This investigation used the theory of planned behavior (TPB) as the overarching theoretical framework and incorporated a number of attitudinal motivations and background variables (e.g., future orientation, cultural worldviews, and belief certainty) that recently emerged in the climate change literature. Results from a survey of 567 U.S. consumers showed that attitudes and collective efficacy were two main considerations in one’s support for climate change policies. Attitudes were predicted by the utilitarian motivation (i.e., perceived effectiveness of climate change actions and policy), moral motivations, and collective efficacy. Further analysis revealed a number of significant relationships between background variables and attitudes and efficacy, which were not previously theorized in the TPB. Practical and theoretical implications are discussed. Climate change, as the result of collective human action in producing greenhouse gases, may bring out catastrophic consequences (Intergovernmental Panel on Climate Change [IPCC], 2015), including temperature increase, extreme weather patterns, rise of sea levels, and destruction of biodiversity of the planet. Although policy change is essential in ensuring full compliance from individuals and various industries, policy change in the United States is often met with gridlock, partly because of the perceived lack of strong support from the public (Shwom, Bidwell, Dan, & Dietz, 2010). Because a good understanding of the public’s reasons for supporting climate change-related policies can help better mobilize the public (Atkin & Freimuth, 2001; Shwom et al., 2010), the present research will examine whether various motivations, personality variables, and cultural worldviews predict the American public’s policy support. This investigation uses the theory of planned behavior (TPB) (Fishbein & Ajzen, 2010) as the overarching theoretical framework, coupled with the attitude functional theory (Katz, 1960; see figures in the publisher’s online depository). It will incorporate a number of variables that have been recently discussed in the climate change literature (Adger et al., 2009; Kahan, 2012) and, thus, contribute to a growing amount of survey-based research that focused mainly on the role of climate change knowledge and beliefs on policy support (Krosnick, Holbrook, Lowe, & Visser, 2006; McCright, Dunlap, & Xiao, 2013). The Theory of Planned Behavior The TPB (Fishbein & Ajzen, 2010) states that individuals form intentions before performing a behavior and that intentions are predicted by attitudes (i.e., favorable or unfavorable evaluation of a behavior or an issue), norms (i.e., perceived pressure from important others or perceived popularity of a behavior among others), and efficacy (i.e., one’s confidence in performing a behavior). Previous meta-analyses and narrative reviews revealed ample evidence to support these relationships (Armitage & Conner, 2001; Fishbein & Ajzen, 2010). Efficacy should be conceptualized at the same level of specificity as is the behavior under investigation. Because many measures to mitigate climate change require collective action (Adger et al., 2009; IPCC, 2015) and the effects of individual action are limited without collective action, I use collective efficacy in this research. Collective efficacy is a group’s joint capabilities to carry out a course of action and achieve desirable outcomes (Bandura, 2009). Consistent with the TPB, I propose Hypothesis 1: H1: Individuals with (a) higher attitudes, (b) higher norms, and (c) higher collective efficacy are more likely to support policies to mitigate climate change. Predictors of Attitudes: Attitude Functions and Collective Efficacy Because attitudes are defined as the general evaluation of a behavior and are not specific (O’Keefe, 2002; Wang, 2013), I used two motivations from the attitude functional theory (Katz, 1960) to understand attitudes. The functional theory states that individuals hold attitudes to serve a number of functions (i.e., motivations; Katz, 1960), including utilitarian and value-expressive motivations. This approach provides a limited number of theory-based motivations and is parsimonious. Although parsimonious, it includes two major issues that have been recently discussed in the climate change literature, particularly perceived effectiveness and moral obligations. First, the utilitarian function is related to the basic aspects of a product or an issue, for example, the effectiveness of aspirin. IPCC (2015) stated that substantial cuts in greenhouse gas emissions can limit the amount of temperature increase in the second half of the twenty-first century and beyond and can effectively mitigate the impact of climate change. On the other hand, delay in mitigating climate change may lead to higher costs in the