In this study we present the implementation of Action Research (AR) within Málaga Racing Team (MART) at the University of Málaga (UMA); initially launched as a multidisciplinary project to participate in Formula Student (FS). Founded in 2016 by a small group of engineering students, MART has evolved into an innovative educational initiative, now involving eighty students from over twenty different undergraduate and graduate programs. MART’s mission extends beyond vehicle development; it encompasses educational, social, and research initiatives aimed at fostering technical skills, promoting social responsibility, and encouraging interdisciplinary collaboration among students. The primary aim of the study is to show how AR has facilitated and guided MART’s progress and achievements, addressing the dual objectives of experiential learning and community engagement.AR, recognised for its iterative and participatory nature, is particularly suited for projects that integrate technical and educational objectives. This approach allows MART to systematically progress through cycles of planning, action, observation, and reflection, facilitating continuous improvement and problem-solving. Through AR, MART has achieved significant milestones, including transitioning from combustion to electric vehicle technology and developing programs such as MART Academy, MART Social, MART Academy School or MART Research. These programs provide specialised training for students, drive social impact through outreach initiatives, contribute to the local community, particularly by promoting STEAM vocations among younger audiences, and facilitates knowledge dissemination and academic contributions.The results demonstrate the effectiveness of AR in enhancing MART’s technical performance and educational impact. Structured cycles have enabled MART to improve both vehicle design and interdisciplinary skill development, leading to notable placements in FS competitions. Additionally, MART’s social initiatives, supported by the AR framework, have positively impacted the community, aligning with the United Nations’ Sustainable Development Goals (SDGs) in education and innovation.The discussion addresses how AR has assisted MART in overcoming challenges related to interdisciplinary coordination and resource management. Coordination among students from various disciplines, including engineering, business, and communication, was facilitated through structured feedback mechanisms and regular team meetings, fostering a collaborative culture. Despite resource limitations, particularly during the transition to electric vehicle technology, MART managed to adapt and grow by establishing partnerships and refining its sponsorship strategies.This study affirms the potential of AR as an approach for educational innovation in multidisciplinary settings. The iterative cycles of AR have allowed MART to balance technical success with social responsibility, setting a benchmark for other educational initiatives. The findings underscore the value of continuous reflection and adaptation in managing complex projects and suggest that AR can serve as an effective approach for projects that aim to integrate technical, educational, and social goals. Future directions include expanding MART’s industry partnerships and further enhancing its training programs to address emerging technical challenges. The success of MART provides a replicable model for institutions seeking to create holistic educational experiences that prepare students for the complexities of modern engineering and social responsibility.

The growing rise of e-commerce, particularly in the fashion sector, has intensified the demand for sustainable packaging solutions. Despite existing research, finding a standardized methodology to evaluate the sustainability of e-commerce packaging, especially in the fashion industry, remains challenging. This study addresses this gap through a comprehensive literature review and an analysis of best practices among leading e-commerce fashion retailers in Spain. The results reveal a wide range of sustainability initiatives, primarily including innovations in materials, optimized packaging dimensions, and circular economy approaches.

