# Social acceptability of bioenergy cashew nut shells in agro-industries: Evidence from Burkina Faso for sustainable energy policy in Africa

Anselme Bagoro, Anthony Benoist, Marie Sawadogo

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Anselme Bagoro, Anthony Benoist, Marie Sawadogo. Social acceptability of bioenergy cashew nut shells in agro-industries: Evidence from Burkina Faso for sustainable energy policy in Africa. Scientific African, 2026, 31, pp.e03258. 10.1016/j.sciaf.2026.e03258. hal-05535742

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# Social acceptability of bioenergy cashew nut shells in agro-industries: Evidence from Burkina Faso for sustainable energy policy in Africa

Anselme Bagoro<sup>a, *, †</sup>, Anthony Benoist<sup>b, c, d †</sup>, Marie Sawadogo<sup>a</sup>

## ARTICLE INFO

Editor: DR B Gyampoh.

Keywords:

Community perceptions

Agro-industrial residues

Cashew nut shells

Social acceptability

Fractional logit model

West Africa

## ABSTRACT

Bioenergy valorization from agro-industrial biomass, particularly cashew nut shells, is increasingly adopted by agro-industries in West Africa as a strategy for waste management and energy supply. However, its long-term sustainability critically depends on social acceptability within local communities exposed to its environmental and economic impacts. Despite the rapid expansion of this practice, empirical evidence on its social acceptability in African agro-industrial contexts remains limited. This research investigates the key factors influencing acceptability among local populations, based on original field evidence from Burkina Faso. It combines a household survey (n = 320, margin of error = 4.20 %) with a multidimensional modelling framework. Social acceptability is first measured using Multiple Correspondence Analysis (MCA), to calculate an individual social acceptability score, then analysed through a fractional logit model to identify its main determinants. Results show that access to information about cashew nutshell energy valorization (p < 0.001), perception of smoke emissions (p < 0.001), and economic incentives (p < 0.001) are the main factors drivers of social acceptability. The type of combustion technology also has a significant effect (p < 0.05), while gender and site location (p < 0.10) moderately influence contextual factors on acceptability. By integrating social perceptions with econometric modelling of acceptability, this study provides new empirical evidence on how technological, environmental and institutional factors jointly shape community support for agro-industrial bioenergy in Africa. These findings highlight the need for energy policies that go beyond technical efficiency by prioritizing transparency, emission-reducing technologies and inclusive economic benefits to ensure socially sustainable bioenergy transitions.

## Introduction

The valorization of agro-industrial waste, particularly from processing plants, has gained global attention due to the scarcity of effective waste management techniques [1]. Among these waste materials, cashew nut shells, primary byproducts of raw cashew nut

<footnote><sup>a</sup> Laboratoire Energies Renouvelables et Efficacité Energétique (LabEREE), Institut International d'Ingénierie de l'Eau et de l'Environnement (2iE), Rue de la Science, Ouagadougou P.O. Box 594, Burkina Faso</footnote>

<footnote><sup>b</sup> CIRAD, Biomass Wood Energy Bioproducts Unit (BioWooEB), F-97743 Saint-Denis, La Réunion, France</footnote>

<footnote><sup>c</sup> BioWooEB, CIRAD, Université de Montpellier, Montpellier, France</footnote>

<footnote><sup>d</sup> Elsa, Research Group for Environmental Lifecycle and Sustainability Assessment, Montpellier, France</footnote>

<footnote>* Corresponding author.
E-mail addresses: anselme.bagoro@2ie-edu.org, bagoro2015@gmail.com (A. Bagoro).</footnote>
processing, present a promising source of chemicals and functional materials. As of 2019, Africa produces nearly 59 % of the world's cashew nuts, reflecting substantial growth in this sector [2].

In Burkina Faso, the cashew sector has experienced significant growth, with production increasing from approximately 72,899 tons per year in 2020 to 106,044 tons in 2021. The Hauts-Bassins region accounts for the majority of processing capacity, representing 70 % of the total [3]. Cashew nut shells, rich in organic content, contain around 20–25 % of an oil known as cashew nut shell liquid (CNSL) [4]. Traditionally challenging to manage, these shells were often discarded into the environment, leading to environmental issues such as soil acidification, biodiversity degradation, and fire hazards [5]. These challenges have driven industries in developing countries like Burkina Faso, Benin, and Côte d'Ivoire to explore alternative solutions.

To address environmental and waste management challenges, the energy valorization of cashew nut shells has emerged as a promising strategy in many countries of the Global South, particularly in West Africa [6]. However, in recent years, its implementation has raised growing concerns among local communities regarding environmental emissions and the distribution of benefits [5]. In Burkina Faso, a preliminary qualitative field survey conducted around several agro-industrial sites revealed underlying tensions between energy ambitions and the well-being of nearby populations. Respondents reported thick, black, and acrid smoke emissions accompanied by irritating odors, which they associated with respiratory discomfort and daily nuisance. These effects may be linked to the chemical composition of cashew nut shells particularly anacardic acid and cardol known for their corrosive and irritant properties [4]. These emerging concerns suggest that social acceptability is a critical factor for the successful implementation of such initiatives, especially in contexts where community engagement and perception play a decisive role. As Antwi & Ley [7] point out, renewable energy projects in Africa often fail when they are imposed without consideration for local realities. A financial approach alone is not enough. To be sustainable, these initiatives must include the social acceptability of communities and respect their norms and expectations.

While extensive research has focused on social acceptability, the majority approximately 60 % of publications, according to Batellier [8] centers on renewable energy sources such as wind farms and carbon sequestration [9].

In contrast, the energy valorization of agro-industrial residues, such as cashew nut shells, remains largely understudied from a social perspective. Existing research has primarily examined technical performance and valorization pathways [5,10], leaving a significant gap in understanding how local populations perceive, evaluate, and accept these technologies.

Beyond filling this thematic gap, this study makes a methodological and empirical contribution to the literature. It is among the first to quantify the social acceptability of agro-industrial bioenergy in Africa using household-level data rather than relying solely on qualitative or descriptive assessments. Social acceptability is operationalized through a multidimensional framework that constructs an individual acceptability index using Multiple Correspondence Analysis (MCA), capturing latent perceptions related to environmental, economic, and institutional factors. This index is then analysed using a fractional logit model, allowing a rigorous econometric estimation of how these dimensions jointly shape community support. This integrated approach goes beyond existing studies that typically examine these factors separately and offers a novel framework for assessing the social sustainability of bioenergy projects in agro-industrial contexts.

This research aims to enrich the literature by identifying the critical social, environmental, and economic factors influencing the acceptability of cashew nut shell energy valorization among local populations, in order to inform more sustainable, inclusive, and socially responsible energy policies. It also provides decision-makers and industry stakeholders with empirical evidence on how technological choices, benefit distribution, and information access shape community responses.

This study contributes new knowledge by providing the first quantitative evidence in West Africa on how environmental exposure, access to information, economic incentives, and combustion technologies jointly shape the social acceptability of agro-industrial bioenergy.

To achieve this objective, a survey was conducted among 320 households living near four industrial sites in Burkina Faso, selected based on their energy valorization technologies. The sample was defined using a two-step approach, ensuring a margin of error of 4.20 % and guaranteeing the results' reliability. Data analysis was performed using Stata 16 software, employing Multiple Correspondence Analysis (MCA) to calculate an individual social acceptability score, complemented by a fractional logit model to identify the main explanatory factors.

