This research is designed to distinguish and describe or explain incubator practices that affect the performance of incubator clients of university technology incubator programs. The research focuses on understanding which practices significantly contribute to increasing job creation for the firms located in university based technology incubators. An increasing number of communities are embracing economic development strategies that target the high tech sector with high wage, high value jobs as a way to diversify their economies and boost local and regional economies. New economic development strategies include the notion of a creation strategy or "growing your own" instead of relying on recruiting of existing companies from other regions. In 1999-2000 (according to the most recent data), small businesses created three-quarters of U.S. net new jobs (2.5 million of the 3.4 million total). The small business percentage varies from year to year and reflects economic trends. Over the decade of the 1990s, small business net job creation fluctuated between 60 and 80 percent. Moreover, according to a Bureau of the Census working paper, start-ups in the first two years of operation accounted for virtually all of the net new jobs in the economy. The study is broken into three parts: (1) a review of the literature on incubation, focusing on its history, best practices, technology incubation, networking theory, and previous empirical studies (2) a review of previous data collected in a recent national survey and (3) case studies of the top performing incubators in the country based on employment growth of client firms contracted with case studies from non-top ten programs. The literature suggests that the study of incubation must be considered in the context of a larger enterprise development system of which the incubator will fill gaps in the larger regional enterprise development system. This notion is explored. In general, there is a great need for more empirical research into best practice of incubation. It is a non trivial task however as the nature of the industry limits the ability to obtain traditional, statistically defendable, measures.

Thesis (M.S.)--Brigham Young University. Dept. of Technology, 2006. / Includes bibliographical references (p. 77-79).

In United States and other developed economies, technology transfer is a very important issue. The success of technology transfer is related with industrial upgrade and the development of economics. It is also a key mechanism to efficiently use those research achievements of universities to commercialize and transfer those valuable technologies. There are many research institutions and agricultural technology research organizations in Taiwan. Because the government support the research organizations continuously, Taiwan¡¦s universities has many valuable research results. In the age valuable Intellectual Pattern Right, the formal intellectual property rights, including patents, technological transfer, and the technological licensing, are still little in Taiwan¡¦s universities. So this research¡¦s main idea is to find a ideal model of the technology licensing office based on the processes of technology commercialization and u.s universities¡¦ experiences. The method utilized for collecting data in this thesis was to interview with the experts, researchers and governmental officers to gather the primary information. The other was to gather the secondary information, including research papers, books, theses, and magazines from the On-line databases and libraries. This thesis analyzes the technology transfer system and management policies based on five different points of view, i.e., the initial stage of technology development, the incubation of new technology, the resource attainment , demo of new technology, and the promotion. The important result observed from the thesis is that the degree of commercialization of the research results is not enough. In addition, Taiwan¡¦s technology transfer center just provide limited function. So, there are only few patents and royalties from technological transfer and low ratio of successful commercialization in Taiwan¡¦s universities. Meanwhile, most technology transfer in Taiwan happened through informal channel. So, the effects on technology transfer centers are not so strong. Three suggestions are drawn from the thesis: (1). The IPR conception of researchers is not enough. Researchers should be encouraged to apply pattens and IPR to improve the quality and quantity of Taiwan¡¦s intellectual property. (2). The technology transfer center should clarify the value of the research results and play the role of connection between industry and research institutions. (3). The regulations of IPR in Taiwan should be quickly updated to catch up the fast advancement of technologies.. Furthermore, the infrastructures of agriculture-related IPR management system should be built-up well. keyword¡Gtechnology transfer center¡Buniversity technology transfer¡BIntellectual Patten Right¡Btechnology licensing¡Btechnology commercialization.

Thesis (Ph.D.)--Mississippi State University. Department of Instructional Systems, Leadership, and Workforce Development. / Title from title screen. Includes bibliographical references.

