Spatial Variations in Perceptions of Decarbonization Impacts and Public Acceptance of the Bioeconomy in Western Macedonia

Abstract

This study examines the regional disparities in public perceptions of decarbonization and the acceptance of the bioeconomy within Western Macedonia, a Greek region undergoing structural economic change. While the environmental benefits of decarbonization, such as reduced carbon emissions and improved air quality, are widely acknowledged, perceptions of economic and social outcomes, including investments, new business development, and policy support, vary significantly across sub-regions. To this end, a structured survey was conducted among 765 residents, utilizing Likert-scale items to assess attitudes, with demographic data providing a contextual framework. Statistical analyses, incorporating techniques such as one-way analysis of variance (ANOVA), Kruskal–Wallis, and multiple regression, were employed to explore spatial variations and identify the primary drivers of bioeconomy acceptance. The results indicate that perceived government action, visible investment, new enterprises, and a positive view of public sentiment are all significant predictors of acceptance, with institutional support showing the strongest influence. The findings reveal that certain areas feel less engaged in the transition, expressing skepticism about its benefits, while others report more optimism. This disparity in perception underscores the necessity for targeted policy interventions to ensure inclusive and equitable participation. The study emphasizes the necessity for regionally responsive governance, enhanced communication strategies, and tangible local development initiatives to cultivate public trust and support. The study makes a significant contribution to the broader discourse on just transitions by emphasizing the role of place-based perceptions in shaping sustainable change.

1. Introduction

Decarbonization refers to the process of reducing carbon dioxide emissions through the transition from fossil fuels to low-carbon energy sources, representing a central pillar in the fight against climate change and a core target of EU climate policy frameworks [1,2]. The primary benefit of pursuing carbon neutrality is the mitigation of negative environmental impacts and a slowing of the global temperature rise [3]. In line with this, virtually every nation has signaled its commitment to deep decarbonization, with all 198 countries analyzed by the early months of 2022 having pledged to achieve carbon-neutral targets in the coming decades [4]. This global commitment is indicative of a collective recognition of the significant environmental benefits that transitioning away from fossil fuels can provide, ranging from climate stabilization to improved air quality [3,5]. In summary, decarbonization is not only technically feasible but also widely regarded as imperative for sustainable futures [6].

In the scholarly literature, decarbonization is increasingly framed as a driver of systemic transformations in regional economies and labor markets. Although the environmental rationale for reducing carbon emissions is global, the economic and social impacts of decarbonization are unfolding in spatially uneven ways. Scholars have warned that, without deliberate policy interventions, low-carbon transitions may exacerbate existing socio-spatial inequalities and disproportionately affect already vulnerable communities [7,8,9,10]. Empirical evidence from the energy sector lends weight to these concerns. For instance, projections by the International Renewable Energy Agency (IRENA) suggest that global renewable energy employment could reach 42 million by 2050—more than triple the current levels [11]. However, these gains are expected to be unevenly distributed: over half of the new jobs are projected to emerge in Asia, due in part to its large population base and rapidly expanding clean energy markets, while regions such as sub-Saharan Africa may capture only a minimal share of the employment benefits. These regional disparities highlight the risk of producing “winners and losers” in the transition process. As a result, there is growing advocacy for a just transition framework that ensures the equitable distribution of decarbonization benefits by targeting investments and capacity-building efforts toward lagging or disadvantaged regions. Addressing such uneven development outcomes is increasingly seen as essential to maintaining public support for climate policies and ensuring the long-term socio-economic sustainability of the transition.

The achievement of decarbonization is contingent upon public acceptance of novel technologies and economic models [2,12]. The bioeconomy, understood as the production, utilization, and regeneration of biological resources to provide sustainable products and services, has emerged as a pivotal component of low-carbon strategies [13,14,15]. Many countries regard the bioeconomy as a driver of green growth and innovation, from bio-based materials and fuels to circular agricultural systems [16,17,18].

Nevertheless, even the most promising bio-based solutions require broad public support to be successfully implemented [16]. Historical experience shows that technologies which are technically and economically viable can fail if communities perceive them as risky, inequitable, or misaligned with local values and interests [19]. It is, therefore, vital to understand what factors shape the public acceptance of bioeconomy initiatives in different locales [20,21].

The interaction between politics and regional context exerts a significant influence on the outcomes and perceptions of the energy transition [22,23]. There is an increasing expectation on the part of policymakers at all levels to ensure that decarbonization progresses in a fair, regionally inclusive manner [2,7]. Targeted interventions have become imperative, especially for communities with a long-standing reliance on high-carbon industries [24]. For instance, the European Union has allocated considerable resources to support coal-dependent regions, with the objective of ensuring that the transition to clean energy is “equitable and no region is left behind” [25]. In addition, energy transition leaders emphasize that addressing entrenched inequalities necessitates unprecedented governmental action to distribute new opportunities across all areas of society [26,27]. The implementation of progressive climate and energy policies is regarded as being pivotal to enhancing the socio-economic benefits of decarbonization and extending them beyond advanced economic centres [28,29]. This encompasses investments in green infrastructure and education, as well as the provision of social safeguards and retraining programmes in regions experiencing industrial upheaval.