## Framework design: basic theories and research hypotheses

This study is based on several complementary theories to examine the factors influencing the social acceptability of the energy valorization of cashew nut shells. These theories include social, economic, environmental and psychological dimensions. By integrating these perspectives, the theoretical framework offers a structured approach to examining how different factors shape public perceptions and acceptability of this practice.

In the literature, a distinction is often made between social acceptability and social acceptance, although this should not be understood as a strict opposition between ex ante and ex post. Social acceptability [11] should rather be seen as a dynamic, negotiated, and territorially embedded process through which perceptions of legitimacy, fairness, and trust are continuously constructed and redefined. Similarly, social acceptance [12] refers to ongoing processes of social negotiation and feedback occurring at multiple levels socio-political, community, and market throughout the life cycle of an energy project. Recent developments in the literature Ellis et al. [13] also emphasize the importance of time, power relations, and scale in understanding these dynamics. In our case, the energy valorization of cashew nut shells remains an evolving process within processing industries, characterized by ongoing technological adjustments and shifting social perceptions. Therefore, the use of the concept of social acceptability provides an appropriate analytical framework for understanding how local perceptions are constructed, transformed, and consolidated over time. Although full adoption
has not yet been achieved, social acceptability remains relevant beyond the pre-decision phase, as it reflects the continuous evaluation and negotiation of project impacts by surrounding communities. Finally, we acknowledge that social acceptability and social acceptance are two interrelated notions that are sometimes used interchangeably in the literature [7]. In this study, we primarily mobilize the former while considering the latter as a complementary analytical perspective that enriches the understanding and interpretation.

First, a basis for analyzing how new technologies is adopted within a community is provided by [14] theory of the diffusion of innovation. Adoption of an innovation emphasizes perceived benefits, ease of use and compatibility with existing practices. This relates to the need to assess how local people perceive the technological aspects and socio-environmental impacts of cashew nut shelling. Given that certain processing technologies provide by-products such as biochar for households, it is important to analyze the extent to which these benefits influence their acceptability. Boudet [15] argue that individuals assess technologies based on their perceived environmental effects.

The theory of social acceptability, as discussed by Fortin & Fournis [11], explores the balance between perceived benefits and risks. Mies & Gold [16] highlight the importance of economic outcomes in gaining community support. Transparency, legitimacy, and trust in decision-making are key factors, supported by Schlosberg [17] theory of environmental justice, which focuses on fairness in the distribution of benefits and access to information. These perspectives show that perceptions of fairness and inclusiveness strongly influence acceptability. Berk et al. [18] adds that clear information on benefits and risks positively affects local perceptions, while and [19] emphasize the importance of trust in project leaders.

Psychologically, environmental psychology provides an understanding of how people interact with their environment [20]. The impact of environmental factors, such as air quality, is emphasized in the theory. In our case, energy recovery from cashew shells could lead to a deterioration in air quality and perceived health risks, thus influencing public perception. The energy valorization of cashew nut shells is not exempt from these environmental and health risks. Due to the emissions of black, acrid and irritating smoke due to the specific characteristics of the shells, which could lead to a deterioration in air quality and perceived health risks, thus influencing public perception. Include in the social acceptability study environmental and health issues as a key factor.

Finally, community engagement theory emphasizes the importance of meaningful public participation in decision-making [21]. Social acceptability is not simply a passive reaction to a project; it is actively built through commitment, negotiation, and establishing a relationship of trust. This perspective shows that projects involving local communities in decision-making are more likely to be accepted.

Taken together, these underlying theories identify several interconnected dimensions of social acceptability: the role of perceived benefits and risks (diffusion of innovation theory and social acceptability theory), the importance of equity and transparency

<figure><img src="image_3.png" /><figcaption>Fig. 1. Conceptual framework.</figcaption></figure>
(environmental justice theory and social acceptability theory), the influence of environmental and health concerns (environmental psychology) and the need for active community involvement (community engagement theory).

This integrated approach permits the formulation of hypotheses and an analytical framework that considers the complexity of social acceptability.

A conceptual framework for formulating the following research hypotheses is provided by the theories presented above:

**H1.** Perceived environmental impact, especially smoke emissions, is significantly associated with lower social acceptability among surrounding communities.

**H2.** Perceived economic benefits from cashew nut shell valorization are significantly associated with higher social acceptability.

**H3.** Current modes of energy valorization, defined by technologies and quantities of shell valorized, are significantly associated with social acceptability.

**H4.** The quality and transparency of information on cashew nutshell energy valorization projects are significantly associated with higher social acceptability.

**H5.** Trust in implementing a cashew nutshell energy valorization project is significantly associated with social acceptability.

Fig. 1 presents the conceptual framework of this research based on the formulated hypotheses.

## Methodology

### Context of the study and energy valorization sites

This study was conducted in Bobo-Dioulasso, the second-largest city in Burkina Faso, located in the Hauts-Bassins region. Bobo-Dioulasso is a major agro-industrial and economic hub, housing the majority of the country's cashew nut processing industries, which account for 80.94 % of the total national processing capacity [3]. These industries are concentrated in both urban and

<figure><img src="image_4.png" /><figcaption>**Fig. 2.** Study sites.</figcaption></figure>
semi-industrial zones, where surrounding communities frequently interact with industrial activities.

Four cashew nut processing sites were selected as study sites based on their energy valorization technologies and proximity to residential areas. The selected sites include two urban areas (U1 and U2), located in densely populated residential neighborhoods, and two semi-industrial zones (I1 and I2), located on the outskirts of the city but close to residential areas. These sites were chosen to compare different technologies and their social acceptability in varied urban and semi-industrial contexts. Fig. 2 show study sites based on their energy valorization technologies.

Each site uses different energy valorization methods for processing cashew nut shells:

* **Site I1 (Semi-industrial Area):** This site uses direct combustion in a boiler system for energy production. Despite these efforts, concerns about air quality persist due to continuous emissions from burning cashew nut shells.

* **Site I2 (Semi-industrial Area):** Site I2 uses a traditional three-stone stove for direct combustion of cashew nut shells. This method, common in rural areas.

* **Sites U1 and U2 (Urban Areas):** These sites use a post-combustion technology for the pyrolysis gases of cashew nut shells to produce biochar and volatile gases for heat production.

## Preliminary survey and determination of the target population

As part of this research, a preliminary survey was conducted in May 2023 around the four-cashew shell energy valorization sites. The primary objective of this pre-survey was to define specific influence radii for each site in order to identify the target population potentially affected by the valorization activities. A questionnaire was administered to households living near the sites (I1 and I2 in semi-industrial zones, and U1 and U2 in urban zones). This questionnaire aimed to collect information on residents' knowledge of valorization practices, their perceptions of smoke emissions, and the perceived impacts both positive and negative on their quality of life. To determine the influence radii, we considered the geographic proximity of households to the valorization sites as well as their exposure to these activities. Residents were asked about the frequency and intensity of smoke emissions and about other factors such as odors, irritation, and noise. We also recorded the GPS coordinates of residences to determine the distance between each home and the valorization site. This distance was used as a criterion to delimit the survey radius, while acknowledging that local topography and prevailing winds may lead to asymmetric smoke dispersion. An atmospheric dispersion model incorporating wind and topographic data would have been required to more accurately estimate actual exposure. However, for feasibility reasons, such modeling could not be implemented within the framework of this study, which we recognize as a limitation. The collected data were analyzed in QGIS to draw circular buffers delineating the areas of influence, based on the maximum distances at which residents reported being affected by smoke or other nuisances. This approach explains why the radii vary from one site to another, as they reflect locally perceived exposure limits rather than an arbitrary uniform distance. As a result of this spatial analysis in QGIS, the influence radii were obtained as 0.530 km for U1, 0.570 km for U2, 0.416 km for I1, and 0.300 km for I2.

