Valuing visitor’s willingness to pay for green tourism conservation: A case study of Bukit Larut Forest Recreation Area, Perak, Malaysia

ABSTRACT

Bukit Larut, previously known as ‘Maxwell Hill’, is declared a Forest Recreation Area as part of green infrastructure that enhances the quality of life of people and boosts green tourism. However, due to the lack of a market, it is difficult to quantify the economic value of green tourism in monetary terms for these resources. Using the Contingent Valuation Method (CVM), this study aims to determine the willingness to pay (WTP) for green tourism conservation in the Forest Recreation Area of Bukit Larut, Perak. In this study, a total of 250 respondents were collected via a questionnaire distributed at random. This study assigned five different bid prices, MYR5, MYR10, MYR15, MYR20, and MYR25. The Logit Model estimates the visitor’s WTP for green tourism conservation. This study indicates that most visitors are willing to pay a certain amount for green tourism conservation, driven by race, religion, age, marital status, education level, and income. Regression analysis showed that the estimated mean visitor willingness to pay is MYR 4.69, whereas the median WTP is MYR 3.68. Therefore, it was determined that Bukit Larut’s conservation initiatives were viable for future green tourism. The financial resources would assist the management in allocating funds for conservation and maintenance.

KEYWORDS:

• green tourism conservation
• willingness to pay
• Contingent Valuation Method
• Bukit Larut

Introduction

Sustainable tourism has emerged as a significant consideration in tourism planning, environmental studies, and sustainable tourism in tourism products (UNWTO, 2014). Faulkner et al. (2000) categorized rural tourism, ecotourism, and green tourism as tourism frequently related to sustainability. In this context, ‘green tourism’ is an active strategy to ensure sustainable tourism development based on Agenda 21 on Tourism: towards environmentally sustainable development (Li et al., 2015). Han et al. (2010) define ‘green’ as actions that could significantly reduce the adverse effects of human activity on the environment. In that sense, public participation in protecting the environment is significant to ensure that the environmental resources can be sustained for the next generation (Asri & Musa, 2021).

Tourism is among the numerous enterprises with solid ties to the natural world and the environment. However, mixed with second-class management, tourism growth has adverse implications for nature, communities, cultures, and land degradation (Budeanu, 2005). The emerging awareness of this problem has triggered alternative tourism, such as green tourism, natural tourism, ecotourism, and rural tourism. Green tourism was described by the Japanese government in 1992 as ‘recreational activities to enjoy the nature and culture of tourist destinations while also interacting with communities in rural areas with the natural landscape’ (Tran & Xuan, 2021). They emphasize the potential for green tourism to play a significant role in environmental management. As a result, ecotourism has been a popular tourist activity in many developing nations, including Malaysia, where the government plans to promote the country as an ecotourism destination. When the Malaysian Ministry of Tourism, Arts, and Culture (MOTAC) is tasked with evaluating green tourism issues, it demonstrates Malaysia’s ambition to become a green tourism destination (Kunjuraman & Hussin, 2019). This agency is responsible for promoting Malaysia as a preferred tourism destination by launching promotional campaigns to attract tourists. Malaysia was named one of the top 17 must-see destinations in 2017 by a CNN Travel study (Hassandarvish, 2019).

In 1997, the Malaysian Ministry of Culture, Arts, and Tourism produced a national ecotourism plan, demonstrating the government’s commitment to encouraging ecotourism in a genuinely concerned country about forestry, marine, and wildlife management (Ngo, 2011). In this scenario, green tourism is a big part of Malaysia’s national ecotourism business and has long been a focus issue. For example, Malaysia’s Matang Mangrove Forest is well-known worldwide for its successful and sustainable tourist management (Noor, 2017). The Forestry Department constantly assesses the forests, and every tourism activity is meticulously measured and enhanced to increase future revenue. In addition, the Peninsular Malaysian Forest Department has built 130 forest recreational parks, referred to as Forest Recreational Areas, under Section 10 of the National Forestry Act, 1984 (Marzuki et al., 2011). Forest Recreation Areas significantly emphasize recreational, green tourism, and public awareness in the forestry industry (Yahya, 1999).

In Malaysia, the Forest Recreational Area focuses on nature-based tourism and recreation destinations: Sekayu, Terengganu, Gunung Pulai, Johor, and Bukit Larut, Perak (Ismail & Rahman, 2010). Interestingly, this research focuses on Bukit Larut, Perak, also famous as the Forest Recreation Area, which promotes green tourism and improves the quality of human life. These Forest Recreation Areas might be transformed into a more sustainable green tourism destination benefiting the entire region. Ibrahim and Yusof (2017) reported that the ecosystem, ecology, and biodiversity of a country ecosystem, ecology, and biodiversity are influenced by the number of forest acres. Forest recreation zones are famous among local and international tourists because of their beauty, uniqueness, and functional significance in green tourism. Tourism is a complex activity that can be considered an extensive system consisting of economic, environmental, cultural, and political components (Suta & Mahagangga, 2018). In this context, the positive impacts of the tourism economy are the expansion of employment opportunities, increase in business opportunities, growth of income, and preservation of local culture (Soewarni et al., 2019). Thus, green tourism strengthens as a source of income and raises the standard of living in Malaysia.

