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.     

研究与开发投资的多阶段实物期权分析

本文结合技术不确定性和现金流不确定性及专利保护 ,将 R& D项目划分为 R& D阶段和新产品商业化阶段 ,运用实物期权法 ,对 R& D项目进行分析 .由动态规划方法推倒出有关项目价值评估和投资期权评价的方程式 ,并作相应典型数值分析 .     

Climate change and optimal energy technology R&D policy

Public policy response to global climate change presents a classic problem of decision making under uncertainty. Theoretical work has shown that explicitly accounting for uncertainty and learning in climate change can have a large impact on optimal policy, especially technology policy. However, theory also shows that the specific impacts of uncertainty are ambiguous. In this paper, we provide a framework that combines economics and decision analysis to implement probabilistic data on energy technology research and development (R&D) policy in response to global climate change. We find that, given a budget constraint, the composition of the optimal R&D portfolio is highly diversified and robust to risk in climate damages. The overall optimal investment into technical change, however, does depend (in a non-monotonic way) on the risk in climate damages. Finally, we show that in order to properly value R&D, abatement must be included as a recourse decision.     

R&D pipeline management: Task interdependencies and risk management

Maintaining a rich research and development (R&D) pipeline is the key to remaining competitive in many industrial sectors. Due to its nature, R&D activities are subject to multiple sources of uncertainty, the modeling of which is compounded by the ability of the decision maker to alter the underlying process. In this paper, we present a multi-stage stochastic programming framework for R&D pipeline management, which demonstrates how essential considerations can be modeled in an efficient manner including: (i) the selection and scheduling of R&D tasks with general precedence constraints under pass/fail uncertainty, and (ii) resource planning decisions (expansion/contraction and outsourcing) for multiple resource types. Furthermore, we study interdependencies between tasks in terms of probability of success, resource usage and market impact. Finally, we explore risk management approaches, including novel formulations for value at risk and conditional value at risk.     

A note on the analysis of the expected value of perfect information with respect to a class of R&D projects

This note is concerned with the question if and when to carry out marketing operations that are aimed at completely reducing marketing uncertainties surrounding the value of a stationary R&D project at its technical completion. It is shown that the benefits arising from thise operations can be measured via the EVPI (the expected value of perfect information). In addition, it is observed that the timing of these operations should only be considered at the beginning of the project's life. Finally, a sensitivity analysis with respect to the statistical properties of the EVPI is performed.     

The option value of advanced R & D

Existing tools for making R&D investment decisions cannot properly capture the option value in R&D. Since many new products are identified as failures during the R&D stages, the possibility of refraining from market introduction may add a significant value to the NPV of the R&D project. This paper presents new theoretical insight by developing a stochastic jump amplitude model in a real setting. The option value of the proposed model depends on the expected number of jumps and the expected size of the jumps in a particular business. The model is verified with empirical knowledge of current research in the field of multimedia at Philips Corporate Research. This way, the gap between real option theory and the practice of decision making with respect to investments in R&D is diminished.     

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.     

Real R&;D options with time-to-learn and learning-by-doing

We model R&D efforts to enhance the value of a product or technology before final development. Such efforts may be directed towards improving quality, adding new features, or adopting technological innovations. They are implemented as optional, costly and interacting control actions expected to enhance value but with uncertain outcome. We examine the interesting issues of the optimal timing of R&D, the impact of lags in the realization of the R&D outcome, and the choice between accelerated versus staged (sequential) R&D. These issues are also especially interesting since the history of decisions affects future decisions and the distributions of asset prices and induces path-dependency. We show that the existence of optional R&D efforts enhances the investment option value significantly. The impact of a dividend-like payout rate or of project volatility on optimal R&D decisions may be different with R&D timing flexibility than without. The attractiveness of sequential strategies is enhanced in the presence of learning-by-doing and decreasing marginal reversibility of capital effects.     

