• Management & Information Systems Review
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• v.19
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• pp.1-15
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• 2006

The concept of portfolio is rarely understood and used in R&D management field. The conventional management technique in selecting R&D projects is scoring each projects and choosing projects based on the scores which are determined during evaluation. As a collection of good stocks is not necessarily a good stock portfolio, a collection of good R&D projects is not always a good R&D project portfolio. In this paper, framework and practical technique for constructing a R&D project portfolio are introduced. This technique can be easily applied in private and plublic R&D institutes.

• Journal of information and communication convergence engineering
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• v.9 no.5
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• pp.491-499
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• 2011

In this paper, we offer a new strategic portfolio model for national IT R&D project selection in Korea. A risk and return (R-R) portfolio model was developed using an objectively quantified index on the two axes of risk and return, in order to select a strategic project and allocate resources in compliance with a national IT R&D strategy. We strategize using the R-R portfolio model to solve the non-strategy and subjectivity problems of the existing national R&D project selection model. We also use the quantified evaluation index of the IT technology road map (TRM) and the technical level reports (TLR) for the subjectivity of project selection, and try to discover the weights using the analytic hierarchy process (AHP). In addition, we intend to maximize the chance for a successful national IT R&D project, by selecting a strategic portfolio project and balancing the allocation of resources effectively and objectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.3
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• pp.501-509
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• 2011

In this paper, we offer a new strategic Portfolio Model for national IT R&D project selection in Korea. A risk and return (R-R) Portfolio Model was developed using an objectively quantified index on the two axes of risk and return, in order to select a strategic project and allocate resources in compliance with a national IT R&D strategy. We strategize using the R-R Portfolio Model to solve the non-strategy and subjectivity problems of the existing national R&D project selection Model. We also use the quantified evaluation index of the IT technology road map (TRM) and the technology level Survey (TLS) for the subjectivity of project selection, and try to discover the weights using the analytic hierarchy process (AHP). In addition, we intend to maximize the chance for a successful national IT R&D project, by selecting a strategic Portfolio project and balancing the allocation of resources effectively and objectively.

• Korean Management Science Review
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• v.25 no.1
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• pp.1-9
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• 2008

This paper investigates the R&D project portfolio selection problem. Despite its importance and impact on real world projects, there exist few practical techniques that help construct an non-dominated portfolio for a decision makers satisfaction. One of the difficulties constructing the portfolio is that such project portfolio problem is, in nature, a multi-attribute decision-making problem, which is an NP-hard class problem. This paper investigates the R&D project portfolio selection problem. Despite its importance and impact on real world projects, there exist few practical techniques that help construct an non-dominated portfolio for a decision makers satisfaction. One of the difficulties constructing the portfolio is that such project portfolio problem is, in nature, a multi-attribute decision-making problem, which is an NP-hard class problem. In order to obtain the non-dominated portfolio that a decision maker or a user is satisfied with, we devise a user-interface algorithm, in that the user provides the maximum/minimum input values for each project attribute. Then the system searches the non-dominated portfolio that satisfies all the given constraints if such a portfolio exists. The process that the user adjusts the maximum/minimum values on the basis of the portfolio found continues repeatedly until the user is optimally satisfied with. We illustrate the algorithm proposed, and the computational results show the efficacy of our procedure.

• Journal of Energy Engineering
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• v.29 no.3
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• pp.1-6
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• 2020

A portfolio matrix analysis was conducted to improve R&D productivity of the government-funded R&D projects in the energy sector. 27 projects (42 detailed technologies) in 2018 were evaluated on a 5-point scale in terms of availability and technology competitiveness, and portfolio matrix analysis was conducted twice. The results of the portfolio matrix analysis could provide the landscape of on-going R&D projects at a time and could be utilized as feedback data to establish development strategies for individual projects, while establishing differentiated management directions to improve R&D productivity in each of the four areas of the portfolio matrix.