This thesis presents a commercial outcome prediction system (CPS) capable of predicting the likely future monetary return that would be generated by an invention. The CPS is designed to be used by university technology transfer offices for invention assessment purposes, and is based on the data from their historical invention cases. It is aimed at improving technology transfer offices' invention assessment performance. Using qualitative critical factors suggested by literature. a prototype CPS based on decision tree induction was developed. The prediction performance achieved by the prototype CPS was unreliable. Three surveys with various technology transfer offices were then performed, and the findings were incorporated into a final version of the CPS, which was based on neural networks. Subject to information obtained in the surveys, a number of potentially predictive attributes were proposed to form part of the predictor variables for the CPS. The CPS starts with a number of data reduction operations (based on principal component analysis and decision tree techniques), which identify the critical predictor variables. The CPS then uses five neural-network training algorithms to generate candidate classifiers, upon which the final classification is based. The prediction results achieved by the CPS were good and reliable. Additionally, the data reduction operations successfully captured the most discriminative invention attributes. The research demonstrated the potential or using the CPS for invention assessment. However, it requires sufficient historical data from the technology transfer office using it to provide accurate assessments.

US corporations have long recognized university related scientific research as an important source of long term economic growth and technological innovation. This dynamic involvement with industry has drastically increased the university technology transfer and licensing activities, and has stretched the human and financial resources of Technology Management and Licensing Offices of many US universities. This research provides a mechanism that can aid in the complex process of properly assessing university-owned technologies and intellectual properties, to identify those with licensing and commercialization potential for the pursuit of truly important breakthrough discoveries. This research focuses on the university technology licensing and commercialization process from the perspectives of those licensing professionals whose firms' activities are engaged in licensing-in university technologies. The objectives of this research are to: 1.Identify the decision factors and licensing determinants that influence or impact the licensing and commercialization of university technologies. 2.Build and conduct a survey among those licensing professionals involved in the technology licensing process to determine the relative importance of each of the licensing determinants identified in the literature review, and their most current and up to date selection criteria for technologies they license. 3.Develop a framework to assist the University Technology Management & Transfer Office's personnel and other stakeholders in the assessment of the potential viability of the university technologies for licensing and commercialization.

This study explains the rise and fall of the Innovations Foundation, the University of Toronto's first office dedicated to the transfer of university-developed technologies to industry. Drawing on extensive archival research, ten interviews with key informants, and other sources, the case study traces the evolution of the Foundation from its launch in 1980 to its closure in 2006. The study delineates three distinct business models under which the Foundation operated from 1980 to 1990, 1990 to 1999, and 1999 to 2006. The reasons for the adoption and failure of each model are explored and a historically grounded, context-sensitive explanation of the university's decision to dismantle the Foundation in 2006 is provided. This explanation emphasizes the importance of managing unrealistic expectations for Canadian university technology transfer, and adds weight to a growing consensus on the importance of historical path-dependence as a conceptual tool for understanding the persistence of differentials in technology transfer performance among universities.

This study explains the rise and fall of the Innovations Foundation, the University of Toronto's first office dedicated to the transfer of university-developed technologies to industry. Drawing on extensive archival research, ten interviews with key informants, and other sources, the case study traces the evolution of the Foundation from its launch in 1980 to its closure in 2006. The study delineates three distinct business models under which the Foundation operated from 1980 to 1990, 1990 to 1999, and 1999 to 2006. The reasons for the adoption and failure of each model are explored and a historically grounded, context-sensitive explanation of the university's decision to dismantle the Foundation in 2006 is provided. This explanation emphasizes the importance of managing unrealistic expectations for Canadian university technology transfer, and adds weight to a growing consensus on the importance of historical path-dependence as a conceptual tool for understanding the persistence of differentials in technology transfer performance among universities.

