No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
University-industry linkages in the UK: What are the factors underlying the variety of interactions with industry?
Abstract
This paper examines the different channels through which academic researchers interact with industry and the factors that influence the researchers’ engagement in a variety of interactions. This study is based on a large scale survey of UK academic researchers. The results show that university researchers interact with industry using a wide variety of channels, and engage more frequently in the majority of the channels examined – such as consultancy & contract research, joint research, or training – as compared to patenting or spin-out activities. In explaining the variety and frequency of interactions, we find that individual characteristics of researchers have a stronger impact than the characteristics of their departments or universities. Finally, we argue that by paying greater attention to the broad range of knowledge transfer mechanisms (in addition to patenting and spin-outs), policy initiatives could contribute to building the researchers’ skills necessary to integrate the worlds of scientific research and application.
... University-industry collaboration refers to several forms of collaborations between one or more universities and one or more firms. The broad nature of universityindustry collaboration allows for various pathways of engagement, and numerous taxonomies have been developed to classify these different types of collaboration (e.g., Abreu & Grinevich, 2017;D'Este et al., 2019;D'Este & Patel, 2007;Lawson et al., 2016;Perkmann et al., 2013). commercialization. ...
... Scientific achievements Aschhoff & Grimpe, 2014;Bekkers & Freitas, 2008;Ding & Choi, 2001;D'Este et al., 2019;Tartari et al., 2014;Zi & Blind, 2015 Academic engagement experience D'Este & Patel, 2007;Lawson et al., 2016; Non-academic experience Aschhoff & Grimpe, 2014;Barbieri et al., 2018;Bruneel et al., 2010;Gulbrandsen & Thune, 2017;Johnson et al., 2017;Lawson et al., 2016;Tartari & Breshi, 2012;Tartari et al., , 2014 Type of research Abreu & Grinevich, 2017;Aschhoff & Grimpe, 2014;Lawson et al., 2019;Schuelke-Leech, 2013;Tartari & Breshi, 2012 Gender Abreu & Grinevich, 2017;Blind et al., 2018;Gaughan & Corley, 2010;Gulbrandsen & Thune, 2017;Kongsted et al., 2017;Lawson et al., 2019;Link et al., 2007;Tartari & Salter, 2015 Biological age Blind et al., 2018;Giuliani & Arza, 2009;Giunta et al., 2016;Iorio et al., 2017;Lawson et al., 2019;Link et al., 2007;Tartari & Breshi, 2012 Academic age and rank Aschhoff & Grimpe, 2014;Boardman & Ponomariov, 2009;D'Este et al., 2019;Lawson et al., 2019;Link et al., 2007;Tartari & Breschi, 2012;Tartari et al., 2014 National and ethnic origin Edler et al., 2011;Lawson et al., 2019;Tartari et al., , 2014Trippl, 2013 Scientific achievements ...
... Research indicates that this holds true; specifically, having academic engagement experience substantially enhances the likelihood of engaging in future academic Patel, 2007;Lawson et al., 2016;. To be more precise, Lawson et al. (2016) demonstrated that individuals with academic engagement experience are more than one and a half times as likely to participate in future academic engagement. ...
... University-industry collaboration refers to several forms of collaborations between one or more universities and one or more firms. The broad nature of universityindustry collaboration allows for various pathways of engagement, and numerous taxonomies have been developed to classify these different types of collaboration (e.g., Abreu & Grinevich, 2017;D'Este et al., 2019;D'Este & Patel, 2007;Lawson et al., 2016;Perkmann et al., 2013). commercialization. ...
... Scientific achievements Aschhoff & Grimpe, 2014;Bekkers & Freitas, 2008;Ding & Choi, 2001;D'Este et al., 2019;Tartari et al., 2014;Zi & Blind, 2015 Academic engagement experience D'Este & Patel, 2007;Lawson et al., 2016; Non-academic experience Aschhoff & Grimpe, 2014;Barbieri et al., 2018;Bruneel et al., 2010;Gulbrandsen & Thune, 2017;Johnson et al., 2017;Lawson et al., 2016;Tartari & Breshi, 2012;Tartari et al., , 2014 Type of research Abreu & Grinevich, 2017;Aschhoff & Grimpe, 2014;Lawson et al., 2019;Schuelke-Leech, 2013;Tartari & Breshi, 2012 Gender Abreu & Grinevich, 2017;Blind et al., 2018;Gaughan & Corley, 2010;Gulbrandsen & Thune, 2017;Kongsted et al., 2017;Lawson et al., 2019;Link et al., 2007;Tartari & Salter, 2015 Biological age Blind et al., 2018;Giuliani & Arza, 2009;Giunta et al., 2016;Iorio et al., 2017;Lawson et al., 2019;Link et al., 2007;Tartari & Breshi, 2012 Academic age and rank Aschhoff & Grimpe, 2014;Boardman & Ponomariov, 2009;D'Este et al., 2019;Lawson et al., 2019;Link et al., 2007;Tartari & Breschi, 2012;Tartari et al., 2014 National and ethnic origin Edler et al., 2011;Lawson et al., 2019;Tartari et al., , 2014Trippl, 2013 Scientific achievements ...
... Research indicates that this holds true; specifically, having academic engagement experience substantially enhances the likelihood of engaging in future academic Patel, 2007;Lawson et al., 2016;. To be more precise, Lawson et al. (2016) demonstrated that individuals with academic engagement experience are more than one and a half times as likely to participate in future academic engagement. ...
... University-industry collaboration refers to several forms of collaborations between one or more universities and one or more firms. The broad nature of universityindustry collaboration allows for various pathways of engagement, and numerous taxonomies have been developed to classify these different types of collaboration (e.g., Abreu & Grinevich, 2017;D'Este et al., 2019;D'Este & Patel, 2007;Lawson et al., 2016;Perkmann et al., 2013). commercialization. ...
... Scientific achievements Aschhoff & Grimpe, 2014;Bekkers & Freitas, 2008;Ding & Choi, 2001;D'Este et al., 2019;Tartari et al., 2014;Zi & Blind, 2015 Academic engagement experience D'Este & Patel, 2007;Lawson et al., 2016; Non-academic experience Aschhoff & Grimpe, 2014;Barbieri et al., 2018;Bruneel et al., 2010;Gulbrandsen & Thune, 2017;Johnson et al., 2017;Lawson et al., 2016;Tartari & Breshi, 2012;Tartari et al., , 2014 Type of research Abreu & Grinevich, 2017;Aschhoff & Grimpe, 2014;Lawson et al., 2019;Schuelke-Leech, 2013;Tartari & Breshi, 2012 Gender Abreu & Grinevich, 2017;Blind et al., 2018;Gaughan & Corley, 2010;Gulbrandsen & Thune, 2017;Kongsted et al., 2017;Lawson et al., 2019;Link et al., 2007;Tartari & Salter, 2015 Biological age Blind et al., 2018;Giuliani & Arza, 2009;Giunta et al., 2016;Iorio et al., 2017;Lawson et al., 2019;Link et al., 2007;Tartari & Breshi, 2012 Academic age and rank Aschhoff & Grimpe, 2014;Boardman & Ponomariov, 2009;D'Este et al., 2019;Lawson et al., 2019;Link et al., 2007;Tartari & Breschi, 2012;Tartari et al., 2014 National and ethnic origin Edler et al., 2011;Lawson et al., 2019;Tartari et al., , 2014Trippl, 2013 Scientific achievements ...
... Research indicates that this holds true; specifically, having academic engagement experience substantially enhances the likelihood of engaging in future academic Patel, 2007;Lawson et al., 2016;. To be more precise, Lawson et al. (2016) demonstrated that individuals with academic engagement experience are more than one and a half times as likely to participate in future academic engagement. ...
... University-industry collaboration refers to several forms of collaborations between one or more universities and one or more firms. The broad nature of universityindustry collaboration allows for various pathways of engagement, and numerous taxonomies have been developed to classify these different types of collaboration (e.g., Abreu & Grinevich, 2017;D'Este et al., 2019;D'Este & Patel, 2007;Lawson et al., 2016;Perkmann et al., 2013). commercialization. ...
... Scientific achievements Aschhoff & Grimpe, 2014;Bekkers & Freitas, 2008;Ding & Choi, 2001;D'Este et al., 2019;Tartari et al., 2014;Zi & Blind, 2015 Academic engagement experience D'Este & Patel, 2007;Lawson et al., 2016; Non-academic experience Aschhoff & Grimpe, 2014;Barbieri et al., 2018;Bruneel et al., 2010;Gulbrandsen & Thune, 2017;Johnson et al., 2017;Lawson et al., 2016;Tartari & Breshi, 2012;Tartari et al., , 2014 Type of research Abreu & Grinevich, 2017;Aschhoff & Grimpe, 2014;Lawson et al., 2019;Schuelke-Leech, 2013;Tartari & Breshi, 2012 Gender Abreu & Grinevich, 2017;Blind et al., 2018;Gaughan & Corley, 2010;Gulbrandsen & Thune, 2017;Kongsted et al., 2017;Lawson et al., 2019;Link et al., 2007;Tartari & Salter, 2015 Biological age Blind et al., 2018;Giuliani & Arza, 2009;Giunta et al., 2016;Iorio et al., 2017;Lawson et al., 2019;Link et al., 2007;Tartari & Breshi, 2012 Academic age and rank Aschhoff & Grimpe, 2014;Boardman & Ponomariov, 2009;D'Este et al., 2019;Lawson et al., 2019;Link et al., 2007;Tartari & Breschi, 2012;Tartari et al., 2014 National and ethnic origin Edler et al., 2011;Lawson et al., 2019;Tartari et al., , 2014Trippl, 2013 Scientific achievements ...
... Research indicates that this holds true; specifically, having academic engagement experience substantially enhances the likelihood of engaging in future academic Patel, 2007;Lawson et al., 2016;. To be more precise, Lawson et al. (2016) demonstrated that individuals with academic engagement experience are more than one and a half times as likely to participate in future academic engagement. ...
... With the broadening of the chemical engineering field, the gap between academia and practical understanding of the industry has increased [1][2][3]. This gap was recognized by John Chen who organized a session at the 2013 American Institute of Chemical Engineers (AIChE) annual meeting revealing that growth areas in engineering research and faculty development are often very different from the areas that require the greatest number of new workers in engineering fields [4]. ...
... In addition, interpersonal and intrapersonal skills are assumed to be acquired in activities that occur as late as the senior year such as senior design and unit operations lab. (2) Faculty teaching courses are not trained in multiple areas of chemical engineering. They develop expertise in their research areas; however, they do not develop knowledge and skills in different areas of chemical engineering nor update themselves in up-to-date practices. ...
... (1) what are the students' understanding of these applications and their impact on students in terms of interest, knowledge of applications, and professional identity formation? (2) What is the relationship between students' identity and course performance and assessments? (3) Is there a significant impact of the proposed approach on underrepresented groups especially women? ...
... Academic engagement's drivers are primarily individual characteristics rather than department and institution-based (D'Este and Patel 2007;Perkmann et al. 2021). These individual characteristics involve academics pursuing broader goals beyond research and those who are well-established and well-connected in the academic community (Perkmann et al. 2013). ...