However, the economic value of green tourism is difficult to quantify due to the non-existence market for these resources. In that case, the forests still comprise around 59.5 percent of Malaysia’s total land area, but the remaining forest is under threat from excessive logging, which is a significant concern given the country’s rapid growth (Jayasooria, 2019). Consequently, visitors should be paid a conservation fee to maintain the environment and conserve significant natural resources. Even though it does not fully replenish natural resources, it would help future generations.

In addition, communities should be aware of the importance of natural resource conservation for green tourism. In this context, a questionnaire survey could be conducted using the Contingent Valuation Method (CVM) to determine the visitor’s willingness to pay (WTP) for green tourism conservation. Furthermore, this study estimates the economic value of green tourism, which may be justified in monetary terms to persuade the government to appropriate budget support for environmental protection. Recently, various research has explored the possibility of the public paying for green tourism conservation and preserving natural resources (Hassin et al., 2021; Mohd Parid, 2010; Rahim et al., 2018). Moreover, research has revealed that the public is willing to pay more for green tourism resources than they now pay (Samdin, 2008).

This paper uses the Contingent Valuation Method (CVM) to determine the visitors’ WTP for green tourism conservation at Bukit Larut’s Forest Recreation Area. Thus, the financial resources obtained from the WTP would assist the stakeholder in allocating funds for conservation and maintenance. Therefore, green tourism could be sustained for long-term tourism development (Tran & Xuan, 2021).

Data and method

Study area

Bukit Larut (Maxwell Hill) is located in Taiping, Peninsular Malaysia (4º51’44.22’’N latitude and 100º47’34.8’’E longitude) (refer to Figure 1). Interestingly, Taiping was ranked third in the ‘Best of Cities’ category during the 2019 Sustainable Top 100 Destination Awards ceremony at the International Tourism-Borse in Berlin, Germany (Sylvia, 2019). Taiping is a city in Malaysia with the highest annual rainfall of approximately 5,800 mm (Mansor & Said, 2008). Meanwhile, Bukit Larut’s tropical climate is hot and humid throughout the year, with an average daily temperature of 15–25°C and a nighttime temperature of 10°C (Akomolafe et al., 2021). In addition, Bukit Larut was designated as an Amenity Forest under Section 10 of the National Forestry Act 1984 to facilitate the local public’s enjoyment of the forest environment, education, and conservation (Ismail & Rahman, 2010). Additionally, it is a 6,878.30-hectare Forest Recreation Area managed by Taiping Municipal Council. Nordin (1987) reported that it is Peninsular Malaysia’s first and oldest hill resort, renowned for its gardens and surrounded by tropical highland rainforest, attracting visitors for sightseeing and recreation. This rationale reclassified forest areas to conserve flora, fauna, and locations for green tourism and public education.

Figure 1. Map of Bukit Larut Forest Recreation Area, Perak, Malaysia.

Source: Google Earth Pro (2022)

Data collection

Based on this study, local visitors were asked about their Willingness to Pay (WTP) using the Contingent Valuation Method (CVM) to conserve green tourism at the Bukit Larut Forest Recreation Area. Using the Slovin formula, a confidence level of 93% was used to calculate the sample size of respondents (Tejada & Punzalan, 2012). In this context, the total number of tourists who visited the Bukit Larut Forest Recreation Area in 2019 was 23,684. Based on this study, 250 respondents were randomly selected in Bukit Larut Forest Recreation Area from June to November 2021. Due to the outbreak of COVID-19, this study excludes the data from 2020 to 2021, as the period for that year could not accurately reflect the actual situation of visitor arrivals. This sample size is comparable to the study by Chu et al. (2020), which involved 249 respondents.

However, due to time and budget constraints in data collection, this study used a single dichotomous choice. According to Markandya et al. (2014), data can be treated with varying degrees of complexity depending on the time and financial resources available and the format of the question used to elicit a person’s value judgement. In this sense, a single-bounded approach requires minimal information, is easier to implement at the data collection and estimation stage, and avoids significant response bias by introducing a follow-up question (Calia & Strazzera, 2000). Potential respondents were only solicited if they were above 18 years old to avoid bias when participating in this survey. This is because respondents’ willingness to pay for green tourism conservation may influence the reliability of their answers to the contingent valuation questions. Johnston et al. (2017) note that face-to-face interviews can benefit completing questionnaires. Therefore, the interviewers conducted this survey directly with the respondents. In this sense, tourists were given a brochure before answering a questionnaire survey to enhance their understanding of the concept and value of green tourism from an ecological, sociological, and economic aspect. Respondents were selected based on several practical considerations, including their availability, willingness to participate, and ease of access (Etikan et al., 2016).

In addition, the survey questionnaire was written in Malay and English. It consisted of five sections: Section A (general information about green tourism and visiting information at Bukit Larut), Section B (the importance of green tourism at Bukit Larut to visitors), Section C (satisfaction level of visitors at Bukit Larut), Section D (willingness to pay for green tourism conservation), Section E (sociodemographic characteristics). The questionnaire consists of five bid prices (MYR5, MYR10, MYR15, MYR20, and MYR25). The method of determining the bid price was changed to avoid the possibility of the beginning of the bid price being unacceptable to respondents. Musa et al. (2020) also used the same bid price, and previous Malaysian research on CVM used a bid price range of MYR1 to MYR50 (Abdullah et al., 2015; Hasan Basri et al., 2020; Ramli et al., 2017). In this context, different bid prices are set to avoid the possibility that respondents cannot agree on the opening bid price (Azlina et al., 2018).

