Sage Journals: Discover world-class research

Abstract

Overtourism increasingly threatens resident wellbeing and destination sustainability. While existing research essentially prioritizes regulatory or infrastructural solutions, this study reconceptualizes marketing as a behavioral governance system, a coordinated mechanism of communication, technology, and policy that shapes tourist decision making toward sustainable outcomes. Drawing on a narrative review of 72 peer-reviewed studies published between 2017 and 2025, the analysis identifies 10 strategic categories, including demarketing, geographic diversification, digital engagement, brand repositioning, and visitor education. The study introduces two complementary models: (1) a diagnostic map that traces the evolution and distribution of marketing-based overtourism strategies and (2) a behavioral governance framework linking marketing interventions to cognitive and affective mechanisms—such as persuasion, emotional engagement, identity alignment, and norm activation—that influence tourist behavior. Findings show that marketing can produce temporal (when tourists travel), spatial (where they go), and experiential (how they engage) shifts that collectively strengthen destination resilience and sustainability. By consolidating dispersed insights into a unified behavioral perspective, the study clarifies marketing's role as a governance tool. It provides a foundation for more effective, evidence-based approaches to sustainable destination management.

Keywords

Overtourism sustainability marketing strategies narrative review strategic branding

Introduction

Worldwide, many famous tourist destinations are increasingly facing overtourism—a problem that endangers environmental health and the wellbeing of local communities. This issue manifests as crowded public spaces, environmental damage, housing shortages, and declining resident satisfaction, all caused by too many visitors exceeding the location's capacity (Koens et al., 2018; Peeters et al., 2018). Cities like Venice, Barcelona, and Kyoto highlight the rising conflict between local needs and the demands of the global tourism industry. The excessive concentration of tourist traffic leads to overcrowding in popular destinations, over-advertising, and aggressive commercialization, which diminishes the aesthetic quality of tourists’ experiences and degrades natural and cultural resources (Szromek et al., 2020).

Several structural and technological factors have sped up this trend. Increasing air connectivity and the growth of low-cost carriers have changed travel patterns, while digital platforms have boosted global access to destinations (Lawton, 2017). Platforms like Airbnb have disrupted housing markets, leading to gentrification, higher living costs, and the “theme parkification” of residential neighborhoods (Gravari & Barbas, 2017; Guttentag, 2015; Madeira et al., 2021). Even in “smart” destinations, technological solutions alone have proven inadequate, as visitors still struggle to manage congestion and spatial constraints (Milano et al., 2019).

Among the proposed solutions, marketing-based approaches have received increasing scholarly attention. Unlike regulatory tools, marketing strategies offer flexible, behaviorally informed approaches that influence when, where, and how people travel—helping destinations manage visitor flows while promoting sustainable growth. Tourism marketing, when designed not only to attract visitors but also to support long-term sustainability goals, includes tactics such as destination branding, market segmentation, off-peak promotions, and community-based product development. However, despite their growing use, there remains a significant gap in understanding how effective these strategies are at reducing overtourism. While digital campaigns, branding repositioning, and alternative destination promotion are now common, the use of advanced technologies such as real-time data, Artificial Intelligence (AI)--driven personalization, and geospatial marketing remains underexplored (Dredge, 2017).

This study aims to systematically review the range of marketing strategies proposed in the academic literature for managing overtourism, identify successful interventions, highlight ongoing gaps, and outline future opportunities for innovation. The key research question is: How can marketing serve as a behavioral governance system to prevent or reduce overtourism? To address this question, the article advances both theory and practice in sustainable destination management. It combines fragmented insights by creating two complementary models: a diagnostic map of scholarly trends across ten strategic categories, and a behavioral governance framework that shows how marketing interventions affect overtourism through cognitive, affective, and systemic mechanisms. Given that marketing-based responses to overtourism have emerged only recently in academic discourse, the study also emphasises the importance of publication recency to ensure that the synthesis reflects contemporary strategic thinking and the most current developments in destination management.

Literature review: Concepts and theoretical background

Overtourism and marketing-based interventions management

Overtourism occurs when the number, intensity, or spatial clustering of visitors exceeds a destination's ecological capacity and local communities’ social tolerance, leading to cumulative negative impacts on the environment, culture, and residents’ quality of life (Koens et al., 2018; Milano et al., 2019). However, beyond numbers, overtourism is primarily a behavioral and perceptual issue—it arises when residents perceive that tourism growth threatens their wellbeing, sense of identity, or sense of place. Therefore, overtourism cannot be explained solely by visitor counts; it also depends on how tourism is distributed, managed, and experienced (Séraphin et al., 2019). Additionally, Mihalic (2020) notes that the development of overtourism involves increasing tourism supply and demand, the overuse of natural resources, and damage to cultural and social environments.

From a governance perspective, overtourism signals a systemic misalignment among destination marketing, spatial planning, and sustainability policies (Butler & Dodds, 2022). It reflects a failure to coordinate demand stimulation with capacity management, with marketing continuing to attract visitors while planning does not sustainably accommodate them. Recent studies (Peeters et al., 2019; Oklevik et al., 2019) emphasize that marketing can serve as both a preventive and corrective tool. Strategic marketing enables destination management organizations (DMOs) to influence tourist demand through branding, communication, segmentation, and digital engagement.

Building on the review of studies, marketing-based interventions to manage overtourism can mainly be categorized into three types—preventive, reactive, and hybrid (adaptive) strategies—each serving a different but related role in sustainable destination management (Hall and Wood, 2021; Lew et al., 2016; Pasquinelli and Trunfio, 2020).

Preventive strategies operate proactively, aiming to influence tourism demand before travel decisions are made by shaping visitor motivations, destination selection, and timing. These strategies actively redirect flows through sustainable branding, demarketing, geographic diversification, high-value targeting, and education or awareness campaigns. By emphasizing ethical travel, authenticity, and environmental responsibility, preventive marketing encourages visitors to choose off-peak or alternative destinations—such as the “Norway, powered by nature” campaign, which promotes low-impact, nature-based experiences (Bouchon and Rauscher, 2019). Preventive measures thus serve as the first line of defense, addressing potential crowding before it occurs.

Reactive strategies, by contrast, are implemented after overtourism pressures have already emerged. These strategies aim to reduce immediate negative impacts through real-time crowd management apps, dynamic pricing, visitor caps, and influencer collaborations that encourage responsible behavior (Camatti et al., 2020; Espinet-Rius et al., 2024). For example, Venice's Smart Control Room system uses live sensor data to track visitor density and send alerts to both officials and tourists, helping to balance flow in real time (Remenyik et al., 2021). Such measures are essential for short-term crisis management and maintaining operational resilience.

Finally, hybrid or adaptive strategies combine preventive and reactive elements to enhance long-term destination resilience. These methods focus on flexibility, tech integration, and stakeholder collaboration—merging AI-driven personalization, smart destination marketing, community co-branding, and event repositioning (Hall and Wood, 2021; Lew et al., 2016). Kyoto's “Respect Kyoto” initiative exemplifies this by blending visitor education with on-site digital guidance tools, encouraging behavioral change while ensuring visitor satisfaction (Oklevik et al., 2019). Thus, hybrid strategies mark the evolution of overtourism management—from short-term fixes to adaptive learning systems that can sustain tourism within ecological and social boundaries.

This categorization provides conceptual clarity and a structured framework for understanding how various marketing tools address the temporal, spatial, and behavioral dimensions of overtourism.

Theoretical underpinnings

Since effective management of overtourism through marketing requires a strong theoretical foundation that explains how marketing interventions shape tourist behavior, destination perceptions, and long-term sustainability outcomes, this study integrates several complementary perspectives—including behavioral, cognitive, and systems theories—to create a multilevel conceptual basis for the proposed approach.

