Ecological Modernization, Perceived Policy Effectiveness, and Environmental Behavior: Evidence from Turkey’s Plastic Bag Charge

Abstract

This study examines the associations among perceived policy effectiveness, emotional environmental engagement, and environmental behavior in the context of the plastic bag charge policy in Turkey. While market-based environmental policies are typically explained in terms of economic incentives, the ways in which policy perceptions and emotional processes are associated with individual behavior remain underexplored in the literature. The data were collected through a nationwide survey in Turkey (n = 515), and the proposed model was tested using Structural Equation Modeling (SEM). The measurement model shows good fit (CFI = 0.94; TLI = 0.92; RMSEA = 0.05; SRMR = 0.04). The findings indicate that perceived policy effectiveness is positively and significantly associated with emotional environmental engagement (β = 0.56, p < 0.001). Emotional engagement is also strongly associated with environmental behavior (β = 0.62, p < 0.001). The direct association between perceived policy effectiveness and environmental behavior is weaker but remains significant (β = 0.21, p < 0.01). Bootstrap analysis (5000 resamples) indicates a significant indirect association (β = 0.35; 95% CI [0.21, 0.49]), suggesting that emotional environmental engagement represents an important explanatory dimension linking perceived policy effectiveness and environmental behavior. Given the cross-sectional and self-reported nature of the data, these findings should be interpreted as associative rather than strictly causal. Nevertheless, the results suggest that the relationship between policy perceptions and environmental behavior is more consistent with a framework in which emotional processes are jointly involved, rather than a purely economic explanation. By examining perceived policy effectiveness, emotional environmental engagement, and environmental behavior within a single analytical framework, this study provides an integrated empirical account of how market-based environmental policies are associated with individual-level environmental behavior.

1. Introduction

In an era of intensifying environmental challenges, the persistent impacts of plastic waste on ecosystems have prompted policymakers to develop more effective intervention instruments. The widespread use of single-use plastics, limited recycling rates, and their long degradation periods have made plastic waste one of the most visible environmental problems worldwide. In this context, market-based environmental policies—such as taxes, charges, and pricing mechanisms—have become widely used tools for influencing individual behavior. The plastic bag charge introduced in Turkey in 2019 represents a prominent example of such policy instruments.

The literature on market-based environmental policies has largely explained their effects through economic incentives. From this perspective, individuals adjust their behavior by re-evaluating cost–benefit calculations, and pricing mechanisms are assumed to encourage environmentally friendly actions. Indeed, even relatively low-cost interventions such as plastic bag charges have been shown to generate measurable changes in consumption behavior. However, this explanatory framework tends to reduce policy effects to economic rationality and pays limited attention to how individuals evaluate policy outcomes and how these evaluations are associated with environmental behavior.

A growing body of research suggests that individuals’ assessments of whether a policy successfully addresses environmental problems are closely associated with their willingness to engage in policy-consistent behaviors [1,2]. Public opinion research also shows that support for environmental policies is shaped not only by policy outcomes but also by broader perceptions of social trust, fairness, and political context, all of which influence how citizens evaluate policy legitimacy and effectiveness [3]. In this regard, perceived policy effectiveness emerges as an important cognitive mechanism reflecting how individuals evaluate policy outcomes. Individuals who perceive a policy as environmentally meaningful and practically effective tend to report stronger alignment between their everyday behaviors and the policy’s broader environmental goals. While this literature establishes an important link between policy evaluations and behavior, it provides only limited insight into the psychosocial processes through which this relationship is formed.

At the same time, the environmental behavior literature emphasizes that individual actions are shaped not only by cognitive evaluations but also by emotional processes. Affective responses such as environmental concern, empathy, moral responsibility, and emotional attachment to nature are among the major determinants of pro-environmental behavior. Emotional engagement is frequently associated with stronger environmental concern and greater behavioral involvement. However, studies focusing on policy evaluations and those emphasizing emotional processes have largely developed in parallel, with limited integration between these two perspectives.

This separation creates an important analytical gap. Existing studies tend to explain policy effects either through economic incentives, cognitive evaluations, or emotional engagement, without systematically examining how these dimensions interact. In particular, empirical research examining whether perceived policy effectiveness is associated with environmental behavior alongside emotional environmental engagement remains limited. As a result, the mechanisms linking policy evaluation to actual behavioral outcomes remain insufficiently specified.

At this point, a conceptual clarification is necessary. This study focuses exclusively on perceived policy effectiveness, defined as individuals’ evaluations of a policy’s capacity to address environmental problems and contribute to environmental improvement. The analysis does not address broader normative dimensions such as procedural fairness, institutional trust, or general perceptions of institutional legitimacy. Instead, it concentrates on outcome-oriented evaluations of policy performance in order to ensure consistency between theory, measurement, and interpretation.

This distinction is particularly important in the case of environmental policies such as plastic bag charges. Individuals may respond to a policy not only because of economic incentives, but also because they perceive that the policy produces meaningful environmental outcomes. Understanding this evaluative dimension is essential for explaining how environmental policies are interpreted and how they are associated with behavioral patterns at the individual level.

Against this background, this study examines how perceived policy effectiveness is associated with environmental behavior and whether this relationship is linked to emotional environmental engagement in the case of Turkey’s plastic bag charge. Using data from a nationwide survey conducted in Turkey (n = 515), the proposed theoretical model was tested through Structural Equation Modeling (SEM). The findings indicate that perceived policy effectiveness is positively associated with emotional environmental engagement (β = 0.56, p < 0.001), while emotional engagement is strongly associated with environmental behavior (β = 0.62, p < 0.001). The direct association between perceived policy effectiveness and environmental behavior remains significant but comparatively weaker (β = 0.21, p < 0.01). Bootstrap analysis further indicates a significant indirect association through emotional environmental engagement (β = 0.35; 95% CI [0.21, 0.49]), consistent with a significant indirect association pattern.

Given the cross-sectional and self-reported nature of the data, these findings should be interpreted as associative rather than strictly causal. The study does not directly examine economic deterrence mechanisms such as price sensitivity, cost perception, or observed purchasing behavior. Rather, it focuses on how individuals’ evaluations of policy effectiveness and their emotional environmental engagement are associated with behavioral outcomes within the broader policy context.

This study contributes to the literature in three ways. First, it develops an integrated analytical framework linking perceived policy effectiveness, emotional environmental engagement, and environmental behavior within a single model. Second, it extends explanations of market-based environmental policies beyond purely economic incentives by incorporating cognitive and affective processes into the analysis. Third, by examining these relationships in the context of Turkey’s nationwide plastic bag charge, it provides empirical evidence from a middle-income country context that remains underrepresented in the literature on environmental policy and behavior.