long term. If the general public believes that climate policies and measures are effective, they hold a utilitarian motivation. The second motivation is related to the expression of one’s values. Presently in the United States, the effects are less obvious or severe compared with those in many other parts of the world (e.g., Africa or the retreat of glaciers; IPCC, 2015). Furthermore, more drastic consequences will be experienced by future generations and the nonpersonal environments. Thus, the fight against climate change can be considered as a moral issue with a less immediate impact on the U.S. participants. I then hypothesize the following: H2: Individuals with (a) a higher utilitarian motivation (vs. lower) and (b) a higher value-expressive motivation (vs. lower) are more likely to have more favorable attitudes toward actions to mitigate climate change. According to Bandura (2009), those who have more confidence in their abilities to perform a behavior usually perform the behavior better (i.e., a better outcome). Because one’s attitudes toward a behavior are based on outcome expectations, collective efficacy should predict attitudes as well. The difference between the utilitarian function and collective efficacy is that the former is the expected effectiveness of climate change policies, whereas the latter focuses on perceived collective abilities and confidence in achieving such an outcome. H3: Individuals with higher collective efficacy (vs. lower) are more likely to have more favorable attitudes toward actions to mitigate climate change. Future Orientation and Communitarianism Recent environmental literature underscores the importance of one’s tendency to consider future consequences (Enzler, 2015; Strathman, Gleicher, Boninger, & Edwards, 1994) and cultural worldviews (Kahan, 2012). Because future-oriented individuals are more likely to consider the long-term consequences of climate change, they are more likely to develop environmental concerns and perform related behaviors. In general, the consequences of climate change have yet to be observed or directly influence many in the world. For those who have not yet experienced the effects of climate change (e.g., most people in the United States), their primary motivation for alleviating climate change should be future-oriented and is related to the concern for others, future generations, and the environment. Furthermore, a longer time frame will make it possible for climate change actions to be effective. H4: Individuals who are future-oriented are more likely to consider that measures to mitigate climate change will be effective (i.e., utilitarian function) and that it is morally responsible to perform behaviors to alleviate climate change (i.e., value-expressive function). Research has shown that when individuals consider distant future events (vs. near future), they are more optimistic and have more confidence (Gilovich, Kerr, & Medvec, 1993; Taylor & Shepperd, 1998). Construal level theory (Trope & Liberman, 2010) states that when individuals consider a future event (vs. an immediate event), they are more likely to engage in high-level construals. High-level construals are characterized by thinking about one’s own dispositions and promotional goals. Furthermore, effective control (i.e., efficacy) requires knowledge and skills that are acquired through a long period of time (Bandura, 2001). Increased temporal distance (i.e., focusing on the distant instead of the near future) offers individuals and communities more opportunities to achieve desired outcomes and, thus, enhances individuals’ collective efficacy. The collective action to mitigate climate change will not see immediate effects and will take many decades to manifest. Those who consider future consequences (vs. not) will be more likely to think that their efforts to reduce climate change would be effective. H5: Individuals with a higher level of future orientation are more likely to have higher collective efficacy. Individualism/communitarianism is the extent to which individuals believe whether they should pursue their own needs and fend for themselves without collective efforts (Rayner, 1992). Douglas and Wildavsky (1982) argued that individualistic people tend to dismiss claims of environmental risk and not to support environmental policies because these risks or policies may restrict commerce or behaviors that they enjoy, for example, driving less or setting higher prices for their entertainment options. On the other hand, those who are high on communitarianism dislike commerce and are more likely to support policies to restrict commerce and promote behaviors to help the majority. By definition, people with a communitarian worldview believe in interacting and collaborating with others. As such, they (vs. individualistic) are