• 대한산업공학회지
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• 제36권1호
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• pp.22-31
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• 2010

In R&D project evaluation, we consider the technical couple. And we set technology modular alternatives, after evaluating technical group based on technical couple. So we solve the problem extracted from existing research of R&D project evaluation. We use Conjoint Analysis(CA) for this research. CA is usually used for confirming customers' preference. However we use it for researchers' preference in the side of technology. This research is followed by the next 4 steps. (1) Hierarchical model of goal technology (2) Composition model of modular alternatives (3) Evaluation model of modular alternatives (4) Setting model of technology modular alternatives.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2001년도 추계학술대회 논문집
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• pp.242-245
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• 2001

This study is aimed to design a priority setting algorithm necessary for evaluating and selecting interdependent R&D planning system alternatives. In case that the relationship of technology alternatives is interdependent, a relative importance as occurrence or nonoccurrence of the technology alternatives viewed from the future time varies. So, we are subject to design the evaluation process considering a cross- impact of future technology alternatives. Thus, we apply the cross impact analysis (CIA) model to consider the cross-impact among interdependent system alternatives. Also, the analytic hierarchy process(AHP) model is applied to determine the priority of alternatives by taking the pair-wise comparison among factors.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2008년도 추계학술대회 및 정기총회
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• pp.440-443
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• 2008

In this research, we develop the model of selecting and setting technology modular alternatives. We compose the selecting process(CHP) after setting technology modular alternatives based on technical couple by Conjoint Analysis(CA). Through this process, we can have several advantages. (1) Increasing the accuracy of R&D project evaluation (2) Declining the load of pair-wise comparison

• 한국품질경영학회:학술대회논문집
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• 한국품질경영학회 2010년도 춘계학술대회
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• pp.386-389
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• 2010

In this research, we develop the model of selecting and setting technology modular alternatives. We compose the selecting process(CHP) after setting technology modular alternatives based on technical couple by Conjoint Analysis(CA). Through this process, we can have several advantages. (1) Increasing the accuracy of R&D project evaluation (2) Declining the load of pair-wise comparison.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2007년도 추계학술대회 및 정기총회
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• pp.152-155
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• 2007

The object of this research is to evaluate the priority of R&B project alternatives which were already screened by both feasibility and suitability of technological performance. This research is a selection model for R&D project alternatives after setting phase. And it is designed by CHP model which include individual and mutual weights. This model have 5 steps. (1) Setting Technology-Modules derived on the setting phase (2) Presenting the evaluation standards divided with 'M-Field' and 'T-Field' (3) Assessing the evaluation standard and technology modules (4) Obtaining and integrating the individually and mutually effective weights (5) Selecting the technology modules based on the priority of order by CHP. Through these steps, this model can suggest the evaluation way from specific technology levels to project level. And it can be guaranteed to perform the selected module set.

• 기술경영경제학회:학술대회논문집
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• 기술경영경제학회 2000년도 제17회 하계학술발표회 논문집
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• pp.35-46
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• 2000

The Analytic Hierarchy Process(AHP) model developed by Saaty is a very useful decision-making model designed for selecting and evaluating project alternatives through $\ulcorner$pairwise comparison$\lrcorner$ in the context of hierarchical structure. In this paper, we construct a modified AHP model named Analytic Dicho-Hierarchy Process (ADHP) model necessary for evaluating technology alternatives.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2000년도 춘계공동학술대회 논문집
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• pp.122-125
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• 2000

The Analytic Hierarchy Process (AHP), a decision making model, which is more applicable than other methods to R&D project selection, particularly when it is applied to intangibles. The objective of this paper is to develop an extended model of the AHP which Is linked to Cross Impact Analysis to assist in the ranking of a large number of technological alternatives. In this study, we developed a priority setting algorithm which considers the cross-impact of the future technology alternatives and thus developed an integrated cross-impact hierarchical decision-making model, which sets the priority by considering technological forecasting and technology dependency

• 기술혁신연구
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• 제13권1호
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• pp.25-54
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• 2005

In this study, priority setting model of new promising IT industries which will be the growth engines for the Korean IT industry, was established. Based on the AHP model, priority setting of IT new promising IT industries was conducted. Firstly, the selection cases of the new promising IT industries and major priority setting methodologies including the AHP methodology, were analyzed. The AHP model was selected as the most feasible methodology for priority setting of the new IT industries, among the various priority setting methodologies. Secondly, in setting up the AHP model for prioritization of the new promising If industries, a 'goal' was established to be priority setting of the new promising IT industries, and an 'alternatives' to be 18 new promising IT industries. Then a logical and a systematic assessment criteria including 5 main criteria('Technological Innovation', 'Market Ability', 'SPin-off Effect', 'Public Benefit', 'Strategic Importance') and 14 sub-criteria, were developed for priority setting of the 18 new promising industries. Finally, with the AHP model, the substantial analysis was made to set up priority of the 18 new promising IT industries. The substantial analysis showed the following priority setting results and implications for the 18 new promising IT industries.

• 한국경영과학회지
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• 제27권1호
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• pp.1-17
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• 2002

The objective of this paper is to develop a new priority setting algorithm that considers the cross-impact of the future technology alternatives and that satisfies the final goal of the technology management through multi-hierarchy evaluation criteria. By combining the Analytic Hierarchy Process (AHP) model, which is a well-known priority setting model, and Cross Impact Analysis (CIA) model, which is a technological forecasting method that considers cross-impact among R&D Items, we developed an Integrated Cross-Impact Hierarchical (CIH) model, which sets the priority by considering technological forecasting and technology dependency simultaneously. A step-by-step numerical example of the model developed here is presented as backup of its practicality.

• 기술혁신학회지
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• 제2권2호
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• pp.201-218
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• 1999

The article contains an introduction of possibility of applying Multi-Attribute Utility Theory(MAUT) for priority setting of R&D projects. MAUT is compared with AHP, which is widely used recently. These two techuiques are applied to set priorities of R&D projects In a Government-funded Research Institute. Six criteria are chosen from consultation with decision makers. They are composed of 1) validity as representative projects, 2) possibility of resource mobilization, 3) spillover effect of developed technologies, 4) possibility of success, 5) scope of participation and 6) clarity of research goal. To set priorities of R&D projects, SMART(Simple MultiAttribute Rating Technique) and DVM(Difference Value Measurement) out of many MAUT methods are used to design the utility function and to determine the weights among criteria. The aggregation model is additive on the assumption the criteria are independent. AHP executes pairwise comparisons for criteria and alternatives. From the results of the case study, the results and theoretical characteristics are compared.