Sustainable Financing of Cultural Landscapes: Insights from Japan’s Furusato Nozei System

1. Introduction

In this era of fiscal austerity and constrained public funding, a fundamental question arises: how can cultural landscapes establish sustainable financing mechanisms to ensure long-term conservation and development? Cultural landscapes—a significant category of World Heritage sites—reflect the unique production systems, customs, and cultural traditions of a region, encompassing tangible and intangible values(Rössler 2006). Compared with singular architectural heritage, maintaining cultural landscapes often requires larger-scale and continuous investments to support routine upkeep, restoration, and infrastructure improvements (Guzmán et al. 2017). As these landscapes rely primarily on public funding and government support (Salpina et al. 2025), many heritage sites face financial shortfalls under fiscal constraints (Darlow et al. 2012). Cases such as the Cinque Terre in Italy illustrate the risks of landscape deterioration due to funding shortages and labour outmigration (Agnoletti et al. 2019). While tourism can revitalize certain landscapes—for example, heritage tourism in vineyard regions has promoted sustainable development (Ruiz Pulpón and Cañizares Ruiz 2019)—tourism revenues alone often cover only a fraction of the conservation costs. Without innovative and stable funding channels, financial gaps jeopardise the physical integrity of cultural landscapes and undermine their contributions to tourism, community cohesion, and ecosystem services (Guzmán et al. 2017). Therefore, developing sustainable financing solutions, alongside broader public engagement, is an urgent priority for the long-term preservation and development of cultural landscapes (Salpina et al. 2025).

To address fiscal challenges and compensate for insufficient public funding, academic research and policy practice have widely employed the concept of willingness to pay (WTP) to quantify the economic contributions the public and tourists are willing to make to heritage conservation (Hanemann 1991; Mitchell and Carson 2013). Tourists are willing to pay for the development of cultural landscapes, heritage preservation, or improvements to cultural environments (Abuamoud 2025; Batool et al. 2025; Cong et al. 2019; H. Li et al. 2023; Maeer et al. 2008; Quiroga 2025). Researcher found that UK tourists were willing to support heritage conservation through admission fees (Moran 2002); Alberini and Longo reported that Italian citizens were willing to pay additional taxes for the improvement of Venice’s cultural environment(Alberini and Longo 2006). Bedate found that Spanish tourists expressed a clear willingness to pay for the restoration of archaeological sites(Bedate et al. 2009). Collectively, these studies highlight the potential of public contributions to support cultural landscape protection.

However, the existing WTP research has two major limitations. First, many studies remain at the intention level without examining the mechanisms that convert stated willingness into actual behaviour, reflecting the well-documented intention–behaviour gap (Ajzen 1991; Sheeran and Webb 2016). According to the theory of planned behaviour, intentions typically explain only a fraction of actual behaviour (often less than 30%), and self-interested motives tend to dominate when trade-offs are considered (Sheeran and Webb 2016). In the absence of immediate incentives or reminders, intended contributions may fail to materialise (Conner and Norman 2022). Second, traditional WTP formats are predominantly purely altruistic donations, which are often one-off or sporadic, lacking continuity and institutionalised mechanisms to generate stable funding streams (Jelinčić and Šveb 2021; Lupu and Allegro 2024). Therefore, innovative and sustainable financing mechanisms are required to overcome or mitigate the inherent limitations of conventional WTP approaches.

Against this backdrop, Japan’s Furusato Nozei system offers a unique case study. Introduced in 2008, this programme allows taxpayers to select their preferred local municipalities for contributions, accompanied by tax deductions and, in many cases, material ‘return gifts’ (Hasegawa 2017; Rausch 2019). Funds raised through Furusato Nozei can be directly allocated by local governments to the protection, restoration, and maintenance of cultural landscapes and heritage, as well as to activities that support traditional culture and educational programmes (Donation to Municipality produced by Furusato Choice | Japan, n.d.; Fukasawa et al. 2020). In practice, the programme has provided critical financial support for numerous community-based cultural landscape projects while revitalising local economies and enhancing regional branding (H. Li et al. 2024a; Shimauchi et al. 2019). For instance, Nara Prefecture utilised Furusato Nozei contributions to restore sections of World Heritage temples (H. Li et al. 2024b), while Inuyama City used the Furusato tax to preserve and restore its Edo-era castle town, aiming to attract tourists and boost the local economy (Toyoshima et al. 2024).