At the micro level, the Theory of Planned Behavior (Ajzen, 1991) offers a cognitive explanation of how marketing messages influence individual decision making. In the context of overtourism, these mechanisms show how marketing can influence tourist choices. Demarketing efforts can change attitudes by associating overcrowded destinations with lower experience quality; influencer stories can shape subjective norms that encourage responsible and ethical travel; and digital tools—such as mobile apps that recommend visits during off-peak times—can enhance perceived control by enabling tourists to make sustainable choices. Therefore, marketing not only shares information but also guides behavior.

At the meso level, the Destination Image Theory (Gartner, 1993) and Destination Positioning Models (Pike and Ryan, 2004) show how communication strategies shape collective perceptions and influence demand flows. Destination choice depends not only on objective features but also on the perceived image, which combines cognitive (knowledge-based), affective (emotional), and conative (behavioral) components. Marketing campaigns that emphasize authenticity, community involvement, or cultural uniqueness can therefore help balance visitor flows and reduce crowding pressures by affecting these perceptual elements.

At the macro level, Sustainable Marketing Theory (Belz and Peattie, 2009) and the Triple Bottom Line framework (Elkington, 1997) provide the ethical and strategic perspectives for aligning tourism marketing with sustainability goals. Traditional tourism marketing emphasizes growth and visibility, while sustainable marketing redefines success as impact optimization rather than simply increasing visitor numbers.

Beyond individual and perceptual models, the Place–Visitor Relationship (PVR) framework provides an interpersonal and relational lens for understanding how marketing influences sustainable behavior. Originating in the Organization–Public Relationship theory in public relations (Bruning and Ledingham, 1999), PVR conceptualizes the destination–visitor relationship as a multidimensional connection grounded in trust, commitment, satisfaction, and mutual control (Hon and Brunner, 2002; Ki & Hon, 2007). When marketing emphasizes authenticity, community wellbeing, and co-created value, it strengthens relational trust and commitment, thereby reducing alienation, dissatisfaction, and irresponsible behavior—key drivers of overtourism (Conze et al., 2010; Vogt, 2010).

From this perspective, managing overtourism is not only about demand regulation but also about relationship cultivation: fostering long-term, mutually beneficial bonds between places and visitors that reinforce sustainable engagement and ethical travel norms.

Finally, Resilience Theory (Folke, 2006; Lew et al., 2016) conceptualizes overtourism as a symptom of maladaptive growth, where demand outpaces the destination's social and ecological capacity. Marketing interventions function as adaptive tools within this system: preventive strategies (e.g. sustainable branding) support proactive capacity alignment, while reactive measures (e.g. digital crowd-management tools) facilitate immediate recovery. Hybrid approaches integrate both to enhance long-term destination resilience.

Methodology

This qualitative narrative literature review used an inductive–abductive thematic analysis to identify and categorize marketing strategies related to overtourism. A narrative review approach was selected because it is well-suited to synthesizing heterogeneous and interdisciplinary bodies of knowledge—such as tourism management, consumer psychology, sustainability, and digital innovation—where the aim is conceptual integration rather than statistical aggregation (Greenhalgh et al., 2005; Snyder, 2019). This approach enables an interpretive synthesis of diverse empirical and conceptual studies and is appropriate for emerging research areas where theoretical and methodological fragmentation is expected.

A thorough search was performed in Scopus (15 February 2025), selected for its extensive coverage of peer-reviewed literature in tourism and marketing. A Boolean search query was created to find articles at the intersection of overtourism and advanced or strategic marketing practices.

Search Query Used: TITLE-ABS-KEY(demarketing OR “de marketing” OR advertis* OR market*) OR TITLE-ABS-KEY(robot* OR “block chain” OR “big data”) OR TITLE-ABS-KEY(”social media” OR insta* OR tiktok OR influencer*) OR TITLE-ABS-KEY (brand OR branding OR “de branding” OR rebranding OR repositioning) And TITLE-ABS-KEY (overtourism).

Finally, it selected peer-reviewed journal articles published from 2017 to 2025 (as no relevant studies were found prior to 2017) that explicitly address overtourism with a marketing or strategic communication focus. Only peer-reviewed journal articles were included for methodological transparency and reproducibility. Industry reports and grey literature were excluded due to the absence of a systematic methodology and potential bias. Exclusion criteria included nonacademic studies, reports, and articles lacking methodological clarity.

A modified PRISMA process guided the identification, screening, eligibility, and inclusion stages (Figure 1). The search initially identified 112 studies. After reviewing titles and abstracts, 83 studies remained. The full-text evaluation yielded 72 articles that met the criteria.

Figure 1.

Prisma diagram.

The thematic coding process included two stages—open and axial coding—and was validated through cross-checking by two researchers to ensure consistency. This process resulted in 10 strategy clusters. After completing the two-stage thematic coding, identifying recurrent themes, and clustering them into strategic categories, the themes were grouped into 10 major strategy clusters, such as sustainable branding, influencer-driven campaigns, demarketing, high-value targeting, and technology integration. Finally, the identified themes were mapped onto behavioral mechanisms and overtourism outcomes, thereby providing the empirical basis for the conceptual and diagnostic frameworks.

This approach ensured a thorough understanding of literature while allowing for the inclusion of diverse sources and emerging trends. The findings were organized into tables and graphs to present distributions, trends, and areas requiring further attention in scholarly discussions, along with brief explanations of both successful and unsuccessful real-world case studies that provide insights into the implementation and limitations of different strategic methods.

Results and discussion

Results of the bibliometric analysis

This line chart shows how academic interest in marketing strategies to address overtourism has changed, based on the number of relevant publications identified through a structured Scopus search (Figure 2). The trend line indicates an increasing scholarly focus starting in 2018, peaking between 2021 and 2023, followed by a slight dip in 2025, possibly due to indexing delays.

Figure 2.

Annual publication trends on new marketing strategies for overtourism (2017–2025).

Figure 3 visualizes the thematic structure of tourism marketing and overtourism research from 2020 to 2023. The clusters reflect a field transitioning from impact-driven debates toward data-enabled and behaviorally informed governance. Sustainability and stakeholder coordination remain central (green), while resident conflict, gentrification, and social pressure form a strong complementary axis (blue). Technological approaches (big data, smart tourism, and digital applications) are emerging as a rapidly expanding research frontier (purple), signaling a shift toward algorithmic visitor management. Smaller clusters related to pricing, seasonality, branding, and destination differentiation highlight ongoing interest in market-based and perceptual strategies. The temporal color overlay indicates a move from crisis-focused research during 2020–2021 toward adaptive, technology-supported governance after 2022. Yet, weak connections between technology, community resilience, and branding reveal a persistent gap in integrating digital innovation with sociocultural and relational dimensions of sustainable tourism marketing.

Figure 3.

Keyword co-occurrence clusters in tourism marketing research (2020–2023).

Results of the literature review

This study identified a wide range of marketing strategies proposed to address overtourism. To capture the overall scholarly focus and development of these strategies, Figure 4 presents a diagnostic bubble chart that maps 10 key strategic categories across three dimensions: publication recency, scholarly attention, and strategic depth. This visualization provides a consolidated overview of how literature has prioritized, expanded on, or overlooked specific marketing approaches. Building on this mapping, the following subsections offer a thematic synthesis of the main mechanisms, empirical insights, and conceptual contributions within each strategic category.

Figure 4.

Diagnostic mapping, strategic focus in overtourism literature (2017–2025).

Two strategies clearly dominate the current research scene: advanced technology integration and demarketing. Advanced technology (n = 31) has become the primary focus of the field, both theoretically and in practice. Recent studies highlight digital infrastructures—such as AI-driven analytics, Internet of Things (IoT)-enabled crowd management, and real-time monitoring systems—as key tools for predicting and reducing congestion (Camatti et al., 2020; Remenyik et al., 2021). Its range of substrategies shows a shift from simply exploring concepts to actively applying them. Demarketing (n = 29) is the second major pillar of this approach. Scholars increasingly view it as a strategic counterbalance to growth-driven marketing, using pricing, capacity limits, and narrative reframing to control tourist flows (Bouchon and Rauscher, 2019; Pasquinelli and Trunfio, 2020). Together, these two strategies point to the rise of a technoregulatory paradigm—an emerging consensus that overtourism management requires both intelligent systems to monitor behavior and marketing tools to influence it. Strategies such as high-value tourism and off-season marketing mark a shift from reactive control to proactive demand differentiation. These emerging themes demonstrate an evolution in scholarly thinking—from limiting overtourism to managing it through value creation and strategic timing. The resulting landscape reveals a research field in transition—shifting from descriptive accounts of overcrowding toward an integrative and behaviorally informed understanding of how marketing can redistribute demand and enhance destination resilience.

