Abstract
Machine learning algorithms offer the capability to analyze large volumes of real-time data, providing transport authorities with valuable insights into traffic conditions, congestion hotspots, and incident detection from diverse data sources. However, these algorithms face challenges related to data quality and reliability. We conducted a comparative analysis of machine-learning models that can be used to identify and filter transportation content from social media or other sources that can provide small and concise text. The filtrated result can then feed models and/or tools used to improve and automate traffic control, operational management, and tactical management decision-making. We consider factors such as run time, generalization capacity, and performance metrics as criteria to assess their suitability for different decision levels. The analysis is supported by a dataset consisting of Twitter content. The predictions from three groups of algorithms are evaluated: traditional machine learning algorithms (Support Vector Machines, Logistic Regression, and Random Forest), a fine-tuned Google BERT model, and Google BERT models without training (BERT-base and BERT-large). The tests are performed using New York, London, and Melbourne data. The findings of this research aim to assist decision-makers in making informed choices when selecting the most appropriate method to filtrate information subsequently used for models that contribute to different traffic management tasks.

Abstract

Abstract
This article proposes the use of social representation theory to validate the structural model of structural equation modeling, thereby enhancing the understanding of the research object. To achieve this, it was employed action research to construct, implement, and confirm the practical feasibility of the metho-dological procedures described herein. This was accomplished through their practical application in a case analysis. It was possible to validate the structural model used in structural equation modeling by applying the proposed methodological procedures to a case involving the governance system construct. This validation opens the possibility for future research to use these procedures in conjunction to validate theoretical models and the causal relationships between their constructs. Therefore, the primary theoretical contribution of this paper is the proposition of a research methodology that combines social representation theory with structural equation modeling to validate the structural model. This approach reduces the risk of using the statistical method to confirm or refute a theoretical model whose causal relationships may not represent a reality supported by practice.

Abstract
This article comparedidentified models in the literature that incorporates sustainability in project management, with an integrated model used as reference, mapping their points of similarity. For this purpose, bibliographic research of 90 articles from the Web of Science and Scopus databases was carried out, which address the themes of sustainability and project management. The reference model was compared with 16 models identified during the literature search, through comparative analysis and grounded theory. As a result, the study presents the identified similarity between model & PRIME;s constructs. It is concluded that there is no pattern or convergence between the different models identified, that thereference model plays a role in stimulating the integration of sustainability with project management in a more comprehensive way.

Abstract
To ensure the safety of passengers concerning virus propagation, such as COVID-19, and keep the turnaround time at low levels, airlines should seek efficient aircraft boarding strategies in terms of both physical distancing and boarding times. This study seeks to analyze the impact of different boarding strategies in the context of the International Air Transport Association's recommendations during the pandemic to reduce interference and physical contact between passengers in airplanes. Boarding strategies such as back-to-front, outside-in, reverse pyramid, blocks, Steffen, and modified optimal have been tested in this context. This study extends the previous literature using discrete event simulation to evaluate the impact of the occupation of the middle seat by family members only. This study also analyses the impact of having passengers carrying hand luggage and priority passengers on the performance of these strategies concerning boarding times. In general, the simulation results revealed a 15% improvement in boarding times when the reverse pyramid strategy is used compared to a random strategy, which essentially results from a reduction in the boarding interferences between passengers. The results also show that Steffen's strategy is the best performing, while the blocks strategy results in the worst performance. This study has practical implications for airline companies concerning both operation efficiency and passenger safety.

Abstract
(1) Background: In this study on Robotic Process Automation (RPA), the feasibility of sustainable RPA implementation was investigated, considering user requirements in the context of this technology's stakeholders, with a strong emphasis on sustainability. (2) Methods: A multi-objective mathematical model was developed and the Weighted Sum and Tchebycheff methods were used to evaluate the efficiency of the implementation. An enterprise case study was utilized for data collection, employing investigation hypotheses, questionnaires, and brainstorming sessions with company stakeholders. (3) Results: The results underscore the significance of user requirements within the RPA landscape and demonstrate that integrating these requirements into the multi-objective model enhances the implementation assessment. Practical guidelines for RPA planning and management with a sustainability focus are provided. The analysis reveals a solution that reduces initial costs by 21.10% and allows for an efficient and equitable allocation of available resources. (4) Conclusion: This study advances our understanding of the interplay between user requirements and RPA feasibility, offering viable guidelines for the sustainable implementation of this technology.