Abstract
This study employs longitudinal process tracing to examine overtourism in Barcelona (1986–2025), tracing its trajectory from an industrial port to a global tourism hub. Drawing on 45 evidentiary units, Bayesian updating, and Collier’s (2011) diagnostic tests, we validate seven causal mechanisms: infrastructure lock-in, regulatory gaps, digital amplification, cultural commodification, resident resistance, governance fragmentation, and biopolitical erosion. These mechanisms interact through path-dependent feedback loops under neoliberal urbanisation, generating housing crises, cultural erosion, and social conflict. Challenging linear destination life-cycle narratives, we propose the Cascade Amplification Framework, a five-layered model designed to mitigate overtourism and offer transferable insights for other urban tourism destinations facing similar pressures.
Keywords
Highlights
The study applies longitudinal process-tracing with Bayesian updating to explain overtourism in Barcelona (1986-2025).
We validate seven causal mechanisms through 45 evidentiary units and Collier’s (2011) diagnostic tests.
We introduce the Cascade Amplification Framework linking infrastructure lock-in to biopolitical erosion.
We provide a transferable diagnostic and policy tool for heritage cities facing tourism pressure.
Introduction
Overtourism, defined as the condition in which tourist flows exceed a destination’s ecological, social, and infrastructural carrying capacity, thereby undermining residents’ quality of life, degrading cultural heritage, and compromising environmental sustainability (Mihalic, 2020; Milano et al., 2024), has become a defining crisis for European heritage cities (Capocchi et al., 2019). While many cities struggle with these pressures, Barcelona serves as more than a mere paradigmatic example of urban strain. It constitutes a significant analytical puzzle: despite being an early adopter of sophisticated tourism management policies, the city continues to face escalating disruptions to housing affordability and its social fabric (Milano et al., 2019). This disconnect between policy intervention and lived reality makes Barcelona an essential site for interrogating why traditional sustainability frameworks often falter in high-density urban environments.
The puzzle is rooted in the city’s post-Franco development strategy. Since the 1992 Olympic Games, tourism was positioned as the cornerstone of the so-called “Barcelona Model” of urban regeneration and neoliberal urbanisation (Balibrea, 2001; Garcia-Ramon & Albet, 2000; Marshall, 2000). By fusing democratic aspirations with growth-oriented policies, this model elevated tourism from merely an economic sector to the central engine of urban transformation, fuelling employment, international branding, and public investment. However, this unwavering focus, combined with unchecked tourism expansion, has produced severe negative externalities, straining the urban fabric through overcrowding, infrastructural overload, and a profound housing affordability crisis widely linked by residents, local authorities, and scholars to processes such as the proliferation of short-term rentals (Bourliataux-Lajoinie et al., 2019; Milano et al., 2019; Russo & Scarnato, 2018).
Although drivers such as platform-mediated accommodations and low-cost aviation are well-documented (Alonso-Almeida et al., 2019; Guttentag, 2015), the literature has paid limited attention to their longitudinal interactions and cumulative effects. Overtourism is often framed as an inevitable stage in a destination life cycle or as a managerial failure of oversight, thereby overlooking its historically contingent and politically mediated nature. This gap is evident when considering comparative cases contexts: While mega-events like the Olympics catalysed regeneration in London (2012) and Atlanta (1996), these cities achieved greater economic diversification and exhibited less pronounced tourism dependency, partly due to stronger pre-existing service sectors and less centralised heritage assets (Baroghi & Ribeiro, 2024). Barcelona’s divergence, where the 1992 Games aligned with democratic transition and entrenched tourism as a form of urban financialisation, thus constitutes more than a policy outcome; it represents a path-dependent lock-in demanding deeper explanation. This comparative puzzle highlights the limitations of existing models and refines our central research question: What sequence of causal mechanisms explains the transformation of Barcelona’s tourism system from post-Olympic expansion to overtourism between 1986 and 2025?
To address this, we argue that neither cyclical destination life cycle models nor linear narratives of decline fully capture the historically contingent, accelerated spiral evident in Barcelona. Instead, we conceptualise overtourism as a cascade amplification process, where early structural commitments within the Barcelona Model are intensified progressively and rapidly by contemporary platform-driven accelerators. This study therefore introduces the Cascade Amplification Framework (CAF) as a new diagnostic tool. Theoretically, the framework advances beyond cyclical models by explicitly incorporating the feedback-driven amplification dynamics of contemporary tourism. Empirically, it provides a structured method to identify key leverage points for intervention.
To empirically validate this framework, the analysis employs longitudinal process-tracing, supported by Bayesian updating and Collier’s (2011) diagnostic tests on 45 evidentiary units spanning nearly 4 decades. This method enables the identification and validation of seven sequentially interacting causal mechanisms. The article proceeds as follows. Section 2 reviews the literature on overtourism drivers and gaps. Section 3 details the methodology. Section 4 traces Barcelona's historical phases and validates the causal mechanisms. Sections 5–7 present the CAF and discuss its theoretical and practical implications.
Literature Review
The academic discourse on overtourism has undergone significant evolution, shifting from initial descriptive case studies documenting its localised impacts to more nuanced analyses probing its complex, multi-causal nature and embeddedness within broader political and economic systems (Novy & Colomb, 2019). Key debates within this burgeoning field now coalesce around five core thematic areas: conceptual definition and evaluation frameworks; identification of primary drivers and accelerators; sociocultural, economic, and environmental impacts; resident resistance and the phenomenon of “tourismphobia”; and governance responses and policy evaluation. Therefore, the subsequent literature review is explicitly structured around these five thematic dimensions to ensure systematic coverage and structural clarity.
Conceptual Definition and Evaluation Frameworks
Early foundational work, such as Russo’s (2002) “vicious circle” framework, conceptualised overtourism in heritage cities as a self-reinforcing process. This model suggested that a destination’s success in attracting visitors inevitably erodes the cultural and environmental assets that form its primary appeal, leading to a decline in quality and growing resident discontent. While influential, this framework has been criticised for its linear perspective and limited attention to the structural forces shaping tourism development. Similarly, Butler’s (1980, 2025) tourism area life cycle model describes destinations evolving through stages of involvement, development, consolidation, or stagnation, and potential rejuvenation or decline. A primary critique is their failure to capture the structural and technological dynamics of the modern crisis; for example, the digital platforms and short-term rentals identified by Dodds and Butler (2019a) as key accelerators are absent from Butler’s (2025) updated TALC model. Dodds and Butler (2019a) height three key gaps: a lack of a comprehensive framework for overtourism’s complex realities; insufficient evidence on stakeholder relations, weakening case-study depth, and superficial coverage of overtourism’s links to heritage tourism, especially residents’ views. They stress that short-term economic priorities and absent collaborative planning continue to worsen the crisis.
Primary Drivers and Accelerators
More recent scholarship marks a clear paradigm shift by embedding overtourism within the broader dynamics of late and platform capitalism (Cocola-Gant & Gago, 2021; Higgins-Desbiolles et al., 2019; Milano et al., 2024). Central to this view is the transformative role of short-term rental platforms, which financialise urban housing and convert residential units into tourist assets, thereby intensifying displacement, gentrification, and resident opposition (Guttentag, 2015, 2019; Wachsmuth & Weisler, 2018). This analysis repositions these phenomena from mere symptoms of overcrowding to structural outcomes of platform capitalism. Consequently, this lens illuminates why technology-enabled mediation has become a primary accelerator of overtourism, frequently overwhelming the regulatory and planning capacities of urban destinations. This emphasis on structural rigidity is further reinforced by the concept of infrastructure lock-in, where large-scale tourism investments create long-term material and political dependencies that are difficult to dismantle (Z. M. Jones & Ponzini, 2018; Novy & Colomb, 2017). A related analytical blind spot is the tendency to treat housing unaffordability and cultural commodification as separate issues, rather than as interconnected effects accelerated by platform economies that drive the resident backlash central to the “overtourism” phenomenon (Cocola-Gant & Gago, 2021).