Unlike conventional donations (Aseres and Sira 2020), the system combines private incentives (return gifts) with public contributions (cultural landscape conservation) to reflect the concept of institutionalised impure altruism (Hasegawa 2017; Rausch 2019). Through this design, individuals gain a ‘warm-glow’ psychological reward and tangible benefits, substantially enhancing participation feasibility and attractiveness (Andreoni 1989, 1990). Concurrently, Furusato Nozei offers a practical mechanism to narrow the intention–behaviour gap: tax incentives and return gifts reduce action costs by converting those with only nominal willingness into actual contributors (Ajzen 1991; Leonard 2008; Sheeran and Webb 2016). By institutionalising these incentives, Furusato Nozei provides a sustainable funding mechanism that supports the long-term preservation of cultural landscapes. Despite the growing recognition of its significance, empirical research on the programme within the context of cultural landscape conservation remains limited, particularly from the perspective of tourists as contributors and regarding the determinants of their WTP (Aseres and Sira 2020; Pengwei and Ji 2023; Witt 2019).

Building on the aforementioned context, this study examines the influence of tourists’ WTP for cultural landscape conservation through Furusato Nozei. To this end, a comprehensive conceptual framework is proposed, integrating three key dimensions: psychological mechanisms (motivation and destination evaluation), behavioural investment (social interactions, time, and monetary expenditure), and demographic conditions (e.g. income and age). This framework enables an analysis of how these factors influence tourists’ WTP for Furusato Nozei contributions.

This study makes three primary contributions to the literature. First, it introduces theoretical concepts of institutionalised impure altruism and the intention–behaviour gap into cultural landscape research, highlighting how institutional design can bridge the gaps between willingness and action. Second, empirically, it provides a quantitative assessment from tourists’ perspectives, addressing an underexplored stakeholder group in heritage financing. Third, the findings offer practical insights for policy and programme design, informing sustainable funding strategies for cultural landscape preservation and guiding the implementation of incentive-based contribution systems.

2. Research Hypotheses and Theoretical Basis

Tourists’ WTP for the conservation of cultural landscapes is not merely a matter of economic rationality but also the outcome of an interplay between multiple psychological mechanisms, actual behavioural investments, and socio-demographic conditions. Tourism decision-making is shaped by subjective cognition and emotional processing (Ajzen 1991; Baloglu and McCleary 1999; Chi and Qu 2008; Hosany and Gilbert 2010; Oliver 2014), moulded by immersive experiences and resource commitments at destinations (Arkes and Blumer 1985; Kyle et al. 2004b; Lee 2016; Ramkissoon et al. 2013), and constrained by socio-demographic factors (Carson et al. 2003; Snowball 2008; Tuan and Navrud 2007). To systematically uncover the mechanism through which tourists support cultural landscapes via Furusato Nozei, this study adopts an integrative framework comprising (1) psychological pathways, (2) behavioural investment, and (3) socio-demographic conditions.

2.1. Psychological Pathway

Tourists’ WTP often originates from motivations and is progressively transformed into loyalty and supportive behaviours through destination image formation and satisfaction. This sequential chain—motivation → destination image → satisfaction and loyalty → WTP—has been widely validated in consumer and tourism behaviour studies (Prayag and Ryan 2012; Yoon and Uysal 2005). In the tourism context, motivations influence destination choice by functioning as push factors (e.g. desire to escape, rest, seek novelty, health, or social interaction) or pull factors (e.g. heritage, cuisine, cultural resources, or natural attractions) (Kim and Lee 2002). Image attributes are often categorised into Cognitive Images(CI) (functional/tangible attributes, such as landscapes and cultural attractions, or psychological/abstract attributes, such as hospitality and atmosphere) and Affective Images(AI) (emotional responses evoked by the destination) (Baloglu and McCleary 1999; Qu et al. 2011). Satisfaction and loyalty(SI) reflect tourists’ evaluative judgements of the perceived quality of a setting and their behavioural intentions, such as revisit intention and word-of-mouth recommendation (da Costa Mendes et al. 2010).

