• Asian Journal of Innovation and Policy
• /
• v.6 no.1
• /
• pp.45-57
• /
• 2017

This study aims to analyze the factors that could influence business decisions of in the commercialization of R&D when technology is transferred from government research institutes (GRIs) to small and medium-sized enterprises (SMEs). We examine 353 such cases of technology transfer. The dependent variable is whether the licensee had the intention of following up with R&D after the technology has been transferred. The independent variables, classified into ex-ante factors and ex-post factors, consist of the involvement of SMEs into GRI R&D, technology readiness level, relatedness to existing technologies, and contribution to sales revenue and level-up of existing technologies. The results of the study show that the contribution to existing technologies has a positive impact on R&D commercialization. However, unlike our expectation, contribution to sales revenue, the involvement of SMEs into GRI R&D, technology readiness level, the relatedness to existing technologies of the technology transferred have no impact on follow-up R&D.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.13 no.6
• /
• pp.191-198
• /
• 2018

Technology transferors and technology transferees decide to transfer technology with various motivations as they share benefits and risks. On top of economic benefit factors and risk factors provided by technology transferees, technology transferors also make technology transfer decisions by taking into account various factors such as government policies and systems, as well as their management strategies. In this study, the factors influencing the technology transfer in the chemical industry and the influence on the technology transfer intention are analysed. As a result of this study, factors influencing technology transfer are economic benefit factor, technological factor, risk factor, and socio-cultural factor. A significant differences in the influencing factors between the technology transferors and the technology transferees are that the economic benefit factors are more considered by the technology transferees and the technological factors are more considered by technology transferors in technology transfer. Technology transferees shows the stronger intention to enter technology transfer than the technology transferors.

• Asian Journal of Innovation and Policy
• /
• v.6 no.3
• /
• pp.354-378
• /
• 2017

Global research and development (R&D) spending has increased in recent years as the need for new technologies has grown and structural changes in the market have become evident. R&D and its transfer into the commercial sector have an important relationship. This paper analyzes the relationship between industrial R&D expenditure and how it affects technology transfer in Malaysia, Singapore and Taiwan. The research is based on the analysis of secondary data from published annual reports followed by a quantitative analysis of primary data using survey questionnaires. The research finds that the bulk of R&D expenditure was from the top ten organizations and the top five industries for each country. The findings also reveal that an organization's readiness in terms of technology and people capabilities is still weak in Malaysia and Singapore. The findings also indicate that there is a relationship between industrial R&D expenditure and the propensity of technology transfer in Taiwan.

• Journal of Power System Engineering
• /
• v.20 no.2
• /
• pp.5-16
• /
• 2016

Generally, methods using transfer techniques, like the transfer matrix method and the transfer stiffness coefficient method, find natural frequencies using the sign change of frequency determinants in searching frequency region. However, these methods may omit some natural frequencies when the initial frequency interval is large. The Sylvester-transfer stiffness coefficient method ("S-TSCM") can always obtain all natural frequencies in the searching frequency region even though the initial frequency interval is large. Because the S-TSCM obtain natural frequencies using the number of natural frequencies existing under a searching frequency. In this paper, the algorithm for the free vibration analysis of axisymmetric conical shells was formulated with S-TSCM. The effectiveness of S-TSCM was verified by comparing numerical results of S-TSCM with those of other methods when analyzing free vibration in two computational models: a truncated conical shell and a complete (not truncated) conical shell.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.18 no.3
• /
• pp.478-484
• /
• 2017

This study analyzed statistically the determinants that affect the royalties of knowledge technology transfer, which accounts for a considerable portion of university technology transfer. As knowledge technology transfer certainly includes a move from tacit knowledge from one side to the other side per se, the scope of knowledge technology transfer is unclear and numerical information of technology transfer, such as research fund scale, which is used widely in previous studies, cannot be used in the analysis. Therefore, this study focused on the researcher characteristics and included its explanatory variables in the present study. In addition, it included the technical characteristics of the knowledge transferred and the characteristics of the contracting company. The knowledge maturity calculated from the appointment year and contract date positively affects the technology royalties, but work experience and patent activity of the researcher are not statistically significant. Statistically significant differences in the technology royalty according to the type of technology transfer and the company location were observed, but there was no meaningful change in the technology royalty depending on the technical field and company business scale.

• Management Science and Financial Engineering
• /
• v.10 no.1
• /
• pp.43-52
• /
• 2004

This paper empirically investigates potential factors that might affect firms' incentives to license out technology. The analysis is done with the help of a panel data set of observed licensing transactions involving U.S. public companies in high-technology industries. The important explanatory factors relate to the firm characteristics such as the company's stock of technological knowledge (patent stock). prior involvement in technology licensing. the company size, R&D intensity and capital expenditure. The results suggest that there seems to be significant inter-sectoral differences as well as similarities in determinants of the propensity to transfer technology through licensing agreements.