This geographic approach allowed us to focus on households directly impacted by the valorization activities. By targeting this population within the defined influence radii, we aim to collect accurate data on the social acceptability of cashew shell energy valorization. This approach aims to ensure that the survey reflects the perceptions and considerations of the local communities on this issue.

## Sampling

The target population size was calculated based on the radius of influence from the preliminary survey, and the average household density for each site from available local population statistics. The estimated target population size for each site is shown in Table S1 in supplementary tables, yielding a total of approximately 774 households using the following formula (Eq. (1) and (2)):

$$N_i = D_i \times \pi \times r_i^2 \qquad (1)$$

$$N_{total} = \sum N_i \qquad (2)$$

i: Represents the district where the site is located, with i = 6 and 7.

N_i: Represents the total number of households among the target population around the site.

D_i: The average household density per square kilometer in the corresponding district i.

$\pi \times r_i^2$: The area of the influence zone to be surveyed around the site based on the considered radius

$N_{total}$: The total number of households targeted for this research.

The breakdown of households by site in the target population is as follows: approximately 216 households for site U1, 248 households for site U2, 181 households for site I1, and 130 households for site I2. A systematic random sampling method was applied to the target population, using a random walk approach. This resulted in a representative sample of 320 households, proportionally distributed among the sites. This approach further bolsters the reliability and accuracy of the findings concerning the social acceptability of cashew shell energy valorization activities. Table S1 in supplementary tables summarizes the sample size distribution and margin of error by site.

To ensure statistical accuracy and reliability, the margin of error was calculated using Cochran [22] formula (Eq. (3)), used to
determine the error margin associated with obtained samples (Eq. (4)). Based on the target population of 774 individuals and the sample size of 320 respondents, the global margin of error was approximately 4.20 % with a 95 % confidence interval.

$$n = \frac{Z^2 \times (1 - P) \times N \times P}{Z^2 \times P \times (1 - P) + (N - 1)E^2} \quad (3)$$

$$E = Z \times \sqrt{\frac{P(1-P)}{n}} \times \sqrt{\frac{N-n}{N-1}} \quad (4)$$

Where:

n:sample size

N: is the target population around the sites,

Z: is the z-score associated with a 95 % confidence interval (1.96).

P: is the estimated proportion of the population within the influence radius (approximated at 0.5), considered radius

E: is the margin of error

The margin of error in this study, which stands at 4 %, further supports the scientific rigor of our survey. Specific margins of error for each cashew nut shell energy recovery site was calculated at 10 %, 7 %, 9 %, and 9 %, all below the 10 % threshold. At a 95 % confidence level, these margins are in line with generally accepted standards for survey reliability, which typically range from 4 % to 10 % [23]. This guarantees the robustness and reliability of the data collected for each site. Additional statistical details are provided in Supplementary Table S1.

## Questionnaire design and data collection

A questionnaire was employed to collect data from the surrounding population, and its design was informed by existing literature [24]. The questionnaire was further refined after a preliminary survey, which helped tailor it to the specific context of the study site. Both the questionnaire and the preliminary survey details are provided in the supplementary material. The questionnaire is structured into six main sections:

(1). Sociodemographic information: Includes basic data such as the name of the survey site, location, gender, age, level of education, and professional status.

(2). Knowledge of Energy Valorization: Assessed participants' knowledge of energy valorization practices, including awareness of processing units and fuel types. Most questions were closed-ended to allow for quick responses.

(3). Perception of Energy Valorization: This question explored respondents' attitudes toward energy valorization, particularly regarding perceived environmental and health impacts. While most questions were closed-ended, some were semi-open to enable respondents to provide specific examples of perceived impacts.

(4). Energy valorization of cashew nut shells and quality of life and social acceptability: examines perceptions of environmental impacts, particularly the effects of smoke emissions from energy valorization. It focuses on their impact on local populations' well-being and overall acceptability.

(5). General attitudes: Evaluate respondents' general attitudes toward supporting or engaging with cashew nut shells.

(6). Suggestions and comments: Invite participants to share any additional feedback or suggestions they have.

In addition to these sections, we collected specific information on each site, such as geographical coordinates, recovery methods, technologies used, and quantity of biomass processed. The survey was conducted in July 2023 among 320 households, with one representative from each household.

## Ethical considerations

In this study, collecting personal data was essential, so anonymity was prioritized to protect respondents' identities. Precautions were taken to ensure confidentiality, with all data used solely for research purposes. The questionnaires did not request personal data that could identify participants.

Participants were fully informed about the study's objectives, and their participation was voluntary. In personal interviews, voice recordings were made only with consent. No participant was coerced, and they could withdraw at any time without consequences.

To protect participants' safety, especially during fieldwork involving environmental exposure assessments, protective gear was provided. The study followed the ethical guidelines set by the research ethics and deontology committee of the 2iE Institute (N°2023/01/DG/SG/DR/HK/fg), which approved the methodology.

Overall, the study adhered to strict ethical standards to ensure participant safety and data integrity.
Measurement of social acceptability for energy valorization of cashew nut shells

To measure the social acceptability of cashew nut shell energy valorization in processing industries in Burkina Faso, we selected five key variables from the questionnaire that capture individual perceptions and attitudes toward this practice. These variables focus solely on social aspects, ensuring that the analysis remains independent of economic, environmental, and technical factors. The selected variables are:

* General perception (positive or negative),

* Overall attitude (favorable or not),

* Personal support (agreement or not to support valorization),

* Personal acceptability (accepted or not within the community), and

* Social concern (concerned or not about social impacts).

We used Multiple Correspondence Analysis (MCA) to explore relationships among these categorical variables while reducing data complexity. MCA allowed us to transform the variables into binary indicators and create a Burt matrix. This approach extracted a primary axis that captured 94.44 % of the total inertia, representing most of the data variance. The contributions of different categories to this axis indicated that negative perceptions and lack of personal support are significant factors affecting social acceptability. To quantify attitudes and perceptions, we coded responses as 1 for positive and -1 for negative, facilitating their integration into the MCA. This coding choice directly influenced how modalities were represented in the factorial space, affecting their contribution to inertia and positioning on the axes. A social acceptability score was calculated using a weighted formula. Each variable was multiplied by its weight. This was determined by its contribution to the inertia of the central axis. The score was then normalized between 0 and 1. This is for ease of individual comparison and for making interpreting results more manageable. Data analysis using Stata 16. The formula (Eq. (5)) for calculating the score is as follows:

$$y_i = (w_1 \times x_1) + (w_2 \times x_2) + (w_3 \times x_3) + (w_4 \times x_4) + (w_5 \times x_5) \quad (5)$$

where:

* $y_i$ represents the social acceptability score calculated for each participant

* $w_1, w_2, ..., w_5$ are the weights assigned to each variable, based on their contribution to the inertia of the main axis in the analysis,

* $x_1, x_2, ..., x_5$ are the responses from individuals on each variable,

To normalize the score, we apply the following formula (Eq. (6)):

$$\text{social acceptability score normalized} = \frac{y_i - \text{minscore}}{\text{Max score} - \text{Min score}} \quad (6)$$

Where:

* Min score represents the lowest possible

* Max score represents the highest possible score

Theoretical model for the analysis of social acceptability factors of cashew shell energy valorization

The modeling of social acceptability for cashew shell energy recovery incorporates several contextual and explanatory factors. Because the dependent variable a normalized acceptability score lies between 0 and 1, a quasi-beta (fractional logit) model was used [25]. Unlike the standard beta model, it does not require strict distributional assumptions while ensuring predictions remain within the (0,1) interval. A logit link function models the relationship between the score and explanatory variables (Eq. (7)).

$$E(Y_i|X) = \frac{\exp(X\beta)}{1 + \exp(X\beta)} \quad (7)$$

$Y_i$ is the social acceptability score for individual i, $\exp(X\beta)$ explained by a linear combination of explanatory variables.

