Preference Heterogeneity of Local Participation in Coupling Conservation and Community-Based Entrepreneurship Development

Abstract

The aims of conservation and economic prosperity for people living near protected areas have rapidly acquired prominence as a viable strategy for global biodiversity protection. To identify potential local enterprise improvement, we examine how rural communities adopt integrated conservation and development programs. Choice experiments are used to establish villagers’ preferences for conservation incentives. The incentive structure as well as attitudes regarding ecosystem services are being investigated. The latent class technique was used to estimate preference parameters, which resulted in two segments that accounted for villager heterogeneity. These segments were discovered through program restrictions, each with different resource usage, time spent, and compensation. Members of the more restrictive program desire a higher reward for participation in one program over another. Attitudes toward provisioning and regulating ecosystem services influence their engagement. The findings show that the younger generation is open to less restrictive programs and sharing resources to boost community enterprises. They are prepared to forego a few hours of farming in exchange for conservation actions. Programs that allow for flexibility in conservation regulations and other program features may be the most effective way to encourage more people to participate in conservation programs while also satisfying community goals.

1. Introduction

The natural conflict between economic growth and biodiversity conservation are global concerns. The two challenges are linked by a recent rise in awareness through conservation strategies. These concerns in rich countries are driven by social factors such as emotional and cultural values attached to the environment, whereas in poor countries, livelihoods are the primary driver [1]. Economic incentives have been used to stimulate local stakeholder engagement in resource management in order to achieve conservation goals in developing countries. The need to promote participation in biodiversity conservation is emphasized for the surrounding populations of protected areas, as impoverished people who rely on the forest have fewer legal rights to govern their own land. Both biodiversity conservation and livelihood goals must be shared in order to overcome the challenges [2]. Previous evidence shows that community-based conservation is more effective and efficient than government-mandated regions [3]. Ecosystem conservation reduces poverty in populations near protected areas, such as in Thailand and other developing nations [4,5]. Communities can gain from nature-based tourism and by putting value on land that has small agricultural value, which is an effective condition for poverty reduction [6]. Unfortunately, this integration approach will not always provide conservation incentives, reduce human-environment conflict, or benefit rural communities in the long run [7]. Inefficient implementation has been exacerbated by ineffective local collaboration and a lack of bottom-up participation in the planning process.

Payment for ecosystem services (PES) has received a lot of attention as a conservation tool in developing countries to fund stakeholders. The basic premise is that people who benefit from ecosystem services (ES) should pay for them, and those who contribute to their generation should be reimbursed. A growing amount of conservation research supports the use of financial incentives to encourage individuals to engage in natural resource management programs [8,9]. Compensation and reward are two forms of financial payments used by ES receivers or ecosystem stewards to enhance, preserve, redistribute, or mitigate harm to the quality of their services [10,11]. Compensation for ES is limited to payments or other types of compensation provided for ecosystem stewardship benefits in order to offset the loss of entitlements to such benefits. Rewards for ES are incentives provided to ecosystem stewards to preserve or improve environmental services. In developing countries, the modified compensation model develops toward coinvestment, where incentives are offered based on effort rather than the amount of ESs provided [12]. Experience with ES in South Asia reveals that a joint and voluntary effort by ES providers and beneficiaries in designing and implementing payment mechanisms is required to prevent unfair circumstances for important stakeholders [13]. The modified payment toward coinvestment scheme depicts an example of user-financed system designed by a local enterprise to combine forest conservation and community needs [14,15]. Thus, this research employs a coinvestment payment framework to investigate and embrace the balance between conservation and poverty reduction through community-based entrepreneurship, adopting reward as a payment mechanism.

The purpose of this study is to investigate the possibilities of constructing an innovative sustainable financing system for rural communities in Thailand bordering protected forests that integrates conservation and development initiatives based on the PES principle. The willingness-to-accept (WTA) concept, which assesses the level of compensation for conservation projects based on scheme design parameters and activity preferences, has been used in studies on the efficiency of payment and incentive schemes [7,16,17,18]. The choice experiment (CE) technique of the stated preference method is utilized in this study because it is flexible and consistent across different incentive schemes. Exploring individual preferences via the CE allows for the elicitation of people’s interests and values as stated in choice circumstances. CE also evaluates conflicts between conservation and development efforts, which is important when both initiatives have nonmonetary components. This permits conservation initiatives to be more precisely compared to development activities. Applying the CE to study farmers in Uganda reveals the significant preferences for a variety of watershed management techniques and their eagerness to implement them, even without pay [17]. We evaluated choice data from 165 houses using a random parameter logit (RPL) model and a latent class model (LC), focusing on variations in preferences among village families. Preferable conservation programs that improve livelihoods were identified using WTA value estimates derived from the results of LC analyses. To capture preference heterogeneity, the villagers are formed into two segments based on the LC model, and then those segments are used to forecast future decision behaviors. Conservation studies have investigated the variability of program preferences among agents by studying the heterogeneity of communities surrounding protected areas depending on conservation aims [19], the objective of a landowner [20], the features of conserved land [21,22], and the characteristics of participants [23,24]. In a similar vein, this study carried out a method that couples conservation goals and activities to a specific incentive scheme.

This study contributes two-fold to the body of knowledge. First, this study focuses on the protected highland areas in Thailand, which are located at the national and global hotspots for ecosystems and biodiversity. Agricultural land usage, land ownership, deforestation, and ecotourism protection have long been issues of contention among the inhabitants of this area. Strengthening integrated planning is critical for natural resource conservation and sustainable development. PES projects have attracted the attention of several parties, including governments and environmental organizations. Our findings inform stakeholders about the villagers’ readiness to safeguard biodiversity while maintaining the growth of the community-based economy. The findings are intended to provide information that can be used to shape legislative changes with respect to community cohesion and resource accessibility that constitutes community development benefits. This recognition has potential opportunities in forming local enterprises that can be created by applying conservation practices that are collectively identified by natural resource uses.

