• International Commerce and Information Review
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• v.10 no.2
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• pp.141-164
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• 2008

This study aims to come up with the elements that have influence on the outcomes of technology transfer in a multi-divisional way by making analysis of the interactive relations among technology transfer factor, technology transfer procedure factors, and technology transfer outcome factors through the Structural Equation Model(SEM). And the sample companies are restricted to the ones that have the records of technology transfer to China for the past five years For research model, technology success factor model of Choi and Lee (2000) and technology receptive capability and technology transfer outcome model of Lin, Tan and Chang(2002) were adopted. The research model was divided into an external variable, technology transfer factors and an internal variables, technology transfer procedure factors and technology transfer outcome factors. Research hypothesis was divided into technology transfer factors and technology transfer procedure factors; and technology transfer outcomes. As a result of analysis, cultural difference associated with technology transfer, technological type, corporate capability, and mutual trust have an effect on the outcomes of technology transfer.

• The Journal of Information Systems
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• v.15 no.1
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• pp.191-213
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• 2006

The purpose of this research is to identify the structure among determining factors focusing on knowledge transfer and analyze and prove the causal relation on knowledge transfer in Korean companies and public corporations. The results from the analysis of data collected in this study are as follows. First, forum among organization related factors has the positive relation with uncertainty in a significant level. Second, the higher the knowledge presentation and the ease of use are among information systems related factors, the lower the ambiguity and uncertainty are. Third, among process related factors, unification has the negative relation with ambiguity and uncertainty in a significant level. Fourth, a better manpower employment contributes to a worse ambiguity and uncertainty. Fifth, ambiguity has a negative relation with knowledge transfer. In conclusion, the factors that lower the ambiguity and facilitate knowledge transfer include information systems, unification, and manpower employment. These factors, however, influence on uncertainty, which turns out to be nothing to do with knowledge transfer.

• Journal of the Ergonomics Society of Korea
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• v.33 no.1
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• pp.49-58
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• 2014

Objective: The aim of this study is to enhance the efficiency of education and training through application and management of 'Transfer of Training' in nuclear power plants. Background: Despite the sophistication and standardization of job-related skills and techniques of workers, accidents/incidents keep taking place due to human errors and unsafe actions and behaviors, which translates into the necessity to review and examine the effectiveness and influence of education and training on the workers of nuclear power plants. Method/Results: This study drew the factors of 'Transfer of Training' through a review on the preceding studies and document research. In addition, through expert examination, this study explored the expected effects and possibility of application when managing the influencing factors of 'Transfer of Training' in nuclear power plants. And lastly, management priority order for nuclear power plants was drawn through an AHP analysis. Conclusion: Among the 'Transfer of Training' factors, the training design factor was the most important. In addition, the design of the training and transfer and goal setting showed a high degree of importance among the influencing factors. Application: The management of 'Transfer of Training' in nuclear power plants enhances the capability of workers and improves the operational integrity of nuclear power plants.

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

• Journal of Distribution Science
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• v.12 no.1
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• pp.35-46
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• 2014

Purpose - This Study aims to promote technology transfer commercialization and ultimately make contribution towards enhancement of the success rate of commercialization of technology transfer at national level by deducing the factors that impart influence on the negotiation at the time of technology trading between the seller and buyer of technology of public research institutions subjected to transfer and sales. Research design, data and methodology - This Study deduced 5 research hypotheses through preceding researches related to technology transfer commercialization related technology marketing for technology trading negotiation. This Study was conducted by verifying the hypotheses through multiple regression analysis. Results - As the result of the Study, the research hypothesis H1, 'Promotion of commercialization of technology transfer trading will be affected in accordance with the innate characteristic factors of the technology', and H5, 'Promotion of commercialization of technology transfer trading will be affected in accordance with the mutual factors of the parties of the technology trading', among the 5 research hypotheses were chosen. Conclusions - It was found that the technology seller must be able to demonstrate technological value of the technology being sold in order to successfully conclude technology transfer trading negotiation and mutual understanding and harmonious communication between the parties.

• Asia pacific journal of information systems
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• v.10 no.4
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• pp.57-75
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• 2000

Most current literature on knowledge and technology transfer(Appropriability Model, Dissemination Model, and Knowledge Utilization Model), describe the process of transfer in details, but has limitation in terms of their application in contemporary high-tech industries since most studies have not provided plausible explanation on levels and factors affecting transfer of knowledge and/or technology. To overcome these limitations, the four levels of knowledge and technology transfer are suggested: Knowledge and Technology Creation(Level I), Sharing(Level II), Implementation(Level III), and Commercialization(Level IV). Comprehensive literature identifies sixteen variables affecting the process and results of knowledge and technology transfer. The survey results show four key factors in knowledge and technology transfer: Communication, Distance, Equivocality, and Motivation, Communication refers to the degree to which a medium is able to efficiently and accurately conveys task-relevant information and media while distance involves both physical and cultural proximity. Equivocality refers to the degree of concreteness of knowledge and technology to be transferred while motivation involves incentives for and the recognition of the importance of knowledge and technology transfer activities. Further analysis shows that there are four distinctive clusters and they show very contrasting characteristics in terms of four key factors. The careful mapping of the four clusters on the four key factors show very informative knowledge and technology transfer patterns, the Knowledge and Technology Transfer Grid. Finally, actions to increase communication interactivity and motivation, and to reduce cultural distance and equivocality are suggested.

