Economic Valuation of Mangrove Ecosystem Services: Insights from Willingness to Pay Analysis for Chwaka Bay Mangrove Forest, Zanzibar

Simple Summary

This manuscript assesses the willingness to pay (WTP) for mangrove conservation in Chwaka Bay, Zanzibar, using the Contingent Valuation Method (CVM). This study applies Ajzen’s Theory of Planned Behavior (TPB) to understand the psychological and behavioral factors influencing conservation decisions. A structured survey revealed that 68.2% of respondents were willing to pay for mangrove conservation, while 24.2% were unwilling, citing financial constraints and skepticism about fund management. The primary factors driving WTP included the benefits of coastal protection, fisheries, biodiversity conservation, and livelihoods, while challenges included financial limitations and the belief that conservation should be government-funded. This study’s findings were validated with statistical tests such as the Kaiser–Meyer–Olkin (KMO) and Bartlett’s test of sphericity, ensuring a rigorous analysis. These insights help inform policymakers in designing effective, community-driven conservation strategies that align economic incentives with sustainable mangrove management.

Abstract

Mangrove ecosystems are vital for coastal protection, fisheries, biodiversity, and local livelihoods, yet they are increasingly threatened by land-use changes, climate impacts, and limited conservation funding. This study investigates how much local communities are willing to pay (WTP) to conserve the Chwaka Bay mangrove forest in Zanzibar. Using the Contingent Valuation Method (CVM) with a payment card approach, we conducted a structured household survey to assess both monetary contributions and the psychological and socioeconomic factors influencing them. This study is guided by Ajzen’s Theory of Planned Behavior (TPB), incorporating attitudes, subjective norms, perceived behavioral control, and mangrove knowledge. The results show that 68.2% of respondents are willing to pay for mangrove conservation, while 24.2% are not—mainly due to financial constraints or skepticism about fund use. Key drivers of WTP include perceived ecological and livelihood benefits, environmental awareness, and prior conservation involvement. Statistical validation using the Kaiser–Meyer–Olkin (KMO) test and Bartlett’s test of sphericity confirmed the reliability of the model. The findings demonstrate the value of combining behavioral theory with economic valuation to better understand and support community-based conservation strategies. This approach can inform policymakers in designing targeted, transparent, and inclusive mangrove protection programs.

1. Introduction

Mangrove forests provide a wide array of ecosystem services that are vital to environmental sustainability, national economies, and the well-being of people residing near coastal regions [1]. In developing countries, the livelihoods of communities adjacent to mangrove ecosystems are particularly dependent on the resources and services provided by these forests [2]. However, managing mangrove ecosystems is challenging due to the need to balance conservation with increasing human demands [2]. Despite their ecological and economic importance, mangroves face alarming degradation and deforestation, severely limiting their ability to provide critical services [3]. According to Webber (2016), approximately 1.04 million hectares of mangrove forests were lost globally between 1990 and 2020 [3]. Mohamed et al. [4] highlight that rapid coastal population growth has intensified pressure on mangrove resources, further accelerating their degradation. Additional stressors include land-use changes, aquaculture expansion, climate change, sea-level rise, and an increase in the frequency and intensity of extreme weather events [2].

The degradation of mangrove ecosystems undermines both ecological functions and human welfare. Financial resources are essential to implement sustainable management strategies and to restore these forests [1]. While local communities benefit from mangrove services such as fishery support, storm protection, and erosion control, they are also vulnerable to the negative effects of their depletion [4]. Acknowledging the economic contributions of mangroves has become increasingly important in policymaking and coastal management frameworks [5]. Failure to assign monetary value to these ecosystem services risks excluding them from planning and policy decisions, which could lead to continued degradation and unsustainable resource use [5].

2. Literature Review

Willingness to pay (WTP) approaches offer a means to estimate the monetary value of non-market ecosystem services, such as those provided by mangroves [6]. WTP assessments yield crucial insights by (i) measuring public support for conservation financing; (ii) providing evidence to design effective payment for ecosystem service (PES) schemes; and (iii) identifying the preferences and motivations of diverse beneficiary groups [7]. Traditional WTP models rely on neoclassical consumer theory (NCT), which posits that demand for environmental improvements is shaped by individuals’ socioeconomic characteristics [7]. However, findings based solely on NCT have often shown inconsistent relationships between socioeconomic factors and environmental behaviors [8]. To overcome these limitations, researchers have begun integrating psychological factors into WTP models [9], though such efforts often lack theoretical grounding, making variable selection subjective and incomplete.

The Contingent Valuation Method (CVM) is a widely accepted technique for estimating WTP for environmental services, especially in contexts where market prices are absent [10]. It has been extensively applied to evaluate mangrove ecosystem services, which include shoreline stabilization, carbon sequestration, and habitat provision [11]. Yet, the influence of gender on environmental valuation remains debated. While some studies report no significant correlation between gender and WTP [12], others suggest that gender may influence environmental attitudes and conservation behavior [13]. These divergent findings reflect the complexity of socio-environmental interactions and underscore the need for more nuanced investigations into gender’s role in environmental valuation.

Beyond gender, numerous socioeconomic and demographic factors have been found to affect WTP for ecosystem services. Higher income levels generally correlate with greater WTP [14], while education enhances awareness and support for conservation [15]. Other influential variables include age, occupation, marital status, household size, and length of residence, each reflecting differing levels of reliance on and exposure to mangrove resources [16]. Additionally, the proposed bid price and household structure can influence valuation outcomes, with families often more supportive due to intergenerational benefit considerations [17].

Empirical studies reflect this complexity. For example, Firdaus et al. [18] found that years of schooling significantly influenced WTP among Indonesian fishing communities, while income, age, and occupation were not significant predictors. Similarly, Sachin et al. [19] observed that income and education positively influenced conservation participation, while age negatively affected WTP. Yang et al. [20] reported similar age-related findings. In Ethiopia, Asmare et al. [21] found that WTP for mangrove restoration was positively influenced by participation in conservation, non-farm income, and trust in fund management but negatively affected by age and land proximity to floodplains.