Methodology

The Stated Preference Approach includes two methods in particular: the Contingent Valuation Method (CVM) and the Choice Experiment (CE). However, this study uses the CVM rather than the CE. Due to the limitations of the survey period of the study, the CVM is more suitable for this study. In addition, Jin et al. (2018) reported that the CVM had a higher valid response rate and average willingness to pay (WTP) than the CE. Hasan Basri et al. (2020) noted that there is no specific guideline to determine when CE is preferable to CVM and vice versa. For the policy researcher, CVM and CE seem to have significant differences in this case; CVM is more suitable for evaluating the policy package, while CE seems more acceptable for measuring the specific qualities of the policy (Musa & Darman, 2022).

In this sense, the CVM is a questionnaire-based valuation that allows respondents to make an economic judgement on forest goods and services for which the market does not exist (Arrow et al., 1993; Carson, 2000; Dickinson & Whitehead, 2015; Heal, 2000; Jin et al., 2018; Johnston et al., 2017; Penn & Hu, 2018). In this study, the CVM estimates the non-market valuation of environmental elements or amenities (Markandya et al., 2014), like the importance of endangered species, recreational possibilities, and aesthetic resources. The fact that the issues raised by the CVM need to be carefully worked out for the answers to have any validity has led to its widespread use in estimating the value of the loss of natural amenities, especially in high-profile cases. However, Heal (2000) argued that most economists tend to agree with valuations based on actual transactions rather than those given in response to hypothetical questions, no matter how carefully constructed. Nevertheless, numerous recent studies have examined tourists’ ability to contribute to biodiversity conservation and environmental protection (Bamwesigye et al., 2020; Musa et al., 2021; Platania & Rizzo, 2018; Truong, 2022; Wang & Jia, 2012). When it has been possible to compare contingent valuation estimates with what people have paid for the service, this approach has provided relatively accurate predictions of what people would pay (Heal, 2000). Previous research shows that tourists are willing to pay more than the current fees for biodiversity conservation and environmental protection (Kamaludin et al., 2021; Mohd Asri et al., 2021; Musa & Darman, 2022).

In general, sample size can affect CVM estimation, with larger sample sizes requiring more counters and being more expensive, but a correctly selected larger sample improves estimation accuracy (Abdullah et al., 2015). However, no specific research has been conducted to determine the optimal sample size for studies using the Contingent Valuation technique of dichotomous choice. In particular, the range of sample sizes ‘greater than 30 and less than 500’ is acceptable for scientific research (Sekaran & Bougie, 2016). In addition, Calia and Strazzera (1998) reported that in terms of bias and efficiency of a single or double-bound CVM model, a sample size of 100 or less (small sample size), a sample size of 250 to 400 (medium sample size) and a sample size of more than 1000 (large sample size) are optimal.

In this regard, this argument has shown that both single- and double-bound CVM provide accurate point estimates of parameters and mean WTP, even with moderate sample sizes (Abdullah et al., 2015). Therefore, the sample size of this study is sufficient for data collection in any study using the CVM. Subsequently, the value estimates were questioned because CVM is based on hypothetical valuation questions. According to Dickinson and Whitehead (2015), validity is the extent to which a valuation method produces an unbiased measure, while theoretical validity is the extent to which a measure changes in response to valuation conditions. Consequently, a dichotomous valuation question asks respondents whether they would be willing to pay a randomly assigned fee in exchange for improving the general welfare. Any CVM survey must determine which instrument or question format will elicit values (Mullarkey & Bishop, 1999). Different valuation questions can lead to different welfare estimates (Welsh & Poe, 1998).

The dichotomous-choice CVM is generally applicable to both single and double-bounded formulations. The single-bounded approach is much easier to implement, while the double-bounded approach is more reliable. Multiple-bounded questions are an extension of single- and double-bounded referendum questions that refer to asking respondents if they would be willing to pay for a project over a range of costs, and this can reduce ‘yes’ votes as they are not limited to a single option to support an environmental improvement (Mullarkey & Bishop, 1999). Johnston et al. (2017) argued that multiple-bounded constrained CVM questions could increase efficiency and be effective with small sample sizes.

Data analysis

The data analysis for this study was divided into two parts: descriptive and statistical analysis. The numerical data’s conclusion used descriptive analysis to explain the demographic respondent’s characteristics. Consequently, regression analysis is a technique that analyses the relationships between variables represented by an equation known as the regression equation (Samdin et al., 2010). It is a collection of statistical techniques that allow us to determine the relationship between a dependent variable and several independent variables (Tabachnick et al., 2007). According to Penn and Hu (2018), when defining a dependent variable, it is vital to determine the magnitude of hypothetical bias, prompting point estimates such as the mean and median WTP for the proper and hypothetical treatments. For this study, willingness to pay (WTP) was the primary indicator studied, with the Logit model serving as the determinant for mean WTP. Table 1 lists the dependent and independent variables involved in this study. Thus, the dependent variable is the respondents’ willingness to pay (WTP) for green tourism conservation in Perak’s Bukit Larut Forest Recreation Area. This study includes seven predictor variables of different data types. The data for salary and age are continuous, while the data for race, religion and marital status are dichotomous.