Productivity and technical changes in the Indian pharmaceutical industry

We study the productivity change and factors driving this change in the Indian pharmaceutical industry during 1994–2003, in the backdrop of economic liberalization and change in regulatory norms. We use a non parametric Data Envelopment based-methodology to estimate productivity change and decompose it into technical and relative efficiency changes. We find that, the long-term strategic measures by a section of innovative firms that foresaw the implications from competitive forces of globalization and a change in the regulatory environment have sphereheaded the technical change. Consequently, few innovative firms, characterized by greater R&D investments, transition into higher value-added products and businesses as a step towards more technically sophisticated new drug development have pushed the production frontier, increasing the technical and productivity gains. The higher technical and R&D capabilities and wider new product portfolios of multinational companies also have contributed to the positive technical and productivity changes in the Indian pharmaceutical industry.     

Modelling of technology lifetime based on patent citation data and segmentation

Stakeholders faced with decisions on whether or not to invest in Research & Development (R&D) are increasingly in need of R&D supporting information. As such, the social demand for reliable methods to collect and assess such data continues to grow. In terms of technology appraisal and valuation, the economic life span is a particularly important factor that affects the size of the profit resulting from that technology. Here, we propose a new methodology for quantitatively estimating the technology lifetime based on patent citation data and segmentation. Using the proposed methodology, we are able to estimate the mean or median patent lifetime at both the technology group level and the individual patent level. The estimated technology lifetime may be used as an index for supporting decision-making on strategic investments related to R&D activities and for managing technology throughout its lifecycle, including R&D planning, development, and application. We have applied the proposed methodology to US patent data for the period 1976–2004 for four communications areas.     

On the prisoner’s dilemma in R&D with input spillovers and incentives for R&D cooperation

This paper considers a standard model of strategic R&D with spillovers in R&D inputs, and extends the result that duopoly firms engaged in a standard two-stage game of R&D and Cournot competition end up in a prisoner’s dilemma situation for their R&D decisions, whenever spillover effects and R&D costs are relatively low. In terms of social welfare, this prisoner’s dilemma always works to the advantage of both consumers and society. This result allows a novel and enlightening perspective on some issues of substantial interest in the innovation literature. In particular, the incentive firms face towards R&D cooperation in the form of an R&D cartel is shown to be maximal for the case of zero spillovers, which is when the prisoner’s dilemma has the largest scope.     

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.     

An approximate dynamic programming framework for modeling global climate policy under decision-dependent uncertainty

Analyses of global climate policy as a sequential decision under uncertainty have been severely restricted by dimensionality and computational burdens. Therefore, they have limited the number of decision stages, discrete actions, or number and type of uncertainties considered. In particular, two common simplifications are the use of two-stage models to approximate a multi-stage problem and exogenous formulations for inherently endogenous or decision-dependent uncertainties (in which the shock at time t+1 depends on the decision made at time t). In this paper, we present a stochastic dynamic programming formulation of the Dynamic Integrated Model of Climate and the Economy (DICE), and the application of approximate dynamic programming techniques to numerically solve for the optimal policy under uncertain and decision-dependent technological change in a multi-stage setting. We compare numerical results using two alternative value function approximation approaches, one parametric and one non-parametric. We show that increasing the variance of a symmetric mean-preserving uncertainty in abatement costs leads to higher optimal first-stage emission controls, but the effect is negligible when the uncertainty is exogenous. In contrast, the impact of decision-dependent cost uncertainty, a crude approximation of technology R&D, on optimal control is much larger, leading to higher control rates (lower emissions). Further, we demonstrate that the magnitude of this effect grows with the number of decision stages represented, suggesting that for decision-dependent phenomena, the conventional two-stage approximation will lead to an underestimate of the effect of uncertainty.     

