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This paper aims to understand the difficulties faced by Latin American oil and gas (O&G) companies in adopting integrated practices aligned with the UN Sustainable Development Goals (SDG) Agenda.

A Delphi study was conducted with 14 experts with extensive knowledge and experience in the O&G sector to collect opinions and investigate sustainable practices in the Latin American context.

A consensus was reached after two rounds, demonstrating a unified view of sustainability experts on the difficulties faced by O&G companies to adopt practices aligned with the SDGs. The difficulties identified through the Delphi method were allocated into five clusters named: “public sector and governments,” “civil society,” “corporate issues,” “technology and innovation” and “financial aspects.” These clusters were used to discuss the main challenges associated with implementing business practices that recognize the SDGs and their achievement as a synergistic reinforcing system rather than an additive structure.

This study provides further insights into the underexplored subject relating to the challenges experienced by Latin American O&G companies in the implementation of the SDGs, adopting the perspective of academic and industry experts in this field. The findings can help professionals in O&G companies implement sustainable practices, policymakers in debates about futures laws and regulations and academic in future research.

The purpose of this paper is to examine competence management practices in Brazilian industries using ISO 10015 as a framework of analysis, which establishes guidelines for competence management and people development.

A survey was conducted with 22 high-qualified human resources management (HRM) professionals (81.8% of participants hold a PhD) with extensive experience in the Brazilian industrial sector (an average of 20.4 years). The experts assessed 13 practices (P) elaborated based on the ISO 10015:2020, considering two categories: large industries (LI) and small and medium-sized industries (SMI). Data analysis was performed using Hierarchical Cluster Analysis, frequency analysis, Fuzzy TOPSIS and sensitivity analysis.

The practice “individual competences are correctly defined by organizations at all hierarchical levels” was deemed the best practice for LIs, while the practice “clear definition of activities and their specificities when structuring competence management and people development programs” was considered the best practice for SMIs. The practice “organizations map employees' future competence and development needs on a regular basis” received the lowest rating for both LIs and SMIs. When compared to LIs, SMIs have more severe deficiencies in applying competence management practices. The study's findings can be of great value in assisting managers in implementing structured competence management systems and people development initiatives.

The findings of this study can be used by managers of businesses of all sizes and economic sectors to analyze their critical points in order to identify opportunities to improve their competence management systems and people development programs.

This study fills a knowledge gap by analyzing the adoption of competence management practices in Brazil, answering the call for HRM research in developing countries. By using ISO 10015 as a framework of analysis, this study also addresses the literature gap regarding this important and relatively new management tool.

This research aims to understand the primary challenges encountered by entrepreneurs operating in emerging economies, where entrepreneurship plays a vital role. The study places a particular emphasis on entrepreneurs in Brazil.

The research methodology involved the analysis of data obtained from interviews, using both content analysis and Grey Relational Analysis techniques.

The analysis revealed several prominent difficulties that entrepreneurs face in these domains. These challenges encompassed issues such as grappling with intricate taxation systems and the associated tax burden, navigating government bureaucracy, securing access to essential financing and initial investments, contending with the absence of supportive government programs and addressing the dynamic nature of market conditions. The findings on the most critical barriers reveal potential pathways for entrepreneurs, policymakers and universities to act in developing the entrepreneurial ecosystem in emerging economies.

The insights garnered from this research have the potential to inform the formulation of robust public policies aimed at fostering entrepreneurship and innovation in emerging countries. Furthermore, these findings can serve as a valuable resource for planning initiatives designed to train engineers to become successful entrepreneurs.

This paper applies fuzzy grey cognitive maps (FGCM) to support multicriteria group decision making (GDM) on supply chain performance (SCP) considering the role of organizational culture as a moderating factor.

This paper follows the quantitative axiomatic prescriptive model-based research. It introduces a MGDM model that relies on the SCOR® model performance attributes and Hofstede’s cultural dimensions. The proposal is underpinned by the soft computing technique of FGCM, aimed at addressing the inherent subjectivity associated with evaluating the culture-performance relationship within supply chains.

The FGCM-based model proposes a management matrix tool for supporting SPC management. It results in a graphical representation that deconstructs SCP and organizational culture into key elements and provides directives for action plans that align improvement efforts. An illustrative application is presented to guide and promote the model’s application in different configurations of supply chains.

This model offers valuable insights into addressing the impact of organizational culture on decision-making related to SCP. Additionally, it facilitates scenario simulation. The management matrix visually illustrates how each performance attribute is influenced by each cultural dimension on a quantitative scale. It also ranks these attributes based on the overall level of influence they receive from culture.

The study provides a unique outlook on the use of FGCMs to support the SCP decisional process by detailing and accounting for the influence of organizational culture. This is done through the development of a novel matrix that allows for visual management and benchmarking.

This study aims to provide an analysis of teaching the “10 Rs” – Refuse, Rethink, Reduce, Reuse, Repair, Remodel, Remanufacture, Reuse, Recycle and Recover energy, in technological-level undergraduate courses offered in Brazil. Technological undergraduate courses are more dynamic and pragmatic than bachelor’s degrees and aim to meet market demand.

The study collected data from 39 educators who know the reality of technological-level undergraduate courses in Brazil. The data were analyzed using the fuzzy technique for order preference by similarity to ideal solution class technique.

The main findings of the research show potential for improvement in teaching all the “Rs” analyzed when considering technological-level undergraduate courses. Refuse, Restore and Recover energy are the most critical when considering how they should be taught in undergraduate technology courses in Brazil.

The paper’s originality lies in a unique empirical analysis of the circular economy – which is increasingly emerging as an intriguing approach to seeking sustainability in production chains – and the new generation of professionals in technological undergraduate courses who need to be educated and aligned with these concepts. The results can improve the curriculum, syllabus, course objectives and learning outcomes, upgrading the courses’ pedagogical projects.

The heterogeneous character of Industry 4.0 opens opportunities for studies to understand the difficulties and challenges found in the transformation process of manufacturers. This article aims to present a critical analysis of the modernization process of an Industry 3.0 automated cell into a fully autonomous cell of Industry 4.0. The objective is to elucidate the difficulties found in this transition process and the possible ways to overcome the challenges, focusing on the management perspective.

For this, the needed steps for the technology transition were defined and the main I4.0 enabling technologies were applied, such as the application of machine learning algorithms to control quality parameters in milling.

The main challenges found were related to the obsolescence of the equipment present in the cell, challenges in data integration and communication protocols, in addition to the training of people who work actively in the project team. The difficulties faced were discussed based on similar studies in the literature and possible solutions for each challenge.

This understanding of possible barriers in the modernization process, and the step-by-step defined for this transition, can be important references for professionals working in manufacturing industries and researchers who aim to deepen their studies in this important and disruptive stage of world industrialization.