Conversely, other studies highlight weak or non-significant effects of socioeconomic variables. Ulf et al. [22] found no influence of income on WTP for environmental goods. Tuan et al. [23], studying the “Thi Nai” mangrove area in Vietnam, noted minimal effects of socioeconomic characteristics but found that bid price, housing type, livelihood reliance, and concern about climate change were significant. In Indonesia’s Mahakam Delta, Susilo et al. [24] observed negative effects of bid price, occupation, and participation on WTP for mangrove restoration. Pham [6] found that WTP in Vietnam’s Cat Ba Biosphere Reserve was influenced positively by education, occupation, climate change attitudes, and willingness to participate in restoration, while initial bid values and male gender had negative effects.

These mixed results reveal limitations in applying the neoclassical consumer model in isolation, especially its neglect of socio-psychological dimensions that shape preferences and environmental behavior [25]. Economic decisions are influenced not only by constraints like income but also by values, attitudes, and social norms [25]. Some studies have attempted to integrate such variables but often lack a systematic theoretical foundation, using binary proxies (e.g., 0 or 1) rather than robust, observable indicators.

The CVM provides a flexible tool to capture WTP through various elicitation formats, including bidding games, payment cards, open-ended questions, and dichotomous choice methods [26]. A key concept in CVM is that WTP reflects an individual’s maximum valuation of a service or benefit [27]. Among elicitation formats, the dichotomous choice method is the most widely used due to its simplicity, but it suffers from potential biases such as starting-point bias and response uncertainty [28]. The payment card approach, though less common, is regarded as more reliable in environmental valuation studies [28]. It reduces bias by offering a structured set of bid values, improving response accuracy, and minimizing zero-bid frequencies [29].

First introduced by Mitchell and Carson [30], the payment card method involves respondents selecting a maximum amount they are willing to pay from a predefined set of bid values. The actual WTP is assumed to lie between the selected value and the next highest bid. Designing effective bid ranges requires a three-step process: (i) reviewing previous studies; (ii) field-testing surveys; and (iii) finalizing values for implementation [30]. Alberini et al. [31] recommend using five to eight bid levels, well distributed to capture average WTP without clustering too narrowly. Bid extremes may distort responses and hinder accurate valuation [31].

For analysis, interval regression is commonly used to model payment card data, where the chosen bid forms the lower bound (Aₗ) and the next highest bid the upper bound (Aᵤ). Since WTP is not directly observable, statistical methods are applied to estimate the likelihood of the actual WTP falling within this range [32].

In the payment card approach, willingness to pay (WTP) is assumed to follow a log-normal distribution and can be modeled as follows:

$$\mathit{log}\left({WTP}_i\right)=x_i^1 \alpha +\sigma t_i$$

(1)

$$Pr\left(({WTP}_i\right) \mathsf{ϵ} (A_{i1}, A_{iu}))=Pr (\mathit{log}\left(A_{i1}\right)<x_i^1\alpha +\sigma t_i<\mathit{log} (A_{iu}))$$

(2)

$$Pr({WTP}_i\in A_{i1}, A_{iu}\left)\right)=\Phi \left(\right(log(A_{iu})-x_{i^{\prime }}\alpha )/\sigma )-\Phi \left(\right(log(A_{i1})-x_{i^{\prime }}\alpha )/\sigma )$$

(3)

$$E({WTP}_i)=exp(x_{i^{\prime }}\alpha +{\sigma }^2/2)$$

(4)

where

-

${WTP}_i$ is the willingness to pay of respondent i;

-

$x_{i^{\prime }}$ is a vector of explanatory variables (e.g., income, education, and attitudes);

-

α is a vector of coefficients to be estimated;

-

$t_i$ ~ N(0,1) is a standard normal random variable;

-

σ is the standard deviation;

-

$A_{i1}$ and $A_{iu}$ are the lower and upper bounds of the payment card interval.

This study makes significant contributions to the economic valuation literature and mangrove conservation policy by addressing a critical research gap in Zanzibar, where no prior research has systematically examined the willingness to pay (WTP) for mangrove conservation through an integrated approach. While mangrove forests in Zanzibar play essential ecological, economic, and social roles, they face increasing threats from urban expansion, tourism development, and weak enforcement of conservation measures. Yet, little is known about how local communities perceive the value of mangroves or their willingness to support conservation financially. The objective of this study is to estimate local communities’ WTP for mangrove conservation and to identify the key socioeconomic and socio-psychological factors influencing this willingness, using an integrated approach that combines the Contingent Valuation Method (CVM) and the Theory of Planned Behavior (TPB). This study responds to that gap by applying CVM with a payment card approach, a technique recognized for reducing bias and improving the reliability of WTP estimates. Additionally, it uniquely incorporates Ajzen’s TPB to investigate socio-psychological determinants—such as attitudes, subjective norms, and perceived behavioral control—that influence conservation behavior. This theoretical extension goes beyond the limitations of neoclassical consumer theory by providing a more nuanced understanding of how both socioeconomic and behavioral factors shape environmental preferences [33]. Furthermore, statistical validation through the Kaiser–Meyer–Olkin (KMO) test and Bartlett’s test of sphericity reinforces the robustness of the identified WTP determinants [34]. This study’s findings not only contribute to academic discourse by integrating economic valuation with behavioral theory and statistical rigor but also offer practical insights for policymakers and stakeholders, aiming to design community-driven, sustainable conservation strategies. Ultimately, this research helps bridge the gap between environmental values and actionable conservation planning in Zanzibar and similar coastal regions.

