Robust Monte Carlo Method for R&D Real Options Valuation

This paper is devoted to developing a robust numerical analysis of least squares Monte Carlo (LSM) in valuing R&D investment opportunities. As it is well known, R&D projects are characterized by sequential investments and therefore they can be considered as compound options involving a set of interacting American-type options. The basic Monte Carlo simulation takes a long time and it is computationally intensive and inefficient. In this context, LSM method is a powerful and flexible tool for capital budgeting decisions and for valuing R&D investments. In particular way, numerical tests are performed to examine the optimal choice of basis function and polynomial degree in terms of reduction of the execution time, accuracy and improvement in the simulation.     

Valuation of R&;D Sequential Exchange Options Using Monte Carlo Approach

This article describes a methodology for evaluating R&D investment projects using Monte Carlo method. R&D projects generally involve multiple phases with or without overlapping. R&D investments are made often in a phased manner, with the commencement of subsequent phase being dependent on the successful completion of the preceding phase. This is known as sequential investment. Moreover, each stage creates an opportunity (option) for subsequent investment. Therefore, R&D projects can be considered as ‘Compound Options’ in which investments present uncertainty both in the gross project value and in their costs. It is possible to use exchange options to value the R&D investment opportunities. In this paper, we propose to evaluate the European and American Real Compound exchange options through Monte Carlo simulations. We also provide a set of numerical experiments to provide evidence for the accuracy of the proposed methodology.      

Innovation systems in Malaysia: a perspective of university—industry R&D collaboration

Collaborative research and development (R&D) activities between public universities and industry are of importance for the sustainable development of the innovation ecosystem. However, policymakers especially in developing countries show little knowledge on the issues. In this paper, we analyse the level of university–industry collaboration in Malaysia. We further examine the fundamental conditions that hinder university–industry collaboration despite the government’s initiatives to improve such linkages. We show that the low collaboration  is a result of an R&D gap between the entities. While the universities engage in basic and fundamental R&D, the private sectors involved in incremental innovation that requires less R&D investments. The different nature of the industries’ R&D requires closer cooperation between firms namely buyers, suppliers and technical service providers and not the universities. Among others, the lack of an intermediary role, absorptive capacity and collaborative initiative by the industry also contribute to the problem. The study suggests that the collaborative activities can benefit both if deliberate and effective efforts on reducing the R&D mismatch are made between the universities and industry. Likewise, proper institutional arrangements in coordinating these activities are required. This result seems to reflect the nature of many developing countries’ national innovation systems, and therefore, lessons from Malaysia may serve as a good case study.     

How Should the Chinese Government Invest R&D Funds: Enterprises or Institutions?

With the rapid increase of the government R&D investment in China, the efficient optimization of the R&D investment areas of the Chinese government significantly influences regional innovation productivity and economic growth in the long run. By expanding the R&D-based growth model and using empirical analysis, this paper discusses the optimal combination for the government to coordinate its R&D expenditure as productive public investment in various sectors, under the condition of promoting long-term economic growth, is discussed by considering the aspects of capability for independent innovation, the development capability for basic knowledge, and the absorption capability for the technique. Results are as follows. (1) The level of production efficiency of enterprises, such as the capability for independent innovation, the development capability for basic knowledge, and absorption capability, influences the inclination of the government to invest in enterprises and institutions. When an enterprise has a high production efficiency level, technological level A, and knowledge storage B, increased investment from institutions to the enterprise can significantly promote regional economy growth. Otherwise, the government should increase R&D investment in institutions. (2) The government R&D investment in institutions can indirectly promote economic growth through the promotion of human capital and the understanding and absorption capacity of external knowledge, independent innovation capability, and basic knowledge development capability of enterprises. This paper may help the government to create appropriate policies with higher efficiency in R&D investment, and promote technical progress and economic growth in China.     

Developing an research and development (R&D) process improvement system to simulate the performance of R&D activities

Because of a shorter R&D cycle time and the increasing complexity of technology development, efficient decision support systems for R&D activities are necessary to facilitate R&D processes. In particular, small and medium enterprises (SMEs) require efficiency of R&D projects due to a lack of R&D budgets and resources. Therefore, this paper aims to develop a system which can assess current levels of R&D processes of companies and improve problematic processes. To this end, the proposed system applies a standard R&D process to evaluate the R&D level of companies, including four types of database and three modules: performance level analysis, comparison analysis, and performance simulation analysis. First, the module of performance level analysis aims to draw strong and weak R&D processes of companies, using three factors: importance, performance goal and current performance on each process. The second module provides the function of comparison analysis that compares the performance level of a company with that of others. Finally, the performance simulation analysis investigates influences of critical processes on R&D outcomes and predicts how much the processes can enhance technical, economic and process outcomes. In particular, a case study is presented to illustrate the application of the proposed system to an IT company. This system can help managers enhance their R&D performance by presenting necessary improvements on critical processes.     