Sociocultural, Economic and Environmental Impacts
The third thematic area delineates the multidimensional impacts of overtourism. Economically, overtourism is a significant source of global employment and has contributed substantially to gross domestic product (GDP) in many destinations. Resident surveys indicate mixed views, with acknowledgment of employment benefits alongside predominant concerns over housing and livability (Elorrieta et al., 2022). However, resident surveys and empirical studies also reveal mixed perceptions, with some acknowledging economic benefits while the majority highlight severe costs related to housing affordability and tourism-induced gentrification (González-Reverté, 2022). The digital platform boom can lead to resident displacement and inflationary pressures, heightening economic dependency and seasonal vulnerability. Socioculturally, overtourism precipitates the commodification of heritage, an erosion of place-based authenticity, the degradation of quotidian social life, and rising anti-tourist sentiment (Żemła, 2020). Environmentally, the impacts extend well beyond the significant carbon footprint from aviation and cruising (Holden et al., 2022). Overtourism intensifies local environmental stress through excessive water consumption, heightened waste generation beyond municipal management capacities, direct ecosystem degradation in sensitive natural and urban areas, and increased levels of air and noise pollution (Diah, 2025). Increasingly, critical analyses of these impacts are framed through environmental-justice and political-ecology lenses, transcending traditional cost-benefit frameworks.
Resident Resistance and “Tourismphobia”
The fourth thematic cluster addresses the reconceptualisation of resident opposition. Scholarly discourse frames this shift as moving away from the characterisation of opposition as irrational “tourismphobia” toward its analysis as a form of sociopolitical contention grounded in “right to the city” claims (Novy & Colomb, 2019). Systematic reviews position tourismphobia as an emergent response to overtourism pressures, manifesting as a continuum of resistance practices that range from aversion and protests to grassroots movements (Milano et al., 2024). Empirical studies in Barcelona have documented and assessed this continuum, citing practices such as graffiti, social media campaigns, and neighbourhood assemblies, which exhibit varying degrees of efficacy (Hughes, 2018). Media amplification and acute housing crises are identified within the literature as critical catalysts for this mobilization.
Governance Responses and Policy Evaluation
Governance fragmentation and a lack of political will are consistently identified as the primary structural drivers of overtourism (Dodds & Butler, 2024). A core issue is the vertical disconnect: city authorities lack effective control over key arrival gateways, ports, airports, and rail terminals, which are governed by regional or national authorities with growth-oriented mandates, severely constraining the ability to impose visitor caps (Butler & Dodds, 2022; Goodwin, 2021). This is compounded by horizontal coordination failures and a political reluctance to abandon a growth-first paradigm, leading destinations to promote tourism long after carrying capacities are exceeded (Butler & Dodds, 2022). The case of Barcelona is illustrative: despite formally prioritising governance reform in its 2010–2015 Strategic Tourism Plan, its corresponding programs were systematically under-implemented and achieved the lowest execution rates (Martins, 2018). Collectively, this evidence reframes overtourism not as a technical management failure but as a predictable outcome of multi-level governance deficits and a political prioritisation of short-term economic gains over resident wellbeing and ecological limits (Butler & Dodds, 2022; Dodds & Butler, 2019a; Goodwin, 2021).
A critical gap, however, remains in understanding the precise temporal sequencing and interaction of these drivers. Theoretically, this review synthesises the disparate literature into a thematic framework, elucidating the causal pathways and feedback mechanisms therein to establish a conceptual architecture for subsequent model building. Practically, by integrating diagnostic metrics, risk determinants, social costs, and policy instruments into a unified analytical schema, it empowers urban managers to identify localised vulnerabilities with precision and facilitates a paradigm shift from ex-post remediation to a governance cycle of ex-ante anticipation and ex-durante adaptation.
Methodology
Process Tracing Method
Process tracing is a qualitative methodology grounded in generative causality, which aims to uncover the causal mechanisms linking interventions to outcomes by reconstructing the “unbroken chains of action and reaction” that connect them (Beach, 2017; Blatter & Haverland, 2014). It addresses key limitations of traditional quantitative methods, which often overlook causal pathways, and counterfactual approaches, which frequently fail to explain why change occurs, by foregrounding context, mechanisms, and stakeholder interactions. Process tracing is an increasingly vital method in tourism studies for establishing causation within complex, politically-charged interventions. It allows researchers to move from correlation to causation by integrating diverse evidence streams and applying rigorous tests. For example, Montano et al. (2025) adopted process tracing to make within-case causal inferences about an EU-Interreg sustainable tourism intervention. Similarly, Suno Wu et al. (2025) used process tracing to evaluate how social learning communities of practice facilitate action-oriented sustainability learning as part of government intervention. This approach provides a transparent and replicable framework for analysing highly contingent sustainable tourism phenomena.
In this study, we employ process tracing to draw within-case causal inferences by systematically identifying and testing the mechanisms that connect specific interventions (X) to observed outcomes ([Y] Kay & Baker, 2015). The methodology is structured around four core components: (1) the specification of causal mechanisms, theoretical sequences that explain how X produces Y, broken down into empirically measurable steps; (2) evidence evaluation using four diagnostic tests (straw-in-the-wind, hoop, smoking gun, and doubly decisive) to assess probative value (Collier, 2011); (3) explicit consideration of rival hypotheses to strengthen the validity of causal claims (Zaks, 2017); and (4) the construction of coherent causal narratives that logically connect causes to effects.
As outlined in Figure 1, the research process unfolded in three structured stages. First, we identified and mapped the types of empirical evidence expected to be generated by each hypothesised causal mechanism. Second, we systematically collected empirical material and assessed its consistency with these theoretical expectations. Third, each piece of evidence was classified using Delahais and Toulemonde’s (2017) contribution analysis framework, which categorises evidence into four distinct types based on source and nature to systematically evaluate its relevance and strength in supporting causal inferences.
The theory building of process tracing.
Evidence Classification
Table 1 presents the evidentiary basis for examining the sequential causal chain of overtourism in Barcelona from 1986 to 2025. The analysis begins in 1986, the year of Barcelona’s Olympic designation, a catalytic event that transformed post-Franco renewal into a tourism-oriented, neoliberal urban project (Balibrea, 2001). This window is strategically chosen to capture the phenomenon’s full trajectory, from its onset and escalation to the associated policy responses and societal dynamics.
Evidence Classification and Test.
Note. Table 1 organized thematically by mechanism for analytical clarity; temporal markers enable phase alignment (see Figure 3).
To facilitate validation, the 45 purposively sampled evidentiary units are organised by causal mechanism rather than strict chronology. Each unit includes temporal references for historical alignment. Full details on the classification, weighting, and justification for each unit are provided within the table. Evidentiary units were identified through a systematic multi-stage search protocol. First, keyword searches were conducted in Scopus, Web of Science, and Google Scholar using terms such as “Barcelona overtourism,” “Airbnb Barcelona,” “1992 Olympics urban legacy,” and “Barcelona tourism governance,” which yielded 32 highly relevant peer-reviewed articles after screening an initial set of approximately 150 records. Second, official sources were systematically retrieved from the Ajuntament de Barcelona (Barcelona City Council) and Spanish government repositories, including key ordinances such as PEUAT 2017, strategic tourism plans and annual budgets. Third, targeted searches in the BBC news archives, CaixaBank Research, Responsible Vacation provided investigative journalism and protest chronologies. For inclusion, each unit had to be directly relevant to the hypothesised causal mechanisms, cover the 1986–2025 period, and contribute to source diversity.