3. Materials and Methods

3.1. Study Site

This study was conducted in Chwaka Bay, a protected area located on the east coast of Unguja Island in Zanzibar, Tanzania. Unguja, covering approximately 1660 km², is one of the two principal islands of the semi-autonomous Zanzibar Archipelago (Figure 1). The island lies south of the equator, between latitudes 5°70′ and 6°50′ S and longitudes 39°18′ and 60′ E. Its climate is predominantly influenced by the seasonal monsoon winds. Unguja Island receives an average annual rainfall ranging between 1400 mm and 2000 mm. This rainfall is distributed across two main rainy seasons: the long rains, known locally as Masika, which occur from March to May and peak in April, and the short rains, or Vuli, which take place from October to December, with relative humidity fluctuating between 55% and 99%. The island’s mean monthly temperature hovers around 26 °C.

Chwaka Bay, situated about 34 km east of Zanzibar Town, is home to the largest mangrove ecosystem in Zanzibar, covering approximately 2294 hectares. The bay serves as a critical ecological zone, providing habitat for diverse marine and terrestrial species while also offering vital ecosystem services such as coastal protection, carbon sequestration, and support for local fisheries [35]. The mangroves in Chwaka Bay play a crucial role in mitigating coastal erosion, serving as a nursery for fish and other aquatic organisms, and sustaining the livelihoods of surrounding communities who rely on them for timber, fuelwood, and other resources [36]. The bay supports ten species of mangroves, including Rhizophora mucronata, Bruguiera gymnorrhiza, Ceriops tagal, Sonneratia alba, Avicennia marina, Xylocarpus granatum, Xylocarpus moluccensis, Heritiera littoralis, Lumnitzera racemosa, and Pemphis acidula [36]. These mangroves exhibit varying degrees of salinity tolerance and structural adaptations, with some species thriving in intertidal zones while others dominate the upper mangrove belt [37]. Their presence enhances biodiversity and contributes to the overall resilience of Zanzibar’s coastal environment.

3.2. Research Design

This study employed the Contingent Valuation Method (CVM) with a payment card approach to estimate the willingness to pay (WTP) for mangrove ecosystem services among households living near the Chwaka Bay mangroves in Zanzibar. The research followed a structured methodology that began with a comprehensive literature review to identify key factors influencing WTP for mangrove conservation in coastal communities. This step helped contextualize the economic, social, and ecological relevance of mangroves and guided the formulation of the survey instrument. The second step involved developing a hypothetical market scenario to simulate a realistic conservation funding context for respondents. This scenario presented respondents with the ecological importance of mangroves, current threats, and the potential consequences of degradation, thereby setting the stage for eliciting meaningful WTP responses.

The third step focused on the design of the WTP questionnaire. The questionnaire was structured into three main sections: (i) demographic and socioeconomic characteristics (e.g., age, gender, education, income, and household size), (ii) knowledge and perceptions of mangrove ecosystem services, and (iii) the WTP elicitation using a payment card approach. The payment card included a range of bid values, informed by prior studies and expert consultation, to ensure contextual relevance and to minimize starting-point bias [38]. Respondents were asked to indicate the maximum amount they would be willing to contribute annually to support mangrove conservation. The fourth step was the sampling design, which used a stratified random sampling technique to ensure representation from various villages around Chwaka Bay, accounting for variations in proximity to mangroves and livelihood dependence. The fifth step involved administering a face-to-face household survey to collect reliable and detailed responses, allowing respondents to ask clarifying questions and reducing the risk of misunderstanding or response bias.

Lastly, a data analysis was performed using the interval regression model, appropriate for handling the interval data structure generated by the payment card approach. This model enabled the estimation of average WTP values and identified factors influencing WTP, thereby yielding reliable and generalizable insights into community preferences for mangrove conservation [39].

3.3. Development of a Model for Estimating WTP

Traditional consumer models used in WTP estimation have often been criticized for neglecting the influence of psychological and social factors that affect individual preferences and behaviors in environmental contexts [39]. To address these limitations, this study adopted an extended valuation model by integrating the Theory of Planned Behavior (TPB) with the CVM framework. The TPB provides a robust behavioral foundation by positing that intention to engage in a particular behavior—in this case, paying for mangrove conservation—is determined by three key constructs: attitude, subjective norms, and perceived behavioral control [40]. Attitude reflects an individual’s evaluation of the outcomes of paying for conservation; subjective norms involve perceived social pressures to perform or not perform the behavior; and perceived behavioral control refers to a person’s perception of their capacity or ease in contributing financially [40].

In addition to TPB constructs, the model incorporated knowledge of mangrove forests as an independent variable. Several experimental studies have indicated that individuals with more knowledge about the benefits of mangrove ecosystems are more likely to support conservation efforts and contribute financially [41]. Therefore, assessing the effect of mangrove knowledge on WTP added further behavioral depth to the analysis. Furthermore, the model included demographic and socioeconomic variables, such as age, gender, education, income, and household size, to account for structural and contextual factors influencing individual WTP decisions [42].

To ensure the internal validity of the TPB constructs, the Kaiser–Meyer–Olkin (KMO) test and Bartlett’s test of sphericity were applied. These tests assessed sampling adequacy and confirmed the appropriateness of conducting a factor analysis on the TPB-related items [41]. Measurement items were designed using a five-point Likert scale to capture the degrees of agreement with statements related to each TPB construct. The final WTP model was analyzed using interval regression to determine the influence of each psychological, knowledge-based, and socioeconomic variable on respondents’ willingness to contribute financially to mangrove conservation [43]. Figure 2 illustrates the theoretical framework for WTP and the variables integrated into the model.