Notably, recent studies highlight substantial conceptual and empirical overlap between ‘destination image’ and ‘satisfaction/loyalty’, as both reflect tourists’ global evaluations of destination attributes, including cognitive perceptions, affective impressions, and evaluative judgements (Chen and Tsai 2007; Prayag 2009). Consequently, some researchers have advocated treating these constructs as comprehensive latent factors that capture tourists’ overall destination evaluation (Stylidis et al. 2017; Tasci and Gartner 2007). Therefore, we adopted a comprehensive construct—Destination Evaluation—to avoid methodological redundancies. Destination Evaluation is a unified construct that integrates perceptual (image-related) and experiential (satisfaction- and loyalty-related) dimensions.

H1: Motivation positively affects destination evaluation.

H2: Destination evaluation positively affects WTP.

2.2. Behavioural Investment

Behavioural investment in tourism is defined as the continuous allocation of time, monetary resources, and cognitive engagement during conscious consumption and interaction with residents (Alrawadieh et al. 2019; Antón et al. 2017; Cevdet Altunel and Erkurt 2015). While prior tourism literature has mainly emphasised the expected length of stay (Jang and Feng 2007), less attention has been paid to actual investments in time and money as determinants of future intentions. Longer stays facilitate deeper exploration, whereas higher expenditures indicate greater engagement with local services and experiences. Drawing on sunk cost and investment–commitment theory (Arkes and Blumer 1985; Rusbult 1980), higher levels of investment enhance commitment and responsibility, increasing the likelihood of supportive behaviours (Jang and Feng 2007). Additionally, interactions with residents strengthen place attachment and social identity (Kyle et al. 2004b; Ramkissoon et al. 2013). These interactions foster emotional bonds, reciprocity, and a sense of obligation, all of which are more likely to translate into WTP.

H3: Engagement (actual time and money already spent) positively affects WTP.

H4: Interacting with the locals positively affects WTP.

2.3. Socio-Demographic Conditions

Socio-demographic factors also influence tourists’ capacity and WTP. Classic environmental valuation and tourism economics studies highlight income as a key determinant of WTP (Onofrio et al. 2025). Other variables—age, sex, education, and marital status—have shown significant effects across contexts (Jeon and Yang 2021). Higher-income individuals generally exhibit greater willingness to contribute to heritage or environmental protection (Hanli et al. 2023), whereas older tourists may demonstrate lower WTP (Onofrio et al. 2025). Furthermore, residential proximity to a destination tends to increase the perceived responsibility for heritage conservation (Wei et al. 2021).

H5a: Age affects WTP.

H5b: Gender affects WTP.

H5c: Marriage situation affects WTP.

H5d: Household income affects WTP.

H5e: Address affects WTP.

Building on the above assumptions and theoretical foundations, this study proposes an integrated WTP model that incorporates psychological pathways, behavioural investment, and socio-demographic conditions. The model aims to elucidate the mechanism by which tourists support cultural landscapes through Furusato Nozei (Figure 1).

3. Materials and Methods

3.1. Study Area

Shibamata (Figure 2), located in Katsushika Ward, Tokyo, is a historic district renowned for its traditional streets and the Shibamata Taishakuten Temple. The area integrates tangible elements, such as historic architecture and streetscapes, with intangible components, including local festivals, rituals, and community narratives, to form a distinctive cultural landscape. As a popular tourist destination, Shibamata attracts visitors for sightseeing, cultural experiences, and interactions with the local communities. Simultaneously, residents actively participate in heritage preservation and festival management. This interplay between tourism, community engagement, and cultural heritage renders Shibamata an ideal case for examining the mechanisms linking visitor behaviour, WTP, and sustainable cultural landscape management.

