Are climate change perceptions related with plastic policy support? Effects of climate change skepticism, guilt, and efficacy on the acceptance of the plastic tax

When analyzing the support for taxes and value factors, we found that environmentalism, altruism, and egalitarianism are positively related to support for taxes, and materialism was negatively related to support for taxes. In particular, sup- port for taxes had the highest correlation with environmentalism, followed by altruism and egalitarianism. Environmental Fig 1. Frequency of support for the plastic tax. https://doi.org/10.1371/journal.pone.0337327.g001 Fig 2. Frequency of support for the plastic tax. https://doi.org/10.1371/journal.pone.0337327.g002

PLOS One | https://doi.org/10.1371/journal.pone.0337327 December 29, 2025 14 / 30 Fig 3. Mean analysis according to demographic variables. https://doi.org/10.1371/journal.pone.0337327.g003 Table 2. Correlation analysis between risk perception, value, and environmental psychological factors regarding the acceptance of the plastic tax. 1 2 3 4 5 6 7 8 9 10 11 1. Placstic Policy Support 1 Value factor 2. Environmentalism .410*** 1 3. Altruism .334*** .358*** 1 4. Egalitarianism .187*** .128*** .198*** 1 5. Materialism −.213*** −.194*** −.249*** −.023 1 Risk perception factor 6. Perceived risk .481*** .464*** .404*** .128*** −.311*** 1 7. Knowledge .283*** .328*** .053* .088*** .099*** .211*** 1 8. Trust .364*** .305*** .184*** .138*** .048 .306*** .485*** 1 9. Emotions .331*** .312*** .274*** .114*** −.213*** .571*** .166*** .168*** 1 Planned behavior factor 10. Climate change skepticism −.200*** −.165*** −.258*** .013 .385*** −.351*** .261*** .142*** −.250*** 1 11. Guilt .352*** .386*** .163*** .138*** −.051* .353*** .471*** .436*** .275*** .096*** 1 12. Efficacy .389*** .398*** .238*** .150*** −.087** .409*** .452*** .545*** .254*** .025 .562*** https://doi.org/10.1371/journal.pone.0337327.t002

PLOS One | https://doi.org/10.1371/journal.pone.0337327 December 29, 2025 15 / 30 values had a strong correlation with the acceptance of the plastic tax because these values refer to environmental pro- tection, nature preservation, and restoration to combat the environmental crisis. Understanding how much the planet is suffering is based on the altruistic value of caring about other living things. In this sense, altruistic values have a defining relationship with the support for the plastic tax. Conversely, materialism had a negative relationship with the acceptance of taxes, probably due to the focus on eco- nomic development and the satisfaction of needs, in contrast to post-materialist values based on self-actualization, which links to environmentalism, altruism, and egalitarianism. These findings suggest conflicts between altruistic, egalitarianism, post-materialistic values and egoism, individualism, and materialism regarding the plastic tax. When analyzing the support factors and risk perception paradigm, we found that perceived risk, knowledge, trust, and emotion were all positively related to support for taxes. In particular, support for taxes and perceived risk had the largest coefficient, followed by trust > emotion > knowledge. These results suggest that the risk of using plastic is a strong argu- ment in favor of the tax. When analyzing the support for taxes and environmental psychological factors, climate change skepticism was found to have a negative relationship with the acceptance of taxes, and guilt and efficacy had a positive relationship with the

support for taxes. In particular, the acceptance of taxes and efficacy (r = .390, p < .001) had the largest coefficient value, followed by guilt and climate change skepticism. These results suggest that individuals’ belief that they can do something about climate change is linked to tax. In reality, the presence of resources or individual abilities increases their sense of control over an object, thus driving relevant behavior. The variables that are associated with the support for taxes, the most were perceived risk > environmentalism > effi- cacy > trust, suggesting that an individual’s perceived risk of climate change is an important factor affecting policy-related tax (dis)agreement. Regression analysis Multiple regression analysis was conducted to identify the factors associated with the acceptance of the plastic tax. Model 1 examined the relationship between independent variables and the support for the plastic tax without including the planned behavior factor, and Model 2 included variables in planned behavior, such as climate change skepticism, guilt, and efficacy (Table 3). The explanatory power of Model 1 was 34.2%, with a model fit of 64.373 (p < .001). The tolerance was greater than 0.1, and the VIF was less than 10, indicating no multicollinearity. The results of Model 1 showed that, in terms of sociodemographic factors, age and education variables were signifi- cantly associated with the support for the plastic tax. A higher age and education were likely to be associated with a higher

the support for the plastic tax because individuals in this group were more likely to experience the problems of climate change. They indicate the need to gain the sympathy of the young and less-educated groups because they have negative attitude toward raising taxes related to climate change in the future. Next, among the value factors, environmentalism, altruism, and egalitarianism were significantly positively associated with the acceptance of the plastic tax, while materialism was significantly negatively associated with the support for the plastic tax. In the risk perception paradigm, perceived risk, knowledge, trust, and emotion all contributed significantly positively to the acceptance of the plastic tax. Based on the standardized regression coefficients, the variables that are associated with the support for the plastic tax were perceived risk > trust > environmentalism > knowledge > altruism > mate- rialism > egalitarianism > emotion. Perceived risk had the strongest association with the support for the plastic tax, which means that the higher an individual’s perceived risk of climate change, the higher their support for the plastic tax. In other words, the higher the perceived risk, the more willing individuals are to pay their taxes to combat climate change. We also observed that in terms of perception, trust and knowledge were operationalized, while in terms of value, environmental- ism and altruism had a significant association with the support for the plastic tax. These results indicate that plastic tax