This study provides an exploratory analysis of the effects of circular materials and components on Occupational Health and Safety (OHS) within the construction industry. With circular economy (CE) principles increasingly integrated into construction, there is an emphasis on resource optimization through reuse, recycling, and waste minimization. These practices support sustainability and economic efficiency but simultaneously bring about unique occupational risks. The transition towards CE in construction necessitates an adaptive approach to safety protocols, ensuring both environmental benefits and worker safety are prioritized.The research evaluates how circular materials such as recycled plastics, reused steel, and innovative composites introduce non-traditional hazards that may compromise worker safety if unaddressed. Traditional OHS practices require modification as these materials may exhibit unpredictable characteristics under stress or deteriorate differently than virgin materials. The potential risks range from respiratory issues due to particulate exposure during material cutting to chemical hazards from residuals in recycled content. This research argues that proactive risk management and detailed material traceability are critical for enhancing OHS in a CE framework.The work adopts a mixed-method approach, including literature review and comparative case studies from four construction companies that integrate CE principles. Data collection incorporates interviews with project managers and OHS officers, accident report analyses, and safety audit reviews to identify safety impacts related to circular materials. Findings highlight a correlation between higher circular material usage and the need for enhanced safety measures, suggesting that comprehensive training on new material properties and risks is essential. Material traceability emerges as a pivotal factor, enabling the identification of hazardous components and facilitating the design of targeted OHS protocols.The findings indicate that CE practices, although beneficial for the environment, introduce complexities to OHS management that require regulatory updates and innovative safety measures. Addressing these challenges would ensure that the construction sector not only meets sustainability goals but also advances worker protection in line with new material technologies. Consequently, the research underscores the importance of aligning CE strategies with robust OHS frameworks, fostering a construction industry that is both resilient and responsible. This dual commitment to sustainability and safety can enhance sectoral competitiveness, particularly in light of growing environmental regulations and resource scarcity.

This paper describes the phases of the two epochs of the nuclear fuel lifecycle used in nuclear power plants in Spain, as well as the main characteristics of dry storage of spent fuel elements from PWR-type nuclear reactors. Two mixed-integer linear programming models are presented to optimize the single-mission encapsulation of spent nuclear fuel. Finally, the mathematical models are applied to a hypothetical case of emptying the spent fuel pool at the Ascó nuclear power plant (Tarragona) in 2028.

The rapid adoption of artificial intelligence (AI) in organizational engineering promises significant productivity gains, yet evidence shows a persistent “AI productivity paradox” in which task-level efficiencies fail to translate into measurable economic benefits. This paper examines how eXplainable AI (XAI) and human–AI collaboration (HAIC) can address this gap by aligning algorithmic capabilities with human expertise, trust, and organizational design. Drawing on recent empirical studies, we analyse the structural, cognitive, and socio-technical barriers that limit AI’s value realization, including inadequate integration, overreliance on automation, and inherent system opacity. We propose that XAI, embedded as both a technical and organizational capability, enables transparency, accountability, and adaptive collaboration across diverse stakeholder groups. Using a simulated organizational engineering scenario, we show how XAI-informed HAIC can enhance decision quality, redistribute cognitive workload, and foster iterative learning. The analysis underscore that AI’s real productivity potential lies not in automation alone, but in deliberate, human-centred integration that treats AI as a collaborative partner within resilient socio-technical systems driving intelligent organizational engineering to increase productivity.

The escalating complexity of B2C e-commerce logistics, particularly in last-mile delivery, coupled with the growing consumer preference for home delivery, presents a significant challenge: the need to reduce disruptions during the delivery process. These disruptions not only diminish perceived service quality but also escalate distribution costs and environmental emissions. This paper introduces a novel initiative to tackle delivery failures resulting from customer absences by enabling users to generate and share location statistics with delivery companies, contingent upon their explicit consent. This feature allows users to define a list of preferred locations for tracking, thereby enhancing coordination between customers and delivery providers. By fostering this collaborative approach, users gain greater control over their data, contributing to a more efficient and customer-centric e-commerce logistics ecosystem. Preliminary results demonstrate the application’s potential to reduce delivery failures by up to 45%. This strategy not only mitigates disruptions and lowers costs but also helps minimize environmental impact.

This paper proposes a Mixed Linear Programming Model (MILP) to address the production rescheduling problem in a job shop type manufacturing system subject to unexpected events, with the objective of minimizing production costs and scheduling changes. Initially, an optimal production plan is calculated by assigning batches to machines. Subsequently, dynamic rescheduling is executed in response to events such as breakdowns or raw material shortages. In the event of a machine breakdown, parts of the plan are set to remain unchanged during rescheduling, ensuring that production of products already in progress is not affected. In case of raw material shortages, the option to defer production batches or make urgent material purchases is incorporated to avoid significant delays, thus adapting the plan to the current state of the shop floor through an iterative and reactive approach algorithm. The results show that rescheduling finds an efficient solution that adjusts to the new conditions, minimizing changes with respect to the initial plan in an acceptable computational time.