Table 1. Definition of variable in Logit Model

Variable Name	Types of Variables	Type of Data	Definition
WTP	Dependent	Dichotomous	Willingness to pay; (1=Yes, 0=No)
Bid	Independent	Ordinal	Bid Price; (1=MYR5, 2=MYR10, 3=MYR15, 4=MYR20, 5=MYR25)
Race	Independent	Dichotomous	Dummy variable for race; (1=Malay, 0=Others)
Religion	Independent	Dichotomous	Dummy variable for religion; (1=Islam, 0=Others)
Age	Independent	Continuous	Age in years
Marital Status	Independent	Dichotomous	Dummy variable for marital status; (1=Single, 0=Others)
Education	Independent	Ordinal	Education level; (1=No formal education, 2=Primary school, 3=Secondary school, 4=Certificate/Diploma/Degree/PhD)
Salary	Independent	Continuous	Monthly gross income in MYR

The general model in this study is as follows:

(1) $\mathrm{P}\mathrm{r}\mathrm{o}\mathrm{b}\left(\mathrm{Y}\mathrm{e}\mathrm{s}\right)=\mathrm{f}\left(\begin{array}{c}\mathrm{B}\mathrm{i}\mathrm{d},\mathrm{R}\mathrm{a}\mathrm{c}\mathrm{e},\mathrm{R}\mathrm{e}\mathrm{l}\mathrm{i}\mathrm{g}\mathrm{i}\mathrm{o}\mathrm{n},\mathrm{A}\mathrm{g}\mathrm{e},\\ \mathrm{M}\mathrm{a}\mathrm{r}\mathrm{i}\mathrm{t}\mathrm{a}\mathrm{l}\mathrm{S}\mathrm{t}\mathrm{a}\mathrm{t}\mathrm{u}\mathrm{s},\mathrm{E}\mathrm{d}\mathrm{u}\mathrm{c}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n},\mathrm{S}\mathrm{a}\mathrm{l}\mathrm{a}\mathrm{r}\mathrm{y}\end{array}\right)$(1)

The Logit Model is as follows:

(2) $\mathrm{L}\mathrm{o}\mathrm{g}\left(\frac{\mathrm{P}\mathrm{r}\mathrm{o}\mathrm{b}\left(\mathrm{Y}\mathrm{e}\mathrm{s}\right)}{1-\mathrm{P}\mathrm{r}\mathrm{o}\mathrm{b}\left(yes\right)}\hspace{0.17em}\right)\hspace{0.17em}=\hspace{0.17em}\alpha \hspace{0.17em}+\beta 1\mathrm{B}\mathrm{I}\mathrm{D}+\beta 2\mathrm{R}\mathrm{A}\mathrm{C}\mathrm{i}+\beta 3\mathrm{R}\mathrm{E}\mathrm{L}\mathrm{i}+\beta 4\mathrm{A}\mathrm{G}\mathrm{E}\mathrm{i}+\beta 5\mathrm{M}\mathrm{S}\mathrm{i}+\beta 6\mathrm{E}\mathrm{D}\mathrm{U}\mathrm{i}+\beta 7\mathrm{S}\mathrm{A}\mathrm{L}\mathrm{i}+\epsilon \mathrm{i}$(2)

Whereby:

Prob (Yes) = Probability of accepting the bid price; 1-Prob (yes) = Probability for not accepting the bid price; α₁, β₁ β₂ … . β₇ = Parameters; ɛi = Random error; BID = Bid price; RAC = Race; REL = Religion; AGE = Age (Year); MS = Marital Status; EDU = Education Level; SAL = Salary (MYR)

(3) $\mathrm{L}\mathrm{o}\mathrm{g}\left(\frac{\mathrm{P}\mathrm{r}\mathrm{o}\mathrm{b}\left(\mathrm{Y}\mathrm{e}\mathrm{s}\right)}{1-\mathrm{P}\mathrm{r}\mathrm{o}\mathrm{b}\left(yes\right)}\hspace{0.17em}\right)=\frac{1}{1+{\mathrm{e}}^{a+\beta 1Bid+\beta 2RACi+\beta 3RELi+\beta 4AGEi+\beta 5MSi+\beta 6EDUi+\beta 7SAL+ei}}$(3)

The estimation of probability can be simplified as shown below:

Whereby:

α _1, β₁, β₂ … . β₇ = parameters which been estimated

(4) $MeanWTP=\frac{\mathrm{l}\mathrm{n}\left(1+\mathrm{e}\mathrm{x}{\mathrm{p}}^{\alpha 1,\beta 1\beta 2\dots .\beta 7\hspace{0.17em}+\beta \mathrm{i}\mathrm{X}\mathrm{i}}\right)}{-\beta i}$(4)

(5) $MedianWTP=\frac{\alpha +\beta iXi}{-\beta i}$(5)

Results and discussions

Respondent’s sociodemographic profile

Green tourism is related to environmental responsibility, which ensures the long-term health of the life-sustaining ecosystem, influenced by education, income, occupation (Biernat & Lubowiecki-Vikuk, 2012), age, gender, and marital status (Samdin et al., 2010). Table 2 illustrates the respondents’ sociodemographic profiles. Based on this study, 53.2% of respondents are females who visit Bukit Larut. Females place a higher value on most destination attributes than males, especially appreciating natural scenery and having recreational activities with friends (Collins & Tisdell, 2002). The study’s results showed that 58.0% of respondents were Malay. In this context, Malaysia is a multi-racial and multi-religious country with a large Malay, Chinese, and Indian population (Muhamat et al., 2012). Most visitors (54.4% of the respondents) who came to Bukit Larut were between 21–40 years old. Interestingly, the elderly above 50 years old are actively doing their recreational activity at Bukit Larut due to its beauty of scenery (Untari et al., 2019). The findings of this study reported that 61.2% of tourists are married. They do recreational activities such as admiring beautiful surroundings (Chiu et al., 2016).

