In the last decade we have witnessed a growing amount of interest for developing better ‘exchange’ between universities, research centres and technology parks and companies, governments and other institutions. The biggest aim of those projects is, on the one hand, to make sure that valuable research does not stay hidden in the ivory tower of academia, and, on the other, that there are clear indications for what kinds of solutions are needed in the market. Due to the lack of empirical research in the topic, the focus of this paper is to establish and explain which factors determine the demand for technological services and how they can contribute to the promotion of greater university–business collaboration in R&D and innovation. To achieve that goal, we applied the PLS-SEM (Partial Least Squares Structural Equation Modelling) method in order to create a theoretical model, which was then verified through the application of the CTA (Confirmatory Tetrad Analysis) with the purpose of evaluating whether the specification of the chosen measurement model based on the theoretical rationale was supported by data. The test run was performed on 96 companies from the Spanish region of Huelva. It showed that only four of the considered factors, namely influence of the environment, market conditions, technology adoption decision and economic characteristics of the company, constituted 65.76% of the variance of the endogenous latent Demand for Technological Services. We believe that thanks to the proposed model and its adaptivity, it is possible to design relevant policies and undertakings aimed at promoting the research-business collaboration at the regional, national and international levels.

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As the world is fighting against the continuous spread of the COVID-Sars-2 virus and the consequences the pandemic has brought about on economic, political and societal levels, the emergence of the vaccination programs seems to be the biggest hope for a quick return to, popularly called, the “new normal”. As it is not feasible to vaccinate at the same time the whole population, the states, provinces and cities had arranged – though, admittedly, taking into consideration limited numbers of criteria - homogenous groups of citizens, who, labelled as “risk groups”, have been chosen as those who will be receiving the vaccination before others, adding to the already existing feelings of chaos and shortage. We want to address the issue that despite the access to the expertise and knowledge of intradisciplinary committees, we still do not have a satisfactory answer regarding the further steps for the vaccination programs. We believe it is due to the persistence of the binary way of reasoning, with its tendency to overlook the complexity of the issue and emphasise objectivity while neglecting the subjective factors that cannot be easily quantified. For that very reason, we propose the application of the theories of uncertainty with the support of the Fuzzy Subset Theory, which will result in the creation of the humanist algorithms of clustering of populations, allotment of different kinds of vaccine for diverse persons in the groups and, finally ranking for the priority of vaccination. This approach will allow designing such a model to maintain, to the highest possible level, the principles of ethics, morale and solidarity, and efficiency and effectiveness.

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.