Professor Susanne Becken

In the face of multiple crises, there is a pressing need to increase knowledge, skills and commitment to sustainability and climate action both amongst tourism practitioners and academics. There is an opportunity to deepen the concept of literacy in ways that not only capture operational aspects of tourism and carbon, but also embrace cultural and contextual knowledge and practices, so that the host-guest relationship is mutually enriching and contributes to regenerating destinations. This conceptual paper proposes a pathway that moves beyond building domain-specific carbon literacy to growing "Green Service Literacy" and ultimately "Regenerative Literacy." The vision of Regenerative Literacy connects to deep ecology thinking and decade-long efforts such as those proffered in the Earth Charter. Ultimately, it seeks to (re-)align our lifestyles with nature and ensure the human footprint remains within planetary boundaries. Changes across the tourism system are recommended to enable this transformation.

Growing concern about the climate crisis comes with increased scrutiny of flying as an emission-intensive activity. This study conceptualises a modern communication system and draws on social media data to examine pre-COVID-19 (September to December 2019) public conversations about aviation and climate change. The analysis of >326,000 Twitter posts reveals that issue salience can be considerable at times, especially during key events such as United Nation climate summits and for users from countries such as Portugal, Puerto Rico, Qatar, France and Spain. Topic modelling identified five key frames: economy and industry, public opinion, fairness and conflict, consequences and responsibility. The fairness and conflict frame recorded the largest number of tweets, and was noteworthy for its negative sentiment. It also had the highest retweet rate and the densest network in terms of average users per community. The responsibility frame was interesting for its positive sentiment, and perhaps the opportunity for aviation stakeholders to contribute proactively to the conversations by sharing climate action success stories. Given the importance of public opinion (voters and consumers), and the link between media activity and policy decisions, the ongoing monitoring of issue salience, frames and peer groups related to flying and climate change seems beneficial.

The COVID-19 pandemic provides an opportunity for tourism to change so to make a more meaningful contribution to sustainable development, including action on climate change. To achieve such a sustainable tourism transition, an effective enabling environment, supported through appropriate governance arrangements, is required, However, our understanding of what suitable governance modes look like to support tourism's climate actions are limited. To address this gap, this study applies a qualitative approach to investigate the link between enabling drivers and different types of governance. Drawing on meta-governance thinking and 23 interviews with tourism experts from the Asia Pacific region, the opportunity for transformational change is assessed. Experts do not believe transformational change is possible but hope for incremental changes. The analysis demonstrates that activating a wide range of enabling drivers across four types of governance mode will be necessary to catalyse change. Three examples of tourism governance highlight that polycentric governance modes have greater potential for strengthening the enabling environment for a low carbon transition.

Air travel forms a substantial component of an organisation's carbon profile, and questions around business travel are becoming more pertinent given the accelerating climate crisis. The current coronavirus pandemic, however, has effectively stopped much travel and organisations had to adapt by switching most interactions to online meetings. Drawing on social practice theory, this paper examines changes in staff air travel behaviour observed in a New Zealand government agency, following the nationwide lockdown in 2020. Integrating air travel data, a staff wellbeing survey and 18 interviews, the research reveals fundamental differences in the meaning of face-to-face versus online meetings, the inseparable nature of productivity and personal wellbeing, and the change processes that staff noted when faced with a (temporary) new reality of restricted mobility. Whether modified routines remain or not will not only be influenced by the government's imposed carbon budgets, but also will be a question of organisational leadership, politics, and ultimately the ethics of trading off environmental impacts with other perceived needs.

Global air travel has reached 3.7 billion passengers in 2017 and is predicted to continue to grow at 4.7% per annum. Such forecasts fail to consider the rising cost of carbon and socio-economic declines due to climate change. Using three scenarios, this paper finds that air travel growth slows considerably, with the high mitigation scenario producing the relatively best outcome for the industry with 9.8 billion passengers in 2070. Low mitigation is the least favourable option in the long term, as emissions continue to grow rapidly, whilst demand turns negative in 2067, due to increasing economic damage and rising inequality. A counterfactual scenario reveals that only extremely optimistic assumptions produce high growth rates produced in the Boeing forecast. •Three climate change mitigation scenarios have been developed.•Air travel demand will decrease in all three scenarios compared with BAU.•Low investment into climate mitigation will result in negative growth.•Only optimistic assumptions can lead to industry-led growth projections.

