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.     

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.     

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).     

An intelligent adaptive system for the optimal variable selections of R&D and quality supply chains

The cost of research & development (R&D) and quality management are always regarded as two major parts of total cost. The variable performance of R&D and quality design is an important index that will reflect the effectiveness of the cost reduction. This research has attempted to simultaneously vary all of the variables to achieve the global optimum for the optimal variable selections of R&D and quality design. Genetic algorithm (GA) can treat all of the variables for the global search. In this study, fuzzy refinement with orthogonal arrays was effective in improving the performance of the GA, and also showed the benefits of a good chromosome structure on the behavior of GA. It is also proposed the postponement design with temporal concept, to select the effective variables for the cost reduction of R&D and quality management design. The experimental results showed that tempo-postponement design will increase the flexibility and quick response for supply chain management. Hence, this approach can act as a useful guideline for researchers working on the optimization of the key variable selections for R&D and quality model design.     

Dynamic R&D with strategic behavior

We consider a two-player infinite-horizon discrete-time game where the players invest in R&D in order to develop a new technology to reduce production costs. We compute firms’ equilibrium R&D investment strategy as a function of the level of knowledge in the economy. The latter changes endogenously with firms’ decisions to invest in R&D. We show that firms do not invest in R&D if the knowledge level is too low, while both firms do R&D when the level of knowledge is high. However, there is an intermediate knowledge region where there are two pure Nash equilibria: either no firm does R&D or both firms do R&D. Multiplicity of equilibria leads generally to a challenging selection problem. In our context, it is shown that the case of both firms investing in R&D can be Pareto-dominating for both players. It follows that government actions which allow an economy to increase the level of knowledge above a threshold may be welfare enhancing.     

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.      

Exploring core competencies for R&D technical professionals

In order to maintain technical competitiveness, companies have an ongoing need to identify and foster core competencies for technical professionals in the area of research and development (R&D). Exploring core competencies is, however, a qualitative problem. The rough set theory (RST), which has recently become well known as a data-mining technique, is a good tool for data reduction in qualitative analysis. Thus, the rough set approach is suitable for dealing with the problem of exploring competencies. This study extends practical applications of RST in mining the critical competencies for R&D technical professionals employed by semiconductor manufacturers in Taiwan. This paper demonstrates a successful reduction of the numerous essential competencies into a more compact set, and arrived at six core competencies which can be regarded as the as indispensable attributes for the design of competency development programs for R&D technical professionals.     

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.     

A semantic-based platform for R&D project funding management

Innovation is one of the keys to success in the business world, particularly within the current economic climate. R&D projects constitute the building blocks of the innovation process, hence the importance of searching for funding for these projects. As ontologies and semantic technologies mature, they provide a consistent and reliable means to represent and aggregate knowledge from different sources. The present work explores the use of ontologies to model R&D grant funding calls and the application of semantic technologies to the development of an enhanced funding management system. Our experiments confirm the success of the proposed approach, and reveal that it may bring considerable benefits to R&D funding.     

An Optimal Balanced Economic Growth and Abatement Pathway for China Under the Carbon Emissions Budget

Arguments over equity during abatement goal setting is the principal obstacle to climate mitigation cooperation, while allocating global emissions to each country as deduced from the climate objective according to certain equitable principles offers an effective alternative to ending this dispute. Such an alternative also endows each country with the freedom to determine and develop its own pathway under its emissions budget while ensuring that global climate targets are met. Within this context, this paper integrated economic growth theory with the optimal control model and simulated the optimal abatement pathway as well as the economic growth trajectory for China within the allocated emissions budget. The study found that research and development (R&D) investment is an effective way of improving energy efficiency. Our simulation showed that the R&D intensity of the gross domestic product (GDP) would see a slight decline for the inceptive period, followed by an aggressive rise to a relatively high level before decreasing again. Under the 450 ppm carbon concentration target, the R&D investment intensity would have to increase significantly beginning from 2014 because of the more stringent demands as compared to other less rigorous targets such as 500 ppm. The economy would continue to grow, although growth would occur less rapidly under rigorous targets: relative to 2007 levels, the GDP would grow by 11-fold and 15-fold under the 450 and 500 ppm scenarios, respectively. Before enforcement of an effective R&D investment, the carbon emissions would increase rapidly, while after enforcement, the speed of carbon emissions would slow down.     

Seven software engineering principles for autonomic computing development

The complexity of modern middleware and software solutions is growing at an exponential rate. Only self-managing, or autonomic computing technology can reasonably stem the confusion this complexity brings to bear on human administrators. While much has been published on “architecture” and “function” for producing such systems, little has been written about the engineering of self-managing systems as a distinct paradigm. In this short article we suggest a set of software engineering principles for engineering of autonomic systems that should guide the planning of autonomic systems and their interfaces, with the intent to guide the thinking of R&D organizations pursuing the development of autonomic computing capability.     