Finding research trend of convergence technology based on Korean R&D network

Traditionally, collaboration network or citation network is used to answer the old question how scientists or engineers interact with each other. This paper introduces a R&D network to make up the missing aspect of the traditional approaches about using multi-sources and to find out the trend of convergence technology R&D in Korea. We collect data about human resources and national R&D projects from Korean national R&D databases, and then construct a weighted network between experts by using meta-data mapping and the network folding technique. And we apply Newman’s grouping algorithm that is generalized to a weighted network for detecting the community structure of the network. Gathering data from multi-sources is useful to reveal the structure of network rather than to use only one database. Lastly, we perform a network analysis to examine important experts. The result shows significant information about research trend and core experts in Korea. We expect this study will be helpful in three ways: (1) how to make a network from heterogeneous multi-sources, (2) how to figure out the current situation of convergence technology R&D, (3) how to discover who are important people in Korean convergence technology R&D network. And this paper is just a cornerstone of the work to investigate the current situation of national R&D projects in Korea.     

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.     

Consumer driven product technology function deployment using social media and patent mining

The capability of identifying real-time customer needs is critical for manufacturers that provide short life cycle consumer products such as smart phones. Companies need to form research and development (R&D) strategies to improve key functional features for short lifespan products to reflect the adoption of innovative technologies and changing customer expectations. With the pervasive use of the Internet, this research crawls and analyzes the online voice of customers (VoC), overcoming the time lag of offline surveys, to identify and prioritize product functions for deployment using extended quality function deployment (eQFD) models. In this research, the novel analytics of the manufacturer’s patent portfolio is added as an additional eQFD dimension to map ranked functional improvements to a manufacturer’s R&D capabilities. Thus, a computer supported eQFD system is developed to perform the unique mappings and gap analyses between the VoC, the prioritized product functions, and the manufacturer’s patent portfolio. The newly developed eQFD methodology and its novel discoveries are demonstrated in detail using a case study of three smart phones launched during the same time frame. The products include the Samsung Galaxy S7, the Huawei Honor 5X, and the ASUS Zenfone 3. The newly developed methodology is generally applicable to support VoC-centric product function deployment and R&D strategic planning in other domains.     

A milp bi-objective model for static portfolio selection of R&;D projects with synergies

This paper presents a multi-objective MILP model for portfolio selection of research and development (R&D) projects with synergies. The proposed model incorporates information about the funds assigned to different activities as well as about synergies between projects at the activity and project level. The latter aspects are predominant in the context of portfolio selection of R&D projects in public organizations. Previous works on portfolio selection of R&D projects considered interdependencies mainly at the project level. In a few works considering activity level information the models and solution techniques were restricted to problems with a few projects. We study a generalization of our previous model and show that incorporating interdependencies and activity funding information is useful for obtaining portfolios with better quality. Numerical results are presented to demonstrate the efficiency of the proposed approach for large models.     

Application of factor analysis for service R&D classification: A case study on the Korean ICT industry

This paper introduces an application of factor analysis for classifying and illuminating the nature of distinct dimensions of service research and development (R&D) which are difficult to examine due to the unique characteristics of services. The application is based upon the concept that firms would benefit from clarifying R&D and R&D-like activities to assist their R&D decision. Using principal component analysis (PCA) of factor analysis, a number of possibly correlated R&D activities is transformed into a smaller number of uncorrelated activities called principal components, and firms can identify the patterns of service R&D, express their similarities and differences, and develop its R&D portfolio. A case example for service R&D in the Korean ICT industry is provided.     

Knowledge kanban system for virtual research and development

Virtual research and development (R&D) is inevitable to reduce the product life cycle. Enterprises tend to rely on their foreign partners for supporting technology and knowledge acquisition to conduct and improve firms’ product development with low R&D risk. R&D is a highly creative and knowledge-intensive activity, Therefore, efficient knowledge flow, which transmits the right knowledge to the right people at the right time, is key to improving efficiency of the R&D process.     

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).     

How Imitations Impact on R&D Behaviors

I. INTRODUCTION Technology innovations are important for firms to compete in the market, whereas spillovers of research knowledge are unavoidable. Arrow (1962) has argued that technologies have some public good characteristics. Moreover, rival firms are able to access and copy new innovations through industrial espionage and reverse engineering, and are thus able to eat into monopoly profits of innovators. While patents are designed to provide protection to inventors, they provide only im…     

基于R&D溢出的集中研发联盟合作行为

研究了在联盟合作R&D中R&D溢出、R&D溢出的抑制能力以及创新能力对联盟成员的R&D投资策略的影响, 确定了联盟获得最大期望投入的最优分配方式. 研究表明: 1) R&D溢出和创新能力对联盟成员增加R&D投入有正效应; 企业抑制R&D溢出的力量对R&D投入有负效应, 但影响力很弱. 2) 对于创新能力强的联盟, 平均分配为最优分配方式; 对于创新能力弱的联盟, 市场规模低时选择按投入比例分配方式, 市场规模高时选择平均分配方式.     