The theoretical model equation is specified as follows (Eq. (8)):

$$\text{logit}(Y_i) = \beta_0 + \beta_1 X_1 + \beta_2 X_2 + \dots + \beta_n X_n + \varepsilon_i \quad (8)$$

Where:

$Y_i$: represents the social acceptability score of individual i,

$\beta_0$: is the intercept, $\beta_1, \beta_2$ and $\beta_n$ are coefficients of the explanatory variables $X_1, X_2$ and $X_n$; $\varepsilon_i$: is the random error term accounts for unobserved influences.

The fractional logit model applies a logit link function to bounded proportions, ensuring predictions remain within the (0,1) interval and allowing coefficients to be interpreted as odds ratios. By maximizing a quasi-likelihood without strict distributional assumptions, it is particularly suited to discrete proportional data. This makes it especially appropriate for modeling the social
acceptability scores in our study, which are both bounded and discrete, while preserving the limited nature of these scores.

## Presentation of variables and empirical specification of the social acceptability model for energy valorization of cashew nut shells

This section details the variables selected for the empirical specification of the social acceptability model of cashew nutshell energy valorization. The choice of factors influencing social acceptability was based on a literature review, although few studies focus directly on the acceptability of cashew nut shell energy valorization. Consequently, this study identifies relevant factors by drawing on broader research into the social acceptability of energy projects.

### Presentation of variables in the social acceptability model

The variables included in the analysis perceived environmental impact, health and safety concerns, and trust in institutions are grounded in environmental psychology and social impact theory. They capture how individuals cognitively and emotionally respond to stressors such as pollution or industrial risk, factors known to drive conflict or rejection of energy projects.

Key determinants were drawn from the literature on community engagement and perception in renewable energy projects [9] and structured following Champagne & Côté-Demers [26]. The selected variables cover:

* **Social Factors:** Awareness, understanding, and information access [9] and relationships with stakeholders [27].

* **Economic Factors:** Financial benefits and perceived economic impacts on local populations [28].

* **Environmental & Quality of Life Factors:** Environmental concerns and quality of life, sometimes outweighing economic incentives [29].

* **Technological Factors:** Type and performance of energy valorization technologies [30].

* **Institutional Factors:** Regulatory frameworks and governance mechanisms [31].

Table 1 summarizes these variables used to estimate the factors influencing social acceptability of cashew nutshell energy valorization.

### Empirical specification of the fractional logit model

The following empirical model is presented to identify and evaluate the factors influencing the social acceptability of cashew nut shell energy utilization:

$$ \text{logit}(Y_i) = \beta_0 + \beta_1 \text{Gender} + \beta_2 \text{Socio Professional Category} + \beta_3 \text{Quality information} + \beta_4 \text{Distance} + \beta_5 \text{Duration of Exposure} \\ + \beta_6 \text{Location of the Site} + \beta_7 \text{Community Trust} + \beta_8 \text{Perceived Economic Benefits} \\ + \beta_9 \text{Type of Technologies Used & Quantity of Biomass Valorized} + \beta_{10} \text{Community Trust} + \varepsilon_i $$

This quasi-beta regression approach is suitable given the bounded nature of the dependent variable, ensuring robust estimation of

<table><caption>**Table 1**
Key variables.</caption><thead><tr><th>Variable</th><th>Description</th></tr></thead><tbody><tr><td><strong>Social</strong></td><td></td></tr><tr><td><strong>Gender</strong></td><td>Categorical variable for gender (1 = male, 0 = female).</td></tr><tr><td><strong>Socio-professional category</strong></td><td>Categorizes participants by professional status (1 = worker in the processing industry, 0 = other).</td></tr><tr><td><strong>Quality of information held</strong></td><td>Measures the quality of information communities hold about valorization. Indicates whether the respondent is informed about the energy valorization of cashew nut shells (1 = informed, 0 = not informed).</td></tr><tr><td><strong>Community Trust</strong></td><td>Level of trust in implementing a cashew shell valorization project. Indicates if the respondent supports the implementation of a project/regulatory framework for energy valorization of shells by the units (1 = Yes, 0 = No).</td></tr><tr><td><strong>Economic</strong></td><td></td></tr><tr><td><strong>Perceived economic benefits</strong></td><td>Perception of economic benefits, such as employment or co-products. Indicates if the respondent receives an economic incentive like cashew nut shell charcoal from the energy valorization unit (1 = Yes, 0 = No).</td></tr><tr><td><strong>Environmental</strong></td><td></td></tr><tr><td><strong>Perception of environmental impacts</strong></td><td>Perception of environmental impacts, especially smoke emissions. Indicates if the respondent observes environmental impacts from smoke emissions related to cashew shell valorization (1 = Yes, 0 = No).</td></tr><tr><td><strong>Technological</strong></td><td></td></tr><tr><td><strong>Type of Technologies Used & Quantity of Biomass Valorized</strong></td><td>Identifies the technologies used for energy valorization at each site and the amount of biomass valorized for a production cycle. (1 = direct combustion stove with 615 kg; 2 = pyrolysis stove with 300 kg; 3 = pyrolysis & open combustion stove with 930 kg; 4 = Traditional Three-Stone Fire with 100 kg.</td></tr><tr><td><strong>Institutional</strong></td><td></td></tr><tr><td><strong>Location of the site</strong></td><td>Indicates the type of the energy valorization site (1 = urban area, 0 = semi-industrial area).</td></tr><tr><td><strong>Duration of exposure</strong></td><td>Duration of exposure to potential impacts of energy valorization of cashew shells, defined by years of living around the valorization site.</td></tr><tr><td><strong>Distance</strong></td><td>Indicates the distance of households from the energy valorization site in meters.</td></tr></tbody></table>
the determinants of social acceptability across diverse dimensions (social, economic, environmental, technological, and institutional).

## Result

### Descriptive statistical results: sociodemographic factors of the respondents

Table S2 in supplementary presents descriptive socio-demographic factors considered in analyzing the social acceptability of the energetic use of cashew nutshells.

**Age:** The respondents' average age is 33, with the majority (52%) between 25 and 34 years old. Only 6.56% are over 44. The age variance of 0.569 suggests relative homogeneity, while a slight positive skewness (0.322) and kurtosis (2.87) imply a distribution that is primarily normal but slightly skewed toward older ages. These findings indicate that the sampled population is relatively young and well-balanced in age, though slightly skewed toward older individuals.

**Gender:** Women make up 54.38 % of the respondents.

**Residence Duration:** The average duration of residence near the sites is 11 years, with 45.4 % of respondents having lived in the community for over 10 years, suggesting a stable population. The variance (0.683), slight negative skewness (-0.372), and moderate kurtosis (0.156) indicate a relatively flat distribution, reflecting diverse residence durations.

**Socio-professional Category:** Approximately 66.88 % are not employed in an energy valorization industry related to cashew nut shells.