It is imperative to acknowledge the existence of a dynamic feedback loop between public perceptions and policy action within this domain [30]. On the one hand, the implementation of government measures that are responsive to public attitudes can influence public opinion [31]. For instance, incentive programmes that deliver visible community benefits have been shown to generate political support for the entrenchment of further transition policies [32]. The observation of tangible benefits, such as new employment opportunities, enhanced services, or other co-benefits, arising from decarbonization initiatives, has been demonstrated to foster increased acceptance among the public [33]. Consequently, this heightened acceptance often gives rise to the formation of a constituency that advocates for the continuation of the transition. Conversely, public sentiment (and subsequent backlash) can exert a direct influence on the trajectory of policy. For instance, when citizens perceive themselves to be excluded or unfairly burdened, they may resist projects or demand policy adjustments [34]. This phenomenon has been observed in cases where a lack of local support signaled deeper issues of environmental injustice [35,36]. This dynamic interplay between public perceptions and policy decisions is a continuous and reciprocal process, shaping the evolution of both [37]. The governance of such transitions, therefore, necessitates the establishment of effective feedback mechanisms, which, if they are to be effective, must be iterative, engaging with communities, gauging public sentiment, and refining policies accordingly, in order to build and maintain momentum [38]. In conclusion, effective government leadership, in conjunction with attentive public dialogue, is imperative for navigating the political and regional complexities of decarbonization in an equitable manner [39,40].

In consideration of the aforementioned context, it is evident that there exists a compelling rationale for the examination of spatial variations in relation to the perception of decarbonization impacts and the acceptance of the bioeconomy [41,42]. Energy transitions are not occurring in isolation; they are profoundly place-based processes [43]. The transition is subject to variations in regional economies, cultures, and institutional support, resulting in diverse experiences and perceptions among communities. A green economic boom, for example, might be welcomed in one region but viewed with skepticism or concern in another, depending on the local context [44,45]. Consequently, there is a necessity for further research in this area, as previous studies have stressed that sustainability transitions happen in “situated, particular places” [46] and call for deeper engagement with the socio-spatial dimensions of change [47]. However, the transition literature has historically overlooked the role of geography, particularly the disparities in gains and losses across different regions and the variation in public opinion by locale [48]. This oversight has far-reaching consequences, as disregarding spatial heterogeneity can result in the implementation of one-size-fits-all policies that fail to address local needs, potentially engendering perceptions of injustice or inciting opposition.

The examination of geographical disparities in perception and acceptance offers scholars and policymakers a valuable opportunity to elucidate the underlying factors that precipitate the adoption of decarbonization initiatives in certain regions while others exhibit hesitancy [49,50,51]. This insight is particularly pertinent to the bioeconomy, which frequently intersects with local industries (agriculture, forestry, etc.) and, thus, gives rise to region-specific interests and concerns [52]. A spatial perspective facilitates the identification of the drivers and barriers operating in diverse regions, encompassing factors such as the prevalence of green employment opportunities and investments, the robustness of policy frameworks, and prevailing community perceptions. The importance of targeted strategies is also emphasized: for instance, regions lagging in public acceptance might benefit from additional outreach, compensation mechanisms, or development programmes tailored to their socio-economic context [53,54]. Conversely, regions with favorable perceptions can function as exemplars or innovation hubs, disseminating best practices to other regions. Incorporating a spatial perspective into the discourse on the global energy transition enriches our understanding of public acceptance as a dynamic, geographically differentiated phenomenon. This perspective is consistent with the growing emphasis on “just transitions” which emphasizes the need to ensure that decarbonization and the growth of the bioeconomy proceed in ways that are not only environmentally effective but also socially inclusive across all regions [55,56].

Although the literature on just transitions highlights the importance of interactive dialogue, participatory governance, and the establishment of feedback mechanisms as central components of inclusive decarbonization processes [22,23,37], the present study concentrates on a specific and empirically measurable dimension within this broader framework: public acceptance and perception. While acceptance does not inherently imply participation or co-creation, it constitutes a foundational condition for the effectiveness and legitimacy of governance strategies. Public trust and demonstrated support are frequently precursors to more substantive forms of engagement. Accordingly, although this study does not directly assess participatory design or institutional responsiveness, it offers valuable insights into how individuals evaluate the perceived outcomes and credibility of transition initiatives in their locality. These findings can inform policy efforts aimed at fostering the societal preconditions necessary for more inclusive and participatory transition pathways.

Against this backdrop, the present study investigates how the impacts of decarbonization and the development of the bioeconomy are perceived across the four regional units of Western Macedonia, a Greek region undergoing structural transition. The analysis draws on original survey data (n = 765) and employs descriptive statistics, ANOVA, and Kruskal–Wallis tests to identify the spatial variation in perceived environmental, economic, and social impacts, as well as levels of public acceptance.

The manuscript is divided into five sections. The introduction outlines the context, rationale, and research gap. The Material and Methods section details the analytical approach and data sources. The Results and Discussion section presents the key findings and interprets them in light of international comparisons. Finally, the Conclusion summarizes the main insights and offers policy implications for advancing an inclusive and regionally balanced energy transition.

2. Materials and Methods

2.1. Study Area

Western Macedonia (Figure 1) is currently experiencing an energy transition, also referred to as “decarbonization” [57]. Western Macedonia’s energy transition refers to the region’s systematic shift away from its historical dependence on lignite (brown coal) for energy production. For decades, the region was the main hub of coal-based electricity generation in Greece, hosting large-scale power plants and lignite mining operations. The term “decarbonization” in this context specifically denotes the gradual phasing out of lignite-based energy and its replacement with cleaner, low-carbon energy sources such as renewables (e.g., photovoltaics and wind), alongside investments in green infrastructure, retraining programmes, and alternative economic models. This transition, mandated by both national policy and EU-level climate targets, represents not only a technical energy shift but also a structural economic transformation with far-reaching implications for employment, regional development, and social cohesion [58].

