Ancestral knowledge is essential in the construction of learning to preserve the sense of relevance, transmit and share knowledge according to its cultural context, and maintain a harmonious relationship with nature and sustainability. The objective of this research is to study and analyze the management of ancestral knowledge in the production of the Raicilla to provide elements to rural communities, producers, and facilitators in decision-making to be able to innovate and be more productive, competitive, sustainable, and improve people’s quality of life. The methodological strategy was carried out through Bayesian networks and Fuzzy Logic. To this end, a model was developed to identify and quantify the critical factors that impact optimally managed technology to generate value that translates into innovation and competitive advantages. The evidence shows that the optimal and non-optimal management of knowledge, technology, and innovation management and its factors, through the causality of the variables, permits us to capture the interrelationship more adequately and manage them. The results show that the most relevant factors for adequate management of ancestral knowledge in the Raicilla sector are facilitators, denomination of origin, extraction and fermentation, and government. The proposed model will support these small producers and help them preserve their identity, culture, and customs, contributing greatly to environmental sustainability.

To evaluate the efficiency of decision-making units, researchers continually develop models simulating the production process of organizations. This study formulates a network model integrating undesirable outputs to measure the efficiency of Vietnam’s banking industry. Employing methodologies from the data envelopment analysis (DEA) approach, the efficiency scores for these banks are subsequently computed and comparatively analyzed. The empirical results indicate that the incorporation of undesirable output variables in the efficiency evaluation model leads to significantly lower efficiency scores compared to the conventional DEA model. In practical terms, the study unveils a deterioration in the efficiency of banking operations in Vietnam during the post-Covid era, primarily attributed to deficiencies in credit risk management. These findings contribute to heightening awareness among bank managers regarding the pivotal importance of credit management activities.

This study addresses the impact of the tourism sector on poverty, poverty depth, and poverty severity in Indonesia, focusing on the micro-level dynamics in the province. Despite numerous tourism destinations, their strategic contribution to regional progress remains underexplored. The motivation stems from the need to comprehend the nuanced relationship between tourism and poverty at both the national and local levels, with specific attention to the untapped potential at the province level in Indonesia. We hypothesize that a higher tourism sector GRDP will be inversely correlated with poverty levels, and the inclusion of a Covid-19 variable will reveal a structural impact on poverty dynamics. Employing a Panel Regression Model, secondary data from the Central Statistics Agency (BPS) spanning 2011–2020 is utilized. A panel data regression equation model, including CEM, FEM, and REM, is employed to analyze the intricate relationship between tourism and poverty. The findings demonstrate a negative correlation between higher tourism sector GRDP and the number of poor people. The Covid-19 variable, considered a structural break, reveals a significant association between increased cases and elevated poverty and severity across Indonesian provinces. This study contributes a micro-level analysis of tourism’s role, emphasizing its impact at the provincial level. The findings underscore the need for strategic initiatives to harness the untapped potential of tourism in alleviating poverty and promoting regional progress.

The Circular Economy is one of the most prominent cross-disciplinary and cross-sectoral concepts to emerge in recent decades. It has permeated academia, policymaking, business, NGOs, and the general public, leading to numerous applications of the concept, some of which only partially overlap. In this article, we review recent debates and research trends in the Circular Economy, outlining the ten most common groups of its conceptualizations using the PRISMA (Preferred Items for Systematic Reviews and Meta-Analysis) method. We then propose a post disciplinary and transnational research program on the Circular Economy that would not only combine hard and soft sciences in unprecedented ways but also have important practical applications, such as developing tools to embed the Circular Economy in natural, technical, economic, and socio-cultural settings.

The article presents an answer to the current challenge about needs to form methodological approaches to the digital transformation of existing industrial enterprises (EIE). The paper develops a hypothesis that it is advisable to carry out the digital transformation of EIE based on considering it as a complex technical system using model-based system engineering (MBSE). The practical methodology based on MBSE for EIE digital representation creation are presented. It is demonstrated how different system models of EIE is created from a set of entities of the MBSE approach: requirements—unctions—components and corresponding matrices of interconnections. Also the principles and composition of tasks for system architectures creation of EIE digital representation are developed. The practical application of proposed methodology is illustrated by the example of an existing gas distribution station.