The rush of the humanitarian suppliers into the disaster area proved to be counter-productive. To reduce this proliferation problem, the present research is designed to provide a technique for supplier ranking/selection in disaster response using the principles of utility theory. A resource allocation problem is solved using optimisation based on decision maker’s preferences. Due to the lack of real-time data in the first 72 h after the disaster strike, a Decision Support System (DSS) framework called EDIS is introduced to employ secondary historical data from disaster response in four humanitarian clusters (WASH: Water, Sanitation and Hygiene, Nutrition, Health, and Shelter) to estimate the demand of the affected population. A methodology based on multi-attribute decision-making (MADM), Analytical Hierarchy processing (AHP) and Multi-attribute utility theory (MAUT) provides the following results. First a need estimation technique is put forward to estimate minimum standard requirements for disaster response. Second, a method for optimization of the humanitarian partners selection is provided based on the resources they have available during the response phase. Third, an estimate of resource allocation is provided based on the preferences of the decision makers. This method does not require real-time data from the aftermath of the disasters and provides the need estimation, partner selection and resource allocation based on historical data before the MIRA report is released.

In recent years, the social perspective on disability has been changing, abandoning the more traditional medical paradigm, and replaced by more socially and contextually aware methods. In this sense, disability is now seen as a social construct, as the inability to accommodate the personal requirements of each individual. This has prompted changes in both educational interventions and media creation frameworks, based on paradigms that promote inclusivity. Considering the recognized social and educational potential of tabletop games, their recognized potential for inclusion intervention, it makes sense to look at this medium and how it can advocate the inclusion of each individual player's needs. The present study explores different conceptual structures for the purposes of establishing a framework for inclusive development approaches in tabletop games. Beyond people with disabilities and specific accessibility needs, this study also intends to broaden the spectrum of inclusion through analogue games reflecting on human diversity, with a specific focus on Game-Based Learning (GBL). Results intend to foster evidence based and inclusive GBL interventions, which does not present inclusive design and accessibility as an obstacle but instead a creative process that can be addressed proactively by the different stakeholders. Furthermore, the developed reflections constitute a concrete bridge between the premises of the social model of disability, the broad range of individuals' support needs, and the learning potential of tabletop games.

For a long time, Games Research suffered from what Jaakko Stenros and Annika Waern classified as the Digital Fallacy – the tendency to regard analog games as a subset of digital games rather than the other way around. Where boardgames were once associated with the past of games and learning and digital games with the future, there are now fresh insights and applications for boardgames in learning – alongside with their renaissance as games for entertainment. Even as boardgames found new relevance in learning, the already-recognized possibilities in digital games for learning have continued to expand, with more flexible and ubiquitous tools and platforms allowing for a greater variety of avenues of learning research and practice to be explored. Augmented and mixed reality as well as virtual reality are frontiers in learning that beg for further exploration.

Background: This paper proposes a framework to cope with the lack of data at the time of a disaster by employing predictive models. The framework can be used for disaster human impact assessment based on the socio-economic characteristics of the affected countries. Methods: A panel data of 4252 natural onset disasters between 1980 to 2020 is processed through concept drift phenomenon and rule-based classifiers, namely the Moving Average (MA). Results: Predictive model for Estimating Data (PRED) is developed as a decision-making platform based on the Disaster Severity Analysis (DSA) Technique. Conclusions: comparison with the real data shows that the platform can predict the human impact of a disaster (fatality, injured, homeless) with up to 3% error; thus, it is able to inform the selection of disaster relief partners for various disaster scenarios.

Performance frameworks are common ways to guarantee the success of a collaboration by assessment/improvement of the organisations. However, collaborative performance in recurring collaborations (RC) and temporary ones (TC) are being measured differently due to their inherent characteristics. A systematic review of 282 existing studies, from 2000 onwards, into collaborative networks divided between RC and TC based on the duration of collaboration and the application of the studies was performed. The result gave rise to the thematic analysis of the textual narratives, as well as a quantitative meta-summary of the synthesis. The review shows two different approaches to guarantee the performance of the collaboration. The first group provide a recipe for success by recognizing the causal relationship between nine collaborative measures, including information and risk sharing, trust, commitment, agility, power balance, leadership, prior-experience, and alignment. The second group ensures the success of collaboration by selecting suitable partners based on their previous performance emerging through synergy, readiness, agility and internal–external factors. The reasoning behind these differences are discussed and the current gaps in research are outlined.