... Likewise, it is strongly influenced by research-related motives (D'Este and Perkmann 2011). The individual characteristics of academics have a more substantial impact on the variety and frequency of interactions than the characteristics of their departments or universities (D'Este and Patel 2007). ...
Society's growing demand for knowledge transfer from higher education institutions to firms through academics is a notable trend. Nonetheless, the nuances of how business school academics perceive their engagement in knowledge transfer to firms remain inadequately explored. This research endeavors to bridge this knowledge gap by drawing upon interviews conducted with 52 business school academics in Ghana. The synthesized findings derived from the interpretive phenomenological data analysis provide crucial insights grounded in the ability–motivation–opportunity theory framework. Within this framework, “opportunity” describes image- and project-opportunity context drivers, such as media engagement, goodwill, in-service training students, and projects by international development organizations fostered through relationship-building and networking. “Motivation” explains the established national, societal, and self-serving mandates, stimulating institutional-, society-, and person-driven motivations. “Ability” encompasses the capacity of academics to employ both generic and relational mechanisms. The interplay among ability, motivation, and opportunity catalyzes the creation of various knowledge content types linked to specific market contexts.
... In earlier work, researchers have mainly focused on technology transfer issues concerning patents, licenses, and spin-offs without paying due attention to successful and practical models of interaction between universities and enterprises Page 5 of 45 Tereshchenko et al. Journal of Innovation and Entrepreneurship (2024) 13:28 (Czarnitzki et al., 2012;Grimpe & Hussinger, 2013;Rajalo & Vadi, 2017;Wendji & Pilag Kakeu, 2022). In addition, the main emphasis tends to be on the barriers that hinder UIC, such as a lack of funding, overly bureaucratic structures, lengthy approval processes, etc., and not on the possible drivers of UIC (Attia, 2015;Hilkenmeier et al., 2021;Kleiner-Schaefer & Schaefer, 2022;O'Dwyer et al., 2022;Ruíz-Ruano García et al., 2019). ...
... Implementing all these parts is optional for a successful collaboration model; however, combining them can strengthen long-term UIC relations tremendously. The most typical form of UIC is linked to educational activities (D'Este & Patel, 2007;Perkmann & Walsh, 2007). This activity involves different types of interaction between universities and industry regarding the training of students, educating company personnel on courses similar to those done by full-time students, and offering certification and re-training activities for company employees. ...
Continuous technological development, digitalization, Industry 4.0, robotization, virtualization, and related investments in new types of physical assets are imposing increasing financial and intellectual demands on micro, small, and medium-sized enterprises (MSMEs). While fast technological development and rapid societal change make maintenance of a successful competitive edge ever more challenging, they also offer considerable potential for differentiation. In the area of networking and outside resources, MSMEs can utilize external resources and cooperate and collaborate with higher educational institutions (HEI) to boost their innovations pipeline and develop new technologies and processes to generate commercial products/services and improve their service offering. This research explores existing highly effective university–industry collaboration (UIC) models and seeks explanations for their success by examining the literature from the point of view of establishing successful relationships, emphasizing the importance of critical drivers for success. Our work synthesizes current knowledge of best practices based on a comparative analysis of practical collaboration. In the work, we identify eight popular and successful collaboration models: research and development partnerships, internships and co-op programs, knowledge transfer programs, entrepreneurship, and incubation programs, sponsored projects and grants, joint ventures and licensing agreements, executive education, professional and student career development. Based on analysis of globally reviewed successful models, a concept for robust, productive, and extended collaboration between companies and universities is produced suitable for the Finnish context. Several practical experiences are given for robust collaboration in the current post-COVID transition and energy crisis.
... Within such ecosystems, the anchor tenant plays a central role in spurring the innovation activities (Agrawal and Cockburn, 2003) and often coincides with the local university system (Tötterman and Sten, 2005). Universities support local innovation by transferring the knowledge they generate through different channels, such as scientific publications, education of skilled individuals, and research collaborations with companies (D'Este and Patel, 2007;Gunasekara, 2006). ...
... Academic knowledge can boost industrial development through formal collaborations with companies, technology transfer, and the foundation of spinoffs (Apa et al., 2021;Bragoli et al., 2024;García-Vega and Vicente Chirivella, 2020). At the same time, indirect knowledge spillover can flow via scientific papers, the education of skilled individuals (D'Este and Patel, 2007;Gunasekara, 2006;OECD, 2019), and the enhancement of capabilities exploited by firms (García-Vega and Vicente Chirivella, 2020; Kim et al., 2005). ...
Regional specialization is a complex evolutionary process in which new industries and technologies evolve from existing ones following a non-ergodic path-dependent branching process. Although the scientific literature acknowledges the role of universities in shaping both the industrial and technological trajectories of geographical regions, empirical studies analyzing the link with the emergence of a local industrial specialization are relatively few. Our work contributes to filling this gap by investigating the relationship between the stock of patents developed by universities in a specific technology and the subsequent industrial specialization of the hosting region in the same domain. The empirical setting focuses on all Italian provinces (i.e., the geographical areas at the third level of the NUTS classification) in the years from 1995 to 2018. We examine the effect of the local and the neighboring knowledge stocks on subsequent industry specializations identified through the revealed technology advantage index. The results indicate the presence of a positive and significant correlation, robust to the inclusion of multiple fixed effects and several alternative model specifications. Instrumental variable regressions suggest that a causal relationship is likely to exist. Patent stocks of universities located in neighboring geographical areas have also a positive impact on the specialization, although of a smaller magnitude. Moreover, the patenting activity of local universities has an additional positive effect in both southern geographical areas and academies with lower internationalization levels whereas no significant premium or penalty is detected for high-tech and low-tech patent fields.
... Scientific research may yield useful applications (Brooks, 1994;Jaffe, 1989) and may transform the search and problem-solving process underlying technological innovation (Fleming & Sorenson, 2004). Besides the general provision of academic research, universities may affect firms' innovation activities through many other channels (Cohen et al., 2002;D'Este & Patel, 2007;Link & Siegel, 2005;Salter & Martin, 2001;Thursby & Thursby, 2002). They educate scientists and engineers, who may constitute the future workforce of firms, they provide experts and consultants to help firms solve particular technological problems, they serve as collaboration partners on embryonic and applied projects, and they engage in knowledge transfer through patenting and licensing activities (Belderbos et al., 2016;Cassiman et al., 2008;Hall et al., 2003;Perkmann et al., 2013). ...
... Our study is not without limitations. While we do examine different types of academic research, the quality of research, the role of doctorates, and the engagement of universities in patenting activities, future work should further disentangle the different mechanisms through which multinational firms may benefit from academic research, such as joint R&D projects, formal IP arrangements (licenses and spin-offs), conference participation, and consultancy and informal meetings (D'Este & Patel, 2007;Link & Siegel, 2005;Perkmann et al., 2013;Salter & Martin, 2001;Thursby & Thursby, 2002). Second, our analyses allowed for investor heterogeneity by distinguishing research from development investments and by estimating random coefficient models, investor heterogeneity may also stem from differences in absorptive capacity for science due to heterogeneous R&D strategies or from other factors. ...
Universities play an important role in regional development and innovation and engage with the industry through various channels. In this paper, we examine the role of heterogeneous characteristics of university research, in particular universities’ orientation towards basic or applied research and the quality of this research, in attracting firms’ R&D investment. We analyze the location decisions in the United States by foreign multinational firms at the level of metropolitan areas. We contrast research and development projects and explore whether they are driven by different factors. We find that the drivers of location choice differ importantly as a consequence of the type of the focal R&D investment of the firm. Universities with an orientation towards applied scientific research and exhibiting higher academic quality of applied research attract more R&D investment focusing on development activities. In contrast, firms’ investments in research activities are attracted by the academic quality of basic scientific research of local universities. Hence, increased university emphasis on academic engagement and applied research may have negative consequences for industrial research in the region.
... Actualmente, existe un consenso generalizado sobre el rol positivo que la cooperación ciencia industria orientada a la generación de conocimiento puede ejercer para el sistema productivo y la sociedad en su conjunto (Rosenberg y Nelson, 1994;Cohen et al, 2002;Arocena y Sutz, 2005). La cooperación ciencia-industria puede asumir características diversas y realizarse a través de múltiples esquemas, tales como la consultoría, el contrato de investigación, la investigación conjunta, la comercialización de propiedad intelectual, la creación de start ups, entre otros (Meyer-Krahmer y 111 Schmoch, 1998; Lee, 2000;Schartinger et al., 2002;Cohen et al., 2002;D'Este y Patel, 2007). El esquema específico a través del cual ciencia e industria cooperan influencia fuertemente tanto las motivaciones para cooperar como los efectos que la cooperación genera. ...
... Los efectos económicos tienden a verificarse en todos los esquemas y se refieren, por ejemplo, a la obtención de fondos privados, al financiamiento público para la compra de equipamiento de laboratorio, a compartir equipos e instrumentos con la industria, entre otros (Meyer-Krahmer y Schmoch, 1998;Lee, 2000;D'Este y Patel, 2007;Ankrah et al, 2013;De Fuentes y Dutrénit, 2012). Si bien tales beneficios son considerados en forma dicotómica respecto a los beneficios intelectuales, algunos autores han indicado una relación de complementariedad entre ellos (D'Este y Perkmann, 2011;Verre et al., 2021). ...
La investigación conjunta es un esquema de cooperación potencialmente virtuoso para generar aprendizajes en la parte pública y efectos beneficiosos en la sociedad. El trabajo se propone, a partir de la experiencia argentina en la pandemia de Covid-19, analizar la trama de capacidades, relaciones y efectos generada, a lo largo del tiempo, por una serie de proyectos financiados por el Estado en 2010, para esclarecer el nexo entre efectos de aprendizaje y efectos sociales. Se utilizó una metodología cualitativa centrada en el método de estudio de casos múltiples, donde cada caso abarca proyectos financiados por el Estado que derivaron posteriormente en diferentes soluciones para el Covid-19. El trabajo identifica un proceso de aprendizaje público que integra tanto los aportes de la industria como la dimensión intelectual de los beneficios económicos; conceptualiza el proceso de acumulación de capacidades como un multiplicador de efectos sociales que emergen a medida que el conocimiento es reutilizado; identifica la articulación entre diferentes esquemas como condición para que los efectos de aprendizaje y los efectos sociales se manifiesten a lo largo del tiempo.
... The chemical engineering field has expanded, resulting in an increased gap between academia and industry [1][2][3]. This gap was acknowledged by John Chen at the 2013 American Institute of Chemical Engineering (AIChE) Annual meeting, who highlighted that the areas of growth in engineering research and faculty development differ from the areas that require new workers in engineering fields [4]. ...
... (1) what are the students' understanding of these applications and their impact on students in terms of interest, knowledge of applications, and professional identity formation? (2) What is the relationship between students' identity and course performance and assessments? (3) Is there a significant impact of the proposed approach on underrepresented groups especially women? ...
