ECONOMIC VALUATION OF CULTURAL HERITAGE: THE IMPORTANCE OF DETERMINANTS OF DEMAND

Abstract

Economic valuation of cultural heritage is challenging because of the specific nature of culture and heritage. Different methods have been developed and used in past few decades and those, among other things, result in deriving a demand function for specific site. Previous research and studies of cultural heritage sites mostly used different regression models to estimate the importance of certain determinants of demand using different methods. The aim of this paper is to explore and identify determinants of demand for a few cultural heritage sites in Herzegovina, south part of Bosnia and Herzegovina, and asses their importance using Structural Equations Modelling (SEM). One of the main advantages of SEM is that it can be used for variables that are difficult to quantify which is important in case of cultural heritage. This method was selected because it is appropriate to study the relationship between concepts and specify structural and measurement model for all selected locations. By comparing results of analysis on different sites in Herzegovina conclusions can be made on importance of specific demand factors and that information is useful for local authorities while creating strategies and plans for development of tourist industry.

ABSTRACT

Economic valuation of cultural heritage is challenging because of the specific nature of culture and heritage. Different methods have been developed and used in past few decades and those, among other things, result in deriving a demand function for specific site. Previous research and studies of cultural heritage sites mostly used different regression models to estimate the importance of certain determinants of demand using different methods. The aim of this paper is to explore and identify determinants of demand for a few cultural heritage sites in Herzegovina, south part of Bosnia and Herzegovina, and asses their importance using Structural Equations Modelling (SEM). One of the main advantages of SEM is that it can be used for variables that are difficult to quantify which is important in case of cultural heritage. This method was selected because it is appropriate to study the relationship between concepts and specify structural and measurement model for all selected locations. By comparing results of analysis on different sites in Herzegovina conclusions can be made on importance of specific demand factors and that information is useful for local authorities while creating strategies and plans for development of tourist industry.

Keywords: cultural heritage site, determinants of tourist demand, measurement model, SEM, structural model

1. INTRODUCTION

Cultural heritage is considered as an asset that has cultural, historic and socio-economic significance in a contemporary society. It is the legacy of physical artefacts and intangible attributes of a group that are inherited from previous generations, kept in the present and assigned for the future. (Nijkamp 2012). According to UNESCO cultural heritage includes "artefacts, monuments, a group of buildings and sites, museums that have a diversity of values including symbolic, artistic, aesthetic, ethnological or anthropological, scientific and social significance" (UNESCO, 2009).

Heritage as a resource can bring various social and economic benefits to different stakeholders. (Dumcke, Gnedovsky 2013). Economic valuation of heritage, according to Mourato and Mazzanti (2002) may, among other things, help to make the decisions and introduce policies for different cultural destinations to increase profits or access, to evaluate pollution, to assess tourism effects, type and degree of conservation measures etc. Economic value of heritage consists of use and non-use values. Use value is the direct value of the assets" services by those who consume the services, for instance the tickets to entry a site. Non-use value is a value for those who experience benefits of cultural heritage as a public good and it includes existence, option and bequest value that are not observable in market transactions. (Thorsby 2002). To measure values associated with cultural heritage two groups of methods have been developed: revealed and stated preference methods.