more likely to hold high confidence in their collective ability to achieve goals. H6: Individuals with higher communitarian cultural worldviews are more likely to (a) have higher utilitarian motivations, (b) have higher collective efficacy, and (c) support policies to alleviate climate change. Finally, based on previous research (Kiley, 2015; Lorenzoni, Nicholson-Cole, & Whitmarsh, 2007), the following analyses control for belief certainty and party affiliation, which may influence one’s information seeking and understanding of climate change. Method This analysis was based on part of a larger data set collected in November 2013. An online panel of 2,629 U.S. participants was purchased from Qualtrics. Qualtrics provided a final data set of 572 complete responses, after deleting 115 participants who failed an attention-filter question (i.e., please select “agree” for this question) and a small number of participants who completed the questionnaire in <5 min (one third of the average completion time) on the survey. The response rate was 21.8%. Finally, five cases were not included when the LISREL program converted the raw data for the final analysis (n = 567). The final sample included 49.5% males. The racial breakdown of the sample was as follows: 3.3% Asian, 8.6% African Americans, 4.7% Hispanics, 80.9% White, and 2.4% “other racial background.” The average age for the sample was 49.1 years (SD = 13.8). Questionnaire Responses for the following scales ranged from 1 (strongly disagree) to 7 (strongly agree), unless noted otherwise. Future orientation (α = .87) was based on three future-related items adapted from Strathman et al. (1994): “I try to influence future outcomes through my day-to-day activities,” “I often engage in a particular behavior to achieve outcomes that may not result for many years,” and “I’m willing to sacrifice my immediate happiness in order to achieve long-term outcomes.” Two negatively worded items (recoded) loaded on a different dimension and were deleted. Communitarian worldviews were initially measured by five items from Kahan (2012). Because Kahan’s questions are often double-barreled and involve multiple dimensions, these items revised and analyzed through confirmatory factor analysis. After deleting two society-related items that loaded on a different dimension, we used the following (α = .88): “The government should do more to advance society’s goals,” “The government should guide individuals to make choices good for society,” and “The government should help people when they are in need.” For the utilitarian function (α = .90), participants were presented “some people propose the following actions as ways to reduce greenhouse gas emission or ways to mitigate global warming. However effective do you think they are?” followed by “use reasonably less energy (e.g., heat or air conditioning),” “use energy efficient appliances or products (e.g., car or light bulb),” “drive less if possible,” and “support laws and regulations on reducing carbon dioxide for businesses.” Responses ranged from 1 (very ineffective) to 7 (very effective). The value-expressive motivation was measured by four items (α = .91): “My taking actions to alleviate global warming shows I am a moral person,” “… shows I care about the environment,” “… shows I am a responsible person,” and “… shows I care about human survival.” Attitudes (α = .93) were adapted from Conner and Sparks (1996): “Taking actions against global warming is wise/good/necessary.” Questions related to these actions were asked earlier in the questionnaire (e.g., reduce energy use and policy support). Descriptive norms were measured by asking the participants to respond to the following items (α = .90) when they consider actions to reduce global warming: “Most people in my community do so,” “most people in my country do so,” and “my family members do so.” Collective efficacy was measured by three items (α = .93). “My action can make a difference,” “People in the U.S. can reduce the impact of global warming,” and “Humans can make an impact on reducing global warming.” Policy support was measured by 4 times (α = .94), for example, “I will support a national policy to alleviate global warming,” and “I will support an international treaty to reduce global warming.” Belief certainty that climate change was happening was measured by three items (α = .88): “I think global warming is happening,” “I have already noticed signs of global warming,” and “The weather patterns have changed since I was a child.” A number of demographic variables (e.g., age and gender) were also measured and were included in the initial data analysis. Party affiliation was coded as follows: Democrat (1), Independent (2), and Republican (3). Results Means, SDs, and Pearson correlations are provided in the publisher’s