Second, we use a choice experiment to find out how people feel about different management techniques for protecting biodiversity and supporting economic growth. In conservation and other similar activities, CE is frequently used to assess WTA compensation. Studies on PES preferences in developing countries are obscure, particularly in rural Asia, where most prior studies have mostly focused on contracts for watershed, mangrove, coastal, and marine conservation; for example [25,26,27,28]. There have been fewer studies on rural communities’ preferences for incentives accounting for the conservation and development. This research integrates solid evidence with a feasibility study of PES program preferences in Thailand. Because CE research on PES is context-specific, payment and support mechanisms are also necessary to establish the conservation adoption potential in developing countries. We also investigate the influence of ES attitudes on the likelihood of participating in incentive schemes, embracing their relevance to community-based businesses. In particular, this article attempts to answer the research questions: (1) What are the benefits of forest ecosystem services perceived by the locals? (2) Are the rural villagers near protected forests willing to participate in the hypothetical integrated conservation program? (3) Is there preference heterogeneity among villagers in terms of acceptance of conservation rewards? If so, to what extent does it reflect the preferences of local enterprise?

The rest of the article is organized as follows. Section 2 introduces the study area, the choice experiment method, the survey design, and the econometric models, followed by details of the data collection in Section 3. Section 4 presents the characteristics of the village respondents, the results from the random parameter logit model, and the latent class model. The welfare estimation of villagers across models is also included. Finally, Section 5 discusses heterogeneity in program preferences and potential implications for designing integrated conservation-development policies, followed by concluding remarks in Section 6.

2. Study Area

The goal of this project is to promote villagers’ engagement in conservation-development initiatives while also conducting a case study in Thailand. This study focuses on five localities in the northeastern Thailand (HuaiYang subdistrict, Khon San district, Chaiyaphum Province) (Figure 1). Because of conservation and land use problems, Chulabhorn Reservoir and Phu Khieo Wildlife Sanctuary (PKWS) are being considered. In 2007, roughly 52.60 hectares of the Chulabhorn reservoir were protected, signaling the start of conservation efforts. This location is well-known for its biodiversity and ecosystems, which include butterfly communities [29], elephants [30], and rare plant species [31]. The PKWS is a nearby forest that can assist large mammals in surviving in the country. On the other hand, the PKWS has reduced the number of endangered animal populations [30,32,33,34,35]. According to the literature, preserving natural habitats is critical in conservation and management planning. It should be done on a regular basis.

Almost two-thirds of the Khon San district’s land area is protected forest and national parks. Many government programs aimed at integrated and sustainable development have prioritized forest-dependent populations. With the increasing demand for land in the study region, the natural environment’s vulnerability grows as well, with activities such as wild animal hunting, over-consuming non-timber products, and converting lands for agricultural use. Furthermore, at this study site, where land ownership disputes exist between rural communities and urban authorities, the complex subject of land management has affected societal perceptions [36]. Although the new legislation’s intentions (Community Forest Act, 2019 (B.E. 2562)) promise to empower local communities with the authority to manage and utilize natural resources, the uncertainty associated with permissible resource exploitation greatly impedes the community’s attempt to engage. These conditions exacerbate conservation efforts, making it even more difficult to sustain both biodiversity and economic prosperity.

3. Methodology and Data Collection

The stated preference information, produced from the discrete choice approach, is applied to analyze choice behavior concerning participation in contingent development programs. The choice modeling approach has been applied in the agricultural and environmental literature to investigate choice behavior in different ranges of conservation policies. For instance, wildlife conservation [7,37], sustaining agro-biodiversity [16,38], and assessing the monetary value of protected areas [19,39] have been considered.

3.1. Discrete Choice Experimental Design

The choice experiment is a promising method of exploring the conditions that enhance the motivation of villagers to participate in conservation programs. The CE method is often applied to goods and services that have multiple attributes, especially natural resources and ecosystems.

To elicit the preferences of villagers and determine the tradeoff value farmers place on various environmental conservation and economic development initiatives, a series of choice experiments are implemented following guidelines of best practices [40], particularly in developing countries. The CE design complies with a four-stage approach, namely, (1) identifying features of attributes and assigning their level, (2) implementing an experimental design, (3) creating a questionnaire, and (4) designing the sample.

The first step in the CE design was to identify which features of conservation-development options were considered feasible for inclusion. Two focus groups and interviews were conducted with the community leaders, heads of villages, community enterprises, and local authorities. The choice was also informed according to the previous literature on agriculture-environment and conservation in rural areas [41,42], in particular, that for developing countries [43,44,45]. The interviewees ranked the proposed conservation and community enterprise development options based on its importance, which were then translated into features of program attributes with the respective levels. It should be noted that a history of community-based entrepreneurship in the area is a key underlying idea in constructing the combined incentive scheme. Villagers are eager to participate in at least one business. Their nonfarm income is mostly generated from business participation. The CE survey was pretested on 90 villagers, and Pearson’s chi-squared test was carried out for validity tests on the difference of categorical variables in each block. The results indicated a nondifference of choice set in a different block. An example of a choice experiment card is illustrated in Figure S1, Supplementary Materials.

The hypothetical program features and the corresponding levels offered in this study are presented in Table 1. The program attributes are a mixture of categorical dummy and continuous variables. In the beginning, four attributes were created. The appropriate number of attributes were tested using Pearson’s chi-squared test, which resulted in no difference between three and four attributes. The attribute government assistance was less often stated, among others. Hence, this attribute was excluded, and the remaining three attributes of CE were retained in the final version. The two nonmonetary attributes with three levels were those of resource applications and time requirements attending preservation activities. These activities relate to the restrictions on natural resource consumption. Based on information obtained from two focus group meetings, the communities were keen on utilizing local resources in three ways and mentioned them as main sources of off-farm income, including producing local food and the handicraft production of wicker work such as baskets and mats. These productions are tied to culture and livelihood customs involving the environments that are passed on from ancestors. Ecotourism or homestay was also identified as a preference for local communities depending on the natural recreations. Each program option explains the features associated with local businesses and the responsibilities for conservation efforts that should be evident to them.