Despite progress, essential areas still need development. Segmentation and targeting (n = 25) are often regarded as static demographic tools rather than dynamic, psychographically informed strategies (Georgescu Paquin and Cerdan Schwitzguébel, 2021). Expectation management (n = 10) receives limited attention despite its importance in aligning perceptions and preventing dissatisfaction (Song and Wondirad, 2023). Brand repositioning (n = 5) is an overlooked area, with few studies examining how to reconstruct brand identity to reflect sustainability and promote responsible behavior (Séraphin et al., 2019; Skinner, 2021). This indicates a preference for technical strategies over softer, emotional, or cultural approaches that could fundamentally change tourism behavior.

Building on this mapping, the upcoming sections examine each strategic category in detail. Each subsection covers the primary mechanisms, key examples, and important findings from the reviewed literature, showing how different marketing strategies help manage or reduce overtourism. (The Appendix table classifies selected articles by 10 overtourism mitigation strategies and their substrategies.)

Using advanced technology

Advanced technologies have shifted overtourism management from reactive monitoring to proactive behavioral control. Rather than serving as mere technical add-ons, smart platforms, real-time analytics, and AI systems function as behavioral enablers that influence tourist movement, guide decision making, and enhance managerial responsiveness (Camatti et al., 2020; Jurinčič, 2022).

Recent advances in big data and AI enable DMOs to shift from simple monitoring to predictive management (Vila-Lopez and Küster-Boluda, 2022). Using mobile tracking, geolocation data, and machine learning, destinations like Amsterdam and Barcelona can forecast crowd patterns and adjust promotional messages or prices in real time (Cheng et al., 2025; Kuenen et al., 2023).

Smart apps and mobility dashboards provide real-time cues that help visitors avoid congestion, select alternative routes, or move activities to less crowded areas. IoT-based systems installed in destinations such as Dubrovnik and Venice demonstrate how sensor data and adaptive platforms can redistribute traffic and support ground-level mitigation (Bouchon and Rauscher, 2019; Remenyik et al., 2021). Immersive tools such as Virtual Reality (VR) and Augmented Reality (AR) further enhance these efforts by providing low-impact experiences and reducing pressure on heritage sites (Skinner, 2021).

The expansion of big data and AI allows destinations to shift from descriptive monitoring to predictive governance. Techniques like Geographic Information Systems (GIS)-based saturation mapping, automated counters, predictive algorithms, and deep learning models, including Long Short-Term Memory (LSTM) networks, support short-term forecasting and scenario planning. This enables DMOs to intervene before congestion occurs (De la Osada Saurí, 2024; Ramos et al., 2021; Rogowski et al., 2025; Scott et al., 2020).

However, scholars warn that algorithmic systems are not fully unbiased (Buitrago and Yñiguez, 2021; Geffroy et al., 2025). Bias in data collection, a focus on high-value segments, and unequal representation of community interests can exacerbate disparities rather than reduce them. Nonetheless, the same digital platforms that increase viral exposure can be intentionally used to direct attention to sustainable, less-visited areas, thereby creating a more ethical and balanced visibility system (Song and Wondirad, 2023).

Overall, advanced technologies enhance both preventive and reactive capabilities by creating ongoing feedback loops among visitors, managers, and the destination environment, thereby supporting more adaptable, resilient, and behaviorally informed governance.

Demarketing strategies

The concept of demarketing was first introduced by Kotler and Levy (1971) as a strategic approach to decrease consumer demand, either broadly or from specific sectors, temporarily or permanently. Demarketing has become an important behavioral management tool for balancing visitor demand with destination capacity. Instead of encouraging visits, demarketing influences tourists’ mental assessments and emotional reactions by modifying price, access, and visibility. These strategies generate strategic “friction” that reduces impulsive or high-impact visits while promoting shifts to other locations or times.

Price- and access-based measures—such as Venice's day-visitor fees, Amsterdam's tourist taxes, and Cinque Terre's limits on short stays—demonstrate how financial and regulatory signals can discourage unsustainable visitation patterns (Vegnuti, 2020; Bei and Celata, 2023). Gülsen et al.'s (2021) study shows that price as a demarketing tool is the most effective option when a destination seeks to reduce overtourism through demarketing strategies. Spatial demarketing further redistributes visitor flows by decreasing promotional exposure for overused hotspots and emphasizing lesser-visited areas (Antunes and Ferreira, 2021). Studies also reveal that narrative reframing, influencer participation, and targeted communication can reshape social norms and lessen Fear of Missing Out (FOMO)-driven travel (Gibson, 2021; O’Regan and Choe, 2023).

However, research highlights that demarketing is most effective when embedded within broader governance systems. Capacity planning, community engagement, and brand repositioning are crucial to ensure fairness, legitimacy, and long-term acceptance (Jurinčič, 2022; Scott et al., 2020). From a resilience standpoint, effective demarketing functions not as a punitive restriction but as an adaptive tool that balances protection, participation, and sustainable access.

Precise segmentation and targeting

Precise segmentation and targeting have become essential for managing overtourism, shifting from a marketing tactic to a tool for behavior governance. Zarhari et al. (2023), in their discussion of the importance of segmentation, argue that planning destination management based on tourism segmentation can lead to more effective tourism flows and movements. Instead of focusing on volume-driven promotion, destinations increasingly use segmentation to identify visitor groups whose attitudes, norms, and behaviors align with sustainability goals (Cheng et al., 2025; Georgescu Paquin and Cerdan Schwitzguébel, 2021). By targeting eco-conscious travelers, cultural explorers, and high-value, low-impact segments, DMOs can adjust demand while maintaining economic sustainability.

Segmentation also functions as a social mediation tool. Location-based and behavior-based segmentation help ease pressure on residential neighborhoods and foster social harmony, as highlighted by Postma and Schmuecker (2017). Advances in data analytics further enhance this method: quantile modeling, geo-tagged movement data, and sentiment analysis enable dynamic targeting that adjusts promotional content based on real-time crowd density, visitor satisfaction, and environmental impact (De Luca and Rosciano, 2020; Scott et al., 2020).

Emerging perspectives even view visa regimes as potential tools for segmentation, affecting visitor composition and aligning travel flows with sustainability goals (Lehmann, 2023). Overall, segmentation serves as a strategic tool that helps destinations control who visits when they visit, and how they interact—supporting more balanced and resilient tourism systems.

Geographic diversification and promoting alternative destinations

Geographic diversification has become a key strategy for demand management, redirecting visitor flows from crowded hotspots to lesser-known or emerging areas. Instead of limiting access, diversification serves as a proactive behavioral intervention that reshapes tourists’ mental maps, perceived attractiveness, and spatial decision making (Bouchon and Rauscher, 2019; Mendoza de Miguel et al., 2023). Marketing campaigns that promote alternative sites, themed routes, or regional clusters encourage dispersal by changing perceptions of what makes a site desirable or a “must-see” experience (Vu et al., 2021).

Empirical evidence shows its effectiveness. In Campania, Italy, promotional efforts resulted in a significant increase in off-hotel accommodations, indicating successful distribution beyond main hubs (De Luca and Rosciano, 2020). In Dubrovnik, targeted promotion of Lokrum Island and nearby beaches eased congestion on the UNESCO-listed Old Town (Camatti et al., 2020). Similar thematic diversification in Spain—linking Girona, Montserrat, and coastal villages—strengthened both regional identity and spatial distribution (Eckert et al., 2019).

