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This paper aims to propose an accurate and efficient decision-making process adapted to the specific context of Claim Management situations, implying partners engaged in a high-involvement relationship.

We used a three-step approach: first, an inductive phase based on 12 past case studies. Second, a theory-building phase. Third, a theory-testing phase based on an ongoing case study to observe and test our propositions.

Proposal 1: Partner’s Strategic Value is an influential decision parameter that must be incorporated into Claim Management-related decision-making processes in high-involvement relationships. Proposal 2: The Fast-and-Frugal Heuristic is adapted to the intense, interactive and iterative nature of the Claim Management context. Our final proposal combines these two findings, i.e. a Fast-and-Frugal Heuristic incorporating the Partner’s Strategic Value and based on using decision criteria as a sequence, not simultaneously.

In the context of high-involvement business relationships and Claim Management, this study introduces the importance of selecting an appropriate decision methodology and integrating a strategic decision parameter (Partner’s Strategic Value) into an operational decision-making context. Furthermore, the principle of considering decision parameters in a specific sequence corresponds to the iterative and interactive nature of the Claim Management processes.

This article presents two Brazilian Portuguese corpora collected from different media concerning public security issues in a specific location. The primary motivation is supporting analyses, so security authorities can make appropriate decisions about their actions.

The corpora were obtained through web scraping from a newspaper's website and tweets from a Brazilian metropolitan region. Natural language processing was applied considering: text cleaning, lemmatization, summarization, part-of-speech and dependencies parsing, named entities recognition, and topic modeling.

Several results were obtained based on the methodology used, highlighting some: an example of a summarization using an automated process; dependency parsing; the most common topics in each corpus; the forty named entities and the most common slogans were extracted, highlighting those linked to public security.

Some critical tasks were identified for the research perspective, related to the applied methodology: the treatment of noise from obtaining news on their source websites, passing through textual elements quite present in social network posts such as abbreviations, emojis/emoticons, and even writing errors; the treatment of subjectivity, to eliminate noise from irony and sarcasm; the search for authentic news of issues within the target domain. All these tasks aim to improve the process to enable interested authorities to perform accurate analyses.

The corpora dedicated to the public security domain enable several analyses, such as mining public opinion on security actions in a given location; understanding criminals' behaviors reported in the news or even on social networks and drawing their attitudes timeline; detecting movements that may cause damage to public property and people welfare through texts from social networks; extracting the history and repercussions of police actions, crossing news with records on social networks; among many other possibilities.

The work on behalf of the corpora reported in this text represents one of the first initiatives to create textual bases in Portuguese, dedicated to Brazil's specific public security domain.

Staffing is one of the most influential human resource (HR) activities and is the primary method of hiring and retaining human resources. Among staffing’s several activities, recruitment and selection are one of the most crucial activities. It is possible to rehire former firm employees using the talent management strategy known as “boomerang recruitment”. The boomerang recruitment trend has tremendously grown because many employees who believe they are qualified for the position now wish to return to their old employers. According to data, boomerang employees can be 50% less expensive than conventional ways of hiring. The purpose of this study is to identify the generic critical factors that play a role in the boomerang hiring process based on the literature review. Next, the objective is to determine the relative weight of each of these factors, rank the candidates, and develop a decision-making model for boomerang recruitment.

This paper focuses on the grey-based multicriteria decision-making (MCDM) methodology for recruiting some of the best candidates out of a few who worked for the organization earlier. The grey theory yields adequate findings despite sparse data or significant factor variability. Like MCDM, the grey methods also incorporate experts' opinions for evaluation. Furthermore, sensitivity analysis is also done to show the robustness of the suggested methodology.

Seven (7) recruitment criteria for boomerang employees were identified and validated based on the opinions of industry experts. Using these recruitment criteria, three candidates emerged as the top three and created a pool out of six. In addition, this study finds that Criteria 1 (C1), the employee's past performance, is the most significant predictor among all other criteria in boomerang hiring.

Since the weights and ratings of attributes and alternatives in MCDM methods are primarily based on expert opinion, a significant difference in expert opinions (caused by differences in their knowledge and qualifications) may impact the values of the grey possibility degree. However, enough attention was taken while selecting the experts for this study regarding their expertise and subject experience.