The remainder of the article is structured as follows. Section 2 presents the literature review and theoretical framework and develops the research hypotheses. Section 3 describes the materials and methods, including the research design, measurement model, and analytical strategy. Section 4 reports the empirical findings. Section 5 discusses the results in relation to the broader literature, and Section 6 concludes with the main theoretical, empirical, and policy implications.

2. Literature Review and Theoretical Background

2.1. Policy Evaluation, Emotions, and Environmental Behavior

2.1.1. Policy Evaluation and Compliance

One of the central strands in the public policy literature focuses on the relationship between policy evaluation and compliance. Research has long shown that compliance is not shaped solely by the existence of regulation or its enforcement capacity; rather, individuals’ evaluations of how policies function in practice also play an important role. In addition to instrumental considerations, perceptions of policy outcomes, fairness, and effectiveness influence the extent to which individuals align their behavior with policy objectives [1,4].

Applied to environmental policy, this literature suggests that public support for and compliance with environmental regulations depend not only on economic costs but also on how individuals evaluate policy outcomes [4,5]. In particular, perceived policy effectiveness has emerged as an important explanatory factor. Individuals who believe that a policy meaningfully contributes to solving environmental problems are more likely to support policy-consistent behaviors and to view the policy as socially relevant [1,2,6].

This perspective is particularly important for market-based environmental policies such as plastic bag charges. While such policies are often interpreted primarily through economic deterrence mechanisms, individuals’ evaluations of whether the policy actually reduces environmental harm may also shape behavioral responses. In this sense, policy effectiveness reflects an outcome-oriented assessment of policy performance rather than a broader institutional or normative judgment.

Accordingly, the present study focuses on perceived policy effectiveness, defined as individuals’ evaluations of the environmental effectiveness of the plastic bag charge. This approach provides a more conceptually consistent and empirically measurable framework for examining how policy perceptions are associated with emotional engagement and environmental behavior.

Based on this theoretical background, individuals who perceive the plastic bag charge as more environmentally effective are expected to report stronger emotional environmental engagement.

H1. 

Perceived policy effectiveness is positively associated with emotional environmental engagement.

2.1.2. Emotions and Environmental Behavior

The environmental behavior literature has long been dominated by cognitive and rational-choice models, which explain behavior primarily in terms of knowledge, attitudes, and cost–benefit calculations [7,8]. While these approaches have provided important insights, their explanatory power remains limited, particularly in explaining the persistent gap between environmental awareness and actual behavior.

In response to these limitations, an expanding body of research emphasizes the role of affective processes in shaping pro-environmental behavior. Emotions are not merely secondary reactions; they influence attention, evaluation, motivation, and behavioral involvement [9,10,11]. Affective responses such as environmental concern, empathy, guilt, and moral responsibility have been shown to be closely associated with behavioral intentions and environmentally responsible actions.

A comprehensive review by Heidbreder et al. [12] further shows that emotional involvement and public perceptions are central determinants of plastic-related environmental behavior and policy responsiveness. Similarly, Steg and Vlek [13] argue that pro-environmental behavior is shaped by a combination of motivational, contextual, and affective factors rather than by knowledge alone. Personal values, emotional attachment, and social context also play important roles in shaping environmental concern and behavioral consistency [8].

From a broader theoretical perspective, integrative frameworks such as Value–Belief–Norm (VBN) theory [14,15] and broader value-based approaches to environmental behavior [8] emphasize the role of emotional and normative dimensions in explaining environmental behavior. These approaches suggest that behavior is shaped not only by instrumental reasoning but also by moral considerations and affective engagement. Recent empirical studies similarly show that emotional engagement is associated with both individual and collective environmental action [16,17]. Individuals with stronger emotional involvement in environmental issues tend to report higher levels of behavioral participation and stronger support for environmental initiatives. However, the role of emotions has largely been examined at the individual level, with more limited attention to how policy contexts may shape or reinforce these affective responses.

H2. 

Emotional environmental engagement is positively associated with environmental behavior.

2.1.3. Market-Based Instruments Beyond Economic Explanations

Market-based environmental instruments are typically designed to influence behavior by altering cost–benefit structures. Within this framework, policies such as taxes, fees, and charges seek to internalize environmental externalities and encourage behavioral change through pricing mechanisms [18,19].

Empirical evidence suggests that even relatively low-cost interventions, such as plastic bag charges, can produce measurable behavioral shifts. However, explaining policy effects solely through economic deterrence offers only a partial explanation, as policy framing, perceived effectiveness, and broader social and symbolic meanings also shape public responses [6,20,21,22].

Similar findings have been reported in the case of the plastic bag charge policy in England, where policy implementation significantly reduced plastic bag consumption while also increasing public support for broader measures aimed at reducing plastic waste [20,21]. Research from Wales similarly shows that single-use carrier bag charges generate not only immediate reductions in plastic bag consumption but also broader attitudinal spillover effects that encourage other forms of pro-environmental behavior [23]. Additional evidence shows that plastic bag restrictions can alter both consumption habits and attitudes toward reducing dependence on disposable products [21].

In this respect, perceived policy effectiveness emerges as an important link between policy design and behavioral outcomes. Individuals who perceive a policy as environmentally meaningful and practically effective tend to report stronger alignment with policy-consistent behaviors. However, this relationship should not be understood as purely direct or automatic.

Recent research suggests that behavioral responses to environmental policies are shaped by broader psychosocial processes, including values, beliefs, and emotions [14,15,16]. Emotional engagement, in particular, provides an important explanatory dimension for understanding how policy evaluations are associated with behavioral responses. Rather than functioning as a deterministic mechanism, emotional involvement appears to strengthen the relationship between policy perceptions and environmental action.

Beyond purely economic deterrence, individuals who perceive environmental policies as meaningful and effective are expected to show stronger behavioral alignment with policy goals.

H3. 

Perceived policy effectiveness is positively associated with environmental behavior.

2.1.4. Policy Acceptance and Perceived Effectiveness

A growing body of research examines policy acceptance and perceived policy effectiveness in the context of environmental governance. These studies show that public support for environmental policies depends not only on economic interests but also on whether policies are perceived as effective, fair, socially meaningful, and institutionally appropriate [1,4,6]. Beyond outcome-oriented evaluations, broader research also suggests that compliance is influenced by whether policies are perceived as socially acceptable and normatively appropriate [24,25]. In environmental governance, these broader legitimacy dimensions often interact with perceived effectiveness, fairness, and public trust.

In particular, Ejelöv and Nilsson [1] identify perceived effectiveness as one of the strongest predictors of policy acceptance. Policy acceptability is also strongly shaped by perceived fairness, revenue use, and the extent to which citizens believe that policy outcomes are socially beneficial [4,5,6]. Harring et al. [26] further demonstrate that perceived fairness and policy effectiveness jointly shape public support for environmental policies, particularly in the case of climate-related interventions where distributive concerns are highly salient. This reinforces the importance of perceived policy effectiveness as a more direct explanatory dimension linking policy evaluation and behavioral alignment. Dechezleprêtre et al. [27] similarly show that environmental taxation becomes more acceptable when citizens perceive broader economic and technological co-benefits rather than only immediate financial costs. Likewise, recent research shows that policy acceptance increases when individuals believe that policy interventions produce visible collective benefits and socially meaningful outcomes [1,2]. These findings support the argument that perceived policy effectiveness functions as an important bridge between policy evaluation and behavioral alignment.