The design of conservation initiatives focuses in particular on the restrictions and their responsibilities in exchange for resources consumed. The hypothetical scenario depicts a forest protection committee governed by locals. The committee has set regulations for protection actions and is regularly monitoring those rules to guarantee that members of the community adhere to those standards. Monitoring the reservoir and riverbank, for example, is a task for those devoted to food production. They are restricted in the amount of fish they can catch in a single day. It implies that food production and handicrafts alternatives are less demanding than homestay options in terms of public engagement. Locals are responsible for keeping the environment and rules in check in this sort of resource consumption, whereas homestays are accountable for tourists, which is more dynamic and involves more public participation. The monetary attribute represented the approximate expected payoff for conservation initiatives. The level of financial incentives was determined by estimating the range of opportunity costs for various types of local businesses in this research region; it ranges from 5.5 USD (180 Baht) to 9.86 USD (320 Baht) per day. Before asking participants to select the one with which they agreed the most, a succession of restrictions and ES benefits were outlined.

The characteristics of integrated conservation-development programs in each choice question present two sustainable development programs inherited conservation incentives described by the three program attributes. Two forms of restriction are included in resource use attributes. Combining the three program elements and the levels resulted in 36 alternative contractual designs, two with three levels each and one with four levels. The participants were overwhelmed by the amount of outcomes. In order to decrease the number of possible outcomes, the complete factorial design technique was utilized with a D-efficient [46]. The method offered at least 48 treatment options. Each survey participant was presented four sets of four-choice cards and asked to choose one. They had to choose between two programs (A and B) or not participate in any program at all (status quo). This question received binary responses. According to demand theory, including an opt-out option is critical for welfare estimation [47,48]. The opt-out choice implied a decision not to engage in any of the development programs. Then each respondent was asked about their understanding of the choice questions, followed by a question on the difficulty of making a decision based on the instruction cards. The results reveal that the respondents have a clear understanding and little hesitation in making decisions (Figure S2, Supplementary Materials).

3.2. Data Collection

To ensure that the sample population reflected both members and nonmembers of agricultural extension demographics of the communities, half of the respondents were targeted as members of the community enterprise and other household productions. The community leader made an official announcement to the villagers and purposive selected household representatives to participate in the study. Sample size was defined as a proportion of the population of each village, considered together with the size of the community enterprise in each area. Data came from a total of 165 household samples. The survey was conducted through face-to-face interviews using a semi-structured method, and illustrated cards were used as a visual aid for village participants during the choice experiments. Before conducting the choice experiments, the survey participants were given crucial information including (1) an eligible adult member with accessible benefits from a program and compliance with conservation activities given by the conservation project for a length of one year; (2) a description of the conservation-development program for the community that was proposed in several forms, with each program being different in terms of production activities, time spent, and income payment; and (3) the conservation activities that should be performed by any capable adult member of a household so that a different member could perform a task without sacrificing time and labor from their routine work. The focus groups started in February 2020 and the field surveys were conducted from March to May 2020.

The questionnaire was divided into five portions, each with 41 questions, both open-ended and closed-ended. Each interview lasted about 30 min on average. The questions in the first portion were generalized questions about the participants’ socioeconomic characteristics, such as age, education, number of household members, primary crop of farm income, and revenue. The second section included questions about the household’s perspective of ecosystem services as well as social interactions in the neighborhood. The final section of the questionnaire included questions regarding views about ESs. An open-ended question was offered to fill out the list of plants, herbals, animal species, and natural areas that should be preserved. The choice experiment was in the fourth and last parts of the questionnaire. At the start of the interview, a consent form was announced, and the participant households were informed that they could opt out at any time if their participation became uncomfortable.

3.3. Theoretical Approach and Estimation Method

Early development of behavioral models in economics used a utility-maximizing framework, as this technique may integrate both economic and noneconomic elements in conservation choices [49]. In this study, the choice modeling is applied to analyze choice behavior for participating incentive programs. The attributes of the incentive program are anticipated to influence program alternatives, given that villagers maximize their utilities. The CE model is based on random utility maximization (Rum) [50] and Lancaster’s attribute-based utility theory [51]. Random utility defines the utility of a given alternative from a choice set; the value of a good, therefore, consists of the sum of the value of all attributes. In RUM, the random component of the utility of the options is assumed to be independent and identically distributed (i.i.d.) with type-I extreme value distributions. A mixed multinomial logit model or random parameter logit model can be used to estimate the probability of preferences that are homogeneous throughout the population [52]. However, preference variability has frequently been reported in investigations based on sociodemographic, geographic location, and psychological traits. Several factors, including gender, age, and educational attainment, have been proven to be important predictors of villager preferences [53].

To estimate the probabilities of choice, the random utility from chosen conservation activity can be allocated to attributes making up the support program. According to Broch and Vedel [19], utility ($U_{ij}$) that individual i receives from choosing program j $(j\in J)$ can be expressed by Equation (1):

(1)$U_{ij}=V(x_{ij};\beta )+{\epsilon }_{ij}$

Because utility cannot be observed, $U_{ij}$ is assumed to consist of an observable component ($V(\cdot )$) and unobservable component (${\epsilon }_{ij}$), the variation villager choice in the utility function. $V(x_{ij};\beta )$ is commonly specified as a linear indirect utility function depending on the characteristics of the explanatory variable $x_{ij}$. $\beta$ is a vector of unknown parameters. These factors affect individual i’s utility (in this case, the conditions in conservation program design). ${\epsilon }_{ij}$ is a vector of error term that is i.i.d. type-I extreme value random variables.