Comparative evaluation of performance of national R&D programs with heterogeneous objectives: A DEA approach

The strategic importance of performance evaluation of national R&D programs is highlighted as the resource allocation draws more attention in R&D policy agenda. Due to the heterogeneity of national R&D programs’ objectives, however, it is intractably difficult to relatively evaluate multiple programs and, consequently, few studies have been conducted on the performance comparison of the R&D programs. This study measures and compares the performance of national R&D programs using data envelopment analysis (DEA). Since DEA allows each DMU to choose the optimal weights of inputs and outputs which maximize its efficiency, it can mirror R&D programs’ unique characteristics by assigning relatively high weights to the variables in which each program has strength. Every project in every R&D program is evaluated together based on the DEA model for comparison of efficiency among different systems. Kruskal–Wallis test with a post hoc Mann–Whitney U test is then run to compare performance of R&D programs. Two alternative approaches to incorporating the importance of variables, the AR model and output integration, are also introduced. The results are expected to provide policy implications for effectively formulating and implementing national R&D programs.     

HETEROGENEOUS INFORMATION ARRIVAL AND R＆D OPTION PRICING

The paper models the arrival of heterogeneous information during R&D stages as a doubly stochastic Poisson process(DSPP). The new product market introduction is considered as a timing option(an American perpetual option). Investment in R&D can be thought of as option on an option(a compound option). This paper derives an analytic approximation valuation formula for the R&D option, and demonstrates that the accounts for heterogeneous information arrival may reduce the pricing biases. This way, the gap between real option theory and the practice of decision making with respect to investment in R&D is diminished.     

Are economically advanced countries more efficient in basic and applied research?

Research and development (R&D) of countries play a major role in a long-term development of the economy. We measure the R&D efficiency of all 28 member countries of the European Union in the years 2008–2014. Super-efficient data envelopment analysis (DEA) based on robustness of classification into efficient and inefficient units is adopted. We use the number of citations as output of basic research, the number of patents as output of applied research and R&D expenditures with manpower as inputs. To meet DEA assumptions and to capture R&D characteristics, we analyze a homogeneous sample of countries, adjust prices using purchasing power parity and consider time lag between inputs and outputs. We find that the efficiency of general R&D is higher for countries with higher GDP per capita. This relation also holds for specialized efficiencies of basic and applied research. However, it is much stronger for applied research suggesting its outputs are more easily distinguished and captured. Our findings are important in the evaluation of research and policy making.     

不确定竞争市场的R&D投资决策分析

本文针对不确定的竞争市场 ,分析降低成本的不可逆 R& D投资决策 .考虑到 R& D结果不确定 ,而这种不确定与投资量有关 ,在利用博弈论方法分析和给出了投资结果不确定的投资期权价值后 ,设随机市场需求规模服从均匀分布 ,本文分析了各种因素对 R& D投资的影响 ,发现较大的市场需求预期和较强的成本节约效果鼓励了 R& D投资 ;相反地 ,较大的成功 R& D所需的最大投资量挫败了 R& D投资 ;而投资期望净收益与投资成本之间的权衡使得存在事前最优投资量最大化投资期权价值     

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.     

Terrorism deterrence in a two country framework: strategic interactions between R&D, defense and pre-emption

In this paper, we analyze the equilibrium responses (in terms of defense, R&D and preemption) to a potential terrorist attack in a two-country framework (Home and Foreign) using a multi-stage game with imperfect information. We highlight three different types of strategic interactions: (a) how the choice of defense, R&D and pre-emption affects the choice of the same in the other country (strategic interdependence across countries); (b) the strategic interaction between the instruments of terrorism deterrence, namely, defense, R&D and pre-emption in a given country and (c) the strategic interaction between the terrorist and the defender. Our main results are as follows: (i) defense effort in Home is a strategic complement to the defense effort in Foreign. (ii) Even without R&D sharing between countries, we find that R&D effort in one country is a strategic substitute to that in the other; (iii) similar results hold for pre-emption because of its public good nature; (iv) for a given country, defense and R&D efforts may be strategic substitutes or complements depending on the magnitude of the ratio of weighted expected damage between Foreign and Home; (v) R&D and pre-emption may be strategic substitutes or complements depending on the magnitude of the elasticity of damage and (vi) an increase in the likelihood of the terrorist being weak reduces defense effort, may increase or decrease R&D depending on the magnitude of elasticity of damage but increases pre-emptive effort in both countries.