- Title
- Understanding the social dilemma of sustainability using agent-based modelling and evolutionary game theory
- Creator
- Dhakal, Sandeep
- Relation
- University of Newcastle Research Higher Degree Thesis
- Resource Type
- thesis
- Date
- 2022
- Description
- Research Doctorate - Doctor of Philosophy (PhD)
- Description
- The three dimensions of human sustainability—economic, environmental and social — are closely integrated with each other. Successful implementation of policies and actions for addressing the economic and environmental issues of sustainability is a social challenge that can only be solved by achieving individual and societal change. This social challenge arises due to the conflicts between short-term individual goals and long-term collective goals, and can be characterised as a social dilemma. Social capital, which is derived from the network of interrelationships among people and refers to features of social organisation, such as trust and cooperation, is acknowledged as one of the means of solving the social dilemma of sustainability. Addressing the social dilemma of sustainability is an important goal towards achieving human sustainability. This can only be achieved by understanding the social dilemma, in the context of the environmental and economic issues of sustainability, as well as investigating the interrelationship between the various aspects of social capital. This research project uses one representative issue of economic and environmental sustainability each, the sharing economy and climate change induced migration (CCIM), to further our knowledge of the social dilemma of sustainability. In addition, this project also analyses the correlation between four core aspects of social capital: cooperation, trust, interaction networks and migration. These components of social capital have been chosen because promoting cooperation and trust in a highly interconnected world that is characterised by increasing levels of mobility and rapid diffusion of information and behaviour is a challenge that must be addressed for the purpose of human sustainability. This study uses a combination of {evolutionary game theory (EGT) as the theoretical foundation and agent-based modelling (ABM) as the methodology to understand the social dilemma of sustainability. {EGT has proven effective for illustrating social dilemmas and analysing the strategic thinking of rational individuals facing those dilemmas in various research domains. Similarly, ABM provides an ideal medium for modelling human behaviour, societies, causal processes, emergent phenomena and mechanisms. Three social dilemma models are formulated, one each for analysing the formation of trust in the sharing economy, the evolution of cooperation under CCIM, and the interrelationship between the above-mentioned four social capital components. The first study of this research project uses a trust game to highlight the social dilemma of trust in sharing economy situations, particularly when the participants are constrained to being only either a consumer or a provider. Most studies in the literature have assumed that roles are flexible even when a significant majority of sharing economy participants assume only one role, and this study bridges this gap in the literature, in addition to studying the trust formation patterns under different interaction networks. The results of this study indicate that allowing users to change their role in the sharing economy is vital to promote trust among the participants, and point to the impact of the degree of connectivity of interaction networks. The second study uses a social dilemma game similar to the public goods game to study the social dilemma regarding cooperation, climate change and migration. This model connects individuals using physical as well as social networks for the purpose of interaction and information diffusion, allows them to migrate from one physical group to another to adjust to the impacts of climate change, and tests the utility of requiring minimum levels of cooperation, called cooperation thresholds, for obtaining benefits. This is one of the first studies in the literature to study the evolution of cooperation and CCIM using EGT. The results show that controlled migration and cooperation thresholds have a positive impact on the evolution of cooperation among the individuals. The final study advances our understanding of the interrelationships between four different aspects of social capital (cooperation, mobility, trust and interaction networks) in the context of decision-making in social dilemma situations. This study focuses on using the idea of tags or stereotypes as cognitive tools for decision-making, particularly about migration, and is one of the first studies in the literature to do so. The results of the experiments show that tags, trust and controlled migration are generally conducive for cooperative behaviour. Results also show that allowing people to seek better options through migration is an important factor for promoting trust and cooperation, and that the presence of a large number of tags decreases their utility as cognitive tools resulting in reduced levels of trust. In summary, this research project addressed some of the social dilemma issues surrounding human sustainability by focusing on the interrelationship between the three dimensions of sustainability. By advancing the theoretical understanding of the evolution of cooperation and trust in the population, particularly when migration and interaction networks are a key component of the social dilemma situations, this study provides a foundation for future studies that can focus on understanding and solving the real-world cases of the social dilemma of human sustainability.
- Subject
- evolutionary game theory; sustainability; agent-based modelling; social dilemma; sharing economy; climate change induced migration; collaborative consumption; trust; evolution of cooperation; thesis by publication
- Identifier
- http://hdl.handle.net/1959.13/1505372
- Identifier
- uon:55666
- Rights
- Copyright 2022 Sandeep Dhakal
- Language
- eng
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