The sample size of 45 was determined based on three key considerations. First, preliminary sampling confirmed that theoretical saturation was attainable, as additional evidence ceased to yield new insights into the four hypothesised mechanisms. The final count of 45 units was therefore considered sufficient to capture all relevant causal pathways. Second, methodological rigour required that each mechanism be supported by at least two to three pieces of evidence to pass Collier’s (2011) four empirical tests: straw-in-the-wind, hoop, smoking gun, doubly decisive. Third, the sampling focused on critical events rather than the entire duration of the study period (1986–2025) to ensure alignment with the key nodes of the overtourism causal chain. The final sample resulted from a strict two-step stopping rule: sampling ceased at unit 45 upon reaching theoretical saturation, and the final collection ensure every mechanism passed at least one smoking-gun or doubly-decisive test. Credibility was enhanced through source diversification, and reliability was ensured via cross-verification.
Sources of these evidentiary units included peer-reviewed articles, municipal ordinances, government budgets, investigative journalism, geocoded short-term rental data, protest chronologies, and institutional reports. Each unit underwent context-aware independent double coding following a unified three-tier protocol conducted by three primary coders with expertise in qualitative methods. A detailed coding manual was developed to operationalise test classifications in line with Collier (2011), Bennett and Checkel’s (2015) typology (shown in Figure 2): “hoop tests” were defined as evidence that must be present to sustain the mechanism; “smoking-gun tests” were defined as evidence that strongly confirms the mechanism but may not be universally present; “doubly decisive tests” were defined as evidence that simultaneously confirms the target mechanism and rules out rival explanations; “straw-in-the-wind tests” were defined as evidence that provides weak circumstantial support without being necessary or sufficient. Coding disagreements were adjudicated by a third independent senior colleague from a Spanish university, who was blinded to the initial codes and provided written justification for final decisions. Inter-coder agreement exceeded κ = 0.88. The probative weight of each piece of evidence was assigned strictly according to Collier’s (2011) standard four-test hierarchy: +0.5 for straw-in-the-wind, +1.0 for hoop, +1.5 for smoking-gun, and +2.0 for doubly decisive. These weights, together with the specific test passed by each unit, full details on the classification, weighting, and justification of each evidentiary unit, are provided in Table 1.
Process-tracing diagnostic tests.
While process tracing is widely used in political science and international relations, its implementation is not without challenges, particularly regarding epistemological and methodological assumptions (Vennesson, 2008). Researchers must address issues such as transparency, formalisation, and the development of robust interpretive variants (Checkel, 2021). To address these challenges, especially the difficulty of unambiguously specifying probabilities, explicit Bayesian analysis in process tracing offers a solution: it can help pinpoint areas of contention and refine researchers’ intuition to follow Bayesian probability principles more systematically (Beach & Pedersen, 2013).
Findings
The evidence classification in Tables 1 and 2, evaluated using Collier’s (2011) diagnostic tests, provides the empirical foundation for validating the causal mechanisms. Table 2 summarises the formal process-tracing results, listing each mechanism (M1–M7), the key evidentiary units and tests passed, and the resulting average probative score.
Mechanism Test.
Note. Test strength follows Beach and Pedersen (2013).
Section 4.1 derives each mechanism sequentially from the evidence chains in Table 1, emphasising causal interactions and feedback loops. Section 4.2 then integrates these mechanisms into the historical phases illustrated in Figure 3, tracing the full escalation trajectory of overtourism in Barcelona.
Historical periods and causal mechanism of overtourism in Barcelona.
Mechanism Derivation
The seven mechanisms were identified through an iterative deductive-inductive process: initial deduction from literature gaps outlined in Section 2, followed by inductive refinement based on recurring empirical patterns, concluding at theoretical saturation when no further mechanism added explanatory value. The weights in Table 2 follow Collier’s (2011) diagnostic criteria and are aggregated to yield mechanism-specific average scores.
Mechanism 1(M1): Mega-event infrastructure and accessibility lock-in causes long-term tourism dependency
The causal process begins with two hoop tests that establish necessary preconditions: EB1 demonstrates that pre-1992 Barcelona suffered from severe deficits in international visibility, coastal accessibility, and modern transport infrastructure; without the Olympic bid, these gaps would have remained unaddressed (Degen & García, 2012). EB22 confirms that the new transport nodes, airport expansion, ring roads, and especially the relocation of the cruise terminal to the foot of La Rambla were explicitly designed to serve large-scale tourist inflows, thereby making tourism-oriented accessibility a non-substitutable requirement of the 1992 Games (Kukkamäki, 2020).
Two smoking-gun tests then provide decisive evidence of the lock-in effect: EB2 and EB31 show that the massive, fixed capital investments in the Vila Olímpica, waterfront regeneration, ring roads, and port upgrades created sunk costs that could be amortised through continuously rising visitor volumes. The original 1992 Olympic Bid Dossier and subsequent infrastructure plans explicitly tied economic viability to mass tourism (Sánchez & Broudehoux, 2013), while the combined effect of low-cost airlines, high-speed rail, and cruise megaships produced the “hypermobility” that drove airport passengers from 9 million in 1990 to 47.28 million in 2017, and turned day-trippers into nearly half of all visitors (Tesfahuney & Ek, 2024). EB3 (straw-in-the-wind) further reinforces the self-perpetuating nature of the “Barcelona Model” narrative through the explosive post-Olympic hotel boom, with a net increase in hotel numbers from 1990 to 2015 at a growth rate of 225% (Cocola Gant, 2018), and Barcelona’s consolidation as Spain’s leading cruise hub (Statista Research Department, 2025a), which politically cemented tourism as the primary justification for the original investment.
Taken together, the evidence chain passes two necessary hoop tests (EB1, EB22) and two highly probative smoking-gun tests (EB2, EB31), supplemented by one straw-in-the-wind test (EB3), yielding a derivation: the mega-event infrastructure built in Phase 1 (1986–1992) did not merely facilitate tourism growth; it generated path dependency by tying the city’s economic viability to ever-higher tourist inflows. This structural lock-in forms the foundational commitment from which all subsequent mechanisms cascade. As aligned in Figure 3, this mechanism dominates Phase 1 (1986–1992), setting the trajectory for post-Olympic consolidation in Phase 2.
Mechanism 2(M2): Regulatory gaps and governance failures cause unregulated STR growth, housing overload, and labor inequality
Building on the structural lock-in established by M1, which created tourism-dependent infrastructure, Mechanism 2 examines how regulatory gaps amplified this dependency into housing and labour crises. The causal chain for Mechanism 2 begins with two hoop tests that establish necessary preconditions for uncontrolled short-term rental expansion: EB4 demonstrates that Barcelona operated without any specific zoning or licensing regime for tourist apartments until the introduction of PEUAT in 2017; in the absence of this prolonged regulatory vacuum, the mass conversion of residential housing stock into tourist accommodation would have been impossible (Guttentag, 2015). EB34 further confirms the presence of a vertical governance disconnect between municipal, regional, and national authorities, compounded by tourism’s reliance on low-wage, seasonal, and migrant-dominated jobs, which was required for systematic enforcement failure to occur (Solís & Gil, 2024).