• The Journal of Asian Finance, Economics and Business
• /
• v.6 no.4
• /
• pp.271-279
• /
• 2019

The purpose of this study is to identify the barriers of university and industry cooperation and to develop recommendations for the internal ecosystem of technology commercialization. The research method used is a survey of three categories of experts from 9 universities of Almaty (researchers, technology transfer managers, spin-off-owners). Despite the strong efforts of the government of Kazakhstan in building innovation infrastructure, there is a low level of innovation activity, less than 5% of university inventions are transferred into the industry. The results of the expert survey showed that the main barriers for cooperation between university and industry are: lack of resources to build university-industry links, lack of time due to high teaching load, poor qualification of technology transfer managers and lack of networking with industry. Based on the results of the expert survey, it is proposed to develop the ecosystem for the commercialization of university-based technologies, for which the following economic activities are important: human resources, financing, intellectual property management system, and intermediary infrastructure. The results of this study can be applied in developing the strategies and policies for universities, public research organizations, as well as for national R&D and higher education policies.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.2
• /
• pp.851-860
• /
• 2021

The Knowledge Transfer (KT) for higher education institutions (HEIs) is boundless. Still and all, the members of the staff affiliated with these institutions do recognize an array of hitches in relation to KT practices. The study in question underscores social interactions, training, and Information and Communication Technology (ICT) as the primary barriers and treats them as the independent variables of the study. The study posits that inadequate management of the above-mentioned barriers would impact effective KT unfavorably. Besides, putting forth some striking solutions needed to fix the obstructions that hamper the adequate management of the KT exercises is another aim of the study. For data collection purposes, the study picks out higher education institutions (public) of the Quetta district. The reckoned sample size is 317 subjects. The research type that has been used is cross-sectional research and, in this context, the cross-sectional explanatory sequential design has been used. Concerning the findings of the paper, the results of PLS-SEM show positive and significant relationships of social interaction and training with knowledge transfer, while ICT shows an insignificant positive relationship with the knowledge transfer. The most influencing factor for the knowledge transfer is social interaction as suggested by social interaction theory.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.27 no.1
• /
• pp.75-94
• /
• 2002

The development of Information technologies huts contributed on-line training as one of important education methods. On-line training In firms, which is similar to e-learning or virtual education, provides trainees with more education opportunities in diverse ways. It has developed a range of innovative services with an one-stop solution of education within the electronic sector. Also under the on-line training environment, trainees can undertake customized training packages at anytime and any places. Moreover, information technology allows both the trainers and other trainees to be decoupled in any of the elements of time, place, and space. Two research questions are investigated : what are the determinants affecting the on-line training effectiveness and how those variables effect the two aspects of training effectiveness: learning performance and transfer performance. Based on the previous literature conducted on the traditional training environment, the determinants of training effectiveness are derived. light hypotheses are developed based on literature reviews and tested by questionnaires survey data. The collected data have been analyzed by LISREL. It is found that the relationship between individual, organizational and on-line sloe design variables and training effectiveness (learning and transfer) are significant. The contribution and limitations of this research are also discussed tilth future studies.

• Journal of Korea Technology Innovation Society
• /
• v.19 no.2
• /
• pp.254-279
• /
• 2016

Recently, with the conversion towards knowledge-based economy era, the importance of the evaluation for patent valuation has been growing rapidly because technology transactions are increasing with the purpose of practically utilizing R&D outcomes such as technology commercialization and technology transfer. Nevertheless, there is a lack of research on determinants of patent valuation by analyzing technology transactions due to the difficulty of collecting data in practice. Hence, to suggest quantitative determinants for the patent valuation which could be applied to scoring methods, 15 patent valuation models domestically and overseas are analysed in order to assure the objectiveness for subjective results from qualitative methods such as expert surveys, comparison assessment, etc. Through this analysis, the important 6 common determinants are drawn and patent information is matched which can be used as proxy variables of individual determinant factors by advanced researches. In addition, to validate whether the model proposed has a statistically meaningful effect, total 517 technology transactions are collected from both public and private technology transaction offices and analysed by multiple regression analysis, which led to significant patent determinant factors in deciding its value. As a result, it is herein presented that patent connectivity(number of literature cited) and commercialization stage in market influence significantly on patent valuation. The meaning of this study is in that it suggests the significant quantitative determinants of patent valuation based on the technology transactions data in practice, and if research results by industry are systematically verified through seamless collection of transaction data and their monitoring, we would propose the customized patent valuation model by industry which is applicable for both strategic planning of patent registration and achievement assessment of research projects (with representative patents).