dc.contributor.advisor | Borit, Melania | |
dc.contributor.author | Szczepanska, Timo | |
dc.date.accessioned | 2023-11-23T12:29:24Z | |
dc.date.available | 2023-11-23T12:29:24Z | |
dc.date.issued | 2023-12-04 | |
dc.description.abstract | <p>This thesis presents the development of the games and agent-based model methodology and provides methodological guidelines for using GAM research, i.e., combining games and agent-based models in research.
<p>GAM research is rooted in complexity sciences and transdisciplinary research, offering valuable insights into complex, adaptable systems. GAM research has particular relevance in decision-making and complex-system management, thus fostering collaboration among scientists and non-academics from various disciplines. It is an engaging platform for data collection and stakeholder processes, thus enriching causal explanations. It should be noted that GAM research has the potential to overcome the limitations of traditional methods by facilitating hypothesis testing with simulation-based observations of human behaviours. Investigations in GAM research can change how social science addresses pressing global challenges. The immersive nature of games combined with agent-based models offers an innovative approach that attracts diverse participants, making it a promising tool for science that reaches beyond the classic academic spheres.
<p>As a comprehensive handbook, this thesis offers researchers inspiration and references for conducting GAM research across diverse application domains. This thesis presents an assessment of the state of research that combines games and agent-based models and proposes a structured approach to making progress in this field. Addressing the lack of a standardised methodology, this thesis is aimed at improving research practices, transparency, and replicability . Practical advice is provided for guiding researchers through designing and conducting GAM research, thus promoting rigorous and comprehensive studies. | en_US |
dc.description.doctoraltype | ph.d. | en_US |
dc.description.popularabstract | This thesis presents the development of the games and agent-based model methodology and provides methodological guidelines for using GAM research, i.e., combining games and agent-based models in research.
GAM research is rooted in complexity sciences and transdisciplinary research, offering valuable insights into complex, adaptable systems. GAM research has particular relevance in decision-making and complex-system management, thus fostering collaboration among scientists and non-academics from various disciplines. It is an engaging platform for data collection and stakeholder processes, thus enriching causal explanations. It should be noted that GAM research has the potential to overcome the limitations of traditional methods by facilitating hypothesis testing with simulation-based observations of human behaviours. Investigations in GAM research can change how social science addresses pressing global challenges. The immersive nature of games combined with agent-based models offers an innovative approach that attracts diverse participants, making it a promising tool for science that reaches beyond the classic academic spheres.
As a comprehensive handbook, this thesis offers researchers inspiration and references for conducting GAM research across diverse application domains. This thesis presents an assessment of the state of research that combines games and agent-based models and proposes a structured approach to making progress in this field. Addressing the lack of a standardised methodology, this thesis is aimed at improving research practices, transparency, and replicability . Practical advice is provided for guiding researchers through designing and conducting GAM research, thus promoting rigorous and comprehensive studies. | en_US |
dc.identifier.isbn | 978-82-8266-254-3 | |
dc.identifier.uri | https://hdl.handle.net/10037/31866 | |
dc.language.iso | eng | en_US |
dc.publisher | UiT The Arctic University of Norway | en_US |
dc.publisher | UiT Norges arktiske universitet | en_US |
dc.relation.haspart | <p>Paper I: Antosz, P., Szczepanska, T., Bouman, L., Polhill, G. & Jager, W. (2022). Sensemaking of causality in agent-based models. <i>International Journal of Social Research Methodology, 25</i>(4), 557-567. Also available in Munin at <a href=https://hdl.handle.net/10037/25984>https://hdl.handle.net/10037/25984</a>.
<p>Paper II: Szczepanska, T., Antosz, P., Berndt, J., Borit, M., Chattoe-Brown, E., Mehryar, S., … Verhagen, H. (2022). GAM on! Six ways to explore social complexity by combining games and agent-based models. <i>International Journal of Social Research Methodology, 25</i>(4), 541-555. Also available in Munin at <a href=https://hdl.handle.net/10037/25983>https://hdl.handle.net/10037/25983</a>.
<p>Paper III: Szczepanska, T., Angourakis, A., Graham, S. & Borit, M. (2022). Quantum Leaper: A Methodology Journey From a Model in NetLogo to a Game in Unity. In: Czupryna, M. & Kamiński, B. (Eds.), <i>Advances in Social Simulation. Springer Proceedings in Complexity</i>, pp 191-202. Springer, Cham. Also available at <a href=https://doi.org/10.1007/978-3-030-92843-8_15> https://doi.org/10.1007/978-3-030-92843-8_15</a>. | en_US |
dc.rights.accessRights | openAccess | en_US |
dc.rights.holder | Copyright 2023 The Author(s) | |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-sa/4.0 | en_US |
dc.rights | Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) | en_US |
dc.subject | Agent-based modelling | en_US |
dc.subject | Complexity science | en_US |
dc.subject | GAM research | en_US |
dc.subject | Games | en_US |
dc.subject | Interdisciplinarity | en_US |
dc.subject | Methodology | en_US |
dc.subject | Research design | en_US |
dc.title | Foundations of GAM Research. Methodological Guidelines for Designing and Conducting Research that Combines Games and Agent-based Models | en_US |
dc.type | Doctoral thesis | en_US |
dc.type | Doktorgradsavhandling | en_US |