online depository. We conducted a two-step structural equation modeling analysis. In the first step, confirmatory factor analysis was conducted to examine the construct validity of the measurement items (i.e., examine whether the questionnaire items loaded on their respective factors). To improve the model fit, the error covariance of three pairs of indicators (between two certainty questions, between two utilitarian questions, and between two collective efficacy questions) was set free. The final scale items were listed in the Method section. Confirmatory factor analysis showed that the model fit the data well: Satorra–Bentler Scaled (S-B) χ2 (366, N = 567) = 847.2, p < .001, root mean square error of approximation (RMSEA) = .048, 90% confidence interval (CI) of RMSEA: [0.044, .052], and comparative fit index (CFI) = .99. In the second step, a structural model was evaluated. Party affiliation was used as a single indicator with fixed error variance. Two nonsignificant demographic variables (i.e., gender and race) were dropped from the model after the initial analysis. Satorra–Bentler χ2 (414, N = 567) = 1,049.3, p < .001, RMSEA = .042, 90% CI of RMSEA [.048, .056], and CFI = .99. Figure 1 shows the standardized path coefficients among various variables. Figure 1 View largeDownload slide Standardized path coefficients for factors predicting U.S. consumers intentions to support policies to mitigate global warming. All paths using solid lines were significant (p < .05). Satorra-Bentler X2 (414, N = 567) = 1049.3, p <.001, root mean square error of approximation (RMSEA) = .042, 90% CI of RMSEA [.048, .056], comparative fit index = .99. Standardized factor loadings for measurement items ranged from .51 to .97 and are not shown in the figure Figure 1 View largeDownload slide Standardized path coefficients for factors predicting U.S. consumers intentions to support policies to mitigate global warming. All paths using solid lines were significant (p < .05). Satorra-Bentler X2 (414, N = 567) = 1049.3, p <.001, root mean square error of approximation (RMSEA) = .042, 90% CI of RMSEA [.048, .056], comparative fit index = .99. Standardized factor loadings for measurement items ranged from .51 to .97 and are not shown in the figure For H1, Figure 1 showed that one’s intention to support climate change policies was predicted by attitudes (β = .35, p < .001), descriptive norms (β = .09, p = .040), and collective efficacy (β = .35, p < .001). For H2, individuals’ utilitarian motivation (β = .13, p = .027) and value-expressive, moral motivation (β = .37, p < .001) predicted their attitudes toward climate change mitigation actions. Table 1 Means, SDs, and Pearson Correlations for the Variables Based on Observed Variable Scores (N = 567) 1 2 3 4 5 6 7 8 9 10 1. Party affiliation (1 = Republican, 3 = Democratic) – 2. Communitarianism −.30 – 3. Future orientation −.12 .45 – 4. Climate change belief certainty −.31 .59 .43 – 5. Utilitarian motivation (effectiveness of climate measures/behaviors) −.29 .53 .42 .60 – 6. Value-expressive motivation −.21 .60 .46 .58 .60 – 7. Collective efficacy −.26 .62 .54 .66 .70 .72 – 8. Attitudes −.26 .60 .52 .69 .66 .73 .81 – 9. Descriptive norms −.13 .44 .45 .35 .37 .48 .47 .40 – 10. Policy support −.27 .67 .59 .69 .66 .70 .79 .78 .47 – Means 1.85 4.53 4.63 5.33 9.31 4.98 5.12 5.56 4.08 4.75 SDs 0.73 1.41 1.27 1.43 3.86 1.30 1.40 1.28 1.35 1.57 1 2 3 4 5 6 7 8 9 10 1. Party affiliation (1 = Republican, 3 = Democratic) – 2. Communitarianism −.30 – 3. Future orientation −.12 .45 – 4. Climate change belief certainty −.31 .59 .43 – 5. Utilitarian motivation (effectiveness of climate measures/behaviors) −.29 .53 .42 .60 – 6. Value-expressive motivation −.21 .60 .46 .58 .60 – 7. Collective efficacy −.26 .62 .54 .66 .70 .72 – 8. Attitudes −.26 .60 .52 .69 .66 .73 .81 – 9. Descriptive norms −.13 .44 .45 .35 .37 .48 .47 .40 – 10. Policy support −.27 .67 .59 .69 .66 .70 .79 .78 .47 – Means 1.85 4.53 4.63 5.33 9.31 4.98 5.12 5.56 4.08 4.75 SDs 0.73 1.41 1.27 1.43 3.86 1.30 1.40 1.28 1.35 1.57 Note: All correlations were significant (p < .01). Covariance or correlation matrix of the measurement items is available from the author. Table 1 Means, SDs, and Pearson Correlations for the Variables Based on Observed Variable Scores (N = 567) 1 2 3 4 5 6 7 8 9 10 1. Party affiliation (1 = Republican, 3 = Democratic) – 2. Communitarianism −.30 – 3. Future orientation −.12 .45 – 4. Climate change belief certainty −.31 .59 .43 – 5. Utilitarian motivation (effectiveness of climate measures/behaviors) −.29 .53 .42 .60 – 6. Value-expressive motivation −.21 .60 .46 .58 .60 – 7. Collective efficacy −.26 .62 .54 .66 .70 .72 – 8. Attitudes −.26 .60 .52 .69 .66 .73 .81 – 9. Descriptive norms −.13 .44 .45 .35 .37 .48 .47 .40 – 10. Policy support −.27 .67 .59 .69 .66 .70 .79 .78 .47 – Means 1.85 4.53 4.63 5.33 9.31 4.98 5.12 5.56 4.08 4.75 SDs 0.73 1.41 1.27 1.43 3.86 1.30 1.40 1.28 1.35 1.57 1 2 3 4 5 6 7 8 9 10 1. Party affiliation (1 = Republican, 3 = Democratic) – 2. Communitarianism −.30 – 3. Future orientation −.12 .45 – 4. Climate change belief certainty −.31 .59 .43 – 5. Utilitarian motivation (effectiveness of climate measures/behaviors) −.29 .53 .42 .60 – 6. Value-expressive motivation −.21 .60 .46 .58 .60 – 7. Collective efficacy −.26 .62 .54 .66 .70 .72 – 8. Attitudes −.26 .60 .52 .69 .66 .73 .81 – 9. Descriptive norms −.13 .44 .45 .35 .37 .48 .47 .40 – 10. Policy support −.27 .67 .59 .69 .66 .70 .79 .78 .47 – Means 1.85 4.53 4.63 5.33 9.31 4.98 5.12 5.56 4.08 4.75 SDs 0.73 1.41 1.27 1.43 3.86 1.30 1.40 1.28 1.35 1.57 Note: All correlations were significant (p < .01). Covariance or correlation matrix of the measurement items is available from the author. For H3, collective efficacy was a strong predictor of one’s attitudes (β = .63, p < .001). For H4, those who were future-oriented were more likely to agree that actions to mitigate climate change were effective (β = .26, p = .023) and that it was morally right to support behaviors and policies to mitigate climate change (β = .37, p = .003). For H5, future-oriented individuals (vs. not) were also more likely to have higher collective efficacy (β = .23, p = .003). For H6, individuals holding a higher communitarian worldview were more likely to perceive actions to mitigate climate change to be effective (β = .27, p < .001), had higher collective efficacy to mitigate climate change (β = .58, p < .001), and were more likely to support climate change-related policies (β = .21, p < .001). Finally, party affiliation predicted climate change belief certainty (β = −.37, p < .001), showing that Republicans were less likely to believe that climate change was happening, whereas Democrats were the more likely to believe so. Belief certainty was positively related to perceived effectiveness of climate change measures and policies (β = .42, p < .001) and the moral aspect of climate change (β = .55, p < .001). Discussion Theoretical Discussion Consistent with the TPB predictions, one’s intentions to support policies to mitigate climate change were predicted by attitudes, collective efficacy, and descriptive norms. In general, norms are the weakest predictor of intentions among the three (Armitage & Conner, 2001). In the case of policy support, descriptive norms are a relatively weak predictor (β = .09) compared with attitudes and collective efficacy. This indicates that the perceptions of whether other people perform behaviors to mitigate climate change only marginally guide the U.S. public’s policy support. Instead, their attitudes toward adopting behaviors and policies to alleviate climate change and their perceptions of collective efficacy had much larger correlations with their behavioral intentions. To better understand the predictors of attitudes, we incorporated the utilitarian and value-expressive (moral) motivations from attitude functional theory (Katz, 1960). These two motivations closely captured two important considerations in the climate change literature (IPCC, 2015). Results show that the utilitarian motivation was a significant predictor of attitudes, but it was not as important as the moral aspect of taking actions against climate change. Individuals’ attitudes toward adopting policies against climate change are also predicted by their perceptions of collective efficacy. Klandermans (2004) found that individuals participate in social or political movements if their action and participation are effective and if they can align themselves with certain groups or derive meaning from their participation. Furthermore, the influence of collective efficacy on intentions was mediated by attitudes, indicating that the role of efficacy is more complicated than previously specified in the TPB. We did not include an ego-defensive motivation in the final analysis because our measure showed a low reliability and did not predict attitudes. The ego-defensive function refers to whether supporting climate change policies may enhance one’s social status or make one look weird or obnoxious to others because they are different in their stance on climate change. Future research might need to better conceptualize this motivation. Fishbein and Ajzen (2010) did not specify the relationships between background variables (e.g., belief certainty and communitarianism) and the attitudinal, normative, and efficacy beliefs because the number of background variables (and beliefs) is many. We argue that if we incorporate attitudinal functions instead of many beliefs, we can provide parsimonious, theory-based predictions and thus extend the TPB. For example, consistent with the