3.2. Data Acquisition

A questionnaire survey targeting tourists who had visited Shibamata was conducted in February 2023, in collaboration with Freeasy Questionnaire Inc., a professional online survey company in Japan, with over 13 million registered part-time respondents (https://freeasy24.research-plus.net/). In the preliminary screening phase, 4,000 randomly selected respondents were asked whether they had visited Shibamata in the past two years. Of these 760 confirmed their visits. From this subset 250 male and 250 female respondents were randomly selected for the survey. The questionnaire comprised three sections. The first section collected socio-demographic information (Table 1). The second section measured the latent variables included in the proposed model (Table 2). The third section assessed WTP through Furusato Nozei, asking, ‘What is your opinion about utilising the Furusato Nozei system (hometown tax donation) for the conservation of Shibamata’s cultural landscape and regional development?’ Respondents were required to select one of four options: Not interested in Furusato Nozei; Interested but have not considered it; Already donated to other municipalities, but interested in donating to Shibamata; Intend to donate.

Unlike monetary valuation, this study focuses on how the institutional context transforms willingness into actual action, making a categorical, context-specific measure of WTP more appropriate. The participants were informed about the survey’s purpose and provided consent for utilising their responses. Five hundred valid responses were obtained after screening and removing invalid ones, yielding an effective response rate of 100%.

3.3. Socio-Demographic Characteristics

Table 1 summarises the respondents’ socio-demographic characteristics. The sex ratio was balanced (50% male and 50% female). The largest age group was 31–50 years. More than half of the respondents were married (56%), and over 50% reported an annual household income below 7 million JPY. Additionally 46.2% of respondents resided in Tokyo.

3.4. Questionnaire Design

The second section measured latent variables, including motivation, destination image, satisfaction and loyalty, interaction with locals, and engagement. All constructs were assessed using a five-point Likert scale ranging from ‘strongly disagree’ (1) to ‘strongly agree’ (5). The draft questionnaire was reviewed by two PhD students specialising in urban planning and landscape architecture. A pilot test was conducted with six tourists who had previously visited Shibamata. Based on their feedback, minor revisions were made to improve clarity and contextual appropriateness. The final measurement items and their corresponding references are listed in Table 2.

3.5. Statistical Analysis

This study employed partial least squares structural equation modelling (PLS-SEM) for empirical analysis. PLS-SEM is particularly suitable for exploratory research because it enables the prediction of key target constructs and the identification of important drivers. Data were analysed using SmartPLS 4 (version 4.1.1.2).

Prior to model estimation, categorical socio-demographic variables were dummy-coded: female = 1, male = 0; married = 1, unmarried = 0; Tokyo = 0, other regions = 1. Annual household income (10,000 JPY) was treated as a continuous variable by assigning the midpoint of each income bracket (e.g. an income range of 100–200 was coded as 150).

4. Results

The results are presented in the following sections. First, the measurement model was assessed. Second, the model fit and explanatory power of the structural model were examined. Finally, the hypotheses were tested.

4.1. Measurement Model

The measurement model was evaluated in terms of indicator reliability, internal consistency reliability, convergent validity, and discriminant validity (Hair et al. 2022). Table 3 reports the standardised factor loadings, Cronbach’s alpha (α), composite reliability (CR), and average variance extracted (AVE) for each latent construct. All indicator loadings exceeded the recommended threshold of 0.70, while α and CR values were greater than 0.70, indicating satisfactory internal consistency reliability. All the AVE values were greater than 0.50, confirming convergent validity. Before testing the structural relationships, collinearity was assessed using variance inflation factors (VIF). As shown in Table 3, all the VIF values were well below the conservative threshold of 5 (Hair et al. 2019)—multicollinearity was not a concern.

Discriminant validity was assessed using the Heterotrait–Monotrait ratio (HTMT). As reported in Table 4, the square root of the AVE for each construct was generally higher than its correlation with other constructs, indicating adequate discriminant validity. For HTMT, all values were below the conservative threshold of 0.90 (Henseler et al. 2015), supporting discriminant validity among the constructs. As all criteria were satisfied, and the excess was marginal, discriminant validity was considered acceptable for the purposes of this study.

4.2. Structural Model

To assess the model fit, the standardised root mean square residual (SRMR) and discrepancy measures were examined. The results indicate that the SRMR values were 0.050 for the saturated model and 0.060 for the estimated model, both below the recommended threshold of 0.08 (Henseler et al. 2014; Hu and Bentler 1999), suggesting an acceptable model fit.