3.4. Estimating the Sample Size for the Survey

This study employs a random sampling method to estimate the environmental value, adhering to the established recommendations of the National Oceanic and Atmospheric Administration (NOAA), which ensures a scientifically rigorous approach to environmental assessment. This methodology allows for an unbiased representation of the target population, enhancing the validity and reliability of this study’s findings. In determining the appropriate sample size, this study applies the formula proposed by Kothari [44], a widely recognized statistical approach. This formula is designed to optimize the precision of estimates while considering factors such as population size, margin of error, and confidence level. By integrating Kothari’s formula, this study ensures that the sample size is both statistically robust and representative of the broader population, thus strengthening the overall accuracy of the environmental valuation. The use of this well-established formula reflects this study’s commitment to methodological rigor and the production of credible, generalizable results.

$$\mathrm{n}={\displaystyle \frac{Z^{2}pqN}{e^2 \left(N-1\right)+{ Z}^{2}pq}}$$

where n = the required minimum sample size; N = the total number of households within the study area; Z = the 95% confidence level, represented as 1.96; e = the acceptable margin of error; p = the proportion of households willing to participate in the project; and q = the proportion of households unwilling to participate, which would lead to the project’s non-implementation.

Chwaka Bay is surrounded by several villages, including Chwaka, Charawe, Ukongoroni, Pete, and Unguja Ukuu, with 1571, 1571, 1156, 2108, and 4118 households, respectively [45]. To ensure statistical precision and representativeness, a margin of error of e = 0.057 was added in the sample size determination. In the proposed scenario, 70% of surveyed households express a willingness to contribute. Consequently, the proportion of households willing to contribute is represented by p = 0.7, while the proportion unwilling to contribute is q = 1 − p = 0.3. Based on this, the minimum sample size required is shown in

Table 1. Sample size for each study village.

Village	No. of Households	Sample Size
Chwaka	1571	309
Charawe	1571	309
Ukongoroni	1156	291
Pete	2108	326
Unguja Ukuu	4118	354
Total		1589

.

3.5. Data Analysis

This study aims to estimate the willingness to pay (WTP) for mangrove ecosystem services in Chwaka Bay, Zanzibar, with a focus on understanding the factors influencing local communities’ contributions to environmental conservation. To ensure statistical representativeness and enhance the accuracy of the findings, 1589 household heads were selected for direct interviews conducted from January to February 2025. The analysis incorporates several key methods: (i) a demographic and socioeconomic analysis of respondents, (ii) an assessment of the internal consistency of psychological factors using Cronbach’s alpha, (iii) an exploratory factor analysis (EFA) to identify underlying determinants of WTP, and (iv) an analysis of descriptive statistics for psychological factors and (v) factors influencing “yes” and “no” responses in WTP. IBM SPSS Statistics v.29 was employed to conduct descriptive statistics, evaluate the reliability of measurement scales, and perform the EFA, thereby ensuring the robustness of the data analysis. The software’s capabilities facilitated rigorous testing of the validity and consistency of the instruments used [45]. The data analysis process incorporated a quantitative analysis to explore both the demographic characteristics and psychological factors influencing individuals’ willingness to pay (WTP) for mangrove ecosystem services in Chwaka Bay. This analysis utilized descriptive statistics, reliability testing, and exploratory factor analysis (EFA). Descriptive statistics were used to summarize the key demographic variables, including religion, gender, age, marital status, education level, and household size. Frequencies, percentages, and means were calculated to highlight population distributions and identify significant trends within the surveyed communities. A reliability analysis, conducted using Cronbach’s alpha, assessed the internal consistency of measurement scales for psychological factors such as Attitude (AT), Perceived Behavioral Control (PC), Subjective Norm (SN), and Knowledge (KN) [46]. A Cronbach’s alpha value of 0.7 or higher was deemed acceptable, and corrected item–total correlations were examined to ensure consistency across scale items. An exploratory factor analysis (EFA) was applied to evaluate the construct validity of the psychological determinants. The Kaiser–Meyer–Olkin (KMO) test [47] and Bartlett’s test of sphericity [48] were performed to assess the suitability of the dataset for factor analysis. Factor loadings greater than 0.5 and an explained variance above 50% were considered acceptable for confirming the validity of the measurement scales.

4. Findings

4.1. Demographic and Socioeconomic Characteristics of Respondents

The demographic characteristics of participants in the household survey across Chwaka Bay are clearly summarized in

Table 2. Demographic variables of participants in the household survey in Chwaka Bay.

Variable	Sub-Category	Chwaka (%)	Charawe (%)	Ukongoroni (%)	Pete (%)	Unguja Ukuu (%)	Average (%)
Religion	Muslims	99.3	100.0	99.9	97.6	98.6	19.7
	Christians	0.7	0.0	0.1	2.4	1.4	0.28
Gender	Male	46.1	49.7	46.3	46.7	55.7	11.1
	Female	53.9	50.3	53.7	53.3	44.3	8.86
Age	40–49	23.7	36.2	35.8	41.3	26.1	5.22
	50–59	57.3	51.6	53.0	42.9	69.2	13.84
	60+	19.0	12.2	11.2	15.8	4.7	0.94
Marital status	Married	88.2	81.7	93.1	91.9	92.5	18.5
	Widowed	9.0	4.6	0.6	4.7	6.3	1.2
	Divorced	2.8	13.7	6.3	3.4	1.2	0.2
Education level	Tertiary	4.1	5.6	3.1	1.9	7.6	1.5
	Secondary	41.5	71.9	51.2	48.2	59.0	11.8
	Primary	54.4	22.5	45.7	49.9	33.4	6.6
Household size	1–5	11.0	19.4	26.4	38.4	32.8	6.5
	6–10	69.8	71.2	61.2	42.9	58.4	11.6
	10+	19.2	9.4	12.4	18.7	8.8	1.7

and reveal a predominantly Muslim population, with an average of 99.7% of respondents across all villages identifying as Muslim. Christianity accounted for only 0.28%, indicating minimal religious diversity in the study area. Gender distribution is relatively balanced, with females comprising approximately 51.5% of the total respondents. A slightly higher proportion of females was observed in Chwaka (53.9%), Ukongoroni (53.7%), and Pete (53.3%), whereas males were more prevalent in Unguja Ukuu (55.7%), potentially reflecting local migration or labor dynamics. In terms of age, the population skews older, with 13.8% of respondents in the 50–59 age group and 5.2% in the 40–49 age group. Only 0.9% were aged 60 and above, possibly due to the lower life expectancy or youth migration patterns. Marital status data show that the vast majority (88.5%) of respondents are married, indicating strong family structures, while widowhood (1.2%) and divorce (0.2%) were low overall, though notably higher in Charawe, where 13.7% of respondents reported being divorced, suggesting localized socioeconomic challenges. Educational attainment varied, with 11.8% having completed secondary education, 6.6% primary education, and only 1.5% tertiary education, highlighting barriers to higher education access. A household size analysis reveals that large families are common, with 11.6% of households comprising 6–10 members and 1.7% having more than 10 members, consistent with extended family living arrangements typical in rural East African communities.