... The necessary conditions for the existence of cycles are that human capital employed in science creation and high valued innovations is high, and the interest rate is low. Our study complements a literature that is heavily empirical and lacks dynamic models, including academic entrepreneurship (D'Este and Perkmann 2011), university-industry R&D nexus (D'Este and Patel 2007;Perkmann et al. 2013), technology transfer (Audretsch et al. 2022;Etzkowitz andLeydesdorff 1995, 2000), academic incubators, and university spin-offs (Meoli and Vismara 2016;Pirnay et al. 2003). ...
To formally understand cyclicity in innovation and to tie to Schumpeter’s idea about waves of creative destruction, we elaborate upon Thomas Kuhn’s (1962) hypothesis that science evolves through a succession of paradigm life cycles by noting that entrepreneurs recognize the profitability of new scientific theories through a delay. The delay from innovation to entrepreneurship may be due to technological inertia, the time taken in recognizing the applications of basic research, or related to how quickly technological change evolves over time and its returns are realized. In our model, a profit-maximizing entrepreneur uses the latest scientific knowledge to create innovative technologies, which generates cycles between science and innovation. The necessary conditions for the existence of cycles are that human capital employed in science creation and high valued innovations is high, and the interest rate is low. The findings also tie to the notion about the variability of innovation over the business cycle and can provide useful inputs into the formulation of more effective technology policies.
... Extensive literature delves into the role of NGOs in cultivating innovation capacity, the dynamics of university-industry partnerships, the impact of academic faculty on technology transfer, and the intricate interplay of universities within the innovation ecosystem (Bozeman & Boardman, 2014;Brink & Brink, 2010;Brouwer, Kleinknecht & Reijnen, 1993;D'Este & Patel, 2007;Gao & Newman, 2013;Huang & Wu, 2013;Huggins & Johnston, 2010;Kocakülah, 2018). ...
As widely recognized, Turkey is hosting the world's highest number of registered refugees since 2011. Notably, 20% of this refugee population comprises young individuals aged 18-29, highlighting significant youth. Gaziantep, second to Istanbul in refugee concentration, accommodates over 440,000 refugees. This study delves into the necessity of forging a new symbiotic relationship between residents and migrants. Such a partnership can positively affect industry, productivity and human resource diversity. Notably, research indicates that a majority (80%) of refugees do not foresee a return to Syria, underscoring the significance of maximizing the productivity and efficiency of these individuals in their adopted regions. Consequently, the study investigates the interplay between young migrants and the city's entrepreneurship ecosystem, drawing upon data from 14 collaborative projects, focusing on enhancing local and refugee youth's capacity and entrepreneurial skills, between Gaziantep University and NGOs. The findings underscore the outcomes stemming from the alliance between young refugees and their local counterparts, which fosters innovation and productivity through collaboration. This study illuminates the potential for new ecosystems to drive entrepreneurial effectiveness and efficiency, culminating in innovation-driven accomplishments facilitated by the collaboration between refugee and local youth.
... However, to close existing research gaps and complement previous research, this study tests for the existence of a marginal effect of university-hospital-industry collaboration (UHIC). On the one hand, limited capabilities (Muscio, 2010), increasing coordination efforts (D'Este & Patel, 2007), and a growing perceived threat of losing academic freedom (Azagra-Caro et al., 2006;Tartari & Breschi, 2012), as well as an increasing cognitive distance between academic and industrial researchers (D'Este & Perkmann, 2011;Muscio & Pozzali, 2013), may limit the integration of too many external knowledge sources. On the other hand, increasing marginal returns of UHIC intensity might exist because of learning effects and emerging trust toward industry partners (Bruneel et al., 2010;Rajalo & Vadi, 2017). ...
In the face of the challenges of rising demand and increasing economic pressure, medical service innovations and university hospitals are becoming increasingly important as cornerstones for the continuous development of medical care. Simultaneously, increasing technological complexity, scarce funding, and resource-intensive technology development are forcing university hospitals to open up their internal innovation processes. Numerous studies have highlighted the beneficial effects of cross-sectoral collaboration on the innovation performance of industrial entities, while neglecting the perspective of academic institutions. The impact of industry collaborations on the service innovativeness of university hospitals in particular has not been addressed in previous research. Although the potential for nonlinear effects of university-industry collaborations has been discussed in research, adequate evidence, particularly in the healthcare context, has not been provided. Therefore, this study addresses the questions: (1) What is the impact of university-hospital-industry collaboration (UHIC) on the service innovativeness of university hospitals? (2) Can a nonlinear relationship between UHIC and university hospitals' service innovativeness be empirically verified? The hypotheses are tested based on an unbalanced panel data set, which combines three distinct data sources and comprises annual observations from 2011 until 2019 of all German university hospitals. The findings indicate that the UHIC intensity has a positive effect on university hospitals’ service innovativeness with a one-year time lag. Furthermore, a negative quadratic UHIC effect was found. In doing so, this study complements existing research and opens the black box by uncovering the downside of cross-sectoral collaboration for a more complete understanding of the underlying dynamics of this growing area of research, with a particular focus on university hospitals.
... University-industry linkages play a critical role in facilitating technology and knowledge transfer between higher learning institutions and industries and fostering innovation. Researchers classify various modes of university-industry linkages according to different criteria, including organizational forms (Bonaccorsi and Piccaluga, 1994), the duration of relationships (Chen, 1994), channels (Arza, 2010;Nsanzumuhire et al, 2021), and functions (Santoro and Gopalakrishnan, 2000;D'Este and Patel, 2007;Kruss and Visser, 2017;Nsanzumuhire et al, 2021). Educational collaboration, research engagement, and academic entrepreneurship are typical modes of university-industry linkages (Nsanzumuhire et al, 2021). ...
This chapter examines the trajectory and effectiveness of Africa-China digital talent development cooperation by investigating university-industry-government relations. Based on participant observation conducted in China from 2017 to 2019 and fieldwork in Ethiopia from 2019 to 2020, it identifies a typology of four collaboration types based on the nature of initiators and the partnership modes. Ethiopia is selected as an information-rich case due to its diverse typology variations. Each collaboration type addresses specific digital education needs in Ethiopia, including equipping education officials and professionals with digital knowledge in higher education, providing digital skills training for pre-service and in-service teachers, and empowering youth through digital innovation and entrepreneurship. This chapter uncovers the interactions among universities, industry, and governments in digital talent development between Africa and China. It argues that African governments should take a more proactive role in facilitating effective university-industry linkages.
... There is a long experience and tradition of conducting surveys in order to understand the knowledge exchange practices of researchers in relation to the variety of collaborative practices (Díaz-Faes et al., 2023), modes of knowledge exchange with industry (D'Este & Patel, 2007), exchange with policy (Thune et al., 2023), or research and innovation practices in industry through the Oslo Manual (Bloch, 2007;Gault, 2020;OECD & Eurostat, 2018), innovation in the public sector (Arundel et al., 2019), and practices of Responsible Research and Innovation (RRI) (Meijer, Brasil et al., 2023 Reference Needed) (in fact RRI cover various OS dimensions). Studies aimed at monitoring OS processes also relied on surveys: for example on sharing of research materials (Shibayama et al., 2012), open peer review (Ross-Hellauer et al., 2017), policy use (Cole et al., 2023), engagement with non-academics (Lawson et al., 2019), integrity (Schneider et al., 2023), or broader perceptions and habits of OS (Ollé et al., 2023). ...
Background: Following a flurry of policies for Open Science (OS), there is now a wave of initiatives to monitor its adoption. However, the great diversity of understandings and activities associated related to Open Science makes monitoring very challenging. There is a danger that by focusing on what can be readily observed (e.g. publications) many other OS activities are overlooked (e.g. participation), with a potential narrowing of OS scope, ‘street-light’ effects, and deviation from the values of OS.Methods:We have conducted desk research to analyse existing OS conceptualisations and monitoring efforts against the evaluation literature. Since Open Science can be understood as a systemic transformation of the research system, we have borrowed in particular concepts from Transformative Innovation Policies (TIPs) frameworks which aim at evaluating socio-technical transitions.Results: In accordance with the notion of OS as a systemic transformation, we propose that OS should imply a change in monitoring frameworks for OS. Just like the shift from the ‘linear model’ to ‘innovation systems’ models in the 1980s was accompanied with new statistical concepts and tools (e.g. the OECD’s Oslo manual and innovation surveys), tracking OS adoption requires a far-reaching change in monitoring. We propose that the new monitoring should shift towards: (i) a systemic perspective which considers the various actions related to OS, including policies and outputs (e.g. datasets) but also processes (e.g. participatory events), outcomes (e.g. use of knowledge in policy) and expected impacts (e.g. increased attention to societal problems); (ii) implementation of monitoring as learning (rather than accountability or benchmarking) for strategic perspectives and reflexive evaluation; (ii) mapping the directionality of the activities and the values associated with the choices in directions. Conclusions:A monitoring framework for OS requires a profound change in monitoring framework and practices. The scope should broaden from outputs (such as publications) towards the processes of connection that make science ‘open’ (usage, co-creation and dialogue), as well as towards outcomes (changes in practices) and the longer-term impacts that reflect the values and normative commitments of OS.
... Various modes of university-business interaction exist, such as spin-out companies or patenting (D'Este and Perkmann, 2011). Of these modes, collaboration is the most frequent channel, which includes joint precompetitive research, directed contract research, and consultancy (D'Este and Patel, 2007;Perkmann and Walsh, 2007). Thus, a spectrum of collaborative options exists for the use of risk-related university science in the wider world, yet all of these must engage a variety of interested parties and need a plausible and tractable project plan to overcome a variety of difficulties inherent to cooperation across organisational boundaries. ...
Translation of geoscience research into tangible changes, such as modified decisions, processes, or policy, in the wider world is an important yet notably difficult process. Illustratively, university-based scientists and professionals work on different timescales, seek different insights, and may have a substantial cognitive distance between them. The work on Co-RISK reported in this paper is motivated by an ongoing need for mechanisms to aid this translation process. Co-RISK is an accessible (i.e. open access, paper based, zero cost) toolkit for use by stakeholder groups within workshops. Co-RISK has been developed to aid the co-creation of collaborative inter-organisational projects to translate risk-related science into modified actions. It is shaped to avoid adding to a proliferation in increasingly complex frameworks for assessing natural hazard risk and is given a robust basis by incorporating paradox theory from organisation studies, which deal with navigating the genuine tensions between industry and research organisations that stem from their differing roles. Specifically designed to ameliorate the organisational paradox, a Co-RISK workshop draws up “maps” including key stakeholders (e.g. regulator, insurer, university) and their positionality (e.g. barriers, concerns, motivations) and identifies exactly the points where science might modify actions. Ultimately a Co-RISK workshop drafts simple and tailored project-specific frameworks that span from climate to hazard, to risk, to implications of that risk (e.g. solvency). The action research approach used to design Co-RISK, its implementation in a trial session for the insurance sector, and its intellectual contribution are described and evaluated. The initial Co-RISK workshop was well received so it is envisaged to be applicable to other sectors (i.e. transport infrastructure, utilities, government). Joint endeavours enabled by Co-RISK could fulfil the genuine need to quickly convert the latest insights from environmental research into real-world climate change adaptation strategies.