Recent research underscores the importance of data-driven approaches that integrate marketing and spatial planning, enabling destinations to implement adaptive, evidence-based dispersion strategies (Ignaccolo et al., 2023; Postma and Schmuecker, 2017). However, diversification carries risks. Viral exposure can quickly turn “alternative” sites into new hotspots (Alonso-Almeida et al., 2019), and ongoing promotional bias toward iconic landmarks can undermine long-term spatial balance (Georgescu Paquin and Cerdan Schwitzguébel, 2021). Additionally, limited local participation and fragmented governance hamper implementation (Bei and Celata, 2023; Çakar and Uzut, 2020).

Therefore, geographic diversification is most effective when combined with policy alignment, community participation, and sustainable storytelling, which help ensure that alternative destinations can accommodate increased visitors without creating a cycle of overtourism.

Tourist education and awareness campaigns

Tourist education and awareness campaigns serve as preventive behavioral interventions, aiming not only to inform visitors but also to influence attitudes, norms, and perceived behavioral control—key predictors of responsible travel (Bouchon and Rauscher, 2019; Oklevik et al., 2019). Successful campaigns combine emotional storytelling, experiential learning, and clear guidance to close the gap between awareness and action (Szőllős-Tóth et al., 2024).

Recent initiatives such as “Love San Sebastián. Live Donostia” and Barcelona's community-based messaging demonstrate how local stories humanize sustainability efforts and ease tensions between residents and visitors (Mendoza de Miguel et al., 2023). Digital micro-interventions—such as congestion alerts and behavioral reminders in Dubrovnik—further translate awareness into real-time behavioral compliance (Camatti et al., 2020). Online conversations such as #overtourism also offer insights into shifting visitor expectations and identities, providing feedback to improve communication strategies (O’Regan and Choe, 2023).

Community-led educational efforts enhance authenticity and message credibility, as residents co-develop heritage and ecotourism programs that boost cultural understanding and social cohesion (Gowreesunkar et al., 2019; Sánchez-Aguirre et al., 2025). Destinations increasingly run campaigns to clarify capacity limits, booking requirements, and codes of conduct (Espinet-Rius et al., 2024), thereby aligning visitor expectations with sustainable practices and improving overall experience quality. Sæþórsdóttir et al. (2020) argue that educating policymakers, destination managers, and the public is essential for effective destination management, emphasizing the importance of considering both “media discourse” and “real data” to build awareness.

Sustainable and experience-based destination branding

Sustainable destination branding is a key strategy to prevent overtourism by shaping expectations, guiding travel plans, and redistributing demand before congestion occurs. Rather than focusing solely on visual appeal, modern branding emphasizes value alignment—connecting destination identity to authenticity, environmental responsibility, and community health (Bouchon and Rauscher, 2019; Oklevik et al., 2019). These stories encourage exploring lesser-known areas and low-impact experiences, serving as early behavioral guidance tools.

Research indicates that transparent sustainability claims and credible green labels build trust and attract visitors who exhibit more responsible behaviors (Majdak and de Almeida, 2022; Pasquinelli et al., 2021). Emotional storytelling and heritage-based communication further strengthen attachment to place, encouraging slower and more meaningful engagement rather than mass, fast consumption (Crossley, 2020).

However, recent studies warn that overly idealized imagery can distort expectations and unintentionally stimulate overcrowding, especially in ecologically fragile regions (Ortanderl and Bausch, 2023). The rise of social media exacerbates this problem: user-generated content increases visibility but can direct visitors to sensitive areas beyond management's control (Jang and Park, 2020; Kádár and Klaniczay, 2022). To address this, scholars promote “ethical branding governance,” in which DMOs co-create digital narratives with communities and influencers to ensure accurate representation and responsible visibility. Sustainable branding must therefore include local identity and emotional authenticity; when the brand image diverges from residents’ perceptions, cooperation declines and tourism fatigue worsens (Kato et al., 2024).

Attracting high-value and luxury tourists

Targeting high-value tourists has emerged as a strategic demand-shaping approach that reduces pressure on overcrowded destinations by prioritizing travelers who generate higher economic contributions with lower environmental and social impacts. This strategy reframes destination competitiveness in terms of exclusivity, cultural depth, and sustainability rather than visitor volume (Mendoza de Miguel et al., 2023). By promoting premium yet responsible experiences, DMOs influence travel intentions before they form, attracting segments that value authenticity, wellbeing, and ethical consumption.

Empirical evidence from eco-luxury lodges in Oceania, rural boutique tourism in Asia, and gastronomy- and wellness-focused branding in cities such as Valencia and San Sebastián shows that high-value experiences can boost economic gains without increasing crowding. These efforts also serve as behavioral filters, attracting visitors whose expectations align with sustainable, culturally respectful travel.

Recent work suggests that visa regimes may evolve into segmentation tools, helping destinations attract high-quality, low-impact markets (Lehmann, 2023). Overall, high-value tourism shifts overtourism management from restrictive measures to aspirational, selective demand cultivation, thereby promoting tourism growth in more balanced, regenerative, and socially responsible ways.

Managing visitor expectations through clear and consistent messaging

Managing visitor expectations through clear, consistent messaging is a key preventive strategy to reduce overtourism. By providing precise and realistic information about destination conditions, capacity limits, and cultural norms, DMOs shape tourists’ perceptions before travel, reducing expectation gaps that often lead to dissatisfaction, conflict, and irresponsible behavior (Bouchon and Rauscher, 2019; Song and Wondirad, 2023). Effective messaging serves as a mental filter, aligning visitors’ expectations with the destination's actual social and environmental limits.

Visual communication plays an essential role. Authentic, experience-based imagery counters the distortions created by utopian marketing and shifts interest toward less crowded sites. Real-time updates—such as congestion alerts or access restrictions—also serve as behavioral nudges, allowing visitors to adjust their plans to reduce environmental and social impacts (Rogowski et al., 2025).

Community participation boosts credibility and emotional connection. Locally guided tours and resident-led stories promote cultural understanding and improve compliance with destination norms (Heslinga et al., 2024). Overall, expectation management lessens psychological friction, boosts satisfaction, and supports more resilient, sustainable visitation patterns.

Off-season marketing

Off-season marketing is a preventive approach that influences the timing of tourist behavior by shifting travel plans from peak to shoulder or off-peak seasons. By presenting off-season periods as appealing, high-quality experiences, DMOs ease pressure on overcrowded destinations and improve overall demand balance. Seasonal storytelling and customized communication, as employed in the Pieniny and Tatra National Parks, demonstrate that narrative reframing can increase visitation in spring and autumn without compromising ecological integrity (Rogowski et al., 2025; Vu et al., 2021).

Dynamic pricing further supports temporal redistribution. Evidence from Venice shows that time-sensitive pricing based on online booking data effectively leverages demand elasticity to shift visitation away from peak periods while maintaining economic viability (Angelini et al., 2025). Event-based strategies, including conferences, wellness retreats, and niche cultural festivals, also attract visitors seeking tranquility and personalized experiences (Çakar and Uzut, 2020; Eckert et al., 2019).

Overall, off-season marketing supports sustainability and destination resilience by easing peak-season congestion, smoothing revenue cycles, and encouraging more authentic visitor engagement beyond the typical high-season imagery.

Brand repositioning toward sustainable and value-based tourism

Brand repositioning is increasingly viewed as a strategic approach to shift destinations from volume-driven tourism to sustainable, value-based development. Instead of merely updating the visual identity, repositioning redefines what the destination represents, alters market expectations, shapes visitor identities, and encourages more responsible forms of engagement (Butler and Dodds, 2022; Skinner, 2021). By emphasizing cultural authenticity, environmental responsibility, or community wellbeing, repositioning acts as a subtle behavioral guide, directing demand away from overcrowded areas and toward slower, higher-quality tourism.