Three smoking-gun tests then provide decisive evidence of direct causation. EB5 isolates a causal effect of STR proliferation on an additional 1.9% annual rent increase, 4.6% transaction price escalation, and 3.7% posted price increase that cannot be attributed to general urban growth, migration, or macroeconomic trends alone (Garcia-López et al., 2020). EB26 documents that the 2012–2013 introduction of SOCIMI tax exemptions explicitly channelled large-scale speculative foreign capital into tourist-oriented real estate investment vehicles (Blanco-Romero et al., 2018).
Four straw-in-the-wind tests consistently reinforce the same causal direction: EB6 and EB27 record widespread resident perception of illegality and injustice, evidenced by over 16,000 critical social-media posts and tweets from neighbourhood assemblies ABTS/ABDT denouncing housing encroachment and rent hikes (Aguilera et al., 2021; Morales-Pérez et al., 2022); EB10 and EB24 highlight chronic delays in inspections, poor inter-agency coordination, and low participation that rendered even the limited pre-2017 regulations unenforceable (Goodwin, 2017; Gyódi et al., 2025); overlapping evidence further ties tourism’s economic dominance to deepening labour inequality.
Passing two necessary hoop tests (EB4, EB34) and three smoking-gun tests (EB5, EB26) with an average score of 0.89, supplemented by four straw-in-the-wind tests, the evidence chain derives with medium-high confidence that regulatory gaps and misaligned governance priorities actively caused the uncontrolled growth of short-term rentals, the ensuing housing affordability crisis, and deepening socioeconomic inequality. By converting the physical and accessibility surplus created by M1 into a financialised rent-extraction mechanism, M2 constitutes the critical first amplification layer that made subsequent digital concentration (M3) and cultural commodification (M4) both feasible and socially explosive. In Figure 3, M2 bridges Phases 2-3 (1992-2010), escalating unregulated growth.
Mechanism 3(M3): Social media and digital platforms cause tourist flow concentration, experience homogenisation, and behavioural disruptions
Extending M2’s platform-enabled expansion, Mechanism 3 explores how digital tools further concentrate flows, homogenising experiences. The causal chain for Mechanism 3 begins with a single but decisive smoking-gun test: EB23 provides direct, geocoded and ethnographic evidence that algorithmic ranking systems on Instagram, Airbnb Experiences, and TripAdvisor actively funnelled tourist flows into a handful of hyper-visible sites, such as Park Güell, Sagrada Família, La Rambla and Barceloneta, generating concentration ratios that rose from 18% of total visits in 2010 to over 62% by 2018–2019, and cannot be explained by historical prestige, transport improvements, or organic word-of-mouth alone. This spatial compression simultaneously triggered a rapid commercial shift in neighbourhood shops toward tourist-oriented goods, erasing local cultural traits and rendering once-unique areas increasingly homogeneous and charmless (Calle-Vaquero et al., 2020). This evidence is sufficiently probative to confirm that digital platforms were the primary driver of spatial imbalance after 2010.
Four straw-in-the-wind tests consistently reinforce the same directional effect and extend it to experiential and behavioural consequences: EB12 documents the explosive growth of “must-photograph” locations driven by user-generated content cascades on Chinese social media platforms (Alonso-Almeida et al., 2019); EB13 and EB14 show how viral mechanics and the rise of “Instagrammable” culture systematically shifted visitor preferences toward highly staged, photo-centric experiences that curtailed exploration of secondary neighbourhoods and produced a measurable decline in dispersal indices (Bourliataux-Lajoinie et al., 2019; Patrichi, 2023); EB33 records the resulting behavioural disruptions, peak-season noise, littering, drunkenness, and prolonged occupation of benches and public squares, particularly by low-cost-airline and cruise-enabled day-trippers following identical platform-generated itineraries (Lashley, 2024).
Although the mechanism relies on one smoking-gun test (EB23) and four straw-in-the-wind tests (EB12, EB13, EB14, EB33) with an average score of 0.70, the unidirectional pattern across independent quantitative, qualitative, and geospatial sources is sufficiently consistent to derive medium-high confidence that digital platforms and social media did not merely mirror demand but actively caused extreme tourist flow concentration, experience homogenisation, and associated behavioural overload. As shown in Figure 3, M3 accelerates in Phase 3 (2001–2010), peaking in Phase 4.
Mechanism 4(M4): Tourism-oriented cultural packaging causes authenticity erosion, social exclusion, and environmental degradation
The causal chain for M4 is the most highly confirmed in the study, resting on four doubly decisive tests that simultaneously affirm the hypothesised pathway and rule out rival explanations. EB7, EB19, EB28, and EB32 collectively demonstrate that deliberate revenue-driven repackaging of heritage and public space, including ticketed access to Gaudí sites, tourist-priority zoning, cruise-port megastructures, and “live-like-a-local” marketing, directly produced measurable loss of everyday authenticity in the historic centre, residential displacement and the formation of tourism-saturated enclaves, social exclusion of lower-income households to peripheral municipalities, and environmental overload, such as Barcelona’s hotels hosting nearly 7.9 million guests in 2014, up from 1.73 million in 1990 (Statista Reasearch Department, 2025b), alongside average rents reaching 15–17 euros per square metre in 2018 (CaixaBank Research, 2019), while explicitly eliminating alternative drivers such as general urban regeneration, demographic ageing, or macroeconomic shocks. EB19 further evidences how residents’ competition for housing and space has seriously compromised social and communal structures, fuelling negative attitudes toward tourism (Elorrieta et al., 2022). EB28 isolates the process of short-term rental-driven gentrification that turns core areas into “tourist-dominated communities,” irreversibly weakening community cohesion (Nieuwland & Van Melik, 2020). EB32 confirms the ecological toll, with overtourism generating about 9.5 million tons of CO₂-equivalent emissions in 2015 and positioning Barcelona (tied with Palma) as Europe’s most polluted port in 2019 due to cruise tourism (Responsible Vacation, 2020). EB21 (smoking-gun) isolates the causal effect of tourism-oriented marketing on residential invasion, documenting the shift from 3S (sun, sea, sand) to 3E (experience, engagement, authenticity) tourism that, fuelled by Airbnb’s “live like a local” campaigns, has occupied residential areas like the Old Town and La Rambla (Żemła, 2020). EB25 (hoop) confirms that systematic reallocation of public resources toward visitor infrastructure, including the privatisation of beaches and prioritisation of tourist transport, was a necessary condition for these outcomes (Milano, 2018).
M4 is therefore derived with the highest average score in the entire analysis: tourism-oriented cultural packaging constitutes the direct and sufficient cause of irreversible authenticity erosion, social exclusion, and environmental degradation in Barcelona. As shown in Figure 3, M4 intensifies during Phases 3–4 (2001–2015), transforming spatial overload into irreversible socioecological impacts that trigger subsequent resistance.
Mechanism 5(M5): Exceeded tourism density and housing costs cause resident resistance and policy pressure
Having crossed critical socio-spatial thresholds through M4’s commodification, Mechanism 5 examines how these impacts endogenously generate organised resident resistance. The causal chain for M5 begins with EB17 (hoop test), which establishes widespread emotional dissatisfaction and perceived loss of neighbourhood identity as a necessary intermediate step in the emergence of organised opposition (González-Reverté, 2022). Three smoking-gun tests then provide decisive evidence of threshold-driven causation. EB8 directly links the post-2014 surge in tourist apartments and visitor density to the formation of neighbourhood assemblies and the outbreak of visible anti-tourism protests, including the widely documented “Tourists go home” campaign of 2016–2017, and its continuation in subsequent years (Hughes, 2018; Rainsford, 2024). EB15 documents an observable discursive shift in resident manifestos and activist platforms from earlier tourism-positive or neutral stances to explicit demands for tourism degrowth and de-commercialisation (Milano et al., 2019). EB18 isolates the negative perceptions generated by tourism-induced gentrification and cultural commodification (M4) as the specific trigger that transformed latent irritation into sustained collective action (Genç et al., 2022).
