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This study aims to examine the intricate relationship between Chile’s coastal communities and the increasing effects of climate change, with a focus on Caleta Lenga as a case study. Chile’s extensive coastline is closely linked to the country’s economic well-being and the livelihoods of millions of people. The mounting threats posed by climate change require immediate action. To strengthen resilience and reduce risk, adaptive measures are imperative. However, effective adaptation is hindered by numerous barriers, including adaptive capacity and governance challenges.

This study uses a case study approach, which centres on Caleta Lenga’s unique socio-environmental and demographic context. This study used semi-structured interviews and historical reconstruction to reveal a socio-economic and environmental narrative that was influenced by significant events and transitions.

The residents’ perception of climate change impacts was viewed through the lens of industrial activities and changing weather patterns. This study emphasizes the community’s resilience in the face of changing socio-environmental dynamics. It highlights the importance of informed decision-making, community cooperation and the preservation of ancestral knowledge in promoting adaptive strategies based on community solidarity and collective decision-making. The findings underscore the need for effective adaptation measures that address both adaptive capacity and governance challenges to bolster climate resilience in vulnerable coastal communities.

The findings underscore the need for effective adaptation measures that address both adaptive capacity and governance challenges to bolster climate resilience in vulnerable coastal communities.

This paper aims to look at the implementation of project-funded research governance and its potential to induce organisational learning on responsible research and innovation (RRI). This paper analysed what types of organisational learning and change can take place within organisations of an Europe-funded project and to what extent. This paper examined whether and how change occurs and how it is shaped and co-produced with other orderings.

The paper is based on materials and evidence collected while working on the internal evaluation of a Horizon 2020-funded project. Analysis of the results of the mixed methods evaluation design was used to characterise occurrences of organisational learning and change.

The authors identified different forms of learning (single-loop learning, double-loop learning, reflexive and reflective learning and situational learning). The extent of learning that could lead to long-lasting organisational change was limited. This was due to the project-based and organisational design, the key-based definition of RRI and the indeterminacy of what constitutes learning and change – both at the level of funding and performing the project. For organisational change to occur, the authors argue for governance mechanisms based on reflexive learning that consider a range of structural conditions and measures.

Organisational learning plays an important role in change processes, which has so far been given too little consideration concerning the governance and implementation of RRI through project-based funding. The authors argue for a restructuring of governance and funding mechanisms to create more space for reflexivity and learning.

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.