In addition, value orientations and everyday consumption patterns shape how individuals translate policy evaluations into behavioral responses.

Previous research also shows that pro-environmental consumption is often embedded in broader lifestyle values, moral preferences, and social norms rather than purely rational cost calculations [13,14,28]. Similarly, van Valkengoed and Steg [11] show that behavioral adaptation is strongly associated with risk perception, emotional concern, and value-based motivations, highlighting that environmental behavior is rarely explained by economic incentives alone.

However, an important limitation of this literature is that the relationship between policy support and actual behavior is often addressed only indirectly. Supporting a policy does not necessarily imply engaging in the behaviors that the policy seeks to encourage. As a result, the mechanisms linking policy perceptions to everyday environmental behavior remain insufficiently specified.

In this respect, perceived policy effectiveness provides a more direct analytical bridge between policy evaluation and behavior. Individuals who believe that a policy meaningfully contributes to solving environmental problems tend to report stronger behavioral alignment with policy goals than those who merely express general policy support [1,2]. Nevertheless, the psychosocial processes through which this relationship develops—particularly the role of emotional engagement—remain underexamined.

Because policy evaluations and emotional processes jointly shape environmental action, emotional environmental engagement is expected to represent an important explanatory dimension linking perceived policy effectiveness and environmental behavior.

H4. 

Emotional environmental engagement is expected to represent an important explanatory dimension linking perceived policy effectiveness and environmental behavior.

2.1.5. Research Gap and Contribution

Taken together, the literature shows that environmental policies have been examined through multiple perspectives, including economic incentives, policy evaluation, policy support, and emotional processes. From a broader environmental sociology perspective, Dunlap and Catton [29] argue that environmental behavior cannot be fully understood within purely human-centered or economically reductionist frameworks, emphasizing the need to consider ecological limits and broader social value systems in the analysis of environmental action. More recent systematic reviews also show that the public acceptability of environmental policies depends on how policies are framed in relation to fairness, effectiveness, and everyday social consequences, rather than economic incentives alone [30]. However, these strands have often developed separately, with limited integration between them, despite recent systematic reviews emphasizing the need for more comprehensive models linking policy evaluations, emotional engagement, and behavioral outcomes [6,28,30].

In particular, empirical research examining how perceived policy effectiveness is associated with emotional environmental engagement and how these relationships relate to environmental behavior within a single analytical framework remains limited. Most studies focus either on policy acceptance or on individual emotional responses, without systematically connecting these dimensions.

This study addresses this gap by integrating perceived policy effectiveness, emotional environmental engagement, and environmental behavior within one model. Rather than assuming a direct causal mechanism, it focuses on the observed direct and indirect associations among these variables. In doing so, it moves beyond explanations based solely on economic incentives or general policy support by incorporating cognitive evaluations and affective processes into the same analytical framework.

By examining these relationships in the context of Turkey’s nationwide plastic bag charge, the study also provides empirical evidence from a middle-income country context that remains relatively underrepresented in the literature on environmental policy and behavior. Given the cross-sectional and self-reported nature of the data, the findings should be interpreted as indicative of associative patterns rather than definitive causal relationships.

3. Materials and Methods

3.1. Research Design and Data Collection

This study employs a quantitative research design to examine the relationship between the plastic bag charge policy implemented in Turkey and individual environmental behavior. The research is structured as a cross-sectional survey designed to examine theoretically grounded associations among perceived policy effectiveness, emotional environmental engagement, and environmental behavior.

This design enables the analysis of relationships among latent constructs using Structural Equation Modeling (SEM). SEM was employed because of its capacity to estimate multiple direct and indirect associations among latent variables simultaneously while maintaining theoretical coherence. Given the cross-sectional nature of the data, the analysis focuses on associative patterns rather than definitive causal mechanisms.

Data were collected from April to June 2025 using an online survey distributed through Google Forms. Participants were informed about the purpose of the study, participation was entirely voluntary, and no financial incentive was provided. An informed consent statement was included at the beginning of the questionnaire.

The ethics approval was obtained following the introduction of the mandatory plastic bag charge policy in Turkey on 1 January 2019. Since the policy had only recently been implemented at that time, data collection was intentionally postponed in order to allow sufficient time for the policy’s effects on environmental awareness and behavior to become more observable. Because the research instrument, study scope, and ethical conditions remained unchanged, the original ethics approval remained valid and applicable for the 2025 data collection process.

Anonymity and confidentiality were assured to reduce response bias and encourage more accurate self-reporting.

3.2. Sample and Measures

The population of the study consists of individuals aged 18 and above residing in Turkey. A convenience sampling strategy was employed, resulting in a final sample of 515 valid responses.

The sample is predominantly female (61.9%), with the majority of participants between the ages of 18 and 35. In terms of education, most respondents hold at least a bachelor’s degree. While this profile may indicate relatively high awareness of environmental issues and policy evaluation capacity, it also limits the generalizability of the findings. Accordingly, the results should be interpreted with caution and understood as reflecting patterns within this sample rather than the entire population.

This study includes three main latent constructs: perceived policy effectiveness, emotional environmental engagement, and environmental behavior.

Perceived policy effectiveness refers to individuals’ evaluations of the extent to which the plastic bag charge policy contributes to reducing environmental problems and increasing environmental awareness. The construct captures outcome-oriented perceptions of policy performance rather than broader institutional or normative judgments.

Emotional environmental engagement reflects individuals’ affective responses to environmental issues, including concern, empathy, sadness, and a sense of environmental responsibility.

Environmental behavior refers to environmentally responsible actions performed in daily life. This includes both routine individual behaviors (e.g., recycling and resource conservation) and behaviors involving collective participation (e.g., supporting environmental initiatives or campaigns).

All measures were assessed using a five-point Likert scale (1 = strongly disagree, 5 = strongly agree).

3.3. Analytical Strategy

Data analysis was conducted in two stages. In the first stage, SPSS (Version 25) and AMOS (Version 24) was used to examine missing data, outliers, and normality assumptions. Skewness and kurtosis values within the range of ±1.5 indicated that the data met the assumption of approximate normality.

In the second stage, SEM analyses were conducted using AMOS. The analysis proceeded in two steps. First, the measurement model was evaluated using Confirmatory Factor Analysis (CFA). Second, the structural model was examined to assess the proposed theoretical relationships among the constructs.