Understanding the perceptions of climate change by those working in tourism greatly supports development of adaptation measures in destinations. However, limited evidence of either perceptions or tourism adaptation measures is available from China. Building on protection motivation theory, this study explores how Chinese working in tourism perceive climate change and what their adaptation intentions are. The study demonstrates that the current level of climate risk perception is relatively high, and people feel informed. The results indicate that (1) Information plays an important role in risk and adaptation appraisals; (2) Individuals are more likely to take adaptation measures if they perceive greater climate risks and have higher adaptive capacity; (3) An increase in adaptive incentives would generally support an increase in adaptation appraisal; (4) Providing greater adaptive incentives will motivate tourism staff to take actions and implement adaptation measures. The findings have implications for adaptation policies and strategies in destinations.

This paper reviews tourism-relevant advances in climate science and tourism policy in the Australasia region over the past 20 years, focusing particularly on the seven years (2015-2021) since the IPCC Fifth Assessment Report. Within the Australasia region, Australia and New Zealand have a complicated relationship with climate change, as both countries are dependent upon stable climates for tourism while contributing to high tourism greenhouse gas emissions. Both are economically reliant on their respective tourism industries, which market environmental products to predominantly long-haul tourism markets. In this paper we critically address the climate change context in Australasia, reviewing the tourism systems, climate risks and carbon risks in the region. We critique the (dis)connection of climate change and tourism policy at the national scale in the region, and find that the extent of climate responses in relation to tourism are generally limited to descriptive (Generation 1) and normative (Generation 2) approaches. We conclude that serious deficiencies remain in the climate science - tourism policy translation required to transform the tourism systems of Australia and New Zealand in response to climate change.

Tourism is shaped by a wide range of factors and forces, including exogenous ones that have no direct link with the tourism sector. Natural disasters and unexpected events are prime examples of such determining factors, as they have profound effects on individuals and society, and as a result have the potential to affect tourism flows considerably. Several theoretical arguments exist why natural disasters and unexpected events could influence tourist destination choices. However, empirical research to confirm the nature and extent of impacts of disasters on tourism is lacking. To address this gap, this paper incorporates a dataset on natural and man-made disaster events into a model of international tourism flows to evaluate the effect of different types of disasters on international arrivals at the national level. Findings provide evidence that the occurrence of different types of event change tourist flows to varying degrees. Although in some cases a positive effect is estimated, in general the impacts are negative, resulting in reduced tourist arrivals following an event. Understanding the relationship between disaster events and tourism is helpful for destination managers who make critical decisions in relation to recovery, reconstruction and marketing. [Display omitted] •First global evaluation of the impact of disasters on international tourism flows.•Tsunamis, Floods and Volcanic Eruptions constitute negative motivators.•Volcanic Eruptions impact most negatively on international tourism flows.•High economic consequences of a disaster impact negatively on tourism.•In line with theory, some disasters can also positively affect flows.

Effective climate change action relies on the production of relevant knowledge. This review provides an interdisciplinary meta-analysis to critically assess tourism and climate change knowledge production across three knowledge domains: academic, practical and political. Building on existing tourism knowledge frameworks and applying systems thinking, the Tourism Climate Change Knowledge System is developed consisting of five knowledge dimensions: Source of knowledge, Knowledge creation, Influence on knowledge, Knowledge content and Knowledge impact. Results reveal how knowledge differs across domains and what barriers impede effective knowledge generation. While some links could be identified, there remains a disconnect between academic knowledge outputs and practical and political knowledge needs. The holistic lens enables the formulation of recommendations to enhance the production and use of knowledge. •The Tourism Climate Change Knowledge System consists of five knowledge domains.•Knowledge across academic, practical and political domains is compared.•Outputs reflect a range of underlying ideologies, dominated by neoliberalism.•Barriers to the science-policy-practice interface of tourism and climate are identified.•Feedbacks and links between system elements need to be improved.

