With increasingly complex safety-critical systems like healthcare being developed and managed, there is a need for a tool that allows us to understand their complexity, design better strategies and guide effective change. System dynamics (SD) has been widely used in modelling across a range of applications from socio-economic to engineering systems, but its potential has not yet been fully realised as a tool for understanding trade-off dynamics between safety and efficiency in healthcare. SD has the potential to provide balanced and trustworthy insights into strategic decision making. Participatory SD modelling and learning is particularly important in healthcare since problems in healthcare are difficult to comprehend due to complexity, involvement of multiple stakeholders in decision making and fragmented structure of delivery systems. Participatory SD modelling triangulates stakeholder expertise, data and simulation of implementation plans prior to attempting change. It provides decision-makers with an evaluation and learning tool to analyse impacts of changes and determine which input data is most likely to achieve desired outcomes. This thesis aims to examine the feasibility of applying participatory SD modelling approach to safe and efficient staffing level management within hospital pharmacies and to evaluate the utility and usability of participatory SD modelling approach as a learning method. A case study was conducted looking at trade-offs between dispensing backlog (efficiency) and dispensing errors (safety) in a hospital pharmacy dispensary in an English teaching hospital. A participatory modelling approach was employed where the stakeholders from the hospital pharmacy dispensary were engaged in developing an integrated qualitative conceptual model. The model was constructed using focus group sessions with 16 practitioners consisting of labelling and checking practitioners, the literature and hospital pharmacy databases. Based on the conceptual model, a formal quantitative simulation model was then developed using an SD simulation approach, allowing different scenarios and strategies to be identified and tested. Besides the baseline or business as usual scenario, two additional scenarios (hospital winter pressures and various staffing arrangements, interruptions and fatigue) identified by the pharmacist team were simulated and tested using a custom simulation platform (Forio: user-friendly GUI) to enable stakeholders to play out the likely consequences of the intervention scenarios. We carried out focus group-based survey of 21 participants working in the hospital pharmacy dispensaries to evaluate the applicability, utility and usability of how participatory SD enhanced group learning and building of shared vision for problems within the hospital dispensaries. Findings from the simulation illustrate the knock-on impact rework has on dispensing errors, which is often missing from the traditional linear model-based approaches. This potentially downward-spiral knock-on effect makes it more challenging to deal with demand variability, for example, due to hospital winter pressures. The results provide pharmacy management in-depth insights into potential downward-spiral knock-on effects of high workload and potential challenges in dealing with demand variability. Results and simulated scenarios reveal that it is better to have a fixed adequate staff number throughout the day to keep backlog and dispensing errors to a minimum than calling additional staff to combat growing backlog; and that whilst having a significant amount of trainees might be cost efficient, it has a detrimental effect on dispensing errors (safety) as number of rework done to correct the errors increases and contributes to the growing backlog. Finally, capacity depletion initiated by high workload (over 85% of total workload), even in short bursts, has a significant effect on the amount of rework. Evaluative feedback revealed that participatory SD modelling can help support consensus agreement, thus gaining a deeper understanding of the complex interactions in the systems they strive to manage. The model introduced an intervention to pharmacy management by changing their mental models on how hospital winter pressures, various staffing arrangements, interruptions and fatigue affect productivity and safety. Although the outcome of the process is the model as an artefact, we concluded that the main benefit is the significant mental model change on how hospital winter pressures, various staffing arrangements, interruptions and fatigue are interconnected, as derived from participants involvement and their interactions with the GUI scenarios. The research contributes to the advancement of participatory SD modelling approach within healthcare by evaluating its utility and usability as a learning method, which until recently, has been dominated by the linear reductionist approaches. Methodologically, this is one of the few studies to apply participatory SD approach as a modelling tool for understanding trade-offs dynamics between safety and efficiency in healthcare. Practically, this research provides stakeholders and managers, from pharmacists to managers the decision support tools in the form of a GUI-based platform showcasing the integrated conceptual and simulation model for staffing level management in hospital pharmacy.