Recent examples demonstrate this transformation. Amsterdam's shift from permissive leisure branding to an emphasis on heritage and cultural value (focused on art, heritage, and cuisine), or Cinque Terre's promotion of slow tourism, demonstrates how repositioning can attract visitors who share sustainability values (Avond et al., 2019; Kuenen et al., 2023). Digital storytelling and VR tools have further supported this change by highlighting lesser-known or low-impact experiences (Godovykh et al., 2022).

Contemporary studies emphasize that sustainable repositioning must be participatory and enduring. Co-created branding ensures narrative authenticity and stakeholder engagement (Séraphin et al., 2019). However, scholars warn that superficial or crisis-driven rebranding might inadvertently revive unsustainable demand if it is not backed by consistent governance (Pasquinelli and Trunfio, 2020).

Overall, brand repositioning functions as a governance tool rather than just a surface-level change. By shaping expectations and emotional bonds, it influences when, where, and how tourists engage with destinations—encouraging more balanced visitor flows, stronger community identity, and long-term destination resilience.

Conceptual framework: A strategic marketing model for overtourism management

Based on the synthesis of the reviewed studies, this framework conceptualizes tourism marketing as a form of behavioral governance, in which communication, technology, and policy interact to shape tourist decision making toward sustainable outcomes. The model (Figure 5) distinguishes three types of strategic intervention: preventive (ex-ante demand shaping), reactive (ex-post mitigation), and hybrid or adaptive approaches, reflecting the temporal moments at which marketing influences tourist behavior.

Figure 5.

Behavioral governance framework linking marketing strategies, behavioral mechanisms, and overtourism outcomes.

Preventive strategies—such as sustainable branding, off-season marketing, and awareness campaigns—operate before travel decisions are made, primarily shaping tourists’ expectations, risk perceptions, and value assessments. These strategies are typically associated with temporal demand redistribution (e.g. shifting visitation to shoulder or low seasons) and longer-term norm formation around responsible travel.

Reactive strategies, including demarketing, expectation management, and real-time technological tools, are employed once overtourism pressures become evident. These approaches rely on immediate behavioral cues, such as price signals, access restrictions, or real-time information, and are most strongly associated with the spatial redistribution of visitors, congestion relief at hotspots, and short-term reductions in pressure on infrastructure and residents.

Hybrid strategies combine preventive and reactive approaches through continuous feedback mechanisms, such as smart platforms, community co-branding, and adaptive digital communication. These approaches enable destinations to dynamically balance visitor flows, resident wellbeing, and economic objectives, improving both operational efficiency and experiential quality.

Across all three strategy types, marketing interventions operate through distinct but interrelated behavioral mechanisms, which can be grouped into:

Cognitive mechanisms (e.g. information framing, expectation management, and awareness building),

Affective or psychological mechanisms (e.g. emotional engagement, place attachment, and identity alignment), and

Social–normative mechanisms (e.g. norm activation, responsibility framing, and collective identity).

These mechanisms translate marketing strategies into three observable categories of behavioral outcomes:

Temporal changes (when tourists travel),

Spatial changes (where tourists go), and

Experiential changes (how tourists engage with destinations and communities).

Together, these outcomes contribute to reduced congestion, improved utilization of existing capacity, lower resident irritation, and enhanced destination resilience over time. Supporting this system is a multilevel governance infrastructure—comprising DMOs, local communities, policymakers, and digital platforms—which enable coordination, data sharing, and ethical implementation.

The figure illustrates how preventive, reactive, and hybrid marketing strategies activate cognitive, affective, and social–normative mechanisms, thereby producing temporal, spatial, and experiential changes in tourist behavior. These changes are linked to outcomes related to overtourism, including reduced congestion, alleviated pressure, improved resident wellbeing, and enhanced destination resilience.

Comparative insights from case studies of strategic marketing for overtourism management

An analysis of real-world cases reveals differences between successful and unsuccessful efforts to address overtourism. Success often depends on coordination among marketing, governance, and behavioral management, while failures are caused by overpromoting, emotional overload, or poor systemic cooperation.

Integrated and data-driven approaches—such as Madeira's rural tourism diversification (Majdak and de Almeida, 2022), Lisbon's influencer-based green branding (Cooke et al., 2022), and Spain's GIS-supported spatial marketing (De la Osada Saurí, 2024)—demonstrate that when destination branding aligns with community narratives and data analytics, it can influence visitor flows and promote long-term sustainability. Likewise, projects such as SHCITY (Zubiaga et al., 2019) emphasize the importance of technological mediation and real-time visitor management for maintaining livability.

In contrast, overly emotional or unregulated branding efforts—such as those in Cinque Terre (Vegnuti, 2020), Iceland (Sæþórsdóttir et al., 2020), and Kraków (Kruczek, 2019)—actually triggered the very overload of tourism they aimed to prevent. These failures generally shared three main weaknesses: (1) limited demarketing or capacity management; (2) lack of data-driven monitoring; and (3) weak community involvement or expectation setting. Similarly, uncontrolled viral tourism in Ihwa Mural Village (Jang and Park, 2020) and reactive campaigns in Hangzhou (Song and Wondirad, 2023) revealed the risks of unmanaged social media exposure without proactive narrative control.

The evidence indicates that strategic marketing is most effective when integrated into a broader behavioral and policy framework that incorporates community input, technology, and real-time adjustments. These insights support the conceptual model (Figure 5): marketing alone cannot solve overtourism, but when combined with expectation management, segmentation, and technological feedback mechanisms, it becomes a vital part of sustainable destination governance.

Conclusion and discussion

This study reconceptualizes tourism marketing as a behavioral governance system rather than a purely promotional activity, responding to growing calls for demand-side approaches to overtourism management. Drawing on a narrative review of 72 peer-reviewed studies published between 2017 and 2025, the analysis identified 10 distinct categories of marketing-based strategies, ranging from demarketing and geographic diversification to technological integration and visitor education. To synthesize these fragmented insights, the study developed two complementary models: (1) a diagnostic map that captures the evolution, intensity, and strategic depth of marketing responses to overtourism (Figure 4) and (2) a behavioral governance framework (Figure 5) that explicitly links marketing interventions to behavioral mechanisms and overtourism-related outcomes.

The behavioral governance framework advances tourism and marketing scholarship by clarifying how marketing strategies influence tourist behavior and the mechanisms by which this occurs. Specifically, the findings show that marketing interventions operate through three interrelated mechanisms: cognitive mechanisms (e.g. expectation management, awareness formation, and information framing), affective or psychological mechanisms (e.g. emotional engagement, place attachment, and moral emotions), and social–normative mechanisms (e.g. responsibility cues, identity alignment, and norm activation). These mechanisms jointly shape tourists’ decision-making processes and behavioral responses across the stages of the travel experience.

Through these pathways, marketing strategies yield distinct overtourism-related outcomes. Preventive and adaptive interventions, such as off-season marketing, sustainable branding, and segmentation, primarily redistribute temporal demand, reducing peak-period congestion while improving capacity utilization during shoulder or low seasons. Spatially oriented strategies, including geographic diversification, smart routing, and selective visibility management, disperse visitor flows, alleviating pressure on overcrowded hotspots. Reactive tools such as demarketing, capacity signaling, and real-time information systems help mitigate acute congestion and infrastructure stress, while education- and community-based narratives foster improvements in resident–visitor relations, destination livability, and social acceptance of tourism.

Although the reviewed strategies vary in scope and implementation, they collectively signal a fundamental shift in marketing logic—from demand stimulation toward behavioral design and governance. Rather than merely persuading tourists to visit, contemporary marketing increasingly shapes norms, expectations, and choices about where, when, and how travel occurs. This shift aligns with and extends key theoretical debates in behavioral economics, sustainable marketing, and destination governance, including theories of planned behavior, destination image formation, and resilience thinking, into the specific context of overtourism management.

Despite growing academic attention, important gaps remain. Substrategies such as influence-led interventions, blockchain-enabled transparency, and location-based digital nudging remain unevenly theorized and empirically evaluated. Moreover, much of the existing literature examines technological solutions in isolation, with limited consideration of their social, ethical, and experiential implications. This fragmentation highlights the need for more integrative research that combines behavioral science, data analytics, cultural storytelling, and stakeholder collaboration to better understand when, why, and for whom specific marketing interventions succeed or fail.

From a practical perspective, the findings underscore a transition toward value-based, community-centered destination branding, moving away from volume-driven promotional narratives. When aligned with carrying capacity, social inclusion, and environmental responsibility, marketing can serve as a form of stewardship—guiding tourists toward more mindful and regenerative forms of engagement. In this regard, demarketing should be understood not as a degrowth-oriented or anti-tourism measure but as a strategic governance tool that enables destinations to recalibrate demand in line with social and environmental thresholds (Najafi and Costa, 2026).

Overall, this study contributes to emerging debates on behavioral governance in tourism by positioning marketing as an active instrument for shaping sustainable futures. By systematically mapping existing strategies and clarifying their behavioral mechanisms and expected outcomes, the research provides both a conceptual foundation and a diagnostic tool for scholars and practitioners seeking more balanced, ethical, and resilient approaches to managing overtourism.

Implications for practice and research

The findings offer actionable insights for DMOs and advance conceptual debates in sustainable tourism research. The two proposed models provide complementary tools for bridging theory and practice. The diagnostic model (Figure 4) enables practitioners to assess the maturity and scholarly attention devoted to different marketing strategies, helping DMOs prioritize interventions based on existing evidence and identified research gaps. In contrast, the behavioral governance framework (Figure 5) serves as a decision-support guide by linking specific marketing interventions to distinct forms of behavioral change—temporal, spatial, and experiential—through clearly articulated psychological mechanisms.

Importantly, the framework does not prescribe universal solutions but supports context-sensitive strategy selection, recognizing that effectiveness varies across destination types, cultural settings, and symbolic meanings. For example, destinations with high iconic value, such as Venice, Machu Picchu, or Santorini, may be less responsive to demarketing because of FOMO-driven demand, requiring complementary approaches such as expectation management or experiential reframing.

Future research directions

Building on the diagnostic and conceptual models introduced in this study, future research should move beyond descriptive mapping to empirically validate and refine marketing-based overtourism strategies. Experimental and quasi-experimental studies could test the behavioral effects of interventions such as demarketing, influencer-led messaging, and AI-driven personalization across diverse destination contexts. Comparative and longitudinal designs could further reveal how similar strategies perform in urban versus rural settings or across regions in the Global North and Global South, particularly in relation to resident wellbeing and destination resilience.

Future research should also address the ethical and governance questions raised by behavioral marketing approaches. Key issues include who defines the “desirable” tourist, how branding and segmentation decisions affect inclusion and power relations, and how unintended consequences—such as displacement to equally fragile locations—can be monitored and mitigated. Integrating behavioral economics, cultural psychology, and big-data analytics offers promising pathways to predictive, adaptive, and ethically grounded models of destination marketing governance.

Supplemental Material

sj-docx-1-jvm-10.1177_13567667261423653 - Supplemental material for Marketing responses to overtourism: A strategic mapping and diagnostic review

Supplemental material, sj-docx-1-jvm-10.1177_13567667261423653 for Marketing responses to overtourism: A strategic mapping and diagnostic review by Maryam Najafi and Carlos Costa in Journal of Vacation Marketing

Footnotes

ORCID iD

Maryam Najafi

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Supplemental material

Supplemental material for this article is available online.

Appendix

Branding	Emphasis on Sustainability	Bouchon and Rauscher (2019), Oklevik et al. (2019), Pasquinelli et al. (2021), Crossley (2020), Zarhari et al. (2023)
	Sustainability Certifications	Majdak and de Almeida (2022)
	Storytelling to Attract	Pasquinelli et al. (2021), Crossley (2020), Kádár and Klaniczay (2022)
	Consistent Brand Messaging	Sæþórsdóttir et al. (2020), Ortanderl and Bausch (2023)
High-Value Tourists	Longer Stays	Banerjee & George (2025), De Luca and Rosciano (2020)
	Slow Tourism	Banerjee & George (2025), Vegnuti (2020)
	Low-Impact Activities	Banerjee & George (2025), Mendoza de Miguel et al. (2023)
	Authentic Cultural Experiences	Rickly (2019), Kuenen et al. (2023)
	Luxury/Niche Marketing	Mendoza de Miguel et al. (2023), Hall and Wood (2021)
Geographic Diversification	Regional Collaboration	Espinet-Rius et al. (2024), Heslinga et al. (2024)
	New Tourism Routes	Mendoza de Miguel et al. (2023), Gowreesunkar et al. (2019)
	Promoting Lesser-Known Areas	Camatti et al. (2020), Kuenen et al. (2023), Rogowski et al. (2025), Bei and Celata (2023)
Off-Season Marketing	Low-Season Promotions	Espinet-Rius et al. (2024), Eckert et al. (2019)
	Dynamic Pricing	Angelini et al. (2025), Hall and Wood (2021)
	Seasonal Events	Mendoza de Miguel et al. (2023), Rogowski et al. (2025), Çakar and Uzut (2020)
Education & Awareness	Visual Communication	Taecharungroj et al. (2024), Szőllős-Tóth et al. (2024)
	Community-Based Ecotourism	Gowreesunkar et al. (2019), Sánchez-Aguirre et al. (2025)
	Digital Awareness Campaigns	Camatti et al. (2020), Song and Wondirad (2023), Wengel et al. (2022)
	Responsible Tourism	Oklevik et al. (2019), Bouchon and Rauscher (2019), Séraphin et al. (2019)
Segmentation & Targeting	Cultural/National Segmentation	Cheng et al. (2025), Postma and Schmuecker (2017)
	Social Media Targeting	Georgescu Paquin and Cerdan Schwitzguébel (2021), Alonso-Almeida et al. (2019), O’Regan and Choe (2023)
	Behavioral Segmentation	De Luca and Rosciano (2020), Scott et al. (2020)
Expectation Management	Digital Updates & Sentiment Analysis	Song and Wondirad (2023), Cho (2021)
	Local Laws & Etiquette	Bouchon and Rauscher (2019), Heslinga et al. (2024)
	Transparent Communication	Rogowski et al. (2024), Wengel et al. (2022)
Advanced Technology	GIS / Heatmaps	De la Osada Saurí (2024), Cheng et al. (2025)
	IoT Sensors	Bouchon and Rauscher (2019)
	Big Data / AI	Avond et al. (2019), Kuenen et al. (2023), Ramos et al. (2021)
	AR/VR	Godovykh et al. (2022), Skinner (2021)
	Real-Time Monitoring	Zubiaga et al. (2019), Espinet-Rius et al. (2024), Remenyik et al. (2021)
Brand Repositioning	Participatory Branding	Séraphin et al. (2019), Gibson (2021)
	Digital Repositioning	Song and Wondirad (2023), Godovykh et al. (2022)
	Cultural Branding	Rickly (2019), Lehmann (2023), Georgescu Paquin and Cerdan Schwitzguébel (2021)
	From Mass to Sustainable	Butler and Dodds (2022), Kuenen et al. (2023), Šenková et al. (2022)
Demarketing	Pricing / Visitor Caps	Gülsen et al. (2021), Avond et al. (2019), Kuenen et al. (2023)
	Zoning / Access Limits	Camatti et al. (2020), Pasquinelli and Trunfio (2020)
	Reduction in Promotion	Skinner (2021), Bouchon and Rauscher (2019), Mendoza de Miguel et al. (2023)
	Regulating Short-Term Rentals	Bei and Celata (2023), Antunes and Ferreira (2021)

References

Ajzen

(1991) The theory of planned behavior . Organizational Behavior and Human Decision Processes 50(2): 179–211.

Alonso-Almeida

M-d-M

Borrajo-Millán

(2019) Are social media data pushing overtourism? The case of Barcelona and Chinese tourists. Sustainability 11(12): 3356.

Angelini

Costa

Guizzardi

(2025) Complex data in tourism analysis: a stochastic approach to price competition. Big Data Research 40: 100520.

Antunes

Ferreira

(2021) Short-term rentals: how much is too much – spatial patterns in Portugal and Lisbon. Tourism and Hospitality Management 27(3): 581–603.

Avond

Bacari

Limea

, et al. (2019) Overtourism: a result of the Janus-faced character of the tourism industry. Worldwide Hospitality and Tourism Themes 11(5): 552–565.

Banerjee

George

(2025) Identifying overtourism & spill-over tourism using ST-DBSCAN analysis for sustainable management of tourism. Current Issues in Tourism 28(18): 2927–2947. doi: 10.1080/13683500.2024.2382378.

Bei

Celata

(2023) Challenges and effects of short-term rentals regulation: a counterfactual assessment of European cities. Annals of Tourism Research 101: 103605.

Belz

Peattie

(2009) Sustainability Marketing: A Global Perspective. West Sussex, UK: John Wiley & Sons.

Bouchon

Rauscher

(2019) Cities and tourism, a love and hate story; towards a conceptual framework for urban overtourism management. International Journal of Tourism Cities 5(4): 598–619.

10.

Bruning

Ledingham

(1999) Relationships between organizations and publics: development of a multi-dimensional organization-public relationship scale. Public Relations Review 25(2): 157–170.

11.

Buitrago

Yñiguez

(2021) Measuring overtourism: a necessary tool for landscape planning. Land 10(9): 889.

12.

Butler

Dodds

(2022) Overcoming overtourism: a review of failure. Tourism Review 77(1): 35–53.

13.

Çakar

Uzut

(2020) Exploring the stakeholder’s role in sustainable degrowth within the context of tourist destination governance: the case of Istanbul, Turkey. Journal of Travel and Tourism Marketing 37(9-10): 917–932.

14.

Camatti

Bertocchi

Carić

, et al. (2020) A digital response system to mitigate overtourism: the case of Dubrovnik. Journal of Travel and Tourism Marketing 37(9-10): 887–901.

15.

Cheng

Jian

, et al. (2025) Spatial concentration of intra-urban tourist activities and inter-group differences between Asian, European and North American travelers in Korean cities. Tourism Management 107: 105064.

16.

Cho

Yoonhee

(2021) Awareness and Resolution of Touristification in Korea Using Social Media Big Data Analytics. Global Business & Finance Review 26(1): 68–78. 10.17549/gbfr.

17.

Conze

Bieger

Laesser

, et al. (2010) Relationship intention as a mediator between relational benefits and customer loyalty in the tour operator industry. Journal of Travel & Tourism Marketing 27(1): 51–62.

18.

Cooke

Nunes

Oliva

, et al. (2022) Open innovation, soft branding and green influencers: critiquing ‘fast fashion’ and ‘overtourism’. Journal of Open Innovation: Technology, Market, and Complexity 8(1): 52.

19.

Crossley

(2020) Ecological grief generates desire for environmental healing in tourism after COVID-19. Tourism Geographies 22(3): 536–546.

20.

De la Osada Saurí

(2024) Urban tourism in Spain: a methodology for the identification of saturated areas. Application in Barcelona, Bilbao, Madrid, and Valencia. Investigaciones Turísticas 28: 18–40.

21.

De Luca

Rosciano

(2020) Quantile dependence in tourism demand time series: evidence in the Southern Italy market. Sustainability 12(8): 3243.

22.

Dredge

(2017) “Overtourism” old wine in new bottles? Berlin, Germany: De Gruyter. Available at: https://www.linkedin.com/pulse/overtourism-old-wine-new-bottles-dianne-dredge/.

23.

Eckert

Zacher

Pechlaner

, et al. (2019) Strategies and measures directed towards overtourism: a perspective of European DMOs. International Journal of Tourism Cities 5(4): 639–655.

24.

Elkington

(1997) Cannibals with Forks: The Triple Bottom Line of 21st Century Business. Oxford, UK: Capstone.

25.

Espinet-Rius

García-Sánchez

Gassiot-Melian

(2024) Seasonality in the cruise industry: activity, prices, and regionality. European Journal of Tourism Research 38: 1–21. 10.54055/ejtr.v38i.3481.

26.

Folke

(2006) Resilience: the emergence of a perspective for social–ecological systems analyses . Global Environmental Change 16(3): 253–267.

27.

Gartner

(1993) Image formation process . Journal of Travel & Tourism Marketing 2(2-3): 191–216.

28.

Geffroy

Anduze Rivero

Ceccato

(2025) Statistics as politics: a methodology for the critical approach of tourism quantification. Tourism Recreation Research 50(5): 1127–1140. 10.1080/02508281.2024.2379690.

29.

Georgescu Paquin

Cerdan Schwitzguébel

(2021) Analysis of Barcelona’s tourist landscape as projected in tourism promotional videos. International Journal of Tourism Cities 7(2): 257–277.

30.

Gibson

(2021) Critical tourism studies: new directions for volatile times. Tourism Geographies 23(4): 659–677.

31.

Godovykh

Baker

Fyall

(2022) VR In tourism: a new call for virtual tourism experience amid and after the COVID-19 pandemic. Tourism and Hospitality 3(1): 265–275.

32.

Gowreesunkar

Séraphin

Teare

(2019) Reflections on the theme issue outcomes: what smart and sustainable strategies could be used to reduce the impact of overtourism? Worldwide Hospitality and Tourism Themes 11(5): 634–640.

33.

Gravari-Barbas

Guinand

(2017) Tourism and gentrification in contemporary metropolises: International perspectives. 1–21.

34.

Greenhalgh

Robert

Macfarlane

, et al. (2005) Storylines of research in diffusion of innovation: a meta-narrative approach to systematic review. Social Science & Medicine 61(2): 417–430.

35.

Gülşen

Yolcu

Ataker

, et al. (2021) Counteracting overtourism using demarketing tools: a logit analysis based on existing literature. Sustainability 13(19): 10592. 10.3390/su131910592.

36.

Guttentag

(2015) Airbnb: disruptive innovation and the rise of an informal tourism accommodation sector. Current Issues in Tourism 18(12): 1192–1217.

37.

Hall

Wood

(2021) Demarketing tourism for sustainability: degrowing tourism or moving the deckchairs on the Titanic? Sustainability 13(3): 1585.

38.

Heslinga

Yusuf

Damanik

, et al. (2024) Future strategies for tourism destination management: post COVID-19 lessons observed from Borobudur, Indonesia. Journal of Tourism Futures 10(1): 68–74.

39.

Hon

Brunner

(2002) Measuring public relationships among students and administrators at the University of Florida. Journal of Communication Management 6(3): 227–238.

40.

Ignaccolo

Zheng

Williams

(2023) Tourism morphometrics in Venice: constructing a Tourism Services Index (TSI) to unmask the spatial interplay between tourism and urban form. Cities 140: 104369.

41.

Jang

Park

(2020) Social media, media and urban transformation in the context of overtourism. International Journal of Tourism Cities 6(1): 233–260.

42.

Jurinčič

(2022) Tourism carrying capacity in the municipalities of Tolmin, Kobarid, and Komen. Acta Geographica Slovenica 62(1): 89–104.

43.

Kádár

Klaniczay

(2022) Branding built heritage through cultural urban festivals: an Instagram analysis related to sustainable co-creation, in Budapest. Sustainability 14(9): 5020.

44.

Kato

Ikeda

Koizumi

(2024) Side effects of city branding: differences in brand image and loyalty factors from the perspective of residents in 21 Japanese cities. Urban, Planning and Transport Research 12(1): 2403382.

45.

Hon

(2007) Reliability and validity of organization-public relationship measurement and linkages among relationship indicators in a membership organization. Journalism and Mass Communication Quarterly 84: 419–438.

46.

Koens

Postma

Papp

(2018) Is overtourism overused? Understanding the impact of tourism in a city context. Sustainability 10(12): 4384.

47.

Kotler

Levy

(1971) Demarketing, yes, demarketing. Harvard Business Review 49(6): 74–80.

48.

Kruczek

(2019) Ways to counteract the negative effects of overtourism at tourist attractions and destinations. Annales Universitatis Mariae Curie-Skłodowska, Sectio B 74: 45–57.

49.

Kuenen

Fletcher

Jakobs

, et al. (2023) From overtourism to undertourism… and back? The struggle to manage tourism regrowth in post-pandemic Amsterdam. Boletín de la Asociación de Geógrafos Españoles 99: 2–34. 10.21138/bage.3482.

50.

Lawton

(2017) Cleared for take-off: Structure and strategy in the low fare airline business. London, UK: Routledge.

51.

Lehmann

(2023) Pick me! I am young, healthy, and interested in the arts in your city! I – Exploring the future of travel visas. Journal of Tourism Futures 1–7. 10.1108/JTF-01-2023-0013.

52.

Lew

, et al. (2016) A framework for tourism resilience . Tourism Geographies 18(4): 435–448.

53.

Madeira

Palrão

Mendes

, et al. (2021) Perceptions about tourism and tourists in historic neighborhoods: the case of Alfama. Sustainability 13(15): 8357.

54.

Majdak

de Almeida

AMM

(2022) Pre-emptively managing overtourism by promoting rural tourism in low-density areas: lessons from Madeira. Sustainability 14(2): 57.

55.

Mendoza de Miguel

De la Calle Vaquero

Martínez Parra

(2023) Gestión del overturism en centros históricos mediante demarketing. Investigaciones Turísticas 25: 196–219.

56.

Mihalic

(2020) Conceptualising overtourism: a sustainability approach. Annals of Tourism Research 84: 103025. 10.1016/j.annals.2020.103025.

57.

Milano

Novelli

Cheer

(2019) Overtourism and tourismphobia: a journey through four decades of tourism development, planning and local concerns. Tourism Planning & Development 16(4): 353–357.

58.

Najafi

Costa

(2026) Demarketing as a strategic response to overtourism: paradoxes, pitfalls and future directions. Journal of Hospitality and Tourism Insights 9(11): 1–19.

59.

Oklevik

Gössling

Hall

, et al. (2019) Overtourism, optimization, and destination performance indicators: a case study of activities in Fjord Norway. Journal of Sustainable Tourism 27(12): 1804–1824.

60.

O’Regan

Choe

(2023) #Overtourism on Twitter: a social movement for change or an echo chamber? Current Issues in Tourism 26(7): 1082–1095.

61.

Ortanderl

Bausch

(2023) Wish you were here? Tourists’ perceptions of nature-based destination photographs. Journal of Destination Marketing & Management 29: 100799.

62.

Pasquinelli

Trunfio

(2020) Reframing urban overtourism through the Smart-City Lens. Cities 102: 102729.

63.

Pasquinelli

Trunfio

Bellini

, et al. (2021) Sustainability in overtouristified cities? A social media insight into Italian branding responses to the COVID-19 crisis. Sustainability 13(4): 1848.

64.

Peeters

Gössling

Klijs

, et al. (2018) Research for TRAN Committee-Overtourism: impact and possible policy responses. Brussels, Belgium: European Parliament.

65.

Pike

Ryan

(2004) Destination positioning analysis through a comparison of cognitive, affective, and conative perceptions . Journal of Travel Research 42(4): 333–342.

66.

Postma

Schmuecker

(2017) Understanding and overcoming negative impacts of tourism in city destinations: conceptual model and strategic framework. Journal of Tourism Futures 3(2): 144–156.

67.

Ramos

Yamaka

Alorda

, et al. (2021) High-frequency forecasting from mobile devices’ bigdata: an application to tourism destinations’ crowdedness. International Journal of Contemporary Hospitality Management 33(6): 1977–2000.

68.

Remenyik

Barcza

Csapó

, et al. (2021) Overtourism in Budapest: analysis of spatial process and suggested solutions. Regional Statistics 11(3): 179–197.

69.

Rickly

(2019) Overtourism and authenticity. In: R

Dodds

Butler

(eds) Overtourism: Issues, realities and solutions, 46–61.

70.

Rogowski

Zawilińska

Hibner

(2025) Managing tourism pressure: exploring tourist traffic patterns and seasonality in mountain national parks to alleviate overtourism effects. Journal of Environmental Management 373: 123430. https://doi.org/10.1016/j.jenvman.2024.123430.

71.

Sánchez-Aguirre

Driselda P

Alvarado-Sizzo

Moury-Fernandes

(2025) Intangible cultural heritage versus tourism: residents’ reactions to temporal overtourism during the Day of the Dead in Mixquic, Mexico. Journal of Heritage Tourism 20(2): 235–259. 10.1080/1743873X.2024.2415334.

72.

Scott

Steiger

Rutty

, et al. (2020) Climate change and ski tourism sustainability: An integrated model of the adaptive dynamics between ski area operations and skier demand. Sustainability 12(24): 10617.

73.

Sæþórsdóttir

Hall

Wendt

(2020) Overtourism in Iceland: Fantasy or reality? Sustainability 12(18): 7375.

74.

Šenková

Kormaníková

Matušíková

(2022) Perception of overtourism in selected European destinations in terms of visitor age and in the context of sustainable tourism. GeoJournal of Tourism and Geosites 45(4 supplement): 1643–1649. 10.30892/gtg.

75.

Séraphin

Zaman

Olver

, et al. (2019) Destination branding and overtourism. Journal of Hospitality and Tourism Management 38: 1–4.

76.

Skinner

(2021) Place branding—the challenges of getting it right: Coping with success and rebuilding from crises. Tourism and Hospitality 2(1): 173–189.

77.

Snyder

(2019) Literature review as a research methodology: An overview and guidelines. Journal of Business Research 104: 333–339.

78.

Song

Wondirad

(2023) Demystifying the nexus between social media usage and overtourism: Evidence from Hangzhou, China. Asia Pacific Journal of Tourism Research 28(4): 364–385.

79.

Szőllős-Tóth

Bujdosó

Csapóné Riskó

(2024) Deciphering overtourism impacts through eye-tracking analysis. Ecocycles 10(1): 18–23.

80.

Szromek

Kruczek

Walas

(2020) The attitude of tourist destination residents towards the effects of overtourism—Kraków case study. Sustainability 12(1): 228.

81.

Taecharungroj

Viriya

Vasiljević

Đorđije

Pattaratanakun

Ake

(2024) Snapshots of nature: Harnessing Flickr data to frame sustainable brand positioning strategies for Thailand's national parks. Journal of Outdoor Recreation and Tourism 46: 100765. 10.1016/j.jort.2024.100765.

82.

Vegnuti

(2020) Cinque Terre, Italy – a case of place branding: From opportunity to problem for tourism. Worldwide Hospitality and Tourism Themes 12(4): 471–483.

83.

Vila-Lopez

Küster-Boluda

(2022) Sharing-collaborative economy in tourism: A bibliometric analysis and perspectives for the post-pandemic era. Tourism Economics 28(1): 272–288.

84.

Vogt

(2010) Customer relationship management in tourism: Management needs and research applications. Journal of Travel Research 50(4): 356–364.

85.

Muskat

, et al. (2021) Improving the resident–tourist relationship in urban hotspots. Journal of Sustainable Tourism 29(4): 595–615.

86.

Wengel

Yana

Ling

Yixiao

Apollo

Michal

Maciuk

Kamil

Ashton

Ann Suwaree

(2022) The TikTok effect on destination development: Famous overnight, now what?. Journal of Outdoor Recreation and Tourism 37: 100458. 10.1016/j.jort.2021.100458.

87.

Zarhari

NAA

Mat Som

Azinuddin

, et al. (2023) Overtourism and destination branding: The mediating role of functional and emotional values among tourists. Tourism and Hospitality Management 29(2): 303–308.

88.

Zubiaga

Izkara

Gandini

, et al. (2019) Towards smarter management of overtourism in historic centres through visitor-flow monitoring. Sustainability 11(24): 7254.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.02 MB