Climate change poses complex challenges and addressing these requires increasing integration across policy domains. This research developed a framework to assess policy integration between the tourism and climate change domains by examining coverage, scope, materiality and alignment. A database of 101 policy documents was compiled, representing 61 countries over 17 years. Only 37 documents covered the tourism-climate nexus substantially, suggesting climate change has not yet become a priority for tourism policy makers. Considering that tourism makes considerable contributions to and is substantially impacted by climate change, the observed gaps in tourism policy needs to be addressed. The paper concludes with some minimum expectations for policy integration, including examples of good practice, and suggests that more effort is required to achieve climate change policy integration in tourism.

Transformational system change is required to respond to the current climate emergency and the COVID-19 induced structural break presents an opportunity to progress such change. While the tourism industry accepts the need for change, how this may look like remains unclear. This article contributes to identifying pathways by presenting critical reflections on the research process and findings from a three-year research project on reducing climate change risk in Vanuatu. The approach is anchored in systems thinking and draws on the concept of leverage points. Seven points are identified for intervening in the tourism system to reduce climate change risk and achieve varying levels of systemic change. Each is explored in the context of Vanuatu before its broader relevance is discussed. The findings highlight the importance of engaging with deeper influences of risk and unsustainable system outcomes. This has implications for how decision-makers approach crisis management and what 'tourism recovery' means, especially when considering that system resilience might stand in the way of more profound transformational change required to address long-term risks.

•Conceptualizing two separate levels of public engagement: attitudinal versus behavioral.•Place values consist of a core motivating factor of public engagement.•Trust is the most important antecedent of attitudinal engagement (i.e., acceptance).•Guilt is the most important influencer of behavioral engagement (i.e., support).•Hope could increase public acceptance but has no impact on public support. The twin crisis of biodiversity loss and climate change make it urgent to find ways of restoring natural ecosystems, including coral reefs. Methods for coral reef restoration are rapidly advancing, bringing with them a range of potential risks and opportunities. Attention to public engagement in the governance of such activities therefore becomes critical. This research examines public attitudinal and behavioral engagement in ‘traditional’ coral restoration projects in the Great Barrier Reef World Heritage Area (i.e. coral gardening at relatively small scales). Grounded on dual-process decision-making and trust theories, rational factors (i.e., perceived benefits), emotions (i.e., hope and guilt) and trust are conceptually three main determinants of public engagement in ecological restoration. We used a mixed-method approach, including 63 individual interviews and a follow-up survey with 1585 participants, to clarify the roles of these psychological factors in motivating public engagement in current coral restoration projects. Trust was found to be the most important factor influencing public acceptance (i.e., attitudinal engagement) of coral restoration, while the emotion of guilt was the most influential factor affecting public support (i.e., behavioral engagement). Therefore, when advocating for conservation projects, different campaigns could be implemented with: (1) positive messages of hope and trust to gain public acceptance for government-funded restoration projects and (2) messages highlighting individual responsibility to motivate behavioral support to scale up restoration projects.

Even before the global halt to extensive mobility due to the coronavirus crisis, there has been growing resistance amongst some groups to flying. Reflecting increasing concern about the imminent climate emergency, the phenomenon of feeling ashamed of flying and expressing related emotions through communication has resulted in the neologism "flygskam". Drawing on 14,212 Twitter posts that contained "flygskam" and a further 1037 using the English "flightshame", this research examined the spatial-temporal spread of these words from Sweden starting in 2016 to the rest of the world indicating a global phenomenon. The findings indicate that national context continues to be important in understanding the nexus of individual and social sensemaking and processing of new information. They also demonstrate, however, that global networks (facilitated through social media) might challenge the needs of physical mobility as requirements to connect, exchange views, and create identity through peer group membership. Further analysis of the content revealed key perspectives and topics, providing insight into the relatively homogeneous discussions amongst a network community. Only 6% of posts rejected the notion, whilst the majority indicated support and advanced suggestions for more sustainable alternatives. It might be too early to say whether language behaviour expressed in online communication translates into real behaviour, but the current pandemic may well provide further impetus to no-fly movements by way of a strategic alliance between different peer groups.