• Korean Management Science Review
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• v.25 no.3
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• pp.59-72
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• 2008

This paper proposes an R&D opportunity scan framework for information and telecommunications company in aging society. The framework consists of trend analysis, market-oriented search, technology-oriented search, and R&D Portfolio development. We identify technology themes in the market-oriented search by developing market scenarios and analyzing a new business model framework. And then we search prospective technologies in the technology-oriented recess by technology scanning and patent analysis. By matching technology themes with prospective technologies, generate an R&D portfolio. Finally, we evaluate the risk of the proposed R&D portfolio.

• The Korean Journal of Financial Management
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• v.21 no.1
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• pp.87-124
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• 2004

Some studies indicate that investors systematically underreact to new information in the stock market and Other studies indicate that investors systematically overreact. If investors irrationally react to the R&D intensity information, The portfolio strategy based on the R&D intensity information will be provided substantial excess returns. This study investigate that investors systematically underreact or overreact to the R&D intensity and whether portfolio strategy based on the R&D intensity is useful or not. Major results we as follows. First, This study indicate that investor systematically underreact to high R&D intensity and overreact low R&D intensity information. Second, after controlling the firm's specific factor such as firm size, BV/MV and past price performance, it is found that the performance of portfolio strategy based on the R&D intensity is not significant.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2017.11a
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• pp.129-129
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• 2017

In planning and evaluating government R&D programs, one of the first steps is to understand the government's current R&D investment portfolio - which fields or topics the government is now investing in in R&D. Analysis methods of an investment portfolio of government R&D tend traditionally to rely on keyword searches or ad-hoc two-dimensional classifications. The main drawback of these approaches is their limited ability to account for the characteristics of the whole government investment in R&D and the role of individual R&D program in it, which tends to depend on the relationship with other programs. This paper suggests a new method for mapping and analyzing government investment in R&D using a combination of methods from natural language processing (NLP) and network analysis. The NLP enables us to build a network of government R&D programs whose links are defined as similarity in R&D topics. Then methods from network analysis show the characteristics of government investment in R&D, including major investment fields, unexplored topics, and key R&D programs which play a role like a hub or a bridge in the network of R&D programs, which are difficult to be identified by conventional methods. These insights can be utilized in planning a new R&D program, in reviewing its proposal, or in evaluating the performance of R&D programs. The utilized (filtered) Korean text corpus consists of hundreds of R&D program descriptions in the budget requests for fiscal year 2017 submitted by government departments to the Korean Ministry of Strategy and Finance.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2000.11a
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• pp.259-277
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• 2000

In this paper, we suggest theoretical grounds on the problem of R&D portfolio with different option premiums utilizing the Real Options Model, which has received intensified attention as the method of assessment of R&D project with high risk. Even though there have been many studies focused on the evaluation of option value of single project from technology valuation's perspective. there are few study on the portfolio of multiple technology investment by option value using. This paper bears practical importance by showing simple examples with the option value of investment alternatives and the valuation of related risk, the construction of optimum portfolio in technology investment alternatives.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.6
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• pp.677-682
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• 2018

The relationship-type research and development (R&D) portfolio is a method for selecting core technologies based on their unique purposes and characteristics when the criteria for selecting them are independent. This study presents a relationship-type R&D portfolio method as a way to derive core technologies, and describes the methodology by dividing it into three steps: 1) analyze the relationships between selection criteria and analytical indicators, 2) form a portfolio matrix that best matches each selection criteria, and 3) derive the core technologies. In this study, the relationships between four selection criteria for selecting core technologies and the analytical indicators for identifying the technology level, economics, and the technology itself, are written in a table with HoQ. Based on the relationship table, analytical indicators to be considered were derived to satisfy each selection criterion, and the derived analytical indicators and the selected technologies were constructed with two axes in the portfolio matrix. The satisfied portfolio, P0, that satisfies all four criteria, and the portfolio, P1~P4, that satisfies selection criteria based on the unique characteristics of the four criteria, were constructed, and core technologies derived. The selected core technologies can be utilized in selecting a core area against the future security environment through a process like key word analysis based on the specifications.