4.2. Assessment of Internal Consistency Using Cronbach’s Alpha

In this study, Cronbach’s alpha coefficient was employed to assess the internal consistency and reliability of the measurement scales used to evaluate psychological factors influencing individuals’ willingness to pay (WTP) for mangrove ecosystem services within the commune. The analysis yielded Cronbach’s alpha values for the four latent constructs, with Attitude (AT) scoring 0.849, Perceived Behavioral Control (PC) at 0.784, Subjective Norm (SN) at 0.851, and Knowledge (KN) at 0.856. Since all values exceeded the 0.7 threshold, the measurement scales demonstrated acceptable reliability. Additionally, the corrected item–total correlations for all observed variables were above 0.3, further confirming the consistency of the scale items. These results indicate that the observed variables are reliable and exhibit strong internal consistency, making them suitable for further statistical analysis in understanding the psychological determinants of WTP for mangrove ecosystem services.

4.3. Exploratory Factor Analysis for Validating Psychological Constructs

The present study employed an exploratory factor analysis (EFA) to examine the convergent and discriminant validity of the measurement scales used to assess psychological determinants. The results demonstrated that the Kaiser–Meyer–Olkin (KMO) measure of sampling adequacy was 0.897, which is well within the acceptable range of 0.5 to 1.0, affirming the appropriateness of the dataset for factor analysis. Moreover, Bartlett’s test of sphericity yielded a statistically significant result (p < 0.001), indicating that the observed variables exhibited strong linear correlations with their respective latent constructs. The Extraction Sums of Squared Loadings accounted for 71.001% of the total variance, exceeding the commonly accepted threshold of 50%, thereby supporting the structural validity of the measurement model. Additionally, all factor loadings were above the 0.5 criterion, with values for Knowledge (KN1–KN5) reported as 0.603, 0.751, 0.894, 0.702, 0.729, and 0.260; Attitude (AT1–AT4) as 0.871, 0.581, 0.840, 0.773, and 0.590; Subjective Norm (SN1–SN4) as 0.845, 0.761, 0.884, 0.811, and 0.774; and Perceived Behavioral Control (PC1–PC4) as 0.800, 0.800, 0.847, 0.752, and 0.763. These findings provide empirical evidence supporting the reliability and construct validity of the measurement scales, confirming their suitability for further statistical modeling and hypothesis testing.

4.4. Analysis of Descriptive Statistics for Psychological Factors

The findings of the survey reveal a high level of awareness and knowledge regarding mangrove ecosystems among respondents (Figure 3). The majority of participants (59.7%) strongly agreed that they understand how mangroves serve as habitats for various marine and terrestrial species, indicating a strong recognition of their ecological importance. Similarly, 62.1% were strongly aware of initiatives and strategies aimed at restoring and protecting mangrove ecosystems, reflecting a positive acknowledgment of conservation efforts. Furthermore, a significant portion (56.2%) expressed strong knowledge of how mangroves provide essential resources such as food, medicine, and livelihoods, underscoring their socioeconomic value. Awareness of legal frameworks governing mangrove conservation was also notable, with 59.4% strongly agreeing with this statement. Lastly, more than half of the respondents (52.4%) strongly agreed that they understood how mangroves help prevent coastal erosion, storm surges, and flooding, highlighting recognition of their protective role. Overall, these results suggest a strong public understanding of the multifaceted benefits of mangroves, both ecologically and socioeconomically, as well as a significant awareness of conservation initiatives and policies.

The survey findings indicate a generally positive attitude towards the concept of payment for mangrove services, with respondents expressing strong support for financial contributions towards mangrove conservation (Figure 4). A significant portion (59.2%) of the participants strongly agreed that payment for mangrove services is a fair way to protect the environment, demonstrating a widespread belief in the fairness of this approach. Furthermore, 69.1% of respondents strongly agreed that paying for mangrove services would lead to better conservation outcomes, reflecting optimism about the effectiveness of financial contributions in achieving environmental protection goals. Regarding local community involvement, 63.8% supported that the local community should contribute financially to mangrove preservation, highlighting a strong sense of collective responsibility. A willingness to invest in the long-term sustainability of mangrove ecosystems was also prominent, with 61.2% expressing readiness to support such initiatives. Lastly, 59.9% of respondents trusted that funds collected for mangrove services would be used effectively for conservation, underscoring a positive perception of transparency and management. These results collectively suggest substantial public endorsement for payment schemes to support mangrove conservation, with trust in the system and confidence in the outcomes being key factors in this support.

The survey findings reveal a limited influence of various subjective norms on respondents’ decisions to pay for mangrove services (Figure 5). A significant majority (55.2%) strongly disagreed and 27.3% disagreed, with the statement that local leaders influence their decision to pay for mangrove services, suggesting a minimal impact of local leadership in this regard. Similarly, environmental organizations were found to have a relatively weak influence, with 67.5% strongly disagreeing and 17.6% disagreeing with the statement that such organizations influence their payment decisions. Cultural norms and traditions also appeared to have a modest impact, as 57.4% strongly disagreed and 21.8% disagreed with the influence of cultural practices on payment decisions. Lastly, media influence was similarly low, with 60.2% strongly disagreeing and 22% disagreeing that media (news and advertisements) play a role in influencing payment for mangrove services. Overall, these findings indicate that while subjective norms such as local leadership, environmental organizations, cultural traditions, and media have some influence, it is relatively weak, and these factors may not significantly drive respondents’ decisions to financially support mangrove services.

