PLS-SEM model on business demand for technological services and R&D and innovation activities
Abstract
The aim of the current study is to search for the elements that determine the companies’ demand for technological services, and by doing so, to contribute to the advancement of a closer University-Company partnership in the sphere of activities in research, development and innovation. Based on the PLS-SEM methodology, an explanatory-predictive model was drawn up, which concluded that the four most influential variables are: the influence of the environment, market conditions, the technology adoption decision and the economic characteristics of the company. The originality and main contributions of this work lie in the construction and design of the proposed model, particularly the application of both the Confirmatory Tetrad Analysis and the Global Goodness-of-Fit measures adapted for the scope of PLS-SEM, both aiming to elaborate on its use and to provide a model that could be used by other researchers in different regions. By implementing this type of analysis, it is possible to better understand the drivers that push the choice of enterprises concerning the demand for technological services and, subsequently, policymakers, academy, and R&D agencies, as well as corporations leading to better strategies for closer and stronger cooperation and collaboration among themselves.
Keyword : technology demand, technology adoption, R&D&I, PLS-SEM, CTA-PLS
How to Cite
García-Machado, J. J., Sroka, W., & Nowak, M. (2023). PLS-SEM model on business demand for technological services and R&D and innovation activities. Technological and Economic Development of Economy, 29(1), 1–22. https://doi.org/10.3846/tede.2023.17968
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Conde-Pumpido Touron, R., & Cerezo García, L. (2019). Investigación y Transferencia de Conocimiento en las Universidades Españolas 2017. CRUE Universidades Españolas. http://www.crue.org/Documentos%20compartidos/Publicaciones/Encuesta%20Inves
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Dijkstra, T., & Henseler, J. (2015b). Consistent partial least squares path modeling. MIS Quarterly, 39(2), 297–316. https://doi.org/10.25300/MISQ/2015/39.2.02
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Etzkowitz, H., & Leydesdorff, L. (2000). The dynamics of innovation: From National Systems and “Mode 2” to a Triple Helix of university–industry–government relations. Research Policy, 29(2), 109–123. https://doi.org/10.1016/S0048-7333(99)00055-4
Etzkowitz, H., Webster, A., Gebhardt, C., & Terra, B. R. C. (2000). The future of the university and the university of the future: Evolution of ivory tower to entrepreneurial paradigm. Research Policy, 29(2), 313–330. https://doi.org/10.1016/S0048-7333(99)00069-4
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Figueroa-García, G., García-Machado, J. J., & Pérez-Bustamante Yábar, D. C. (2018). Modeling the social factors that determine sustainable consumption behaviour in the community of Madrid. Sustainability, 10(8), 2811. https://doi.org/10.3390/su10082811
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