Globalization and the ever-growing presence of technology have paved the way for better developmental opportunities in society. Nonetheless, these have also been to the detriment of the environment as well as sustainable development. The aim of this study is to discover the mediating effect of green innovation with regard to the relationship which exists between green culture and environmental performance in the State of Mexico’s automotive sector. The research hypotheses were formulated following an extensive study of the literature available and were based on resource- and capability-based theory, specifically, the natural-resource view of the firm (NRBV). The design of the study was non-experimental and cross-sectional with a confirmatory reach, applied to a sample of 157 observations. The proposed theoretical model was tested using partial least squares structural equation modeling (PLS-SEM). The findings provide empirical evidence that green innovation acts as a mediator variable on the relationship between green culture and environmental performance. The scientific merit of the study is found in its proposal of a hierarchical second-order model, categorized as reflective-formative, and the study’s confirmation of the role of green innovation as a mediating construct. Therefore, the findings herein can be considered as complementary to the existing body of knowledge in the field. The practical implications derived from this study will contribute to sustainable development and expand knowledge in the following areas: Government institutions, companies that operate in the sector, decision makers, academics, and practitioners who are working on this issue at different levels.

This paper defines the social factors that determine sustainable behavior and identifies the elements that promote such behavior. These factors are external from the individual and causal regarding sustainable behavior, an area that receives little attention in literature. It uses a theoretical model, based on existing research, which is tested through a questionnaire with 26 indicators adapted to the Spanish context. In an initial analysis, this model proposed, as determining social factors in the CCS, aspects such as government action, social pressure, influence of the social environment, demographic variables (age, gender, education level), education and information, and market conditions. Finally, it was concluded that 43.4% of the variance of the endogenous latent variable (SCC) can be explained only by three exogenous latent constructions: environmental influences (in particular the influence of family and friends, as well as that generated by cultural factors such as traditions), education and information (specifically related to information on sustainability and the effects of personal consumption on the environment), and market conditions (referring to the positive perception of sustainable products by consumers, including their willingness to pay higher prices than those of conventional products). The rest of the exogenous variables did not have a significant relationship with the endogenous variable. These results are very useful for government institutions, companies that operate in the sector and pro-environmental and pro-social groups, that knowing what motivates people to adopt this form of behavior can design relevant strategies to get positive answers about the environment, the economy and the society.

In recent years educational institutions are increasingly using online learning and because of this trend it is necessary to investigate its impact on student academic performance. Although this topic has been addressed in different educational fields before, there is an objective justification for our approach. Thus, the reasoning behind this particular research is the fact that recent findings have shown that the academic performance of students using online education is affected by a series of motivating factors which can have an impact on their performance. The main goal of this paper is to highlight and analyze the mediating effect of intrinsic student motivation and student academic engagement and how they affect the relationship between the range of support, which students receive during their online learning and thus their academic performance. This study was conducted in two higher educational institutions in Mexico and Romania, with a sample of 822 students. The data was analyzed using a second generational PLS-SEM technique. The results confirm that the support students enjoy during online learning has no direct impact on their academic performance, unless it is fully mediated by their own intrinsic motivation and academic engagement. The influence of Gender was also analyzed, but it was not found to be a determining factor of academic performance in both higher educational institutions. These findings not only have theoretical and practical implications for students, teachers and education authorities, they also help us to broaden the field of knowledge in the e-learning environment.

The objective of this article was to determine the mediating effect of shared knowledge and organisational commitment in the relationship between organisational values and collaborative public management. Organisational values are also made up as a second-order construct consisting of other first order sub-dimensions such as authority, autonomy, conservatism, equality, harmony, and hierarchy. This research is based both on the Theory of Resources and Capacities and the theoretical perspective based on knowledge. The hypotheses proposed were supported with the use of structural equation models based on composites (PLS-SEM). The results show empirical evidence of a multiple fully mediating effect. The findings confirmed that organisational values do not have a significant direct positive impact on collaborative public management unless they are full mediated by shared knowledge and organisational commitment. In addition, this research framework is effective for improving public employees’ work efficiency and has practical implications for scholars, practitioners, and the authorities.

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.

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