... In this study we advance new understanding on commercially-oriented academic-industry entrepreneurial collaborative initiatives by exploring various schools of thought on factors affecting it, namely, individual level factors (Azjen, 1988;Bolton & Lane, 2012;Covin & Slevin, 1989), organisational level factors (Chiva et al., 2007;Gomez et al., 2004) and interorganisational level factors (Garstka et al., 2012) that influence academicians' involvement, performance and outcomes (Calvert & Patel, 2003;D'Este & Patel, 2007;Glassman et al, 2003). All this is done with a sample of 510 academicians from private universities in Malaysia using the aforementioned theoretical approaches to entrepreneurship in the context of commercially-oriented academic-industry entrepreneurial collaborations. ...
This study seeks to analyse the experience of academicians from foreign branch campuses and private universities in Malaysia and point out the multi-level factors that influence the outcomes of commercially-oriented academic-industry entrepreneurial collaborations. This study is cross-sectional and follows an explanatory factor analysis research design. Data was collected from 510 academics from 36 foreign branch campus universities and private universities using a simple random probability sampling method. First, only two multi-level factors, ‘age’ and ‘readiness to collaborate,’ are significant when testing the relationship between cross-functional engagement and the performance factor ‘effective knowledge transfer’. Second, only two multi-level factors, 'age' and 'readiness to collaborate’, are significant when testing the relationship between cross-functional engagement and the performance factor ‘effective knowledge transfer’. It categorises the various types of commercially-oriented academic-industry collaboration activities. Secondly, it illustrates the consequences of each kind of commercially-oriented academic-industry collaboration. Lastly, it measures the performance of commercially-oriented academic-industry collaboration against the performance variables in developing nations like Malaysia.
... In order to identify interviewees, we first identified intrapreneurial initiatives in the three universities by searching for online information via the HEI's webpages and reading newsletters. Inspired by Abreu andGrinevich (2013), D'Este andPatel (2007), and Audretsch et al. (2021), we considered examples of relevant formal and informal intrapreneurial, value-creating activities, such as engaging in strategic collaboration with stakeholders, founding research centers and programs, attaining large sums of research grants from national or international financiers such as the EU, innovating and commercializing new technologies and ideas, establishing radically new education programs, developing radically new teaching methods and textbooks, fundraising, and initiating stakeholder engagement. All the initiatives identified entailed innovative value-creating activities beyond the traditional academic roles of teaching and research, implying that the intrapreneurs took risks that potentially led to financial or reputational gains for a wider purpose within the academic environment. ...
... Studies of valorization so far show that humanities researchers interact with actors outside of academia to at least the same extent as researchers in other fields (D'Este & Patel, 2007;Olmos-Peñuela et al., 2014a, b), and often more so (Gulbrandsen, 2016;Pedersen et al., 2018). However, the collaboration patterns are different. ...
Despite its proven societal value, humanities knowledge tends to be marginalized in research policy; this has been a topic of debate for some time. In this chapter, we focus on the valorization of humanities knowledge, with the aim of comprehending the way this process engenders societal impact. We argue that historical impact stories offer an effective methodological approach for a deeper understanding of such valorization and its subsequent impact. Drawing on three humanities research cases from Sweden, we propose that valorization and impacts of humanities knowledge should be seen as processual and as influenced by societal actors who determine the premises and condition the somewhat unpredictable nature of such impacts. We introduce two concepts: (i) acting space , which involves access to collaborators, audiences, and channels that enable knowledge valorization, and (ii) meandering knowledge flows , which provides insight into the uneven and hard-to-predict nature of valorization. Through these concepts, we wish to provide a better and more nuanced understanding of how knowledge valorization in the humanities unfolds. By doing so, we hope to support humanities scholars to find ways of articulating their own modes of mattering.
In developed countries, collaboration between universities and industry has always proven beneficial from both an industry and academia perspective. Universities want to collaborate with industry not only for impactful research but also to expand their research and commercialize their knowledge base. Industries, especially financially strapped ones, are also turning to science to solve research and development problems to remain competitive nationally and globally. The active participation of industry professionals in academia and the exposure of students and scientists to the industrial environment through internships and training contribute to the development of skills in line with modern requirements. University-industry linkages encompass a range of collaborative initiatives, including internships, research partnerships, cooperative programs, and industry-sponsored projects. These interactions provide students with valuable opportunities to bridge the gap between theoretical learning and practical applications, fostering a deeper understanding of industry-specific requirements and expectations. Moreover, these collaborations enable students to develop diverse skill sets that align with current industry trends, making them more attractive to potential employers. Introduction Research aims to identify university-industry activities that enhance student employability. It highlights how these collaborations empower students to develop critical skills such as problem-solving, adaptability, and teamwork while exposing them to the latest industry trends and technologies. Moreover, exposure to industrial mentors and professionals expands students' professional networks, providing them with invaluable connections for future job opportunities and career growth. Universities benefit from access to industry expertise, cutting-edge research projects, and potential funding sources that enhance their academic programs and research capabilities. Industries benefit from a pool of job-ready graduates who can quickly contribute to their organizations, reduce training costs, and improve overall productivity. University-industry linkages bolster student employability by equipping them with practical skills, industry knowledge, and networking opportunities. These collaborations are win-win for students, universities, and industries alike and they hold the key to preparing graduates for the challenges and opportunities of the modern workforce. This abstract underscores the importance of fostering and expanding such partnerships to ensure that students are well-prepared for the ever-evolving job market. (Rupika et al., 2016) Universities, industry, and government agencies all play important roles in the growth and development of the knowledge economy in the modern era. These organizations also play an important role in creating knowledge and deploying it for the benefit of society. In this article, we measure and describe university-industry-government (UIG) relationships in the context of research and innovation. (Kuriakose, 2016) Traditionally, universities were dedicated to basic teaching and research and were considered sources of scientific knowledge. It was not until after World War II that universities began to be seen as agents of local economic development through large-scale investments in commercial technology. (Ashraf et al., 2018)Regarding unemployment, intense challenges are faced by developed and especially developing countries. Especially in Europe, developed countries are searching for environmentally sustainable solutions, while as if in limbo remains the unemployment situation in developing countries. Consequently, the situation is getting even worse as the trend for unemployment of graduates is still rising. However, industries can cope with this problem in certain ways. Developing countries like Pakistan, Bangladesh, Sri Lanka,
In today's modern and advanced world of technology, innovation and entrepreneurship are the key. In past decades, entrepreneurship had become one of the top concepts in the business field. This chapter deals with the importance of innovation and entrepreneurship development among the learners and teachers of the University, which can help in fostering an innovative ecosystem to lead socio-economic development of the country. The chapter explains the National Education Policy (NEP) 2020 of Government of India and its initiative through MoE's innovation cell (MIC) and institution's innovation council (IIC). The chapter also indicates through various activities undertaken, the improvement in the quality of education imparted, the nurturing of innovative mindsets using the approach of critical problem solving that intends to address various societal and scientific issues through a case-based approach, taking Sinhgad Technical Education Society's Sinhgad Institute of Management as an example. Here it is extremely a leading management institute in Pune- an educational hub of Maharashtra, India.
Purpose
As little is known about the productivity levels of small and medium-sized enterprises (SMEs) engaging with universities and the relative changes in productivity of SMEs subsequent to these collaborations, the paper examines the following questions: (1) Does the relative productivity of SMEs engaging in university collaboration differ from those that do not? (2) Are subsequent changes in firm productivity following university collaboration related to their initial levels of productivity?
Design/methodology/approach
The paper utilises data on 254 SMEs from the Longitudinal Small Business Survey and uses two statistical techniques: First, bivariate tests of difference were used to inspect the relationships between productivity levels and whether the firm collaborated with a university to introduce its innovation. Second, ordinary least squares regressions were used to test whether the future productivity of SMEs that collaborated with universities was related to their initial productivity levels.
Findings
The analysis reveals that SME–university collaboration is unrelated to starting productivity. Furthermore, the analysis suggests a nonlinear relationship exists between the starting productivity of SMEs and their subsequent productivity following a university collaboration. Therefore, higher levels of subsequent productivity are observed among those SMEs where starting productivity was either relatively low or high, suggesting that collaborations have a transformative effect on SMEs with relatively lower initial levels of productivity and a maintenance effect for SMEs with relatively higher levels of initial productivity.
Practical implications
Given the fact that the extant literature also suggests that, overall, university collaboration is beneficial, policymakers should strive to encourage greater levels of collaboration involving SMEs. In light of the evidence that SME–university collaborations can transform less productive firms, it appears unjustified for practitioners and policymakers to only consider stronger-performing firms to be included in such programmes.
Originality/value
The study contributes new theoretical and practical knowledge to the understanding of the role of firm productivity in predicting the proclivity of firms to collaborate with universities. Furthermore, as few studies have examined the impact of these collaborations on the subsequent productivity of firms that collaborate with universities, this paper fills an existing gap in the literature.
Food crops contribute to food security in developing countries while being planted and harvested for profit in many industrialized countries. To improve food security and farmer income, the National Agricultural Research System of India developed and disseminated many crop varieties through technology transfer. Non-exclusive licensing allowed faster distribution due to multiple players having seed production rights and a market pricing control mechanism. Current literature shows technology transfer mechanism research on non-exclusive licensing is scarce. This study investigates the determinants of crop variety tech transfer in the case of non-exclusive licensing. It collects data from 100 seed licensees of India's largest agricultural research institute to examine the process from their perspective. Multivariate regression is applied to analyze the data under four domains, i.e., technology, technology transferor, tech transfer procedure, and policy. Technology readiness, availability, and an amicable tech transfer procedure boost technology commercialization, while stringent tech transfer policies negatively affect it. Results are used to create an effective technology transfer action framework to improve crop variety technology dissemination and enhance food security.
We investigate how the interplay between academic researchers’ and innovators’ entrepreneurial intentions and open innovationactivities fosters their market commercialization activities. We qualitatively analyse five case studies of European research consortia topropose potential theoretical mechanisms that limit or abet market commercialization activities. Our results show that inbound andcoupled open innovation activities compensate for lower entrepreneurial intentions among scientists. However, establishing partnershipsremains challenging, particularly in pre-prototyping phases. Noticeably, our findings point towards prosocial motivation as an enablerto make innovation outcomes more publicly available.
(17) (PDF) Are Entrepreneurial Intentions and Open Innovation complements or substitutes for eliciting activities towards the market commercialization of academic breakthrough technologies?. Available from: https://www.researchgate.net/publication/380562731_Are_Entrepreneurial_Intentions_and_Open_Innovation_complements_or_substitutes_for_eliciting_activities_towards_the_market_commercialization_of_academic_breakthrough_technologies [accessed May 14 2024].
Purpose
University-industry collaboration studies have placed greater emphasis on intrinsic motivators that drive academic researchers to pursue collaboration. This paper explores the relationship between spiritual motivation and collaboration intentions mediated the antecedents of university-level collaboration through theories of self-determination and planned behaviour. This study was conducted to validate the proposed relationship between spirituality and academic researchers in the field of engineering affiliated with higher educational institutions in India.