Model fit was evaluated using commonly reported indices, including the Comparative Fit Index (CFI), Tucker–Lewis Index (TLI), Root Mean Square Error of Approximation (RMSEA), and Standardized Root Mean Square Residual (SRMR).

Given the cross-sectional design, the analysis focuses on observed associations rather than definitive causal relationships.

3.4. Measurement Model Evaluation

The validity and reliability of the measurement model were assessed using CFA. The results indicate a good fit between the model and the data (CFI = 0.94; TLI = 0.92; RMSEA = 0.05; SRMR = 0.04).

Reliability was evaluated using both Cronbach’s alpha and Composite Reliability (CR). All CR values exceeded the recommended threshold of 0.70, indicating satisfactory internal consistency.

Convergent validity was assessed using Average Variance Extracted (AVE). All constructs exhibited AVE values above the recommended threshold of 0.50, indicating that the indicators adequately represent their respective latent constructs.

Discriminant validity was tested using two complementary approaches. First, the Fornell–Larcker criterion showed that the square root of AVE for each construct exceeded its correlations with other constructs. Second, the Heterotrait–Monotrait ratio (HTMT) values were below the recommended threshold of 0.85.

These findings indicate that the constructs are both conceptually and empirically distinct and that the measurement model demonstrates satisfactory convergent and discriminant validity.

3.5. Structural Model and Indirect Effect Analysis

The structural model was analyzed to examine the associations among perceived policy effectiveness, emotional environmental engagement, and environmental behavior.

Perceived policy effectiveness was specified as the independent variable, emotional environmental engagement as the explanatory dimension, and environmental behavior as the dependent variable. Hypotheses were evaluated based on standardized path coefficients (β) and statistical significance levels (p-values).

The indirect relationship between perceived policy effectiveness and environmental behavior through emotional environmental engagement was examined using a bootstrap procedure with 5000 resamples.

The significance of the indirect effect was assessed using 95% confidence intervals. Confidence intervals excluding zero were interpreted as evidence of a statistically significant indirect association. Given the cross-sectional design, these findings are interpreted as indicative of associative patterns rather than definitive mediation.

3.6. Common Method Bias and Study Limitations

Since all variables were measured using a single survey instrument and self-reported data, the potential for common method bias was considered.

Harman’s single-factor test indicated that a single factor did not account for the majority of the variance, with the first factor explaining less than 50% of the total variance. This suggests that common method bias is unlikely to pose a serious threat to validity.

In addition, several procedural remedies were implemented, including anonymity assurance, separation of scale sections, and careful item structuring to reduce social desirability bias and common method bias. These procedural precautions complement the statistical assessment and strengthen confidence in the findings.

This study is based on cross-sectional data, which limits the ability to draw causal inferences. The findings should therefore be interpreted as indicative of associations rather than definitive causal effects.

In addition, the use of self-reported data may introduce biases such as social desirability and common method bias. Although statistical tests and procedural remedies suggest that these risks are limited, future studies should employ multiple data sources, temporal separation, or longitudinal designs.

Finally, economic deterrence mechanisms—such as price sensitivity, cost perception, and observed purchasing behavior—were not directly measured. Accordingly, the findings should be interpreted primarily in terms of policy evaluations and emotional engagement rather than the economic dimension of policy effects.

4. Results

4.1. Preliminary Analysis and Data Screening

As presented in Table 1, the skewness (−0.59) and kurtosis (−0.27) values for the PPEEEB total scale fall within the recommended range of −1.5 to +1.5, indicating no substantial deviation from normality. According to Tabachnick and Fidell [31], skewness and kurtosis values within this range indicate approximate normality and support the use of parametric analyses and Structural Equation Modeling (SEM).

Table 1. Descriptive Statistics and Normality Test Results.

Variable	Mean (M)	SE	Skewness	SE	Kurtosis	SE
PPEEEB Scale (Total)	3.41	0.04	−0.59	0.11	−0.27	0.22

Note. M = Mean; SE = Standard Error. According to Tabachnick and Fidell [31], skewness and kurtosis values within the range of ±1.5 indicate approximate normality.

Because the distribution remains within acceptable thresholds, the normality assumption required for SEM estimation is considered to be satisfied. Given the relatively large sample size (n = 515), minor deviations from perfect normality are not expected to substantially affect parameter estimation. Therefore, the data were regarded as appropriate for confirmatory factor analysis and structural model testing.

As shown in Table 2, all skewness and kurtosis values for the three environmental awareness sub-dimensions remain within the recommended range of ±1.5, indicating that none of the dimensions shows substantial deviation from normality.

Table 2. Normality Test Results for Environmental Awareness Sub-Dimensions.

Variable	Mean (M)	SE	Skewness	SE	Kurtosis	SE
Individual Action	3.50	0.03	−0.16	0.11	−0.49	0.22
Emotion	4.71	0.02	−0.37	0.11	0.37	0.22
Collective Action	3.16	0.04	−0.13	0.11	−0.42	0.22

Note. SE = Standard Error. According to Tabachnick and Fidell [31], skewness and kurtosis values within ±1.5 indicate approximate normality.

The Individual Action dimension demonstrates a near-symmetrical distribution (skewness = −0.16; kurtosis = −0.49), while the Emotion dimension shows a stronger concentration at the higher end of the scale (M = 4.71), reflecting relatively high emotional environmental engagement among participants. The Collective Action dimension also remains within acceptable normality limits.

Overall, these findings support the suitability of the sub-dimensions for subsequent parametric analyses and structural modeling.

4.2. Scale Development and Factor Analysis

The measurement model was evaluated in two stages. First, Exploratory Factor Analysis (EFA) was conducted to examine the initial factor structure of the scales and to assess construct dimensionality. Second, Confirmatory Factor Analysis (CFA) was performed to test the reliability and validity of the final measurement model involving perceived policy effectiveness, emotional environmental engagement, and environmental behavior.

The EFA results supported the dimensional structure of both scales. Subsequently, CFA confirmed that all observed indicators loaded significantly on their respective latent constructs, and standardized factor loadings exceeded the commonly accepted threshold (λ ≥ 0.50), indicating satisfactory indicator reliability.

Composite Reliability (CR) values were above 0.70 for all constructs, supporting internal consistency. Convergent validity was assessed using Average Variance Extracted (AVE), and all AVE values exceeded the recommended threshold of 0.50, indicating that the indicators adequately represented their intended latent dimensions.

Discriminant validity was evaluated using both the Fornell–Larcker criterion and the Heterotrait–Monotrait (HTMT) ratio. For each construct, the square root of AVE exceeded inter-construct correlations, and all HTMT values remained below the recommended threshold of 0.85. These findings indicate that the constructs are empirically distinguishable and do not show problematic conceptual overlap.