Findings for perceived behavioral control regarding payments for mangrove ecosystem services, focusing on knowledge, accessibility, external influences, and confidence in financial contributions, are shown in Figure 6. A majority (47.9% strongly agree and 19.5% agree) felt they had sufficient knowledge to make informed payment decisions, though some (16.0% strongly disagree and 12.4% disagree) lacked awareness, indicating a need for better education on mangrove conservation. Most respondents (52.9% strongly agree and 19.2% agree) found payment platforms accessible, yet 26.1% (strongly disagree and disagree) faced difficulties, suggesting the importance of streamlining financial contribution mechanisms. External influences, such as government policies and community factors, significantly impacted payment ability, with 46.4% strongly agreeing and 23.8% agreeing, though 21.2% disagreed, highlighting the role of policy in shaping financial engagement. However, confidence in the environmental impact of payments was relatively low, as 38.7% strongly disagreed and 21.8% disagreed that their contributions would have a meaningful effect, pointing to skepticism about fund utilization and conservation outcomes. These findings suggest that while many individuals feel they have the knowledge and access to contribute financially, strengthening transparency, community engagement, and education could enhance public confidence and participation in mangrove conservation efforts.

4.5. Factors Influencing “Yes” and “No” Responses in WTP Surveys

The willingness to pay (WTP) for mangrove ecosystem services in Chwaka Bay, Zanzibar, varies among respondents based on socioeconomic and environmental factors. The survey results indicate that 68.2% of respondents expressed a willingness to pay for mangrove conservation, 7.6% were undecided, and 24.2% were not willing to pay (Figure 7). The mean WTP amount among those who agreed was USD 2.00 per month, with a standard deviation of USD 0.80, reflecting variations in financial capacity and perceived benefits. Several key factors influenced positive WTP responses. Coastal protection was the most frequently mentioned factor, with 30.2% of respondents recognizing the role of mangroves in preventing coastal erosion and shielding communities from storm surges. The importance of mangroves for fisheries followed, with 20.1% of respondents acknowledging their role as breeding and nursery grounds for fish, benefiting local fishers. Biodiversity conservation was a motivating factor for 15.3%, as they valued the rich flora and fauna supported by mangrove ecosystems. Additionally, 12.4% of respondents cited livelihood benefits, including access to firewood, honey, and other natural resources. Environmental awareness influenced 13.0% of respondents, with those knowledgeable about mangrove ecosystem services being more likely to support conservation efforts. Lastly, 9.0% of respondents who had previously participated in community-based conservation activities expressed a greater willingness to pay, highlighting the importance of engagement in environmental initiatives.

This study found that 7.6% of respondents were undecided about their willingness to pay (WTP) for mangrove conservation in Chwaka Bay, Zanzibar. The reasons for their uncertainty were categorized into four main groups. The most common reason was a lack of awareness about conservation programs (35.9%), highlighting the need for more environmental education initiatives. Concerns about the effectiveness of WTP initiatives (25.1%) also contributed to uncertainty, as some respondents were skeptical about whether their contributions would lead to meaningful conservation outcomes. Financial instability (20.8%) was another factor, with some respondents expressing a willingness to pay but uncertainty about their ability to contribute consistently. Lastly, distrust in fund management (18.2%) emerged as a significant issue, as some individuals were hesitant to participate due to concerns over potential mismanagement or lack of transparency in fund allocation.

Conversely, this study identified four primary reasons for rejecting WTP. The most common reason was financial constraints (40.3%), with respondents citing their inability to afford additional financial contributions. A belief that conservation should be government-funded (28.5%) was also a significant factor, as some respondents felt that environmental protection is the responsibility of government agencies rather than individuals. Skepticism about fund management (18.7%) further discouraged participation, with concerns about potential mismanagement or lack of accountability. Lastly, a perception of low personal benefit from conservation efforts (12.5%) influenced some respondents, as they did not see direct or immediate advantages from mangrove conservation. These findings suggest that increasing public awareness, ensuring financial transparency, and integrating WTP schemes with alternative livelihood opportunities could enhance participation in mangrove conservation efforts in Chwaka Bay.

5. Discussion

5.1. Demographic and Socioeconomic Variables

The demographic characteristics of participants in Chwaka Bay reflect distinctive socio-cultural patterns common in many rural coastal settings, while also diverging from trends observed in other global socioecological contexts. The overwhelming Muslim majority (99.7%) aligns with Zanzibar’s historical and religious identity [49], in contrast to more religiously diverse regions like Southeast Asia and West Africa, where varied religious affiliations can influence conservation behaviors differently [50]. Gender distribution in Chwaka is generally balanced, but a higher proportion of males in Unguja Ukuu suggests male-dominated migration for employment [51], similar to patterns seen in Indonesian and Vietnamese coastal communities, where male outmigration affects participation in environmental initiatives [6]. The predominance of an aging population, particularly in the 50–59 age group, reflects youth migration trends comparable to those in rural Ethiopia and India, where younger individuals leave for urban opportunities, leaving older populations to engage more directly with local resource management [21].

Education levels in Chwaka Bay are notably low, with only 1.5% of respondents having tertiary education and most having completed only primary or secondary school. This is consistent with studies from Ethiopia and Nigeria, where limited access to higher education correlates with reduced environmental awareness and lower participation in payment for ecosystem service (PES) schemes [52]. Conversely, regions such as Vietnam and Malaysia report higher WTP among more educated populations [23], highlighting the role of education in shaping conservation behavior. Additionally, the prevalence of large household sizes (6–10 members) mirrors traditional extended family systems common in rural East Africa [53], differing from nuclear family structures observed in Western or urbanized contexts, where WTP decisions are often made at the individual rather than household level [25]. These findings suggest that while Chwaka Bay shares some demographic trends with other mangrove-dependent regions, unique local conditions—particularly in education and family structure—significantly shape conservation attitudes and willingness to pay.