Design/methodology/approach
This study surveyed 242 participants and utilised structural equation modelling. Research has found that the beneficial relationship between spiritual motivation and collaboration intentions is mediated by attitudes and perceived behavioural control. This study represents a quantitative investigation within the realm of university-industry collaboration, which aims to document the ways in which spiritual motivation can augment collaboration with industry. The study employs self-determination theory and the theory of planned behaviour to elucidate the underlying mechanism to support entrepreneurial debate.
Findings
This study identified attitude and perceived behavioural control as mediators in the relationship between spiritual motivation and collaboration intentions.
Originality/value
The results of this study provide additional support for existing theories and present a diverse perspective on the intrinsic motivation of academic researchers to adopt UIC.
Geographic proximity is widely acknowledged as a primary catalyst for research collaborations in general, and specifically for cross-sector collaborations. This study proposes a large-scale empirical analysis to examine the moderating role of certain territorial features of research infrastructure in the relationship between geographic distance and collaboration type. Our approach employs bibliometrics, using individual Italian coauthors of publications from both private and public sectors as the units of analysis. On average, cross-sector collaborations exhibit greater distances compared to intra-sector public collaborations. Importantly, this outcome is attributed to the uneven territorial distribution of private R&D in Italy. Specifically, as the size of research staff in private organizations within a region increases, the average distance of cross-sector collaborations tends to decrease significantly. A similar, though less pronounced, effect can be observed in regions with varying intensities of inventive activity.
This study examines the determinants of academia-industry collaboration (AIC) in the context of Bariloche, Argentina, and provides valuable insights into collaboration dynamics in a developing economy. Using a quantitative research approach, data was collected through a survey administered to academic researchers in Bariloche. The survey included questions on researcher characteristics, organizational attributes, and disciplinary norms, which were then tested through eight hypotheses related to factors influencing AIC. Data analysis, including descriptive and inferential statistics, revealed significant relationships between independent variables (e.g., prior career experience, organizational affiliation, disciplinary norms) and researchers’ involvement in AIC. The study’s limitations, such as reliance on self-reported data and non-probabilistic sampling, are acknowledged. Nevertheless, the findings contribute to the understanding of AIC in Bariloche and have implications for promoting effective academia-industry partnerships. Future research should consider longitudinal studies and explore additional factors to inform evidence-based policies in developing economies.
Background
Following a flurry of policies for Open Science (OS), there is now a wave of initiatives to monitor its adoption. However, the great diversity of understandings and activities related to Open Science makes monitoring very challenging. There is a danger that by focusing on what can be readily observed (e.g. publications) many other OS activities are overlooked (e.g. participation), with a potential narrowing of OS scope, streetlight effects, and deviation from the values of OS. Since Open Science can be understood as a systemic transformation of the research system, we have borrowed concepts from Transformative Innovation Policies frameworks which aim at evaluating socio-technical transitions. In accordance with this view of OS as a systemic transformation, we propose that the new monitoring efforts should shift towards: (i) systemic perspectives which considers the various actions related to OS, including policies and outputs (e.g. datasets) but also processes (e.g. participatory events), outcomes (e.g. citizen interest in science) and expected impacts (e.g. better scientific contributions to addressing societal problems); (ii) implementation of monitoring as reflexive learning (rather than accountability or benchmarking); (iii) mapping the directionality of the activities and the values associated with the choices in directions. In summary, a monitoring framework for OS requires a profound change in conventional monitoring practices. The scope should broaden from current focus on outputs (such as publications) towards the processes of connection that make science ‘open’ (usage, co-creation and dialogue), as well as towards outcomes (changes in practices) and the longer-term impacts that reflect the values and normative commitments of OS.
Purpose
The purpose of the study was to examine the factors that are important for strengthening university–industry collaboration (UIC). This study also investigates the outcome of UIC in the light of creativity, skill, knowledge, and research work.
Design/methodology/approach
A survey method has been used to collect data for the study. This study applied a purposive judgmental sampling technique where particular types of respondents like university faculty members and the top officials of the organizations were selected who are knowledgeable and can provide the desired information. The current study used the structural equation modeling method to analyze the data. In the first stage, this research assessed the demographic factors of the respondent. Then this study conducts confirmatory factors analysis and convergent and discriminant validity and reliability test. Finally, the hypotheses are tested by using nonparametric.
Findings
This study finds that knowledge transfer mechanism, governmental factors, organizational design factors, technology transfer and the collaborative network has a significant impact on strengthening UIC, which ultimately facilitates creativity, knowledge creation, skills development and supply of graduate according to the requirement of the industry, good research work.
Originality/value
The current study identified some important determinant that has a substantial influence on strengthening UIC. According to the study organizational design, government, technology, collaborative network and mechanism for knowledge transfer play very crucial roles in strengthening collaboration that ultimately increases the creativity, skills, knowledge and research capability of graduates.
More than ever, universities and policymakers are paying attention to faculty members' engagement in industries' projects because university-industry collaboration (UIC) is seen as the key to economic development. However, the UIC differs from country to country , and researchers may have different motivations. This study explored the relationship between university researchers' motivations and varied UIC channels. A questionnaire was administered to the relevant faculty in public universities in two cross-border regions of Portugal and Spain. Drawing on data gathered from 841 researchers, the results reveal differences in these academics' motivations to engage in different channels. Pecuniary motivations (i.e., access to funding and commercialization) drive UIC through joint and contract research, while non-pecuniary motivations (i.e., learning opportunities and access to resources) inhibit cooperation through the same two engagement channels. In addition, joint and contract research involvement also depends on researchers' age, academic status, department size, and field of study. This study provides empirical evidence on the motivations and channels of UIC in two cross-border regions of Portugal and Spain. Furthermore, it presents important results for universities and policymakers who need to increase motivation and improve UIC channels.
Purpose
The purpose of this paper is to examine the evolution of the literature on technology transfer and culture, identifying the main contents of the current body of knowledge encompassing culture and technology transfer (TT), thus contributing to a better understanding of the relationship between TT and culture based on bibliometric and multivariate statistical analyses of the relevant body of literature.
Design/methodology/approach
Data for this study were collected from the Web of Science (WoS) Core Collection database. Based on a bibliometric analysis and in-depth empirical review of major TT subjects, supported by multivariate statistical analyses, over 200 articles were systematically reviewed. The use of these methods decreases biases since it adds rigor to the subjective evaluation of the relevant literature base.
Findings
The exploratory analysis of the articles shows that first, culture is an important topic for TT in the literature; second, the publication data demonstrate a great dynamism regarding the different contexts in which culture is covered in the TT literature and third, in the last couple of years the interest of stimulating a TT culture in the context of universities has continuously grown.
Research limitations/implications
This study focuses on culture in the context of TT and identifies the main contents of the body of knowledge in the area. Based on this first insight, obtained through more detailed bibliometric and multivariate analyses, it is now important to develop and validate a theory on TT culture, emphasizing the dimensions of organizational culture, entrepreneurial culture and a culture of openness that fosters economic and societal spillovers, and to link those dimensions to the performance of TT activities.
Practical implications
From the practical point of view, managers in companies and universities should be aware of the importance of identifying those dimensions of culture that contribute most to the success of their TT activities.
Originality/value
Despite several literature reviews on the TT topic, no studies focusing specifically on culture in the context of TT have been developed. Therefore, given the multifaceted nature of the research field, this study aims to expand and to deepen the analysis of the TT literature by focusing on culture as an important and commonly cited element influencing TT performance.
The burgeoning interest in university-industry collaborations (UIC) has sparked significant attention in both management practice and research. However, despite extensive efforts to identify the determinants of UIC, the majority of studies have predominantly focused on the motivations of academic researchers and limited UIC channels. This study aims to delve deeper into the influence of five factors—structural, behavioral, motivational, attitudinal and policy-related on firms' decisions to collaborate with universities across five collaboration forms: research partnership, researcher service, technology transfer, utilization of university facilities, and human resource transfer. The research draws upon original microdata from the Thai Community Innovation survey, encompassing 8,701 firms and spanning the years 2015, 2017, and 2018. By employing a multivariate probit model, the results unveil that Thai firms perceiving universities as innovation sources are inclined to engage with them irrespective of the UIC channels. However, the effects of structural, behavioral, and motivational factors differ when influencing industry participation in various UIC modes. Thus, this research significantly contributes to the UIC literature by offering both theoretical and practical insights. The nuanced understanding of the factors influencing collaborative decisions can inform policymakers and managers seeking to foster effective university-industry partnerships. The identified implications underscore the need for a more tailored approach, recognizing the diversity of influences on UIC, thereby advancing both academic discourse and practical strategies in the field.
University-Industry Linkage (UIL) is the interaction of academic or research universities and industries of different sectors for complementary benefits. This paper presents the results of a study conducted to understand the present status and challenges of UIL in the Regional State of Tigray, Ethiopia. Using convergent parallel mixed research design, the study addressed two research questions: (1) what is the status of UIL in the Regional State of Tigray, Ethiopia? (2) what are the UIL challenges facing universities and industries in the Regional State of Tigray, Ethiopia? Respondents were recruited from two universities and eight industries of different business areas including service, manufacturing, finance and energy. A survey questionnaire and interview protocols were developed by adapting items used in previous studies and distributed to a sample size of 1350. The findings show that there are occasional collaborations between the universities and industries in the Region mostly focusing on internship and training. Although communications and meetings are conducted between the universities and industries to create UIL opportunities in Tigray, signed collaboration agreements remain mostly on the shelf mainly due to lack of due attention and commitment from both sides in taking the step forward. Therefore, awareness creation measures and sound policy framework and guidelines should be in place for effective and practical collaborations to exist and get realized.
Knowledge transfer in university-industry collaboration (KTUIC) has been a hot issue of concern in recent years. Based on 874 articles published in the core collection of Web of Science, this paper conducts an in-depth bibliometric and visual analysis in terms of literature distribution, cooperation network, co-citation, knowledge base, and research hotspots analysis. The results show that the number of annual publications has shown an approximate exponential growth in the past decades. The UK is the most critical node in cross-border cooperation. Alessandro Muscio, with 11 publications, and Henry Etzkowitz, with 793 citations, are the most prolific and cited authors respectively. Research Policy has the highest frequency of citations. The knowledge base of KTUIC includes UIC and knowledge transfer, basic theories of U-I relationships, university TTOs, Bayh-Dole Act and university patenting, and individuals in university technology transfer. Research hotspots mainly focus on the related issues of third mission and entrepreneurial universities. Additionally, we also propose the future research agenda of KTUIC from the perspective of five knowledge bases. These findings contribute to a deeper understanding of the development status and core issues in KTUIC, and offer valuable guidance for future research directions.