Photo aesthetics assessment is a challenging problem. Deep Convolutional Neural Network (CNN)-based algorithms have achieved promising results for aesthetics assessment in recent times. Lately, few efficient and effective attention-based CNN architectures are proposed that improve learning efficiency by adaptively adjusts the weight of each patch during the training process. In this paper, we investigate how real human attention affects instead of CNN-based synthetic attention network architecture in image aesthetic assessment. A dataset consists of a large number of images along with eye-tracking information has been developed using an eye-tracking device (https://www.tobii.com/group/about/this-is-eye-tracking/) power by sensor technology for our research, and it will be the first study of its kind in image aesthetic assessment. We adopted a Residual Attention Network and ResNet architectures which achieve state-of-the-art performance image recognition tasks on benchmark datasets. We report our findings on photo aesthetics assessment with two sets of datasets consist of original images and images with masked attention patches, which demonstrates higher accuracy when compared to the state-of-the-art methods.

This paper introduces an innovative approach for assessing visitor satisfaction at the destination level by identifying attributes of interest from social media text and indirectly measuring performance and importance values. A lexicon-based method for sentiment analysis is applied to determine performance value at the destination level, while importance is calculated using an adjusted association rule mining algorithm. The results are validated with earlier survey-based attributes relevant to visitors and Australia's case. The results demonstrate encouraging accuracy, suggesting that the proposed methodology offers opportunities to assess tourist satisfaction at destinations with larger sample sizes for a lower cost and greater data collection flexibility than traditional approaches. The methods proposed could be beneficial in a wide range of tourism contexts. •Destinations are recognized from tourists' travel itineraries.•Sentiment analysis is applied to identify performance at multiple destinations.•The importance of each attribute is calculated proportionally at each destination.•Validated results of social media data with survey data

Decarbonising tourism is an immeasurable challenge but increasingly recognised as inevitable. This has prompted vast developments in theoretical models by academics and indicators by peak bodies to explore the pathways. One limitation to the pathways is the lack of emission data. This research presents a framework integrating the principles of TSA with the National Greenhouse Accounts. Tourism emissions are estimated and examined by destinations, producing industries and visitor types. The framework is applied to destinations in the State of Queensland, Australia, to illustrate the types of results and insights that can be produced for decisionmakers. Mitigation policies can then be tailored to the specific context of each destination, increasing effectiveness and ability to balance economic benefits with reducing emissions.

Social media opens up a great opportunity for policymakers to analyze and understand a large volume of online content for decision-making purposes. People's opinions and experiences on social media platforms such as Twitter are extremely significant because of its volume, variety, and veracity. However, processing and retrieving useful information from natural language content is very challenging because of its ambiguity and complexity. Recent advances in Natural Language Understanding (NLU)-based techniques more specifically Transformer-based architecture solve sequence-to-sequence modeling tasks while handling long-range dependencies efficiently, and models based on transformers setting new benchmarks in performance across a wide variety of NLU-based tasks. In this paper, we applied transformer-based sequence modeling on short texts' topic classification from tourist/user-posted tweets. Multiple BERT-like state-of-the-art sequence modeling approaches on topic/target classification tasks are investigated on the Great Barrier Reef tweet dataset and obtained findings can be valuable for researchers working on classification with large data sets and a large number of target classes.