PLOS One | https://doi.org/10.1371/journal.pone.0337327 December 29, 2025 16 / 30 acceptance requires multi-faceted policy approaches addressing both risk communication and value-based messaging. Specifically, policymakers should combine evidence-based risk communication strategies to enhance perceived climate threats with targeted messaging that resonates with environmental and altruistic values while addressing materialistic concerns through economic framing. The explanatory power of Model 2, which adds the three variables in planned behavior to Model 1, was 36.0%, with a model fit of 55.503 (p < .001). The tolerance was above 0.1, and the VIF was below 10, indicating no multicollinearity. In Model 2, the sociodemographic factors were the same as in Model 1: Higher age and education were significantly associated with the support for the plastic tax. The value factors of environmentalism, altruism, and egalitarianism had a significantly positive effect on the support for the plastic tax, while materialism demonstrated a significantly negative relationship with the support for the plastic tax. As for the risk perception paradigm factors, perceived risk, knowledge, and trust, excluding emotion, all had a significantly positive association with the support for the plastic tax. Among planned behavior factors, climate change skepticism had a significantly negative link with the support for the plastic tax; guilt and efficacy had a significantly positive association with the support for the plastic tax.

Based on the standardized regression coefficients in Model 2, we found that the effect size is positively associated with in the order of perceived risk > climate change skepticism > trust > environmentalism > knowledge > egalitarianism > altruism > guilt > efficacy > materialism. As in Model 1, perceived risk had the strongest positive association with the support for the plastic tax. In Model 2, the moderator variable of climate change skepticism had the second largest relationship, which can be interpreted as a result of different political frameworks. Despite the emphasis on reducing greenhouse gas emissions, doubts about Table 3. Regression analysis to identify factors associated with the acceptance of the plastic taxes. Variables Model 1 Model 2 b S.E Beta b S.E Beta (Constants) .135 .239 .478 .249 Sociodemographic factors Sex −.009 .041 −.005 −.038 .040 −.020 Age .054*** .015 .082 .054*** .015 .083 Education .105* .042 .056 .098* .042 .052 Income .029 .024 .026 .029 .024 .026 Independent 1 Values factors Environmentalism .174*** .034 .131 .136*** .034 .103 Altruism .094*** .023 .099 .082*** .023 .087 Egalitarianism .101*** .023 .095 .098*** .023 .093 Materialism −.105*** .025 −.097 −.072** .025 −.067 Independent 2 Risk Perception Paradigm Perceived risk .269*** .036 .217 .200*** .037 .161 Knowledge .126*** .031 .103 .119*** .033 .098 Trust .184*** .033 .139 .149*** .036 .113 Emotion .071* .032 .058 .053 .032 .043 Moderating Environmental Psychological factors

Climate change skepticism −.123*** .026 −.122 Guilt .101** .034 .081 Efficacy .086* .034 .072 F value 64.373*** 55.503*** R 0.585 0.600 R2 0.342 0.360 adj. R2 0.337 0.353 * p < .05, ** p < .01, *** p < .001. https://doi.org/10.1371/journal.pone.0337327.t003

PLOS One | https://doi.org/10.1371/journal.pone.0337327 December 29, 2025 17 / 30 global warming have increased, for example, due to the U.S. withdrawal from the Paris Agreement in 2017. Many Americans believe that the problem of climate change has been exaggerated, meaning that climate change skepticism is widespread. As the study of climate change is a risk analysis based on scientific uncertainty, global warming has long been a matter of debate. Thus, the results showed that, except for emotions, value, risk perception, and planned behavior variables are all sig- nificantly associated with the support for the plastic tax. In the case of the plastic tax, risk perception and skepticism about climate change play a particularly important role. Hypothesis testing results systematically support our theoretical framework (Table 3). Value-based hypotheses were largely confirmed, validating Stern’s [14] value-belief-norm theory applications to environmental policy contexts. Environ- mentalism significantly predicted plastic tax acceptance (H1: β = .103, p < .001), consistent with previous research demon- strating environmental values’ positive impact on policy support [27,55]. This finding aligns with Mozumder’s [57] work showing environmental consciousness effects on renewable energy support and extends Kim’s [106] findings on environ- mentalist values supporting environmental protection policies to plastic taxation contexts. Altruism showed significant positive effects (H2: β = .087, p < .001), supporting VBN theory predictions that altruistic val-

ues drive pro-environmental behaviors [14]. This result resonates with Lee et al.‘s [107] demonstration that altruistic value orientation influenced eco-friendly food purchasing intentions, with altruistic values showing stronger effects than individu- alistic orientations. Our findings extend this pattern to environmental taxation acceptance. Egalitarianism positively predicted acceptance (H3: β = .093, p < .001), confirming cultural theory predictions [62] that egalitarian individuals demonstrate greater sensitivity to environmental risks and support collective action. This aligns with Kahan et al.‘s [24] findings that individuals with egalitarian values tend to accept climate change risks, while those with individualistic values remain skeptical. Materialism showed expected negative effects (H4: β = −.067, p < .01), supporting post-materialist theory [64] and extend- ing Gelissen’s [67] findings on dematerialization’s positive effects on environmentalism. This result confirms Hurst et al.’s [68] meta-analysis demonstrating materialism’s negative correlation with environmental attitudes and validates Kilbourne et al’s [70] argument that materialistic values predispose individuals toward less supportive environmental policy attitudes. Risk perception hypotheses received strong empirical support, validating psychometric paradigm applications [108]. Perceived risk emerged as the strongest predictor (H5: β = .161, p < .001), consistent with Kim et al’s [74] findings that