The proposed method provides the groundwork for HR management. Managers confronted with recruiting employees who want to rejoin may use this model. According to experts, each attribute is not only generic but also crucial. In addition, because these factors apply to all sectors, they are industry-neutral.

To the best of the authors’ knowledge, this is the first study to apply a grey-based MCDM methodology to the boomerang recruitment model. This study also uses an example to explain the computational intricacies associated with such methods. The proposed system may be reproduced for boomerang recruiting in any sector because the framework is universal and replicable. Furthermore, the framework is expandable to include new criteria for different work.

The objective is to contribute to the development of strategies through the identification of sustainability practices. Thus, the research has a twofold objective: to unveil sustainability practices integrated into last-mile logistics activities by e-commerce retailers, analyze the interrelations among these practices and categorize them based on their significance for small Brazilian e-commerce retailers.

A literature mapping was conducted to identify sustainability practices in last-mile activities adopted by e-retailers, leading to the proposal of a meta-model. A total of 67 articles are part of the final sample. Subsequently, the study applied the Decision-Making Trial and Evaluation Laboratory (DEMATEL) multicriteria decision-making technique to structure the research problem through cause-and-effect analysis among practices, aiming to prioritize critical practices.

The results indicate a strong dependence on economic practices to enable sustainability in last-mile logistics. In the economic dimension of sustainability, operating costs and quality of services are effect variables and achieved the highest relation concerning the other practices.

The article provides theoretical contributions by addressing two complementary areas of knowledge: Stakeholder Theory and Sustainability, also aligning with Global Reporting Initiative (GRI) guidelines. In practical terms, it stands out for offering valuable insights into the implementation of sustainable strategies by identifying economic, environmental and social practices in last-mile logistics, particularly within the context of small businesses in the e-retail segment.

The results help e-retailers re-evaluate last-mile logistics processes from a sustainability perspective. This study aims to fill the knowledge gap in the current literature on adopting sustainable practices in small e-commerce retail firms.

Considering that one of the pillars of sustainability is a commitment to social development, this study contributes to understanding the view of small e-retailers on the independent goods delivery workers responsible for the delivery of goods.

The originality of this research lies in identifying economic, social and environmental sustainability practices adopted by e-retailers in last-mile logistics processes. Additionally, the study focuses on the small-scale e-commerce retail segment, an area that has been little explored in the Brazilian context. Lastly, the proposed meta-model contributes to addressing practices from the perspective of Stakeholder Theory and the Sustainability approach.

El objetivo es contribuir al desarrollo de estrategias mediante la identificación de prácticas sostenibles. Por lo tanto, la investigación tiene un doble objetivo: revelar las prácticas de sostenibilidad integradas en las actividades logísticas de última milla de minoristas de comercio electrónico, analizar las interrelaciones entre estas prácticas y categorizarlas según su importancia para los pequeños minoristas de comercio electrónico en Brasil.

Se llevó a cabo un mapeo de la literatura para identificar prácticas de sostenibilidad en las actividades de última milla adoptadas por minoristas en línea, lo que llevó a la propuesta de un metamodelo. Un total de 67 artículos forman parte de la muestra final. Posteriormente, el estudio aplicó la técnica de toma de decisiones multicriterio Decision-Making Trial and Evaluation Laboratory (DEMATEL) para estructurar el problema de investigación mediante análisis de causa y efecto entre las prácticas, con el objetivo de priorizar las prácticas críticas.

El resultado indica una fuerte dependencia de prácticas económicas para implementar la sostenibilidad en la logística de última milla. En la dimensión económica de la sostenibilidad, los costes operacionales y la calidad de los servicios son variables de efecto y presentan una fuerte correlación.

La originalidad de esta investigación radica en identificar prácticas de sostenibilidad económica, social y ambiental adoptadas por minoristas en línea en los procesos logísticos de última milla. Además, el estudio se centra en el segmento minorista de comercio electrónico a pequeña escala, un área poco explorada en el contexto brasileño. Por último, el metamodelo propuesto contribuye a abordar prácticas desde la perspectiva de la Teoría de los Stakeholders y el enfoque de Sostenibilidad.

El artículo proporciona contribuciones teóricas al abordar dos áreas complementarias de conocimiento: la Teoría de los Stakeholders y la Sostenibilidad, alineándose también con las directrices de la Iniciativa de Reporte Global (GRI). En términos prácticos, destaca al ofrecer ideas valiosas sobre la implementación de estrategias sostenibles al identificar prácticas económicas, ambientales y sociales en la logística de última milla, particularmente en el contexto de las pequeñas empresas en el segmento minorista en línea.