Tourism is strongly interlinked with the natural and social environment, in particular in destinations around the Pacific. These environments are vulnerable to climate change which impacts on the social-ecological system of destinations. Ecosystem-based Adaptation (EbA) uses ecosystems to manage the risks of climate change. However, a gap remains in understanding how the tourism sector can use EbA to create destination-wide benefits. The destination EbA framework presented here aims to address this gap by focusing on well-being and climate risk reduction. The framework is applied to a Pacific case study site, Tanna Island in Vanuatu, by drawing on primary qualitative data. Results highlight that EbA offers an approach for the tourism sector to create holistic benefits to destinations. Several constraints to successful implementation, and how these may be overcome, are identified. The article contributes by providing a framework for other destinations which aim to create benefits through tourism.

The COVID-19 pandemic alongside other environmental and social crises have raised questions around the role of government, governance and the notion of tourism value. The aim of this paper, therefore, was to develop a conceptual framework that makes sense of the tourism value discussion within the wider context of the New Zealand Department of Conservation's aspiration of Papatūānuku Thrives (Mother Earth Thrives). Drawing on critical studies, current New Zealand tourism strategies, stakeholder input and discussions with government employees, a values-based tourism framework has been developed. The "tourism tree" integrates aspects of a regenerative tourism paradigm and cultural values from Te Ao Māori (the world of Māori) and recognises the importance of healthy roots for tourism to contribute positively to multiple wellbeings and give back to place. Whilst only a stepping-stone towards transformative blending of paradigms, the framework will help the Department in their policy and operational decisions, with a view towards achieving intergenerational positive outcomes from tourism.

The COVID-19 pandemic triggered worldwide lockdowns and mobility restrictions, which continue to impact the global tourism industry. Early discussions on restarting the tourism industry occurred in high uncertainty constant change, and apprehension amongst political leaders and the public. Therefore, understanding public emotions and reactions toward border opening and international travel are essential. This research used the particular case of the 'travel bubble' between Australia and New Zealand to examine people's range of emotions as evident in social media. An automatic emotion analysis method was applied to identify eight emotions expressed through language. Furthermore, the content analysis was applied to detect key topics and understand potential triggers of the emotions. The theoretical background is appraisal theory which helps explain how a particular emotion was aroused. The results showed that people reacted positively to the travel bubble with anticipation, joy, and trust. Although fear peaked when the travel bubble temporarily paused, the confidence in the travel bubble was restored once a situation was resolved. By gauging people's emotions and concerns about the travel bubble, this research generates insights for tourism recovery and provides a method to gauge public emotions in future crises that affect international travel.

Understanding travel patterns is helpful for decision-makers to draw insights from consumers' perspectives. This work took advantage of social media and analysed tourists' travel patterns from the length of itineraries and duration of stay. Using Chinese tourists in Australia as a case study, results showed that most visitors prefer to stay in two core destinations, with an average duration of 8.5 days, while adding one destination increases the stay by around 2.5 days and caps at approximately 14 days. The travel patterns were further analysed by social network analysis and explained the network structure using core-periphery theory. The results were compared with official national survey data and demonstrated encouraging accuracy, which provides practical implications for destination planning and management. •Building a travel network from social media data to understand tourist mobility•Domestic flight connections played a significant role in connecting the destinations•Visitors prefer to stay in the two core destinations, with an average of 8.5 days•Length of itineraries influences the core-periphery structures in travel patterns