higher perceived climate change risk increases response behavior intensity. This supports Visschers et al’s [72] demon- stration that perceived risks significantly influence acceptance decisions across various technologies. Knowledge significantly predicted acceptance (H6: β = .098, p < .001), supporting O’Connor et al.’s [49] findings that greater knowledge associates with higher climate action intentions. However, our results acknowledge Bamberg et al’s [23] caveat that knowledge functions as necessary but insufficient condition within broader psychological processes, requiring combination with values and situational factors [77]. Trust showed substantial effects (H7: β = .113, p < .001), validating trust’s role as representative socio-cultural factor in risk research [82]. This finding extends Visschers et al’s [72] work on government trust in nuclear power operations to climate policy contexts, supporting our competence trust measurement approach [36]. Planned behavior factors demonstrated expected patterns, supporting TPB applications to environmental contexts [16]. Climate skepticism showed strong negative effects (H9: β = −.122, p < .001), consistent with environmental skepticism research showing overestimated crisis beliefs and data error concerns [74]. Guilt demonstrated positive effects (H10: β = .081, p < .01), supporting Ferguson et al’s [90] findings that collective guilt mediates climate change beliefs and mitiga- tion behaviors. Efficacy showed positive associations (H11: β = .072, p < .05), extending Bandura’s [93] self-efficacy frame-

work to environmental policy contexts and confirming Lee et al.’s [94] findings on efficacy’s positive effects on eco-friendly behaviors. The associations in this study should be interpreted as correlational relationships rather than causal effects, given our cross-sectional research design.“

PLOS One | https://doi.org/10.1371/journal.pone.0337327 December 29, 2025 18 / 30 Interaction effect analysis Following the previous analysis, this study analyzed the moderating effects of the environmental psychological factors of climate change skepticism, guilt, and efficacy. Baron and Kenny’s [109] three-step test was used to check the variables and interaction terms, and the results were tested for the simple slope effect. The results showed that climate change skepticism, a moderating variable, had an interaction effect with materialism and emotion, which are independent vari- ables. Table 1 in S1 Appendix in support information lists the results of the interaction effect analysis. Figs 4 and 5 show climate change skepticism as a moderating variable. Fig 4 shows that as materialism increases, support for the plastic tax decreases. However, this effect is reinforced in groups with low climate change skepticism. In the high climate change skepticism group, increased materialism does not increase the support for the tax. These results sug- gest that climate change skepticism and materialism interact to create a negative attitude toward plastic taxes. Climate skep- ticism significantly moderated materialism-acceptance relationships, where materialistic individuals under high skepticism conditions showed particularly strong negative attitudes toward plastic taxes. This interaction supports motivated reasoning theory [24], suggesting that skeptical individuals use materialistic values to justify opposition to environmental policies.

Fig 5 shows that negative emotion, a component of the risk perception paradigm, interacts with climate change skep- ticism.. The skepticism-emotion interaction indicates that negative climate emotions have stronger positive effects on tax support among highly skeptical individuals, potentially representing cognitive dissonance resolution mechanisms. This finding extends Slovic et al.‘s [83] work on emotional responses to environmental risks and supports Kim et al’s [82] find- ings on negative emotions’ significant impacts on nuclear energy acceptance. Fig 4. Materialism*Climate change skepticism. https://doi.org/10.1371/journal.pone.0337327.g004

PLOS One | https://doi.org/10.1371/journal.pone.0337327 December 29, 2025 19 / 30 Next, guilt as the moderator variable interacts with environmentalism, altruism, egalitarianism, and perceived risk (Table 2 in S1 Appendix in support information). Fig 6 shows that environmentalism, a value factor, interacts with guilt. As environmentalism increases, the support for the plastic tax increases, which is larger for those who feel more guilty about climate change than for those who feel less guilty. Altruism also interacts with guilt, and an increase in altruism leads to an increase in the support for the plastic tax, with a larger slope for the middle- and high-guilt groups than for the low-guilt groups (Fig 7). Fig 8 shows that the support for the plastic tax increases as egalitarianism increases, with the width of the slope for guilt increasing in the low and middle groups compared to the high group. Fig 9 shows an interaction effect between perceived risk and guilt in the risk perception paradigm. As the perceived risk increases, the support for the plastic tax increases, with a larger slope for those with higher guilt group. Guilt demonstrated multiple significant interactions, moderating environmentalism (β = .053, p < .05), perceived risk (β = −.088, p < .05), altruism (β = .050, p < .05), and egalitarianism (β = −.050, p < .05) effects. These patterns suggest emo- tional amplification mechanisms where guilt enhances value-based motivations while potentially overwhelming risk-based

reasoning, consistent with affective-cognitive models of environmental behavior [23]. Guilt’s multiple interactions demon- strate emotional amplification mechanisms predicted by affect-cognition theories [29]. Table 3 in S1 Appendix in support information demonstrates that the moderating variable efficacy has an interaction effect with altruism and perceived risk. Fig 10 shows that as altruism increases, the support for the tax increases, and the slope is larger for the middle- and high-efficacy groups than for the low-efficacy groups. Finally, Fig 11 shows that the support for the tax increases as perceived risk increases, with a larger slope for the high-efficacy group than for the low-efficacy group. The regression analysis shows that the perceived risk of climate change has a significant effect on the acceptance of plastic textiles, which can be moderated by self-efficacy. Efficacy interactions with altruism (β = .065, p < .01) and perceived risk (β = −.083, p < .05) indicate that self-efficacy beliefs enhance altruistic motivations while moderating risk perception effects. This supports Bandura’s [93] framework showing efficacy’s influence on cognitive functioning through self-satisfaction with personal development and goal achievement. Fig 5. Emotion*Climate change skepticism. https://doi.org/10.1371/journal.pone.0337327.g005

