Humanitarian disasters are highly dynamic and uncertain. The shifting situation, volatility of information, and the emergence of decision processes and coordination structures require humanitarian organizations to continuously adapt their operations. In this study, we aim to make headway in understanding adaptive decision-making in a dynamic interplay between changing situation, volatile information, and emerging coordination structures. Starting from theories of sensemaking, coordination, and decision-making, we present two case studies that represent the response to two different humanitarian disasters: Typhoon Haiyan in the Philippines, and the Syria Crisis, one of the most prominent ongoing conflicts. For both, we highlight how volatile information and the urge to respond via sensemaking lead to fragmentation and misalignment of emergent coordination structures and decisions, which, in turn, slow down adaptation. Based on the case studies, we derive propositions and the need to continuously align laterally between different regions and hierarchically between operational and strategic levels to avoid persistence of coordination-information bubbles. We discuss the implications of our findings for the development of methods and theory to ensure that humanitarian operations management captures the critical role of information as a driver of emergent coordination and adaptive decisions.

The online spread of rumours in disasters can create panic and anxiety and disrupt crisis operations. Hence, it is crucial to take measure against such a distressing phenomenon since it can turn into a crisis by itself. In this work, the automatic rumour detection in natural disasters is addressed from an imbalanced learning perspective due to the rumour dearth versus non-rumour abundance in social networks. We first provide two datasets by collecting and annotating tweets regarding the Hurricane Florence and Kerala flood. We then capture the properties of rumours and non-rumours in those disasters using 83 theory-based and early-available features, 47 of which are proposed for the first time. The proposed features show a high discrimination power that help us distinguish rumours from non-rumours more reliably. Next, We build the rumour identification models using imbalanced learning to address the scarcity of rumours compared to non-rumour. Additionally, to replicate the rumour detection in the real-world situation, we practice cross-incident learning by training the classifier with the samples of one incident and test it with the other one. In the end we measure the impact of imbalanced learning using Bayesian Wilcoxon Signed-rank test and observe a significant improvement in the classifiers performance.

Rumour is a collective emergent phenomenon with a potential for provoking a crisis. Modelling approaches have been deployed since five decades ago; however, the focus was mostly on epidemic behaviour of the rumours which does not take into account the differences between agents. We use social practice theory to model agent decision-making in organizational rumourmongering. Such an approach provides us with an opportunity to model rumourmongering agents with a layer of cognitive realism and study the impacts of various intervention strategies for prevention and control of rumours in organizations.

This paper concentrates on methods to facilitate interactions and knowledge exchange between different expert groups. The specific case examined is on expert groups from the aviation and humanitarian context. Both are highly complex, multidisciplinary systems where stakeholders work under high time pressure and uncertainty and in a complex decision-making environment. Especially during a sudden on-set (natural) disaster, stakeholders from the humanitarian field and airport management need to work closely together to guarantee the most efficient way of handling issues like overwhelmed customs officials, unsolicited aid donations and unsafe or unprepared warehouses. While several approaches are available, the question still remains: which method works best to create a mutual understanding between these two worlds. To answer it, three different approaches have been examined: (1) discussion rounds with experts, (2) gaming-related method and (3) simulation game. The set-ups as well as the results will be described and pros and cons of each method discussed.

The Kenyan government has made significant advances in water resources management at the local authority (county) level with little or no cooperation at the drainage basin level. Research on critical determinants of cooperation amongst transboundary water negotiation teams is limited. In this paper, we assess whether personal attribute diversity (PAD) is a stronger factor than demographic diversity (gender, age, and education play) in determining whether the negotiation team will cooperate or make unilateral actions. We use a negotiation game to study decisions taken by water policymakers. After that, we conduct a multiple discriminant analysis (MDA) to assess the influence of PAD, gender, age, and education on water negotiation outcomes. The findings indicate that PAD plays a significant role in determining whether the group will cooperate or compete. Gender, education, and age barely influence the outcome. Only upon removal of the PAD variable do we see an increase in the discriminant power of gender and education. Age has minimal influence on the negotiation outcomes. We apply the research at a lower level of governance (Nzoia River Basin). However, results might be extrapolated to a bigger basin, like the Nile Basin, through future multiple level analysis which takes account of the complex socio-technical systems.