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.     

纵向研发合作的研发绩效和成本分担机制

在日益激烈的市场竞争环境下,企业往往会选择研发合作以降低研发的成本和风险,而纵向研发合作已成为其中的重要模式。构建了一个存在两个上游企业和多个下游企业所组成的复杂双层市场结构,对上下游企业实施纵向研发合作的产量变化和利润变化进行了分析,在此基础上探讨了研发合作的最优研发绩效。研究了纵向研发合作下利润匹配型和固定比例型两种分担机制的分担系数和净利润等经济指标,得出了一些符合现实经济活动的结论。     

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.     

Japanese activities of micromachine and its future prospects

 Every corner of advanced R&D seems to head toward micronization. Micronization research in mechanics started recently but an intensive and comprehensive approach has been taken since 1992 when both the government R&D project and Micromachine Center were initiated. Micromachine is a new technological paradigm and has the same potential benefit as today’s macromachine. Micromachine will take considerable time span to be completed for full-fledge application. Until then, a wide range of approaches, i.e. R&D, dissemination, international exchange are indispensable. Received: 22 October 1996 / Accepted: 28 October 1996     

Social networks and genetic algorithms to choose committees with independent members

Choosing committees with independent members in social networks can be regarded as a group selection problem where independence, as the main selection criterion, can be measured by the social distance between group members. Although there are many solutions for the group selection problem in social networks, such as target set selection or community detection, none of them have proposed an approach to select committee members based on independence as group performance measure. In this work, we propose a novel approach for independent node group selection in social networks. This approach defines an independence group function and a genetic algorithm in order to optimize it. We present a case study where we build a real social network with on-line available data extracted from a Research and Development (R&D) public agency, and then we compare selected groups with existing committees of the same agency. Results show that the proposed approach can generate committees that improve group independence compared with existing committees.     

Regional Specialisation for Technological Innovation in R&D Laboratories: A Strategic Perspective

The present paper attempts to highlight the strategy of regional specialisation for technological innovation in R&D laboratories. The paper makes a proposition that regional specialisation should be recognised as a strategic initiative for technology development in R&D laboratories. The rationale for this strategic initiative has been substantiated with the help of illustrations from the cases of technology development efforts taken up in different laboratories in the country under the Council of Scientific and Industrial Research (CSIR), India. In this direction, CSIR and other centres of excellence have played a pioneering role in the development of various industrial clusters and artisan concentrations in different parts of the country. The implications of adoption or otherwise of this strategy initiative for technological innovation in R&D laboratories have been discussed.     

A Neural Network Approach to Value R&D Compound American Exchange Option

Computational Economics - In this paper we show as the neural network methodology, coupled with the Least Squares Monte Carlo approach, can be very helpful in valuing R&D investment...     

A study on framework for effective R&D performance analysis of Korea using the Bayesian network and pairwise comparison of AHP

To effectively evaluate and analyze R&D performance, it is necessary to measure the relative importance of performance analysis factors and quantitative analysis methods that consider the objectivity and relevance of detail factors that constitute performance evaluation. This study suggests a framework for R&D performance evaluations by computing weights through an AHP (Analytical Hierarchy Process) expert survey and by applying a Bayesian Network approach whereby, through which, giving objectivity and allowing inference analyses. This framework can be used as a performance analysis indicator, which uses input and output performance factors in order to perform quantitative analysis for projects. We can quantitatively define the satisfactory level of each project and each performance analysis factor by assigning probability values. It is possible to analyze the relationship between project evaluation results (qualitative evaluation) and performance analysis indicator (quantitative performance). This performance analysis framework can infer posteriori probability using the prior probability and the likelihood function of each performance factor. In addition, by inferring the relationships among performance factors, it allows performing probability analyses on the successful and unsuccessful factors, which can provide further feedback. In conclusion, the framework would improve the national R&D program in terms of financial investment efficiency by aligning budget allocation and performance evaluation.     

Pop Up Play: a digital creative play space

This article discusses the research findings from a year-long investigation funded by a Digital R&D for the Arts grant. The overarching aims of this research project were to understand how arts and cultural organisations can access mixed-reality environments and digital technology for creative play and learning, and how they can enable children and young people to access meaningful digital realm engagement. The article starts by introducing the underlying philosophical and cognitive framework built from embodiment philosophy, gaming theory and digital pedagogy that helped the research team determine what was meant by meaningful engagement in mixed reality. This is woven into an analysis of the four action-research case studies, followed by a discussion on the potential future areas for investigation. The conclusion evaluates how the resultant Pop Up Play product (free software download, supporting materials and bespoke digital creative play framework http://thesparkarts.co.uk/popupplay/) can be considered an environment for communications skill development, innovative thinking and immersive exploration through experiential play.