PLOS One | https://doi.org/10.1371/journal.pone.0337327 December 29, 2025 20 / 30 Fig 6. Environmentalism*Guilt. https://doi.org/10.1371/journal.pone.0337327.g006 Fig 7. Altruism*Guilt. https://doi.org/10.1371/journal.pone.0337327.g007

PLOS One | https://doi.org/10.1371/journal.pone.0337327 December 29, 2025 21 / 30 Fig 8. Egalitarianism*Guilt. https://doi.org/10.1371/journal.pone.0337327.g008 Fig 9. Perceived risk*Guilt. https://doi.org/10.1371/journal.pone.0337327.g009

PLOS One | https://doi.org/10.1371/journal.pone.0337327 December 29, 2025 22 / 30 Fig 10. Altruism*Efficacy. https://doi.org/10.1371/journal.pone.0337327.g010 Fig 11. Perceived risk*Efficacy. https://doi.org/10.1371/journal.pone.0337327.g011

PLOS One | https://doi.org/10.1371/journal.pone.0337327 December 29, 2025 23 / 30 Results and summery The negative effects of climate change are a current cause for concern, rather than a future issue. In addition, the convenience of consumption exacerbates the problem of climate change. In particular, the unconscious use of plastics has emerged as a leading cause of the increase in greenhouse gases, emphasizing the urgent need to regulate plastics. Thus, introducing a plastic tax is essential; however, the acceptability of the tax seems to hinder its implementation. This study analyzed the deter- minants of the decision to pay a tax to reduce plastic use by setting the planned behavior factors such as climate change skepti- cism, guilt, and efficacy as predictor and moderating variables. The main findings of this study are summarized as follows. First, in terms of value factors, environmentalism, altruism, and egalitarianism had a significantly positive effect on the support for the plastic tax, whereas materialism had a significantly negative effect. In addition, in the risk perception paradigm, perceived risk, knowledge, and trust had significantly positive effects on the support for the tax. Regarding the planned behavior factors, climate change skepticism, guilt, and efficacy had significant effects on the support for the plas- tic tax, with climate change skepticism demonstrating a negative effect and guilt and efficacy showing a positive effect. The explanatory power of the variables in the factors mentioned above increased in the order of perceived risk > climate

We analyzed factors determining plastic tax support, focusing on willingness to pay rather than tax amount, finding that values, risk perception, and planned behavior factors determine support for plastic taxes. Our study demonstrates that effective plastic tax policies must simultaneously address values, risk perceptions, and planned behavior elements. This integrated approach aligns with van der Werff et al. [110], who showed environmental policies succeed when addressing both motivational and implementation factors. However, balancing these factors faces challenges from potential conflicts. Gifford [111] notes that policies targeting rational risk assessments may clash with deeply held values, while Steg et al. [112] emphasize that behavioral control interventions can be ineffective if underlying values are unaddressed. Additionally, Harring et al. [113] demonstrate that policies focusing on economic incentives may undermine intrinsic environmental motivations if perceived as coercive. Theoretical insights Our findings provide theoretical insights into plastic tax acceptance mechanisms. The strong predictive power of perceived risk (β = .161) supports psychometric paradigm assertions that subjective risk evaluations drive policy preferences more than objective assessments [108], extending Kahan et al.‘s [24] work on motivated reasoning where individuals process climate information through value-laden filters.

PLOS One | https://doi.org/10.1371/journal.pone.0337327 December 29, 2025 24 / 30 Value-based patterns align with Stern’s [14] VBN theory, where environmentalism, altruism, and egalitarianism activate moral obligation toward collective action. Our study uniquely demonstrates that materialistic values create competing motivational frameworks, supporting post-materialist theory [64] while extending it to taxation contexts. Climate skepticism’s strong negative effect (β = −.122) and moderation patterns reveal motivated reasoning processes where ideological beliefs filter information processing [24]. Our contribution lies in demonstrating how skepticism interacts with materialism to strengthen opposition, suggesting policy communication must address both cognitive and motivational barriers simultaneously. The guilt and efficacy interactions represent theoretical advances in environmental psychology. Unlike previous studies focusing on direct effects [90], our research reveals boundary conditions where emotional and cognitive factors amplify or attenuate value-based motivations. Policy implications These findings have important policy implications requiring simultaneous consideration of multiple variables for plastic tax implementation. From a factor perspective, balanced mixes of values, risk perception, and planned behavior should be reflected in policy. First, introducing plastic tax requires educating the public about climate change risks. Although climate change risks

are visible, risk communication remains lacking. Therefore, we need to effectively communicate facts and present climate change evidence to the public. Second, environmentalism, trust, and climate change concerns have significant relationships with plastic tax acceptabil- ity. These variables differ in nature: environmentalism relates to values, trust to perceptions, and climate change skepti- cism to evaluative attitudes. Persuasive strategies should consider these attributes through three approaches: values-based persuasion using moral reframing strategies that align messages with recipients’ core values [114]; perception-focused strategies using visualization and narrative techniques making abstract risks concrete [115]; and attitude-targeted interventions leveraging existing positive attitudes as bridges to new behaviors [116]. Our main finding that climate change skepticism, guilt, and efficacy act as moderating variables suggests plastic tax implementation requires strategic efforts focused on overcoming skepticism, imposing responsibility, and increasing efficacy. Skepticism can be addressed through evidence-based communication strategies as demonstrated in Ireland’s successful plastic bag levy [117]. For imposing responsibility, the UK’s approach combined guilt messaging with corporate responsibility frames, resulting in 86% reduction in single-use plastic bags [118]. Efficacy was effectively built in Sweden through community-based initiatives showcasing tangible impacts [119].

Our findings confirmed the policy-relevant mechanism connecting public acceptance to plastic tax implementation and consumption reduction. Nielsen et al. [22] demonstrates that public acceptance is critical for successful plastic tax imple- mentation, minimizing political resistance and increasing compliance. When implemented, plastic taxes effectively reduce consumption – Homonoff et al. [11] documented 42% decrease in plastic bag use after taxation in Chicago, while Convery et al. [117] that Ireland’s plastic bag levy led to a reduction in usage by over 90%, demonstrating how strong public sup- port enabled effective implementation and substantial behavioral change. Implementation recommendations To strengthen policy relevance, we offer specific recommendations. First, targeted communication strategies address- ing psychological factors are essential. Rivers et al. [10] demonstrated that messages emphasizing collective efficacy increased environmental tax support by 37%, while Gifford et al. [111] showed guilt-framed messages were effective for environmentally-concerned citizens but counterproductive for skeptics. Phased implementation with initial focus on single-use items allows adaptive policy design. Xanthos et al. [120] found gradual introduction with 6–12 month prepara- tion periods substantially improved business compliance and public acceptance.

PLOS One | https://doi.org/10.1371/journal.pone.0337327 December 29, 2025 25 / 30 Second, policymakers can strategically frame plastic tax initiatives to align with dominant cultural values rather than attempting to change them. Bolderdijk et al. [121] demonstrated that environmental policies framed to resonate with exist- ing public values achieve higher acceptance rates. Communication strategies can emphasize how plastic taxes support specific value orientations—highlighting environmental protection for those with strong environmentalism values or eco- nomic efficiency for those with materialist values. Future research and limitations Future research should extend this framework across multiple domains. Testing our integrated model with other environ- mental policies would establish generalizability beyond plastic taxation. Cross-cultural validation is essential, as cultural values significantly influence environmental policy acceptance [17]. Experimental designs could establish causal relation- ships through field experiments manipulating risk communication messages or laboratory studies varying guilt induction. Longitudinal designs tracking attitude changes over policy implementation periods would reveal dynamic relationships between values, perceptions, and support [122]. Investigating policy sequencing effects would inform strategic policy implementation, addressing spillover effects in environmental behavior change [123]. This study has several important limitations. Our cross-sectional design precludes causal inferences about relation-

ships between psychological factors and policy support. Self-reported measures may suffer from social desirability bias, particularly regarding environmental attitudes [124]. The single-country Korean context limits generalizability across cultural and political systems. Brief scales (2–3 items) may inadequately capture complex constructs like guilt and efficacy, and we measured behavioral intentions rather than actual tax-paying behavior, creating potential intention-behavior gaps [122]. A significant limitation is our failure to measure participants’ political ideology and party affiliation. Since plastic taxation represents environmental policy with political implications, political orientations likely substantially influence support attitudes. Research demonstrates that political ideology strongly predicts environmental policy acceptance, with conservatives showing greater skepticism toward climate policies than liberals [102]. Political partisanship also affects how individuals process envi- ronmental information, potentially moderating relationships between psychological factors and policy support [24]. This study’s Korean cultural context significantly limits generalizability. Environmental values and policy preferences vary substantially across cultures [125]. Korean collectivistic values and hierarchical social structures may influence plastic tax acceptance differently than individualistic Western contexts [126]. Our findings specifically reflect Korean envi-

ronmental attitudes shaped by rapid industrialization experiences and Confucian value systems emphasizing collective responsibility [65]. Cross-cultural validation is essential before generalizing results to other contexts, particularly given documented cultural variations in environmental concern and policy support [17]. Finally, the relationships identified represent associations rather than causal effects, given our cross-sectional correla- tional design. Future research should employ causal research designs to test the directional relationships proposed in our theoretical framework. Supporting information S1 Appendix. (PDF) Author contributions Conceptualization: Seoyong Kim. Data curation: Seoyong Kim. Formal analysis: Miri Kim. Investigation: Miri Kim.

PLOS One | https://doi.org/10.1371/journal.pone.0337327 December 29, 2025 26 / 30 Methodology: Sehyeok Jeon. Visualization: Sehyeok Jeon. References 1. Department SR. Global plastics production from 1950 to 2021: Statista; 2023. Available from: https://www.statista.com/statistics/282732/ global-production-of-plastics-since-1950/ 2. Plastics B. The new coal: plastics and climate change. Beyond Plastics at Bennington College; 2021. 3. IUCN. Marine plastics: International Union for Conservation of Nature; 2023. Available from: https://www.iucn.org/resources/issues-briefs/ marine-plastics 4. Geyer R, Jambeck JR, Law KL. Production, use, and fate of all plastics ever made. Sci Adv. 2017;3(7):e1700782. https://doi.org/10.1126/ sciadv.1700782 PMID: 28776036 5. Jambeck JR, Geyer R, Wilcox C, Siegler TR, Perryman M, Andrady A, et al. Marine pollution. Plastic waste inputs from land into the ocean. Sci- ence. 2015;347(6223):768–71. https://doi.org/10.1126/science.1260352 PMID: 25678662 6. Lau WWY, Shiran Y, Bailey RM, Cook E, Stuchtey MR, Koskella J, et al. Evaluating scenarios toward zero plastic pollution. Science. 2020;369(6510):1455–61. https://doi.org/10.1126/science.aba9475 PMID: 32703909 7. Forum WE. The new plastics economy: rethinking the future of plastics. 2016. 8. Law CfIE. Plastic & climate: the hidden costs of a plastic planet. Washington (DC); 2019. 9. Union E. Council Decision (EU) 2019/665 of 15 April 2019 amending Decision 2014/335/EU on the system of own resources of the European Union. Official Journal of the European Union; 2019.