The evidence chain therefore passes one necessary hoop test (EB17) and three smoking-gun tests (EB8, EB15, EB18). Alternative explanations, such as exogenous ideological radicalisation, general anti-globalisation sentiment, or macroeconomic recession effects, fail to account for both the precise post-2014 timing and the tourism-specific content of the mobilisation. M5 is accordingly derived with a high average: once the socio-spatial impacts produced by M4 crossed residents’ tolerance thresholds, organised resistance and sustained policy pressure became an endogenous and predictable outcome of the cascade rather than an external or purely ideological phenomenon. In Figure 3, M5 marks the pivotal transition in Phase 5 (2016–2017), shifting latent discontent into explicit contention.
Mechanism 6(M6): Governance fragmentation causes ineffective overtourism interventions and broken feedback loops
The policy pressure generated by M5’s resistance exposed deeper institutional barriers, which Mechanism 6 identifies as governance fragmentation. The causal chain for M6 opens with three hoop tests that establish the structural preconditions without which regulatory failure would not have occurred. EB9, EB11, and EB43 jointly confirm that decentralised authority and vertical disconnects, particularly municipal lack of jurisdiction over airports, the port, and high-speed rail gateways, (Goodwin, 2021); long-standing fragmentation in heritage management, exemplified by the absence of unified governance for Gaudí sites since 1984 (C. Jones & Svejenova, 2017); and the inability of local authorities to impose licensing caps or volume controls in key districts (Bei, 2025), were all necessary conditions for systematic intervention collapse. As already evidenced in earlier phases, these governance constraints, particularly the vertical disconnects highlighted in EB11 and the chronic fragmentation in heritage management noted in EB43, represent the intensification of structural issues that originated in the post-Olympic consolidation period (Phase 2) and persisted across subsequent phases.
Four smoking-gun tests then directly link these preconditions to observable policy failure despite intense resident pressure from M5. EB29 documents that the 2017 Special Urban Plan for Tourist Accommodation (PEUAT), despite formal adoption and collaboration with platforms, achieved implementation rates below 50% and failed to reduce overall short-term rental growth or eliminate unlicensed activity (Elorrieta et al., 2022). EB42 shows that strategic plans consistently prioritised growth over resident rights and lacked concrete instruments such as visitor caps or de-marketing (Dodds & Butler, 2019b). EB44 demonstrates that political will to reduce tourist volume remained absent, with multi-level governance fragmentation explicitly identified as the primary barrier to effective intervention (Butler & Dodds, 2022). EB45 provides quantitative evidence that the “Governance” programme of the 2010–2015 Strategic Tourism Plan reached less than 50% execution, rendering the city incapable of adapting to the collaborative economy (Martins, 2018).
Supporting straw-in-the-wind tests (EB16, EB20, EB24) further reinforce chronic coordination deficits, policy inertia—characterised by the prolonged absence of adaptive regulations amid emerging platform accelerators, such as chronic enforcement delays and low coordination pre-2012—and the overriding influence of global capital flows that constrained local regulatory autonomy (Bianchi, 2018; Goodwin, 2017, 2019).
The evidence chain therefore passes three necessary hoop tests (EB9, EB11, EB43) and four smoking-gun tests (EB29, EB42, EB44, EB45). No rival explanation can account for the persistent sub-50% implementation rates across multiple policy cycles and instruments. M6 is accordingly derived with a medium-high average score: governance fragmentation actively blocked the closure of feedback loops generated by resident mobilisation (M5), thereby sustaining the amplification cascade initiated by M1–M4 and delaying meaningful reconfiguration until the 2024–2025 regulatory offensive. As aligned in Figure 3, these constraints originate in Phase 2 and persist through Phases 6 (2018-2019), delaying reconfiguration until the 2024–2025 offensive.
Mechanism 7(M7): Biopolitical erosion drives activism and reconfiguration
By sustaining the cascade through broken feedback, M6 paved the way for the culminating biopolitical erosion examined in Mechanism 7. The causal chain for M7 begins with EB30 (hoop test), which establishes a governance approach focused on profit and avoiding political debate and depoliticisation, prioritising capital accumulation and postpolitical consensus over democratic deliberation and degrowth alternatives, as a necessary precondition for tourism’s deepening socio-spatial exclusion (Novy & Colomb, 2019). Six smoking-gun tests then provide decisive evidence of the mechanism’s culmination and reconfiguration phase. EB35, EB36, EB37, and EB38 show that combining mass tourism with pandemic-era measures, like health passes, tracking apps, restricted access zones, and stratified mobility controls that privilege tourist flows over resident autonomy, inflicted systemic harm on everyday urban life. This included weaker civic rights, loss of shared public spaces, and reduced community ties, as people moved in separated ways under new tourism-related controls (Minca, 2025; Munar & Ek, 2022; Roelofsen & Minca, 2023; Tesfahuney & Ek, 2024). These outcomes are underscored by the prevalence of “Tourism kills the city” graffiti and the temporary restoration of inclusive public space during the 2020–2021 near-total tourist absence, a reversal that reflects not just pandemic effects, but the pre-existing biopolitical capture of urban space by tourism capitalism shaped by M1–M6.
The reconfiguration phase is confirmed by two additional smoking-gun tests (EB39, EB40), marking a coordinated institutionalised reversal of biopolitical erosion. EB39 documents that in March 2025, Spain’s Constitutional Court upheld Barcelona’s municipal plan to phase out all short-term tourist apartment licenses by 2028, dismissing appeals on property rights grounds, while in May 2025, the Consumer Rights Ministry ordered the removal of over 65,000 non-compliant Airbnb listings nationwide for lacking license numbers or ownership details (Reuters, 2025a, 2025b). These 2025 regulatory developments are based on policy trajectory analysis. Limitations include potential delays in implementation due to industry litigation or changes in regional government priorities. EB40 provides enforcement data showing that since 2016, Barcelona has issued over 11,500 fines and nearly 11,600 cease-and-desist orders, reducing detected active illegal flats from approximately 6,000 to an average of 300 per month and recovering nearly 4,000 units for residential use (Ajuntament de Barcelona, 2022, 2025). These state-level interventions, prompted by resident mobilisation (M5), institutionalise the pandemic’s temporary spatial redress into enduring governance reforms that reclaim urban space from platform-mediated biopolitical capture.
The evidence chain therefore passes one necessary hoop test (EB30) and six smoking-gun tests (EB35-EB40). Alternative explanations, such as isolated economic recovery, exogenous judicial activism, or pandemic-specific ephemera, fail to account for the sequential integration of pre-existing erosion with post-2024 enforcement outcomes. M7 is accordingly derived with the highest average score in the analysis: the buildup of problems from earlier mechanisms created a crisis in city community life, while the pandemic provided a critical juncture to catalyse structured, rights-based reconfiguration via 2024–2025 regulatory and enforcement actions. In Figure 3, M7 culminates in Phase 7 (2020–2025), revealing both crisis depth and contested windows for structural reversal.
