Knowledge nations are keeping knowledge to themselves.
A report by Deloitte 2018 shows that less than 5% of industry forms collaborations with universities in NZ and only 3% in Australia, which puts us a long way behind other developed countries.
Bridging the ‘missing middle’: a design based approach to scalingdebbieholley1
Holley, D., Peffer, G. Santos, P., and Cook, J. (2014). Bridging the ‘missing middle’: a design based approach to scaling. Presented to the ALT-Conference, September 2014
A paper contributing to EU learning layers project,:Scaling up Technologies for Informal Learning in SME Clusters
A 9.9 million EU Framework Project (2012-2016)
Abstract
Taking innovation from concept through to scalable delivery is complex, contested and an under-theorised process. In this paper we outline approaches to scaling that have influenced in our work in the EU Learning Layers Integrating Project, a consortium consisting of 17 institutions from 7 different countries. The two industries identified for the initial work are the Health sector in the UK, and the Construction sector in Germany. The focus of the EU project is scaling informal learning in the workplace through the use of technologies; the focus of our paper, the ‘Help Seeking’ tool, an online tool developed by co-design with GP Practice staff in the North of England. Drawing upon three Scaling taxonomies to underpin our work, we map the complex and interrelated strands influencing scaling of the ‘Help-Seeking’ tool, and go on to suggest that the typical measure of scaling success ‘by number’ needs a more nuanced analysis. Furthermore, we will propose that the emerging framework enables the orchestration of team discourse about theory, the production of artefacts as tools for design discourse, the identification of scalable systemic pain points, and is thus throwing light on the ‘missing middle’ (where key scaling factors reside between top down strategy and bottom up initiatives).
Three key points about strengthening industry-university collaboration:
1. While university research projects often achieve promising outcomes, they frequently fail to translate into tangible impacts for partner companies.
2. The authors conducted a two-year study of over 50 university projects partnered with 27 multinational companies.
3. The study identified nine best practices for managing collaborations, including criteria for partner selection, project management practices, and establishing internationally competitive research platforms to solve challenges for both industry and society.
Strategies for turning ideas into business at universitiesAlexander Decker
This document discusses strategies for universities to turn ideas into businesses. It provides examples of successful university business development programs, such as those at Central Michigan University, National University of Singapore, and Brunel University. The key recommendations for universities include developing an entrepreneurial vision, cultivating partnerships with public and private organizations, and creating linkages to promote mentorship and funding opportunities for turning ideas into businesses.
Strategy for Technology Transfer and Research Results Commercialization in Un...YogeshIJTSRD
In the globalization stage, there has been an increasing interest in the determinants and outcomes of successful technology transfer and commercialization of research results. In this study, An evaluation framework which crosses technology transfer services and research results commercialization in University has been created. We found that research based business idea generation increase at a faster rate for professors with private sector work experience who have more time for research in their positions. The article ends with a discussion of our empirical findings and its implications for support activities related to technology transfer and commercialization of research results. Dr. Le Nguyen Doan Khoi "Strategy for Technology Transfer and Research Results Commercialization in University" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-5 , August 2021, URL: https://www.ijtsrd.com/papers/ijtsrd44945.pdf Paper URL: https://www.ijtsrd.com/management/randd-management/44945/strategy-for-technology-transfer-and-research-results-commercialization-in-university/dr-le-nguyen-doan-khoi
Design of Success Criteria Based Evaluation Model for Assessing the Research ...Waqas Tariq
Innovations and inventions are not outcomes of single activity of any organization. This is a result of collaboration of different partners. Collaborated research of university and industry can enhance the ability of scientist to make significant advances in their fields. The evaluation of collaborated research between university and industry has created the greatest interest among the collaborational researchers because it can determine the feasibility and value of the collaboration. This paper intends to illustrate the evaluation metrics and success criteria- based evaluation model in between university-industry in their collaborated research. For bridging the model, the success criteria have been identified based on key evaluation metrics. A successful Collaboration of university and industry is not dependent on any single metric but instead on the confluence of multiple metrics from the growth of basic research to commercialization. This study is intended to provide different evaluating metrics to impound the research collaboration constraints between university and industry, and design success criteria to upsurge the successful linkage. For this purpose we have developed constraints and success criteria based evaluation metrics (CASEM) model. The proposed model is appropriate for almost all types of collaborations specially research collaborations between university and industry. By adopting this model, any university or industry can easily cross the threshold in the grown-up research collaborational community.
Presentation by Mr. Tuomo Alasoini (Director, Tekes - Finnish Funding Agency for Technology and Innovation) on "Workplace Innovation and Workplace Development in Finland" during the study visit of the sub-committee on Innovative workplaces to Helsinki on 25 January 2011
This paper investigates how internal and external knowledge sources contribute to firms' innovation performance. The study analyzes data from 303 firms across 7 European countries. The results show that internal knowledge sources, such as in-house R&D, continuous improvements, and employee training, have the strongest influence on innovation. However, firms also need external knowledge to innovate. Knowledge from local, national, and international sources helps firms supplement their internal knowledge and introduce new ideas that lead to innovation. Firms mainly rely on links with other firms and institutions in their local and global environments to access external knowledge flows that support innovation.
Bridging the ‘missing middle’: a design based approach to scalingdebbieholley1
Holley, D., Peffer, G. Santos, P., and Cook, J. (2014). Bridging the ‘missing middle’: a design based approach to scaling. Presented to the ALT-Conference, September 2014
A paper contributing to EU learning layers project,:Scaling up Technologies for Informal Learning in SME Clusters
A 9.9 million EU Framework Project (2012-2016)
Abstract
Taking innovation from concept through to scalable delivery is complex, contested and an under-theorised process. In this paper we outline approaches to scaling that have influenced in our work in the EU Learning Layers Integrating Project, a consortium consisting of 17 institutions from 7 different countries. The two industries identified for the initial work are the Health sector in the UK, and the Construction sector in Germany. The focus of the EU project is scaling informal learning in the workplace through the use of technologies; the focus of our paper, the ‘Help Seeking’ tool, an online tool developed by co-design with GP Practice staff in the North of England. Drawing upon three Scaling taxonomies to underpin our work, we map the complex and interrelated strands influencing scaling of the ‘Help-Seeking’ tool, and go on to suggest that the typical measure of scaling success ‘by number’ needs a more nuanced analysis. Furthermore, we will propose that the emerging framework enables the orchestration of team discourse about theory, the production of artefacts as tools for design discourse, the identification of scalable systemic pain points, and is thus throwing light on the ‘missing middle’ (where key scaling factors reside between top down strategy and bottom up initiatives).
Three key points about strengthening industry-university collaboration:
1. While university research projects often achieve promising outcomes, they frequently fail to translate into tangible impacts for partner companies.
2. The authors conducted a two-year study of over 50 university projects partnered with 27 multinational companies.
3. The study identified nine best practices for managing collaborations, including criteria for partner selection, project management practices, and establishing internationally competitive research platforms to solve challenges for both industry and society.
Strategies for turning ideas into business at universitiesAlexander Decker
This document discusses strategies for universities to turn ideas into businesses. It provides examples of successful university business development programs, such as those at Central Michigan University, National University of Singapore, and Brunel University. The key recommendations for universities include developing an entrepreneurial vision, cultivating partnerships with public and private organizations, and creating linkages to promote mentorship and funding opportunities for turning ideas into businesses.
Strategy for Technology Transfer and Research Results Commercialization in Un...YogeshIJTSRD
In the globalization stage, there has been an increasing interest in the determinants and outcomes of successful technology transfer and commercialization of research results. In this study, An evaluation framework which crosses technology transfer services and research results commercialization in University has been created. We found that research based business idea generation increase at a faster rate for professors with private sector work experience who have more time for research in their positions. The article ends with a discussion of our empirical findings and its implications for support activities related to technology transfer and commercialization of research results. Dr. Le Nguyen Doan Khoi "Strategy for Technology Transfer and Research Results Commercialization in University" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-5 , August 2021, URL: https://www.ijtsrd.com/papers/ijtsrd44945.pdf Paper URL: https://www.ijtsrd.com/management/randd-management/44945/strategy-for-technology-transfer-and-research-results-commercialization-in-university/dr-le-nguyen-doan-khoi
Design of Success Criteria Based Evaluation Model for Assessing the Research ...Waqas Tariq
Innovations and inventions are not outcomes of single activity of any organization. This is a result of collaboration of different partners. Collaborated research of university and industry can enhance the ability of scientist to make significant advances in their fields. The evaluation of collaborated research between university and industry has created the greatest interest among the collaborational researchers because it can determine the feasibility and value of the collaboration. This paper intends to illustrate the evaluation metrics and success criteria- based evaluation model in between university-industry in their collaborated research. For bridging the model, the success criteria have been identified based on key evaluation metrics. A successful Collaboration of university and industry is not dependent on any single metric but instead on the confluence of multiple metrics from the growth of basic research to commercialization. This study is intended to provide different evaluating metrics to impound the research collaboration constraints between university and industry, and design success criteria to upsurge the successful linkage. For this purpose we have developed constraints and success criteria based evaluation metrics (CASEM) model. The proposed model is appropriate for almost all types of collaborations specially research collaborations between university and industry. By adopting this model, any university or industry can easily cross the threshold in the grown-up research collaborational community.
Presentation by Mr. Tuomo Alasoini (Director, Tekes - Finnish Funding Agency for Technology and Innovation) on "Workplace Innovation and Workplace Development in Finland" during the study visit of the sub-committee on Innovative workplaces to Helsinki on 25 January 2011
This paper investigates how internal and external knowledge sources contribute to firms' innovation performance. The study analyzes data from 303 firms across 7 European countries. The results show that internal knowledge sources, such as in-house R&D, continuous improvements, and employee training, have the strongest influence on innovation. However, firms also need external knowledge to innovate. Knowledge from local, national, and international sources helps firms supplement their internal knowledge and introduce new ideas that lead to innovation. Firms mainly rely on links with other firms and institutions in their local and global environments to access external knowledge flows that support innovation.
Globaalin yliopistojärjestelmän suuri murros - uhka vai mahdollisuus XAMK:n k...Jouni Eho
This document discusses the disruption happening in the global university system and whether this represents a threat or opportunity for XAMK campus investment plans. It notes that the current university model is like a landline in a smartphone world. Alternative disruptive education programs and concepts from around the world are presented, as well as insights from interviews with innovators and students about future learning environments. A 21UNI prototype is proposed for a 3-week entrepreneurship and design thinking program in Kotka, to help scale results and the model for the future XAMK campus. The document concludes this is a chance for XAMK to become a disruptive higher education institution and revolutionize the way learning is done in Finland.
Maghe - National innovation system and policy mixinnovationoecd
This document summarizes a study that classified innovation policies across 34 countries based on their objectives, instruments, beneficiaries, and sectors. Cluster analysis identified 5 main policy clusters: 1) countries focusing on research organizations and science, 2) countries targeting market-oriented R&D, 3) weaker innovators focusing on knowledge transfer, 4) Eastern EU countries targeting competencies, and 5) top innovators focusing on upstream R&D. The study aims to evaluate policy efficiency and complement traditional innovation performance indicators. Further research needs extensive comparable policy databases across countries.
University Industry Partnership For Innovationsguest5ce3a8
Managing innovations and creating winning partnerships between universities and industry is key to wealth creation. Universities can play an important role in supporting firms through various stages of the innovation process when firms face constraints, ambiguity, or resistance to change. EPIC Lanka has identified several areas for collaboration between industry and universities, including joint research, technology transfer, industry training and employment opportunities, and curriculum development. This can help both universities and firms promote innovations for profitability, growth, and sustainability.
Knowledge sharing innovation_and_firm_performance_evidence_from_turkeyMesut DOĞAN
The aim of this study is to determine relationship between knowledge sharing, innovation and firm performance. In the current study, a survey was conducted on a total of 150 high-tech companies operating in Istanbul, Ankara and Antalya. In the analysis results, it is seen that innovation speed and quality affect both the operational and financial performance of firms. In other words, as innovation speed and quality increase, so does the operational and financial performance of firms. Another important finding obtained in the current study is that explicit knowledge sharing, and tacit knowledge sharing have a positive effect on firm performance. A high level of innovation encompasses new products, processes or applications in most company activities. As a result, innovation can create a competitive advantage by creating synergy in the activities of companies and encourage creativity. Keywords: Innovation Speed and Quality, Explicit and Tacit Knowledge Sharing, Firm Performance
JEL Classification: L25, O31, O33
KNOWLEDGE SHARING, INNOVATION AND FIRM PERFORMANCE: EVIDENCE FROM TURKEYMesut DOĞAN
- The document analyzes the relationship between knowledge sharing, innovation, and firm performance based on a survey of 150 high-tech companies in Turkey.
- The results show that innovation speed and quality positively impact both operational and financial performance, and that explicit and tacit knowledge sharing also positively impact firm performance.
- Innovation encompasses new products, processes, and applications that can create competitive advantages by encouraging creativity and synergies within companies.
Future of education project overview oct 2018 lrFuture Agenda
Future of Education
The broadening world of education is undergoing several major shifts. Driven in part by technology innovation and new business models, the learning process is being reinvented and there is a transformation of education economics and outcomes. Alongside this, there are government imperatives to improve access and address the growing requirement for flexible knowledge workers with transferable skills who can adapt to the changing job market. An ageing workforce also means that there is an increasing need for lifelong learning and re-skilling. In addition there is an increasing demand for a more personalised, immersive and mobile learning experience. All this is challenging the traditional expectations around higher education and the role that universities should play. While countries such as Finland and Singapore are consistently seen as leaders in the field, other nations are trying hard to catch up.
Ahead of a series of global expert events during 2019, this is an overview of the Future of Education project. It provides some background on Future Agenda and preceding multi-nation programmes, highlights some of the questions being raised and outlines options for organisations around the world to get involved. Different governments, technology companies, universities and education service providers are collaborating to support this programme that will develop a clear, shared and detailed view of how the future of education may unfold. If you would like to join in and host one of these events in your region, do let us know (tim.jones@futureagenda.org) and we can integrate that into the planning.
The 2011 Horizon Report summarizes the findings of the Horizon Project, which identifies emerging technologies that are likely to have significant impact on higher education in the next five years. The report examines six technologies in total, two that are expected to enter mainstream use within one year, two within two to three years, and two within four to five years. The report is a collaboration between the New Media Consortium and the EDUCAUSE Learning Initiative, and is informed by an international Advisory Board comprising experts in various fields.
Towards open innovation measurement system – a literature reviewar1815
This document summarizes a literature review of quantitative studies on open innovation published between 2003-2013:
1) The review analyzed 100 papers that used quantitative methods like surveys to measure open innovation concepts. Most papers used established frameworks that define open innovation as inbound/outbound processes or knowledge flows.
2) Common metrics included external knowledge breadth/depth to measure inbound open innovation, and technology transfer capabilities to measure outbound open innovation.
3) Over time, the methods evolved from case studies to large surveys and new methods like simulations. Early papers focused on industries like chemicals and IT, while later papers included a wider range of industries.
Our programs have been featured as an impact case study in the Research Excellence Framework, a rigorous assessment process of the quality and impact of UK-based research intensive Universities.
The 2011 Horizon Report summarizes the findings of the Horizon Project Advisory Board regarding emerging technologies likely to have a significant impact on higher education over the coming years. The report identifies six key technologies or trends across three adoption horizons: near-term (1 year or less), mid-term (2-3 years), and far-term (4-5 years). Electronic books and mobiles are highlighted as near-term technologies, while augmented reality and game-based learning are seen as mid-term technologies with relevance for teaching, learning, and creative inquiry. Gesture-based computing and learning analytics are presented as farther-term technologies to watch. Accompanying each technology discussion are examples of real-world applications and suggested additional
Report of perspectives from 102 industry leaders on how they approach and value university relationships for innovative collaborations. Report from 18 high-tech sectors and businesses of all sizes
Science, Innovation and the Economy: UK Challenges and OpportunitiesTera Allas
Presentation for Government Economic Service seminar in July 2014 on the role of science and innovation in economic growth and the UK's respective strengths and weaknesses
This document is the executive summary of the 2011 Horizon Report, which examines emerging technologies and their potential impact on teaching, learning, and creative inquiry over the next five years. Key findings include:
- Electronic books and mobiles are technologies that could be adopted within the next year. Augmented reality and game-based learning have a two to three year adoption horizon. Gesture-based computing and learning analytics are further out at four to five years.
- Important trends include the abundance of online resources challenging traditional teaching roles, and people expecting to work and learn anywhere anytime on mobile devices.
- Critical challenges are developing digital media literacy skills and evaluating new forms of scholarly work. Economic pressures are also driving new models
This document summarizes key points from the OECD's 2015 Science, Technology and Industry Scoreboard. It finds that Japan, along with other countries, faces productivity challenges and slowing population growth, making innovation imperative. However, Japanese living standards are below the OECD average. The document discusses the need to invest in broader knowledge beyond R&D, develop frontier technologies, and support long-term government research. International collaboration and mobility are important for strengthening research capabilities. While a few countries and companies dominate in research and innovation, greater efforts are needed to engage firms in global innovation networks.
The Diffusion And Implementation of InnovationCSCJournals
In their efforts to try and meet the requirements of the ‘new economy’, corporations would be helped with a conceptual framework in which their innovative business models are combined with new perceptions of knowledge creation, the diffusion and implementation of innovations and change management. To come up with adequate problem analyses and (business) solutions for the complex issues they address, corporations need not only technological knowledge, but also have to gain insight into how technologies relate to the values of people, and how they can be implemented successfully. Action research set up in the form of reciprocal Human Resource Management projects is particularly designed to create solutions and implement strategies that cover this whole spectrum. In a corporate effort of academic researchers and experts in the field, technological and practical knowledge and skills are integrated in a mutual learning and knowledge creation process aimed at the implementation of innovative solutions. With that, it provides an answer to the call for a new knowledge and innovation paradigm that serves to support the ‘new economy’.
This document summarizes research on skills, management practices, and productivity in small and medium enterprises (SMEs). The main points are:
1. The research examines the links between managerial skills, practices adopted by SMEs, and productivity using survey and longitudinal data. It finds that higher entrepreneurial skills are associated with more structured managerial practices, and adopting more practices leads to higher productivity.
2. Key results show entrepreneurial skills, leadership skills, and organizational skills are positively correlated with productivity. Adopting additional human resource practices is also linked to around 2% higher productivity after 3 years.
3. The implications are that both skills development and coaching to help firms adopt practices are needed to
1) Universities contribute significantly to the UK economy through teaching, research, and commercialization, generating billions annually. However, university-business engagement and commercialization could be improved, especially for small firms.
2) The level of university-business engagement is sub-optimal, with only 20% of innovating firms collaborating with universities. Engagement varies significantly across regions.
3) There is heterogeneity in knowledge exchange capabilities across the higher education sector, with research-intensive universities better positioned for commercialization while less research-intensive focus more on human capital development.
4) Firms may need support to find the "right" university partner, as they are more likely to engage with national rather
A Collaborative Framework Between Industry And Academia To Stimulate Entrepre...Daniel Wachtel
The document discusses a collaborative business incubation program between Harare Institute of Technology, Sandown Corporate, and UNDP in Zimbabwe. The program aimed to support young Zimbabweans in transforming technical prototypes into commercially viable businesses. A total of 10 prototypes were refined and investor-ready business plans were developed. The collaboration allowed participants to gain valuable business skills, coaching, and mentoring. University-industry partnerships are seen as useful for setting up sustainable business incubation centers. When universities and industry work together, it drives innovation and economic growth.
Research questions revolving around oi in ict industry. psaradis
This document discusses coupled open innovation processes, where companies cooperate and share knowledge to jointly develop innovations. It provides examples of how coupled processes are implemented in the ICT sector. Specifically, it discusses Ericsson's use of coupled processes through strategic alliances and platforms like Ericsson Labs that allow it to combine internal and external ideas. Ericsson participates in standardization initiatives like 3GPP that involve over 300 companies cooperating to develop telecom industry standards through a coupled innovation process. The document analyzes the benefits of coupled processes for value creation and competitive advantage, as well as challenges around intellectual property protection and balancing openness between companies and customers.
This document discusses national innovation systems and knowledge flows within them. It describes a national innovation system as a complex set of relationships among private enterprises, universities, and public research institutions that creates and shares knowledge. It outlines four primary knowledge flows within these systems: 1) interaction between enterprises through collaboration and information sharing, 2) interaction between enterprises, universities, and research institutions through joint projects and knowledge diffusion, 3) diffusion of knowledge and technology to firms from public research, and 4) movement of personnel between sectors. The quality and fluidity of connections within a national innovation system determine a country's innovative performance.
Globaalin yliopistojärjestelmän suuri murros - uhka vai mahdollisuus XAMK:n k...Jouni Eho
This document discusses the disruption happening in the global university system and whether this represents a threat or opportunity for XAMK campus investment plans. It notes that the current university model is like a landline in a smartphone world. Alternative disruptive education programs and concepts from around the world are presented, as well as insights from interviews with innovators and students about future learning environments. A 21UNI prototype is proposed for a 3-week entrepreneurship and design thinking program in Kotka, to help scale results and the model for the future XAMK campus. The document concludes this is a chance for XAMK to become a disruptive higher education institution and revolutionize the way learning is done in Finland.
Maghe - National innovation system and policy mixinnovationoecd
This document summarizes a study that classified innovation policies across 34 countries based on their objectives, instruments, beneficiaries, and sectors. Cluster analysis identified 5 main policy clusters: 1) countries focusing on research organizations and science, 2) countries targeting market-oriented R&D, 3) weaker innovators focusing on knowledge transfer, 4) Eastern EU countries targeting competencies, and 5) top innovators focusing on upstream R&D. The study aims to evaluate policy efficiency and complement traditional innovation performance indicators. Further research needs extensive comparable policy databases across countries.
University Industry Partnership For Innovationsguest5ce3a8
Managing innovations and creating winning partnerships between universities and industry is key to wealth creation. Universities can play an important role in supporting firms through various stages of the innovation process when firms face constraints, ambiguity, or resistance to change. EPIC Lanka has identified several areas for collaboration between industry and universities, including joint research, technology transfer, industry training and employment opportunities, and curriculum development. This can help both universities and firms promote innovations for profitability, growth, and sustainability.
Knowledge sharing innovation_and_firm_performance_evidence_from_turkeyMesut DOĞAN
The aim of this study is to determine relationship between knowledge sharing, innovation and firm performance. In the current study, a survey was conducted on a total of 150 high-tech companies operating in Istanbul, Ankara and Antalya. In the analysis results, it is seen that innovation speed and quality affect both the operational and financial performance of firms. In other words, as innovation speed and quality increase, so does the operational and financial performance of firms. Another important finding obtained in the current study is that explicit knowledge sharing, and tacit knowledge sharing have a positive effect on firm performance. A high level of innovation encompasses new products, processes or applications in most company activities. As a result, innovation can create a competitive advantage by creating synergy in the activities of companies and encourage creativity. Keywords: Innovation Speed and Quality, Explicit and Tacit Knowledge Sharing, Firm Performance
JEL Classification: L25, O31, O33
KNOWLEDGE SHARING, INNOVATION AND FIRM PERFORMANCE: EVIDENCE FROM TURKEYMesut DOĞAN
- The document analyzes the relationship between knowledge sharing, innovation, and firm performance based on a survey of 150 high-tech companies in Turkey.
- The results show that innovation speed and quality positively impact both operational and financial performance, and that explicit and tacit knowledge sharing also positively impact firm performance.
- Innovation encompasses new products, processes, and applications that can create competitive advantages by encouraging creativity and synergies within companies.
Future of education project overview oct 2018 lrFuture Agenda
Future of Education
The broadening world of education is undergoing several major shifts. Driven in part by technology innovation and new business models, the learning process is being reinvented and there is a transformation of education economics and outcomes. Alongside this, there are government imperatives to improve access and address the growing requirement for flexible knowledge workers with transferable skills who can adapt to the changing job market. An ageing workforce also means that there is an increasing need for lifelong learning and re-skilling. In addition there is an increasing demand for a more personalised, immersive and mobile learning experience. All this is challenging the traditional expectations around higher education and the role that universities should play. While countries such as Finland and Singapore are consistently seen as leaders in the field, other nations are trying hard to catch up.
Ahead of a series of global expert events during 2019, this is an overview of the Future of Education project. It provides some background on Future Agenda and preceding multi-nation programmes, highlights some of the questions being raised and outlines options for organisations around the world to get involved. Different governments, technology companies, universities and education service providers are collaborating to support this programme that will develop a clear, shared and detailed view of how the future of education may unfold. If you would like to join in and host one of these events in your region, do let us know (tim.jones@futureagenda.org) and we can integrate that into the planning.
The 2011 Horizon Report summarizes the findings of the Horizon Project, which identifies emerging technologies that are likely to have significant impact on higher education in the next five years. The report examines six technologies in total, two that are expected to enter mainstream use within one year, two within two to three years, and two within four to five years. The report is a collaboration between the New Media Consortium and the EDUCAUSE Learning Initiative, and is informed by an international Advisory Board comprising experts in various fields.
Towards open innovation measurement system – a literature reviewar1815
This document summarizes a literature review of quantitative studies on open innovation published between 2003-2013:
1) The review analyzed 100 papers that used quantitative methods like surveys to measure open innovation concepts. Most papers used established frameworks that define open innovation as inbound/outbound processes or knowledge flows.
2) Common metrics included external knowledge breadth/depth to measure inbound open innovation, and technology transfer capabilities to measure outbound open innovation.
3) Over time, the methods evolved from case studies to large surveys and new methods like simulations. Early papers focused on industries like chemicals and IT, while later papers included a wider range of industries.
Our programs have been featured as an impact case study in the Research Excellence Framework, a rigorous assessment process of the quality and impact of UK-based research intensive Universities.
The 2011 Horizon Report summarizes the findings of the Horizon Project Advisory Board regarding emerging technologies likely to have a significant impact on higher education over the coming years. The report identifies six key technologies or trends across three adoption horizons: near-term (1 year or less), mid-term (2-3 years), and far-term (4-5 years). Electronic books and mobiles are highlighted as near-term technologies, while augmented reality and game-based learning are seen as mid-term technologies with relevance for teaching, learning, and creative inquiry. Gesture-based computing and learning analytics are presented as farther-term technologies to watch. Accompanying each technology discussion are examples of real-world applications and suggested additional
Report of perspectives from 102 industry leaders on how they approach and value university relationships for innovative collaborations. Report from 18 high-tech sectors and businesses of all sizes
Science, Innovation and the Economy: UK Challenges and OpportunitiesTera Allas
Presentation for Government Economic Service seminar in July 2014 on the role of science and innovation in economic growth and the UK's respective strengths and weaknesses
This document is the executive summary of the 2011 Horizon Report, which examines emerging technologies and their potential impact on teaching, learning, and creative inquiry over the next five years. Key findings include:
- Electronic books and mobiles are technologies that could be adopted within the next year. Augmented reality and game-based learning have a two to three year adoption horizon. Gesture-based computing and learning analytics are further out at four to five years.
- Important trends include the abundance of online resources challenging traditional teaching roles, and people expecting to work and learn anywhere anytime on mobile devices.
- Critical challenges are developing digital media literacy skills and evaluating new forms of scholarly work. Economic pressures are also driving new models
This document summarizes key points from the OECD's 2015 Science, Technology and Industry Scoreboard. It finds that Japan, along with other countries, faces productivity challenges and slowing population growth, making innovation imperative. However, Japanese living standards are below the OECD average. The document discusses the need to invest in broader knowledge beyond R&D, develop frontier technologies, and support long-term government research. International collaboration and mobility are important for strengthening research capabilities. While a few countries and companies dominate in research and innovation, greater efforts are needed to engage firms in global innovation networks.
The Diffusion And Implementation of InnovationCSCJournals
In their efforts to try and meet the requirements of the ‘new economy’, corporations would be helped with a conceptual framework in which their innovative business models are combined with new perceptions of knowledge creation, the diffusion and implementation of innovations and change management. To come up with adequate problem analyses and (business) solutions for the complex issues they address, corporations need not only technological knowledge, but also have to gain insight into how technologies relate to the values of people, and how they can be implemented successfully. Action research set up in the form of reciprocal Human Resource Management projects is particularly designed to create solutions and implement strategies that cover this whole spectrum. In a corporate effort of academic researchers and experts in the field, technological and practical knowledge and skills are integrated in a mutual learning and knowledge creation process aimed at the implementation of innovative solutions. With that, it provides an answer to the call for a new knowledge and innovation paradigm that serves to support the ‘new economy’.
This document summarizes research on skills, management practices, and productivity in small and medium enterprises (SMEs). The main points are:
1. The research examines the links between managerial skills, practices adopted by SMEs, and productivity using survey and longitudinal data. It finds that higher entrepreneurial skills are associated with more structured managerial practices, and adopting more practices leads to higher productivity.
2. Key results show entrepreneurial skills, leadership skills, and organizational skills are positively correlated with productivity. Adopting additional human resource practices is also linked to around 2% higher productivity after 3 years.
3. The implications are that both skills development and coaching to help firms adopt practices are needed to
1) Universities contribute significantly to the UK economy through teaching, research, and commercialization, generating billions annually. However, university-business engagement and commercialization could be improved, especially for small firms.
2) The level of university-business engagement is sub-optimal, with only 20% of innovating firms collaborating with universities. Engagement varies significantly across regions.
3) There is heterogeneity in knowledge exchange capabilities across the higher education sector, with research-intensive universities better positioned for commercialization while less research-intensive focus more on human capital development.
4) Firms may need support to find the "right" university partner, as they are more likely to engage with national rather
A Collaborative Framework Between Industry And Academia To Stimulate Entrepre...Daniel Wachtel
The document discusses a collaborative business incubation program between Harare Institute of Technology, Sandown Corporate, and UNDP in Zimbabwe. The program aimed to support young Zimbabweans in transforming technical prototypes into commercially viable businesses. A total of 10 prototypes were refined and investor-ready business plans were developed. The collaboration allowed participants to gain valuable business skills, coaching, and mentoring. University-industry partnerships are seen as useful for setting up sustainable business incubation centers. When universities and industry work together, it drives innovation and economic growth.
Research questions revolving around oi in ict industry. psaradis
This document discusses coupled open innovation processes, where companies cooperate and share knowledge to jointly develop innovations. It provides examples of how coupled processes are implemented in the ICT sector. Specifically, it discusses Ericsson's use of coupled processes through strategic alliances and platforms like Ericsson Labs that allow it to combine internal and external ideas. Ericsson participates in standardization initiatives like 3GPP that involve over 300 companies cooperating to develop telecom industry standards through a coupled innovation process. The document analyzes the benefits of coupled processes for value creation and competitive advantage, as well as challenges around intellectual property protection and balancing openness between companies and customers.
This document discusses national innovation systems and knowledge flows within them. It describes a national innovation system as a complex set of relationships among private enterprises, universities, and public research institutions that creates and shares knowledge. It outlines four primary knowledge flows within these systems: 1) interaction between enterprises through collaboration and information sharing, 2) interaction between enterprises, universities, and research institutions through joint projects and knowledge diffusion, 3) diffusion of knowledge and technology to firms from public research, and 4) movement of personnel between sectors. The quality and fluidity of connections within a national innovation system determine a country's innovative performance.
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2. Collaboration between
universities and
industry
There is significant international research indicating that university-industry
collaboration (UIC) is a powerful source of innovation. For example, World
Bank (2013) found that UIC is critical for skills development, generation,
adoption of knowledge, and promoting entrepreneurship. Similarly, Nelson
(2017) found that UIC is a critical for the development of knowledge
economies and societies.
It is in this context that Universities New Zealand commissioned Deloitte
Access Economics to prepare a paper on UIC. This paper defines UIC,
explores the key benefits of UIC, and provides insights into how to improve
UIC in New Zealand and how to measure the outcome of UIC.
What is university-industry collaboration?
Collaboration means different things to different people. Perspectives of
collaboration varies between company leaders, government and academia,
and these views differ across disciplines.
Adler et al. (2011) wrote “collaborative communities encourage people to
continually apply their unique talents to group projects - and to become
motivated by a collective mission, not just personal gains and the intrinsic
pleasure of autonomous creativity.” Indeed, this approach fosters not only
innovation and agility, but also efficiency and scalability (Deloitte Access
Economics, 2014).
Collaboration is an activity that is widely spread across the economy. It is not
only limited to a workplace, or between universities, but also occurs between
universities and industry.
UIC can be formal or informal. Formal UIC includes formal contracts,
collaborative research projects, patent licensing, co-development, and co-
authorship, where both parties are expected to contribute to knowledge
development. Informal UIC includes, among others, human capital mobility,
interaction at conferences, and expert groups (Deloitte Access Economics,
2018).
Universities tend to participate in UIC for reputation enhancement, and to
gain access to funding and industry empirical data. Comparably, companies
tend to participate in UIC to gain access to knowledge, universities facilities
and equipment, to influence the research agenda of universities, and to share
research and development (R&D) risks (World Bank, 2013).
3. Understanding the benefits of university-industry collaboration
Little is known about companies’ progression from informal UIC to more
formal UIC. Literature suggests successful formal UICs deliver benefits to the
economy predominantly through innovation and productivity. However, there
is little literature to support the benefits of informal UIC.
Productivity
There are several international studies that establish a positive relationship
between UIC and productivity, which ultimately contributes to economic
growth.
For example, Mark and Norn (2014) quantified the economic impact of UIC
based on formal collaboration mechanisms - but not informal collaboration
mechanisms. The study was based on 6,338 formal collaborations between
the University of Copenhagen – the largest university in Denmark – and
1,537 private companies. It compared the productivity of a pool of companies
in UIC (the base case), with a pool of non-collaborating companies (the
counterfactual).
The study measured the economic impact in terms of increased productivity,
and established a positive causal connection between companies entering into
formal collaboration with universities and productivity, but with a lagged
effect. Two years after some form of formal collaboration, companies
experience an average productivity return of 6%, which increased to 11%
four years after the collaboration was established (Mark and Norn, 2014).
In a report by BiGGAR Economics (2017) for Oxford University, business
innovation is regarded as having an “absorptive capacity”1
that could benefit
from collaboration with universities, by fostering greater productivity from
innovative new ideas, insights, and practices. Networks and collaboration
have been identified as having a strong role in the means to foster greater
productivity. However, this fundamentally requires an open and engaged
university.
Innovation
Collaboration is often thought of as the key ingredient to ‘frontier’ or ‘creative’
innovation (‘new to the world’ products/services) (Department of Industry,
2006). Collaborating with a group of open-minded people who can quickly
validate the merits of an idea and help build upon them can accelerate the
process of iterative thinking, and speed up the innovation process (Deloitte
Access Economics, 2014).
UIC supports economic growth through innovation, resulting in new products,
new patents and new solutions to problems (Federica et. Al, 2014). A study in
Chile and Colombia showed that UIC increased the propensity of firms to
introduce new products, and to patent them (Marotta, Blom and Thorn,
2007). Previous research also suggests UIC makes R&D less risky for
companies (Baba et al., 2009; Woerter, 2012). This suggests UIC can
stimulate additional R&D investment, and foster the commercialisation of
public research.
1
Absorptive capacity refers to the propensity and capability to engage, absorb,
translate and exploit technology – whether obtained internally or externally (UK’s
National Endowment for Science, Technology and the Arts, 2008).
4. Research and innovation also helps to improve the practical competitiveness
of companies, and may contribute to an increased standard of living in
society. Collaboration in high-performance academic–practitioner research
teams can lead to greater certainty that such outcomes are achieved (Cooper
and Guthrie, 2017).
University-industry collaboration in New Zealand
To provide New Zealand context, Deloitte Access Economics conducted
primary research into domestic examples of UIC. Chart 1 provides a summary
of the research of various UICs, based on information available from four key
universities in New Zealand. The research suggests the nature of UIC is wide-
ranging across New Zealand – even if it is not always practical to quantify the
extent to which they contribute to innovation.
Chart 1: Examples of university-industry collaboration in New Zealand
Source: Deloitte Access Economics; University of Canterbury (2018); The University of
Auckland (2018); University of Otago (2018); Victoria University of Wellington (2018)
Specialised equipment
and laboratory hire permit
the use of scientific
equipment and facilities by
firms, on either a contract or
collaborative basis.
Technical solutions through a
postgraduate or research group
project that offer industry
partners the opportunity to
develop a project of use, with
much greater value than the
financial contribution that is
required.
Conferences that facilitate the
dissemination of developments
in research between academic
staff and industry participants.
Academic consultation that
provides paid work for
academic staff to inform firms
on technical solutions they may
not otherwise be able to solve.
Graduate positions that
provide career pathways for
students and allow firms to
select only the most talented
prospects to join their team.
Firm sponsorship/scholarship
of a final-year student
research and development
project that benefits both
students and firms by enabling
the latter to gain quality research
and higher qualifications for the
former
Joint University-Industry
advisory boards that
provide a forum for faculty
staff to discuss research
programmes. Advisory boards
also informs the relevance of
the Faculty’s activities to
industry.
Assistance to university
research by industry
provides industry insight and
increases the overall
relevancy and quality of
university research.
5. Despite the benefits of UIC recognised internationally, by international
standards there is a low level of UIC in New Zealand.
The OECD (2017) defines innovation collaboration as the active participation
with other organisations in joint innovation projects, with the aim of
introducing a new or significantly improved product or process. This can
involve the joint implementation of innovation with customers, suppliers, or
the partnerships with other firms or organisations.
Based on the 2017 OECD survey of small and medium enterprises (SMEs) in
the business of innovating products and/or processes, only about 5% of New
Zealand firms are reported to be collaborating with higher education or
research institutes, ranking New Zealand 29th
out of 33 OECD countries.
Increasing these levels of collaboration is central to translating New Zealand
research output into something economically impactful.
Chart 2: Percentage of small and medium enterprises collaborating on innovation
activities with higher education institutions, 2012 to 2014
Source: Deloitte Access Economics; OECD (2017)
What can New Zealand universities, industry and government do to further
stimulate UIC?
Average
0% 5% 10% 15% 20% 25% 30%
RUS
AUS
CHL
NZL
BRA
KOR
ITA
LVA
LTU
PRT
CHE
GRC
TUR
ISL
HUN
JPN
CZE
SVK
AVG
POL
FRA
DEU
MEX
NLD
DNK
ESP
NOR
EST
SVN
BEL
GBR
FIN
AUT
CHN
6. Success factors of university-industry collaboration
Collaboration between universities and industry vary in size, scale and stage
of collaboration.
There are various successful UIC with a focus on driving innovation cited in
international literature (Edmosnon, et al. 2012; Pertuze et al 2010; UDIP
2013). A common and powerful success factor relates to trust, and the quality
of relationship between universities and industry. These relationships
determine the extent to which universities and firms understand each other
and the desired outcomes for both parties. For universities, this means
ensuring that research aligns with the company’s strategic interest.
Appendix A provides a more detailed summary of examples of successful
international UICs.
Overall, international literature suggests five success factors:
1 Long-term strategic relationships with on-going interaction
According to Pertuze et al (2010) and UDIP (2013), long-term university-
industry relationships generate the most successful innovation. In
examples that have extended over a long time period, collaboration is
aligned with the strategic and tangible interests of firms, whilst
simultaneously providing universities with research funding, improved
curriculum relevancy, and experience for students.
2 Bi-lateral exchange and shared infrastructure
Findings from Larsen et al (2016) and from Edmosnon et al (2012) show
that universities and firms can achieve greater ties by engaging in two-
way exchange that goes beyond funding. This includes sharing
infrastructure and equipment.
3 Encourage new avenues for innovation
A key generator of new innovative collaborations are individuals referred
to as ‘boundary spanners’. Boundary spanners are industry-side
managers on an existing UIC that take on the role of linking the
innovative needs of other inter-firm departments with the university. In
doing so, they develop new avenues for innovation, and deliver impact
for their company (Pertuze et al., 2010).
4 Strong communication linkage between university and company
and/or industry
Pertuze et al. (2010) reports having university researchers regularly visit
company personnel on-site bolsters these relationships, and
consequently fosters the success of the collaboration. Maintaining
university-industry contact, both during and after a project, positively
influences the likelihood of future collaboration.
5 Streamlined negotiations to establish clear guidelines for
intellectual property ownership early on
While contractual negotiations are important, they are time consuming,
and delay research. Establishing terms early, especially those around
intellectual property (IP) ownership, avoids conflicts that can delay
research further on (UDIP, 2013 and Edmosnon et al, 2012).
Further research into how New Zealand stacks up against these success
factors would be useful to understand the current success of UICs in New
Zealand, and to identify target areas to improve both the level and success
rate of UIC in the future.
7. Improving university-industry collaboration in New Zealand
In a recent study, Professor Nielsen provided a European perspective on UIC,
which is just as relevant in the New Zealand context (Nielsen, 2017):
“We need to revamp academics’ incentives to encourage more
academics to engage in university–industry collaboration. We also
need to educate academics on how to work with companies. Finally,
we need to turn this company interaction into a resource by
contemplating how to create reciprocal value creation between all
the potential stakeholders. Then we will have genuine, meaningful
university–industry collaboration.”
To accomplish this, and to improve UIC in New Zealand, government support
is necessary through policies that improve the propensity of firms to
collaborate with universities.
Research and development grants
In New Zealand, there are a number of examples of R&D grants and funding:
The Government currently provides funding through the Growth Grant
to support private R&D funding; firms could be eligible for a 12.5% tax
credit on eligible R&D expenditure
The Endeavour Fund focuses on longer-term research that has high
potential to positively transform New Zealand’s future economy
The Te Punaha Hihiko Vision Fund supports Maori participation in
science and innovation
The PreSeed Accelerated Fund supports early-stage technology
commercialisation activity
However, there is no specific grant that is linked to UIC. A possible
international example that could be investigated in New Zealand is an
innovation voucher, which is an instrument used in the Netherlands, Ireland
and the UK to promote UIC (World Bank 2013). Innovation vouchers are
credit provided by governments to firms to purchase services from
universities to introduce innovation.
Intellectual property rights
A common and important lesson from international examples is not to let IP
become a barrier to innovation. Clear and mutual understanding of IP
ownership from project inception is imperative. Failing to do so can result in
disagreements later on, which has an adverse impact on the research being
undertaken.
It is unclear from the information available how, and at what stage of the
collaboration, IP rights are agreed in a New Zealand context. Guidelines on IP
management could provide more transparency around this for universities
and industry.
Performance-based funding of universities
Internationally, governments seek to stimulate UIC through their role in
funding universities. World Bank (2013) suggests performance measures that
determine funding include indicators such as the number of formal
collaboration arrangements with industry. In this example, the World Bank
referred to countries such as the UK, Canada and Singapore, where
universities are offered additional funding research, conditional upon the
university entering contracts with industry.
8. New Zealand has a Performance-based Research Fund administered by the
Tertiary Education Commission. A measure specifically linked to UIC could be
added as an indicator in New Zealand to assess performance-based funding of
universities.
Formalised PhD internships
To encourage UIC, and in turn innovation, formalised PhD internships could
be considered by government. This could involve, for example, PhD students
in science, technology, engineering or mathematics (STEM) subjects being
encouraged to complete an internship with a relevant industry organisation
and, wherever possible, to develop their research proposal jointly with
academic and industry input.
By providing formalised PhD internship opportunities, students can spend
time with an employer or industry group before they determine their actual
research topic. This allows them to learn about an industry, and
understanding that industry’s challenges and needs, which could generate
more relevant applied research with or for industry.