**Distance from Site:** Various distances between the household location and the valorization sites were considered: 0–50 m (25.16 %), 50–200 m (27.04 %), and 200–570 m (47.8 %). The distribution, variance (0.68), and negative skewness (-0.43) indicate a leftward concentration, meaning respondents reside closer to the sites.

**Location of Sites:** Approximately 42.81 % of the survey respondents live near sites located in semi-industrial areas, while 57.19 % are near urban sites.

These results help to delineate the demographic, socio-professional, and geographic characteristics of the survey respondents. Additional statistical details are provided in Supplementary table S2.

### Descriptive statistics: social acceptability of cashew shell energy valorization

The statistical analysis of the social acceptability scores shows an asymmetric distribution, with an asymmetry of (0.886) and a kurtosis of (2.353). This shows a positively skewed distribution, suggesting an above-average acceptability score, although some scores remain low.

Fig. 3 shows the distribution of respondents' social acceptability scores. Colors are used solely to enhance visual clarity and to differentiate the score intervals, without representing any predefined categories of social acceptability.

The results show that for scores between [0,0.1] and (0.1,0.2), where the number of respondents reaches about 40 and 18,

<figure><img src="image_5.png" /><figcaption>Fig. 3. Uncumulative distribution of social acceptability scores.</figcaption></figure>
respectively, there is a significant proportion of individuals with low acceptability scores.

The tendency is decreasing to [0.2, 0.4], indicating a transition to a simpler acceptability.

Starting from the intermediate values [0.4, 0.5] and [0.5, 0.6], the number of respondents increases, which indicates a more positive, although still mixed, perception. However, the relatively low frequency in the categories [0.6, 0.7] and [0.7, 0.8] reflect a particular uncertainty or partial acceptability. The highest values were found in the ranges (0.8, 0.0) and (0.9, 1), with almost 140 participants indicating greater acceptability of using cashew kernel hulls as an energy source.

This distribution highlights a polarization of perceptions: while a fraction of households surveyed expressed limited acceptability, the majority adopted a more favorable stance.

This distribution of the social acceptability score may be due to factors that need to be analyzed more closely to understand better the drivers of acceptability within the community, such as economic benefits, perception of environmental impacts, or the level of information available to the population.

Fig. 4 shows the cumulative distribution of social acceptability scores plotted against cumulative density.

The blue curve illustrates how social acceptability scores progress as cumulative density increases, while the orange segments highlight noticeable plateaus. These plateaus indicate distinct groups of respondents categorized by their levels of social acceptability: low, medium, and high.

* Low acceptability group (0 - 0.44): This group consists of respondents who may be concerned about the environmental or health risks associated with the energy valorization of cashew nuts. These concerns reveal areas where improved information or technological adaptations could reduce perceptions.

* Medium acceptability group (0.44 - 0.83): This group expresses more neutral or conditional acceptability, balancing the project's benefits and potential risks. Their opinions are balanced.

* High acceptability group (above 0.83): This group consists of people who strongly support the practice. They may accept it because they see the economic benefits as positive or trust the technology used. They represent a key demographic for practice support. They may act as community advocates for the initiative.

Acceptability groups show a diversity of perceptions regarding the social acceptability of cashew shell energy valorization.

## Factors influencing the social acceptability of cashew shell energy valorization

Table 2 presents the fractional logistic regression results. The model is globally significant ($\chi^2 = 233.02, p < 0.001$) and explains 28.7 % of the variance in social acceptability scores (pseudo-R$^2$ = 0.2872), which is acceptable for behavioral studies (McFadden, 1974).

Key determinants: Social acceptability is significantly influenced by awareness of energy valorization ($z = 3.69, p < 0.001$),

<figure><img src="image_6.png" /><figcaption>Fig. 4. Cumulative distribution of social acceptability scores by density.</figcaption></figure>
perceived smoke emissions ($z = 9.47, p < 0.001$), and economic incentives ($z = -4.54, p < 0.001$). Awareness enhances acceptability, while concerns about smoke reduce it. Surprisingly, economic incentives have a negative effect, suggesting that financial benefits do not offset environmental and health concerns.

**Technological effect:** The type of valorization technology ($z = -2.75, p < 0.05$) also matters, indicating skepticism toward current technologies.

Contextual factors such as Gender ($z = -1.95, p = 0.051$), site location ($z = -3.20, p = 0.001$), and household distance ($z = 2.31, p = 0.02$) have moderate effects: men and urban residents tend to be more supportive, and acceptability rises with distance from the site.

**Non-significant factors:** Duration of residence, professional category, and prior participation in energy projects show no significant effect.

## Distribution of social acceptability scores by selected variables

After identifying the factors influencing the social acceptability of cashew shell energy valorization, we examined the distributions of key significant variables such as perceptions of smoke emissions, information levels, economic benefits, and gender relative to acceptability scores through boxplots, histograms and scatter plots. These comparisons revealed perceptual distinctions within the sample population.

### Social acceptability scores and perceptions of smoke emissions

Figure S1 in supplementary figure shows a boxplot of acceptability scores based on respondents' perception of smoke emissions, divided into "Yes" (emissions are impactful) and "No" (emissions are not impactful).

The analysis of the acceptable score distribution, based on how smoke is perceived, shows a clear difference between the two groups. Respondents in the "No" group exhibit higher acceptability scores, with a median of 1. The concentration of the distribution in this group around higher values indicates a consistently positive opinion.

Those who answered "Yes" had a lower median score of around 0.13. The group had a wide range of scores from almost 0 to 1. This shows that people had different opinions.

These results show the importance of considering perceptions of smoke emissions' environmental impact when evaluating social acceptability.

### Social acceptability scores and information level

The box plot below (Figure S2) in supplementary figure shows how social acceptability scores are distributed based on how much respondents know about energy valorization (whether informed or uninformed).

The analysis reveals a subtle difference in median scores between the two groups, with informed individuals generally showing higher social acceptability scores a median of 1 and an average of 0.77. However, the wide score ranges in both groups indicate significant variability in perceptions.

The group that was not informed shows a more concentrated distribution around a lower median (0.57).

These results demonstrate that the social acceptability of the energy valorization of cashew nut shells depends on the level of information about this practice.

### Social acceptability scores and technology type

Figure S3 in supplementary figure illustrates the distribution of social acceptability scores for various technologies used in the energy valorization of cashew nut shells.

<table><caption>**Table 2**

Results of the fractional logit regression estimation.</caption><thead><tr><th>Variables</th><th>Coefficients</th><th>Values Z</th><th>P&gt;|z|</th></tr></thead><tbody><tr><td>Gender</td><td>-0.43 (0.224)</td><td>-1.95</td><td>0.051*</td></tr><tr><td>Duration of Exposure</td><td>-0.002 (0.015)</td><td>-0.18</td><td>0.855</td></tr><tr><td>Professional Category</td><td>-0.037 (0.246)</td><td>-0.15</td><td>0.878</td></tr><tr><td>Distance</td><td>0.001 (0.006)</td><td>2.31</td><td>0.021**</td></tr><tr><td>Site Location</td><td>-1.37 (0.429)</td><td>-3.20</td><td>0.001***</td></tr><tr><td>Information</td><td>0.76 (0.207)</td><td>3.69</td><td>0.000***</td></tr><tr><td>Economic Incentive</td><td>-1.13 (0.250)</td><td>-4.54</td><td>0.000***</td></tr><tr><td>Smoke Emissions</td><td>2.10 (0.222)</td><td>9.47</td><td>0.000***</td></tr><tr><td>Type of Stove and quantity of Shells Valorized</td><td>-0.54 (0.19)</td><td>-2.75</td><td>0.006**</td></tr><tr><td>Project/Program</td><td>-0.40 (0.387)</td><td>-1.04</td><td>0.297</td></tr><tr><td>Constant</td><td>2.25 (0.857)</td><td>2.63</td><td>0.009**</td></tr><tr><td>Number of obs = 320</td><td></td><td></td><td></td></tr><tr><td>Wald chi2(10) = 223.02</td><td></td><td></td><td></td></tr><tr><td>Prob &gt; chi2 = 0.0000</td><td></td><td></td><td></td></tr><tr><td>Pseudo R2 = 0.2872</td><td></td><td></td><td></td></tr><tr><td>Log pseudo-likelihood = -183.75</td><td></td><td></td><td></td></tr></tbody></table>