La gestion de l'eau peut être un domaine complexe, incertain et conflictuel. Dans différentes régions du monde il se confronte à de nombreux problèmes, tel que la disparité des intérêts liés à la ressource de l’eau, plusieurs décideurs, des réseaux administratives complexes, la distribution d'eau inefficace, divers événements socio-politiques et le changement climatique. Par conséquent, la prise de décision a lieu dans un système fortement interconnecté, dans lequel ni les ramifications décisionnels ni la complexité de ses impacts peuvent être négligés. Dans la région des Pouilles, la rareté de l'eau est le principal problème croissant qui touche les communautés humaines et plus qu’humaines.La pénurie d'eau génère la nécessité d'améliorer les processus décisionnels collaboratifs avec agents multiples. Les chercheurs suggèrent que la «tragédie des communs» pourrait être évitée si une ressource partagée était gérée de manière collective. Cela nécessite le développement d'outils dynamiques d’aide à la décision. Ceux-ci devraient être capables d'intégrer les différents cadres de problèmes détenues par les décideurs, de clarifier les différences entre les cadres, de soutenir la création d'un processus collaboratif pour la structuration d’un problème et de fournir des plates-formes communes et des espaces d'interaction.À cet égard, nous avons construit un espace d'interaction dynamique (DIS), mettant en évidence les points critiques opératoires et permettant aux analystes d'identifier une définition commune du problème. Les nouveaux défis de la collecte et de l'échange de connaissances et de la représentation des concepts structurés peuvent être résolus par une approche combinée. Les systèmes multi-agents joints aux systèmes dynamiques pourraient fournir des alternatives non conventionnelles qui utilisent des composants physiques et sociales, avec une attention particulière sur les comportements individuels et collectifs dans la gestion des ressources avec plusieurs décideurs.Dans notre étude de cas, le modèle a été utilisé comme une plate-forme pour la modélisation des organisations multi-agents, afin de soutenir la prise de décision collective dans la gestion de l'eau. Le modèle est capable de représenter un système de gestion de l'eau distribuée complexe, où les comportements simulés sont basées sur des observations sur le terrain et sur la participation des parties prenantes. De plus, l'approche de système multi-agents permet l'interaction et la formalisation des comportements des usagers de l'eau dans le processus de gestion. Une modélisation type systèmes dynamiques dans un environnement d'interaction entre agents de décision, nous permet d’intégrer explicitement les différents cadres et de simuler les interactions lors de l'adoption d'une nouvelle politique. Le modèle peut montrer comment la compréhension limitée de l'espace d'interaction affecte les actions suivies par chacun des décideurs et, enfin, comment elle pourrait conduire à des mécanismes de résistance systémique. En conclusion, le résultat est l’image la plus riche possible de la situation du problème existant, qui traite de la gestion de l'eau d'irrigation dans les systèmes agricoles. / Water resource management can be a complex, uncertain and conflictual domain. It faces numerous problems in many regions of the world, such as the disparity of interests associated with the water resource, multiple decision makers, complex networks of administration, inoperative water distribution, various socio-political events and climate change. Consequently, environmental decision-making takes place in a highly interconnected system, in which neither the decisional ramifications nor the complexity of its impacts can be neglected. In the Apulia Region, water scarcity is the main rising problem and is affecting human and more-than-human communities.Water scarcity generates the need to enhance collaborative multi-agent decision-making processes. Researchers suggest that the “tragedy of commons” could be avoided when a shared resource is at stake, provided that communities interact and operate in a collective way and avoid, for example, the market rules constraints. This requires the development of dynamic decision-aiding tools. They should be capable to integrate the different problem frames held by the decision makers, to clarify the differences among those frames, to support the creation of a collaborative problem structuring process and to provide shared platforms and interaction spaces.In this regard, we built a dynamic interaction space (DIS), highlighting the operative criticalities and allowing the analysts to identify a shared problem definition. The emerging issues of gathering and exchanging knowledge and representing structured concepts can be solved through a combined approach. Multi-agent systems joined with system dynamics can provide unconventional alternatives that use physical and social components, with a particular focus on individual and collective behaviours in resource management with multiple decision makers.In our case study, the model was used as a platform for modelling multi-agent organizations, in order to support collective decision-making in water management. The model is capable of representing a distributed complex water management system, where simulated behaviours are based on field observations and on the participation of stakeholders. What is more, the multi–agent system approach enables the interaction and allows to formalize theIrene Pluchinotta – “Multi-Agent Modelling For Distributed Intelligent Decision In Water Management”iibehaviours of water users in the management process. A system dynamics modelling in an environment of interacting decision agents, allows us to explicitly consider the different frames and to simulate interactions when adopting a new policy. The model can showcase how the limited understanding of the interaction space affects the actions followed by each decision-makers and, finally, how it could lead to policy resistance mechanisms. In conclusion, the result is the richest possible picture of the existing problem situation that deals with irrigation water management in agricultural systems.

