Integrating scenario planning with futures wheels: a sequential framework for exploring tourism futures

The future of the tourism industry is increasingly shaped by uncertainties (Postma et al., 2024) arising from global challenges such as climate change (Gössling et al., 2010, 2023, 2024; Hall, 2019; Hall et al., 2015; Scott and Gössling, 2015), shifting consumer and community behaviours (Amelung et al., 2007; Becken, 2021; Gössling et al., 2020; Soler et al., 2020) and technological advancements (Becken and Shuker, 2019; Edelenbosch et al., 2017; Fletcher et al., 2019; Gössling, 2020; Gota et al., 2019; Soler et al., 2020). As these factors interact in complex ways, traditional forecasting methods often struggle to capture the full range of possible developments. Approaches utilizing a mix of methods in qualitative futures research offer a valuable means of addressing these complexities and uncertainties by providing deeper insights (Balula and Bina, 2013; Bengston, 2016; Metzger et al., 2010; Postma, 2015; Postma et al., 2017) into the implications and potential transformations for the tourism system and related stakeholders.

Among the various foresight tools available, scenario planning (Amer et al., 2013; Balula and Bina, 2013; Metzger et al., 2010; Postma, 2015; Walton, 2008) and futures wheels (Benckendorff, 2008; Ernst et al., 2018; Farrow, 2022; Kunttu et al., 2022) are gaining momentum as methodologies for exploring plausible futures. Scenario planning facilitates the development of multiple future narratives, enabling researchers and decision-makers to move beyond linear projections and anticipate a range of possible outcomes (Amer et al., 2013; Balula and Bina, 2013; Metzger et al., 2010; Postma, 2015; Walton, 2008). Meanwhile, the futures wheel method systematically maps first-, second- and third-order consequences of emerging trends and events, offering a structured approach to assessing cascading impacts (Benckendorff, 2008; Ernst et al., 2018; Farrow, 2022; Kunttu et al., 2022). Both tools have been rarely applied independently in tourism research, evidenced by a Scopus search on “tourism and futures wheel” yielding only three publications (Benckendorff, 2008; Moscardo et al., 2017; Seegolam et al., 2016) – and their integrated use remains unexplored.

This article proposes a mix-of-methods approach as a sequential exploratory design, where insights from one qualitative method inform the subsequent application of another, also in tourism. The first method, scenario planning, produces key insights and themes that then provide the foundation for the second method, the futures wheel, which builds upon and deepens the initial findings. This ensures the methods are analytically connected as interdependent stages within a coherent research strategy. By combining the strengths of both methods, this framework seeks to provide a more comprehensive means of identifying key uncertainties, of visualizing their effects and of generating actionable insights.

The following sections discuss the theoretical foundations of these tools and then present a case study that illustrates their practical application in tourism futures research.

To contextualize the proposed methodological framework, this literature review first provides an overview of futures research in tourism before discussing the two core methods used in this study: scenario planning and futures wheels.

Quantitative system modelling sometimes struggles to incorporate social drivers such as actors, decision-makers and institutions, key elements in sectors undergoing transition (Bell and Olick, 1989; De Cian et al., 2020; Melnikovas, 2018). Although tourism futures studies may still be considered in the early stages of development (Postma, 2015), social constructionist approaches have been effectively employed to explore potential tourism futures (Yeoman et al., 2015; Yeoman and Postma, 2014). Social constructionism in futures studies suggests that knowledge is not about predicting a predetermined future but about constructing plausible scenarios through abstraction and classification (De Smedt et al., 2013; Fuller and Loogma, 2009). While the future remains uncertain, methods can offer presumptive evidence of plausibility (Bell and Olick, 1989). Foresight grounded in social constructionism generates qualitative scenarios to anticipate future developments (Yeoman and Postma, 2014). This approach involves clarifying assumptions, engaging stakeholders and ensuring scenarios are coherent and contextually relevant (Yeoman and McMahon-Beattie, 2018).

Exploratory qualitative research provides a structured way to investigate under-researched phenomena and generate deeper insights in futures research (Kosow and Gaβner, 2008; Melnikovas, 2018). Such studies often serve as a foundation for more structured research approaches. Abduction as an approach to knowledge accumulation is suitable for qualitative futures research, as it allows for knowledge accumulation based on existing insights, progressing toward plausible explanations through iterative learning and revisiting existing knowledge for further explanations (Melnikovas, 2018; Moriarty, 2012; Paavola et al., 2006). Bell and Olick (1989) propose using “knowledge surrogates”, constructed on a “what if” basis for future-oriented social action to further develop depth and plausibility in future research and support decision-making. The authors define knowledge surrogates as substitutes for direct knowledge of the future to construct images of alternative futures (Bell and Olick, 1989). These surrogates serve as cognitive tools in decision-making, enabling social action in contexts of uncertainty. Their credibility relies on making their underlying assumptions explicit and intelligible – both of which allow for critical scrutiny – ensuring logical coherence, alignment with relevant past and present facts and consistency with other plausible projections within the same timeframe (von Bergner and Lohmann, 2014).

Futures research, therefore, is not a static process but a dynamic interplay of discourse, negotiation and evolving social interaction (Yeoman and McMahon-Beattie, 2014). Key uncertainties may stem from external or internal forces (von Bergner and Lohmann, 2014), influenced by sudden disruptive events or gradual developments unfolding at varying speeds.

Building on these principles, a mix-of-methods approach has been suggested to enhance the robustness of scenario planning (Benckendorff, 2008; Truong et al., 2020) by integrating expert-driven analysis with participatory research techniques. This study operationalizes such an approach, employing literature analysis and expert interviews to identify drivers of change and then using futures wheel workshops to explore the implications of tourism decarbonization for destination management. Such integration strengthens the reliability of foresight research (Star et al., 2016), although challenges such as power dynamics and participant fatigue remain (Derbyshire and Wright, 2017; Fuller, 2017; Patomäki, 2006). To understand how specific methods can be integrated to leverage these strengths while navigating potential challenges, the following sections detail the theoretical foundations of scenario planning and futures wheels.

Scenario planning is a strategic foresight method used to explore plausible future developments by identifying key drivers of change and uncertainties (Metzger et al., 2010). Rather than predicting the future, it constructs alternative scenarios (Amer et al., 2013; Balula and Bina, 2013; Khosravi and Jha-Thakur, 2019) that illustrate possible pathways without explicit claims about probability (Yeoman and Postma, 2014). The intuitive logic approach to scenario planning asserts that the future operating environment is shaped by a complex interplay of political, economic, social, technological, environmental and legal (PESTEL) factors, resulting in hypothetical scenarios that map out causal processes and key decision points (Amer et al., 2013; Derbyshire and Wright, 2017; Keseru et al., 2021; Melnikovas, 2018; Star et al., 2016). While certain factors such as demographics are precise and quantifiable, many, such as consumer attitudes, political dynamics, financial conditions and product demand, remain qualitative and unpredictable, a complexity that this approach explicitly acknowledges (Amer et al., 2013; Metzger et al., 2010).

This approach has been widely applied also in destination management at national and organizational levels (Amer et al., 2013) and is often an iterative process that evolves with shifting drivers and improved understanding (Postma, 2015). Scenarios can range from optimistic to apocalyptic (Bergman et al., 2010; Walton, 2008), though research often focuses on pragmatic scenarios that balance technological and societal shifts (Dator, 1979 as cited in Amer et al., 2013). When integrated with strategic planning, scenario planning helps decision-makers manage risks and navigate toward desirable futures (Benckendorff, 2008).

Despite its long history (Amer et al., 2013; Walton, 2008), scenario planning has gained traction in tourism research only in recent decades (Ahmadi Kahnali et al., 2020; Clark et al., 2022; Khosravi and Jha-Thakur, 2019; Postma, 2015; Scott and Gössling, 2015; Yeoman, 2012). Seyitoğlu and Costa (2022) note that much of this research remains internally focused on tourism matters, often overlooking broader external influences. This narrow scope may be a result of tourism's entrenched growth paradigm, driven by consumerism and neoliberal capitalism (Becken, 2017).

Scenario planning as a method, driven by identifying key forces, is inherently qualitative, relying on dialogue, creativity and intuition (Walton, 2008). The process involves categorizing key PESTEL drivers based on impact and unpredictability (Keseru et al., 2021). Key uncertainties serve as the foundation for constructing scenario narratives, which illustrate causal relationships and decision points (Amer et al., 2013). Given its qualitative nature, scenario planning is heavily influenced by facilitator expertise, participant diversity and communication dynamics (Derbyshire and Wright, 2017).

The methodology follows structured steps to ensure internal coherence. Moriarty (2012) outlines a widely used framework that involves identifying key issues, clustering related elements, prioritizing uncertainties and constructing scenario narratives. Earlier iterations of scenario planning were criticized for lacking reproducibility (Moriarty, 2012), but rigorous logical structuring and internal consistency are proposed to mitigate these concerns (Amer et al., 2013).

A combination of qualitative research methods enhances scenario planning's effectiveness and the robustness of outcomes. For example, expert consultations, brainstorming, interviews and document analysis help identify and interpret drivers of change (Ahmadi Kahnali et al., 2020; Amer et al., 2013; Ernst et al., 2018). Yeoman and McMahon-Beattie (2014) developed tourism scenarios by synthesizing literature, engaging experts in workshops and prioritizing key driving forces. Postma et al. (2017) similarly combined literature reviews with expert consultations to construct European tourism futures. Additionally, Barbosa et al. (2022) used a literature review to frame a study on the future of work in 2050, demonstrating the importance of integrating existing knowledge into foresight methodologies.

Scenario planning enables the exploration of multiple future trajectories, serving as a tool for providing plausible insights into structuring decision-making processes at the later stages. By acting as an interpretative framework, it may help stakeholders navigate uncertainties, anticipate challenges and adapt to evolving conditions in tourism and beyond. While scenario planning excels at constructing these broad future narratives, a complementary method is necessary to uncover implications in the evolving conditions and adaptations in the future.

The futures wheel is a structured foresight method designed to systematically capture expert knowledge and assess the direct and indirect implications of possible future changes (Kunttu et al., 2022). By mapping out causal relationships, it facilitates an exploration of complex interconnections between related issues and their potential impacts (Ernst et al., 2018; Farrow, 2022). Although originally developed in the 1970s (Benckendorff, 2008), its limited application in tourism means this research draws on broader applications of the method from other domains.

Recent studies have successfully employed the futures wheel to examine the long-term social impacts of COVID-19 and the future of work (Barbosa et al., 2022), assess geopolitical disruptions on supply chains (Krykavskyy et al., 2023) and evaluate European policy impacts on the Finnish forestry sector (Kunttu et al., 2022). The method has also been successfully employed in tourism research. Benckendorff (2008) evaluated the method for envisioning sustainable tourism futures, demonstrating how it can map systemic implications of emerging trends. Benckendorff et al. (2009) combined the futures wheel with backcasting to explore tourism's impact on host community quality of life, generating actionable insights for policy and planning. More recently, Konovalov et al. (2021) applied the futures wheel in participatory workshops to examine destination community well-being, revealing its value for fostering innovative and inclusive tourism futures. Given its flexibility and efficiency (Farrow, 2022), the method is well suited for examining complex futures, including tourism decarbonization.

The method is typically implemented in workshop settings lasting between 2.5 and 4.5 h (Ernst et al., 2018), depending on group dynamics and the complexity of identified implications. The futures wheel structure places a central issue of the future at its core, with successive concentric rings illustrating first-, second- and third-order implications (Barbosa et al., 2022; Farrow, 2022). Clearly defining the central issue enhances data comprehensiveness (Bengston, 2016), while structured brainstorming fosters creative and critical thinking (Benckendorff, 2008; Toivonen and Viitanen, 2016). Participatory approaches ensure diverse perspectives, but effective facilitation is crucial to prevent speculative or unstructured outcomes (Ernst et al., 2018).

Workshops typically proceed in stages: stakeholders identify first-order implications, which then inform second- and third-order implications on the wheel that stem from the previous upper-level implication (Benckendorff, 2008; Kunttu et al., 2022). Some studies incorporate predefined likelihood and desirability matrices to refine evaluation of the mapped implications (Bengston, 2016). This visual and qualitative method is efficient in terms of research resources, as it requires minimal data processing and enables clear identification of key linkages (Bengston, 2016, 2019; Bengston et al., 2022).

A notable limitation of the futures wheel is the potential for researcher bias, particularly in workshop facilitation. To mitigate this, facilitators should provide neutral information at the outset and avoid steering discussions (Benckendorff, 2008). Despite this challenge, the futures wheel is still a useful tool for exploring tourism futures, especially when dealing with complex and layered transition issues.

Building on the previous discussion, combining scenario planning with the futures wheel method provides a structured way to explore possible futures in tourism and future-related uncertainties. Using expert interviews and literature reviews as knowledge surrogates strengthens the plausibility of future scenarios by drawing on existing research and expert insights. Additionally, framing futures wheels around well-defined scenarios expands the exploration of potential implications and impacts of the future scenarios when contributions come from a separate group of experts. The next section will examine how this approach can be applied in practice.

Given the absence of standardized qualitative futures methodologies, integrating diverse approaches enhances the comprehensiveness of futures research and mitigates biases (Barbosa et al., 2022; Toivonen, 2021; Toivonen and Viitanen, 2016). Combining techniques such as the Delphi method and cross-impact analysis has proven effective in structuring tourism foresight studies (Benckendorff, 2008; von Bergner and Lohmann, 2014). Scenario planning remains relatively underutilized in tourism research (Khosravi and Jha-Thakur, 2019; Schwenker and Wulf, 2013; Scott and Gössling, 2015), though it has recently gained momentum (Losekoot 2025; Postma et al., 2024). The futures wheel has been recognized (Benckendorff, 2008; Toivonen, 2021) as a valuable tool for understanding the cascading impacts of future developments. By leveraging these complementary methods, tourism foresight research can more effectively inform strategic decision-making and long-term policy planning. The following section illustrates a sequential exploratory design that integrates scenario planning and futures wheels with a view to enhancing qualitative futures research in tourism.

This section details the application of the sequential exploratory design used in this study. In this logically structured flow, insights from scenario planning (Step 1) directly inform the futures wheel workshops (Step 2), integrating the two methods into a single, analytically connected framework.

The scenario development process, discussed hereafter, followed Moriarty's (2012) seven-step approach (Figure 1). As a starting point, this study employed a systematic literature review to identify key drivers of change and uncertainties around tourism concerned with decarbonization, and this provided a foundation for expert interviews and scenario planning. The literature review followed a structured four-phase process (Moher et al., 2009, 2015), namely identification, screening, eligibility and inclusion, using Scopus as the primary database to source the titles. Initial searches yielded 1,068 articles, which were refined to a final sample of 279 relevant publications. These were categorized based on key research topics and interests related to tourism carbon emissions, decarbonization efforts in tourism, drivers for related change and destination management approaches. Thematic analysis of the literature identified factors influencing the decarbonization of tourism, which were then used as an input to inform the subsequent expert interviews.

Experts interviewed were selected as knowledge surrogates (Patton, 2014) based on their recent scholarly contributions to tourism futures, destination management and decarbonization. An initial sample of eight academics was identified, with four ultimately participating in semi-structured interviews. These interviews focused on envisioning tourism in 2040, assessing uncertainties and identifying critical drivers of change. Experts were provided with preliminary factors derived from the literature and asked to validate, refine and prioritize these findings with their insights.

Data collected during the expert interviews underwent the usual coding and thematic clustering using the PESTEL framework (Derbyshire and Wright, 2017). Subsequently, each factor was assigned a fuzzy value to reflect its impact and uncertainty, which was then normalized to prioritize key uncertainties (Mitic et al., 2021). The analysis identified 21 critical factors within 17 sub-clusters, further refined through expert input, compared to 10 factors within 8 sub-clusters that were elicited through the literature analysis. Following this, mind-mapping was carried out by the lead researcher to illustrate interconnections.

In the fourth step of the seven-step process (Moriarty, 2012), the two most impactful and uncertain driving forces were identified through an XY scatter chart, highlighting factors with high impact but low predictability. These forces formed the foundation for scenario building. Extreme outcome variations for each force and cluster were then formulated based on the findings from the expert interviews. In step six, a scenario matrix was developed, mapping intersections of the driving forces and their possible outcomes. Finally, in step seven, four scenario storylines were crafted, providing logically coherent narratives that synthesized interrelationships between earlier identified factors and potential trajectories for tourism decarbonization in 2040 as projected by the matrix.

These four “tourism and decarbonization 2040” scenarios then served as the direct input for the next phase of the research, which explored their implications for regional tourism destinations through futures wheels.

With the scenarios established, this phase employed purposive sampling (Patton, 2014) to select representatives from New Zealand's 31 Regional Tourism Organizations (RTOs). A consultation with Regional Tourism New Zealand, an umbrella organization for RTOs, helped identify RTOs with an interest in reducing tourism's carbon footprint. Seven RTOs were initially shortlisted, but all declined participation. To expand the pool, a snowball sampling approach (Patton, 2014) was adopted, leading to the inclusion of two RTOs from the original list and five additional representatives from other RTOs.

To gather data, 6 futures wheel workshops were held with 25 representatives from RTOs and their associated stakeholders such as attraction operators, airport managers, transportation providers, accommodation operators, destination consultants and resource managers. Prior to the workshops, participants were sent an overview of the project, an introduction to the futures wheel methodology and participant consent forms. The workshops averaged 2 h and 17 min in duration and were recorded for later review purposes.

During the workshops, a designated future scenario was placed at the centre of the futures wheel (Figure 2). Participants familiarized themselves with this scenario and generated potential implications for the destination, tourism and its stakeholders by addressing the prompt, “What if […] ?” These implications were organized into a three-tier structure: first-, second- and third-order implications. Across six completed workshops, participants identified a total of 179 implications: 47 first-order, 79 second-order and 53 third-order – with second-order implications typically outnumbering first-order ones, as is common with this method (Benckendorff, 2008; Epp et al., 2022; Nielsen et al., 2023; Toivonen and Viitanen, 2016). Additionally, workshops with larger participant groups produced more comprehensive outcomes, while variations in complexity were linked to the region's stage of tourism development and the diversity of its wider economy, as well as the extent of active involvement in destination management.

In the following phase of the workshop, participants scored their first-order implications on a nine-point feasibility/likelihood scale (Bergesen et al., 2017; Farrow, 2022), considering factors such as technical, financial and operational constraints, as well as support from the community and stakeholders. The objective was to assess the suitability of the current destination management approach to address these implications in case the future scenario actually unfolded.

Subsequent data analysis involved converting the completed futures wheels into a digital format and using thematic analysis (Bengston, 2016) to identify recurring themes among the first-order implications. The analysis employed open coding (Patton, 2014) to identify major themes, and further coding was applied to examine implications specific to destination management functions. The data were cross-referenced to ensure consistency in interpretation. Seven key themes emerged: alignment with community values; tourism system effectiveness and streamlining; evolving industry practices and product offerings; alignment between visitor and community values; tourism-related carbon emissions; legislative frameworks and intervention; alterations in visitor profiles and revamped marketing strategies. The feasibility scoring revealed that implications relating to strategic development and leadership received lower scores, indicating that the current destination management approach may be ill-suited for implementing the systemic changes required.