Note: Asterisks denote levels of significance: \*p < 0.10, \*\*p < 0.05, \*\*\*p < 0.01.
The analysis reveals significant variations in social acceptability across these technologies:

* **pyrolysis & open combustion with 930kg:** This combination has the highest average acceptability score of 0.80, with a median of 1 indicating strong acceptance. The skewed distribution toward higher scores suggests a generally favorable perception, likely due to its larger capacity and energy efficiency, although some respondents express reservations.

* **pyrolysis with 300 kg:** This technology shows a more even distribution around a median of 0.44, indicating consistent but lower social acceptability than the higher-capacity combination, suggesting moderate acceptance.

* **direct combustion with 615 kg:** This technology demonstrates relatively high acceptability with an average score of 0.722 and a median of 0.865. However, a slight skew toward lower scores implies that some respondents have less favorable views, possibly due to concerns about emissions or efficiency compared to pyrolysis stoves.

* **Traditional Three-Stone Fire** with 100kg: This stove has an average score of 0.671 and a median of 0.865, reflecting moderate acceptance. The distribution of scores shows a slight tendency towards lower scores.

Most respondents seem to assess the social acceptability of energy recovery positively as a function of technology, but some have a less favorable perception.

This negative perception may be linked to environmental concerns and perceived lower efficiency. Each technology has a group of respondents with mixed perceptions.

## Social acceptability scores and economic incentives

Figure S4 in supplementary figure presents the distribution of social acceptability scores about the "Economic Incentive" variable, distinguishing between individuals who receive this incentive and those who do not.

The group of non-beneficiaries exhibits a limited dispersion with consistently high social acceptability scores, reflected in a median close to 1 and an average score of 0.91. This suggests that, despite lacking economic support, many individuals in this group maintain a steady and positive acceptance of the energy valorization project.

In contrast, respondents receiving the benefits show a wider range of acceptability, from 0 to 1, with a median score of 0.67. This shows that people have different perceptions of the economic incentive. This suggests that some beneficiaries may have more expectations while others place less importance on perceived benefits in their evaluation of social acceptability.

## Social acceptability scores by gender

Figure S5 in supplementary illustrates the distribution of social acceptability scores by gender, highlighting slight variations between men and women:

The women's group presented a median social acceptability score of 0.67. The median score for men is around 1, higher than for women.

## Social acceptability scores and distance of households from the site

Figure S6 shows household distances from the cashew nutshell energy valorization site and their social acceptability scores. Acceptability rises progressively with distance. At 20 - 100 m, scores are highly dispersed, reflecting mixed perceptions some households report smoke, odors, and irritation, while others, influenced by economic benefits or better information, show high acceptance. These perceptions align with evidence that cashew shell combustion or pyrolysis emits incondensable gases (CO, CO, CH₄, H₂), fine particulates (PM₂.₅, PM₁), and toxic compounds such as acrolein and polycyclic aromatic hydrocarbons. Between 100–200 m, intermediate scores (0.46 - 0.8) increase, indicating more balanced views. Low scores decline at 200–300 m, while beyond 300 m acceptability generally exceeds 0.57. By 400–570 m, scores cluster near 1, reflecting minimal nuisance perception and stronger recognition of economic benefits.

## Social acceptability scores and site location

Figure S7 in supplementary illustrates the distribution of social acceptability scores based on site location, comparing semi-industrial areas with urban areas.

The median acceptability score for urban sites is slightly higher, indicating a positive perception.

The results show that people's perception of a location's acceptability does not change much based on its location.

## Discussion

The results of this study reveal several interrelated factors influencing the social acceptability of cashew nutshell energy recovery, including social, environmental, economic, technological, and institutional dimensions. However, these relationships should not be interpreted as static or one-time associations. In line with Ellis et al. [13] social acceptability is best understood as a dynamic and negotiated process that evolves over time, shaped by community experiences, power relations, and local contexts. The results presented here thus represent a particular stage in the ongoing social construction of acceptability around this emerging energy practice.

Perceptions of environmental impacts especially smoke emissions are critical determinants of social acceptability [32]. Negative perceptions of air pollution substantially decrease acceptability, consistent with Ali et al. [33]. From the perspective of environmental psychology, attitudes are influenced by lived experiences and by the perceived implications for quality of life [34,19]. Over time, as cleaner technologies are introduced and information circulates more widely, such perceptions may evolve, illustrating the temporal
dynamics of social evaluation.

Improving social acceptability therefore requires continuous efforts to reduce perceived environmental and health risks, notably through investments in less polluting and more efficient technologies. Consistent with and de Oliveira Galvão et al. [35], perceived health risks such as respiratory issues from smoke exposure remain major barriers. Managing these risks through emission-reduction technologies and participatory awareness campaigns can gradually shift public perceptions in a positive direction.

Perceived economic benefits also play a complex, evolving role in social acceptability [36]. In this study, their apparent negative association suggests that individuals economically involved in the valorization process develop higher expectations and thus more critical attitudes [37]. Such de Oliveira Galvão et al. [35] attitudes can be seen not as rejection, but as expressions of adaptive negotiation over fairness and transparency in benefit distribution. This finding highlights that social acceptability fluctuates with community learning and experience, reflecting an evolving relationship rather than fixed opposition.

Technological adoption also interacts dynamically with social perceptions. Research by Busse et al. [38] shows that cleaner combustion technologies can enhance community perceptions by reducing visible pollutants. The introduction of advanced systems such as staged combustion [39] demonstrates how technological innovation can gradually rebuild trust and reshape local evaluations of environmental justice. Contrary to our initial hypothesis, community trust did not show a significant statistical link with acceptability possibly because trust itself evolves more slowly and indirectly through iterative interactions and feedback mechanisms [12].

In urban sites, higher social acceptability may reflect greater exposure to information, more interaction with project representatives, and a longer history of coexistence with industrial activity. This aligns with the notion that acceptability develops cumulatively through social learning and contextual adaptation [40]. Gender differences also warrant further exploration, as gendered experiences can shape perceptions of both risk and fairness [41].

Overall, this study underscores that social acceptability of cashew nut shell energy valorization is not a fixed attitude but a dynamic trajectory of adjustment between perceived risks, technological performance, and local expectations. Managing these evolving perceptions requires ongoing engagement, equitable benefit-sharing, and transparent communication throughout the project's life cycle. Future longitudinal or participatory studies could capture these dynamics more fully and illuminate how social acceptability transforms as communities and technologies co-evolve.