The Paris Agreement was a monumental stride towards global climate change governance. It unlocked the climate change gridlock, introducing country-subjective commitments and a five-year review mechanism. To support the implementation of the Paris Agreement, we designed the Nzoia WeShareIt climate change game. Game sessions were conducted in June and July 2015, and 35 respondents completed a pre- and post-game situation awareness (SA) questionnaire and an in-game performance measurement system. The questionnaire uses a 10-dimensional situation awareness rating technique (SART). Subsequently, we conducted a factorial MANOVA (multivariate analysis of variance) to assess the interaction effects between familiarity, team, and gender. Results indicate an increase in situation awareness. However, policymakers' action was not contingent on the increased SA only, there was a significant interaction effect between familiarity and SA, to lead to climate change actions. Therefore, we recommend more emphasis on the role of familiarity in enhancing SA and, subsequently, supporting the implementation to the Paris five-year review country commitments. We also recommend the increased usage of symbols and capacity development of policymakers on connective capacity to enable them to span the climate change boundaries.

Purpose: The purpose of this paper is to analyze how far technology and information enable, facilitate or support the planning and implementation decisions in humanitarian vaccine cold chains for vaccination campaigns. The authors specifically focus on three emerging technologies that have the potential to create more flexible conditions in the field, and identify the need to further explore the link between uncertainty, information and irreversibility. Design/methodology/approach: The authors present a basic structure for the analysis of cold chain disruptions in terms of three distinct yet connected layers of deficient infrastructure and capacity, information gaps and failures in decision making. The authors then review three humanitarian technologies and their impact on vaccine campaigns along these layers. From there, a research agenda is developed to address research gaps this review brought forward. Findings: Three critical research gaps in the areas of technology innovation for humanitarian vaccine cold chain management are presented. The authors argue that technology to improve capacity, information and decisions need to be aligned, and that the areas of uncertainty, information and irreversibility require further investigation to achieve this alignment. In this way, the paper contributes to setting the research agenda on vaccine cold chains and connects humanitarian logistics to technology, information management and decision making. Originality/value: This paper presents the humanitarian vaccine cold chain problem from an original angle by illuminating the implications of technology and information on the decisions made during the planning and implementation phases of a vaccine campaign. The authors develop an agenda to provide researchers and humanitarians with a perspective to improve cold chain planning and implementation at the intersection of technology, information and decisions.

The Horizon 2020 interim evaluation (2017) indicates a steep increase in citizen engagement in European Union Citizen Science (CS) projects, with less than 1% in budgetary terms and minimal influence. Research findings attribute weak CS influence to the restriction of citizen actions to data collection, with minimal or no engagement in co-design, co-creation, data analysis, and elucidation of results. We design a participatory GIS and CS methodology aimed at engaging the citizens in the entire Earth Observation (EO) project cycle. The methodology also seeks to address previous CS project challenges related to data quality, data interoperability, citizen-motivation, and participation. We draw the high-level requirements from the SENDAI framework of action and the three pillars of active citizen engagement, as enshrined in Principle 10 of the Rio Declaration and the Aarhus Convention. The primary input of the methodology is the Haklay (2018) approach for participatory mapping and CS, and the Reed (2009) stakeholder analysis framework. The proposed methodology comprises of three main parts: system analysis, stakeholder analysis, and a six-step methodology. We designed the six-step methodology using an iterative and flexible approach, to take account of unforeseen changes. Future research will focus on implementing the methodology and evaluating its effectiveness in the Solotvyno Saltmine case study in Ukraine.