Public research organizations (PROs) and universities receive large amounts of public funding for the generation and transmission of knowledge, and companies contract external knowledge from both. An important question for the management of a firm's R&D and for public innovation policies is: What is more beneficial for the generation of firm innovations, external knowledge created by PROs or by universities? In this paper, we assess the impact of external knowledge from PROs versus universities on firm innovativeness. We use information on R&D acquisitions from a panel dataset of more than 10,000 Spanish firms from 2005 to 2014. We show that external knowledge from PROs and universities increases firm innovativeness. Our results suggest that knowledge generated by PROs is more sensitive to the absorptive capacity of the firm than knowledge generated by universities. This has implications for research policy, R&D management, and organizational strategies of firms’ knowledge activities. Firms with low absorptive capacities benefit relatively more from knowledge generated by universities than from knowledge generated by PROs. Moreover, R&D managers should plan both their external and internal R&D if they acquire external R&D from PROs.
Between 1995 and 2007, the Irish Government implemented a variety of measures designed to enhance the infrastructure and profile of research activities in Irish Higher Education Institutions (HEIs). The aim was to foster a culture of innovation-led academic entrepreneurship and, thereby, develop links between HEIs and indigenous industry in Ireland, with particular emphasis on research and development (R&D) links. This paper analyses the barriers and stimulants to the creation and maintenance of links between HEIs and industry and focuses specifically on R&D and consultancy links. The findings indicate that indigenous high-tech firms are not the key benefactors of Ireland’s science and technology (S&T) base. Whilst firms are engaging in innovative activities, HEIs are excluded from such developments. Teaching and training links constitute the most common form of interaction, not R&D links and consultancy links, as might have been expected.
Purpose
The purpose of this study is to investigate university–industry partnerships in Armenia from the viewpoint of universities. By doing so, it contributes to the existing literature on university–industry collaboration by identifying and addressing the specific challenges that impede the establishment of successful university–industry partnerships in Armenia and other post-Soviet countries.
Design/methodology/approach
A comprehensive literature review was conducted to examine the barriers, benefits and institutional, functional framework of collaboration. Additionally, this study used a survey methodology to gather data from faculty managing staff members at six Armenian higher educational institutions on various aspects of university–industry collaboration as well as the perceptions and experiences of the participants.
Findings
The results show that the effectiveness and applicability of the university–industry collaboration channels and institutional structures in six higher educational institutions are limited. Specifically, the channels that rely on academic entrepreneurship and innovation were found to be currently unviable. Moreover, the existence of spin-offs and start-ups is notably absent. Furthermore, limited access to funding and inadequate entrepreneurial support systems pose significant barriers to developing university–industry partnerships in Armenian reality.
Originality/value
This study represents a pioneering effort within the context of Armenian higher educational institutions, as it is the first time a survey has been organized to specifically investigate the topic of university–industry partnerships. Before this study, there was a lack of empirical research and data collection on this topic in Armenian higher education settings. Therefore, this research holds significant originality and contributes to filling the existing gap in knowledge regarding university–industry partnerships in Armenia. The research is shedding light on a previously unexplored area and providing a valuable contribution to the field of university–industry collaboration research in Armenia and other post-Soviet countries.
Due to the increasing innovation pressure of industry, joint research between industry and science has become enormously important in recent years. Increasing complexity of the industry offer, the digital transformation and the upcoming of new forms of work, collaboration increasingly switches from classic bilateral collaborations between one company and one scientific partner towards multilateral research cooperation. A wide range of collaborative research formats are existing, facilitating bilateral collaboration between industry and research to aim a defined goal and facilitating mutual benefit. Accompanying research on collaboration performance exists for bilateral collaborative initiatives. However, still little research on formats for multilateral research cooperation exists. In the following study we want to identify existing forms of multilateral cooperation between industry and science and analyse them according to their collaboration performance in the age of digitalisation. Therefore, in a first step, desktop research was conducted to identify real, existing collaborations between industry and science. Within those, relevant key characteristics which affects the performance of multilateral collaboration were derived (such as “number of partners”, “partnership structure”, “funding model”, “contractual arrangements”). In the second step, seven representatives of real multilateral collaborations were interviewed to characterise their research cooperations. The survey captures different perspectives of research collaboration management, the business partners, and the partners from academia. The third step involved an analysis of the interview results, which finally were merged with the findings from literature and formed the foundation for defining the ten relevant characteristics of successful research collaborations.
Актуальность: статья посвящена анализу роли научно-исследовательской деятельности в становлениии развитии профессиональных и личностных компетенций обучающихся вузов, а также исследованиюособенностей их профессиональной мотивации в процессе взаимодействия в системе «вуз−работодатель−студент». Эти компоненты обучения в вузе являются ключевыми для формированияпрофессиональных знаний, умений и навыков студентов, а также их интереса и потребности в дальнейшем росте собственного потенциала. Цель: проанализировать особенности формирования компетенций студентов в ходе их участия в научно-исследовательской работе; выявить мотивацию их деятельности в студенческих научных объединениях; определить оценки научно-исследовательской и учебной деятельности, а также их взгляды на свое профессиональное будущее. Методы: количественная стратегия социологического исследования, метод анкетирования. В ходе опроса соблюдались все процедурные требования к реализации метода анкетирования в практике эмпирического исследования. Выборка – репрезентативная, сплошная, опрошены все студенты, являющиеся участниками студенческих научных объединений Иркутского национального исследовательского технического университета. Результаты: определены компетенции и ценности, являющиеся базовыми для формирования профессионализма студента – будущего участника взаимодействия на рынке труда. Оценена роль системы взаимодействия «вуз–работодатель–студент». Сотрудничество вуза и работодателей в целом может рассматриваться как перспективное и эффективное направление, усиливающее процесс формирования научно-исследовательских и профессиональных компетенций студентов. Успешность функционирования данной системы отношений в рамках вузовской среды напрямую влияет на развитие профессиональной мотивации обучающихся.
This paper examines participation in technology transfer activity using data on individual researchers from the medical schools of two prominent universities, Duke University and Johns Hopkins University. The paper provides a model of participation in technology transfer by faculty members within academic departments and tests hypothesis about the effects of individual attributes, organizational incentives and social interactions on the decision to participate in technology transfer. Our results suggest that the adoption of strategic initiatives like technology transfer is a function of the norms at the institutions where the individual trained; the observed behavior of their chairman and the observed behavior of similar individuals.
American universities are experimenting with new mechanisms for promoting the commercialization of academic research and generating revenue from university intellectual property. This paper discusses mechanisms available to universities in managing the commercialization of intellectual property, considering equity as a technology transfer mechanism that offers advantages for both generating revenue and aligning the interests of universities, industry and faculty. Employing data from a national survey of Carnegie I and Carnegie II institutions, we document the recent rise in university equity holdings. We present and estimate a model that considers the university's use of equity to be a function of behavioral factors related to the university's prior experiences with licensing, success relative to other institutions, and the organization of the technology transfer office, as well as structural characteristics related to university type.
A small sample of 38 Advanced Technology Projects funded between 1993 and 1996 are surveyed to explore the reasons for university non-participation, or, in the cases where they did participate, whether the partnerships encountered any difficulties from their participation. 32 percent report that intellectual property issues were an insurmountable barrier to university participation. Such barriers are more likely when the ATP share of funding is high and when the expected duration of the research is relatively short. They are also somewhat more likely for projects involving chemical technology, and when industrial participants have had previous experience with universities as research partners. These difficulties over IP may arise because the cultures in the two institutional forms differ, or because the original ATP guidelines do not recognize the existence of the Bayh-Dole Act (which grants universities title to inventions made by their employees using outside funding).
The Triple Helix of university-industry-government relations provides a neo-evolutionary model of the process of innovation that is amenable to measurement. Economic exchange, intellectual organization, and geographical constraints can be considered as different dynamics that interact in a knowledge-based economy as a complex system. Differentiation spans the systems of innovation, while performative integration enables organizations to retain wealth from knowledge. Because of the systematic organization of interfaces among the subsystems under study, different perspectives can be expected in the reflection. Consequences for the heuristics, the research design, and normative implications are specified and the organization of the issue is further explained.
Professorial entrepreneurship has recently attracted much attention. This paper draws upon historical research, a survey of faculty, and an Internet-based methodology for identifying professorial affiliations with entrepreneurial firms at two of the premier electrical engineering and computer science departments in the US, The University of California, Berkeley and Stanford. We employ the concept of “nested embeddedness” to explain why the faculty members in these two institutions have different levels of entrepreneurship and corporate involvement. EE&CS faculty at both universities were found to be socially embedded in departments and disciplines that supported and placed value on entrepreneurial activities. However, while being embedded in a university environment with a history of success and high level of support for entrepreneurship, EE&CS faculty at Stanford had a significantly greater level of corporate involvement, including the founding of start-ups. Although significantly less than Stanford, the level of corporate involvement among EE&CS faculty at Berkeley was also substantial. This suggests that being embedded in an academic department and disciplines with cultures that are supportive of entrepreneurial activity can help counteract the disincentives created by a university environment that is not strongly supportive of these activities.
The Triple Helix of university–industry–government relations is compared with alternative models for explaining the current research system in its social contexts. Communications and negotiations between institutional partners generate an overlay that increasingly reorganizes the underlying arrangements. The institutional layer can be considered as the retention mechanism of a developing system. For example, the national organization of the system of innovation has historically been important in determining competition. Reorganizations across industrial sectors and nation states, however, are induced by new technologies (biotechnology, ICT). The consequent transformations can be analyzed in terms of (neo-)evolutionary mechanisms. University research may function increasingly as a locus in the “laboratory” of such knowledge-intensive network transitions.
Previous research has indicated that investment in R&D by private firms and universities can lead to knowledge spillover, which can lead to exploitation from other third-party firms. If the ability of these third-party firms to acquire knowledge spillovers is influenced by their proximity to the knowledge source, then geographic clustering should be observable, especially in industries where access to knowledge spillovers is vital. The spatial distribution of innovation activity and the geographic concentration of production are examined, using three sources of economic knowledge: industry R&D, skilled labor, and the size of the pool of basic science for a specific industry. Results show that the propensity for innovative activity to cluster spatially is more attributable to the influence of knowledge spillovers and not merely the geographic concentration of production. (SFL)
We use the results of the policies, appropriation and competitiveness in Europe (PACE) 1993 survey of Europe's largest firms to explore the effect of proximity on knowledge flows from affiliated firms, suppliers, customers, joint ventures, competitors and public research organisations to innovative firms. The focus is on the last. First, we find that public science is among the most important sources of technical knowledge for the innovative activities of Europe's largest industrial firms. Then, after comparing the PACE results with the Community Innovation Survey II (1997) and the Carnegie Mellon Survey (1994), we use the unique information from the PACE survey on the geographic location of knowledge sources and the methods used to access them to develop an econometric analysis of proximity and location. The importance of proximity for sourcing knowledge from public research increases with the quality and output of domestic public research organisations and the importance given to public science by the respondents. It declines with an increase in the firm's R&D expenditure, activity in the North American market and the importance to the firm of codified basic research results. Surprisingly, firms that find informal contacts to be an important method for acquiring public research results are more likely to find proximity less important, even though proximity allows firms to access tacit knowledge. This effect is primarily limited to European countries, suggesting the development of a 'European Research Area'.