Data to understand the inventiveness and technology transfer process for medical devices in India is lacking and majority of medical devices are imported. The presence of a medical school in a university system is expected to enhance healthcare inventiveness. Universities with medical schools have 2.5 times more R&D expenditure and productivity than universities without medical schools. Therefore, the presence or absence of medical schools in universities serves as interesting samples for technology transfer analysis. This thesis focuses on medical device inventiveness and technology transfer office efficiencies of American universities. Three sample sets are used. The first is data from 1242 US universities, of which 734 had medical schools, and their Technology Transfer Office (TTO) productivity from years 1999-2008. The second consisted of 5693 medical device patents filed at USPTO by universities worldwide during years 1999-2008, including US universities. The third consisted of 32 cochlear implant university based patents from 7 primary patent classes in USPTO. Universities involved in medical device research (MDU) and universities not involved in medical device research (NMDU) are compared in our study to understand differences in their technology transfer activities. Initially, Social network analysis is used to understand the interrelatedness of technologies in university based research using patent classes. Degree, betweenness and closeness centrality of 32 cochlear implant patents (out of 345 overall filed patents in USPTO including corporate filings), showed the importance of universities’ R&D contribution to the overall evolution of cochlear implant technology. Dynamics in terms of emergence and disappearance of technologies (represented by US patent classes in years 1977 to 2012), are identified. Our study highlights that universities' research focus within medical device research is confined to few technology classes like surgery, drugs and body treating compositions for therapeutic purposes and image analysis. In these technology areas, universities share of patent holding is found to be more compared to other medical device technologies. Multivariate OLS and binary logistic regressions are used to understand university characteristics that influences amount of patenting by universities. Our study attempts to delineate and highlight university characteristics that may influence amount of patenting in general, i.e., across all technologies and specifically those university characteristics that may influence more patenting in medical device technologies. Our study establishes that university characteristic variables like age, public/private ownership and research productivity influences amount of patenting by universities in general, across all technologies. However, additional university characteristics like presence of medical school and expenditure on legal fees are found influencing amount of patenting in medical device technologies by universities. Data Envelopment Analysis (DEA) is used in our attempt to understand the efficiency of universities in transferring their technologies to industries. Interesting insights are obtained on observing slack obtained during DEA. Our study highlights that some universities may have to reduce their research expenditure in large scales and number of employees working in their technology transfer offices in large scales compared to other universities in order to improve their efficiency in technology transfer process. Our study establishes that in order to improve technology transfer efficiencies, MDUs with higher research expenditure may have to reduce their research expenditure in large volumes compared to universities with lesser research expenditures. However, these MDUs may not be required to greatly reduce their technology transfer employees as compared to universities with lesser research expenditures, in order to improve their technology transfer efficiencies. Moreover, MDUs generating more number of invention disclosures and receiving more faculty awards annually can increase their patenting, licensing and startups in smaller volumes, in order to improve their technology transfer efficiencies, as compared to universities generating lesser invention disclosures and receiving lesser faculty awards, which can increase their patenting and licensing in larger volumes.

Malaysia is a transition economic country that aims to be a developed country by 2020. In realising this mission (Vision 2020), the cluster concept has been an interest and adopted by the central authorities. There are few years ahead to reach the targeted year and it interest of this study to investigate the relevant development on its own engineered cluster of the Multimedia Super Corridor (MSC) that was put forward on the success of Silicon Valley in the US. This thesis focuses on the development of the MSC cluster in the Malaysia context. It examines and measures the state of the cluster, the role played by its core actors (from Triple Helix perspective) and their relationship in the MSC. The role of collaboration has been used to measure the relationship among actors with the key determinants of cluster formation. A mixed data collection method was used to answer the research question and objectives involved. A conceptual model for analysing the MSC cluster is proposed, bringing together insights from the literature on clusters, role of actors, collaborative relationship and the complex systems of innovation approach. This conceptual model uncover the weaknesses of social dimension (social infrastructure) in Porter’s diamond model and the general approach of Triple Helix model in the cluster development. The cluster lifecycle model is used to add the depth to the analysis on the condition of cluster development.