The analysis of these themes identified several negative yet manageable implications that regional destination management deemed within their capacity to handle. In contrast, implications that fell outside the control of regional destinations and their stakeholders were considered unmanageable under the current framework. Overall, scenarios in which regional destination management organizations maintained control or received support from national leadership were assessed as both more desirable and more manageable, whereas initiatives led at the global level, despite their feasibility, were viewed as less desirable.

Having detailed the application of the integrated methodology, the discussion that follows will analyse its methodological synergy and implications.

This paper proposes and analyses an integrated methodological framework designed to enhance qualitative foresight and futures research (Figure 3). The integration of scenario planning with the futures wheel method offers a comprehensive and structured approach to exploring future uncertainties in tourism based on a sequential exploratory design. This framework combines qualitative insights with systematic mapping techniques to construct plausible future narratives and identify their related implications.

The framework recognizes the importance of integrating diverse data collection methods and involving multiple participant groups to capture the multifaceted nature of future scenarios. In the case presented here, combining these methods leveraged the strengths of academic rigour and practical tourism industry experience, offering a more complete and nuanced picture of potential futures (Derbyshire and Wright, 2017; Fuller, 2017; Patomäki, 2006; Star et al., 2016; von Bergner and Lohmann, 2014). Although underutilized in tourism research (Khosravi and Jha-Thakur, 2019; Schwenker and Wulf, 2013; Scott and Gössling, 2015), this mix-of-methods framework revealed a broader array of insights than traditional single-method approaches could have.

In the case study presented here, this process was implemented as an integrated and coherent research strategy, not a segmented application of isolated tools. It began with scenario planning, where academic experts provided deep insights into uncertainties and driving forces (Balula and Bina, 2013; Metzger et al., 2010; Postma et al., 2017). Guided by an intuitive logic approach (Melnikovas, 2018), the researchers developed narrative-based scenarios (Moriarty, 2012; Walton, 2008) that incorporated both predictable trends and unexpected shifts.

These scenarios then formed the foundation for futures wheel (Barbosa et al., 2022; Kunttu et al., 2022; Toivonen, 2021) workshops conducted with regional tourism organization stakeholders. In these sessions, a previously created scenario storyline was placed at the centre of the wheel (Figure 1), and participants were tasked with mapping out first-, second- and third-order implications (Barbosa et al., 2022; Ernst et al., 2018; Farrow, 2022; Krykavskyy et al., 2023; Kunttu et al., 2022) – essentially tracing the cascading impacts that might affect destination management. This dual-phase process created a dynamic feedback loop: the academic insights that shaped the scenarios were enriched by practitioner-led analysis of potential outcomes. This framework not only enhanced the plausibility of the future scenarios by drawing on established research and expert perspectives but also broadened the exploration of implications by engaging a separate group of experts in evaluating the consequences.

Evaluating the implications using likelihood and desirability scales provided additional depth, highlighting which impacts were likely to occur and how they might influence destination management practices if any of the future scenarios were to unfold. The workshop data indicated that groups of 4–6 participants yielded a greater number and diversity of implications and optimal group dynamics, underscoring the importance of participant group size and composition.

Findings from the case indicate that engaging both academic and practitioner perspectives enhances the credibility and applicability of futures research. Academic expert-driven scenario development broadened the range of factors and clarified uncertainties, while practitioner-led futures wheels provided a context-specific assessment of implications at the regional level. Such comprehensive insights would not be possible if only one of these methods were used in isolation.

While this integrated framework offers considerable strengths, its application involves several methodological considerations common to mix-of-methods futures research in relation to the number and nature of the participants and their contextual environments and the role of the researcher. Stakeholder engagement and sampling require close attention. Participatory research often requires adaptive recruitment strategies, especially when engaging senior stakeholders with significant time constraints (Patton, 2014). Researchers must be mindful that the chosen sampling approach can influence the composition of the participant pool and the subsequent breadth of perspectives gathered. For instance, in this study, the initial purposive sampling of seven RTOs was unsuccessful, necessitating a shift to a snowball sampling strategy to successfully recruit the required number of participants.