Overall, the measurement model demonstrates satisfactory reliability, convergent validity, and discriminant validity, providing an appropriate basis for structural model analysis. Model fit indices further support this conclusion (CFI = 0.94; TLI = 0.92; RMSEA = 0.05; SRMR = 0.04). This two-stage procedure strengthens the consistency between initial scale validation and final structural model estimation.

As reported in Table 3, the PPEEEB scale demonstrates a clear unidimensional structure, with all items loading above the recommended thresholds. This supports the interpretation of the scale as a coherent measure of perceived policy effectiveness related to the environmental outcomes of the plastic bag charge. The strong reliability coefficient further indicates high internal consistency across the nine items.

Table 3. Exploratory Factor Analysis (EFA) Results for Initial Scale Validation of the PPEEEB Scale.

Item	Factor 1
The plastic bag charge has helped protect many land and marine species.	0.888
The policy has significantly contributed to reducing environmental pollution.	0.883
The policy has contributed to reducing water pollution.	0.870
Charging for plastic bags has contributed to reducing air pollution.	0.864
The policy has increased awareness of environmental protection.	0.851
The policy has significantly reduced plastic bag use.	0.844
The policy has contributed to the development of ecological modernization awareness.	0.812
The policy has positively contributed to the country’s modern image.	0.722
The use of reusable shopping bags has increased.	0.574

Note. Principal Component Analysis (PCA) was used, and a single-factor structure was identified. Factor loadings below 0.40 were excluded. The Kaiser–Meyer–Olkin (KMO) measure was 0.903, indicating strong sampling adequacy, and Bartlett’s test of sphericity was significant (p < 0.001). The scale demonstrated high reliability (Cronbach’s α = 0.937).

As reported in Table 4, the analysis revealed a three-factor structure consisting of individual action, emotional engagement, and collective action. The individual action dimension reflects routine pro-environmental practices, the emotional dimension captures affective responses to environmental issues, and the collective action dimension represents participation in environmental initiatives.

Table 4. Exploratory Factor Analysis (EFA) Results for Initial Scale Validation of the EAA Scale.

Item	Factor 1 (Individual Action)	Factor 2 (Emotion)	Factor 3 (Collective Action)
I prefer environmentally friendly packaging.	0.807	—	—
I prefer recyclable products when shopping.	0.790	—	—
I prefer products from environmentally responsible firms.	0.717	—	—
I prefer stores offering compostable bags.	0.691	—	—
I prefer less polluting transportation options.	0.679	—	—
I prefer energy- and water-efficient products.	0.678	—	—
I separate waste for recycling.	0.553	—	—
I report environmentally harmful businesses.	0.421	—	—
I try to prevent waste of resources.	0.407	—	—
I feel sad when animals die due to pollution.	—	0.827	—
I feel sad when I see injured animals.	—	0.791	—
I feel disturbed by plastic waste in nature.	—	0.749	—
I see nature as a shared living space.	—	0.739	—
I feel happy when people help animals.	—	0.585	—
I voluntarily participate in environmental campaigns.	—	—	0.736
I participate in animal welfare campaigns.	—	—	0.706
Participating in environmental campaigns makes me feel good.	—	—	0.668
I actively engage in environmental activities.	—	—	0.552

Note. Principal Component Analysis with Varimax rotation was used. Factor loadings below 0.40 were suppressed. The KMO value was 0.903, and Bartlett’s test was significant (p < 0.001). The overall reliability of the scale was satisfactory (Cronbach’s α = 0.876).

All factor loadings fall within acceptable ranges, supporting construct validity and scale reliability. This multidimensional structure is consistent with the theoretical framework of the study and provides an empirical basis for distinguishing behavioral, emotional, and collective dimensions of environmental engagement without assuming deterministic causal relationships.

4.3. Measurement Model and Validity Assessment

The validity and reliability of the measurement model were assessed using Confirmatory Factor Analysis (CFA). The analysis focused on the three main latent constructs of the study: perceived policy effectiveness, emotional environmental engagement, and environmental behavior.

Model fit indices indicate a satisfactory fit between the proposed measurement model and the observed data (CFI = 0.94; TLI = 0.92; RMSEA = 0.05; SRMR = 0.04), suggesting that the latent structure is empirically consistent with the theoretical framework.

Reliability was evaluated using Composite Reliability (CR) and Cronbach’s alpha. All CR values exceeded the recommended threshold of 0.70, indicating satisfactory internal consistency across the constructs. Convergent validity was assessed using Average Variance Extracted (AVE), and all AVE values were above the recommended threshold of 0.50, demonstrating that the indicators adequately represented their intended latent dimensions.

Discriminant validity was examined using two complementary approaches: the Fornell–Larcker criterion and the Heterotrait–Monotrait ratio (HTMT).

According to the Fornell–Larcker criterion presented in Table 5, the square root of AVE for each construct exceeds its correlations with the remaining constructs. This indicates that each construct shares more variance with its own indicators than with conceptually related constructs, supporting discriminant validity.

Table 5. Discriminant Validity: Fornell–Larcker Criterion.

Constructs	(1)	(2)	(3)
(1) Policy Effectiveness	0.82
(2) Emotional Engagement	0.56	0.85
(3) Environmental Behavior	0.49	0.63	0.78

Note. Diagonal elements (in bold) represent the square root of Average Variance Extracted (AVE). Off-diagonal elements represent inter-construct correlations.

This conclusion is further supported by the HTMT results shown in Table 6. All HTMT values remain below the recommended threshold of 0.85, suggesting that the constructs do not exhibit problematic conceptual overlap and can be treated as empirically distinct dimensions.

Table 6. Discriminant Validity: HTMT Ratios.

Constructs	(1)	(2)	(3)
(1) Policy Effectiveness	—
(2) Emotional Engagement	0.68	—
(3) Environmental Behavior	0.61	0.74	—

Note. All Heterotrait–Monotrait (HTMT) values are below the recommended threshold of 0.85.

Demonstrating discriminant validity is particularly important given the conceptual proximity between perceived policy effectiveness, emotional environmental engagement, and environmental behavior. These findings reduce the possibility that the observed relationships are simply the result of measurement overlap or common method inflation.

Overall, the measurement model demonstrates satisfactory reliability, convergent validity, and discriminant validity, providing a robust basis for subsequent structural model analysis. This strengthens the interpretation of the findings while supporting the conceptual distinction between policy evaluation, emotional engagement, and behavioral outcomes.

4.4. Structural Model (SEM)

To examine the proposed theoretical framework, the direct and indirect associations among perceived policy effectiveness (PPE), emotional environmental engagement (EEE), and environmental behavior (EB) were analyzed using Structural Equation Modeling (SEM). The analysis was designed to test the four hypotheses derived from the literature review and to evaluate whether emotional environmental engagement represents an important explanatory dimension linking policy evaluations and environmental behavior.

