Developing causal loop diagrams (CLDs) involves identifying stakeholders and endogenous variables and formulating variable causal relationships. Traditionally, the CLDs are developed mainly using a qualitative approach such as literature review, observations and interviews with stakeholders. However, modellers may question which stakeholders should be approached, whether the relevant variables are selected, and what to do when stakeholders perceive different variable relationships in the CLDs differently. Applying in a case study, this research proposes a multi-method approach by combining both quantitative and qualitative methods to select stakeholders, identify endogenous/exogenous variables, and develop the CLDs. The proposed quantitative method is expected to provide modellers with a justifiable stakeholder and variable selection process. The method also highlights possible hidden variables and relationships, which were further explored with a traditional qualitative approach.

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Previous research regarding PhD students’ well-being (PhD-WB) has lacked a comprehensive and systemic analysis. This research engages with a systems approach to examine the multiple variables, including feedback mechanisms, which influence PhD-WB over time. The model was developed using a structural analysis method (Cross-impact analysis MICMAC) that informed a causal loop diagram (CLD). The aim was to understand what promotes (drivers) and inhibits (barriers) PhD students’ well-being. The results show that PhD students’ well-being reflects an interplay between university, financial support, students’ mental and physical health, and family/friends. However, the analysis shows that the role of the drivers is dynamic, and they can become barriers in certain circumstances. This insight validates the application of systems thinking to illustrate the complexity of PhD students’ well-being.

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Renewable energy technology (RET) is promoted to combat climate change, reduce poverty and reduce reliance on fossil fuels (UNEP, 2011). However, its impacts need to be managed to promote sustainable growth. RET has several impacts, for example on human health through wind turbine syndrome and RET-work related accidents; on social inequality because some RET incentive policies may benefit certain groups in society; on the environment during its production; and on centralised distribution networks. This research focuses on the hotel sector because of its relatively high energy intensity compared with other commercial buildings; and also because of its embeddedness in local communities and environments. The results of a systematic quantitative literature review reveal that studies about the impact of RET deployment in the hotel sector are currently absent. Moreover, existing studies that explore the effect of RET deployment use a linear approach rather than a holistic systems approach. The systems approach provides a framework for dealing with dynamic complexity, for seeing patterns of change rather than static 'snapshots'. The overall aim of this research is to analyse RET deployment strategies in the hotel sector and to identify suitable strategies that: (a) balance environmental, social and economic risks and benefits; and (b) promote sustainable growth of RET deployment. This conference paper presents the result of the first stage of this research including the typologies of variables that influence the deployment of RET in the hotel sector in Queensland, Australia. The data were collected from stakeholders, and were analysed using a structural analysis with the MICMAC approach. The results show that the respondents has rated 'the reliability of electricity produced by RET' and 'a tourist comfort' as influential variables and 'whether the hotel has green program' and 'energy storage or not' as dependent variables. The next step in this research is to develop a causal loop diagram in a stakeholder engagement workshop to identify underlying systems structures likely to influence a hotel deployment decision in RET within Queensland, Australia. Details of this workshop are outlined in this paper. A final causal loop diagram will be used to develop a simulation model to suggest improvement to hotel RET deployment strategies that balance environmental, social and economic risks and benefits.