Purpose Destination monitoring is crucial to understand performance and identify key points of differentiation. Visitor satisfaction is an essential driver of destination performance. With the fast-growing volume of user-generated content through social media, it is now possible to tap into very large amounts of data provided by travellers as they share their experiences. Analysing these data for consumer sentiment has become attractive for destinations and companies. The idea of drawing on social media sentiment for satisfaction monitoring aligns well with the broader move towards smart destinations and real-time information processing. Thus, this paper aims to examine whether the electronic word of mouth originating from Twitter posts offers a useful source for assessing destination sentiment. Importantly, this research examines what caveats need to be considered when interpreting the findings. Design/methodology/approach This research focusses on a prominent tourist destination situated on Australia's East Coast, the Gold Coast. Using a geographically informed filtering process, a collection of tweets posted from within the Gold Coast destination was created and analysed. Metadata were analysed to assess the population of Twitter users, and sentiment analysis, using the Valence Aware Dictionary for Sentiment Reasoning algorithm, was performed. Findings Twitter posts provide considerable information, including about who is visiting and what sentiment visitors and residents express when sending tweets from a destination. They also uncover some challenges, including the "noise" of Twitter data and the fact that users are not representative of the broader population, in particular for international visitors. Research limitations/implications This paper highlights limitations such as lack of representativeness of the Twitter data, positive bias and the generic nature of many tweets. Suggestions for how to improve the analysis and value of tweets as a data source are made. Practical implications This paper contributes to understanding the value of non-traditional data sources for destination monitoring, in particular by highlighting some of the pitfalls of using information sources, such as Twitter. Further research steps have been identified, especially with a view to improving target-specific sentiment scores and the future employment of big-data approaches that involve integrating multiple data sources for destination performance monitoring. Social implications The identification of cost-effective ways of measuring and monitoring guest satisfaction can lead to improvements in destination management. This in turn will enhance customer experience and possibly even resident satisfaction. The social benefits, especially at times of considerable visitation pressure, can be important. Originality/value The use of Twitter data for the monitoring of visitor sentiment at tourist destinations is novel, and the analysis presented here provides unique insights into the potential, but also the caveats, of developing new, smart systems for tourism.

Smart tech offers much promise for tourism recovery from the COVID-19 crisis and the broader issue of decarbonising tourism. This paper investigates how accommodation managers engaged with smart tech during the crisis, and the journey of learning how to use numerical data output to drive sustainability actions. Interviews with nine accommodation managers/owners at six sites uncovers a 'tech journey' that extends prior to, and beyond, the acquisition and installation of the smart technology itself. The journey is explained by a new framework that recognises the need for users (here, the accommodation managers) of smart tech to 'make it their own', integrating it into their decisions, workflows and finally, identity. This can only happen through a capacity to understand what the data (i.e. numerical outputs) mean, and a process of transforming data into actions. Understanding these processes of 'data domestication' and 'data clotting' addresses key gaps in how to achieve potentially radical changes in resource use. Only one case study site had reached this final stage of the journey. The theoretical framework uses the findings from each case to propose early diagnostic questions/tools that can help identify where smart system may need assistance to move from data to action.

People provide information on their thoughts, perceptions, and activities through a wide range of channels, including social media. The wide acceptance of social media results in vast volume of valuable data, in variety of format as well as veracity. Analysis of such 'big data' allows organizations and analysts to make better and faster decisions. However, this data had to be quantified and information has to be extracted, which can be very challenging because of possible data ambiguity and complexity. To address information extraction, many analytic techniques, such as text mining, machine learning, predictive analytics, and diverse natural language processing, have been proposed in the literature. Recent advances in Natural Language Understanding-based techniques more specifically transformer-based architectures can solve sequence-to-sequence modeling tasks while handling long-range dependencies efficiently. In this work, we applied transformer-based sequence modeling on short texts' topic classification and sentiment analysis from user-posted tweets. Applicability of models is investigated on posts from the Great Barrier Reef tweet dataset and obtained findings are encouraging providing insight that can be valuable for researchers working on classification of large datasets as well as large number of target classes.

The purpose of this research is to test the usefulness of eye-tracking in measuring the perceived beauty of photos of the Great Barrier Reef. Eye-tracking is used to measure visual attention (fixation count, fixation duration) to 21 photos ranked in the degree of perceived beauty. Results indicate significant differences in visual attention to 'beautiful' and 'ugly' photos and a significant correlation between average perceived beauty and attention measures. This study provides evidence that eye-tracking can be used to measure the relative perceived beauty of natural images reflecting the attention given to 'attractive' images.