Existing bioeconomy activities in Western Macedonia are relatively nascent and unevenly distributed across regional units. While the regional capital Kozani has seen early-stage investments in circular bio-based startups and pilot projects in agri-waste valorization, other areas such as Grevena report minimal visible activity. Florina and Kastoria have witnessed some engagement through educational initiatives or local cooperative ventures. These differences provide context to the spatial variation in public perceptions, as some residents may have directly observed bioeconomy efforts while others remain unfamiliar with the concept beyond policy rhetoric [59].

2.2. Survey Design and Implementation

A structured survey was conducted to assess the socio-economic and environmental impacts of the decarbonization process in Western Macedonia, as well as to evaluate public acceptance of the emerging bioeconomy. The survey targeted the general adult population (aged 18 and above) across all four regional units of Western Macedonia. Participants were recruited using a stratified convenience sampling strategy through both online dissemination (email, and social media) and in-person outreach conducted in public spaces and municipal buildings. Data collection took place between December 2024 and May 2025. Out of approximately 900 individuals approached, 765 completed the questionnaire, yielding a response rate of approximately 85%. The regional distribution of valid responses was as follows: Kozani (403), Florina (172), Kastoria (109), and Grevena (81). While the sample size varies across regions, each exceeds the minimum threshold for non-parametric analysis. The Kruskal–Wallis test, which does not assume equal variances or normally distributed data, was employed specifically to accommodate these variations and ensure statistical validity. While efforts were made to ensure geographic and demographic diversity, potential selection biases—particularly those related to digital access and prior interest in the subject matter—cannot be entirely excluded; these limitations are further addressed in the concluding section.

The final sample included a broad distribution across age groups. Approximately 46% of respondents were aged 30–59, 34% were under 30, and 20% were over 60. This variation enhances the representativeness of perspectives across generations. Regarding education, the majority of respondents held at least a secondary or tertiary qualification, reflecting a population with sufficient educational background to comprehend and respond meaningfully to the survey items. This demographic structure supports the reliability of the responses. Furthermore, to ensure comprehension, all survey items were written in plain language and pilot-tested with non-expert respondents prior to full deployment. The Greek-language version used in the study included clarifying phrases where needed, especially for items related to environmental impacts such as biodiversity and land use. Respondents were able to complete the questionnaire at their own pace and had access to explanatory text where appropriate.

Respondents were asked to rate a series of statements using a 5-point Likert scale (1 = “Strongly Disagree” to 5 = “Strongly Agree”) pertaining to the perceived impacts of decarbonization (e.g., on GDP, unemployment, and CO₂ emissions) and the status of the regional bioeconomy (e.g., levels of investment, public perception, and policy engagement). The dataset also includes demographic information such as gender, age group, educational attainment, and the respondent’s specific regional unit. The analysis that follows employs two main statistical approaches in alignment with the study’s research objectives (see Figure 2): first, it compares public perceptions across the four sub-regions of Western Macedonia; and, second, it identifies the factors most strongly associated with the level of public acceptance of the bioeconomy.

2.3. Reliability and Validity

The survey data comprise both categorical demographics and Likert-scale opinion items. Each Likert item ranges from 1 to 5, indicating increasing agreement. Despite the ordinal nature of Likert responses, it is customary to treat them as approximately interval-level data when multiple categories and large samples are involved [60,61]. This methodological approach enables the utilization of parametric tests (e.g., ANOVA and regression) to facilitate more robust analysis, while underscoring the imperative for meticulous assumption verification. In this study, parametric analyses were conducted, and the findings were validated through the implementation of non-parametric methods in instances where assumptions were found to be violated.

In order to ascertain whether perceptions vary according to region, a comparison was made of mean Likert scores across the four regional units for key survey items. One-way analysis of variance (ANOVA) tests were conducted for selected variables [62] representing economic, environmental, and social aspects (for example, perceived increase in bioeconomy investments, new bioeconomy businesses, air quality improvement, etc.). Post hoc tests (Tukey’s HSD) were then used to identify which regions differed significantly. In instances where the Likert distributions were found to be skewed or possessed unequal variances, non-parametric Kruskal–Wallis tests were employed as a measure of robustness [63].

In order to assess which factors predict the perceived acceptance of the bioeconomy, a multiple linear regression was fitted with “The bioeconomy is accepted in the region” (Likert 1–5) as the dependent variable. Predictors were selected based on their plausible influence on acceptance, including “Investment in the bioeconomy has increased,” “There are new businesses in the bioeconomy sector,” “Public perception of the bioeconomy is positive,” and “The region has implemented policies and subsidies for the bioeconomy.” These factors are hypothesized to encompass economic developments, public opinion, and institutional support. Following preliminary assessments, demographic variables were found to be non-significant predictors of acceptance and were, therefore, excluded from the final model.

All statistical tests were conducted at a significant level of α = 0.05 (two-tailed). The following assumptions were verified for both ANOVA and regression [64,65]:

The normality of the ANOVA was ascertained as follows: Given the substantial sample size per group (range: 81 to 403 respondents in each region), the F-test demonstrates notable robustness to non-normal data. Nevertheless, the distribution of responses for each region was examined. While many Likert variables exhibited slight skew (e.g., the majority of respondents expressed agreement that “CO₂ emissions have decreased”), no severe deviations were identified. The decision was taken not to transform the ordinal data, as the interpretation in the original scale is clearer. In instances where normality was questionable, the non-parametric Kruskal–Wallis test was employed to corroborate the findings of the ANOVA.