## Conclusion and policy implications

Energy recovery from cashew nut shells, the main residue of raw cashew nut processing, has become a widespread practice in agro-industries. This approach offers an effective solution for managing agro-industrial waste while supplying thermal energy for food processing. However, its social acceptability within neighboring communities varies significantly and depends on multiple interrelated factors. While previous studies have mainly focused on the energy potential and technical valorization pathways of cashew shells, very few have examined the social conditions under which this practice becomes acceptable. This study addressed this gap by identifying the key social, environmental, and technological factors shaping the social acceptability of cashew nut shell energy valorization in Burkina Faso.

The results show that perceived environmental impacts, economic incentives, access to information, and combustion technology are central determinants of social acceptability. Communities are particularly sensitive to smoke emissions and the quality of information provided about risks and benefits. These findings indicate that an integrated strategy is required to ensure the long-term social sustainability of bioenergy projects based on cashew nut shells. Environmental regulations should therefore be strengthened, including stricter emission standards and the promotion of cleaner combustion technologies such as staged combustion systems.

This study also provides new and policy-relevant knowledge on the social acceptability of agro-industrial bioenergy in Africa. It shows that economic beneficiaries may be less supportive due to higher expectations and greater awareness of environmental risks, challenging the assumption that benefit-sharing automatically leads to acceptance. The results further establish a clear hierarchy of determinants, with access to information, smoke and pollution, and economic incentives playing a stronger role than socio-demographic factors or simple proximity to industrial sites. In addition, the significant effect of combustion technology demonstrates that technological choices are not only technical decisions but also social ones. Finally, by combining Multiple Correspondence Analysis with a fractional logit model, this study offers a transferable methodological framework for assessing social acceptability in other bioenergy and waste-to-energy projects across African contexts.

From a policy perspective, these results call for a multidimensional approach. Transparent governance and access to information should be prioritized to strengthen trust and raise community awareness of environmental and health risks. Technological innovation must focus on reducing smoke and pollutant emissions through investments in cleaner and more efficient combustion systems. At the same time, economic inclusion policies should be reinforced by designing fair and transparent incentive mechanisms that improve the perceived distribution of benefits among local populations. In addition, promoting the productive use of by-products such as biochar and ash in agriculture could further enhance the perceived value of cashew nut shell valorization for local communities.

Finally, this study highlights that social acceptability is not a fixed condition but a dynamic process shaped by technological change, information flows, and social learning. Recognizing this evolving nature is essential for designing adaptive energy policies and community engagement strategies capable of sustaining long-term support for bioenergy transitions in Africa.

## Institutional review board statement

The study was conducted in compliance with ethical standards and was approved by the Research Ethics and Deontology Committee of the 2iE Institute (N° 2023/01/DG/SG/DR/HK/fg) for studies involving human subjects.
**Informed consent statement**

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

**Declaration of generative AI and AI-assisted technologies in the writing process**

During the preparation of this work the author(s) used Chat GPT and Grammarly to reduce the word count, to enhance the language and readability of the text in english. After using these tools, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the publication.

**Funding**

This study has received funding from the European Union and French Development Agency (AFD) through the BioStar Project (FOOD/2019/410-794) in the frame of DeSIRA initiative. The contents of this document are the sole responsibility of the authors. They cannot be regarded as reflecting the position of the European Union or French Development Agency (AFD).

**CRediT authorship contribution statement**

**Anselme Bagoro:** Conceptualization, Methodology, Formal analysis, Investigation, Writing – original draft, Writing – review & editing. **Anthony Benoist:** Methodology, Formal analysis, Investigation, Writing – review & editing, Conceptualization, Resources, Supervision, Funding acquisition. **Marie Sawadogo:** Writing – review & editing, Conceptualization, Resources, Supervision, Funding acquisition.

**Declaration of competing interest**

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

**Acknowledgements**

We sincerely thank Adama BANEYA for his invaluable help and support during the data collection.

**Supplementary materials**

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.sciaf.2026.e03258.

**References**

[1] I. Prado-Acebo, J. Cubero-Cardoso, T.A. Lu-Chau, G. Eibes, Integral multi-valorization of agro-industrial wastes: a review, Waste Manag. 183 (2024) 42–52, https://doi.org/10.1016/J.WASMAN.2024.05.001.

[2] Peter, T., Léonard Cossi, H., Daouda, Y., & Alain, A. (2018). *Cashew Nut Processing in West Africa-Value Chain Analysis-Benin and Côte d'Ivoire*.

[3] S. Villard, A. Bamogo, J. Artigas Sancho, *Etude de faisabilité Valorisation de la coque de noix de cajou Burkina Faso*, https://www.nitidae.org/files/5951da84/rapport_final_de_1_etude_coqenstock sur_la_faisabilite_de_la Valorisation_de_la_coque_de_noix_de_cajou_au_burkina_faso.pdf, 2021.

[4] P.P. Kumar, R. Paramashivappa, P.J. Vithayathil, P.V.S. Rao, A.S. Rao, Process for isolation of cardanol from technical cashew (Anacardium occidentale L.) nut shell liquid, J. Agric. Food Chem. 50 (16) (2002) 4705–4708, https://doi.org/10.1021/JF020224W.

[5] T. Godjo, J.-P. Tagutchou, P. Naquin, R. Gourdon, Valorisation des coques d'anacarde par pyrolyse au Bénin, Environ. Ing. Dév. N°70-novembre 2015 (2015) 11–18, https://doi.org/10.4267/DECHETS-SCIENCES-TECHNIQUES.3282.

[6] M.L. Adekanbi, T.T. Olugasa, Utilizing cashew nut shell liquid for the sustainable production of biodiesel: a comprehensive review, Clean. Chem. Eng. 4 (2022) 100085, https://doi.org/10.1016/J.CLCE.2022.100085.

[7] S.H. Antwi, D. Ley, Renewable energy project implementation in Africa: ensuring sustainability through community acceptability, Sci. Afr. 11 (2021) e00679, https://doi.org/10.1016/J.SCIAF.2020.E00679.

[8] P. Batellier, Acceptabilité sociale : cartographie d'une notion et de ses usages. Les Publications du Centr'ERE, Centre de Recherche En éducation et Formation Relatives à L'environnement Et à L'écocitoyenneté (Centr'ERE), Université du Québec à Montréal (UQAM), 2015. https://www.espace-ressources.org/wp-content/uploads/2015/07/Batellier-2015-Acceptabilite-sociale.pdf.

[9] S. Alam, M.E. Moula, R. Lahdelma, Social acceptability of using low carbon building: a survey exploration, Int. J. Sustain. Energy 39 (10) (2020) 951–963, https://doi.org/10.1080/14786451.2020.1781852.

[10] M. Sawadogo, S. Tchini Tanoh, S. Sidibé, N. Kpai, I. Tankoano, Cleaner production in Burkina Faso: case study of fuel briquettes made from cashew industry waste, J. Clean Prod. 195 (2018) 1047–1056, https://doi.org/10.1016/J.JCLEPRO.2018.05.261.

[11] Y. Fournis, M.J. Fortin, From social 'acceptance' to social 'acceptability' of wind energy projects: towards a territorial perspective, J. Environ. Plan. Manag. 60 (1) (2017) 1–21, https://doi.org/10.1080/09640568.2015.1133406.

[12] R. Wüstenhagen, M. Wolsink, M.J. Bürer, Social acceptance of renewable energy innovation: an introduction to the concept, Energy Policy 35 (5) (2007) 2683–2691, https://doi.org/10.1016/J.ENPOL.2006.12.001.