theorizing in cultural worldviews (Kahan, 2012), participants who held stronger communitarian worldviews (vs. lower) had higher perceptions of the effectiveness of climate change policies and measures (i.e., utilitarian motivation) and had stronger value-expressive motivations. Practical Implications Future orientation and cultural worldviews can provide readers with a more detailed understanding of climate change attitudes and policy support. However, these variables are not open to change in a short time frame. Public educators and policymakers may consider them as a way to segment the target audience and to match message appeals with them. For example, for future-oriented individuals (vs. present-oriented), it might be easier to persuade them by using appeals related to future consequences or collective efficacy. For present-oriented individuals, more efforts or other message appeals may enhance their perceptions of efficacy and moral obligations, which should be dealt with in future studies. On the other hand, social cognitive variables (e.g., motivations, attitudes, and efficacy) are more open to change. Although participants’ cognitions are partially influenced by personalities or cultural worldviews, they can also be shaped by various media (Morgan, Shanahan, & Signorielli, 2009; Nelkin, 1995). It is encouraging to observe that the media have recently started to address the moral aspect of climate change. Feinberg and Willer (2013) found that major newspapers in the United States discussed moral concerns related to the environment and more frequently mentioned harm and care than other moral aspects (e.g., fairness). A growing amount of literature (IPCC, 2015) has also started to address the moral aspects of climate change. In “An Inconvenient Truth,” Al Gore framed the fight against climate change as a moral issue. Similarly, IPCC report (2015) discussed the effectiveness of various measures in mitigating climate change. Regarding collective efficacy, it is important to stress in the media how humans can collectively make an impact on mitigating climate change, instead of stressing how useless an individual’s efforts can be. Recent research (Lewandowsky, Gignac, & Vaughan, 2013) has shown that accepting scientific consensus, a concept similar to belief certainty, leads participants to accept various beliefs in other domains. Lewandowsky et al. state that accepting scientific consensus will lead to further elaboration on related content. It is assumed that further elaboration will be based on various sources from the media or from one’s own personal experience. If further elaboration is based on erroneous information, we should not observe a positive relationship between belief certainty and correct motivations. Although correlational in nature, the present results were encouraging and showed that belief certainty was related to the utilitarian and moral motivations measured by items consistent with the position advocated by IPCC (2015) and Natural Resources Defense Council (2016). This indicates that we might need to emphasize the scientific consensus on climate change and present correct information in the media or through other information channels (e.g., education). Limitations and Conclusion By incorporating a number of variables that recently emerged from the climate change literature, I provided a detailed analysis of the factors that predicted the American public’s support for climate change policies. Because this analysis was based on a cross-sectional survey, readers cannot infer causal relationships among the variables. Reverse causality, especially among those that do not involve demographic or personality variables, is possible. Additional research on the factors that predict other climate change behaviors and intentions is also important (e.g., personal behaviors to use less energy). Future research should also measure the actual behavior. Readers should avoid generalizing the results beyond the present sample or the online population because online samples are not probability-based samples. Future research should replicate this analysis using a more representative sample and in other nations. Supplementary Data Supplementary Data are available at IJPOR online. Xiao Wang (PhD, Florida State University) is an associate professor of communication. His research interests include health and environmental communication, persuasion, intercultural communication, and big data. References Adger W. N., Dessai S., Goulden M., Hulme M., Lorenzoni I., Nelson D. R.,, Wreford A. ( 2009). 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International Journal of Public Opinion Research – Oxford University Press
Published: Feb 27, 2017
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“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud