scholarly journals Generating science-based growth: an econometric analysis of the impact of organizational incentives on university–industry technology transfer

2005 ◽  
Vol 11 (3) ◽  
pp. 169-181 ◽  
Author(s):  
Albert N. Link ◽  
Donald S. Siegel
Keyword(s):  
Technology Transfer ◽  
Econometric Analysis ◽  
The Impact ◽  
University Industry

scholarly journals Commercialization Of Academic Research In Canadian Universities: Optimizing Technology Transfer

2021 ◽  
Author(s):  
Melissa Golberg
Keyword(s):  
Technology Transfer ◽  
New Ventures ◽  
Academic Research ◽  
Canadian Universities ◽  
Level Of Economic Development ◽  
Technology Managers ◽  
The Right ◽  
High Level ◽  
The Impact ◽  
University Industry

In recent years, in addition to the basic tenets of teaching and research, commercialization and innovation have become core priorities in higher education (Friedman & Silberman, 2003; Etzkowitz, 2003; Rasmussen et al., 2006). Universities have the right ingredients to be natural technology transfer incubators with a high influx of innovators and the capability to create new ventures and have high potential to generate a high level of economic development. Commercialization allows the results of innovative research to be utilized through transformation into marketable products or ‘technology transfer’. Since the 1980s, Canadian universities have begun dedicating resources and effort to discover how to best harness the innovation arising out of university-based research for knowledge transfer and revenue generation through commercialization. This thesis focuses on specific university inputs that influence the volume of technology transferred to industry through various commercialization channels and the impact each factor may have considering the institution size. Through data verified primarily from the Association of University Technology Managers’ (AUTM) annual surveys of Canadian and American universities from 2011 to 2015, this study analyzes the effect of administrative characteristics on technology transfer at a university. While the results of the study do not provide much conclusive guidance on the reasons behind growth in university-industry technology transfer, they do suggest that there is some greater effect in large universities that leads to more technology transfer activity than in smaller universities.

scholarly journals Commercialization Of Academic Research In Canadian Universities: Optimizing Technology Transfer

2021 ◽  
Author(s):  
Melissa Golberg
Keyword(s):  
Technology Transfer ◽  
New Ventures ◽  
Academic Research ◽  
Canadian Universities ◽  
Level Of Economic Development ◽  
Technology Managers ◽  
The Right ◽  
High Level ◽  
The Impact ◽  
University Industry

In recent years, in addition to the basic tenets of teaching and research, commercialization and innovation have become core priorities in higher education (Friedman & Silberman, 2003; Etzkowitz, 2003; Rasmussen et al., 2006). Universities have the right ingredients to be natural technology transfer incubators with a high influx of innovators and the capability to create new ventures and have high potential to generate a high level of economic development. Commercialization allows the results of innovative research to be utilized through transformation into marketable products or ‘technology transfer’. Since the 1980s, Canadian universities have begun dedicating resources and effort to discover how to best harness the innovation arising out of university-based research for knowledge transfer and revenue generation through commercialization. This thesis focuses on specific university inputs that influence the volume of technology transferred to industry through various commercialization channels and the impact each factor may have considering the institution size. Through data verified primarily from the Association of University Technology Managers’ (AUTM) annual surveys of Canadian and American universities from 2011 to 2015, this study analyzes the effect of administrative characteristics on technology transfer at a university. While the results of the study do not provide much conclusive guidance on the reasons behind growth in university-industry technology transfer, they do suggest that there is some greater effect in large universities that leads to more technology transfer activity than in smaller universities.

scholarly journals Two Sides of the Same Coin. University-Industry Collaboration and Open Innovation as Enhancers of Firm Performance

2021 ◽  
Vol 13 (7) ◽  
pp. 3866
Author(s):  
Joana Costa ◽  
Ana Rita Neves ◽  
João Reis
Keyword(s):  
Firm Performance ◽  
Open Innovation ◽  
Primary Data ◽  
Company Performance ◽  
Innovation Ecosystem ◽  
Industry Collaboration ◽  
And Performance ◽  
Performance Results ◽  
The Impact ◽  
University Industry

Open innovation is proved to be determinant in the rationalization of sustainable innovation ecosystems. Firms, universities, governments, user communities and the overall environment are called to contribute to this dynamic process. This study aims to contribute to a better understanding of the impact of open innovation on firms’ performance and to empirically assess whether university-industry collaborations are complementary or substitutes for this activity. Primary data were collected from a survey encompassing 908 firms, and then combined with performance indicators from SABI (Spanish and Portuguese business information). Econometric estimations were run to evaluate the role of open innovation and university-industry collaboration in the firm innovative propensity and performance. Results highlight the importance of diversity in collaborations with the academia and inbound open innovation strategy as enhancers of firm performance. The two activities reinforce each other. By testing the impact of open innovation practices on company performance, the need for heterogeneity in terms of contact type and university is also demonstrated. Findings cast light on the need to reformulate existing policy packages, reinforcing the ties with academia as well as the promotion of open innovation strategies. The connection to the innovation ecosystem needs to be further encouraged as well as the promotion of persistent connections with the knowledge sources in an open and multilateral framework.

scholarly journals Competitiveness Determinants of Moroccan Exports: Quantity-Based Analysis