Historical Phases of Overtourism Escalation in Barcelona (1986–2025)
Figure 3 further illustrates the process tracing evolution of these mechanisms in Barcelona across seven chronologically sequential phases from 1986 to 2025. Each phase is defined by the cause, effect, and seven causal mechanisms. The vertical continuum distinguishes two polar states of tourism status. Following Blázquez-Salom et al. (2023), Gowreesunkar and Vo Thanh (2020), undertourism is operationalised as a persistent condition in which tourist arrivals, overnight stays, and associated economic activity remain durably below the destination’s ecological, social, physical, and economic carrying capacities. This results in under-utilised infrastructure, limited tourism-related employment, and broad political support for growth-oriented strategies. Overtourism, in contrast, occurs when arrivals and their spatial concentration durably exceed multiple dimensions of carrying capacity, thereby generating negative externalities that include housing unaffordability, loss of urban authenticity, resident displacement, environmental degradation, and widespread tourismphobia (Koens et al., 2018; Milano et al., 2019). Figure 3 documents Barcelona’s transition from pronounced undertourism in the pre- and immediate post-Olympic years to acute overtourism within a single generation.
Phase 1 (1986–1991) was initiated by Olympic-driven urban regeneration, which activated a mechanism of infrastructure lock-in and established long-term dependency on tourism. Building on this foundation, Phase 2 (1992–2000) consolidated the trajectory through post-Olympic expansion, where governance failures enabled unregulated market growth, resulting in housing pressures and labor market distortions. This path-dependent dynamic was further intensified in Phase 3 (2001–2010) by the rise of digital platforms and social media, which triggered a mechanism of platform-mediated acceleration, concentrating tourist flows and producing spatial congestion alongside experiential homogenisation. As commodification deepened, Phase 4 (2011–2015) saw tourism-oriented heritage management erode local authenticity and displace residents through a mechanism of cultural packaging. These cumulative socio-spatial stresses eventually exceeded the limits of resident endurance, leading to Phase 5 (2016–2017), wherein organised resident resistance emerged as a collective response, transforming diffuse discontent into explicit political demands. In reaction, Phase 6 (2018–2019) introduced regulatory efforts that were nonetheless undermined by institutional fragmentation, resulting in ineffective governance and persistent policy incoherence. Finally, Phase 7 (2020–2025) unfolded amid a pandemic-induced crisis that temporarily disrupted the tourism regime, catalysing biopolitical reconfiguration and prompting contested attempts at systemic reorientation. Together, these seven phases illustrate a self-reinforcing escalation from initial tourism-led regeneration to systemic socioecological crisis, wherein amplifying mechanisms consistently outpaced adaptive capacity until an exogenous shock opened a narrow window for structural intervention.
Mechanism Validation: Bayesian Updating
To strengthen the rigour and transparency of the causal inferences, each of the seven hypothesised mechanisms was subjected to systematic process-tracing tests following Beach and Pedersen (2019) and Bennett and Checkel (2015). Posterior probabilities were calculated iteratively using Bayesian confidence updating. We adopted a neutral prior of 0.5, expressing genuine pre-evidence equipoise.
Table 3 synthesises the validation results for seven proposed mechanisms (M1–M7) by documenting the quantity of evidentiary units, types of key tests passed, and final conclusions. Across all mechanisms, the number of evidentiary units ranges from 4 (M5) to 10 (M6), indicating variation in data availability but consistent adherence to the study’s evidence standards.
Summary of Mechanism Test Results: Evidentiary Support and Conclusions.
Assume a mechanism M, with prior probabilities P(M) = 0.5 and P(M’) = 0.5 for it being true or false, respectively. There are four types of evidence: hoop evidence E1, smoking-gun evidence E2, straw-in-the-wind evidence E3, and doubly decisive evidence E4. All evidence types are assumed to be independent given the mechanism M.
In reality, the evidence is not absolutely reliable, even though the collected evidence comes from government reports, journal papers, and social media posts. The conditional probabilities are set as follows:
The Bayesian posterior probability formula is:
It can be seen that when smoking-gun evidence or doubly-decisive evidence appears in the evidence set, P(E2|M’) = 0.05, P(E4|M’) = 0.05, the posterior probability directly approaches 1, meaning the mechanism M is considered established.
In terms of key tests, a core component of the study’s causal identification strategy, all mechanisms passed a combination of hoop, smoking-gun, straw-in-the-wind, or doubly decisive tests. Notably, M4 is distinguished by passing four doubly decisive tests, supplemented by one smoking-gun test and one hoop test; M7 exhibits the highest number of six smoking-gun tests, paired with one hoop test, reflecting strong causal evidence; meanwhile, straw-in-the-wind tests provide supplementary contextual support, while hoop tests ensure adherence to necessary causal conditions.
Consistent with the Bayesian posterior probability framework, all seven mechanisms are “Confirmed.” This outcome stems from smoking-gun or doubly decisive tests, which, per the study’s logic, elevate the posterior probability of mechanism validity to near certainty.
Macro Data-Driven Empirical Examination
To rigorously ground the causal mechanisms in macro-level realities and provide robust quantitative corroboration for the qualitative process-tracing evidence, we realign the key indicators from Table 4, drawing on longitudinal data spanning 1990–2024, with the seven validated mechanisms. This analysis relies exclusively on data from the Statista Research Department, which aggregates figures from authoritative primary sources including Spain’s National Statistics Institute (INE), Eurostat, and the United Nations World Tourism Organization (UNWTO). Since all indicators are traceable to their original official statistics, this approach ensures the reliability, transparency, and replicability essential for rigorous causal mechanism testing.
Key Macro-Level Trends in Barcelona’s Tourism and Housing Sectors.
Source. Statista Research Department (2025c).
First, the data provide definitive confirmation of M1, the mega-event infrastructure lock-in. The trajectory of fixed assets demonstrates a clear path dependency originating from the 1992 Olympic investments. As shown in Table 4, hotel room supply did not merely grow but nearly quadrupled from 10,265 rooms in 1990 to 38,733 in 2019, continuing to rise to 39,776 in 2024. This infrastructure expansion drove a parallel surge in capacity utilisation. Hotel overnight stays increased from 3.796 million in 1990 to a peak of 19.852 million in 2019, reaching 20.159 million in 2024. Furthermore, cruise infrastructure lock-in is evident in passenger volumes exploding from 0.115 million in 1990 to 3.656 million in 2024, having peaked at 3.138 million in 2019. These figures illustrate that the initial mega-event investment created a self-reinforcing cycle of capacity expansion that persists decades later, validating the lock-in hypothesis of M1.
Second, the quantitative trends validate M2, regulatory gaps enabling unregulated short-term rental growth, and M4, cultural commodification leading to housing distortion. The data reveals an explosive divergence between traditional hospitality and the unregulated short-term rental sector. While short-term rentals were negligible in earlier decades with only 2,349 listings in 2010 across the Barcelona province, they skyrocketed to 18,157 listings in 2024. This massive injection of tourist-oriented supply correlates directly with housing market distortion. The average housing price per square metre climbed steadily from €1,050 in 1990 to €4,569 in 2024, with significant acceleration post-2010 as prices rose from €2,537 to €4,000 by 2019. The simultaneous exponential rise in short-term rental listings, which grew by 673% from 2010 to 2024, and housing prices, which increased by 80% over the same period, provides empirical evidence that regulatory gaps allowed residential stock to be commodified for tourist use. This dynamic directly drove the affordability crisis and eroded local authenticity, central tenets of M2 and M4.
Third, the macro indicators offer precise temporal evidence for M5, resident resistance triggered by exceeded carrying capacity. The data pinpoints a specific threshold of social tolerance. Resident perception of tourism as the main problem of the city remained marginal at less than 0.9% through 2010, even as visitor numbers grew. However, as tourism intensity peaked—evidenced by the 2019 highs in overnight stays at 19.852 million and air passengers at 52.69 million—resident discontent surged dramatically to hit a peak of 15.6% in 2017. This lagged but sharp reaction confirms the M5 hypothesis that resistance is not linear but triggers only after carrying capacity is exceeded. The subsequent decline to 5.4% in 2024, despite record-high visitor numbers of 20.159 million overnight stays, suggests that the resistance threshold was breached and has since been managed or reconfigured rather than the pressure itself disappearing.