Los resultados ayudan a los minoristas electrónicos a reevaluar los procesos logísticos de última milla desde una perspectiva de sostenibilidad. Este estudio pretende contribuir el avance del conocimiento de la literatura actual sobre la adopción de prácticas sostenibles en pequeñas empresas de comercio electrónico.

Teniendo en cuenta que uno de los pilares de la sostenibilidad es el compromiso con el desarrollo social, este estudio contribuye a comprender la visión de los pequeños minoristas electrónicos sobre los trabajadores independientes encargados de la entrega de mercancías.

To address the challenges encountered in disaster responses, optimize resource utilization, minimize environmental and social impact, and ensure transparency and accountability, it is essential to review humanitarian supply chains and incorporate sustainability considerations. Humanitarian organizations can enhance their ability to deliver timely and effective assistance to those in need by continuously improving supply chain practices. Consequently, this work explores the convergence of two fast-growing domains: sustainability and humanitarian supply chain management (HSCM).

The authors conducted a systematic literature review of peer-reviewed articles to identify the prominent research trends and themes from the two domains' interactions. The extant literature is represented under the theory, context, characteristics, and research method (TCCM) framework. The authors have utilized a stakeholder theory perspective to identify coordination and collaboration among the various stakeholders.

This study's review findings reveal five future research directions formulating this study's central themes: the role of environmental sustainability, coordination, and collaboration in building effective HSCs; the role of humanitarian aid for the responsive HSC; the influence of big data predictive analytics on the HSC performance; development and empirical validation of sustainable HSC performance framework; the role of HSC stakeholders in building effective and efficient HSCs.

There is no existing academic literature review available on sustainable HSCM. This review fills this void by fostering discussion about sustainable humanitarian supply chains where the authors notably propose the TCCM framework in the context of sustainable HSCM, followed by a stakeholder network.

Factors like bid price, submission time, and number of bidders influence the procurement process in public projects. These factors and the award criteria may impact the project’s financial compliance. Predicting budget compliance in construction projects has been traditionally challenging, but Machine Learning (ML) techniques have revolutionised estimations.

In this study, Portuguese Public Procurement Data (PPPData) was utilised as the model’s input. Notably, this dataset exhibited a substantial imbalance in the target feature. To address this issue, the study evaluated three distinct data balancing techniques: oversampling, undersampling, and the SMOTE method. Next, a comprehensive feature selection process was conducted, leading to the testing of five different algorithms for forecasting budget compliance. Finally, a secondary test was conducted, refining the features to include only those elements that procurement technicians can modify while also considering the two most accurate predictors identified in the previous test.

The findings indicate that employing the SMOTE method on the scraped data can achieve a balanced dataset. Furthermore, the results demonstrate that the Adam ANN algorithm outperformed others, boasting a precision rate of 68.1%.

The model can aid procurement technicians during the tendering phase by using historical data and analogous projects to predict performance.

Although the study reveals that ML algorithms cannot accurately predict budget compliance using procurement data, they can still provide project owners with insights into the most suitable criteria, aiding decision-making. Further research should assess the model’s impact and capacity within the procurement workflow.

Previous research predominantly focused on forecasting budgets by leveraging data from the private construction execution phase. While some investigations incorporated procurement data, this study distinguishes itself by using an imbalanced dataset and anticipating compliance rather than predicting budgetary figures. The model predicts budget compliance by analysing qualitative and quantitative characteristics of public project contracts. The research paper explores various model architectures and data treatment techniques to develop a model to assist the Client in tender definition.

Reconstruction of old buildings is often necessary after prolonged usage, but these projects encounter various complexities, leading to their failure. However, there is a lack of studies that focus on investigating the complexity of old building reconstruction initiatives. Thus, this study aims to examine the complexity of reconstruction projects for old buildings in Vietnamese urban areas.

Through a literature review and discussions with experienced practitioners, 12 significant complexity factors were identified. The study then utilized the fuzzy decision-making trial and evaluation laboratory (DEMATEL) technique to analyze the interrelationships among these complexity factors.