In order to ascertain the homogeneity of the ANOVA, Levene’s test was employed to verify the equality of variances across the various regions [66]. For certain items, such as “Investment in bioeconomy has increased”, Levene’s test was found to be significant (p < 0.001), thus indicating heterogeneity of variances. In such cases, the interpretation of the ANOVA should be approached with caution, and, where applicable, the use of Welch’s ANOVA is recommended [67]. Furthermore, the validation of group differences was undertaken using Kruskal–Wallis, which does not assume equal variances [68]. For other variables, variances were found to be homogeneous (Levene’s p > 0.05).

Regarding regression assumptions, linearity and additivity were checked by examining the scatterplots of each predictor against the outcome. The independence of the observations holds as each respondent is independent [69]. Residual diagnostics showed an almost normal distribution of errors (small negative skewness ≈ −0.31); the large sample resulted in a significant Shapiro–Wilk test (p < 0.001), but Q-Q plots showed only a small deviation. Homoscedasticity was supported by a random scatter of residuals versus fitted values. Multicollinearity was also assessed: variance inflation factors (VIF) were low (~1.1–1.3) for all predictors, indicating no multicollinearity of concern.

3. Results

3.1. Regional Differences in Perceptions

Given the variation in sample sizes across regions, non-parametric tests were used to ensure robustness in comparing ordinal responses between groups. The results of the survey indicated a uniform acknowledgement among respondents of the environmental improvements attributable to decarbonization across the region. However, a more pronounced variation in opinion was observed with regard to economic and social outcomes, with responses demonstrating a greater degree of heterogeneity across different geographical areas. The majority of respondents expressed agreement with the statement “CO₂ emissions have decreased” (overall mean ≈4.13 on the 5-point scale, corresponding to “Agree”). Similarly, air quality improvements were widely recognized (overall mean ~3.9). Conversely, perceptions of favorable economic developments in the bioeconomy were found to be minimal, with a significant proportion of respondents expressing disagreement with the statement “Investment in the bioeconomy has increased” (overall mean ~1.7, between “Strongly Disagree” and “Disagree”) (

Table 1. Descriptive table.

Variable	Overall Mean (SD)	Scale
CO2 emissions have decreased	4.13	1–5
Air quality improvement	3.91	1–5
Perceived emergence of new bioeconomy businesses	1.72	1–5
New bioeconomy businesses exist	2.21	1–5
Bioeconomy is accepted in the region	3.08	1–5
Education and training programmes	3.60	1–5

Source: author’s own creation.

). It was observed that certain regions consistently reported lower scores on these development-related items than others, suggesting an uneven regional experience in the transition.

To examine whether perceptions differed across regional units, statistical tests such as ANOVA (analysis of variance) and the Kruskal–Wallis test were applied. These tests help determine whether there are statistically significant differences in survey responses between groups. ANOVA is used when the data meet certain assumptions (e.g., equal variances), while the Kruskal–Wallis test is its non-parametric counterpart, used when those assumptions are not met. These analyses ensure the robustness of the findings regarding spatial variation in public attitudes.

A one-way analysis of variance (ANOVA) revealed several significant differences between the four regional units on key survey items.

Table 2. ANOVA results for regional comparisons.

Variable	F	p-Value
Perceived increase in bioeconomy investment	10.92	0.0
Perceived emergence of new bioeconomy businesses	4.48	0.004
Air quality improvement	3.39	0.018
Biodiversity and land use	1.39	0.24
Education and training programmes	8.81	0.0
Green technology investments	6.92	0.0

Source: author’s own creation.

provides a concise overview of these findings.

A significant effect of the region on the belief that bioeconomy investment has increased was identified (F = 10.92, p < 0.001). The regional unit of Grevena exhibited an exceptionally low mean score (M ≈ 1.09, SD = 0.29), denoting pervasive strong disagreement that investments have increased. In contrast, the regional unit of Kozani demonstrated a higher mean score (M ≈ 1.86, SD = 1.13), although it remained within the disagree category. The regional units of Kastoria and Florina exhibited intermediate mean scores of 1.58 and 1.58, respectively. Post hoc comparisons (Tukey HSD) confirmed that Grevena was significantly lower than Kozani and Kastoria (p < 0.01), and also lower than Florina (p < 0.05). Conversely, Kozani’s mean was modestly but significantly higher than Kastoria’s (p = 0.04). These differences were corroborated by a non-parametric Kruskal–Wallis test (H = 38.68, p = 0.000), reinforcing the idea that respondents in some areas (notably Grevena) report substantially less investment activity than others.

A comparable regional pattern was observed for the statement, “There are new businesses in the bioeconomy sector.” The analysis of variance (ANOVA) revealed a significant result (F = 4.48, p = 0.004). Grevena once again demonstrated the lowest level of agreement (M ≈ 1.95), a result that differed significantly from the levels observed in Kastoria (M ≈ 2.41, p = 0.012) and Kozani (M ≈ 2.44, p = 0.002). This suggests that respondents from Grevena perceived a notable absence of new bio-based firms, while those in other regions, while generally still in disagreement (means below 2.5), reported slightly more of such activity. This finding suggests that nascent bioeconomic enterprises are more likely to be perceived in specific regional units. The Levene’s test indicated unequal variances for this item (p = 0.004), and the Kruskal–Wallis test again supported a significant regional effect (H = 13.0, p = 0.005).