Purpose This paper aims to examine key parameters of scholarly context and geographic focus and provide an assessment of theoretical underpinnings of studies in the field of social media and visitor mobility. This review also summarised the characteristics of social media data, including how data are collected from different social media platforms and their advantages and limitations. The stocktake of research in this field was completed by examining technologies and applied methods that supported different research questions. Design/methodology/approach This literature review applied a mix of methods to conduct a literature review. This review analysed 82 journal articles on using social media to track visitors' movements between 2014 and November 2020. The literature compared the different social media, discussed current applied theories, available technologies, analysed the current trend and provided advice for future directions. Findings This review provides a state-of-the-art assessment of the research to date on tourist mobility analysed using social media data. The diversity of scales (with a dominant focus on the city-scale), platforms and methods highlight that this field is emerging, but it also reflects the complexity of the tourism phenomenon. This review identified a lack of theory in this field, and it points to ongoing challenges in ensuring appropriate use of data (e.g. differentiating travellers from residents) and the ethics surrounding them. Originality/value The findings guide researchers, especially those with no computer science background, on the different types of approaches, data sources and methods available for tracking tourist mobility by harnessing social media. Depending on the particular research interest, different tools for processing and visualization are available.

•A novel and innovative way of tracking Chinese visitors' mobility to Australia and other world regions•Mining data from Chinese social media Sina Weibo to understand their travel pattern•Hight resolution of data visualisation•Discover new dimension of global mobility

The adoption of renewable energy technology (RET) in the hotel sector is low, despite the technology's potential to reduce a hotel's energy consumption and carbon emissions. Previous research has explored selected aspects of RET adoption in hotels, but a comprehensive and systemic analysis is missing. This research uses a systems approach, which allows examination of a wide range of dynamics and complexities, including feedback mechanisms that influence system behaviour over time. The model was developed using the structural analysis method and causal loop diagramming in conjunction with theories of diffusion and patterns of innovation. The aim was to enhance our understanding of the hotel energy system, with a focus on drivers and barriers to RET adoption in the sector. The results demonstrate that the uptake of RET by hotels reflects an interplay between incentive policy, hotel owner/manager perceptions of RET, tourists' behaviour, technology advancement and electricity grid price. The analysis also uncovers the dynamics of key drivers that, under different circumstances, can also become barriers. The insights generated from the analysis validate the use of systems thinking to capture the complexities and dynamics of interactions.

Coral reef systems are at the point where passive restoration measures may have to be complemented by active restoration to protect global reefs. No longer is habitat conservation enough with the level and frequency of reef disturbance. This review explores the ecosystem-based adaptation (EbA) approach of active coral restoration, with people at the centre of analysis. This paper undertakes a perspective review that collated ( n = 37) academic papers and develops a ‘Human Dimensions of Coral Restoration Technology Adaptation’ framework that helps position the wide range of human dimensions of coral restoration studies. Seven phases were considered including assessing risks, assessing cost/benefits, understanding the socio-cultural context, implementing and technology transfer, managing conflict and maintaining success and scale-up of coral restoration. With every new restoration technology, calculating the micro- and macro-risks of such interventions is critical, followed by weighing up opportunity costs of such new technologies. People in situ hold the power to shape these restoration projects including the scientists envisioning these interventions, communities at grassroots, leaders that act as gatekeepers and businesses and tourists alike. Stakeholder management as well as the enabling governance arrangements are also critical strengthening opportunities to managing any potential underlying conflict that is possible between stakeholders.