The findings revealed intricate interdependencies among the complexity factors, visualized in a complexity map. The map highlighted the critical complexities of site compensation, clearance and the long project duration. Furthermore, a causal diagram categorized the complexity factors into net-effect and net-cause groups.

By examining the relationships and interactions among these factors, the study emphasizes the interconnected nature of complex systems and the influence of one factor on others. Therefore, decision-makers and stakeholders involved in reconstructing old buildings are suggested to possess a comprehensive understanding of these interdependencies to ensure effective decision-making.

This study aims to explore the integration of Industry 4.0 technologies with lean six sigma practices in the manufacturing sector for enhanced process improvement.

This study used a fuzzy decision-making trial and evaluation laboratory approach to identify critical Industry 4.0 technologies that can be harmonized with Lean Six Sigma methodologies for achieving improved processes in manufacturing.

The research reveals that key technologies such as modeling and simulation, artificial intelligence (AI) and machine learning, big data analytics, automation and industrial robots and smart sensors are paramount for achieving operational excellence when integrated with Lean Six Sigma.

The study is limited to the identification of pivotal Industry 4.0 technologies for Lean Six Sigma integration in manufacturing. Further studies can explore the implementation challenges and the quantifiable benefits of such integrations.

Integrating Industry 4.0 technologies with Lean Six Sigma enhances manufacturing efficiency. This approach leverages AI for predictive analysis, uses smart sensors for energy efficiency and adaptable robots for flexible production. It is vital for competitive advantage, significantly improving decision-making, reducing costs and streamlining operations in the manufacturing sector.

The integration of Industry 4.0 technologies with Lean Six Sigma in manufacturing has significant social implications. It promotes job creation in high-tech sectors, necessitating advanced skill development and continuous learning among the workforce. This shift fosters an innovative, knowledge-based economy, potentially reducing the skills gap. Additionally, it enhances workplace safety through automation, reduces hazardous tasks for workers and contributes to environmental sustainability by optimizing resource use and reducing waste in manufacturing processes.

This study offers a novel perspective on synergizing advanced Industry 4.0 technologies with established Lean Six Sigma practices for enhanced process improvement in manufacturing. The findings can guide industries in prioritizing their technological adoptions for continuous improvement.

Throughout human history, the occurrence of disasters has been inevitable, leading to significant human, financial and emotional consequences. Therefore, it is crucial to establish a well-designed plan to efficiently manage such situations when disaster strikes. The purpose of this study is to develop a comprehensive program that encompasses multiple aspects of postdisaster relief.

A multiobjective model has been developed for postdisaster relief, with the aim of minimizing social dissatisfaction, economic costs and environmental damage. The model has been solved using exact methods for different scenarios. The objective is to achieve the most optimal outcomes in the context of postdisaster relief operations.

A real case study of an earthquake in Haiti has been conducted. The acquired results and subsequent management analysis have effectively assessed the logic of the model. As a result, the model’s performance has been validated and deemed reliable based on the findings and insights obtained.

Ultimately, the model provides the optimal quantities of each product to be shipped and determines the appropriate mode of transportation. Additionally, the application of the epsilon constraint method results in a set of Pareto optimal solutions. Through a comprehensive examination of the presented solutions, valuable insights and analyses can be obtained, contributing to a better understanding of the model’s effectiveness.

The purpose of this study is developing a new buy-back coordination contract in the symbiotic supply chain. In this new contract, the goal of the supply chain members (profit maximization) is realized.

This paper encourages the manufacturer to order products optimally by presenting a new buy-back coordination contract, and in return, the supplier undertakes to buy the unsold products from the manufacturer at the buy-back price. By using data-driven decision-making and multiobjective decision-making and considering the existing conditions in the symbiosis industry, a contract has been presented that guarantees the profits of supply chain members.

In this paper, it was found out how the authors can determine the order quantity, buy-back price and wholesale price in a symbiotic supply chain in such a way that it makes a profit for both the supplier and the manufacturer. In other words, how to determine these variables to encourage the manufacturer to order more quantity to the supplier so that both will benefit.

To the best of the authors’ knowledge, this is the first paper that defines a new buy-back coordination contract in the symbiotic supply chain by considering uncertain demand and a multiobjective model. Due to the importance of environmental issues, the sharing of resources by companies and organizations with each other, and the necessity of their cooperation, industries are moving toward a symbiosis industry.