In contrast to economic perceptions, environmental benefits exhibited minimal regional disparities. For the statement “Air quality has improved due to decarbonization,” all regions exhibited relatively high levels of agreement (means ~3.8–4.1). A one-way ANOVA revealed a marginal difference (F = 3.39, p = 0.018), but the effect size was negligible. Of particular note is the observation that Kozani’s mean (M ≈ 3.78) was marginally lower than that of Florina (M ≈ 4.06; p < 0.05 in Tukey post hoc), suggesting that the region most impacted by historical pollution may be more circumspect in its declaration of air quality enhancements. However, no regional unit’s mean fell below “Agree,” and Levene’s test was non-significant (p = 0.50), indicating homogeneous variances. Collectively, all regions of Western Macedonia recognized enhancements in air quality, with only slight variations in the intensity of this perception.

The statement “Biodiversity and land use have improved due to decarbonization” was met with a generally tepid response, as evidenced by the overall mean score of approximately 2.45, which indicates a tendency towards disagreement (i.e., the statement was, on the whole, not considered to be strongly supported). The analysis revealed no statistically significant differences by regional unit (F = 1.39, p = 0.24). This uniformly low score suggests that residents across all sub-regions do not perceive notable biodiversity/land-use benefits from the transition so far.

A statistically significant variation was observed among respondents in their perception of the existence of educational and training programmes in bioeconomy skills within the region (ANOVA F = 8.81, p < 0.001). Grevena and Florina reported moderately higher levels of agreement (means ~3.81 and 3.88, respectively, approaching “Agree”) compared to Kastoria and Kozani (means ~3.37 and 3.31). Post hoc tests revealed that Grevena and Florina significantly exceeded the levels observed in Kozani (p = 0.004 and p < 0.001, respectively) and Kastoria as well (p < 0.05). The variances were found to be equal (Levene’s p = 0.27). This finding suggests the presence of the unequal availability or awareness of bioeconomy training opportunities, with two of the regional units exhibiting (or perceiving) a greater abundance of such programmes, while the remaining units appear to be lagging behind.

Similarly, the perception that “investments in green technologies and infrastructure have been made in the region” varied by area (F = 6.92, p < 0.001). Grevena and Florina again showed higher agreement (means ~4.10 and 3.99) than Kozani (mean 3.53, which is only slightly above neutral). Kozani’s mean was significantly lower than Grevena and Florina (Tukey p = 0.002 and p = 0.005, respectively). Kastoria was in between (M3.79) and not significantly different from the others. This suggests that the implementation of green infrastructure is perceived as least in Kozani compared to the others. It is worth noting that Kozani also had the largest sample and is probably the core coal mining area—residents there may have higher expectations or have not yet seen as much green investment as those in some smaller units with specific projects.

The analysis of the regional units shows a clear pattern: environmental improvements (air quality and emissions) are perceived uniformly across Western Macedonia, while positive economic outcomes of the transition are perceived unevenly. Regions differ significantly in the extent to which they see new bioeconomy investments, enterprises, and capacity building efforts. Grevena stands out as consistently reporting the fewest benefits in terms of new investments or enterprises—essentially a strong skepticism that the bioeconomy is taking root there. Conversely, Florina reports relatively more progress on these fronts. These discrepancies are likely to reflect the actual distribution of projects and support: some places have seen tangible bioeconomy initiatives (and, therefore, residents are more likely to agree that such things exist), while others have not and remain unconvinced. Despite these differences, all regions equally perceive certain negatives of the decarbonization transition (e.g., all moderately agree that unemployment has increased, F = 2.28, p = 0.078, n.s.) and certain positives (all strongly agree that emissions have decreased, with no regional gap). This suggests a shared regional understanding of broad outcomes (such as the environmental benefits and economic drawbacks of coal plant closures) alongside local differences in new opportunities.

3.2. Factors Influencing Bioeconomy Acceptance

A pivotal question for policymakers pertains to the factors that precipitate public acceptance of the bioeconomy in this transitioning region. Utilizing a survey instrument, the statement “The bioeconomy is accepted in the region” was assigned an overall mean of approximately 3.08 (SD = 0.93), denoting an average neutral stance (neither strong acceptance nor rejection). In an effort to identify the factors that might engender heightened acceptance, a multiple linear regression analysis was conducted with “Bioeconomy is accepted” designated as the outcome. Four predictor variables were entered into the model (all measured on the same 5-point agreement scale): (1) the perceived increase in bioeconomy investment, (2) the perceived emergence of new bioeconomy businesses, (3) the perception that the public attitude toward the bioeconomy is positive, and (4) the perception that the region has implemented supportive bioeconomy policies/subsidies. These predictor variables represent tangible economic developments, social receptiveness, and institutional support, respectively—all hypothesized to influence whether people feel the bioeconomy is accepted locally.

The regression model was statistically significant (overall F(4760) = 27.08, p < 0.001) and explained approximately 12.5% of the variance in the acceptance ratings (R² = 0.125, adjusted R² = 0.120). This R², while modest, is not unexpected given that “acceptance” is a broad outcome likely affected by many unmeasured factors (e.g., personal values, communication, etc.). The model’s explanatory power is acceptable for a cross-sectional attitudinal survey, and, importantly, it identifies several significant predictors of acceptance. The appropriateness of the linear model was confirmed by diagnostic checks, which revealed only minor deviations from normality in the residuals and the absence of significant heteroscedasticity. Additionally, the predictor inter-correlations were moderate (all pairwise r < 0.45), thereby ensuring the reliability of the beta estimates.

All four predictors demonstrated positive regression coefficients and attained statistical significance (p < 0.05), indicating that an increased level of agreement with each of these statements is correlated with a higher “bioeconomy acceptance” score. The following

Table 3. Regression results predicting bioeconomy acceptance.

Predictor	B (Unstandardized Coefficient)	Standard Error	t-Statistic	p-Value
The region has implemented policies and subsidies for the bioeconomy	0.209	0.039	5.42	0.001
Investment in bioeconomy has increased	0.119	0.033	3.61	0.001
There are new businesses in the bioeconomy sector	0.089	0.035	2.56	0.011
Public perception of the bioeconomy in the region is positive	0.093	0.038	2.49	0.013

Source: author’s own creation.

presents the unstandardized coefficients (B), which can be interpreted in terms of the 1–5 scale.

The regression coefficient for the statement “The region has implemented policies and subsidies for the bioeconomy” was the most significant (B = 0.209, SE = 0.039, t = 5.42, p < 0.001). When controlling for other variables, respondents who expressed agreement with the implementation of bioeconomy-friendly policies within their region demonstrated a 0.21-point increase in their acceptance rating (on a 5-point scale) for each one-step increase in their agreement. In practical terms, respondents who indicated a strong belief in the existence of such policies exhibited a notably higher level of acceptance. This finding suggests that the existence of discernible institutional support, such as policies and subsidies, is a significant predictor of public acceptance. This is likely due to the fact that concrete government action serves to legitimize the bioeconomy and fosters community support. The predictor “Investment in bioeconomy has increased” was also found to be significant (B = 0.119, SE = 0.033, t = 3.61, p < 0.001). Despite the fact that a considerable proportion of respondents expressed disagreement with this statement (as previously mentioned), those who do perceive an increase in investment tend to exhibit a greater degree of acceptance for the bioeconomy. A one-unit rise in perceived investment is associated with a 0.12 increase in acceptance score, suggesting that tangible economic investments can influence people’s perceptions of the bioeconomy’s acceptance. This phenomenon may be attributed to the fact that investment can serve as a signal that the bioeconomy is gaining traction and viability in the region, potentially leading to the creation of employment opportunities and the development of new projects. The presence of new bioeconomy enterprises was found to have a smaller but significant effect on acceptance (B = 0.089, SE = 0.035, t = 2.56, p = 0.011). This suggests that the existence of new bio-based businesses in the area is associated with higher acceptance, even when general investment is taken into account. It is evident that the personal observation of new bioeconomy enterprises (including small startups or pilot initiatives) contributes to the perception that the bioeconomy is gaining traction and is accepted within the local community. The study found that the perception of the bioeconomy in the region was positively correlated with the perception of public opinion, suggesting that the former may serve as a predictor of the latter. This variable was identified as a significant predictor, with a beta coefficient of 0.093, standard error of 0.038, t-value of 2.49, and a p-value of 0.013. This finding suggests a reinforcing effect: respondents who believe that the public perception is positive are more likely to report higher acceptance of the bioeconomy. In other words, social consensus matters—if people think their neighbors generally view the bioeconomy favorably, they too report higher acceptance (perhaps reflecting a social norm or simply awareness of community attitudes). This finding lends further support to the notion that “bioeconomy acceptance” is, at least in part, a collective sentiment measure rather than merely an individual stance. The perception of others’ optimism has been shown to positively influence an individual’s assessment of overall acceptance.

The regression equation can be written as follows:

Accepted_score = 1.76 + 0.119 (InvestBioeco) + 0.089 (NewBizBioeco) + 0.093 (PerceptBioeco) + 0.209 (PolicyBioeco)

(1)

where the constant 1.76 is the intercept (baseline acceptance level when all predictor ratings are at the scale minimum). To illustrate this, if a respondent strongly disagrees (1) that there are investments or new businesses or policies, their predicted acceptance score would be around 1.76 (between “Strongly Disagree” and “Disagree” that the bioeconomy is accepted). Conversely, a respondent who moderately agrees (4 on the scale) on all these factors would have a predicted acceptance of ≈1.76 + 40.119 + 40.089 + 40.093 + 40.2 09 = 1.76 + 0.476 + 0.356 + 0.372 + 0.836 = 3.80 (closer to “Agree” that the bioeconomy is accepted). This illustrates how increases in each factor cumulatively raise the perceived acceptance, with the policies factor contributing the most steeply to this increase, underscoring its importance.

The investigation of residuals confirmed the adequacy of the linear model, with a mean of approximately 0 and constant variance across fitted values. The examination of residual plots revealed no indication of non-linearity or omitted variables. A slight negative skew was observed in the residuals (skew ≈ −0.31), which is anticipated given the ordinal nature of the data (a limited number of respondents assigned the extreme lowest acceptance rating of 1, resulting in a mild left tail in the residuals). However, this deviation is minor, and, given the large N = 765, the t-tests for coefficients are robust (the Central Limit Theorem ensures the sampling distribution of coefficients is approximately normal even if residuals are slightly non-normal). Multicollinearity was low (e.g., r = 0.33 between “investment increased” and “policies implemented”; VIFs < 1.5), so each predictor’s effect is distinguishable. The addition of the variable “Sufficient support from local government” (another survey item) as a predictor was considered, but it was found to be highly correlated with the “policies” item and had very low variance (as most people rated local support as poor); thus, it was not deemed to improve the model. The more general “policies and subsidies” variable was, therefore, selected to represent institutional support.

The regression findings suggest that pragmatic factors are driving the sense of acceptance of the bioeconomy. In particular, where people see government action (policies/subsidies) and notice concrete economic changes (investments and new firms), they are more likely to feel that the bioeconomy is being accepted in their region. These factors likely enhance acceptance by signaling that the bioeconomy is real, beneficial, and endorsed by both authorities and the market. Additionally, the influence of perceived public sentiment (the “Public perception is positive” predictor) indicates a social feedback loop: people’s belief about the overall community attitude influences their own acceptance stance, perhaps through peer influence or collective optimism. It is important to note that the model’s R² of 0.125 means a majority (~87%) of the variation in acceptance remains unexplained by these four factors—other elements such as individual economic interests, trust in institutions, awareness of bioeconomy initiatives, or demographic factors might also play significant roles. We tested demographics (age, gender, and education) separately and found no substantial direct effect on the acceptance item (e.g., no significant gender difference in acceptance score, t(763) = 0.08, p = 0.94). This implies acceptance is more shaped by situational perceptions than by personal attributes.

4. Discussion

The analyses conducted yielded two primary insights. Firstly, there is a discrepancy in the perceptions of the decarbonization transition’s outcomes across different regional units, with some areas, potentially those less directly involved or benefiting, experiencing a paucity of positive developments in the bioeconomy. Secondly, the acceptance of the bioeconomy by the public is found to be substantially influenced by concrete actions and outcomes, particularly those pertaining to government policies and visible investments. Across all regional units, there is a widespread recognition of the environmental benefits of decarbonization, as evidenced by a reduction in CO₂ emissions and enhancement of air quality. This suggests a shared awareness of its ecological success. However, the economic and social co-benefits remain limited in their perception and, where they are reported (e.g., training programmes and green infrastructure), they appear to strengthen acceptance of the new bioeconomy paradigm.

The comparative analysis between the four regional units of Western Macedonia was based on non-parametric methods (Kruskal–Wallis tests), which are robust to unequal group sizes and do not require distributional assumptions. The use of these methods supports the validity of the observed regional differences in public perceptions. Despite the sample size variation, all four regional units contributed sufficient responses to permit a meaningful comparative interpretation.

The results of this study have practical implications for the management of the transition in Western Macedonia, where there are stark regional differences in the perceptions of investments [70] and opportunities [59]. These findings suggest that policymakers should address regional equity, as some localities may require more attention and targeted bioeconomy projects to avoid being “left behind” [71,72]. The data show that the regional units with minimal perceived bioeconomy activity also had similar or even stronger perceptions of the negative effects [72,73,74] (e.g., high unemployment due to decarbonization), which can breed frustration. Consequently, the implementation of a balanced regional development strategy is imperative in order to ensure that all regional units of Western Macedonia experience tangible benefits from the post-lignite transition [75]. Furthermore, enhancing public acceptance of the bioeconomy appears to be contingent on demonstrating tangible progress [76,77]. The regression analysis suggests that, if residents observe the enactment of supportive policies and the emergence of new investments and businesses, they are more likely to accept and endorse the bioeconomy shift. This virtuous cycle is further supported by the finding that the implementation of robust policies (e.g., subsidies for bio-based projects and training initiatives) can stimulate business activity and investment, which, in turn, increases public acceptance [59,78]. Consequently, a receptive public can provide further support and participation in bioeconomy initiatives [77,79]. Conversely, a paucity of visible action may engender skepticism or apathy regarding the bioeconomy’s prospects [80]. It is also worthy of note that the perception that others are positive had an effect on acceptance. This suggests that outreach and communication efforts could indirectly raise acceptance by improving the general perception of public support [77,81]. If people hear success stories and believe their community is embracing the bioeconomy, it can become a self-reinforcing belief [82]. Engagement with the community and highlighting local champions of the bioeconomy might, thus, be valuable [83,84].

The findings of the study on Western Macedonia’s bioeconomy transition can be better understood by comparing them with similar sustainability transitions in other regions. Western Macedonia, a coal-dependent area now undergoing decarbonization, reflects many patterns observed elsewhere—from deforestation-hit communities to post-mining economies—but also shows unique regional nuances. Public perception, institutional trust, and socio-economic outcomes have emerged as critical dimensions in sustainability transitions across diverse regions, including post-mining areas, deforestation-affected territories, and agricultural zones undergoing bioeconomy-oriented reforms [72,84,85,86,87,88]. In multiple European contexts, particularly in regions phasing out coal or heavy industry, public attitudes toward transition efforts are often mixed, segmented into supporters, skeptics, and indifferent groups. Studies from Central and Eastern Europe illustrate how attitudes fluctuate based on the perceived risks and benefits: while environmental concerns foster support for change, economic dependency on legacy industries fuels resistance [89,90]. For example, surveys in coal regions of the Czech Republic, Germany, and Poland show that, although many citizens acknowledge the environmental damage from coal, a significant portion remain attached to coal-related employment and community identity, thus maintaining ambivalent or oppositional stances toward decarbonization [89,91,92]. In forestry-dependent regions such as Finland and Austria, acceptance of bioeconomy transitions is generally higher when the shift is perceived as an evolution of existing livelihoods rather than a rupture [93,94]. Positive public buy-in in these areas is often attributed to strong institutional communication, economic continuity, and public involvement in shaping transition paths.

Institutional trust has been identified as a key factor in the acceptance of transition. Research has shown that trust in governance structures significantly correlates with the willingness to engage in and support sustainable policy reforms, both in developed and developing countries [95,96,97]. Successful examples, such as the Ruhr region in Germany, demonstrate how trust can be cultivated through multi-stakeholder collaboration, long-term planning, and transparent decision-making [98]. Conversely, regions where transitions were imposed from the top or where information was not effectively disseminated, such as in the case of former coal communities in the United Kingdom, have witnessed protracted disillusionment and a decline in political engagement. In Eastern European countries, skepticism towards government-led environmental policies has been associated with reduced engagement and the diminished efficacy of just transition programmes [99,100]. Scandinavian case studies further underscore that a high level of institutional trust, when coupled with participatory policy design, not only fosters public confidence but also facilitates a more seamless policy implementation [101,102]. This suggests that trust is not merely a by-product of effective governance, but an essential condition for the social acceptance of transformative agendas.