Indirect effects were assessed using a bootstrap procedure with 5000 resamples and 95% confidence intervals. Because the study is based on cross-sectional and self-reported data, the results are interpreted as associative patterns rather than definitive causal mechanisms.

First, the relationship between perceived policy effectiveness and emotional environmental engagement (H1) was examined. The results indicate a positive and statistically significant association (β = 0.56, p < 0.001), suggesting that individuals who evaluate the plastic bag charge policy as more environmentally effective tend to report stronger emotional engagement with environmental issues.

Second, the direct relationship between perceived policy effectiveness and environmental behavior (H3) was tested. The findings show that this association is positive and statistically significant, although comparatively modest in magnitude (β = 0.21, p < 0.01). This indicates that more positive evaluations of policy effectiveness are associated with stronger self-reported environmental behavior.

Third, the relationship between emotional environmental engagement and environmental behavior (H2) was estimated within the full structural model. Emotional engagement remained strongly and positively associated with environmental behavior (β = 0.62, p < 0.001), indicating that affective involvement plays a substantial role in shaping environmentally responsible actions.

Finally, the indirect relationship proposed in H4 was evaluated through bootstrap analysis. The indirect effect of perceived policy effectiveness on environmental behavior through emotional environmental engagement was statistically significant (β = 0.35; 95% CI [0.21, 0.49]). Because the confidence interval did not include zero, the findings support a significant indirect association pattern consistent with the proposed theoretical framework. This suggests that emotional environmental engagement represents an important explanatory dimension linking policy evaluations and environmental behavior. However, given the cross-sectional design, this result should be interpreted as indicative of associative relationships rather than definitive mediation or causal sequencing.

As shown in Table 7, the findings indicate that perceived policy effectiveness is associated with environmental behavior both directly and indirectly through emotional environmental engagement.

Table 7. Structural Model Results.

Hypothesis	Path	β	t	p	Result
H1	Policy → Emotional Engagement	0.56	9.21	<0.001	Supported
H2	Emotional Engagement → Behavior	0.62	10.47	<0.001	Supported
H3	Policy → Behavior	0.21	2.85	<0.01	Supported
H4	Policy → Emotion → Behavior (indirect)	0.35	—	<0.01	Supported

Note. β values represent standardized path coefficients. Significance levels for direct effects are based on t-values, while the indirect effect is based on bootstrap results (5000 resamples, 95% confidence interval). The indirect effect is interpreted as evidence of a significant indirect association pattern rather than definitive mediation, consistent with the cross-sectional nature of the data.

Taken together, these findings indicate that perceived policy effectiveness is associated with environmental behavior both directly and indirectly through emotional environmental engagement. The stronger indirect association suggests that emotional engagement represents an important explanatory dimension linking policy evaluations and behavioral outcomes. However, given the cross-sectional design, these findings should be interpreted as indicative of associative relationships rather than definitive mediation or causal sequencing.

4.5. Demographic Characteristics

Table 8 presents the demographic profile of the 515 participants included in the study. Female respondents constitute 61.9% of the sample, while 38.1% are male. A majority of participants fall within the 18–35 age range (60.4%), indicating that the sample is relatively young.

Table 8. Sample Characteristics (n = 515).

Variable	Category	n	%
Gender	Female	319	61.9
	Male	196	38.1
Age	18–25	195	37.9
	26–35	116	22.5
	36–45	92	17.9
	46–55	74	14.4
	56–65	31	6.0
	66+	7	1.4
Education	Primary	3	0.6
	Secondary	3	0.6
	High School	24	4.7
	Associate Degree	82	15.9
	Bachelor’s	242	47.0
	Master’s	71	13.8
	PhD	90	17.5
Economic Status	Very low	22	4.3
	Low	87	16.9
	Middle	367	71.3
	High	38	7.4
	Very high	1	0.2
Occupation	Academic staff	90	17.5
	Teacher	64	12.4
	Engineer	49	9.5
	Student	180	35.0
	Civil servant	51	9.9
	Other	81	15.7

Note. Categories are grouped for clarity and readability.

As shown in Table 8, female respondents constitute 61.9% of the sample, while 38.1% are male. A majority of participants fall within the 18–35 age range (60.4%), indicating that the sample is relatively young.

In terms of education, most respondents report relatively high educational attainment. Nearly half of the participants hold a bachelor’s degree (47.0%), while 31.3% report postgraduate qualifications (Master’s or PhD). This suggests that the sample includes a substantial proportion of individuals who may be more exposed to environmental discourse and policy-related evaluation processes.

The sample is predominantly middle-income (71.3%), and students (35.0%) together with academic staff (17.5%) represent the largest occupational groups. This demographic concentration may be associated with stronger environmental awareness and greater sensitivity to policy evaluation.

At the same time, these characteristics should be considered when interpreting the findings. The overrepresentation of younger and highly educated participants limits the direct generalizability of the results to the broader population of Turkey. In particular, education level and age may influence both policy perceptions and self-reported environmental behavior.

Accordingly, the findings should be interpreted as reflecting patterns within this sample rather than as definitive population-level conclusions. Demographic composition therefore forms part of the broader interpretive context rather than a source of causal explanation.

4.6. Descriptive Findings

Table 9, Table 10, Table 11, Table 12, Table 13, Table 14, Table 15 and Table 16 present the descriptive findings regarding participants’ environmental awareness, policy perceptions, behavioral responses, and evaluations of the paid plastic bag policy. To improve clarity and reduce redundancy, each table is interpreted briefly and directly in relation to the proposed theoretical framework.

Table 9. Participants’ Conceptualizations of Environmental Awareness (n = 515).

View	n	%
Avoiding behaviors that harm the environment	162	31.5
Viewing nature as a shared habitat with other living beings	141	27.4
Possessing ecological modernization awareness	86	16.7
Contributing to the diffusion of ecological modernization awareness	54	10.5
Actively combating environmentally harmful factors	26	5.0
Participating in environmental campaigns	18	3.5
Attempting to prevent resource waste	19	3.7
Other	9	1.7
Total	515	100

Table 10. Participants’ Perceptions of the Purpose of the Paid Plastic Bag Policy (n = 515).

View	n	%
A policy aimed at reducing environmental pollution	234	45.4
A policy intended to raise environmental awareness	133	25.8
A measure for generating state revenue	90	17.5
A transitional step toward banning plastic bags	36	7.0
No opinion/not aware of the policy	11	2.1
Other	11	2.1
Total	515	100

Table 11. Participants’ Perceptions of the Most Important Environmental Problem in Turkey (n = 515).

Environmental Problem	n	%
Pollution caused by plastic waste	248	48.2
Drought	65	12.6
Deforestation	64	12.4
Contamination of drinking water resources	44	8.5
Air pollution	31	6.0
Marine and river pollution	21	4.1
Erosion (soil loss)	4	0.8
Other	38	7.4
Total	515	100

Table 12. Perceived Most Effective Measures to Reduce the Use of Plastic Bags and Single-Use Plastics (n = 515).

