Keuntae Cho

A loss function approach to group preference aggregation in the AHP

The Analytic Hierarchy Process is a useful method in aggregating group preference. However, judgments are frequently inconsistent, and, in reality, pairwise comparison matrices rarely satisfy the inconsistency criterion. In this situation, we suggest a new method, called a loss function approach, that uses inconsistency ratio as the group evaluation quality. For this method in detail, we introduce Taguchis loss function. We also develop an evaluation reliability function to derive group weight. Finally, we provide a step-by-step numerical example of a loss function approach.

Hierarchies with dependence of technological alternatives: A cross-impact hierarchy process

Abstract The analytic hierarchy process (AHP), a well-known and useful decision making tool, has been applied to R&D project selection. The objective of this paper is to develop an extended model of the AHP which is linked to cross-impact analysis, called a cross-impact hierarchy process (CHP), to assist in the ranking of a large number of dependent technological alternatives. In reality, dependence with respect to such factors as cost, technology, and positive synergy may exist among R&D projects. For example, a specific R&D project can occur either prior to or after the anticipated time, because it may be affected by the occurrence of other projects. In that case, cross-impacts that imply mutual influences among R&D projects need to be considered and evaluated. As a way to capture their cross-impacts in this study, we think about the future occurrence probability of each project. A step-by-step numerical example of the CHP is also presented.

Determinants of successful technology commercialization: implication for Korean Government-sponsored SMEs

Technology commercialization is an essential step for profiting from technological innovation. The Korean Government has supported technology commercialization; however, previous studies have provided limited empirical evidence on the effect of government support. This study examines the various factors that influence the commercialization strategy and performance of firms. It also identifies the determinants of successful technology commercialization and effective government programmes for commercialization performance by analysing the performance of Korean Government-sponsored firms. The results show that the determinants influence commercialization by firms according to the firm size and the degree of Korean Government support. The appropriability, innovative capabilities and investment in external R&D have significantly positive impacts on SME commercialization. This study provides empirical evidence on the effects of government support and contributes to the formulation of commercialization strategies and improved SME commercialization policy for firms.

The effect of research and development investment and desorptive capacity on firm performance

This research aims to investigate the effect of research and development (R&D) investment on firm performance contingent on desorptive capacity (DC). The structural equation model was used to examine the mediating, independent, moderating, and spurious effects of DC. The empirical results showed that Korean firms’ R&D investment has a positive impact on the firm performance. DC was also found to be a significant variable, which moderates the relation between R&D investment and firm performance. Thus, this study concludes that the increase in R&D investment alone is not sufficient to improve the firm performance which in turn highlights the complementary role of desorptive capacity.

Proposing a portfolio model for performance management of Korea's Health Technology R&D Programme using DEA and MPI: a translational research case

Recently, the importance of health technology related to human life and health has increasingly grown due to population ageing and desired improvements in the quality of life. The Korean government has been continuously increasing its strategic R&D investments through the Health Technology R&D Programme. Therefore, there is a growing interest in the efficiency of public R&D investments. This paper measures and compares the changes in both efficiency and productivity over time, analyses the cause leading to changes in productivity, and proposes a strategic portfolio model for managing the performance of the Translational Research Programme by using data envelopment analysis and Malmquist productivity index. The results conveyed that the productivity of six diseases, among 12 highly efficient diseases, was increased while the productivity of the remaining six diseases was decreased. On the other hand, the productivity of six diseases was increased, among nine low-efficient diseases, even though the relative efficiency was low. Finally, it is important to manage an R&D programme considering the two aspects together: producing higher performance with the given inputs and continuously improving productivity over time. These results are expected to have implications for policy in terms of effective performance management with regard to national R&D programmes.

Towards Measuring Competitiveness : A Management of Technology Approach

Abstract This study aims to develop a framework to measure MOT competiti veness of enterprises while proposing a concept called management of technology competitiveness (MOTC). The framework of MOTC based on both resource-based view and competence-based view is consisted of technology compe titiveness and management competitiveness. A variety of metrics to measure MOTC are extracted through substa ntial literature review. As technology competitiveness metric, this study examines RD as metric of manag ement competitiveness, leadership competitiveness, maturity of the R&D systems, collaboration and partnership, learning and innovation, and commercialization are considered. We then confirm and derive the multi-dimensions of MOTC through its reliability and validity analysis. The study is expected to provide useful guidelines and references for enterprises’ self-evaluation of technology and management competitiveness that is equally applicable to small, medium, and large enterprises that must compete in the global marketplace.

An estimation model for completion times considering the time interval between interdependent R&D events

Abstract Cross Impact Analysis(CIA) as a means of technological forecasting has a critical weakness in that it does not reflect the time impact on forecast events. The objective of this research is to modify the current Cross Impact Analysis and to develop a new model which estimates the impact of time on the completion of R&D events when the interdependency between the events are considered.

Relationships among international joint research, knowledge diffusion, and science convergence: the case of secondary batteries and fuel cells

ABSTRACT Recently, innovation through convergence is being conducted actively. Therefore, understanding the process of facilitating convergence is very important for innovation. According to some studies, diffusion is a factor promoting convergence, and is affected by international joint research (IJR) networks. The objective of this study is to investigate the relationships among IJR networks, knowledge diffusion, and science convergence. For this purpose, we used network analysis and regression analysis, based on scientometric analysis in the fields of lithium ion batteries and fuel cells. The results are as follows. First, institutes with high centrality in IJR networks are more likely to be early adopters, and IJR networks in which knowledge is diffused are scale-free. Second, knowledge diffusion is an important factor in promoting science convergence. This study is significant as it determines that knowledge diffusion may significantly help increase science convergence and IJR networks, one of the major sources of innovative technologies.

A methodology for forecasting future completion times of interdependent R&D events

In the current borderless and unlimited competition age, technological forecasting activities in both company and national level are mandatory for taking the competitive advantage through the strengthening of technology power and creating the market opportunity. These activities which are trying to forecast the future behaviours of complex technology events or R&D events are to try to understand the underlying causal processes which relate the components of the system to each other, and to determine the behavioural consequences of the causal structure. The objective of this research is to develop a model which estimates time impact, the impact on the completion times of R&D events as the interdependency between the events are considered.