2016 ◽  
Vol 8 (7) ◽  
pp. 140 ◽  
Author(s):  
Bilal Lotfi ◽  
Mohamed Karim
Keyword(s):  
European Union ◽  
Literature Review ◽  
Econometric Analysis ◽  
External Factors ◽  
The European Union ◽  
Export Competitiveness ◽  
Main Determinants ◽  
Internal And External Factors ◽  
The Impact ◽  
Relative Concept

<p>The term competitiveness is a relative concept whose perception changes with the level of conducted analysis (nation, sector, company). Thus, a variety of internal and external factors can have deep effects on the competitiveness of a given entity. This paper aims to evaluate the competitiveness of Moroccan exports by identifying the main determinants that explain their performance. This is particularly dealing with the impact of customs’ tariff, the tariff of import, foreign demand, the share of the non-residents in the capital of domestic enterprises and the investment rate compared to the value of exporters.</p><p>Moreover, this paper presents a literature review on competitiveness and examines the main results of our econometric analysis regarding the determinants of export competitiveness applied to the top ten branches most exporters in Morocco. The gained results allow confirming the sensitivity of exports by branch to the situation of Morocco’s main trading partner namely the European Union while emphasizing, quantitatively, on the role played by the investment effort undertaken by Moroccan exporting companies in improving the competitiveness of national exports.</p>

scholarly journals Econometric Analysis of the Impact of Propensities on Economic Occurrences: A Macroeconomic Perspective

2012 ◽  
Vol 10 (2) ◽  
pp. 138-154 ◽  
Author(s):  
Mariusz Doszyń
Keyword(s):  
Spatial Data ◽  
Fixed Effects ◽  
Classical Model ◽  
Econometric Analysis ◽  
Dummy Variables ◽  
Macroeconomic Variables ◽  
Current State ◽  
Famous Book ◽  
Direct Models ◽  
The Impact

Econometric Analysis of the Impact of Propensities on Economic Occurrences: A Macroeconomic PerspectiveThe main aim of this article was the specification of problems connected with analysis of impact of human propensities on economic occurrences and also a proposition of econometric tools enabling the identification of this impact. According to the meaning of propensities in economics the current state of knowledge is mostly an effect of considerations presented by J.M. Keynes in his famous book "The General Theory of Employment, Interest and Money" where J.M. Keynes proposed such economic categories as the average and marginal propensities. One of the goals of the presented deliberations was to specify problems related with economic theory of propensities. Such propensities as a propensity to consume, to save, to invest and thesaurisation were particularly carefully analysed. The impact of these propensities on basic macroeconomic variables was considered with respect to the classical model, the neoclassical Solow-Swan model and theIS-LMscheme. In case of spatial data the effects of the impact of propensities could be analysed by means of models with dummy variables showing presence of given propensities. A procedure enabling the construction of such variables was proposed. In case of time series, conceptions delivered by the integration and cointegration theory could be applied. Especially such models as VAR and VECM could be useful. Models for panel data enable direct (models with fixed effects) or indirect (models with random effects) consideration of the impact of propensities on the analysed processes.

Yield or profit: alternatives to the development of national crop production

Ekonomika APK ◽  
2021 ◽  
Vol 316 (2) ◽  
pp. 15-25
Author(s):  
Dmytro Zherlitsyn ◽  
Andrii Skrypnyk ◽  
Nataliia Klymenko ◽  
Kateryna Tuzhyk
Keyword(s):  
Grain Yield ◽  
Crop Production ◽  
Maximum Yield ◽  
Target Function ◽  
Optimization Methods ◽  
Econometric Analysis ◽  
Practical Significance ◽  
Moderate Increase ◽  
Production Research ◽  
The Impact

The purpose of the article is to determine with the help of econometric and optimization methods the priority strategies of agrarian business in the field of crop production and to compare with the existing leaders in the use of innovations in the field of crop production. Research methods. The study is based on the use of econometric analysis methods to build trends in grain yield dynamics in leading countries in the use of innovative agricultural technologies and optimization methods for the study of dominant strategies used by agricultural enterprises in crop production. Research results. As a result of using the declining marginal grain yield depending on the amount of costs, which are determined by the cost of importing technology per 1 ha, the optimal cost values for both maximum yield and maximum profit. It is shown that at certain time intervals the costs of farmers were excessively high not only in terms of profit optimization but also to optimize yields. It is assumed that taking into account the latest innovation trends, agribusiness will move to a strategy of profit maximization Scientific novelty. As a result of econometric analysis it is shown that the use as a target function of yield leads to a significant increase in the variability of this indicator, while a moderate increase in yield is accompanied by significantly less variability. Quantitative indicators of the impact of climate risks on grain yields in Ukraine have been obtained, which explain approximately 50% of the variance in the grain yield indicator in Ukraine. Practical significance. It is shown that the representation of marginal yield in the form of a decreasing linear function is confirmed in practice. Further research, which in the presence of detailed information on the production processes of individual enterprises can be conducted by panel regression (observation points are spaced in space and time), can provide a more detailed picture of the efficiency of individual production components in their areas of interaction. Tabl.: 4. Figs.: 3. Refs.: 19.

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