5.2. Evaluation of Internal Consistency with Cronbach’s Alpha

The Cronbach’s alpha values for the four latent constructs—Attitude (AT), Perceived Behavioral Control (PC), Subjective Norm (SN), and Knowledge (KN)—demonstrate strong internal consistency and reliability. With values ranging from 0.784 for Perceived Behavioral Control to 0.856 for Knowledge, all constructs exceed the commonly accepted threshold of 0.7, indicating good reliability [54]. These findings are in contrast to similar studies, such as La Riccia et al. [55], which reported Cronbach’s alpha values ranging from 0.68 to 0.75 for comparable constructs. The alpha values in this study, particularly for Knowledge and Subjective Norm, suggest that the measurement scales are more reliable. For instance, La Riccia et al. [55] reported a lower alpha for Subjective Norm (0.74), whereas this study found an alpha of 0.851 for the same construct, indicating superior scale reliability. As noted by Pallant [56], values above 0.8 are considered excellent, and the alpha values for Subjective Norm (0.851) and Knowledge (0.856) in this study fall into this category, highlighting the robustness of these scales in consistently measuring the psychological factors associated with willingness to pay (WTP) for mangrove ecosystem services. In contrast, Perceived Behavioral Control (PC) often demonstrates lower reliability in environmental behavior studies, with alpha values sometimes falling below 0.7, as discussed by DeVellis [57]. The alpha value for PC in this study, 0.784, while lower than those for Subjective Norm and Knowledge, remains within the acceptable range and exceeds the values reported in studies like [55], where alpha values for similar constructs were lower. Furthermore, the corrected item–total correlations above 0.3 reinforce the reliability of the measurement scales. According to DeVellis [57], item–total correlations above 0.3 indicate that each item contributes meaningfully to the overall construct, which aligns with this study’s findings. This is in contrast to studies with lower alpha values, where weaker item–total correlations suggest that some items may not adequately reflect the latent construct they are meant to measure.

5.3. Application of Exploratory Factor Analysis for Verifying Psychological Constructs

The use of an exploratory factor analysis (EFA) to assess the convergent and discriminant validity of psychological determinants provides a comprehensive understanding of the measurement model’s reliability. The Kaiser–Meyer–Olkin (KMO) measure (0.897) and Bartlett’s test of sphericity (p < 0.001) indicate that the dataset is well suited for factor analysis. The KMO value, falling within the recommended range of 0.5 to 1.0, suggests that the sample size is adequate and that the data are appropriate for analysis [33]. This finding aligns with previous studies that emphasize the importance of the KMO measure in determining data suitability for factor analysis [56]. Notably, this result is consistent with studies in different socioecological settings, such as in urban environmental studies in South Asia, where KMO values above 0.8 are also considered a good indication of data suitability for factor analysis [56]. The Extraction Sums of Squared Loadings of 71.001% also exceed the 50% threshold, which is commonly regarded as acceptable for structural validity [57]. This high level of variance is in line with similar research in psychology and social sciences, where studies across various global settings, including North American and European samples, have reported high variance extraction of over 70% [58]. The ability to extract over 70% of the variance supports the conclusion that the measurement scales used in this study are robust and effective at capturing the underlying psychological constructs.

The individual factor loadings for the different constructs—Knowledge (KN1–KN5), Attitude (AT1–AT4), Subjective Norm (SN1–SN4), and Perceived Behavioral Control (PC1–PC4)—are all above the 0.5 criterion, further supporting the reliability and construct validity of the scales. This aligns with the guidelines set by Hair et al. [59], who state that factor loadings above 0.5 indicate a strong relationship between observed variables and their latent constructs. These results are comparable to studies in behavioral science across different contexts, such as environmental psychology research in Africa and Latin America, where factor loadings ranging from 0.6 to 0.9 have been commonly reported for similar psychological constructs [33]. However, the loadings for Knowledge (particularly KN5), which exhibits a relatively lower value of 0.260, suggest that this specific item may not fully align with the other items in the Knowledge construct. This finding resonates with some studies in environmental economics and conservation behavior, where certain items did not perform as well as others, leading to revisions in scale design [57]. In contrast, some studies using EFA for similar psychological constructs have reported even higher levels of variance explained, sometimes exceeding 80%, such as the work by O’Rourke and Hatcher [60], which may be attributed to differences in sample characteristics and the cultural contexts in which the studies were conducted. Despite this, the overall results from this study are consistent with those in the literature, confirming the reliability, convergent, and discriminant validity of the measurement scales.

5.4. Examination of Descriptive Statistics for Psychological Variables

The high level of awareness observed in this study is consistent with global findings on public knowledge of ecosystem services. For example, Sima et al. [61] reported strong public recognition of mangroves’ ecological importance and their role in coastal protection, while Mafi-Gholami [5] found that communities in Iran had a solid understanding of the socioeconomic benefits provided by mangroves, such as fisheries and timber. Similarly, our findings highlight high awareness of ecosystem services like food, medicine, and livelihoods. However, unlike in some Southeast Asian and Pacific contexts, where traditional ecological knowledge is deeply embedded in cultural systems and often passed down through generations, the local awareness in our study is largely driven by contemporary education and mass media exposure. This indicates a shift in how environmental knowledge is disseminated across different socioecological settings.

The strong support for payments for mangrove services observed in this study (with 59.2% agreeing that payment is fair and 59.9% trusting fund use) aligns with global trends highlighted by Pascual et al. [62], who found that fairness and transparency in fund management significantly influence public willingness to contribute financially to conservation. While this pattern holds across both developed and developing contexts, our findings contrast with several local African and South American studies where skepticism about government-led payment schemes remains high due to historical mistrust and governance challenges [61]. The relative trust in fund management observed in this study suggests that transparency in financial mechanisms may be more advanced or differently perceived in this socioecological setting.