Aesthetic values are a key driver of tourist and recreational visitation to natural areas and are listed among the selection criteria for World Heritage properties. However, assessment and monitoring of aesthetic values in natural areas, and coral reefs in particular, have proven to be challenging. In our study we explored the value and limitations of a rapid assessment approach involving non-expert ratings of aesthetic beauty as a potential tool for long-term monitoring of aesthetic values in the Great Barrier Reef World Heritage Area, Australia. We investigated the sensitivity of a rating scale for detecting change and sampling requirements for monitoring, as well as observer biases, using an online survey of 1417 Australians in which respondents rated the aesthetic beauty of 181 coral reef images on a ten-point scale. Our results show average aesthetic rating scores ranged from 4.35 to 8.34 on a scale from 1 (ugly) to 10 (beautiful), with potential to detect differences of statistical significance within one point, indicating sufficient sensitivity to change for monitoring purposes. We found that a sample size of c.100 ratings per image provided a reasonable balance between cost (i.e. sample size) and accuracy (i.e. error). Older respondents (>65 years) with higher levels of coral reef visitation, experience and interest were more likely to give extreme ratings, however, there was no apparent predictor for this bias to be positive or negative (high or low ratings). Based on these results we provide recommendations to assist coral reef managers in their use and interpretation of non-expert aesthetic ratings in coral reef monitoring.

PurposeThe purpose of this paper is to provide contrasting narratives of what the future of Asia Pacific tourism may look like, and to identify how current policy interventions and recommendations made for coronavirus disease 2019 (COVID-19) recovery shape the system's trajectory.Design/methodology/approachDrawing on a set of four possible futures emerging from COVID-19, tourism policy responses are analysed and a link to their potential contribution to the Sustainable Development Goals is made.FindingsA system goal is presented for each scenario, and what this means for the tourism system. Existing policies indicate that tourism is moving towards a "Discipline" future, although evidence for all four trajectories could be identified. Whilst the "Transform" scenario is most aligned with a sustainable future, the findings highlight that sustainability outcomes are possible in the other scenarios as well, if risks are managed adequately.Research limitations/implicationsThe limitation is that the core structure of the four futures was not specifically developed for tourism. However, given that tourism is firmly embedded in national and global economies, this limitation is not material.Practical implicationsThis paper supports decision-makers to develop adaptability in the face of great uncertainty and complexity. Risks and opportunities associated with each of the four tourism futures are identified, and examples are provided how sustainability outcomes can be maximised in each.Social implicationsSustainability is a safe and necessary strategy regardless of the trajectory to any of the four scenarios. The long-term health of the tourism system and anyone involved in it depends on significant progress along the Sustainable Development Goals.Originality/valueThis paper explores pathways for system change and how different COVID-19 policy approaches contribute to shaping the system's trajectory. It highlights the risks associated with certain trajectories, and also identifies how short-term recovery priorities might undermine long-term sustainability.

In March 2017, a category 4 cyclone, ?Cyclone Debbie?, made landfall across the Great Barrier Reef (GBR) region of Australia. Drawing on the social amplification of risk framework and the concept of emotional stability, this research aims to provide insight into the perceptions of risk and individual responses to the disaster event using Twitter data, facilitating future analysis of social media messages during disaster events. This study uses Twitter data collected from the GBR region before, during and after Cyclone Debbie. Findings revealed changes in emotional stability across the stages of the cyclone. The findings suggested that statements revealing lower emotional stability were associated with amplified perceptions of risk, whilst increased emotional stability attenuated perceptions of risk. However, this was not the case for the characteristic ?empathy?, which may have contributed to amplified perceptions of risk. Preparedness was also found to portray higher emotional stability characteristics. The findings have implications for future research analysing social media messages, as well as for disaster planning and response strategies.

Including members of the public in the development of effective environmental monitoring systems is gaining traction. This research assesses the potential for a hybrid monitoring system for the case of coral at the Great Barrier Reef. Based on a review of citizen-derived data sources, the paper first develops a framework and then populates it with five datasets. These are then compared based on data volumes, type of data, spatial coverage, and bleaching patterns. The results reveal the inherent difficulties - both in terms of quantity and quality - for collective sensing data (Twitter in this case) and more structured human sensors approaches (Eye on the Reef Sightings). However, more targeted approaches, such as CoralWatch and tourism-operator based data collection, emerged as important contributors to information generation on the state of coral. Citizen-based data that either deliver a high data density per location, a wide geographic coverage, or regular observations over time are particularly valuable. Recommendations are made for developing a hybrid monitoring system that integrates citizen-derived with professionally collected data.