[13] G. Ellis, N. Schneider, R. Wüstenhagen, Dynamics of social acceptance of renewable energy: an introduction to the concept, Energy Policy 181 (2023) 113706, https://doi.org/10.1016/J.ENPOL.2023.113706.
[14] E.M. Rogers, Diffusion of Innovations (3rd ed.), 3rd ed., The Free Press, 1983. https://teddykw2.files.wordpress.com/2012/07/everett-m-rogers-diffusion-of-innovations.pdf.

[15] H.S. Boudet, Public perceptions of and responses to new energy technologies, Nat. Energy 4 (6) (2019) 446–455, https://doi.org/10.1038/s41560-019-0399-x, 2019 4:6.

[16] A. Mies, S. Gold, Mapping the social dimension of the circular economy, J. Clean Prod. 321 (2021) 128960, https://doi.org/10.1016/J.JCLEPRO.2021.128960.

[17] D. Schlosberg, Defining environmental justice: theories, movements, and nature, Defin. Environ. Justice: Theor. Mov. Nat. 9780199286294 (2007) 1–256, https://doi.org/10.1093/ACPROF:OSO/9780199286294.001.0001.

[18] L. Berk, M. Berk, S. Dodd, C. Kelly, S. Cvetkovski, A.F. Jorm, Evaluation of the acceptability and usefulness of an information website for caregivers of people with bipolar disorder, Springer 11 (1) (2013), https://doi.org/10.1186/1741-7015-11-162.

[19] N.M.A. Huijts, E.J.E. Molin, L. Steg, Psychological factors influencing sustainable energy technology acceptance: a review-based comprehensive framework, Renew. Sustain. Energy Rev. 16 (1) (2012) 525–531, https://doi.org/10.1016/J.RSER.2011.08.018.

[20] R.G. Barker, *Ecological psychology: Concepts and Methods For Studying the Environment of Human Behavior*, Stanford University Press, 1968.

[21] S.R. Arnstein, A ladder of citizen participation, J. Am. Plan. Assoc. 35 (4) (1969) 216–224, https://doi.org/10.1080/01944366908977225.

[22] L.M. Cochran, et al., Fiches techniques et méthodologiques, Calc. Taille Un Échantill. Pour Une Enq. Chapter 3B Page 713 (1977) 1997. http://memento-assainissement.gret.org/IMG/pdf/memento-assainissement-fiche4.pdf.

[23] W.G. Cochran, Sampling Techniques, in: Biometrische Zeitschrift, 2nd edition, 7, John Wiley and Sons, Inc, 1963, https://doi.org/10.1002/BIMJ.19650070312.I Issue.

[24] I. Ajzen, M. Fishbein, Attitude-behavior relations: a theoretical analysis and review of empirical research, Psychol. Bull. 84 (5) (1977) 888–918, https://doi.org/10.1037/0033-2909.84.5.888.

[25] L.E. Papke, J.M. Wooldridge, Econometric methods for fractional response variables with an application to 401 (k) plan participation rates, JM Wooldridge J. Appl. Econom. (1993), https://doi.org/10.1002/(SICI)1099-1255(199611)11:6 (147; Technical Working Paper Series).

[26] M. Champagne, M. Côté-Demers, Acceptabilité sociale d'un projet de développement minier: questionnaire d'analyse, Éd. JFD Inc (2020).

[27] F. Dessi, S. Ariccio, T. Albers, S. Alves, N. Ludovico, M. Bonaiuto, Sustainable technology acceptability: mapping technological, contextual, and social-psychological determinants of EU stakeholders' biofuel acceptance, Renew. Sustain. Energy Rev. 158 (2022) 112114, https://doi.org/10.1016/J.RSER.2022.112114.

[28] K. Ingold, I. Stadelmann-Steffen, L. Kammermann, The acceptance of instruments in instrument mix situations: citizens' perspective on Swiss energy transition, Res. Policy 48 (10) (2019) 103694, https://doi.org/10.1016/J.RESPOL.2018.10.018.

[29] D. Bugden, R. Stedman, A synthetic view of acceptance and engagement with smart meters in the United States, Energy Res. Soc. Sci. 47 (2019) 137–145, https://doi.org/10.1016/J.ERSS.2018.08.025.

[30] O. Ellabban, H. Abu-Rub, Smart grid customers' acceptance and engagement: an overview, Renew. Sustain. Energy Rev. 65 (2016) 1285–1298, https://doi.org/10.1016/J.RSER.2016.06.021.

[31] V.H.M. Visschers, M. Siegrist, Fair play in energy policy decisions: procedural fairness, outcome fairness and acceptance of the decision to rebuild nuclear power plants, Energy Policy 46 (2012) 292–300, https://doi.org/10.1016/J.ENPOL.2012.03.062.

[32] Sella, L., Rota, F.S., & Pollo, N. (2024). *How to measure the social acceptability of alternative environmental management solutions in wetlands and other ecosystems* (1/2024; CNR-IRCrES Working Paper). https://doi.org/10.23760/2421-7158.2024.001.

[33] A. Ali, H. Ayaz, A. Alzahrani, M.A. Alhashem, K. Al-Ghamdi, M. Shafiullah, Rooftop solar photovoltaic system social acceptance in Saudi Arabian residential sector: unveiling public sentiments a survey study, in: 2024 7th International Conference on Energy Conservation and Efficiency, ICECE 2024 - Proceedings, 2024, https://doi.org/10.1109/ICECE61222.2024.10505265.

[34] P. Devine-Wright, Local aspects of UK renewable energy development: exploring public beliefs and policy implications, Local Environ. 10 (1) (2005) 57–69, https://doi.org/10.1080/1354983042000309315.

[35] M.F. de Oliveira Galvão, J.D.F. de Queiroz, E. Duarte, S.F. de, J.J. Hoelzemann, P.A. de André, P.H.N. Saldiva, J.A. Menezes Filho, S.R. Batistuzzo de Medeiros, Characterization of the particulate matter and relationship between buccal micronucleus and urinary 1-hydroxytyrene levels among cashew nut roasting workers, Environ. Pollut. 220 (2017) 659–671, https://doi.org/10.1016/J.ENVPOL.2016.10.024.

[36] M. Wolsink, Planning of renewables schemes: deliberative and fair decision-making on landscape issues instead of reproachful accusations of non-cooperation, Energy Policy 35 (5) (2007) 2692–2704, https://doi.org/10.1016/J.ENPOL.2006.12.002.

[37] R. Mohloding, B. Phogole, K. Yessoufou, Household acceptance of solar water heaters in South Africa: an expectancy-disconfirmation model, Util. Policy 95 (2025) 101916, https://doi.org/10.1016/J.JUP.2025.101916.

[38] M. Busse, R. Siebert, N. Heitepriem, Acceptability of innovative biomass heating plants in a German case study-a contribution to cultural landscape management and local energy supply, Energy Sustain. Soc. 36 (2019) 1–15, https://doi.org/10.1186/s13705-019-0215-2. 9.

[39] O. Karlström, E. Vainio, M. Engblom, A. Brink, M. Hupa, Effect of air staging on NOx emissions in biomass combustion in a bubbling fluidized bed, Fuel 330 (2022) 125565, https://doi.org/10.1016/J.FUEL.2022.125565.

[40] S. Batel, P. Devine-Wright, Towards a better understanding of people's responses to renewable energy technologies: insights from Social Representations Theory, Public Underst. Sci. 24 (3) (2015) 311–325, https://doi.org/10.1177/0963662513514165.

[41] A. Vainio, R. Paloniemi, The complex role of attitudes toward science in pro-environmental consumption in the Nordic countries, Ecol. Econ. 108 (2014) 18–27, https://doi.org/10.1016/J.ECOLECON.2014.09.026.