Monopolistic competition model: The impact of technological innovation on equilibrium and social optimality

This paper considers a monopolistic competition model with the endogenous choice of technology in the closed economy case. Our aim is to obtain the comparative statics of the equilibrium and socially optimal solutions with respect to the technological innovation parameter that affects costs. The key findings are the following: consumption and investments in productivity both increase with the growth of technological innovation; the behavior of the equilibrium variables depends on the elasticity of demand only; the behavior of the socially optimal variables depends on the elasticity of utility only; finally, the behavior of the equilibrium and socially optimal variables does not depend on the properties of the costs as a function of investments in R&D.     

The impact of connecting with Professional Virtual Forum,team member and external person on R&D employee creativity

Accessing external knowledge is an important part of work for Research and Development (R&D) employees to get high creative performance. Currently, Professional Virtual Forum (PVF) in internet is becoming an important virtual knowledge source for R&D employees. However, up to now the impact of R&D employees’ connect with PVF on their creativity still waits to be explored. Furthermore, the interactive effects of connect with PVF and person-to-person knowledge sources on creativity are not clear. This paper empirically studied the 163 R&D employees came from 16 companies in China, and the results turned out that the R&D employees’ frequency of connect with PVF and intra-team, as well as with external person all significantly improved their creativity. Frequency of connect with PVF moderated the relationship between centrality of intra-team knowledge network and employee creativity, in such that when the frequency of connect with PVF was higher, the positive influence of centrality of intra-team knowledge network on employee creativity was also higher. Suggestions for future study on PVF and creativity are discussed.     

The role of R&D and corporate governance in Korea: IT firms versus non-IT firms

Recent economic development in Korea was mostly driven by companies in the IT sector. Also, it is widely argued that R&D investment has a positive impact on firm value, especially for IT firms. In this paper, we analyze how R&D investment has contributed to the growth of Korea’s economy by examining the effect of R&D investment on firms’ market value, measured as Tobin’s Q, and investigate whether this effect is different between firms in the IT sector and firms in the non-IT sector. We also account for the effect of another major change experienced by Korean firms: changes in corporate governance structure. We find that for firms in the IT industry, higher R&D investment coupled with high foreign ownership results in higher firm valuation.     

Organizing Pharmaceutical Innovation: From Science‐based Knowledge Creators to Drug‐oriented Knowledge Brokers

The pharmaceutical industry is exposed to severe conditions: while a typical R&D process lasts up to 13 years, only one out of 10,000 substances becomes a marketable product. In addition, markets for pharmaceutical products tend to become more fragmented, leading to an increased risk of market failure. At the same time, R&D productivity has been deteriorating for several years. The number of new drug approvals is constantly declining, while R&D expenditures are escalating as a result of high investments in new drug discovery technologies and more complex clinical studies. As a response, pharmaceutical firms have started to focus on balancing the right size and structure of their R&D activities. This leads to several organizational trends: (1) novel management of technologies; (2) R&D internationalization; and (3) open innovation modes.     

Structural effects of R&D collaboration network on knowledge diffusion performance

With the advent of knowledge-based economy, the process and structure of knowledge diffusion mechanism in R&D collaboration networks have become more complex and dynamic. However, regardless of the complexity and importance of these R&D collaboration networks, previous empirical analyses have focused mainly on statics, which cannot be a sufficient basis to thoroughly explore knowledge diffusion in the R&D collaboration network. Furthermore, there has been little research done on the relationship between knowledge diffusion and the structure of an R&D collaboration network. Hence, this paper modeled knowledge diffusion based on social network analysis. It also investigated the impact of network structure on the performance of knowledge diffusion, focusing on average knowledge stock and knowledge variance. The results confirm that the small-world network is the most efficient and equitable structure toward effective knowledge diffusion.     

Real Options and Incremental Search in Pharmaceutical R&D Project Portfolio Management

This paper investigates the role of real options reasoning in R&D project portfolio management and investment decisions of pharmaceutical firms. We analyse a unique dataset that integrates information on initiation and termination of clinical trials at the level of specific medical indications. Consistent with existing literature, we find a positive relationship between market size and firm entry in clinical trials. We also show that the option value of R&D investments, as proxied by the scope of R&D projects, affects the selection of target markets. Moreover, high‐risk research areas attract more entry, in line with the predictions of real options theory. However, we also find that more flexibility in project duration and delayed project discontinuation attract higher rates of entry. Departures from pure real options reasoning are motivated by the presence of incremental learning in pharmaceutical R&D.