The socio-economic outcomes of sustainability transitions also vary considerably, with clear lessons emerging on how to mitigate regional inequalities [7,103]. Abrupt closures of extractive industries, especially in mono-industrial towns, have often led to spikes in unemployment, outmigration, and a decline in social cohesion. Evidence from the UK, the United States, and Eastern Europe indicates that, without a proactive social policy, affected populations—particularly older workers, women, and youth—face long-term marginalization [24,104]. Conversely, regions that have integrated skill retraining, local entrepreneurship incentives, and inclusive public services into their transition strategies have witnessed more equitable outcomes [105]. Germany’s Ruhr region is an exemplary case where former industrial sites have been successfully converted into cultural, educational, and innovation hubs, fostering job creation and regional renewal [106,107]. In deforestation-prone areas of Latin America and Southeast Asia, success has been observed where local communities have been engaged in forest stewardship and have shared in the economic benefits of conservation or restoration activities [108]. The cases under consideration demonstrate that equitable transitions require deliberate policy design to ensure the equitable distribution of benefits across different geographical areas and demographic groups, thereby preventing the emergence of “winner” and “loser” localities [109]. Ultimately, comparative international experiences underscore that public engagement, trust-building, and socially inclusive investment are not merely ancillary elements but rather foundational pillars of effective and accepted sustainability transitions.

In addition to spatial variation, demographic characteristics such as age may also shape perceptions of decarbonization and the bioeconomy. While this study primarily focused on regional differences, preliminary observations from the survey data suggest that younger respondents tended to express slightly higher optimism toward environmental outcomes, whereas older groups were more cautious or uncertain. These findings indicate that age-related factors could play a role in shaping transition narratives, and future research should more systematically explore the interaction between demographic and spatial variables.

The present study has several limitations that should be considered when interpreting the results. Firstly, the data are cross-sectional, which means that it is not possible to ascertain whether policies cause acceptance or whether people in areas where acceptance is higher simply notice policies more. Secondly, the Likert measures are subjective perceptions, so there may be differences between perception and reality (for instance, investments might exist but, if people are unaware, their perception remains low). The internal consistency among the survey’s Likert items was relatively low (Cronbach’s α ≈ 0.42 for all items), indicating that the questions tapped into multiple distinct dimensions (economic, environmental, and social) rather than one general attitude. This decision was made to analyze specific items/factors separately rather than computing a single summary score. In the future, factor analysis could be employed to formally identify latent dimensions, once more data or refined survey items are available. However, our exploratory inspection suggested no very strong clustering (people’s responses were not highly correlated across all items).

5. Conclusions

The survey results reveal marked spatial disparities in perceptions of the decarbonization benefits of Western Macedonia. Communities in sub-regions that have already witnessed proactive policy measures or the launch of new bioeconomy ventures report significantly more positive outlooks. In these areas, tangible examples of job creation or environmental improvement from bio-based projects appear to have bolstered public optimism. Conversely, respondents in locales awaiting substantial investment or visible projects maintain a degree of skepticism concerning the bioeconomy’s promised benefits. This geographically uneven perception underscores the risk of a two-speed transition, where some communities progress with confidence while others lag behind, uncertain and unconvinced. It emphasizes the necessity for deliberate attention to be given to those sub-regions that feel left behind, ensuring they, too, witness concrete evidence of post-lignite opportunities.

In order to facilitate a transition that is both cohesive and equitable, policymakers must give priority to the promotion of regional equity in the distribution of bioeconomic investments and support. This will require the scaling up of financial incentives, infrastructure projects, and business development programmes in the lagging parts of Western Macedonia, as well as in the already-advancing hubs. It is vital to ensure that the benefits (and even any short-term costs) of the transition are fairly distributed across all communities. Various EU bodies have noted that perceived fairness in who gains and who pays is a key determinant of local acceptance. In practice, an equitable approach could involve earmarking funds specifically for under-served areas, encouraging decentralized bio-based initiatives (such as community bioenergy projects or cooperatives), and strengthening local capacities to participate in the new economy. Effective communication strategies are also paramount to ensuring that these efforts are both publicized and understood. Authorities should, therefore, ensure that transition plans, progress updates, and success stories are openly disseminated in clear, accessible language through multiple channels. The European Economic and Social Committee emphasizes that transparent decision-making and open communication can make the low-carbon transition more acceptable to society. A coordinated communication campaign would facilitate the management of expectations, the celebration of early successes on a regional scale, and the communication of the integral role of every community in the bioeconomy’s future. By integrating equitable policy action with visible, transparent communication, officials can address both the objective and perceptual gaps between sub-regions. Western Macedonia’s strategic blueprint for the bioeconomy is noteworthy in this regard; it calls for measures to ensure social acceptance of the transition and support local bio-based enterprises as part of the decarbonization plan. Such alignment between on-the-ground policy and strategic planning will be critical for levelling the playing field across the region.

Future research could build on the present findings by integrating perception-based analyses with more comprehensive investigations into participatory governance frameworks and co-design processes. While this study highlights the spatial variations in public acceptance and perceived impacts of decarbonization and the bioeconomy, a deeper understanding of how citizens engage with transition processes—through mechanisms such as stakeholder participation, institutional responsiveness, and feedback structures—remains essential. Exploring the intersection of public perception, institutional trust, and participatory design can offer valuable insights into how inclusive and democratically legitimate bioeconomy transitions may be realized at the regional level.