• Journal of Korean Clinical Health Science
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• v.7 no.1
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• pp.1215-1223
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• 2019

Purpose: This study is to figure out not only the characteristics relating to transfer time of inter-hospital transfer patient which is transferred by a private ambulance, but also factors influencing the transfer time. Methods: In this study, an analysis of 750 patients with high severity levels among those transferred to another hospital by a private ambulance in Busan for whole year of 2017. Results: The results showed that the following factors significantly influence the total inter-hospital transfer time: Ambulance crew (${\beta}=10.525$, p=.001) and patient and carer (${\beta}=37.606$, p<.001) when setting a doctor (selecting a medical institution) as a criterion; availability of the specialized care (${\beta}=12.435$, p=.008) when setting the near distance (reason for selecting a hospital for transfer) as a criterion. The explanatory power of this analysis was R2=0.423, whereas the explanatory power of calibration was R2=0.411. Conclusions: Factors that increase the total inter-hospital transfer time were the ambulance crew, and patient and carer's selecting a medical institution, and the reason for selecting a hospital where enables to offer the specialized care services.

• Journal of Technologic Dentistry
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• v.25 no.1
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• pp.173-185
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• 2003

This study mainly intends to determine the factors for which dental technicians are satisfied with their jobs and how much the resulting job transfer rate is and thus to identify the correlation between them. For these purpose, 200 subjects were sampled out of dental technicians in Seoul and Incheon, and the survey was performed from July 19, 2002 to August 15 (for 25 days) with self-administered questionnaire. Out of all collected questionnaires, 131 pieces(65.5%) were addressed for this study. As for the tools for this study, the structured questionnaire was used with its proven reliability and feasibility, and the contents of questionnaire consisted of 32 questions on the basis of related references. The contents of questionnaire were categorized into 3 sections: General attribute of subjects; Factors for which dental technicians are satisfied with their jobs; and their intention of job transfer. The questionnaire consisted of total 32 questions which included general attribute of subjects(10 questions), factors of their satisfaction with jobs(17 questions) and intention of job transfer(5 questions). The data analysis was processed by computerized system with SPSS(Statistical Package for Social Sciences). Statistical analysis techniques included frequency, percentage, T-test, F-test analysis and regression analysis. As a result of those analyses, the conclusion can be summarized as follows: 1. As a result of analyzing the factors for which the subjects were satisfied with their jobs, it was found that there were significant differences in career and job title out of question items(P<0.001). It was also shown that the factors of subjects' satisfaction averaged 3.43, which was considerably higher value than I expected. It was found that job and management factors were major job satisfaction factors. 2. As a result of analyzing the intention of subjects to decide their job transfer, it was found that there were significant differences in job title and marital status out of question items(P<0.001). It was shown that the total average of the intention of their job transfer amounted to 3.06. It was shown that dental technicians have relatively higher intention of job transfer from their current work place. 3. It was found that there was inverse correlation between the factors of subjects' satisfaction with their jobs and their intention of job transfer(r=-0.490, P<0.05). Likewise, it was also found that there was inverse correlation mostly between the evaluation value for each independent variable region in term of each factor of job satisfaction and the value for the intention of job transfer. In view of these correlations, it was concluded that higher job satisfaction likely led to lower job transfer. 4. As a result of regression analysis so as to determine the influences of job satisfaction factors on the intention of job transfer, it was found that the highest influential factor was management factor. And it was shown that the test values of model were statistically significant and its explanatory power amounted to 54.6%.

• Korea Journal of Hospital Management
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• v.18 no.4
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• pp.54-77
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• 2013

This paper is a comparison study about leadership training transfer factors between physicians working in large scale hospitals and managers working in firms. To fulfill this purpose, this study conducted a regression analysis on 101 managers and 59 physicians who had attended similar leadership training programs more than 16 hours recently in order to identify the differences on the learning transfer factors. 6 factors such as Learner readiness, Performance self-efficacy, (so far as Trainee Characteristics group), Organization Culture, Supervisor's tangible incentives and Supervisor's intangible support, (so far as Work environment group), Content Validity & Transfer Design (so far Training Design group) were used as independent variables while the personal Managerial Capability Increase and Leadership Capability Increase were used as dependent variables. And also we used 5 factors as control variables ; Job style (Manager or Physician), Age, Gender, Working years and Organization size. Here are the summary of major findings ; first, there were statistically significant differences between the learning transfer factors in leadership training programs for managers and those of physicians. Second, there were also statistically significant differences among trainees' working years and their organization size factors while age and gender do not affect the learning transfer factors. Third, for the physician's leadership training the practitioners should focus on two factors ; Organization Culture and Learner readiness.

• The Journal of Information Systems
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• v.15 no.2
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• pp.1-29
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• 2006

The recent development of IT, consolidation of communication and multimedia technology have brought enormous changes in many organizations. Theses changes are enabling the new educational opportunities such as distance teaming and virtual class room. Recently, e-Learning has grown rapidly in business training field, In the context of companies, e-Learning has merits in terms of access convenience, costs reduction self-directed learning, reciprocity, and flexibility. In this regard, the primary purpose of this study is to investigate which factors of e-Learning influence the effectiveness of education and transfer of loaming in business organizations. Based on the prior studies of the education and business training field, research model and research hypotheses were developed. Factors studied in this paper were as follows: 1) learners' characteristics, 2) organizational support and 3) system environments. The results of our study are as follows. (1) Motivation perceived usefulness in Learner factors had an significant influence on both learning effectiveness and transfer of teaming, whereas Ability, expectation had an influence on transfer of teaming. (2) Support from peer, support from supervisor in Organization factors had an significant influence on both Loaming effectiveness and transfer of teaming, whereas support from organization had influence on learning effectiveness. (3) Appropriate contents in system circumstance had an significant influence on both teaming effectiveness and transfer of teaming, whereas interface design had an influence on learning effectiveness.