10. Rivers N, Shenstone-Harris S, Young N. Using nudges to reduce waste? The case of Toronto’s plastic bag levy. J Environ Manage. 2017;188:153– 62. https://doi.org/10.1016/j.jenvman.2016.12.009 PMID: 27978442 11. Homonoff T, Kao LS, Selman J, Seybolt C. The intended and unintended consequences of disposable bag regulation. 2021. 12. Taylor RL, Villas‐Boas SB. Bans vs. fees: disposable carryout bag policies and bag usage. Appl Econ Perspect Policy. 2015;38(2):351–72. https:// doi.org/10.1093/aepp/ppv025 13. Fischbach E, Sparks E, Hudson K, Lio S, Englebretson E. Consumer concern and willingness to pay for plastic alternatives in food service. Sus- tainability. 2022;14(10):5992. https://doi.org/10.3390/su14105992 14. Stern PC. New environmental theories: toward a coherent theory of environmentally significant behavior. J Soc Issues. 2000;56(3):407–24. https:// doi.org/10.1111/0022-4537.00175 15. Fairbrother M. Public opinion about climate policies: a review and call for more studies of what people want. PLOS Clim. 2022;1(5):e0000030. https://doi.org/10.1371/journal.pclm.0000030 16. Ajzen I. The theory of planned behavior. Organ behav Hum Decis Process. 1991;50(2):179–211. 17. Hornsey MJ, Harris EA, Bain PG, Fielding KS. Meta-analyses of the determinants and outcomes of belief in climate change. Nat Clim Change. 2016;6(6):622–6. https://doi.org/10.1038/nclimate2943 18. Bissing-Olson MJ, Fielding KS, Iyer A. Experiences of pride, not guilt, predict pro-environmental behavior when pro-environmental descriptive

norms are more positive. J Environ Psychol. 2016;45:145–53. https://doi.org/10.1016/j.jenvp.2016.01.001 19. van der Linden S, Maibach E, Leiserowitz A. Improving public engagement with climate change: five “best practice” insights from psychological science. Perspect Psychol Sci. 2015;10(6):758–63. https://doi.org/10.1177/1745691615598516 PMID: 26581732 20. Drews S, van den Bergh JCJM. What explains public support for climate policies? A review of empirical and experimental studies. Clim Policy. 2015;16(7):855–76. https://doi.org/10.1080/14693062.2015.1058240 21. Zheng J, Suh S. Strategies to reduce the global carbon footprint of plastics. Nat Clim Chang. 2019;9(5):374–8. https://doi.org/10.1038/ s41558-019-0459-z 22. Nielsen KS, Clayton S, Stern PC, Dietz T, Capstick S, Whitmarsh L. How psychology can help limit climate change. Am Psychol. 2021;76(1):130– 44. https://doi.org/10.1037/amp0000624 PMID: 32202817 23. Bamberg S, Möser G. Twenty years after Hines, Hungerford, and Tomera: a new meta-analysis of psycho-social determinants of pro-environmental behaviour. J Environ Psychol. 2007;27(1):14–25. https://doi.org/10.1016/j.jenvp.2006.12.002 24. Kahan DM, Peters E, Wittlin M, Slovic P, Ouellette LL, Braman D, et al. The polarizing impact of science literacy and numeracy on perceived cli- mate change risks. Nat Clim Change. 2012;2(10):732–5. https://doi.org/10.1038/nclimate1547 25. Rogers RW. A protection motivation theory of fear appeals and attitude change1. J Psychol. 1975;91(1):93–114. https://doi.org/10.1080/00223980. 1975.9915803 PMID: 28136248

26. Klöckner CA. A comprehensive model of the psychology of environmental behaviour—A meta-analysis. Glob Environ Change. 2013;23(5):1028– 38. https://doi.org/10.1016/j.gloenvcha.2013.05.014

PLOS One | https://doi.org/10.1371/journal.pone.0337327 December 29, 2025 27 / 30 27. Heidbreder LM, Bablok I, Drews S, Menzel C. Tackling the plastic problem: a review on perceptions, behaviors, and interventions. Sci Total Envi- ron. 2019;668:1077–93. https://doi.org/10.1016/j.scitotenv.2019.02.437 PMID: 31018449 28. Hart PS, Nisbet EC. Boomerang effects in science communication: how motivated reasoning and identity cues amplify opinion polarization about climate mitigation policies. Commun Res. 2012;39(6):701–23. 29. Schwarz N, Clore GL. Mood, misattribution, and judgments of well-being: informative and directive functions of affective states. J Pers Soc Psy- chol. 1983;45(3):513–23. https://doi.org/10.1037/0022-3514.45.3.513 30. Bandura A. Exercise of human agency through collective efficacy. Curr Dir Psychol Sci. 2000;9(3):75–8. https://doi.org/10.1111/1467-8721.00064 31. Chen M-F. Self-efficacy or collective efficacy within the cognitive theory of stress model: which more effectively explains people’s self-reported proenvironmental behavior? J Environ Psychol. 2015;42:66–75. https://doi.org/10.1016/j.jenvp.2015.02.002 32. Programme UNE. Turning off the Tap: how the world can end plastic pollution and create a circular economy. Nairobi; 2023. 33. WWF DA. No plastic in nature: assessing plastic ingestion from nature to people. Gland, Switzerland; 2019. 34. Rivers N, Schaufele B. Salience of carbon taxes in the gasoline market. J Environ Econ Manag. 2015;74:23–36. https://doi.org/10.1016/j. jeem.2015.07.002

