The twin transition combines digital transformation and the green transition and is a core pillar of the European agenda for the Digital Decade. This study examines how digital transformation and digital human capital relate to labor productivity and greenhouse gas (GHG) intensity across European industries. We compile a country–sector dataset covering 26 European Union Member States and ten NACE A*10 sectors for 2023 using harmonized Eurostat sources. We employ a path-analytic framework based on composite indicators to assess direct, indirect, and context-dependent associations among digital transformation, digital human capital, labor productivity, and environmental performance. The results indicate a positive association between digitalization and digital human capital. While digital skills are positively related to labor productivity, their mediating role between digitalization and labor productivity appears limited. The available evidence also suggests that artificial intelligence plays only a small moderating role in the relationships analysed. On the environmental side, higher levels of digitalization and digital skills are associated with a slight reduction in GHG intensity, although effects are modest and display sectoral heterogeneity. Overall, the findings provide disciplined empirical evidence that can inform discussions on policies and strategies aimed at fostering a competitive, digitally advanced, and lower-emissions economy in the European Union.

La comparación de encuestas presenta problemas metodológicos recurrentes, dentro de los que destacan particularmente: i) las dificultades asociadas a la falta de continuidad, bien por el añadido de nuevas preguntas o por la eliminación de otras; ii) las dificultades propias en la selección de las variables a comparar; iii) la necesidad de recodificación entre cuestionarios no coincidentes, y iv) la discrecionalidad en las unidades de medida de las variables. Así, para la investigación en métodos cuantitativos se precisan procedimientos que permitan recuperar la estructura factorial, realizar comparaciones entre variables y recodificar las unidades de medida y en la escala, todo ello en distintos periodos. Para evaluar en qué medida se mantiene la estructura factorial, en el presente artículo se proponen medidas de bondad del ajuste y contrastes propios del análisis factorial confirmatorio, a lo que se añade una aplicación novedosa del principio de parsimonia a los estadísticos RMSEA, FIT y BIC, a través de la conocida regla del codo en el gráfico de sedimentación. La propuesta metodológica se valida a través de dos publicaciones del Centro de Investigaciones Sociológicas (CIS) de distintos años y centradas en el fenómeno del fraude fiscal.

In this paper, we identify a type of negotiation beyond the well-documented distributive and integrative categories in which the negotiators transcend the transaction and break away from the paradigms of individualism, which dictates that the only possible way to achieve success is by manipulating others for personal gain, emphasizing selfishness. A negotiation can only be transcendent by recognizing the human dimension of the other, prioritizing being over having, respecting the dignity of others, honouring agreements and maintaining the power of one’s word. Negotiations conducted in this manner have the potential to extend benefits to future generations (Chamoun et al. 2016). In addition to defining and identifying the Transcendent Negotiation, a statistical analysis poll, Opinión Pública y Política Fiscal XXXI (Linguaserve IS, 2017) and XXXII (Linguaserve IS, 2017), of 5000 households in Spain from the CIS (Centre of Sociological Research of Spain) was used to discern various social profiles of negotiating agents characterized by four factors (spiritual happiness, negotiating power, interpersonal ethics, and institutional ethics) and two variables (level of interpersonal trust and degree of self-empowerment). Groups with similar characteristics were identified from the statistical analysis and named according to negotiation theory and virtues. The original intent of using this statistical robust survey was to investigate the effect that the four factors and two variables mentioned above have on Transcendent negotiations. The groups were named according to negotiation theory and virtues. These are free riders, passer-by’s, pretenders, equilibrated well-positioned, outraged, equilibrated mediocre, and fighters. We observed tendencies from the statistical data group that are in line with the principles of Transcendence negotiation described in this paper.

Previous studies have established that social capital plays a significant role in individual tax-related behaviors, including inclinations toward tax evasion and compliance. This study seeks to extend the understanding of tax morale in Spain using data from the Public Opinion and Fiscal Policy Survey (CIS, Study 3332). We use factor analysis with maximum likelihood extraction and Varimax rotation to identify key social capital variables and tax attitudes. We identify profiles based on their social capital and tax compliance using cluster analysis. We will apply hierarchical clustering with Ward's chaining and k-means clustering. The robustness of the resulting profiles will be confirmed by discriminant analysis and a multilayer perceptron neural network, which will look for higher rates of correct classification as an indicator of improved profile consistency. Our findings suggest that identifying Spanish tax citizens' profiles helps analyze social capital in tax policy. After our analysis, we have determined that enhancing the accumulation of social capital variables leads to better tax adherence.

Objectives of the research: This project aims to identify the most effective tools for increasing student engagement. Research methods: An ad hoc questionnaire to measure the engagement capacity of teaching tools, principal component analysis (PCA), and machine learning forward regression. Structure of the article: Introduction, methodology and results (sampling, PCA, forward regression), discussion, and conclusions. Research findings: Active interaction and modular organization promote student engagement. A student’s inability to respond to questions about improving a subject often indicates a lack of interest. Engagement increases when previous teaching experiences have not incorporated interactive tools. Pre-class homework assignments enhance interest and make courses more practical. Tools that facilitate teacher-student interaction improve engagement, regardless of whether the teaching style is based on the teacher’s practical experience or a student-centered approach. Conclusions and recommendations: This research identifies several factors that significantly influence student engagement, including a modular structure, active classroom participation, pre- and post-class assignments, content quality, teaching style, and interaction through discussion platforms.