We draw on qualitative data derived from field work on two university campuses to develop an explanation for widely disparate rates of new invention disclosure. We argue that faculty decisions to disclose are shaped by their perceptions of the benefits of patent protection. These incentives to disclose are magnified or minimized by the perceived costs of interacting with technology transfer offices and licensing professionals. Finally, faculty considerations of the costs and benefits of disclosure are colored by institutional environments that are supportive or oppositional to the simultaneous pursuit of academic and commercial endeavors. Copyright 2001 by Kluwer Academic Publishers
The relationship between age and the publishing productivity of Ph.D. scientists is analyzed using data from the Survey of Doctorate Recipients (National Research Council) and the Science Citation Index. The longitudinal nature of the data allows for the identification of pure aging effects. In five of the six areas studied, life-cycle aging effects are present. Only in particle physics, where scientists often speak of being on a "religious quest," is the indication that scientific productivity is not investment-motivated. Vintage effects are also considered. The expectation that the latest educated are the most productive is not generally supported by the data. Copyright 1991 by American Economic Association.
We introduce a new hybrid approach to joint estimation of Value at Risk (VaR) and Expected Shortfall (ES) for high quantiles of return distributions. We investigate the relative performance of VaR and ES models using daily returns for sixteen stock market indices (eight from developed and eight from emerging markets) prior to and during the 2008 financial crisis. In addition to widely used VaR and ES models, we also study the behavior of conditional and unconditional extreme value (EV) models to generate 99 percent confidence level estimates as well as developing a new loss function that relates tail losses to ES forecasts. Backtesting results show that only our proposed new hybrid and Extreme Value (EV)-based VaR models provide adequate protection in both developed and emerging markets, but that the hybrid approach does this at a significantly lower cost in capital reserves. In ES estimation the hybrid model yields the smallest error statistics surpassing even the EV models, especially in the developed markets.
We use the results of a 1993 survey of EuropeÕs largest firms to explore the effect of proximity on knowledge flows from suppliers, customers, joint ventures, competitors and public research organisations to innovative firms. The focus is on the latter, since they are an essential component of National Innovation Systems. The importance of proximity for sourcing knowledge from public research increases with the quality and output of domestic public research organisations and declines with activity in the North American market, an increase in the firmÕs R&D expenditures, and the importance of codified knowledge to the firm.
This paper explores one of Edwin Mansfield’s enduring interests: the interface between academia and industry. It highlights some key lessons regarding the management of university-based spin-outs, drawing on a variety of sources. I highlight the challenges that the spin-off process poses, the impracticality of directly financing firms through internal venture funds, and the ways in which universities can add value to faculty ventures.
Many recent studies, reports, and congressional bills prescribe a new purpose for this country`s federal laboratories. They maintain that the new customer of the federal labs should be U.S. industry and that the labs` new mission should be technology transfer. The common conclusion is that a significant portion of the labs` budgets should be directed toward joint R&D with industry. President Clinton and Vice President Gore also want to encourage the nations`s 726 federal laboratories to act as partners with industry whenever possible. They recommend that Department of Defense, Department of Energy, and National Aeronautics and Space Administration labs be reviewed and that 10 to 20 percent of their budgets be redirected to joint R&D. Legislators seem to agree. The initial question is how the public investment in these resources can best be utilized for national benefit. There are three broad policy options: Abolish the nuclear weapons and defense labs and apply their funding to industry and universities. Reduce investment in the weapons and defense labs, selectively eliminating those whose missions are obsolete and consolidating those that remain around a more limited set of missions. Or redirect the weapons and defense labs toward nondefense missions such as energy, environment, and U.S. competitiveness.
Despite increasing interest amongst policy makers and academics, there have been few attempts at gathering systematic data on the nature and extent of research collaborations between universities and industry. This paper uses joint scientific publications as an indicator of such collaborations in the UK over 20 years. It finds that, although there has been a rapid increase in the volume of university-industry collaborations since the 1980s, the biggest increases were before the major policy measures of the mid-1990s. An important factor would appear to be the growing need for firms, especially non-British firms, to collaborate with leading-edge academic research in promising areas of new technology. Copyright , Beech Tree Publishing.
A rapid rise in the incidence of strategic research partnerships (SRPs) involving firms, universities, non-profit organizations, and public agencies has stimulated an important public policy debate regarding whether these relationships enhance economic performance. In this paper, we present a taxonomy of SRPs and assess empirical studies of their effectiveness. We also identify data limitations that can preclude an accurate evaluation of the private and social returns to SRPs. We provide numerous suggestions for the collection and processing of additional data that would greatly improve our understanding of how these partnerships affect economic performance at the firm, industry, and aggregate levels. Copyright , Beech Tree Publishing.
This study examines institutional characteristics of universities from which scientists in private industry procure research information. Results indicate that research expenditures, faculty quality and salary, and most importantly for policy purposes, land-grant status are significantly associated with the utilization of university scientific research by firms. Urban location and the presence of cooperative research structures do not have predictive value.
There has been no systematic study of the characteristics of the universities and academic researchers that seem to have contributed most to industrial innovation. Nor do we know how such academic research has been funded. This paper, based on data obtained from 66 firms in seven major manufacturing industries and from over 200 academic researchers, sheds new light on the sources, characteristics, and financing of academic research underlying industrial innovation. The findings should be of interest to economists concerned with technological change and to policy makers attempting to increase the economic payoff from the nation's academic research.
The purpose of this paper is to build up a theoretical framework to study university-industry interorganisational relations (U-1 IOR) and formulate hypotheses which will be tested on empirical data in a future research phase. Then, a taxonomy for university-industy relationships is proposed. Finally, the problem of evaluating relationships between universities and industries by defining the concept of ‘relationship performance’ is addressed.
In this paper, we use data from the Carnegie Mellon Survey on industrial R&D to evaluate for the U.S. manufacturing sector the influence of "public"(i.e., university and government R&D lab) research on industrial R&D, the role that public research plays in industrial R&D, and the pathways through which that effect is exercised. We find that public research is critical to industrial R&D in a small number of industries and importantly affects industrial R&D across much of the manufacturing sector. Contrary to the notion that university research largely generates new ideas for industrial R&D projects, the survey responses demonstrate that public research both suggests new R&D projects and contributes to the completion of existing projects in roughly equal measure overall. The results also indicate that the key channels through which university research impacts industrial R&D include published papers and reports, public conferences and meetings, informal information exchange, and consulting. We also finnd that, after controlling for industry, the influence of public research on industrial R&D is disproportionately greater for larger firms as well as start-ups.
In this paper we explore the degree to which patents are representative of the magnitude, direction, and impact of the knowledge spilling out of the university by focusing on the Massachusetts Institute of Technology (MIT), and in particular, on the Departments of Mechanical and Electrical Engineering. Drawing on both qualitative and quantitative data, we show that patenting is a minority activity: a majority of the faculty in our sample never patent, and publication rates far outstrip patenting rates. Most faculty members estimate that patents account for less than 10% of the knowledge that transfers from their labs. Our results also suggest that in two important ways patenting is not representative of the patterns of knowledge generation and transfer from MIT: patent volume does not predict publication volume, and those firms that cite MIT papers are in general not the same firms as those that cite MIT patents. However, patent volume is positively correlated with paper citations, suggesting that patent counts may be reasonable measures of research impact. We close by speculating on the implications of our results for the difficult but important question of whether, in this setting, patenting acts as a substitute or a complement to the process of fundamental research.
This paper addresses research in the life sciences, responsible for significant national expenditures for scientific investigations funded by both the federal government and industry. Our investigation examines faculty members' involvement with industry in entrepreneurial ways that is, involved in translating their research into potentially marketable knowledge or products. First, this study examines whether there are differences in entrepreneurial behaviour between clinical and non-clinical faculty in the life sciences with industry relationships, and, second, to discover any linkage between entrepreneurship and secrecy or productivity in different ways for clinical and non-clinical faculty. The study is based on survey responses of a national sample of 4,000 clinical and non-clinical life sciences faculty in 49 U.S. research universities. The results show non-clinical faculty as more involved at the back end. The more entrepreneurial end of commercialization while clinical faculty are involved at the back end. The more entrepreneurial faculty (non-clinical) are more likely to be secretive about their research. Clinical faculty are less likely to have been denied access to research results or products. Entrepreneurial faculty are not less productive in their faculty roles. This investigation is preliminary in that it addresses one large area of academic research but excludes fields with longer historical relationships with industry.
This paper explores one of Edwin Mansfield''s enduring interests: the interface between academia and industry. It highlights some key lessons regarding the management of university-based spin-outs, drawing on a variety of sources. I highlight the challenges that the spin-off process poses, the impracticality of directly financing firms through internal venture funds, and the ways in which universities can add value to faculty ventures.
This article examines the emerging ‘technology transfer’ role US academics are expected to play in economic development, what specific roles they believe they can play in industrial innovations, and how they might go about collaborating with private industry. Based on a national survey response of approximately 1000 faculty members at research-intensive universities it concludes that US academics in the 1990s believe that they are more favorably disposed than in the 1980s toward closer university-industry collaboration. A majority of the respondents supports the idea that their universities participate actively in local and regional economic development, facilitate commercialization of academic research, and encourage faculty consulting for private firms. A majority of these respondents, however, refuses to support the idea of their universities getting involved in close business partnership with private industry by way of, for example, start-up assistance or equity investment. Of various organizational and motivational underpinnings analyzed from the data, two factors stand out as central to the current debate on university transfer: one is the perception of declining federal R&D support, which threatens the vitality of their research enterprise, and the other is the impact of close university-industry cooperation, which is likely to interfere with academic freedom — the freedom to pursue long-term, disinterested, fundamental research. A search for the boundaries of university-industry collaboration is, therefore, seen as a balancing act between these two competing concerns.
The set of technological opportunities in a given industry is one of the fundamental determinants of technical advance in that line of business. We examine the concept of technological opportunity and discuss three categories of sources of those opportunities: advances in scientific understanding and technique, technological advances originating in other industries and in other private and governmental institutions, and feedbacks from an industry's own technological advances. Data from the Yale Survey on Industrial Research and Development are used to measure the strength of various sources of technological opportunity and to discern interindustry differences in the importance of these sources. We find that interindustry differences in the strength and sources of technological opportunities contribute importantly to explanations of cross-industry variation in R&D intensity and technological advance.
In recent years, the co-operation between industrial firms and universities has increased considerably, but the interaction pattern in different technological fields is not uniform. In science-based fields, university departments have a distinct focus on basic research and the major interest of industry is the observation of science. In less science-based fields, the solution of technical problems is a major concern of industry. In all fields, the exchange of knowledge in techno-scientific communities is a crucial element of interaction. In Germany, strong intra-disciplinary ties between universities and industry in mechanical engineering obviously imply an insufficient openness to, and integration of, new technologies. The particular combination of a long-standing culture of co-operation and the economic success in the mechanical industry can be interpreted in terms of a specific path-dependant evolution of a stable sector of the national system of innovation, but with the tendency to lock-in effects.