RUM assumes that an individual is a utility maximizer and thus chooses the alternative that provides them with higher utility. Alternative k will be chosen over alternative j if and only if

(2)$U_{ik}\ge U_{ij}\hspace{1em}\hspace{0.17em}\forall \hspace{0.17em}j\ne k;\hspace{1em}j,k\in C$

where $C$ is a finite set of J alternatives faced by villager i. Note that the probability given individual chooses alternative k is the same as the probability given the utility of alternative k greater than the utility of any other alternative of the choice set [54,55]. A given choice of alternative carries some probability because the utility includes a random part as follows:

(3)$\mathrm{P}(j|x_i;\beta ,{\gamma }_{\epsilon })=prob(U_{ik}\ge U_{ij}\hspace{0.17em}\hspace{0.17em}\forall \hspace{0.17em}j\in C)$

According to McFadden [50], data collected with discrete choice experiment are modeled following the RUM. Three or more alternatives to choose are the most common. The probability that villager respondent i chooses a specific alternative k in choice task n, given that n = 1, …, N, from the three alternatives j = 1, …, J is logit. The individual choice probability is:

(4)${\mathrm{P}}_{ij}=\frac{\exp ({{\beta }^{\prime }}_i{x}_{kin}+{\gamma }_i)}{{\displaystyle {\sum }_j^J\exp }({{\beta }^{\prime }}_i{x}_{jin}+{\gamma }_i)}$

where ${\gamma }_i$ is the error component associated with the two nonstatus quo choices and is assumed to be normally distributed, $({\gamma }_i\sim N(0,{\sigma }^2))$. The integrals of a conventional logit function of Equation (4) are evaluated over a density function of parameters $f\left(\beta \right)$ in the RPL model, yielding the unconditional choice probability of an individual i selecting alternative k from a choice set n.

An alternative-specific constant (ASC) is added to a model as dummy coded, specified the cancelling of program option and excluded levels. It ties to handicraft enterprise for the main purpose of resource utility. In this manner, the ASC reproduces the utility of development programs associated with handicrafts business, zero income payments, and no time spent in activities. A negative ASC estimate indicates that respondents are willing to enter development programs. A negative coefficient of ASC indicates a status quo bias, the utility associated with selecting either program deviating away from the current situation. This implies that the welfare change associated with change must be compensated by the other welfare gains, known as the endowment effect [56].

We employed the latent class (LC) model to find subgroups of the population that have similar preference structures while trying to estimate preference heterogeneity. According to individual preferences and latent factors, villagers are predicted to form distinct groups depending on their motives and preferences. Multiple diverse preferences are assumed to exist in the population under the LC model. The preferences expected to be uniform within the groups are taken into consideration by the LC model. In order to allocate individuals to classes, an estimation of class membership is used, which is made up of variables depending on the characteristics of the individuals in question [23]. The latent class technique was used in this study to assess the presence of unobserved heterogeneity based on community preferences about their roles and outcomes. These models are more suited to explain the reasons for heterogeneity since it relaxes the homogeneity assumption.

The LC can analyze the preference heterogeneity over a set of classes across individuals, which is evaluated with a noncontinuous distribution $f\left(\beta \right)$ from Equation (4). Assume that the density function $f\left(\beta \right)$ is discrete and degenerate at fixed parameters $b$, where $f\left(\beta \right)=1$ for $\beta$, else 0 for $\beta =b$. The LC also assumes that random parameters $\beta$ have M possible values and all villager participants i are classified into one of M latent classes denoted $b_m,m=1,\dots ,M$ with members of the same class sharing comparables traits such as taste heterogeneity or social economic variables. The choice probability that individual (i) chooses alternatives k from a choice set n from Equation (4) can be further transformed into the LC to classify individual villagers into M different groups by their preference similarity. Specifically, the probability of individual villager i belonging to a latent class segment m, ($s_m$), (i.e., $s_1,\dots ,s_M$) are shown in Equation (5), where $z_i$ is a vector of the socioeconomic characteristics affecting the class probability $s_m$, and ${\lambda }_s$ denotes a vector of the class segment-specific parameters [23].

(5) $s_m=\frac{\exp ({\lambda }_s{z}_i)}{{\displaystyle {\sum }_{s=1}^S\exp ({\lambda }_s{z}_i)}}$

The probability for villager i belonging to latent class m of choosing probability $s_m$ takes on the value $b_m,m=1,\dots ,M$, and $f(\beta )=s_m\hspace{0.17em}\hspace{0.17em}\mathrm{for}\hspace{0.17em}\beta =b_m$ can be written as Equation (6) [19]. Thus, the probability of villager i falling to the mth latent class and choosing the kth incentive attribute set can be expressed as:

(6)$\mathrm{Pr}(kin)={\displaystyle {\sum }_{m=1}^M{s}_m{\displaystyle {\prod }_{n=1}^N\left(\frac{\exp ({b^{\prime }}_m{x}_{k_{n}in})}{{\displaystyle {\sum }_j^J\exp }({b^{\prime }}_m{x}_{jin})}\right)}}$

The selection of the number of classes can be informed by combining quantitative measures of model fit, including the Bayesian information criterion (BIC), Akaike information criterion (AIC), and others [57]. The number of latent classes is determined by the application of generation [58].

The interpretation of the estimated coefficients is calculated in terms of the monetary value of the marginal effects of each attribute. Regarding the model represented Equation (4), the average household’s marginal willingness to accept (MWTA) for a one-unit contribution in any attribute can be estimated by Equation (7). For each attribute of the program scheme, the fraction of an attribute’s parameter coefficients is proportional to the marginal utility of the payment attribute. This value indicates the marginal rate of substitution between the attribute and money [59]:

(7)$WT{A}_{n,k,i}={\displaystyle {\sum }_{m=1}^M{s}_m}(\frac{-{\beta }_{n,att}}{{\beta }_{n,income}})$

where ${\beta }_{n,att}$ refers to the segment-specific coefficient for a particular program attribute, and ${\beta }_{n,income}$ is the segment-specific monetary incentive coefficient.

4. Results

4.1. Socioeconomic Characteristics

The study sampled 165 household representatives, yielding 159 full responses from all five communities. The average age of the household participants was 52 years, with most being female (64%) and having completed primary school (63%) (as shown in Table 2). Sugar cane and cassava were the most common grown cash crops (54%) followed by rice (33%), and seasonal vegetables (14%). Work-for-hire (52%) and retails shop earnings (12%) were the main sources of off-farm income. Because rural people have an uncertain source of incomes, we utilized monthly expenditures as a proxy for financial capital. Monthly average non-farm income was 236 USD (7800 Baht). The respondents also have favorable interactions among others in community, attitudes on leaders, independence, social opportunities, and community safety. The primary resource usage, relevant to the community enterprises, demonstrates a similar distribution of participants between food production, handicrafts, and homestays (20.86%, 22.96%, and 22.86% of total participants, respectively).