35. Alpizar F, Carlsson F, Lanza G, Carney B, Daniels RC, Jaime M, et al. A framework for selecting and designing policies to reduce marine plastic pollution in developing countries. Environ Sci Policy. 2020;109:25–35. https://doi.org/10.1016/j.envsci.2020.04.007 36. Poortinga W, Pidgeon NF. Exploring the dimensionality of trust in risk regulation. Risk Anal. 2003;23(5):961–72. https://doi.org/10.1111/1539- 6924.00373 PMID: 12969411 37. Lee M, Kim H. COVID-19 pandemic and microplastic pollution. Nanomaterials (Basel). 2022;12(5):851. https://doi.org/10.3390/nano12050851 PMID: 35269339 38. Zhang C, Liu L, Xiao Q. The influence of Taoism on employee low-carbon behavior in China: the mediating role of perceived value and guanxi. Psychol Res Behav Manag. 2022;15:2169–81. https://doi.org/10.2147/PRBM.S371945 PMID: 35983021 39. Liu L, Zhang C. Linking environmental management accounting to green organisational behaviour: the mediating role of green human resource management. PLoS One. 2022;17(12):e0279568. https://doi.org/10.1371/journal.pone.0279568 PMID: 36576939 40. Zhang C, Ma X, Liu L. The effect of passion for outdoor activities on employee well-being using nature connectedness as the mediating variable and environmental identity as the moderating variable. Psychol Res Behav Manag. 2023;16:4883–96. https://doi.org/10.2147/PRBM.S436612 PMID: 38077165 41. Dai Q, Peng S, Guo Z, Zhang C, Dai Y, Hao W, et al. Place identity as a mediator between motivation and tourist loyalty in “red tourism”. PLoS

One. 2023;18(10):e0284574. https://doi.org/10.1371/journal.pone.0284574 PMID: 37889893 42. Jung Y. A study on the environment-friendly clothing consumption behavior depending on consumer value orientation and clothing benefits sought [Unpublished doctoral dissertation]. Pusan: Kyungsung University; 2007. 43. Fishbein M, Ajzen I. Belief, attitude, intention, and behavior: an introduction to theory and research; 1977. 44. Kim SLC. The study on negative effect of nuclear corruption scandal and the mechanism of trust. KJPA. 2014;23(3):131–59. 45. Renn O, Rohrmann B. Cross-cultural risk perception: a survey of empirical studies. Springer Science & Business Media; 2013. 46. Sjöberg L, Moen BE, Rundmo T. Explaining risk perception. an evaluation of the psychometric paradigm in risk perception research. 2004;10(2):665–72. 47. Dunlap RE. Lay perceptions of global risk: public views of global warming in cross-national context. Int Sociol. 1998;13(4):473–98. 48. Kempton W. How the public views climate change. Environment. 1997;39(9):12–21. https://doi.org/10.1080/00139159709604765 49. O’Connor RE, Bard RJ, Fisher A. Risk perceptions, general environmental beliefs, and willingness to address climate change. Risk Anal. 1999;19(3):461–71. https://doi.org/10.1111/j.1539-6924.1999.tb00421.x 50. Heilbroner RL, Ajzen I, Fishbein M, Thurow LC. Understanding attitudes and predicting social behavior. Prentice Hall; 1980. 51. Ajzen I. From intentions to actions: a theory of planned behavior. In: Action control: from cognition to behavior. Springer; 1985. p. 11–39. https://doi.

org/10.1007/978-3-642-69746-3_2 52. Sutton S. Predicting and explaining intentions and behavior: how well are we doing? J Appl Soc Pyschol. 1998;28(15):1317–38. https://doi. org/10.1111/j.1559-1816.1998.tb01679.x 53. Du M, Chai CS, Di W, Wang X. What affects adolescents’ willingness to maintain climate change action participation : an extended theory of planned behavior to explore the evidence from China. J Clean Prod. 2023;422:138589. https://doi.org/10.1016/j.jclepro.2023.138589 54. Zhang W, Luo B. Predicting consumer intention toward eco-friendly smart home services: extending the theory of planned behavior. Econ Change Restruct. 2022;56(5):3335–52. https://doi.org/10.1007/s10644-022-09477-2 55. Spence A, Poortinga W, Pidgeon N, Lorenzoni I. Public perceptions of energy choices: the influence of beliefs about climate change and the envi- ronment. Energy Environ. 2010;21(5):385–407. https://doi.org/10.1260/0958-305x.21.5.385 56. Park R, Kim S, Hwang H. Searching for successful condition about new energy governance and energy transition system: analyzing the role of personal value, energy preference, and political and economic factors in acceptance of energy pricing policy. Korean J Policy Anal Eval. 2019;29(4):25–56.

