McGrath et al. A Conceptual Information Model for a ‘Green Economy Tourism System’ (GETS) Proceedings of the Nineteenth Americas Conference on Information Systems, Chicago, Illinois, August 15-17, 2013. 1 A Conceptual Information Model for a ‘Green Economy Tourism System’ (GETS)  G. Michael McGrath Victoria University, Melbourne, Australia michael.mcgrath@vu.edu.au Paul A. Whitelaw Victoria University, Melbourne, Australia paul.whitelaw@vu.edu.au Geoffrey H. Lipman Greenearth.travel, Brussels, Belgium glipman@gmail.com Henk Meijerink Victoria University, Melbourne, Australia hmeijeri@telstra.com Alexandra Law Victoria University, Melbourne, Australia alexandra.law@live.vu.edu.au Terry DeLacy Victoria University, Melbourne, Australia terry.delacy@vu.edu.au ABSTRACT Many tourism destinations are currently pursuing green growth strategies but the development of appropriate policies is a complex task and, consequently, decision support technologies can be used to advantage here. The design and use of one such decision support system (DSS) is described in this paper. Key features of the system are that its design is underpinned both by a need to effectively manage the inherent complexity of the analysis domain and to allow iterative development with minimum impact on previous versions (i.e. to minimize ongoing maintenance costs). A key to realizing both these objectives is the use of a highly-abstracted conceptual information model and this is the major focus of this paper. KEYWORDS Decision support; green-growth tourism; conceptual information model INTRODUCTION The Intergovernmental Panel on Climate Change (IPCC) has declared that “warming of the climate system is unequivocal” (IPCC, 2007). As nations worldwide address the risks of climate change and aim to reduce their greenhouse gas (GHG) emissions, we are seeing the emergence of a new low-carbon, ‘green’ economy. The United Nations Environment Programme (UNEP) defines the green economy as “an economy that results in improved human-wellbeing and reduced inequalities over the long term, while not exposing future generations to significant environmental risks and ecological scarcities” (UNEP, 2010). This new green economy trend has wide ranging implications for the tourism sector. Destinations face complex new challenges, but also significant new opportunities, such as those presented by changing tourism demand, that need to be addressed to remain sustainable and competitive. In its Green Economy Initiative (GEI), UNEP identifies tourism as one of 11 priority sectors where investment in sustainable solutions can drive economic recovery and growth while simultaneously addressing social inequalities and environmental challenges (UNEP, 2010). However, green economy planning in tourism is a complex process, characterized by high levels of uncertainty. For instance, tourism is not included as a sector in traditional emission inventories and as such, little information is avaiable on sources and magnitude of the sector’s GHG emissions (Becken and Hay, 2007). Another example of uncertainty for the tourism sector is the emergence of ‘green demand’, which remains difficult to quantify. While it is anticipated that climate change and environmental perceptions will alter destination choice and consequently influence tourism demand (see e.g. Simpson at al, 2008), there is a lack of information available for destination policymakers and planners to understand the dynamics behind these changes. For targeted mitigation and adaptation strategies, the relationship and interdependencies between the green economy drivers must be understood. However, a planning framework for a green economy transition in tourism destinations does not currently exist. In this context, our ‘Green Economy Tourism System’ (GETS) is being developed to facilitate the capture, organization and access of required strategic planning data in a systematic and convenient way. In addition, an increasing array of ‘add-on’ decision support modules is being developed in order to allow destination planners and policy makers to investigate dynamic ‘what if’ scenarios around their destination and green economy developments.