The attitudes toward ecosystem services, as shown in Table 3, presents how villagers perceive the importance of forest ecosystem services. The 7-point Likert scales were applied to measure how they received benefits from forest. The original 11 ES attitude variables were condensed using a principle component analysis and VARIMAX rotation approach, resulting in three interpretable ES variables (Provision, Cultural, and Regulation). The factor solution was considered to suit all variables with communality scores larger than 0.2. As a result, the ecosystem services perceived by villagers are considerable importance for all services (Mean = 6.22–6.43, Median = 6.5–6.75) with a small variation (Std.Dev. = 0.64–0.86). The results highlight that the villagers place a high to low value of ESs, ranging cultural service (Mean = 6.43, Median = 6.75), regulation service (Mean = 6.43, Median = 6.5), and provisioning service (Mean = 6.22, Median = 6.5).

4.2. RPL Model and Latent Class Model Results

The random parameter logit was used to account for nonhomogeneity in preferences. The model fit improved substantially from the initial RPL to the one with covariates (Pseudo R2). The results show that the RPL models generate significant standard deviations for all program attributes, indicating the choice-specific, unconditional, unobserved heterogeneity preference for all program features. A preference for choice-specific, unconditional, unobserved heterogeneity was seen across all program characteristics, as evidenced by large standard deviations. Additionally, it was noticed that all utility coefficients and their signs were as predicted. In sum, all program features allowed for unconditional heterogeneity, as shown in Table 4. The RPL model should be used to account for preference heterogeneity in developing an incentive program, which is potentially restricted to resource application. It should be noted that the ES attitudes are not statistically significant across resource uses, time spent, and payment. A Kruskall-Wallis test on the resource use reveals the Chi2(3) values 0.05, 0.867, and 0.824 for regulation services, provisioning service, and cultural services, respectively. This explains why these ES attitude variations may not distinguish respondent heterogeneity in latent class.

The LC model was employed to account for the preference heterogeneity. The ideal number of segments is determined by balanced information criterion. The statistics of two to three LC models and RPL were compared. Starting with the three class segments focused on numerical convergence, a two-segment model was the best choice because the number of segments in the sample led to a rise in the pseudo R² and log likelihood of the model. Comparatively, adding three segments to the RPL-to-two-segment model does not remarkably improve the model [23]. AIC often favors a larger number of classes more so than BIC [58]. The BIC change indicates that the two-segment solution provides the best fit to the data, while raising the number to classes to three slightly worsens the solution. Thus, we selected the model with two segments in the subsequent analysis step. More details on the fit goodness of latent class selection illustrates in Table S1 in Supplementary Materials.

The results of the two-segment model (Table 5) show the utility coefficients from the incentive program features in the first part of the table, followed by the report of membership coefficients in the second part. To identify the remaining model coefficients, the segment membership coefficients are normalized to zero. All other coefficients are related to this normalized segment (segment 2). Each respondent was assigned to one of two segments based on the probability score that they considered was the most significant. A segment 1 has 58% of the respondents, whereas a segment 2 has 42% of the respondents as its members. Respondents in the segment 1 valued all program attributes, whereas the homestay enterprise, time spent, and income payment variables played a major role in the segment 2. From these results, we can derive particular segments separated by the program restrictiveness. The membership coefficient for the low restrictive program is substantial for segment 1 respondents. This group prioritized developing a food enterprise. The responsibility on conservations are acceptable for benefits received from ES. The time-spent estimate is positive and statistically significant, meaning that spending more time on conservation yields greater benefit. The estimated coefficient for payment compensation is statistical significant and positive at the 5 percent level. The payment compensation indicates that higher levels of financial support has a positive impact on utility. It worth noting that a positive utility present even with less stringent implications of program. The low restrictive program is more likely to have younger participants joining the program and lower education.

For the second segment, the high restrictive program holds for the ecotourism preference option. The estimated coefficient for homestay option is positive and statistical significant identifying a second segment. It implies that respondents strongly support homestay enterprise. The estimate of the time-spent variable presents the statistical significance for the high restriction program with a negative sign. This suggests that the utility obtained from conservation activities and the benefits received are more likely as villagers spend less time on them. It makes sense because their tasks are responsible for both local norms and biodiversity regulation, which is relatively more difficult. Income payment is positive significant at the 5 percent level, which is similar to the low restrictive program. All in all, two traits of incentive programs illustrate that respondents held in high restrictive program are more likely to select a homestay option with greater levels of effort in conservation activities than those in low restrictive program. Respondents with low restrictive programs are more likely to choose a household production line of enterprises. These variations may differentiate respondent heterogeneity, which is expressed by a utility coefficient that is positive in this segment.

Following the standard interpretation in choice studies, the welfare impact is interpreted in relation to the status quo of not participating in an incentive scheme [54]. The ASC is a dummy variable that measures the alternative specific constant and equals 1 if the respondent does not participate in any program option and 0 if one of the program options is chosen. A negative ASC reveals a welfare effect coefficient for high restrictive program. It means that the utility associated with choosing either program, and that any welfare change must be compensated by other welfare gains. In other words, the preference of incentive programs moves away from the status quo, and the respondents are willing to enter the incentive programs. Note that ASC is positive and significant, meaning that preferences for the none option could not be explained by the model’s variables. However, the payment characteristic for a low restrictive program is positive and significant, indicating that the villagers are more likely to engage when an incentive program delivers larger compensation, all else being equal.

4.3. Willingness to Accept Incentives

The monetary value of program attributes equivalents to the utility coefficient, i.e., the marginal of willingness-to-accept (MWTA) which allow to measure the welfare estimates for villager respondents. The overall MWTA results of the models show that the highest payment of 3.25 USD per day is requested by segment 2 villagers if they are to engage in the highly restrictive scheme (Table 6), in particular for the attribute of homestay enterprise. However, the negative MWTA value for the homestay enterprise option for the LC segment 1 villagers reveals that they are willing to accept a lower payment for participating in high restrictive program as an alternative option. This finding also suggest that villagers would require sufficient remuneration to engage in the program, limiting the higher amounts of food production attribute. These villagers require a daily payment of 2.95 USD per day to participate in the low restriction program. In addition, the villagers should be paid 2.25 USD per day if the program promotes handicraft production as a complement to food production, as indicated by the MWTA of ASC. The time-spending feature has elicited indifference behavior from villagers, as it is insignificant for all the models.