Measuring the benefit of additional funding to support university-
industry collaboration
The estimated benefit of additional funding to stimulate UIC in New Zealand
could be estimated based on a conceptual framework developed by Deloitte
Access Economics to assess the benefit of collaborative research by
universities across jurisdictions (Deloitte Access Economics, 2017).
This conceptual framework was developed for Universities New Zealand to
determine the average returns to the New Zealand economy in Net Present
Value (NPV) terms over a period of 15 years, based on international research
collaboration, academic staff exchanges, student exchanges, and work
placements.
From modelling this framework, it was estimated that an investment of $1.00
in each of the four initiatives would result in a cumulative benefit to the
economy of up to $10.00.
The same model logic could determine the benefits from UIC, relative to a
counterfactual where no UIC has taken place. OECD data on UIC
internationally, results of international studies on productivity gains, and R&D
cost would predominately form the basis of this model.
The model logic is presented in Chart 3, and is based on the key benefits of
UIC discussed in this paper – namely, productivity and innovation.
9. Chart 3: Model logic to assess the economic benefit of UIC
Source: Deloitte Access Economics
To the extent that data is available, it would also be possible to assess the
distribution of benefits between the university, the firm and the wider
economy - in particular, the regional economy. This conceptual framework,
once developed, can also be applied to test what UIC would be the most
effective.
As an alternative, the overall benefit of UIC to the economy could be
estimated. The model developed by Deloitte Access Economics to assess the
economic benefit of collaboration in the workplace could be used as a basis
(Deloitte Access Economics, 2014). The value of collaboration to the economy
was estimated based on the benefits of collaboration in terms of the time
saved by collaborating, and the improvement in work quality, based on a
survey data of businesses in Australia.
The survey data indicated that the level of collaboration within Australian
firms was 10%. It was estimated that the overall benefit of UIC to the
Australian economy was $46 billion, comprising of $22.6 billion for time
saved, $29 billion for quality improvement and $5.4 billion costs associated
with collaboration.
To estimate the overall benefit of UIC in New Zealand, it would be necessary
to undertake a survey across universities and industry. The impact of UIC on
productivity could be estimated based on the survey results within a
computable general equilibrium framework.
University
cost
Companies’
cost
Additional
government
funding
Funds NZ innovative initiative
Increase in research
funding
Improvement in
productivity i.e. greater
impact of research (high
citations)
Impact of research
funding on labour and
productivity
Higher productivity within
the firm
Costs
Intermediate processes
Intermediate benefits
GDP benefits
Funding costs
10. Limitation of our work
General use restriction
This report is prepared solely for the use of Universities New Zealand. This
report is not intended to and should not be used or relied upon by anyone
else and we accept no duty of care to any other person or entity. The report
has been prepared for the purpose of providing the causal link between
universities and local innovation, and the economic impact of university
research expenditure on the New Zealand economy. You should not refer to
or use our name or the advice for any other purpose.
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14. Appendix A
Key lessons from international literature on successful university-industry
collaboration were used to derive the critical success factors outlined in
chapter three.
Table 1.1 Key lessons learnt from successful university-industry collaborations
University(s)/
Institute(s)
Industry
firm(s)
Programme/
project
Lessons
ETH Zurich IBM IBM-ETH Zurich
Nanotechnology
Centre
Establish contracts that cover a broad framework.
Dedicate time and devote leadership to projects.
Longer-term projects generate the largest benefit.
Partnerships should have a win-win approach.
University of
Cambridge
SKF Group University
technology
centres
Strategic relationships with universities can lead to deeper
research ties, and both parties deciding to innovate
together.
Value quality over quantity. Be selective in developing
strategic partnerships.
Encourage exchange that extends in both directions.
Technical University
of Munich
GE Global
Research
Corporate
Research labs
A good bridge to industry are corporate research labs.
Establish and maintain trust.
Choose the right people for the team.
Define an objective.
Collaboration is more than just sponsorship.
Encourage collaboration across disciplines.
IP ownership should not be a barrier to collaboration.
Syracuse University
and JPMorgan
Chase
JPMorgan
Chase
New relational
model for
University-
Industry
relationships
Collaboration between university and industry should
mutually support each collaborator.
Appropriate long-term collaborations between universities
and industry needs to be a focus.
Negotiations need to be streamlined as they are timely and
delay research.
Technical University
of Berlin,
Massachusetts
Institute of
Technology
Siemens Long-term
strategic
partnerships
Understand the needs of both parties to establish a win-
win situation.
Firms need to formulate a strong structure to cooperate
with universities.
Ensure university commercialisation offices do not hinder
strategic relationships.
Teaching soft skills as part of the collaboration can
accelerate innovation.
University of
California, Berkeley
Nokia Traffic Works There needs to be a common understanding between
company and university leaders.
Having the capacity to include cross-disciplinary research
is key
15. Source: Deloitte Access Economics; Edmosnon, et al. (2012); UDIP (2013)
University(s)/
Institute(s)
Industry
firm(s)
Programme/
project
Lessons
Caltech The Boeing
Company
Strategic
Agreement
Senior executives at the firm should be given access to
key faculty and administration at the university.
Encourage students to participate in internships with
companies earlier in their research careers.
Interactions between company and academic scientists
should be regular throughout their respective
collaborations.
University faculty members should provide regular
reporting and updates to their scientific partners.
University of
Tennessee
Scintillation
Materials
Research
Centre and
Siemens
Medical
Solutions
Medical imaging Both parties need to understand that universities need to
publish research, and that companies need to protect IP.
Coming to an agreement on the contractual legalities
requires patience and flexibility by both parties.
University of
Cincinnati
Procter &
Gamble
Simulation and
modelling centre
There needs to be a willingness of faculty staff to do things
differently from the traditional industry-academia
engagements.
Company project teams need to be willing to fund
students, train, and mentor them over a period. Locality is
key to this.
Develop clear guidelines for intellectual property
ownership, and on-site relationship ownership needs to be
established.
Georgia Institute of
Technology,
Brigham Young
University, Purdue
University,
University of
Washington, and
University of
Southern California.
The Boeing
Company
Design-Build-Test
Capstone Course
Integrate situated learning within a university-industry
setting.
Create link between research and rigorous teaching
standards with real-world practice.
Collaborate with practitioners to address complex
problems in real, authentic contexts.