The role of researcher-led synthesis: In a sequential design, the researcher plays a crucial role in bridging the different methodological stages. This involves an interpretative synthesis of data from the initial phase to create the stimulus materials for the subsequent phase (Benckendorff, 2008; Melnikovas, 2018; Moriarty, 2012; Walton, 2008). In this project, this involved synthesizing the literature review and expert interviews into four distinct “tourism and decarbonization 2040” scenarios, which were then presented as the direct stimulus for the futures wheel workshops. This process, along with the careful facilitation of group dynamics in workshops, is an inherent part of the methodology that requires reflexivity to ensure consistency and minimize potential bias.

Context-dependent nature of outcomes: The outputs of participatory foresight methods are naturally shaped by the context of the participants involved. The richness and character of the data generated can vary depending on the professional backgrounds, expertise and specific operating environments of the stakeholders (Derbyshire and Wright, 2017; Kunttu et al., 2022; Star et al., 2016; Yeoman and McMahon-Beattie, 2014). This was evident in the findings, where workshops with participants from regions with more advanced destination management plans yielded a greater number and diversity of implications, highlighting the influence of the local context. This variability yields deep, situated insights but also requires careful consideration when analysing and comparing results across different participant groups.

These points underscore that the framework's application should be tailored to its specific context and highlight opportunities for ongoing methodological refinement. Future research could continue to explore the integration of complementary foresight techniques to further strengthen and adapt these mix-of-method approaches for diverse settings.

For practitioners such as destination managers and policymakers, this framework offers a structured yet flexible tool for strategic foresight. It provides a practical, step-by-step process to move beyond abstract futures thinking and toward actionable insights that support resilient and adaptive planning processes. The structured outcomes generated by the futures wheel are ideally suited for use in sequence with backcasting methodology (Bengston et al., 2020; Konovalov et al., 2021), allowing practitioners to determine the necessary policy steps and milestones required to achieve the desirable futures identified during the workshop. By visualizing cascading implications, the method enables organizations to identify potential triggers, assess strategic vulnerabilities and pinpoint critical inflection points, thereby strengthening proactive risk management in an increasingly complex and dynamic environment.

For researchers, this article provides a detailed and adaptable template for conducting robust qualitative futures research. It responds to the need for more structured qualitative methodologies and can be modified to explore other complex issues beyond tourism decarbonization, such as technological disruption or shifting consumer behaviours.

This article presented a mix-of-methods framework that integrates scenario planning with futures wheels to advance qualitative futures research in tourism. This sequential exploratory design functions as an integrated and coherent research strategy, not a segmented application of isolated tools. By combining intuitive logic-based scenario development with practitioner-led mapping exercises, the framework offers a robust mechanism for identifying key uncertainties, visualizing their cascading impacts and generating actionable insights. For tourism practitioners, this integrated approach provides valuable tools to identify potential triggers, assess strategic vulnerabilities and pinpoint critical inflection points – thereby supporting the development of proactive risk management strategies in an increasingly complex and dynamic environment.

In the sampled case, scenario planning provided a structured framework to identify key drivers and their uncertainties by incorporating insights from academic experts. In parallel, futures wheels enabled practitioners to systematically explore first-, second- and third-order implications, offering nuanced insights into how various future scenarios might unfold. Additionally, participant scoring on feasibility and desirability further underpinned perspectives on the potential implications of the scenarios. The combination of these methods facilitated a holistic exploration of systemic constraints, challenges and potential leverage points, offering a structured yet flexible means for practitioners to navigate uncertainty, thereby supporting more resilient and adaptive planning processes.

This study was approved by the University Human Ethics Committee (Ref: D21/410). Informed consent was obtained from all participants.