Table 2. Sociodemographic characteristics of respondents

Variable	Frequency	Percentage (%)
Gender
Male	177	46.8
Female	133	53.2
Race
Malay	145	58.0
Chinese	50	20.0
Indian	55	22.0
Religion
Muslim	146	58.4
Buddhists	49	19.6
Hindus	54	21.6
Others	1	0.4
Age
<20 years old	16	6.4
21–30 years old	68	27.2
31–40 years old	68	27.2
41–50 years old	50	20.0
>51 years old	48	19.2
Marital Status
Single	97	38.8
Married	153	61.2
Education
No formal education	1	0.4
Primary School	0	0
Secondary School	82	32.8
Certificate/Diploma/Degree/Master/PhD	167	66.8
Occupation
Student	27	10.8
Civil Servant	69	27.6
Private Sector	73	29.2
Self Employed	29	11.6
Unemployed	22	8.8
Retired	30	12.0
Salary
<MYR999	52	20.8
MYR1,000 - MYR3,999	117	46.8
MYR4,000 - MYR9,999	70	30.0
>MYR10,000	6	2.4

Additionally, 66.8% of the respondents from the local communities had tertiary education (certificate/diploma/degree/Master/PhD). Furthermore, it revealed that people with higher education are more conscious of the importance of conserving natural resources and are prepared to spend a certain amount for conservation purposes (Chang-San, 2019; Musa et al., 2021). Despite the idea that more years of schooling can help respondents better comprehend environmental challenges and the necessity of green tourism protection (Jin et al., 2018). It can be hypothesized that the level of education positively impacts WTP (More & Stevens, 2000). Moreover, a better education allows one to understand the significance of preserving green tourism. Besides, the study’s findings reported that 29.2% of the respondents work in the private sector. It is crucial to highlight that the retired respondents in this survey were heavily engaged in green tourism, as most came here for walking and jogging. During the COVID-19 pandemic, retired and unemployed people came to Bukit Larut to spend their leisure time participating in recreational activities. According to Lal et al. (2017), the visitors’ occupation significantly impacts their willingness to pay for green tourism conservation. The study’s results also showed that 46.8% of the respondents earned between MYR1,000 and MYR3,999, indicating that respondents had the highest education level that reflects their occupation. According to Lee and Jan (2019), visitors with a high income are willing to pay for conservation purposes since they have fewer financial problems and are aware of the benefits of green tourism.

Willingness to pay for green tourism conservation

According to Laarman and Gregersen (1996), an individual’s decision to visit a green tourism destination depends on the interaction between an individual’s realization of willingness to pay for green tourism conservation and competing uses of their income. It also assesses the worth of the visitor’s experience, including their expectations and impressions of the journey. The study found that most respondents (56%) were willing to pay for green tourism conservation (refer to Figure 2). The findings of this study were comparable to those of a study by Ding and Alias (2014), Mohd Parid (2010), and Hassin et al. (2020). In this context, conservation is vital to preserving the nation’s distinctive flora and fauna for current and future generations (Tveit et al., 2006).

Figure 2. Willingness to pay among visitors towards green tourism conservation.

This study showed that willingness to pay varies with respondents’ sociodemographic profile, including race, religion, age, marital status, education level, and salary. Lee and Jan (2019) revealed that visitors with a decent income are more willing to contribute to conservation efforts because they have minimal financial concerns and are more aware of the benefits of green tourism. Significantly, the profession influences willingness to pay because a good occupation earns more income (Samdin, 2008). Consequently, visitors with a higher income will be more willing to pay. Also, respondents in this study were aware of the luscious green landscapes of Bukit Larut, which have a long-term positive impact on the environment and local communities. Not surprisingly, Bukit Larut is vital to ecological systems that save air, water, microclimate, and energy resources while enhancing the human quality of life (Mansor & Said, 2008).

In this case, the green tourism concept can support sustainable tourism in the tourism areas of national parks, especially in terms of environmental, economic, socio-cultural, and environmental-educational sustainability (Ilyas et al., 2022). According to Yoeti and Gunadi (2013), sustainable tourism is a continuous process that requires constant monitoring of its impacts and may include proven and corrective measures. In addition, the green tourism concept is being developed to promote sustainable tourism (Ilyas et al., 2022). The components of green tourism include strengthening local economies, protecting the environment and cultural diversity, and enhancing the experience (Dodds & Joppe, 2001). Thus, in many countries, green tourism protects the environment and generates significant revenue. In Costa Rica, Ecuador, Nepal, Kenya, and Madagascar, green tourism is essential to economic growth and financial stability (Gryshchenko et al., 2022).