We present quantitative and qualitative evidence on the relative productivity of university technology transfer offices (TTOs). Our empirical results suggest that TTO activity is characterized by constant returns to scale and that environmental and institutional factors explain some of the variation in performance. Productivity may also depend on organizational practices. Unfortunately, there are no quantitative measures available on such practices, so we rely on inductive, qualitative methods to identify them. Based on 55 interviews of 98 entrepreneurs, scientists, and administrators at five research universities, we conclude that the most critical organizational factors are faculty reward systems, TTO staffing/compensation practices, and cultural barriers between universities and firms.
This paper presents an empirical analysis of the determinants of research cooperation between firms and Public research organisations (PROs) for a sample of innovating small and medium-sized enterprises (SMEs). The econometric analysis is based on the results of the KNOW survey carried out in seven EU countries during 2000. In contrast to earlier works that provide information about the importance of PROs’ research, we know the number of firm/PRO collaborative research and development (R&D) projects. This allows us to study the determinants of firm collaboration with PROs in terms of both the propensity of a firm to undertake R&D projects with a university (do they cooperate or not) and the extent of this collaboration (number of R&D projects). Two questions are addressed. Which firms cooperated with PROs? And what are the firm characteristics that might explain the number of R&D projects with PROs? The results of our analysis point to two major phenomena. First, the propensity to forge an agreement with an academic partner depends on the ‘absolute size’ of the industrial partner. Second the openness of firms to the external environment, as measured by their willingness to search, screen and signal, significantly affects the development of R&D projects with PROs. Our findings suggest that acquiring knowledge through the screening of publications and involvement in public policies positively affects the probability of signing an agreement with a PRO, but not the number of R&D projects developed. In fact, firms that outsource research and development, and patent to protect innovation and to signal competencies show higher levels of collaboration.
The results of this study provide insight into why some universities generate more new companies to exploit their intellectual property than do others. We compare four different explanations for cross-institutional variation in new firm formation rates from university technology licensing offices (TLOs) over the 1994–1998 period—the availability of venture capital in the university area; the commercial orientation of university research and development; intellectual eminence; and university policies. The results show that intellectual eminence, and the policies of making equity investments in TLO start-ups and maintaining a low inventor’s share of royalties increase new firm formation. The paper discusses the implications of these results for university and public policy.
The interface between industry and the universities is of key importance in the promotion of technological change in many industries. There is intense interest in the characteristics of universities that have contributed most importantly to industrial innovation in various fields, but unfortunately very little systematic study has been devoted to this important and complex topic. Also, we know little about the factors determining which universities firms will support to do R&D of various types. Based on data obtained from a carefully selected sample of major US firms in the electronic, information processing, chemical, petroleum, pharmaceutical, instruments, and metal industries, this paper sheds new light on these topics.
Pemetrexed (Alimta; Eli Lilly and Company, Indianapolis, IN) is a new antifolate drug with activity at multiple points in folate metabolism, including thymidylate synthase, dihydrofolate reductase, and glycinamide ribonucleotide formyltransferase. In this way it inhibits the de novo synthesis of both purines and pyrimidines. In phase II studies, pemetrexed has shown good clinical activity as single-agent therapy in patients with advanced breast cancer with or without prior treatment, including patients with prior anthracycline and taxane treatment. Toxicities are primarily neutropenia, mucositis, and skin rash. Hematologic toxicities are markedly reduced by supplementation with vitamin B(12) and folate. Skin rash is ameliorated with prophylactic corticosteroid treatment. Pemetrexed is a promising agent in breast cancer and warrants further investigation in this setting.
We present quantitative and qualitative evidence (field research) on university technology transfer offices (TTOs). These offices negotiate licensing agreements with firms to commercialize university-based technologies. A stochastic frontier production function framework is used to assess the relative productivity of 113 university TTOs. Our field research provided a useful reality check on the specification of the econometric model. The empirical findings imply that licensing activity is characterized by constant returns to scale. Environmental and institutional factors appear to explain some of the variation in TTO efficiency. Relative productivity may also depend on organizational practices in university management of intellectual property, which potentially attenuate palpable differences in the motives, incentives, and organizational cultures of the parties to licensing agreements. Unfortunately, there are no existing data on such practices, so we rely on inductive, qualitative methods to identify them. We present detailed information on our use of these methods. This information may be useful to economists who are contemplating fieldwork. Based on 55 interviews of managers/entrepreneurs and administrators at five research universities, we conclude that the most critical organizational factors are likely to be reward systems for faculty, TTO staffing and compensation practices, and actions taken by administrators to extirpate informational and cultural barriers between universities and firms.
The efforts of a number of OECD governments to emulate the Bayh-Dole Act of 1980, which permitted United States institutions receiving government research funds to patent their inventions, are critiqued.This critique is based on a review of recent research on the characteristics of the university-industry knowledge exchange and technology transfer.Following this review, the effects of the Bayh-Dole Act on patenting are discussed. Although many observers have argued that Bayh-Dole facilitated university-industry technology transfer, the effects of the measure are not wholly positive: increased university patenting could hinder downstream research and product development.It could also encourage academic researchers to pursue "open science," which could in turn lead to publication delays and withholding of data and materials.Even though the supposedly catalytic effects of the Bayh-Dole Act are perhaps overrated, OECD countries such as Denmark, Canada, Germany, Sweden, and Japan have adopted policies similar to Bayh-Dole; ironically, these policies often differ from one another and from Bayh-Dole itself.OECD countries wishing to generate higher levels of university-industry interaction would do well to stop attempting to emulate Bayh-Dole and to focus on reforms that support inter-institutional competition, as well as the external contributors to business creation and technology commercialization.(SAA)
University technology transfer activities are increasingly important as a source of regional economic development and revenue for the university. We use regression analysis, a two-stage model and the most recent data to examine the determinants of technology transfer. Our analysis strongly support four factors, not previously examined in the literature, enhancing university technology transfer: greater rewards for faculty involvement in technology transfer, location of the university in a region with a concentration of high technology firms, a clear university mission in support of technology transfer and the experience of the university's technology transfer office. Copyright 2003 by Kluwer Academic Publishers
In recent years interaction between universities and the business sector and the role of these collaborations in fostering innovation has received greater attention. This paper analyzes different types of interactions between the two sectors from the perspectives of universities and firms. The three major research questions address the frequency of different types of interactions, the benefits that companies derive from interaction with universities and determinants of interaction for both sectors. Two different surveys form the empirical base for this paper: one among innovative firms in Austria, one among all Austrian university departments. The methodologies we use are analyses of variance and logistic regressions. Our results demonstrate that the main channel of knowledge transfer from universities to the business sector still occurs through the mobility of human capital. The major barriers of interaction lie in the differences between "cultures" of the two spheres as well as lack of information at the side of firms. Copyright 2001 by Kluwer Academic Publishers
Examines the growth and development of the biotechnology industry, looking at the effects of individual scientists, universities, and federal research support. Specific focus is on the development of the underlying science in biotechnology and the location of those individuals involved in the development of this science. Data used in this analysis were collected from 751 firms that existed in 183 economic regions of the United States for a fourteen year period (1976-1989). A set of 327 star scientists were also identified. These scientists accounted for approximately 17.3% of published articles in this field as of early 1990. The data is analyzed both over the long-run and on an annual basis. Results using the long-run model show that location of the development of the biotechnology industry in the 1980's was strongly influenced by intellectual human capital variables. Star scientists that play an important role in the process of spillover and geographic agglomeration are able to be identified. Results of the annual model also show support for the strong role that intellectual human capital played in determining the direction of the biotechnology industry. Basic scientific research is shown to be extremely valuable in this industry. Although there was a tendency for intellectual human capital to thrive around universities, the stronger determinant of industry location was the positioning of scientists with high research productivity. (SRD)
In recent years, there has been a substantial rise in the rate of commercialization of university-based technologies — through patenting, licensing, research joint ventures, and the formation of startup companies. We have also witnessed an increase in investment in science parks and other property-based institutions that facilitate the transfer of technology from
Licensing activity of US universities has increased substantially in recent years. We examine this increase focusing on the ‘productivity’ and ‘changes in productivity’ of licensing activity. While it is generally acknowledged that there has been a dramatic increase in licensing, there is little understanding of the licensing process as it relates to university characteristics, nor is there evidence on the extent to which this is the result of increased resources devoted to commercialization or whether it stems from other factors. This paper employs data envelopment analysis (DEA) combined with regression analysis to examine the overall productivity of university licensing activity as well as the productivity of individual universities. We find that licensing has increased for reasons other than increases in overall university resources. Given input levels, universities are today more commercially productive than they were in the recent past; we propose reasons for this shift and analyze factors associated with the shift and factors associated with relative levels of commercialization.
Following the approach suggested by Favero and Rovelli (2002), I estimate a three-equations system for different sub-samples for Canada. The results indicate that the preferences of the monetary authority have changed between the different regimes. In particular, the parameter associated to the implicit target of inflation has been reduced significantly. The macroeconomic conditions from the side of the aggregate demand have been more favorable than those related to the aggregate supply. The standard deviation of the monetary rule suggests that it has been conducted successfully in the last regime.
We examine the interplay of the three major university actors in technology transfer from universities to industry: the faculty, the technology transfer office (TTO), and the central administration. We model the faculty as an agent of the administration, and the TTO as an agent of both the faculty and the administration. Empirical tests of the theory are based on evidence from our survey of 62 US research universities. We find that the TTOs reported licensing objectives are influenced by their views of faculty and administration, which supports the assumption that the TTO is a dual agent. The theory yields predictions for whether or not faculty disclose inventions and if so, at what stage, which in turn affects license contract terms. We also examine how the portion of inventions disclosed at different stages varies with faculty quality. Quality is found to be inversely related to the share of license income allotted to faculty.
Analysis of University–Industry research collaborations in the UK: preliminary results of a survey of university researchers, SPRU Report Why do some universities gen-erate more start-ups than others?
- D Este
- P Nesta
- L Patel
D'Este, P., Nesta, L., Patel, P., 2005 Analysis of University–Industry research collaborations in the UK: preliminary results of a survey of university researchers, SPRU Report, May 2005, http://www.sussex.ac.uk/spru/documents/deste report.pdf. Di Gregorio, D., Shane, S., 2003. Why do some universities gen-erate more start-ups than others? Research Policy 32 (2), 209– 227.
Technology transfer and the aca-demic department: who participates and why? In: Paper presented at the DRUID Summer Conference
- J Bercovitz
- M Feldman
Bercovitz, J., Feldman, M., 2003. Technology transfer and the aca-demic department: who participates and why? In: Paper presented at the DRUID Summer Conference 2003, Copenhagen, June 12–14.
Technology Integration: making Critical Choices in a Dynamic World
- M Iansiti
Iansiti, M., 1998. Technology Integration: making Critical Choices in a Dynamic World. Harvard Business School Press, Cambridge, MA.
On the economics and analysis of diver-sity. SPRU Electronic Working Paper No. 28
- A Stirling
Stirling, A. (1998): On the economics and analysis of diver-sity. SPRU Electronic Working Paper No. 28. University of Sussex, October 1998: http://www.sussex.ac.uk/Units/spru/ publications/imprint/sewps/sewp28.