2. REVIEW OF LITERATURE

Economic valuation of heritage may also help to estimate the demand for an asset and to predict future demand trends, potential demand of non-visitors, price and income elasticities of demand for cultural asset etc. (Mourato, Mazzanti 2002). One of the stated preference valuation methods is Travel Cost Method (TCM) that values cultural heritage by the amount that individual travelling to a particular site is willing to pay for the values of goods and services provided at the site (Armbrecht 2014). TCM is the most appropriate to use for valuing already existing places and for estimation of demand in the absence of reference prices (Fonseca and Rebelo 2010). The travel costs to a specific site act as a price of visit, so the associated travel cost presents a willingness to pay for the cultural heritage good. (Nijkamp 2012). Demand for a recreational destination, natural or cultural one, according to TCM is inversely related to travel costs of a visitor (Merciu, Petrisor and Merciu, 2021). In the analysis of demand curve besides travel costs, there are other factors, that might affect the number of visits to a site such as: trip costs to substitute sites, experience at the site, income and age of visitors, personal preferences etc. (Yung, Yu and Chan 2013, Kaminski, McLoughlin and Sodagar 2007). TCM method has been applied for valuation of specific heritage and cultural sites all over the world but still less than some revealed preference methods. Most of those studies focused on deriving a demand curve and calculating consumer surplus using the demand curve for valuation of sites. Halkos et. al. (2024) used meta regression analysis on 85 studies conducted in the period of 1995-2022 that revealed willingness to pay values (WTP). Overall, the willingness to pay was lower in European countries compared to non-European ones. For European studies factors that were identified as important and had significant effect on willingness to pay and therefore on demand were: education, esthetic and spiritual cultural value. For non-European studies income, intangible heritage goods with skills and oral tradition had significant impact. Europeans are more attracted by tangible cultural heritage while non-Europeans are more influenced by oral traditions. Education also determines WTP in Europe and income in non-European countries. There are studies that focused on specific countries' heritage sites or cultural events. One of those 1$ a study on the value of cultural heritage - the historical center of Bucharest. Results gained through TCM lead to conclusion that tourists' motivation, the quality of recreational experience, desire to revisit historic site and income of visitors affect the demand of tourists (Merciu, Petrisor and Merciu 2021). A study on cultural heritage sites in Jordan included nine different sites and explored willingness to visit (Abuamoud et. al. 2014). It was found that income, education, visiting other country, variety seeking and reason for visit were the factors of tourists" willingness to travel. The research has shown that income has a significant positive effect on willingness to visit. Costs in Jordan were also found to be significant with negative effect. If visitors came for business, it is less likely they would visit cultural heritage sites so that variable shown significant negative effect. Tourists visiting other countries are less likely to visit while education has a positive effect on the number of visits.

Bedate, Herrero and Sanz (2004) discussed potential application of demand curve in terms of calculating consumer surplus for a specific cultural good, allowing for forecasts of possible tax effects, grants or change in prices which is important for relevant authorities for provision and maintenance of cultural heritage sites or events. They used four case studies in Spain (cultural artistic event, village, museum, cathedral). Results have shown that the preferences of tourists for four different case studies are strongly correlated to the touristic appeal of each area. According to them, the number of visits indicate intensity of individuals' preferences regardless of the cultural significance of the sites. The study on museum in Altamira, Spain that used two variations of TCM method: individual and zonal one showed that travel costs were negatively related to number of visits and that the older the visitor the higher number of visits for individual TCM model. The zonal method resulted in recognizing significant positive influence of income of visitors on their number of visits as well negative effect of travel cost (Torres-Ortega et. al. 2018). Tourkolias et. al. (2015) calculated consumer surplus for Poseidon temple in Greece. Several regression models were used with different approaches to calculation of travel costs. Their full model shows that visits to the sites are positively related to age of visitors and that women, visitors who are not freelancers, visitors who revisit the monument, those who combine the visit to other activities in the region visit more the site. The model also identified travel costs having a negative effect on visits. In case of region in Portugal classified by UNESCO as World heritage site application of TCM showed that variables of gender, educational level and travel cost were statistically significant (Fonseca and Rebelo 2010). The results indicate a negative relation between travel costs and the number of visits. Women and more educated visitors tend to visit the site more. The study on historic building in Nigeria showed that value placed by visitors is higher than the price charged that is important for relevant authorities for price forming. The results of this study show travel costs were statistically significant with negative effect on the number of visits (Egbenta 2017). Vicente and de Frutos (2011) discovered that travel costs have significant negative effect on number of visits for the exhibition in Spain and that income has positive effect on number of visits. Studies that used TCM focused on assessing willingness to pay and importance of demand factors since those can help institutions and government authorities in creating of different policies related to cultural heritage in terms of using cultural heritage as an important resource in tourist offer as well as its preservation.

3. METHODOLOGY

3.1. Case studies

Four places in Herzegovina were chosen for this study: Mostar, Trebinje, Pocitelj and Глупо. According to the world travel magazine Lonely Planet, Mostar was ranked 4th among the world's best cities to visit in 2024. (https://nlinfo.ba). Mimar Harudin's project resulted in the construction of a bridge in 1566, known as the Old Bridge in Mostar. Through the centuries, it connected the banks of the Neretva and became the main symbol of the city on the Neretva (Mostar). Unfortunately, it was destroyed during the war on November 9, 1993. Thanks to the efforts of the Bosnian authorities, as well as the international community, the restoration of the Old Bridge was successfully completed in 2004. The Old Bridge is inscribed on UNESCO's World Heritage List "..as an exceptional and universal symbol of the coexistence of communities of different cultural, ethnic and religious backgrounds..." (UNESCO 2005). Trebinje, Pocitelj and Глупо are cities that have a rich cultural heritage from different historical eras, especially from the Ottoman period. During their historical development, these cities had strategic importance, which certainly contributed the most to the construction of public and private buildings that have been preserved to this day and form the core of their historical city areas. Trebinje developed under different cultural influences, so today in this city you can see elements of the Ottoman and Austro-Hungarian legacy.

The development of the historic city center began in the 17th century, and the most intensive construction took place in the first half of the 18th century. During the Austro-Hungarian administration, Trebinje was a military center surrounded by fortifications that still dominate the landscape of this city. In the historical city area of Trebinje, three spatial units can be distinguished according to the period of creation, urban matrix and architectural styles: the Old Town within the walls of Kastel (from the 15th century), the settlement of Кт$ or Omanovica Mahala on the slopes north of the Old Town (from the 18th century) and zone of the inner city center west and south of Stari Grad (since the end of the 19th century).! Pocitelj was created in the late Middle Ages as a strategically important fortress. The era of greatest development was in the Ottoman period, especially from the 16th to the 18th century. During this period, the most important public and monumental buildings such as mosques, madrasa, hammam, han, clock tower, as well as residential buildings were created. With the Austro-Hungarian occupation of Bosnia and Herzegovina in 1878, it lost its previous importance, which is why it gradually decays. Pocitelj presents one of the few urban ensembles in Bosnia and Herzegovina preserved in their integrity to the present time developed through the several phases of history, beginning with the medieval period.? This is why it is often called an open-air museum. Livno is one of the cities where the development of civilization can be traced back to the oldest times. There are numerous traces of cultural heritage in its area from prehistory, antiquity, the Middle Ages, and the Ottoman era. It experienced its greatest development during the 16th and early 17th centuries, when it was the military and political center of the Sanjak of Klis. The most significant buildings built in the settlement are the mosques, of which the dome-shaped mosques are the representative buildings of the highest range of Ottoman architecture in Bosnia and Herzegovina." Among the more important buildings from the later period, we should mention the Franciscan Monastery of Gorica, which was built in the 19th century, and from whose monastery collection the Franciscan museum and gallery of Gorica Livno developed.

3.2. Data and Methods

Primary data for this research were collected by direct survey of visitors from Bosnia and Herzegovina and other countries in the period June 2023-July 2024. The survey was conducted in the territory of Bosnia and Herzegovina on the following locations: the city of Mostar, Livno, Trebinje and Pocitelj. The questions in the survey related to socio-demographic characteristics of visitors and travel costs they incurred. To identify relevant demand factors in selected locations structural equation modelling (SEM) method was used. For preparing data first Confirmatory Factor Analysis (CFA) was applied with a graphical presentation of all variables and corresponding relationships. Variables come in two forms: latent and manifest. Latent variables were introduced as hypothetical constructs, and they cannot be measured directly. Manifest variables are directly observed through answers to survey questions and conclusions on latent variables are based on manifest ones. Modelling with structural equations enables setting one concept model including cause-and-effect relationships between a set of latent variables and relationships between latent and associated manifest variables The measurement model is a part of the SEM model and refers to the relationships between manifest and latent variables, while the structural model shows all the dependence relationships exclusively between latent variables (Hair et al., 2010). By model estimation, relationship" empirical values between the latent themselves as well as between manifest and latent variables were obtained.

3.3. The model

For the purposes of making the demand function and detecting the key determinants of demand, structural equation modeling was performed using the CB SEM (Covariance Based SEM) approach. The first step of the mentioned approach is the specification and construction of the path model. Figure no. 1 shows the constructed trajectory model.

After construction of measurement model, the reliability of the measuring instruments was tested by calculating Cronbach's alpha and did reduction of date. The most widely used method to test reliability is the Cronbach coefficient alpha. For the following constructs and their associated manifest variables, the Cronbach's alpha was greater than 0.70, so it was established that should remain in the analysis:

Manifest variables for Measuring instruments for Socio-demographic characteristics (SDC): Age, Sex, Level of Education (Ed)

Manifest variables for Profile (PROF): Montly income of all members of household (M1), Motive for visit (Mv), Type of visitor (Tv)

Manifest variables for Direct costs (DC): Means of transportation used to arrive at destination (Mot), Travel cost from home to destination (e.g. fuel costs, tolls, airplain tickets, etc.) (Tc), The costs of stay at destination and visiting cultural heritage monuments (e.g. museum tickets, guides" fee, cost of accomodation or total amount of costs) (Sc)

- Manifest variables for Visits: Time spent on visiting cultural heritage monuments at destination (Ts), Visit dynamics (Vd), Enjoyment of stay at destination (proportion of enjoyment visiting cultural heritage monuments compared to total enjoyment of stay at destination) (Es).·

The model was set for four localities: Mostar, Глупо, Potitelj and Trebinje. The final model contained 4 latent and 12 manifest variables for all destinations, and it was specified based on the data of 198 visitors to Mostar (The Old Bridge), 216 visitors to Livno, 121 visitors to Pocitelj and 108 visitors to Trebinje.

The formed model was the basis for assessing how much the empirical data support the set assumptions about three groups of factors (presented as latent variables) on the number of visitors to individual localities. Causality analysis estimated how empirical data support theoretical assumptions about the influence of socio-demographic characteristics of visitors, profile of visitors and direct costs to the number of visitors.

4. RESULTS

The set models are recursive because all relations in the structural model are one-way. Estimation of links in the structural SEM model was carried out on the basis of path coefficients and hypothesis testing that the path coefficients are significantly different from zero. A path coefficient value close to +1 indicates a strong positive or negative association, and the closer the coefficient is to 0, the weaker the association. A higher value of the path coefficient indicates a greater influence on the endogenous variable towards which the arrow 1s pointing. For interpretation and interpretation of the results, these coefficients are interpreted in a relative relationship. In Tables No. 1, 2, 3 and 4 values of unstandardized coefficients are given with associated standard errors and p-values. For all the mentioned factors, the hypothesis, that the evaluated regression coefficients are statistically significantly different from zero, 1s accepted because p<0.05 for the localities of Mostar and Livno. For these localities, the respondents dominantly decided that it was their primary destination. This means that socio-demographic factors, the profile of respondents and direct costs have a statistically significant effect on the number of visitors with different intensity of the achieved influence. An identical conclusion is not relevant for the localities of Trebinje and Pocitelj. From the data presented, the significance of two groups of factors was established. In this case socio-demographic characteristics and the profile of the respondents have a statistically significant effect on the number of visitors. The influence of direct costs on number of visitors did not prove to be statistically significant. A typical definition of visitors to Trebinje and Pocitelj is that for them the mentioned localities are not primary destinations and that they are predominantly visitors to multiple destinations.

Monthly income of all household members, Motive of visit and Type of visitor contribute statistically significantly to the explanation of Profile of Visitors (the size of the coefficient of determination is (74% of the the total variability within the Visitors variable can be explained through the influence of the PROF)

Means of transport for arriving at the destination, Travel expenses from home to destination (e.g. fuel costs, tolls, plane tickets, etc.) and Costs of staying at the destination and visiting cultural heritage monuments (e.g. Museum tickets, guides fee, accomodation costs or total amount of costs) make a statistically significant contribution to Direct Costs (14% of the the total variability within the Visitors variable can be explained through the influence of the DC)

Livno

Age, Sex and Level of Education statistically significantly affect the Socio-demographic characteristics of visitors (24,8% of the the total variability within the Visitors variable can be explained through the influence of the SDC)

Monthly income of all household members, Motive of visit and Type of visitor contribute statistically significantly to the explanation of Profile of Visitors (the size of the coefficient of determination is (75,8% of the the total variability within the Visitors variable can be explained through the influence of the PROF)

Means of transport for arriving at the destination, Travel expenses from home to destination (e.g. fuel costs, tolls, plane tickets, etc.) and Costs of staying at the destination and visiting cultural heritage monuments (e.g. Museum tickets, guides fee, accomodation costs or total amount of costs) make a statistically significant contribution to Direct Costs (18,3% of the the total variability within the Visitors variable can be explained through the influence of the DC)

Trebinje

Age, Sex and Level of Education statistically significantly affect the Socio-demographic characteristics of visitors (32,1% of the the total variability within the Visitors variable can be explained through the influence of the SDC)

Monthly income of all household members, Motive of visit and Type of visitor contribute statistically significantly to the explanation of Profile of Visitors (the size of the coefficient of determination 1s (40,5% of the the total variability within the Visitors variable can be explained through the influence of the PROF)

Pocitelj

Age, Sex and Level of Education statistically significantly affect the Socio-demographic characteristics of visitors (45,4% of the the total variability within the Visitors variable can be explained through the influence of the SDC)

Monthly income of all household members, Motive of visit and Type of visitor contribute statistically significantly to the explanation of Profile of Visitors (the size of the coefficient of determination 1s (54,6% of the the total variability within the Visitors variable can be explained through the influence of the PROF).

The analysis and the collected data provided a framework for the quantification of Number of visits using the following regression equation so that

5. CONCLUSION

Cultural heritage may be an important asset for tourism industry development in a particular region or a country. This paper used TCM method to assess demand factors for four sites in Bosnia and Herzegovina using Structural Equation Modelling. Travel costs have a significant negative effect on the number of visits to two sites: Mostar and Livno while for the other two locations not. A probable reason for this could be that one of the limitations of TCM is the treatment of travel costs in case of multipurpose trips and those two locations are not primary ones for visitors. For all four sites the results showed that age, sex, level of education, monthly income of all household members, motive of visit and type of visitor contribute to the explanation of socio-demographic characteristics and profile of visitors, in other words are key factors of demand. Assessing factors of demand can be of use to local authorities and government in setting policies for tourism development and increase in number of touristic visits.

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Footnote

1http://aplikacija.kons.gov.ba/kons/public/uploads/odluke_bos/Trebinje%20gradsko%20podrucje%20BOS.pdf

2 https://whc.unesco.org/en/tentativelists/5092/

3http://aplikacija.kons.gov.ba/kons/public/nacionalnispomenici/show/2549?return=&search=idgrad:undefined:59

4 The Cronbach's alpha for variables: Ta - Type of accommodation, VW - Visiting destination with ..., Td - Town departure, La - Alternative localities was less than 0.60.