Globally, the green tourism concept in developed countries such as Japan is similar to the rural tourism concept, which takes place in the natural environment and offers tourists the opportunity to experience the local culture and rural lifestyle (Arahi, 1998). Green tourism in Japan focuses more on the sustainable environment of rural areas and is managed by residents, although the capital required for businesses is shared by central and local government and rural residents (Furqan et al., 2010). Japan’s green tourism is a form of rural tourism that uses both the rural culture, which is characterised by a long history of agriculture and forestry, and the nature of rural areas, such as forests and secondary nature in the form of farmland, as points of interest (Arahi, 1998; Knight, 1996).

The findings regarding respondents’ willingness to pay for green tourism conservation based on the bid amount are depicted in Figure 3. Regarding the bid price, the higher value of the first bid proposed to pay for the conservation of Bukit Larut also tended to be rejected by the respondents. Based on this study, 72% of the respondents indicated they were willing to pay MYR5 compared to other bid prices because it was the lowest bid price they could afford. The study’s results indicate that respondents are conscious of the benefits of green tourism in Bukit Larut, which impacts their lifestyles. Green tourism significantly minimizes forest deterioration and promotes pollution-free forests in this context. As a result, the forest’s ecology is preserved and conserved (Suresh Kumar & Lakshmana Rao, 2021). In addition, participating in recreational activities helps prevent obesity and maintain a healthy lifestyle, allowing local communities to relieve stress (Thornburg, 2017). Iasha et al. (2015) assert that the bid price significantly affects visitors’ willingness to pay. The findings of this study were in accord with demand theory, which states that the respondent’s willingness to pay for conservation decreases when the bidding price rises. This study established a minimum bidding price, indicating that a sizable proportion of respondents are more willing to pay the admission fee (Abas et al., 2021; Hassin et al., 2020; Mamat et al., 2020).

Figure 3. Willingness to pay for green tourism conservation based on the bid price.

Reason for willingness to pay for green tourism conservation

Green tourism conservation has a significant impact on the mental and physical well-being of people. In this scenario, the visitors engage in recreational activities and take in the scenery of Bukit Larut. Based on this study, most visitors (88% of the respondents) are willing to pay to protect valuable resources and beautiful natural settings for future generations (Figure 4a). This study corroborates a previous study by Hassin et al. (2020) and Musa et al. (2021). In this context, Bukit Larut is categorized as a flora and fauna habitat and is identified as a green region with a water catchment area (Bhuiyan et al., 2011). Unsurprisingly, it is rich in biodiversity as it houses about 621 plants and 319 animals (Akomolafe et al., 2021), including 55 amphibians, 56 reptiles, pitcher plants, and ten fern families (Shahrudin, 2021). Correspondingly, respondents are willing to pay because they appreciate the value of nature to the environment and local communities.

Figure 4. (a) Reason visitor’s WTP (b) Reason visitor’s not WTP for green tourism.

Generally, green tourism promotes environmental awareness through conserving resources, particularly biological diversity, and ensuring long-term resource utilization for future generations (Kiper, 2013). In this context, tourism stakeholders and visitors are educated on protecting the natural environment to preserve its beauty and viability (Ilyas et al., 2022). Subsequently, only 1% of respondents indicated a willingness to pay the conservation fee to relieve the government of its responsibilities. The study suggests that respondents contribute to management by improving their services and the visitor experience. In this scenario, Bukit Larut is a network of greenery that acts as a green lung for a city and promotes a healthy society by providing recreational, social, and leisure spaces (Hilton, 2007).

In addition, most respondents (42%) expressed reluctance to pay because they believed the government should bear the cost of conservation (Figure 4b). In this case, they did not perceive the funds would be used for green tourism or environmental protection, indicating that some tourists had reservations about the management authority (Wang & Jia, 2012). However, according to Bhuiyan et al. (2011), the government has established a plan and budgeted for green tourism preservation. Nevertheless, 29% of respondents stated that they could afford to pay, but the amount was not specified in the bid price, and that green tourism conservation could be accomplished in other ways. Moreover, approximately 24% of respondents drawn to green landscapes and nature in various ways have varying perceptions of green tourism, which includes volunteering and joining a green society to help save the environment (Kaffashi et al., 2015). Green tourism is acknowledged as an excellent technique for preserving recreational forests and promoting and improving consciousness toward environmental awareness (Sabran et al., 2019).

Therefore, environmental education is essential for achieving sustainable tourism to realize the concept of green tourism (Ilyas et al., 2022). It is a necessary means of building human resources capable of implementing the principles of sustainable development (Indahri, 2020). In Indonesia, for example, applying green tourism in the Mount Rinjani National Park region is quite effective (Ilyas et al., 2022). Evidence of this is the efforts of the community, organizations, and related agencies to clean up and plant trees in both the tourist areas and the tropical rainforest with its rich biodiversity. For example, Ukraine’s overall growth rate of green tourism is acceptable. Interestingly, the defining feature of Ukrainian green tourism is a distinct tourist lifestyle based on harnessing the entrepreneurial potential of rural people to improve their future welfare (Gryshchenko et al., 2022).