The discrepancy measures also provided further support. The d_ULS value was 0.806 for the saturated model and 1.188 for the estimated model, while the d_G values were 0.392 and 0.401, respectively. These results did not indicate problematic model misspecification.

Additionally, the NFI values (0.880 for the saturated model and 0.878 for the estimated model) approached the commonly recommended cutoff of 0.90, further suggesting an adequate model fit. Although NFI is less emphasised in PLS-SEM than in SRMR, its values provide additional evidence for global model adequacy (Hair et al. 2019). Considered together, these results demonstrate that the revised model exhibits an acceptable level of global fit, providing a reliable basis for subsequent structural model analyses.

4.3. Validation of Hypotheses

To test the hypotheses, the standardised path coefficient β of the structural model was estimated to account for the strength of the effect of exogenous variables on endogenous variables (Figure 3, Table 5). When the path coefficient of a potential exogenous variable is close to 0, it indicates a weak influence, while the closer it is to 1 or −1, the stronger its influence on the endogenous variable. furthermore, the significance of the paths was tested using the bootstrap procedure, in which the p-value determined the significance of the hypothetical path. As shown in Table 5, most of the hypotheses presented in Section 2 were statistically supported (p < 0.01).

The structural model demonstrated satisfactory explanatory power, with the endogenous construct WTP accounting for 18.3% of the variance (R² = 0.183). Regarding hypothesis testing (Table 5), most of the proposed relationships were supported. Motivation significantly influenced destination evaluation (β = 0.746, p < 0.001), and destination evaluation exerted an effect on WTP (β = 0.091, p = 0.035). Similarly, engagement (β = 0.186, p < 0.001) and interaction with locals (β = 0.221, p < 0.001) significantly enhanced WTP. Among demographic factors, age was negatively associated with WTP (β = -0.174, p < 0.001), whereas marriage status showed a positive effect (β = 0.212, p < 0.05). Conversely, sex, household income, and address were not significant predictors of willingness to pay.

The mediation analysis revealed that destination evaluation played a significant mediating role in linking motivation to WTP (β = 0.068, p < 0.05). Specifically, motivation exerted an indirect influence on WTP through destination evaluation—tourists’ motivational factors shape their WTP primarily by enhancing their destination evaluation. As only one indirect pathway was identified, the total and specific indirect effects were identical (Table 6). These results underscore the central role of destination evaluation as a conduit through which motivational factors affect tourists’ payment intentions.

¹ ∗p < 0.05., ∗∗p < 0.01, ∗∗∗p < 0.001.

5.1. Psychological, Behavioural, and Socio-Demographic Pathways to WTP

This study verified the core roles of psychological pathways, behavioural investment, and socio-demographic conditions in predicting tourists’ WTP. The results demonstrate that, at the psychological level, motivation significantly enhances destination evaluation (β = 0.746, p < 0.001), increasing WTP (β = 0.091, p = 0.035). This sequential relationship provides structured empirical evidence for tourism behaviour research (Chen and Phou 2013; Prayag et al. 2017). These findings are consistent with previous theories: motivation is an antecedent of travel behaviour (Crompton 1979; Yoon and Uysal 2005) and a driving force shaping tourists’ destination evaluation (Chen and Phou 2013; Prayag et al. 2017). Even in the context of cultural landscape conservation, tourists’ WTP reflects value judgements derived from cognitive–affective processing, aligning with destination image theory, which emphasises that cognitive and affective images jointly shape attitudes and behaviours (Baloglu and McCleary 1999; Chi and Qu 2008).

With respect to behavioural investment, tourists’ actual contributions during the travel process also significantly enhanced their WTP. Time and monetary investment (β = 0.186, p < 0.001) and interaction with local residents (β = 0.221, p < 0.001) positively influenced tourists’ willingness to support cultural landscape conservation. These findings are consistent with the sunk-cost effect(Arkes and Blumer 1985) and place attachment research (Kyle et al. 2004a; Ramkissoon et al. 2013): individuals who have already invested resources in or developed emotional bonds with a place are more likely to sustain or extend their experience through economic contributions. Interaction with residents strengthens the social significance of cultural landscapes and transforms tourists from ‘spectators’ into ‘co-creators’, making their payment behaviour more strongly rooted in emotional belonging and a sense of responsibility (Briedenhann and Wickens 2004; Prahalad and Ramaswamy 2004; Ramkissoon et al. 2013).

Regarding socio-demographic conditions, this study found that marital status and age exerted significant effects on WTP (β = 0.174, β = –0.140), whereas sex, income, and residential location showed no significant influence. This finding contradicts numerous environmental economics studies, in which income is a primary predictor of WTP (Carson et al. 2003; Mitchell and Carson 2013). We argue that this paradox stems from the institutional design of the Furusato Nozei system itself (Hasegawa 2017; Rausch 2019). The tax deduction mechanism effectively neutralises the income effect for many donors because contributions up to a certain limit have a near-zero marginal cost. This shifts the decision from ‘Can I afford this?’ to ‘Do I want to redirect my existing tax liability for this purpose and receive a gift?’. This institutional feature reshapes economic behaviour, making non-economic factors, such as emotional attachment and social roles, critically more important than pure financial capacity (Center 2020). Married individuals with stronger family and social responsibilities may be more inclined to assume cultural protection responsibilities, whereas the mobility and short-term orientation of younger cohorts may weaken their willingness to make long-term contributions (Devaux et al. 2018).

5.2. Mechanism Operation and Policy Implications Under the Furusato Nozei System

The mediation analysis highlighted that motivation influenced WTP primarily through destination evaluation—policy interventions should strengthen the evaluative perception of destinations rather than relying solely on fiscal incentives. One actionable approach is to design altruistic framing campaigns (e.g. ‘Your donation restores one meter of a temple wall’), which directly connect motivational drivers with positive evaluations of the locality. Such message framing has been shown to enhance prosocial behaviours by appealing to moral satisfaction rather than material rewards (S. Li et al. 2022).

In terms of behavioural investment, tourist–resident interactions enhance WTP and foster long-term commitment to preservation activities—conservation extends beyond physical restoration to social reproduction and experiential participation (H. Li et al. 2023). These results suggest that participation-based mechanisms can operate as commitment devices that transform temporary experiences into long-term fiscal engagements. For example, Furusato Nozei projects allow donors to adopt a rice terrace, receive annual reports with photos, or participate in seasonal farming festivals. These measures allow tourists to form tangible, recurring bonds with the destination, effectively reducing the intention–behaviour gap and sustaining contributions over time.

Socio-demographic differences further indicate that a tailored policy design is necessary (Feifei and Salleh 2025). While married individuals may respond to initiatives emphasising family responsibility and heritage transmission, younger cohorts may be more engaged through short-term and digitalised programmes (e.g. virtual heritage tours linked to micro-donations). This differentiation increases inclusivity and maximises policy efficiency by aligning motivational structures with destination evaluation pathways.

5.3. International Comparisons and Broader Implications for Cultural Landscape Financing

Building on the empirical insights from Japan’s Furusato Nozei system, this section situates the system within a global context by comparing it to two other heritage funding mechanisms: the United Kingdom’s National Lottery Heritage Fund (NLHF) and Korea’s Hometown Love Donation System (HLDS). The comparison (Table 7) highlights differences in funding sources, operational mechanisms, donor incentives, and governance and identifies the unique features of the Japanese system that may inform international practice.

While NLHF relies on lottery revenues channelled into centrally managed heritage grants, Furusato Nozei and HLDS operate as decentralised donation systems in which individuals can directly support municipalities of their choice. This design enables a stronger emotional engagement between donors and localities, reflecting the relational dimension of financing that extends beyond fiscal transfers. Donor incentives also diverge; Furusato Nozei and HLDS combine tax deductions with tangible return gifts, embodying ‘impure altruism’ by aligning private benefits with public contributions, whereas NLHF offers only indirect social benefits through lottery participation. Governance structures further differentiate the systems. Local governments manage Furusato Nozei and HLDS under national regulation, ensuring accountability while preserving local autonomy, whereas NLHF follows a centralised governance model that prioritises strategic national planning but limits donor influence over project allocation.

Cultural underpinnings beyond these institutional contrasts are crucial. Japan’s Furusato Nozei is embedded in the traditions of reciprocity and local–urban linkages, transforming tax contributions into acts of place attachment. The UK model reflects a welfare-state legacy in which heritage is framed as a collective national good rather than a local responsibility. Korea’s HLDS, introduced in 2023, mirrors the Japanese design but is closely tied to regional equity policies, highlighting the role of institutional borrowing and adaptation.

Considered together, these comparisons underscore the distinctiveness of Japan’s Furusato Nozei system: it successfully combines decentralised donor choice, material incentives, and local governance to channel individual contributions into cultural landscape conservation. For countries seeking to design sustainable financing mechanisms, three lessons emerge: (1) aligning individual incentives with public objectives to foster participation; (2) balancing local autonomy with national oversight to ensure accountability; and (3) integrating psychological and material motivators to bridge the intention-behaviour gap. Ultimately, cultural landscape financing should be understood as a fiscal arrangement and a sociocultural institution that reflects and mobilises local values, attachments, and identities.

5.4. Limitations and Future Research Directions

Although this study validates the effects of psychological factors, behavioural investment, and socio-demographic conditions on tourists’ WTP, several limitations should be acknowledged and addressed in future research. First, a primary limitation is the potential for hypothetical bias, a well-documented issue in contingent valuation studies where respondents may overstate their true WTP because the question is hypothetical and involves no real financial consequences. Therefore, our WTP estimates should be interpreted as a potential upper bound of actual WTP. This lack of real-world consequences may also contribute to our finding of income insignificance; if the payment question is not perceived as a real economic choice, the relevance of income naturally diminishes. Although the model’s explanatory power is limited, it reflects the multidimensional complexity of cultural landscape financing behaviour, highlighting the need for future studies to incorporate additional factors—institutional incentives, community engagement, and cultural education.

Second, this study focuses on Japan’s Furusato Nozei system, which provides a unique institutionalised case for supporting cultural landscape financing. However, the system is inherently context-specific and dependent on national fiscal and cultural conditions, and its mechanisms may not be directly transferable to other countries or regions. Future research could examine the applicability of such institutionalised WTP mechanisms under different fiscal policies, cultural contexts, and tourism management systems and investigate how varying institutional arrangements influence tourists’ behaviours.

Finally, this study relies primarily on survey data to capture tourists’ psychological states and behavioural investments. Future research could incorporate actual behavioural data, longitudinal tracking, or experimental interventions to validate the dynamic relationship between WTP and concrete conservation actions.

6. Conclusions

This study examined tourists’ WTP for cultural landscape conservation in Shibamata, Tokyo, through Japan’s Furusato Nozei system. By integrating psychological pathways, behavioural investments, and socio-demographic conditions into a structural equation model, we identified the mechanisms through which tourists’ motivations and experiences are transformed into fiscal support for heritage protection.

The results revealed three key findings. First, tourists’ motivations affect WTP primarily through destination evaluation, highlighting the importance of strengthening positive perceptions of heritage sites. Second, behavioural investments, especially interactions with residents, significantly increase WTP—cultural landscape conservation is a financial issue and a social and experiential process. Third, demographic factors such as marital status and age exert notable influences, whereas income does not, reflecting the unique institutional design of Furusato Nozei, which reduces the role of financial constraints.

Theoretically, this study advances cultural landscape research by incorporating the concepts of institutionalised impure altruism and the intention-behaviour gap into heritage financing. Empirically, this study provides quantitative evidence from tourists’ perspectives on how cultural landscapes can be sustained through innovative funding mechanisms. Practically, these findings imply that heritage policymakers and local governments should emphasise participatory programmes, experiential engagement, and tailored communication strategies to convert tourists’ intentions into long-term fiscal contributions.

Future research could address this study’s limitations by incorporating experimental or behavioural data, examining cross-cultural contexts, and exploring the scalability of institutionalised donation systems beyond Japan. Such efforts would enhance our understanding of sustainable cultural landscape financing in an era of fiscal austerity.