PLOS One | https://doi.org/10.1371/journal.pone.0337327 December 29, 2025 28 / 30 57. Mozumder P, Vásquez WF, Marathe A. Consumers’ preference for renewable energy in the southwest USA. Energy Econ. 2011;33(6):1119–26. https://doi.org/10.1016/j.eneco.2011.08.003 58. Kim S, Kim K. Beyond risk and benefit: heuristic effect of experienced affect on acceptance of nuclear power stations. IRPA. 2007;41(3):373–98. 59. Schwartz SH. Universals in the content and structure of values: theoretical advances and empirical tests in 20 countries. Adv Exp Soc Psychol. 1992;25:1–65. 60. Stern PC, Dietz T. The value basis of environmental concern. J Soc Issues. 1994;50(3):65–84. https://doi.org/10.1111/j.1540-4560.1994.tb02420.x 61. Jang H-W, Cho M. Relationship between personal values and intentions to purchase plant-based meat alternatives: application of the dual concern theory. Int J Environ Res Public Health. 2022;19(14):8673. https://doi.org/10.3390/ijerph19148673 PMID: 35886523 62. Douglas M, Wildavsky A. Risk and culture: an essay on the selection of technological and environmental dangers. Univ of California Press; 1983. 63. Douglas M. Natural symbols. Routledge; 2002. 64. Inglehart R. The silent revolution in Europe: intergenerational change in post-industrial societies. Am Polit Sci Rev. 1971;65(4):991–1017. https:// doi.org/10.2307/1953494 65. Kim SKS. Analyzing the universality and particularity of determinant structure of environmentalism: comparative study of 32 countries and policy implication. Korea Policy Study Rev. 2014;23(4):335–71.

66. M K. An empirical study on the influential factors and political effects of materialism and postmaterialism. Korean J Local Gov Adm Stud. 2008;22(1):65–82. 67. Gelissen J. Explaining popular support for environmental protection: a multilevel analysis of 50 nations. Environ Behav. 2007;39(3):392–415. 68. Hurst M, Dittmar H, Bond R, Kasser T. The relationship between materialistic values and environmental attitudes and behaviors: a meta-analysis. J Environ Psychol. 2013;36:257–69. https://doi.org/10.1016/j.jenvp.2013.09.003 69. Ku L, Zaroff C. How far is your money from your mouth? The effects of intrinsic relative to extrinsic values on willingness to pay and protect the environment. J Environ Psychol. 2014;40:472–83. https://doi.org/10.1016/j.jenvp.2014.10.008 70. Kilbourne W, Pickett G. How materialism affects environmental beliefs, concern, and environmentally responsible behavior. J Bus Res. 2008;61(9):885–93. https://doi.org/10.1016/j.jbusres.2007.09.016 71. Slovic P, Fischhoff B, Lichtenstein S. Perceived risk: psychological factors and social implications. Proc R Soc Lond A Math Phys Sci. 1981;376(1764):17–34. 72. Visschers VHM, Siegrist M. How a nuclear power plant accident influences acceptance of nuclear power: results of a longitudinal study before and after the Fukushima disaster. Risk Anal. 2013;33(2):333–47. https://doi.org/10.1111/j.1539-6924.2012.01861.x PMID: 22762151 73. Park E, Ohm JY. Factors influencing the public intention to use renewable energy technologies in South Korea: effects of the Fukushima nuclear

accident. Energy Policy. 2014;65:198–211. https://doi.org/10.1016/j.enpol.2013.10.037 74. Kim S, Kim S. Analyzing the determinants of concern about and responses to climate change. Kor J Pub Ad. 2016;54:179–206. 75. Park C-h, Kim S-y. The role of knowledge in acceptance of nuclear power: a focus on objective and subjective knowledge. KJPA. 2015;53(3):117–50. 76. Langer K, Wooliscroft B. The acceptance of wind energy in a leading country and low deployment country of wind energy: a cross-national compar- ative analysis. Renew Energy Focus. 2018;27:111–9. https://doi.org/10.1016/j.ref.2018.09.003 77. Kollmuss A, Agyeman J. Mind the gap: why do people act environmentally and what are the barriers to pro-environmental behavior? Environ Educ Res. 2002;8(3):239–60. https://doi.org/10.1080/13504620220145401 78. Gifford R, Nilsson A. Personal and social factors that influence pro-environmental concern and behaviour: a review. Int J Psychol. 2014;49(3):141– 57. https://doi.org/10.1002/ijop.12034 PMID: 24821503 79. Earle TC, Siegrist M, Gutscher H. Trust in risk management: uncertainty and scepticism in the public mind. Earthscan; 2010. 80. Siegrist M. The influence of trust and perceptions of risks and benefits on the acceptance of gene technology. Risk Anal. 2000;20(2):195–203. https://doi.org/10.1111/0272-4332.202020 PMID: 10859780 81. Jungermann H, Pfister H, Fischer K. Credibility, information preferences, and information interests. Risk Anal. 1996;16(2):251–61. https://doi. org/10.1111/j.1539-6924.1996.tb01455.x

82. Kim S, Sunhee K. Analyzing the moderation effect of local residents’ perceived benefit on the acceptance of nuclear power energy. Public Policy Rev. 2017;31(4):215–42. https://doi.org/10.17327/IPPA.2017.31.4.008 83. Slovic P, Flynn JH, Layman M. Perceived risk, trust, and the politics of nuclear waste. Science. 1991;254(5038):1603–7. https://doi.org/10.1126/ science.254.5038.1603 PMID: 17782210 84. Huijts NMA, Molin EJE, Steg L. Psychological factors influencing sustainable energy technology acceptance: a review-based comprehensive framework. Renew Sustain Energy Rev. 2012;16(1):525–31. https://doi.org/10.1016/j.rser.2011.08.018 85. Lim CK, Kim S. The study on negative effect of nuclear corruption scandal and the mechanism of trust. Korea Public Admin J. 2014;23(3):131–59. 86. Lomborg B. The skeptical environmentalist. Cambridge: Cambridge University Press; 2001.