Measure	n	%
Complete ban on plastic products	116	22.5
Implementation of a deposit-refund system	110	21.4
Free distribution of reusable bags	89	17.3
Public service announcements and informational campaigns	62	12.0
Additional environmental taxes	39	7.6
Environmental themes in films and TV series	37	7.2
Increased regulatory enforcement	35	6.8
Other	27	5.2
Total	515	100

Table 13. Impact of the Paid Plastic Bag Policy on Consumption Behavior (n = 515).

Impact Level	n	%
No change	116	22.5
Slight decrease	185	35.9
Reduced by half	98	19.0
Significant decrease	108	21.0
Completely stopped	8	1.6
Total	515	100

Table 14. Frequency of Proper Waste Disposal Behavior (n = 515).

Frequency	n	%
Never	6	1.2
Very rarely	10	1.9
Occasionally	12	2.3
Mostly	127	24.7
Always	360	69.9
Total	515	100

Table 15. Frequency of Walking or Cycling for Short Distances (n = 515).

Frequency	n	%
Never	18	3.5
Very rarely	50	9.7
Occasionally	75	14.6
Mostly	179	34.8
Always	193	37.5
Total	515	100

Table 16. Perceived Contribution of the Paid Plastic Bag Policy to Ecological Modernization Awareness (n = 515).

Contribution Level	n	%
Very low	7	1.4
Low	22	4.3
Moderate	69	13.4
High	189	36.7
Very high	228	44.3
Total	515	100

Participants primarily defined environmental awareness as avoiding environmentally harmful behaviors (31.5%) and viewing nature as a shared habitat with other living beings (27.4%). This indicates that environmental awareness is largely framed as an individual ethical responsibility rather than collective participation.

Most participants interpreted the paid plastic bag policy as an environmental measure aimed at reducing pollution (45.4%) or raising environmental awareness (25.8%). This suggests that the dominant public understanding of the policy is aligned with its environmental purpose, although some respondents also perceive it as a revenue-generating mechanism (17.5%).

Nearly half of the participants (48.2%) identified plastic waste pollution as the most important environmental problem. This reinforces the contextual relevance of the plastic bag charge policy and supports its analytical suitability for the present study.

Participants tended to favor stronger and more direct interventions such as a complete ban on plastic products (22.5%) and deposit-refund systems (21.4%) over indirect measures such as additional environmental taxes (7.6%). This indicates a preference for visible and immediate policy action.

Most respondents reported some degree of reduction in plastic bag use, while 22.5% indicated no change. This suggests that respondents report a generally positive behavioral change following the policy, although responsiveness varies across individuals.

A large majority of participants reported consistently disposing of waste properly, with 69.9% selecting “always.” This indicates that basic pro-environmental practices are relatively well internalized.

Walking or cycling for short distances is also common, with 72.3% reporting that they do so mostly or always. This reflects a relatively high level of routine environmentally responsible mobility behavior.

A strong majority of participants (81.0%) evaluated the policy as making a high or very high contribution to ecological modernization awareness. This indicates that the policy is perceived not only as a regulatory measure but also as a broader awareness-generating intervention.

Taken together, these descriptive findings suggest that the effects of the plastic bag policy extend beyond purely economic deterrence mechanisms. Rather, the policy appears to operate through individuals’ evaluations of policy outcomes and the meanings attached to environmental action.

These patterns provide preliminary support for the proposed theoretical framework, in which perceived policy effectiveness is associated with environmental behavior both directly and indirectly through emotional environmental engagement.

4.7. Supplementary Analyses

Additional analyses were conducted to examine whether demographic factors and emotional engagement produced meaningful variation across environmental perceptions and behaviors.

As shown in Table 17, gender differences were generally limited across the main constructs. No statistically significant differences were observed for perceived policy effectiveness, individual action, or collective action. A significant difference emerged only for emotional engagement (p < 0.001), with female participants reporting higher emotional environmental engagement than male participants.

Table 17. Comparison of PPEEEB and EAA Scores by Gender (Independent Samples t-Test Results).

Variable	Gender	n	Mean	SD	p
PPEEEB Impact Dimension	Male	196	3.40	1.02	0.898
	Female	319	3.41	0.90
EAA Individual Action	Male	196	4.88	0.71	0.567
	Female	319	4.92	0.66
EAA Emotion	Male	196	4.60	0.55	0.001 ***
	Female	319	4.77	0.42
EAA Collective Action	Male	196	3.09	0.87	0.142
	Female	319	3.20	0.78

Note. Since Levene’s Test indicated unequal variances for some variables (p < 0.05), the “Equal variances not assumed” values were used where appropriate. Statistical significance was evaluated at p < 0.05. *** p < 0.001.

As shown in Table 18, the ANOVA results indicate that environmental behavior and emotional engagement vary more strongly across demographic variables than perceived policy effectiveness. Age and education were significantly associated with individual and collective action, while emotional engagement showed broader variation across age, education, faculty type, and occupation. In contrast, perceived policy effectiveness differed significantly only by economic status.

Table 18. Comparison of PPEEEB and EAA Scores by Demographic Variables (ANOVA Results).

Dependent Variable	Age	Education	Faculty Type	Economic Status	Occupation
PPEEEB Impact Dimension	0.09	0.57	0.49	0.05 *	0.16
EAA Individual Action	0.00 *	0.02 *	0.33	0.27	0.16
EAA Emotion	0.05 *	0.05 *	0.03 *	0.09	0.01 *
EAA Collective Action	0.04 *	0.04 *	0.75	0.63	0.34

* Note: Values represent p-values. p < 0.05 indicates statistical significance.

As shown in Table 19, correlation analysis revealed positive and statistically significant relationships between perceived policy effectiveness and environmental awareness dimensions. The strongest relationship was observed between policy effectiveness and individual action, while emotional engagement also showed meaningful positive associations with both individual and collective environmental behavior.

Table 19. Correlation Analysis between PPEEEB and EAA and Its Sub-Dimensions (n = 515).

Variables	1	2	3	4	5
(1) PPEEEB Total	—
(2) EAA Total	0.257 **	—
(3) Individual Action	0.232 **	0.914 **	—
(4) Emotion	0.152 **	0.542 **	0.282 **	—
(5) Collective Action	0.175 **	0.783 **	0.584 **	0.271 **	—

Note. ** p < 0.01 (two-tailed).

Integrated Interpretation of Additional Analyses

Taken together, these findings suggest that emotional engagement represents the most socially differentiated dimension of environmental behavior. While perceived policy effectiveness remains relatively stable across demographic groups, affective engagement and behavioral participation appear more sensitive to age, education, gender, and occupational context.

These supplementary findings are consistent with the structural model results and reinforce the interpretation that emotional engagement functions as an important explanatory dimension linking policy evaluations and environmental behavior.