These findings show that villagers can be encouraged to participate in policy initiatives that mandate them to restrict the use of resources while also taking conservation responsibility. The promotion of food production, handicrafts, and homestay businesses as community-based enterprises can persuade villagers to participate in sustainable development programs. The request for incentive shows that the flexibility on programs matter. Uptake of the low restrictive program proved to be cheaper alternative as compared to the uptake of highly restrictive one. Note that the lower and upper 95 percent confidence interval of daily payment was 1.52 USD to 4.37 USD for low restrictive program and 0.57 USD to 5.96 USD for high restrictive program. As expected, welfare gains are smaller when programs are more restrictive, which requires a high incentive.

5. Discussion

The sustainable development program for protecting local biodiversity is used in this study to examine the choice heterogeneity of people living near protected areas. The first two research questions of this study was how villagers perceive the benefits of forest ES and whether these perceptions drive their willingness to participate in conservation programs. The cultural service is prominent for locals since they are bonded by natural leisure, and its intrinsic worth is significant [60,61]. Regardless, it has no influence on villager participation in the incentive scheme. The attitudes toward ES of villagers pay high attention to provisioning and regulating ecosystem services, yet they have indifference to joining an incentive program across villagers’ segments. In other words, villagers value the forest benefits independently of the characteristics of the incentive scheme to which they adhere. This finding is consistent with Pagdee and Kawasaki [62] that people near protected areas perceive tangible benefits from the watershed forest and tend to implement the PES scheme project as means of conservation strategy. It is because they receive those benefits directly and can maintain their livelihoods if the PES is implemented. Furthermore, our result shows that although villagers perceive provisioning benefits are more inclined to engage in an incentive program, their views on regulating services hinder them from supporting the development initiative. This demonstrates that local people are aware that the rising exploitation of forest resources cannot be sustained, and that the majority of people do not mind lowering their use of forest resources and complying with the program regulations [63]. In addition to this knowledge, our findings confirm that the acceptance of alternative conservation practices based on locally oriented enterprises has revealed the emergence of opportunities for forming businesses involving homestays or ecotourism, food production, and handicrafts. In particular, accessibility to the reservoir, allowing one to catch five fish per day, can offset spending extra hours maintaining a clean natural environment, for instance. This suggests that ability of locals to manage resources, despite limits, contributes to local enterprise development.

A classification of villagers based on their views for the conservation task and consequence of establishing conservation in forests reveals that various groups of villagers benefit differently from participating in an incentive scheme. The results from LC models confirm preference heterogeneity into two distinct groups with respect to program restrictiveness. It is clear evidence of significant differences in the behavior of distinct villagers’ segments when it comes to selecting choices. Those in the low restriction program accept a lesser payout than those in the high restriction program. This finding is consistent with recent research on the conservation of forest ES in Nepal. According to Bhatta, et al. [63], the villagers who comply with the restrictive regulations have demanded a higher level of compensation. It is because of the high opportunity cost of diminished forest resource use that they are more susceptible to overexploitation. Moreover, the main aspects of the incentive scheme in this study include the features of resource usage, time spent, and income payment. The majority of locals are willing to accept these rewards and the associated obligations. The members of the low restrictive program are positively influenced by favorable attributes towards food production. In relation to these types of local enterprises, the estimated marginal WTA measures reveal the required additional payment for enhancing aquatic provisioning services (approximately 2.95 USD per day) and non-timber provisioning services (2.25 USD per day). With these findings, PES scheme may be created by bundling complementary resources in food production and handicraft industry into a single package, with payments paid individually for each ES inside the same scheme framework.

Another group of participants in the highly restrictive program is influenced positively by favorable characteristics toward homestay enterprises. The estimated marginal WTA measures indicate the needed payment for restoring cultural services (about 3.27 USD per day). Our findings show that this group is more costly to remunerate for income payment compared to the previous group. Developing an effective PES strategy with collective efforts may necessitate a site-specific restoration project. Government and local social actors must collaborate to restore ecotourism recreation and maintain cultural ES in exchange for compensation. For example, sustaining the natural beautiful landscape of waterfalls may be jointly sponsored by government agencies and local business group, in conjunction with a strategy targeting homestay enterprises by implementing a fee to pay for expanding the cultural value of recreational activities. It is worth noting that villagers in various segments also attach varying utility weights to non-payment program features. To ensure that combined conservation and sustainable development policies, such as PES interventions, are properly implemented, an understanding of how people live and make decisions in their households and communities is critical for policy design.

In terms of time commitment for an incentive program, this study specifies a one-year agreement and demonstrates that daily task hours can launch the engagement. A one-year commitment allows for flexibility in the following program continuance. The results are in line with previous studies with farmers in Thailand. Kanchanaroek and Aslam [64] found that smaller contract lengths of an incentive program attracts farmers to adopt the feasible sustainable practice options. Farmers are willing to be more environmentally conscious if a program has shorter period [38,65]. Additionally, having the opportunity to cancel the contract leads to a readiness to cut the compensation [19]. The short-term contract, lasting no more than five years, is more cost-effective for large-scale conservation, whereas long-term contracts may reduce participation and raise the expense of supporting PES initiatives [66]. Contracts are renewed yearly, which adds up over time allows more individuals to stay involved and adapt to local changes [15]. A long-term contract continuance in the case of forest ES restoration would only function if the program ensures ES provision and livelihood enhancement [67]. As a result, it is critical to determine how long incentive programs can lead to flexible contracts with periodic renegotiations and terminations [68].