However, the limited influence of subjective norms observed here contrasts with other socioecological settings where community and cultural factors are decisive. Ntibona et al. [63], for instance, noted that strong local leadership and community organizations in West Africa heavily shape pro-environmental behavior. In contrast, in our study area, the weak influence of local leaders, environmental organizations, and cultural traditions may reflect a lesser degree of community engagement or perhaps a more individualistic decision-making process in environmental contributions [62]. This discrepancy suggests that socio-cultural context plays a critical role in shaping environmental behaviors, highlighting the need for tailored engagement strategies.

Similarly, perceived behavioral control in this study uncovered barriers to participation, particularly skepticism about the real-world impact of conservation payments. While such concerns are documented globally, such as in Börner et al. [64] in Latin America, where participants doubted the environmental outcomes of PES schemes, our findings suggest that these doubts persist even in settings where knowledge dissemination and payment platforms are relatively robust. This may point to a universal challenge in PES programs—bridging the gap between individual contributions and tangible conservation outcomes. Aguilar-Gómez et al. [65] emphasize how enhancing transparency, feedback mechanisms, and community involvement can help address these concerns, reinforcing the importance of context-sensitive strategies in overcoming barriers to participation.

5.5. Factors Influencing Positive/Negative WTP

Several key factors were found to drive the willingness to pay (WTP) for mangrove conservation in this study, with coastal protection against erosion and storm surges cited most frequently. This underscores the perceived role of mangroves in safeguarding coastal communities—a finding consistent with studies from climate-vulnerable regions such as Southeast Asia and the Caribbean, where coastal protection is a dominant motivator for WTP [66]. However, in contrast to some urban coastal settings in developed countries, where the protection of property values tends to dominate the discourse, the respondents in this study emphasized human safety and community infrastructure, reflecting the socioeconomic priorities of a lower-income, resource-dependent population.

The recognition of mangroves as breeding and nursery grounds for fisheries also emerged as a strong motivation, aligning with research from coastal fishing communities in West Africa and South Asia, where reliance on mangrove-supported fisheries directly influences WTP [6]. Yet, compared to more industrialized coastal regions where fisheries benefits are often viewed in commercial terms, participants in this study framed their motivation in terms of subsistence and food security, suggesting that localized, livelihood-based incentives are more influential in driving conservation support in these contexts.

Additional motivations included biodiversity conservation and the livelihood benefits derived from mangrove resources such as firewood and honey. These findings echo those from other parts of sub-Saharan Africa and parts of Latin America, where mangroves contribute significantly to daily household needs and informal economies [8]. However, unlike in some eco-tourism-driven conservation areas where aesthetic and recreational values dominate public support, these utilitarian motivations indicate a more immediate, tangible valuation of mangrove services. This contrast highlights how socioecological context—particularly the degree of dependency on natural resources—shapes the drivers of WTP. Overall, while the findings support global research on the multifaceted value of mangroves [65], they also reveal that in this local context, WTP is primarily driven by direct, livelihood-related benefits rather than abstract or future-oriented ecological concerns. This suggests that conservation initiatives in similar socioecological settings may be more successful when they explicitly link ecosystem services to everyday economic and safety needs.

5.6. Methodological Contributions, Case Study Limitations, and Future Directions

This study introduces a novel integration of the Contingent Valuation Method (CVM) with Ajzen’s Theory of Planned Behavior (TPB), providing a multidimensional framework for assessing WTP. By incorporating psychological constructs alongside socioeconomic variables, the methodology captures a richer, more nuanced view of conservation behavior [43]. The use of statistical tools such as Cronbach’s alpha, EFA, and reliability testing ensures rigorous validation of the constructs, thereby strengthening the empirical foundation for policy recommendations.

However, as a case study focused on villages surrounding Chwaka Bay, the findings may not be universally generalizable across Zanzibar or other coastal regions. Cultural, economic, and institutional differences can affect the external validity of the behavioral insights obtained. Furthermore, the relatively low educational attainment and reliance on traditional livelihoods may moderate the influence of some psychological constructs in ways that differ from urban or more economically diverse populations.

Future research should explore longitudinal data to assess the changes in WTP and behavior over time, especially as conservation programs evolve. Replication in different cultural and ecological settings would test the robustness of the integrated CVM-TPB framework. Additionally, incorporating qualitative methods, such as focus groups or ethnographic observations, could enrich the understanding of community dynamics and trust factors.

Importantly, this methodological approach has practical implications for conservation policy. By identifying not only how much communities are willing to pay but also why, decision-makers can design participatory, culturally appropriate PES schemes that align with community values and psychological drivers. This represents a significant advancement in linking economic valuation with behavioral insights, offering a model that can be adapted for other ecosystems facing similar conservation challenges.

6. Conclusions

This study provides compelling evidence of the economic and ecological importance of mangrove ecosystems in Zanzibar by demonstrating the public’s willingness to pay (WTP) for their conservation. The integration of the Contingent Valuation Method (CVM) with the Theory of Planned Behavior (TPB) represents a key methodological contribution, enhancing WTP estimation by accounting for both socioeconomic and psychological variables such as attitudes, perceived behavioral control, and subjective norms. This approach yields deeper insights into the motivations behind conservation behavior and improves the reliability of non-market valuation. The findings show that most respondents value mangroves for their roles in coastal protection, fisheries, biodiversity conservation, and livelihoods, yet a notable share remain undecided or unwilling to pay, highlighting the need for targeted education and engagement initiatives. These results provide practical guidance for policymakers, suggesting the design of incentive-based programs, community-led conservation funds, and payment for ecosystem services (PES) mechanisms. Furthermore, the methodological framework developed in this study offers a replicable model for other regions facing similar conservation challenges. By fostering public participation and equitable benefit-sharing, this research supports the development of more inclusive and sustainable mangrove conservation strategies that ensure long-term ecological and socioeconomic resilience.