5. Discussion

This study examines the relationship between the paid plastic bag policy and individual environmental behavior through the interplay between perceived policy effectiveness and emotional environmental engagement. The findings indicate that policy effects cannot be adequately understood solely through economic incentives; rather, they are also associated with individuals’ evaluations of policy outcomes and the emotional responses accompanying these evaluations. However, these relationships should be interpreted as associative and indicative rather than strictly causal.

First, the strong association between perceived policy effectiveness and emotional environmental engagement (Table 7; β = 0.56) suggests that individuals who evaluate the environmental outcomes of the policy more positively also tend to report stronger emotional engagement with environmental issues. Because the study relies on cross-sectional and self-reported data, causal direction cannot be established. It is equally plausible that individuals with stronger environmental sensitivity are more likely to perceive the policy as effective. Therefore, the findings indicate a meaningful and theoretically consistent association rather than a definitive causal effect.

Second, the strong association between emotional environmental engagement and environmental behavior (Table 7; β = 0.62) highlights that environmental behavior cannot be adequately explained through cognitive evaluations alone. This finding is consistent with previous studies emphasizing the motivational role of affective processes in shaping pro-environmental action [9,11,16]. Since the behavioral measures are self-reported, these results should be interpreted as reflecting stated behavioral tendencies rather than directly observed actions.

Third, the comparatively weaker direct association between perceived policy effectiveness and environmental behavior (Table 7; β = 0.21) suggests that policy evaluations alone may be insufficient to explain behavioral alignment. The structural model presented in Table 7 shows that stronger indirect association patterns emerge when emotional environmental engagement is considered. This supports the view that the relationship between policy evaluation and behavior is not exclusively direct or purely instrumental.

This interpretation is consistent with previous studies emphasizing the role of emotional and collective processes in environmental engagement. Research on collective efficacy and emotional mobilization suggests that individuals are more likely to engage in pro-environmental action when cognitive evaluations are accompanied by affective reinforcement [16,28]. Similarly, studies on plastic bag charges show that policy support and behavioral compliance become stronger when individuals perceive visible environmental outcomes and stronger policy effectiveness [6,20,21,22]. This does not imply that economic mechanisms are unimportant; rather, policy effects are better understood when economic explanations are considered together with evaluative and emotional dimensions.

These findings also align with integrative models of environmental behavior, which emphasize that behavior is shaped by the interaction of cognitive, normative, and emotional factors rather than by any single mechanism [14,15]. The results therefore support a multidimensional understanding of policy effects at the individual level.

The indirect effect analysis (Table 7) indicates that a substantial portion of the relationship between perceived policy effectiveness and environmental behavior is associated with emotional environmental engagement (β = 0.35). This suggests that emotional engagement represents an important explanatory dimension within the observed association pattern. However, this should not be interpreted as definitive evidence of an underlying causal mechanism, but rather as a pattern consistent with the proposed theoretical framework.

The descriptive findings (Table 9, Table 10, Table 11, Table 12, Table 13, Table 14, Table 15 and Table 16) provide contextual support for these analytical results. Participants largely perceive the policy as an environmental intervention (Table 10), identify plastic pollution as a major environmental problem (Table 11), and report that the policy contributes to ecological modernization awareness (Table 16). At the same time, variation in behavioral responses (Table 13) suggests that cognitive recognition does not automatically translate into behavioral consistency. In this context, emotional engagement emerges as a plausible explanatory dimension linking policy evaluation and environmental behavior.

Demographic differences observed in Table 18 and Table 19 further suggest that these processes do not operate uniformly across individuals, but vary according to age, gender, education, and occupation. This highlights the contextual and differentiated nature of policy effects at the individual level.

An important issue concerns conceptual clarity. The construct examined in this study is more accurately captured as perceived policy effectiveness. The analysis focuses on individuals’ evaluations of policy outcomes rather than broader normative dimensions such as procedural fairness, institutional trust, or institutional legitimacy. This distinction ensures consistency between theory, measurement, and interpretation.

This study contributes to the literature in three main ways. Theoretically, it strengthens the integration between ecological modernization theory and environmental behavior research by demonstrating the relevance of emotional engagement as an explanatory dimension linking policy evaluations and behavioral outcomes. Empirically, it provides evidence from the case of Turkey’s nationwide plastic bag charge, a middle-income country context that remains relatively underrepresented in the literature. From a policy perspective, the findings suggest that environmental policies may become more effective when citizens perceive visible environmental outcomes and when policy design supports emotional and cognitive engagement alongside economic incentives.

6. Conclusions

This study investigated the relationship between Turkey’s paid plastic bag policy and individual environmental behavior through perceived policy effectiveness and emotional environmental engagement. The findings suggest that market-based environmental policies cannot be adequately understood solely through economic incentives; they are also associated with how individuals evaluate policy outcomes and how these evaluations relate to emotional engagement.

As shown in Table 7, the direct association between perceived policy effectiveness and environmental behavior is relatively modest, while stronger patterns emerge when emotional environmental engagement is considered. This suggests that policy evaluations and emotional processes should be examined together rather than separately when seeking to understand environmental behavior.

An important contribution of the study lies in clarifying the conceptual focus of the analysis. The construct measured reflects perceived policy effectiveness—that is, individuals’ evaluations of whether the policy meaningfully contributes to solving environmental problems—rather than broader normative concepts such as legitimacy, fairness, or institutional trust. This distinction strengthens both theoretical coherence and empirical validity.

The descriptive findings (Table 9, Table 10, Table 11, Table 12, Table 13, Table 14, Table 15 and Table 16) provide additional support for this interpretation. Participants largely perceive the policy as an environmental intervention, recognize plastic pollution as a major environmental issue, and report that the policy contributes to ecological modernization awareness. At the same time, variation in behavioral responses indicates that cognitive recognition alone does not automatically produce behavioral consistency, highlighting the importance of emotional engagement.

Several limitations should be acknowledged. First, the cross-sectional design limits causal interpretation and does not allow direct observation of temporal ordering. Second, the reliance on self-reported data increases the possibility of common method bias and social desirability effects, although procedural and statistical precautions were taken to reduce these risks. Third, direct behavioral indicators and economic deterrence mechanisms such as price sensitivity and cost perception were not directly measured.

Future research should employ longitudinal designs, experimental approaches, and direct behavioral indicators to examine these relationships more robustly. More comprehensive models integrating perceived policy effectiveness, economic cost perceptions, and emotional engagement may provide a stronger understanding of how environmental policies influence behavior over time.

In conclusion, environmental policies are more likely to produce sustained behavioral change when economic instruments are supported by visible policy outcomes, cognitive evaluations, and emotional public engagement. At the same time, more rigorous empirical designs are needed to verify the temporal and causal ordering of these relationships.