed previously in Guermond and Minev (Mod. Math. Anal. Num. 2001) for solving the Maxwell equations in the low‐frequency limit in a domain composed of conducting and insulating regions. © 2003 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 19: 709–731, 2003.