The socioeconomic variables are consistent in the overall models in terms of magnitude and sign. Our finding is consistent with previous studies regarding age and education [69]. The results reveals that the younger villagers, particularly those who attached to the low restrictive one, are inclined to participate in the program. The villagers’ household income is not statistically relevant in terms of participation in the program. As long as there is demand for natural resource consumption in the community, people are prepared to take part in an incentive program, especially if they are young. This interpretation is consistent with a study that constructed a small-scale PES project to restore agricultural ES [11]. Fewer than two percent of respondents chose not to participate in any program. In principle, this implies that the respondents would choose the development program over having no program, even though the income payment is lower than that offered in the choice decision. Our findings further suggest that some forest benefits derived from an incentive program tend to be locally specific for a younger generation.

This study has two policy implications. First, the findings indicate that preferences over resource consumption vary significantly among various groups of villages. This finding highlights the need for policy-makers to tailor and promote coupled conservation-development programs so that younger generations can engage in activities and spread the message to the larger community. For instance, promoting accessibility to resource use toward development programs can integrate conservation activities and incentivize youngers to participate in a program and offer rewards. The reward setting could be designed such that it is conditioned on their performance toward program restrictiveness, which will elevate cooperation with the local authority. This type of reward can transfer new technology and trace stakeholders’ cooperatives in achieving biodiversity conservation. Second, our study finds that local communities are willing to engage in the coinvestment paradigm if we instantly embrace the idea of environmental governance and underline the possibilities for local people to become involved. To address these constraints, the cooperative business model, such as the community-based enterprise, can overcome these limitations. It is so the locals can coinvest their efforts in conservation together with business viability. Our preliminary findings show that if there is a local forest protection committee, government assistance is the least essential component in establishing the incentive program. It implies that local government should be active in care while the communities manage their own business structures independently. The extension program should be implemented in accordance with community capabilities and alternative livelihood programs. Furthermore, although this case study was conducted in Thailand, the results can be generalized to other low-income countries where resource governance and compliance with conservation rules are often weak. The key research question is how a coupling PES scheme can be governed in a manner that complies with national regulations and local custom needs. Such a PES scheme should be designed and implemented such that the potential plan supports effective conservation, sustainable resource utilization, and rural livelihood development. The policy arrangement should shift from restrictive conservation to voluntary participation conservation [70]. It is because increased participation in such incentive programs can achieve poverty alleviation [71].

While the general results in this paper provide a supportive outlook regarding the integrated conservation-development program, the findings should still be taken with limitations. It is important to note that the results should not be extrapolated too broadly due to the small sample size (165 villager participants) and preference for conservation and compensation strategies outlined in this research location. From a villagers’ perspective, this study contributes to the PES literature and assists program developers in understanding how to construct compensation and cost-effectiveness programs. Another limitation of this study is the possibility of an ex ante bias in the results. Because of this, we provided the survey participants enough time to make of own decisions. The CE approach, however, is a useful tool for obtaining the preferences of low-income villages. A number of ex ante cost estimations can be made with respect to various program scenarios based on actual reward amounts. As a result, the CE method has a significant impact on the design of conservation-development initiatives that are cost-effective for conservation and empower local people.

6. Conclusions

This study has investigated the preference heterogeneity of rural people for conservation-development programs though a CE approach. Villagers have a strong belief in ecosystem services, which drives their participation in the incentive program. We consider the intended use of local resources, which ties the benefits generated through community enterprises with conservation initiatives. Three elements of an incentive program are offered based on existing local business to illustrate numerous potential application features. The goal was to increase future conservation program involvement and create the integration of sustainable development activities that better represent the preferences and social efficiency of the villages. Overall, the results indicate that constraints and authorization on resource use play an important role in conservation engagement. Furthermore, the findings demonstrate that the program elements under consideration are comparable to those of other conservation-development contracts. The time-spent on conservation task that villagers devote to conservation projects provide insight into how individual allocate time among activities. This approach informs the fact that the resilience of program attendance is a crucial feature option for villagers. The quantity of reward earned daily can encourage participation in an incentive program, which should be based on the program’s restrictiveness. In a nutshell, this study can be applied if low involvement in an incentive program persists. The flexible incentive scheme should be considered in conjunction with the local enterprises development strategy to increase participation rate and reinforcing the cost effectiveness. The results suggest that acceptance of alternative conservation techniques based on locally oriented enterprises has shown new potential for local business formation. This collective action drives locals’ ability to manage resources, even when they are few, and contributes to local enterprise creation. The future study in PES program design has the potential to further investigate how locals adapt and comply with conservation rules based on their own preferences and reflect on the community’s prosperity.

Author Contributions

Conceptualization, V.S. and C.S.; data curation, C.S.; funding acquisition, V.S. and C.S.; formal analysis and investigation, V.S. and C.S.; methodology, V.S. and C.S.; writing—original draft preparation, V.S.; writing—review and editing, V.S. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Ethical review and approval were waived for this study because all participants are signed an Informed Consent Form prior, which explain the objective and procedure of projects and that they could withdraw at any time.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

A supplementary materials are available at https://doi.org/10.6084/m9.figshare.17058266.

Acknowledgments

We thank the village participants in the study and nearby, and the enumerators who assisted in conducting the fieldwork. Finally, we appreciate the anonymous comments and suggestions.

Conflicts of Interest

The authors declare no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figure and Tables

Figure 1. Map of the study area in Northeastern Thailand, approximate the location of the nearby provinces.

Table 1

Definitions of choice attributes and levels of the program features in the choice experiment.

Choice Attributes	Definition
Resource use	The alternative uses are linked to the current community enterprises. It is necessary for conservation efforts to restrict the use of ecosystem services.(1) Food production: The program leverages local resources to produce processed foods, mostly fish-based, including dried or pickled fish and roasted chili sauce. Villagers were responsible for maintaining the good quality of the reservoir, riverside, or while fishing. The number of caught fish per day is limited. Fishing is prohibited during the spawning season.(2) Handicraft: The community products include handcrafted baskets, mats, and other wickerwork produced from bamboo or plants. Villagers have to watch for hunting, logging, and wildfires. Villagers are responsible for aiding foresters to maintain fire lines in the forest and be aware of trespassing in the protected area. Forest products were permitted only through headloads or self-carrying.(3) Homestay: Meals and lodging on private properties near woodland fields are provided. The host will earn an extra income. Registered visitors can go on a day excursion to the nearby forests but not in the restricted area. Villagers are in charge of reminding their guests to respect the natural environment and create regulation for safe leisure. In particular, the waterfall, upwelling, and cave area should be monitored with respect to norms and intrinsic values.(If chosen, each attribute was a dummy variable).
Time	The amount of time spent on conservation-related activities (time; zero hours is the reference level), including 1, 3, 5, and 7 h per day.
Income payment	The income received by attending the development project (income), including 180, 250, and 320 THB * per day

Note: The most frequency level is selected as reference variables; * 1 USD = 31.95 THB is approximate in 2019. Variable names are in parentheses.