Se presenta la solución #2 para la instancia ASCO#01(2028_5.5) asociada al vaciado de la piscina de la Unidad I de la central nuclear de Ascó, en una sola misión. La fecha supuesta para iniciar las operaciones de la misión es el 1 de septiembre de 2028. La instancia consta de 1253 elementos de combustible nuclear gastado con calores residuales previstos para tal fecha. El problema consiste en transferir todos los elementos combustibles gastados desde la piscina a cápsulas MPC32, atendiendo a dos funciones objetivo en jerarquía: (1) minimizar el número de cápsulas MPC32 (fase-1) y (2) minimizar la máxima potencia térmica en las cápsulas cargadas (fase-2). La solución final requiere 40 cápsulas con carga térmica máxima𝑄 24.0402 kW, la cual se obtiene con IBM CPLEX concediendo un tiempo de CPU igual a 600 s.

The objective of this paper is to conduct a new benchmark analysis of European cities based of a composite index of efficiency from the dimensions of the Cultural and Creative Cities Monitor 2019 (CCCM). We use two new methodological proposals in this field. In a first phase, the analysis of super-efficiency of the CCCM cities and their convergence process is addressed. As mentioned by Pavkovic’ et al. (2021) the report CCCM is produced by the Joint Research Center, the European Commission’s in-house research center according to the statistical recommendations of (Nardo et al., 2008). The C3 index, based on 29 variables, as mentioned by De Jorge-Moreno and De Jorge-Huertas (2020), evaluates three dimensions: Cultural Vibrancy (CV), Creative Economy (CE) and Enable Environment (EE). These dimensions have been obtained through qualitative and quantitative variables. In this paper we will use the BCC-DEA (Banker et al., 1984 and Data Envelopment Analysis) extension proposed by Andersen and Petersen (1993) to classify the efficient units (super-efficiency model, hereafter). As mentioned by Santin (2014) the super-efficiency reasoning consists of comparing the evaluated unit with a linear combination of all other units in the sample except itself. The evaluated city or DMU (Decision Making Unit) is removed from the inputs and outputs constraints and omitted from the benchmark units. In a second phase, the Hicks-Moortensen indexes are used to estimate the creative productivity of the cities in the existing years. Authors such as O’Donnell (2008, 2011) mention issues such as the fact that Malmquist indices are not fully multiplicative, in addition to not satisfying the transitivity conditions.In relation to productivity performance, there is an increase of 2.02% in average terms across the 190 cities between 2017 and 2019. These productivity gains are a consequence of both technological progress and efficiency with values of 0.02% and 5.39% respectively. Cluster analyses allow us to segment the sample of cities into three groups, which could be considered low, medium and high performers based on their average productivity levels, whose values are -2.79%; 0.9% and 13.41% respectively.It is evident that within the objective of this work in the establishment of a hierarchical classification of cities, according to their efficient management of resources, that allow to establish references for the rest, other questions arise. Such as the fact that it is possible to observe in parallel a certain inequality within European cities with different creative competitive patterns and spatial disparity. However, both the aforementioned convergence analysis and the possibility of establishing good management practices through the best references found, provide a dose of optimism for the future.The methodologies used in this work could be considered useful tools for decision making aimed at finding points of improvement in the management practices of cities. Among the limitations of this work are the short time period analysed, which, although it is the only one available at the moment, also represents a novelty in this field of analysis, given that, in general, cross-sectional data have been used up to now. Possible extensions of this work could be aimed at the consideration of a second stage or exogenous variables that could influence the levels of efficiency or productivity of the cities.