Estimated WTP for green tourism conservation among visitors

The Logit regression was used in this study to identify the probability of visitors’ willingness to pay for green tourism conservation in Bukit Larut. According to Hassin et al. (2021), Logit regression was performed to see a significant difference in socioeconomic characteristics and learn more about the independent variables that influenced willingness to pay. Various studies have found that sociodemographic variables influence willingness to pay (Adamu et al., 2015). In this study, the Logit model involves the variables of bid, race, religion, age, marital status, education, occupation, and salary (refer to Table 3). The study by Amirnejad et al. (2006) found that bid and income were the most influential factors for WTP, followed by education and age, but not household size. Nearly 66.8% of respondents correctly answered ‘yes’ or ‘no’ to the WTP prediction in the model, indicating a relatively good fit with the data (see also Cox & Snell R² and Nagelkerke R²). In this case, the model’s sensitivity is good, as 83.7% of respondents who would choose ‘yes’ rather than ‘no’ were correctly predicted to choose ‘yes’ based on the model.

Table 3. The coefficient for mean and median WTP in the Logit model

Parameter		β	Mean	Std. Error	Sig.
Constant	α	1.630		1.331	0.221
Bid	Β1	−0.292	3.00	0.096	0.002
Race	Β2	21.661	0.58	40193.164	1
Religion	Β3	−21.000	0.58	40193.164	1
Age	Β4	−0.025	38.49	0.013	0.063
Marital Status	Β5	−0.514	0.39	0.386	0.182
Education	Β6	0.099	3.66	0.286	0.729
Salary	Β7	−0.00002397	3002.80	0.00005891	0.684
N		250
2 log-likelihood		319.259
Cox & Snell R^2		0.089
Nagelkerke R^2		0.119
% of right prediction		66.8%

The estimated coefficient of the bid price, the primary explanatory variable of WTP probability, turned out to be statistically significant with the expected negative sign. This indicates that the WTP probability of ‘yes’ decreases in the hypothetical market scenario as the offer price increases and vice versa (Lee & Han, 2002). Moreover, the negative sign of age indicates that the probability of WTP ‘yes’ is higher for younger individuals than for older individuals. Subsequently, a positive correlation for education level indicated that this element significantly impacted the respondents’ decision to participate in WTP. As a result, the greater one’s educational level, the more likely one is to accept WTP (Nurin Fadhlin et al., 2021). Such a positive relationship has been observed by Witt (2019) and Zaiton et al. (2019). The negative sign of age indicates that the probability of WTP ‘yes’ is likely higher in younger people than in older people. Therefore, Bukit Larut’s respondents’ perspectives significantly positively impacted the WTP for conservation fees.

According to Amirnejad et al. (2006), economic theory and previous empirical evidence often indicate that income positively impacts WTP estimates. Nonetheless, according to this study, income had a significant negative connection with WTP. As a result of the findings, visitors in Bukit Larut were willing to conserve green tourism, which harnesses natural resources, regardless of their financial situation. However, several studies also showed similar results where income did not determine WTP (Nguyen & Huang, 2017; Wen & Huang, 2018). Apart from this, Cook et al. (2020) reported that other recent studies on contingent valuation in Iceland, such as those by Cook et al. (2018) and Malinauskaite et al. (2020), have also shown that income is not a factor in determining consumers’ willingness to pay.

Thus, the mean and median WTP for the conservation of green tourism at Forest Recreational Area, Bukit Larut is as follows:

$MeanWTP=\frac{\mathrm{l}\mathrm{n}\left(1+\mathrm{e}\mathrm{x}{\mathrm{p}}^{\alpha +\beta \mathrm{i}\mathrm{X}\mathrm{i}}\right)}{-\beta i}$

$=\frac{\mathrm{l}\mathrm{n}\left(1+\mathrm{e}\mathrm{x}{\mathrm{p}}^{\genfrac{}{}{0ex}{}{\alpha +\beta 2\mathrm{R}\mathrm{a}\mathrm{c}\mathrm{e}\mathrm{i}+\beta 3\mathrm{R}\mathrm{e}\mathrm{l}\mathrm{i}\mathrm{g}\mathrm{i}\mathrm{o}\mathrm{n}\mathrm{i}+\beta 4\mathrm{A}\mathrm{g}\mathrm{e}\mathrm{i}+\beta 5\mathrm{M}\mathrm{a}\mathrm{r}\mathrm{i}\mathrm{t}\mathrm{a}\mathrm{l}\mathrm{S}\mathrm{t}\mathrm{a}\mathrm{t}\mathrm{u}\mathrm{s}\mathrm{i}}{+\beta 6\mathrm{E}\mathrm{d}\mathrm{u}\mathrm{c}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}\mathrm{l}\mathrm{e}\mathrm{v}\mathrm{e}\mathrm{l}\mathrm{i}++\beta 7\mathrm{S}\mathrm{a}\mathrm{l}\mathrm{a}\mathrm{r}\mathrm{y}\mathrm{i}}}\right)}{-\beta i}$

$=\frac{ln\left(1+\mathrm{e}\mathrm{x}{\mathrm{p}}^{\genfrac{}{}{0ex}{}{\left(1.6301\right)+\left(0.58\right)\left(21.661\right)+\left(0.58\right)\left(-21.000\right)+\left(38.49\right)\left(-0.0246\right)}{+\left(0.39\right)\left(-0.514\right)+\left(3.66\right)\left(0.099\right)+\left(3002.8\right)\left(-2.397\right)}}\right)}{-\left(-0.2918\right)}$

$=\frac{ln\left(1+\mathrm{e}\mathrm{x}{\mathrm{p}}^{\genfrac{}{}{0ex}{}{\left(1.6301\right)+\left(12.563\right)\left(-12.264\right)\left(-0.946\right)\left(-0.1996\right)}{+\left(0.3630\right)\left(-0.0720\right)}}\right)}{\left(-0.2918\right)}$