Finally, the data corroborate M7: biopolitical erosion and subsequent reconfiguration. The economic metrics demonstrate the ability of the city to decouple economic gain from social strain. The share of employment in tourism peaked at 12.8% in 2019 and stabiliSed at 11.6% in 2024, while its contribution to GDP remained robust at 14% in 2024. Crucially, while economic indicators remained high or recovered to near-peak levels in 2024, the social indicator measuring residents who view tourism as a problem dropped from its 2017 peak of 15.6% to 5.4%. This divergence, characteriSed by sustained high economic output with a recorded contribution of €10.375 billion and a 14% share alongside reduced social friction, illustrates the reconfiguration described in M7. The city has successfully retained the biopolitical benefits of tourism revenue while mitigating the acute strain on urban life that defined the 2017 crisis.
By aligning the specific data points from Table 4 with each mechanism, this analysis eliminates ambiguity. The sequential amplification is clear. M1 built the capacity, M2 and M4 converted housing stock to meet demand, M5 triggered a social breaking point in 2017 when capacity limits were reached, and M7 represents the current state where economic benefits are maintained through 2024 employment and GDP figures, while social resistance has subsided from its peak.
Discussion
Deriving the Cascade Amplification Framework From the Validated Causal Chain
The seven mechanisms identified in Section 4, while having evolved historically, are bound by a tight internal logic. Process-tracing and Bayesian updating (Tables 2–3) reveal their interrelationships not as isolated events, but as sequential stages in a coherent causal chain. This chain exhibits a consistent pattern: foundational structural commitments create systemic vulnerabilities; these vulnerabilities are then exponentially amplified by contemporary technological and regulatory accelerators; the amplified pressures breach socio-spatial and ecological carrying capacities, triggering direct impacts and resident resistance; ineffective governance due to institutional fragmentation entrenches these impacts by blocking corrective feedback; ultimately, this cascading process culminates in a biopolitical crisis that threatens the foundations of urban democracy and livability.
We therefore inductively derive the CAF by grouping the seven validated mechanisms (M1–M7) into five interconnected layers, each representing a distinct stage in this amplification process (see Figure 4):
The cascade amplification framework: Empirically derived layers and causal linkages.
Root layer (M1)
This foundational layer comprises the historically contingent structural commitments, specifically, mega-event infrastructure and accessibility lock-in, which established the necessary preconditions and path-dependent origins for long-term tourism dependency.
Amplification layer (M2 & M3)
This layer captures the exponential intensification of root-layer vulnerabilities through external accelerators. It combines governance failures enabling unregulated short-term rentals growth (M2) with digital platforms that concentrate and homogenise tourist flows (M3), a dynamic starkly evidenced by the post-2010 compression of visitor growth and spatial concentration.
Impact layer (M4 & M5)
This layer encompasses the direct, observable socio-spatial and ecological consequences of exceeding carrying capacities. It includes the erosion of authenticity and environmental degradation from cultural commodification (M4) and the resident resistance fuelled by overcrowding and housing unaffordability (M5), which together generate endogenous pushback against the system.
Barrier layer (M6)
This layer denotes the institutional barriers that systemically entrench the cascade. Governance fragmentation (M6) renders interventions ineffective and severs critical feedback loops, preventing systemic correction and allowing impacts from lower layers to persist and intensify.
Reconfiguration layer (M7)
This layer captures biopolitical erosion as the systemic outcome, wherein a localised tourism issue escalates into an existential crisis for the urban community. As the foundations of democratic civic life erode, they catalyse grassroots activism and broader socio-political reconfiguration.
These layers are intrinsically linked, forming a tight logical sequence.
Overall, these relationships portray overtourism as a non-linear, feedback-driven system that extends Russo’s (2002) “vicious circle” by incorporating 21st-century accelerators, digital platforms (Guttentag, 2015), and biopolitical restructuring (Tesfahuney & Ek, 2024). Early institutional commitments generate vulnerabilities that later responses cannot fully reverse without fundamental systemic change, as the brief pandemic “redress” ultimately demonstrated.
Theoretical and Practical Implications
Theoretical Implications
This research contributes to tourism studies in several significant ways. First, it introduces a rigorous longitudinal application of process tracing combined with Bayesian updating and Collier’s (2011) diagnostic tests to the study of overtourism. This offers a replicable, transparent methodology for establishing causal claims in historically embedded, non-linear urban phenomena, moving beyond traditional qualitative case studies and providing a structured template for other complex tourism and urbanisation processes.
Second, the study empirically validates a dynamic, multi-stage causal chain of overtourism in Barcelona from 1986 to 2025, identifying seven sequentially interacting mechanisms from infrastructural lock-in to biopolitical erosion. By specifying their cumulative interplay under neoliberal urbanisation, it challenges singular-factor explanations and extends Russo’s (2002) “vicious circle” model through the integration of platform capitalism and governance fragmentation, key drivers of modern overtourism absent from the linear “success-erosion” loop. Moreover, the CAF incorporates digital accelerators that redefine tourist flow dynamics beyond the TALC’s traditional stage-based logic. While Milano and colleagues’ (2024) focus on inequalities and asymmetrical power relations lacks actionable policy translation, the CAF enhances this perspective by operationalising abstract systemic critiques into actionable diagnostic layers and identifying phase-specific intervention points tailored to a destination’s position in the overtourism cascade.
Third, drawing on the proposed Cascade Amplification Framework, overtourism is conceptualised as a nonlinear, path-dependent systemic process characterised by sequential intensification. Beyond a robust explanatory model, the framework serves as a structured, multi-tiered heuristic for policymakers, delineating phase-specific interventions. This necessitates a paradigm shift away from pursuing “more tourists equals better economics” toward diagnosing and reinforcing critical systemic nodes, such as governance fragmentation and the recursive amplification effects of digital platforms.
Unlike conventional governance that often relies on isolated, technical fixes, the CAF identifies the breakdown of institutional feedback loops, wherein signals such as resident protests fail to translate into policy adaptation, as a core mechanism of systemic failure. Effective intervention, therefore, must institutionalise adaptive feedback channels, integrating continuous data monitoring with automated policy triggers and formalising citizen deliberation into the policy revision cycle.
Additionally, the framework re-conceptualises digital platforms not as passive tools but as active agents in the production of tourist space, centralising technology within the causal chain. Consequently, policy must evolve beyond mere regulation toward co-opting technological affordances for governance purposes, such as leveraging real-time data-sharing and algorithmic collaboration for dynamic visitor dispersion.
The five-layer architecture of the CAF provides a diagnostic matrix for urban self-assessment, enabling cities to identify their specific position within the cascading sequence and thereby preventing policy mismatch, such as deploying infrastructure-centric solutions when the systemic challenge has already progressed to sociopolitical impacts.
Ultimately, the CAF reframes overtourism as a fundamental tension between capital accumulation in tourism and the preconditions for urban democratic life. This elevates the issue beyond tourism studies, situating it within broader interdisciplinary debates in political ecology, urban geography, and democratic theory. It underscores that sustainable tourism is contingent upon deep structural reforms in urban governance models.
Practical Implications
While the CAF is empirically grounded in Barcelona’s historical trajectory from 1986 to 2025, it is designed not merely as a retrospective explanatory model but as a forward-looking diagnostic and prescriptive tool. Informed by the CAF’s diagnostic logic, effective policy interventions should adopt a principled approach of layered governance and dynamic adaptation, implementing targeted measures across each sequential stage. At the root layer, mandate ex-ante Tourism Carrying Capacity Impact Assessments and diversify industrial pathways in major infrastructure planning. Establish Tourism Revenue Sharing Funds to mitigate structural economic dependency. Enact data-driven, dynamic regulation of short-term rentals and digital platforms at the amplification layer. Implement smart licensing systems with real-time capacity controls and mandate platform data-sharing to enable algorithmic visitor dispersion and content authenticity labelling.
At the impact layer, institute multi-dimensional early-warning systems based on community indicators. Formalise mechanisms to integrate resident dissent and protest into policy feedback loops, such as through permanent “Tourism Governance Citizen Assemblies.” Foster resilient, polycentric governance architectures to overcome fragmentation at the barrier layer. Establish a cross-sectoral, empowered oversight body, and implement policy coherence assessments to eliminate contradictory measures across departments. At the Reconfiguration layer, elevate tourism governance to an issue of spatial justice and urban rights. Advance participatory budgeting and planning, legislate “Tourism Recess Periods” for socio-ecological recovery, and pilot “degrowth” tourism models based on well-being indicators rather than arrival metrics.
Although the CAF is empirically derived from Barcelona as a paradigmatic case, its core mechanisms exhibit strong parallels in other heritage-intensive European cities facing comparable pressures from platform capitalism, low-cost mobility, and concentrated cultural assets. For instance, Venice shares infrastructure lock-in through cruise terminal dependencies and digital amplification of visitor flows, alongside severe housing displacement driven by short-term rentals (Gibson, 2021). Amsterdam demonstrates similar regulatory gaps enabling platform-mediated gentrification, digital concentration at iconic sites, and resident resistance manifesting in anti-tourism protests (Yuval, 2022). These shared dynamics, evident in multi-city comparative studies and rankings, underscore the CAF’s transferability to neoliberal, heritage-dominant contexts, while highlighting context-specific variations, such as Venice’s heavier reliance on cruise tourism versus Barcelona’s blended aviation, cruise, and platform pressures. Parallels can be drawn to non-Western cities such as Kyoto, where digital amplification and resident resistance are evident (Duignan et al., 2022), and Mexico City, where cultural commodification appears transferable (Sánchez-Aguirre et al., 2025). However, mechanisms like multi-scalar governance fragmentation may be less applicable in state-led economies, such as those in parts of Asia, highlighting the need for context-specific adaptations.
Conclusively, the CAF champions a “resilience governance” paradigm. It re-conceives the city as a complex adaptive system, where the goal shifts from controlling tourist numbers to enhancing the system's inherent capacity to withstand, absorb, and transform the shocks induced by overtourism. This framework offers a transferable model for systemic risk management, extending its relevance beyond tourist cities to any resource-dependent urban context. By diagnosing a destination’s position within the five-layer cascade, the CAF enables policymakers to move from reactive crisis management to proactive interruption, targeting root lock-in before digital amplification turns structural vulnerabilities into irreversible biopolitical erosion.
Conclusion and Future Research Directions
Conclusion
This study demonstrates that Barcelona’s evolution from a celebrated post-Olympic regeneration model to one of the world’s most emblematic cases of overtourism is neither an inevitable decline nor a mere failure of destination management. Rather, it is the historically contingent outcome of seven sequentially interacting causal mechanisms within a neoliberal urbanisation framework. The 1992 Olympic Games served as a critical juncture, embedding tourism as the city’s dominant growth vector (Degen & García, 2012), with the mid-2010s crisis intensified by context-specific amplifiers: rapid platform-mediated housing financialisation (Cocola-Gant & Gago, 2021), multi-scalar governance fragmentation placing airports and cruise terminals beyond municipal jurisdiction (Goodwin, 2021), and an unusually high concentration of the United Nations Educational, Scientific and Cultural Organization (UNESCO)-inscribed heritage assets that spatially concentrates visitor pressure (UNESCO, 2024).
Barcelona’s overtourism emerges as the contingent result of these seven validated mechanisms under neoliberal urbanisation, derived from 45 evidentiary units via process-tracing and Bayesian updating. The CAF synthesises them into a five-layer diagnostic model, extending earlier cyclical theories by capturing a compressed, feedback-driven spiral of the platform and mobility era. Specifically, the CAF enhances Butler’s (1980, 2025) tourism area life cycle model with platform-driven acceleration; refines Russo's (2002) “vicious circle” framework through hierarchical feedback loops; and operationalises Milano and colleagues’ (2024) systemic critiques via diagnostic tools. As both an explanatory model and governance instrument, the CAF enables proactive interruption of overtourism cascades in heritage cities.
Crucially, the longitudinal evidence of severe socio-spatial impacts also reveals opportunities for stakeholder agency and policy learning. For instance, the near-total absence of tourists in 2020–2021 acted as a temporary “redress,” showing that urban livability and democratic public space can be rapidly restored when tourism flows are disrupted (Tesfahuney & Ek, 2024).
The CAF thus serves as a forward-looking diagnostic tool rather than a universal model. By helping policymakers identify active mechanisms and layers, anticipate rebound dynamics, and design targeted, multi-layer interventions, it offers a transferable resource for other heritage cities to preserve urban democracy and cultural sovereignty amid platform-driven tourism. In essence, the CAF promotes proactive strategies for sustainable tourism.
Limitations and future research directions
Although the Cascade Amplification Framework offers a robust, historically grounded explanation of overtourism in Barcelona, three deliberate limitations of the present study open clear directions for future scholarship.
First, given the near-40-year timespan (1986–2025), certain indicators, most notably tourist arrivals and overnight stays, are affected by changes in statistical definitions and data-collection methods over time. While we mitigated this risk through source triangulation, context-aware coding, and a focus on relative trends rather than absolute figures, minor measurement inconsistencies cannot be entirely ruled out. This constitutes an inherent limitation of long-term secondary-data analysis. Future research could further enhance cross-temporal comparability by constructing harmonised panel datasets or complementing secondary sources with primary longitudinal surveys.
Second, we fully acknowledge that the single-case design is a limitation in terms of immediate generalisability. The findings are necessarily embedded in Barcelona’s unique post-Franco democratic transition, Olympic-driven regeneration, and specific multi-level governance structure. We explicitly note that the CAF framework’s external validity is strongest for heritage cities in liberal market economies with comparable institutional arrangements, such as Venice, Amsterdam, Lisbon, and Dubrovnik (Koens et al., 2018; Novy & Colomb, 2019). Applicability to cities in the Global South, Asia, or different welfare or regime contexts, requires further comparative testing. Although cross-case process tracing is possible and sometimes used to test mechanism portability (Bennett & Checkel, 2015), our research question focuses on the sequential, path-dependent amplification within one extended trajectory; adding multiple cases would dilute the fine-grained temporal evidence required to validate the seven mechanisms and derive the five-layer Cascade Amplification Framework. We therefore view this as an initial step, and future multi-case studies will be essential to refine and broaden the framework’s scope.
Third, the seven-mechanism, five-layer architecture of the CAF, while theoretically necessary for explanatory depth, sacrifices parsimony and may initially limit practitioner uptake. Future research should develop and pilot-test simplified operational versions, such as early-warning indicator dashboards or modular “CAF-Lite” toolkits, in collaboration with municipal planning departments.
Taken together, these extensions will refine the framework’s applicability, enhance its practical utility, and transform the CAF from a Barcelona-centred explanatory model into a globally relevant instrument for sustainable destination governance in the platform era.
Footnotes
Funding
The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Financial support from Spain Ministry of Science, Innovation and Universities and the Chinese Government Scholarship are gratefully acknowledged.
Declaration of Conflicting Interests
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.