Table 2

Characteristics of household responses to development programs.

	Percent	SD.	Mean	Min	Max
Development program characteristics
Purpose of resource usage (yes, no)
Food production	20.86	-	-	0	1
Handicraft	22.96	-	-	0	1
Homestay	22.85	-	-	0	1
Time requirement (hour/day)	2 b	2.67	2.63	0	7
Income payment (THB a/day per household)	180 b	3.93	5.18	0	10.02
Household characteristics
Female	64%	-	-	-	-
Age of respondents (years)	-	12.16	52.23	20	81
Education (years)		3.90	7.25641	0	18
Nonfarm expenditure a (USD/month)		253.87	246.28	0	1571.21
Crop incomeRice	34.62%
Field crop (Sugar cane and cassava)	53.85%
Seasonal vegetables	13.46%
Animal farming	10.9%
Off-farm income:
Retails	11.54%
Work for hire	53.2%
Sample size = 159

^a The exchange rate is 1THB to 0.031 USD, and the values are for 2019, the year in which the choice experiments were implemented. ^b median.

Table 3

Summaries statistics of villagers’ attitudes toward forest ecosystem services.

Ecosystem Services	Measures	Value
Provision
OrnamentalsGenetic resourcesFresh water	Mean	6.220
	Median	6.5
	Std. Dev.	0.855
	Minimum	2.5
	Maximum	7
Cultural
AestheticRecreationalHeritageSpiritual	Mean	6.428
	Median	6.75
	Std. Dev.	0.643
	Minimum	4.25
	Maximum	7
Regulation
Air and water purification	Mean	6.381
Climate regulation	Median	6.5
	Std. Dev.	0.784
	Minimum	3.5
	Maximum	7

Note: Rotation converged in 7 iterations. Measure of Sampling Adequacy is 0.843 Bartlett’s test of sphericity is <0.0001: Approx. Chi-Square = 7159.515, df = 55, Sig ≤ 0.0001.

Table 4

RPL estimates for development program attributes.

	RPL Based-Model		RPL Model with Covariates
Attributes	Coefficient	Coeff.Std.	Coeff.Std	Coeff.Std
Random parameter means
ASC	0.187 (0.352)	1.503 *** (0.000)	0.240 (0.819)	2.129 * (0.081)
Food	0.973 *** (0.000)	2.072 *** (0.000)	1.005 ** (0.034)	1.552 * (0.096)
Homestay	−0.722 *** (0.010)	2.096 *** (0.000)	−0.797 * (0.068)	1.396 (0.391)
Time	−0.065 (0.112)	0.193 ** (0.019)	−0.115 ** (0.044)	0.233 (0.218)
Income payment	0.013 *** (0.000)	-	0.004 ** (0.046)	-
Nonrandom parameters
Age (year)			−0.059 ** (0.018)	-
Education (year)			−0.145 * (0.060)	-
Household earning			0.296 (0.341)
Provision			0.827 ** (0.034)
Regulating			−1.176 ** (0.036)
Cultural			0.199 (0.621)
Model statistics
Log Likelihood a	−454.8776		−436.6983
Number of choice sets	1908		1908
AIC	927.7551		911.3967
Pseudo R2	0.289		0.318
Chi-squared	64.980		18.235

Note: p-values in parentheses. ***, **, * denotes statistical significance at 1%, 5%, and 10% levels. ^a log simulated likelihood.

Table 5

Two-segment latent class model estimates for development program attributes.

	Low RestrictiveSegment 1	High RestrictiveSegment 2 (Reference)
Utility function: program attributes
ASC	0.798 *** (0.000)	−0.340 (0.122)
Food	1.047 *** (0.000)	0.279 (0.348)
Home	−1.709 *** (0.000)	0.814 ** (0.005)
Time	0.060 * (0.086)	−0.068 ** (0.023)
Income payment	0.011 *** (0.000)	0.0078 *** (0.000)
Membership probability	58%	42%
Segment function: respondent’ s characteristics
Constant	−1.191(0.481)
Age	−0.035 ** (0.020)
Education	−0.042 * (0.064)
Nonfarm household earning	0.025 a (0.458)
Log likelihood	461.829
Pseudo R2	0.278
Number of choice sets	1908

Note: p-values in parentheses. ***, **, * denotes statistical significance at 1%, 5%, and 10% levels. ^a e-02.

Table 6

,the incentive program (THB/day), by segment.

	RPL Model	LC Model
		Low Restrictive	High Restrictive
Attributes	Mean WTA	Mean WTA	Mean WTA
Food	−3.25 *** (−5.01, −1.48)	2.95 *** (1.52, 4.37)	1.12 (−1.38, −3.62)
Home	1.99 ** (0.30, 3.67)	−4.81*** (−6.56, −3.06)	3.27 *** (0.57, 5.96)
Time	0.15 (−0.01, 0.41)	0.17 (−0.15, 0.49)	−0.27 (−0.65, 0.10)
ASC	−1.07 * (−2.28, 0.15)	2.25 *** (1.07, 3.34)	−1.36 ** (−2.92, 0.19)

Note: ***, **, * denotes statistical significance at 1%, 5%, and 10% levels, respectively. Confidence interval in parentheses at 95% level, 1THB = 0.031 USD.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/su14127441/s1, Figure S1: A choice card example. Figure S2: The response distribution to the follow-up questions in choice survey. Table S1: A comparison of goodness of selecting number of latent class models.

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