Les alpages sont des espaces utilisés par la majorité des exploitations d’élevage de montagne et de Provence, qui y envoient tout ou partie de leurs troupeaux durant la saison estivale. Ce sont des milieux très riches sur le plan environnemental, mais aussi très fragiles et gérés exclusivement par le pâturage des troupeaux, constituant de ce fait des espaces particuliers dans la problématique de l’adaptation au changement climatique pour les systèmes d’élevage provençaux et de montagne. Or le constat est fait que les approches de diagnostic d’alpage et les références utilisées au plan pastoral présentent des lacunes pour appréhender la gestion dynamique des alpages : vision statique des végétations d’alpage et des pratiques, prise en compte des aléas et de la variabilité interannuelle souvent réduite à un coefficient forfaitaire de sécurité... et pas de prise en considération des interactions entre alpage et exploitations utilisatrices. Afin de renouveler ces cadres d’analyse, notre travail de thèse propose une modélisation conceptuelle du fonctionnement du système « alpage-exploitations », intégrant les plans biophysique et de la gestion. La construction du modèle s’appuie sur la combinaison de travaux en écologie et en agronomie « système », et de dires d’expert (modélisation participative). Le modèle est mis à l’épreuve sur une diversité de cas, issus du réseau Alpages Sentinelles dans le massif Alpin. Une analyse de la vulnérabilité des systèmes à la recrudescence des aléas climatiques est effectuée en étudiant leur exposition aux aléas puis leur sensibilité ; afin d’intégrer la dynamique de long terme du changement climatique dans la gestion des alpages, une analyse mobilisant les théories de la résilience socio-écologique est proposée en complément. / Alpine pastures, or mountain summer pastures can be defined as permanent grasslands used in summer by mountain and surrounding plains farmers (especially Provence in the French Alps). They are rich but fragile ecosystems, managed exclusively through the grazing of herds. Therefore adaptation to climate change is very specific on these spaces. Pastoral diagnosis methods and technical references are insufficient to analyse dynamic management of summer mountain pastures: static vision of vegetation and practices, climatic hazards considered only through a security coefficient, and no consideration for interactions between summer pastures and farms. In order to renew these analytical frameworks, our PhD thesis proposes a conceptual model of how the system “mountain summer pastures-farm” works, both in biophysical terms and in terms of management. The building of this model relies both on researches in ecology and agronomy, and on participatory modelling. We evaluate the model through an analysis of the vulnerability to climatic hazards of a diversified sample of systems. In order to take into account long term dynamics of climate change, we also mobilise the theories of social-ecological resilience.

Because of global warming, companies have started to tackle sustainability issues within their operations, but major uncertainties exist on how to establish a quantitative baseline of the current environmental performance of companies. Numerous investigations have been made to assess the carbon footprint of companies with a variety of methods, tools and strategies. However, the lack of transparency in the methods used and the assumptions made could prevent companies to replicate methods and to analyse the results. Because of this, we will investigate how participatory modelling could be used to create a model of the carbon emissions of a company, but also how this method enables the company to understand the methods used and the results from the investigation. By doing this, we also aim to clarify how the process could be set up, which stakeholders that need to be involved and what data sources that could be used. The thesis was conducted as a single case study at a manufacturing company named DeLaval. A participatory modelling process with three major phases was carried out according to proposed methodologies in previous research. In the first phase, a conceptual model of the system accounting for the emissions was created. In the second phase, a quantitative model of the system was developed by gathering data and validating the calculation methodologies with operational stakeholders within the company. In the third phase, the results were verified, and the company could set up sustainability targets based on the findings. The outcomes of the case study showed that there are major benefits with applying participatory modelling because different perspectives throughout the organisation could be gathered efficiently to create a representable model of the company. The modelling strategy had more benefits in organisational areas characterised by high complexity with numerous of different stakeholders with different roles or by geographical distribution. To create the model, primary data consisting of master product data and transactional data was used, together with secondary data, consisting of carbon emission coefficients and gap filling data created by the modellers. By basing the calculations on the methodology set up by the GHG protocol and anchoring the root definition of the system with strategic stakeholders, the results were trusted by the organisation. / På grund av den globala uppvärmningen har företag börjat att hantera hållbarhetsutmaningar inom sin verksamhet, men stora frågetecken kvarstår gällande hur en kvantifierad bild av företagets nuvarande utsläpp ska beräknas. Flertalet studier har genomförts för att undersöka koldioxidavtrycket på företag, med flertalet olika metoder och verktyg. Metoderna och antaganden som gjorts har dock bristande transparens, vilket hindrar andra företag från att replikera beräkningarna och att göra analyser av resultatet. Baserat på detta kommer denna studie att undersöka hur participativ modellering kan användas för att skapa en modell av koldioxidutsläppen från ett företag, men också hur denna metod underlättar för företaget att förstå metoderna som använts och resultaten från undersökningen. Genom detta ämnar vi att bringa klarhet gällande hur processen kan se ut, vilka intressenter som ska vara delaktiga och vilka datakällor som kan vara användbara. Studien genomfördes som en enkel fallstudie på det producerande företaget DeLaval. En participativ modelleringsprocess med tre faser genomfördes i enlighet med etablerade modelleringsprinciper från tidigare studier. I den första fasen utvecklades en konceptuell modell av systemet för estimering av koldioxidutsläppen. I den andra fasen utvecklades en kvantitativ modell as systemet genom att samla in data och validera beräkningsmetoderna tillsammans med operative intressenter på företaget. I den tredje fasen verifierades resultaten och företaget hade möjlighet att sätta upp hållbarhetsmål baserat på resultatet. Utfallet av fallstudien visar att det finns stora fördelar med att använda participativ modellering eftersom olika perspektiv i organisationen kunde inhämtas på ett effektivt sätt för att skapa en representativ modell av företaget. Modelleringsstrategin hade större fördelar i delar av företaget som karakteriserades av hög komplexitet, med många olika intressenter med olika roller eller av geografisk utspriddhet. För att skapa modellen krävdes primärdata innehållande produktinformation och transaktionsdata samt sekundärdata, innehållande utsläppsfaktorer och överbryggande data skapad av modellerarna. Genom att basera beräkningarna på metodiken skapad av GHG protocol och förankra syftet med systemet tillsammans med strategiska intressenter, skapades en tillit till resultaten inom organisationen.