$=\frac{ln\left(1+\mathrm{e}\mathrm{x}{p}^{1.0749}\right)}{0.2918}$

$=\frac{1.3686}{0.2918}$

Mean WTP = MYR 4.69 per person

$MedianWTP=\frac{\alpha +\beta iXi}{-\beta i}$

$\frac{\begin{array}{c}\alpha +\beta 2Racei+\beta 3\mathrm{R}\mathrm{e}\mathrm{l}\mathrm{i}\mathrm{g}\mathrm{i}\mathrm{o}\mathrm{n}i+\beta 4\mathrm{A}\mathrm{g}\mathrm{e}i+\beta 5MaritalStatusi\\ +\beta 6Eeducationleveli+\beta 7Salaryi\end{array}}{-\beta i}$

$=\frac{\begin{array}{c}\left(1.6301\right)+\left(0.58\right)\left(21.661\right)+\left(0.58\right)\left(-21.000\right)\\ +\left(38.49\right)\left(-0.0246\right)+\left(0.39\right)\left(-0.514\right)\\ +\left(3.66\right)\left(0.099\right)+\left(3002.8\right)\left(-2.397\right)\end{array}}{-\left(-0.2918\right)}$

$=\frac{\left(1.6301\right)+\left(12.563\right)\left(-12.264\right)\left(-0.946\right)\left(-0.1996\right)+\left(0.3630\right)\left(-0.0720\right)}{-\left(-0.2918\right)}$

$\hspace{0.17em}=\hspace{0.17em}\frac{1.0749}{0.2918}$

Median WTP = MYR 3.68 per person

The mean and median WTP for green tourism conservation in Bukit Larut Forest Recreation Area was thus MYR 4.69 and MYR 3.68 per person, respectively. Previous studies on nature conservation in Malaysia reported that the mean WTP for domestic tourists was MYR 6.32 in Taman Negara National Park, Pahang (Samdin, 2008) and MYR 16.87 in Pulau Redang Marine Park, Terengganu (Mohd et al., 2013). The results of this study show that the WTP was the lowest compared to the studies by Samdin (2008) and Mohd et al. (2013). Bukit Larut Forest Recreation Area has not introduced conservation fees for local visitors. Thus, Bukit Larut Forest Recreation Area management should introduce conservation fees to conserve biodiversity for future green tourism development. Therefore, responsible tourism initiatives support the expansion of green tourism to achieve sustainability (Karjoko et al., 2020).

Conclusions

In conclusion, green tourism raises environmental awareness by conserving resources, particularly biological diversity, and improves the quality of life. The finding’s study showed that most respondents were willing to pay (WTP) a certain amount of money to conserve green tourism due to the respondents’ awareness of the importance of green tourism for future generations. Race, religion, age, married status, education, and income are connected to sociodemographic characteristics and positively affect willingness to pay (WTP). According to the results of this study, the mean and median WTP is MYR4.69 per person and MYR3.68 per person, respectively. Bukit Larut is a public area where no charges are levied on tourists. However, recently, the community has been enlightened that green tourism resources are under threat due to rising population and climate change and that steps must be taken to address this issue. Thus, this study resembles and gives the impression that visitors might need to pay a conservation charge based on the findings.

As a result, the findings of this study applying the Contingent Valuation Method (CVM) could be a beneficial tool in providing vital information for decision-makers and policy reasons in managing green tourism and protected areas. These findings can help Bukit Larut’s management establish the most appropriate fee structure for visitors and achieve its purposes. Heal (2000) emphasized that the role of economics is to help design institutions that provide incentives for the conservation of critical natural systems and mitigate human impacts on the biosphere to ensure sustainability. In this scenario, a conservation fee should be charged to the visitors to protect the ecosystem and conserve valuable natural resources. Therefore, it would benefit future generations even though it does not fully replenish natural resources. In this regard, the entrance fee to Bukit Larut could be considered a conservation fee for the stakeholder to allocate public funds for the future preservation and protection of Bukit Larut. Thus, this conservation fee would enhance facility quality, attracting visitors to Bukit Larut.

Additionally, policymakers are encouraged to implement conservation fees based on visitors’ willingness to pay. In this context, most visitors come to Bukit Larut to engage in recreational activities such as jogging and sightseeing. Consequently, policymakers must consider more effective payment mechanisms that are not burdensome to visitors. Interestingly, Bukit Larut’s old residential building has been refurbished as the Bukit Larut Biodiversity Centre, designated as a national asset. Therefore, biodiversity sustainability in green tourism could be achieved by collaborating with governments, stakeholders, non-governmental organizations, and communities.

Fundings

Universiti Malaysia Sabah funded this manuscript’s Article Publishing Charge (APC). Scheme Grant Acculturation (SGA) [Grant Number: 00832019] from Universiti Malaysia Sabah partially funded this work.

Acknowledgements

The authors would like to express sincere appreciation to Bukit Larut Management for performing this research during the COVID-19 outbreak and to all respondents who participated without hesitation and contributed meaningful recommendations on improving Bukit Larut in the future.

Data availability statement

The data supporting this study’s findings are available from the corresponding author, Fazilah Musa ([email protected]), upon reasonable request.

Disclosure statement

No potential conflict of interest was reported by the authors.