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Article

Exploring Citizens’ Behavior to Promote Environmental Sustainability: The Role of Information Overload and Urban Sustainable Policies

by
Paola Briganti
1,
Concetta Metallo
2,*,
Maria Margherita Pagliuca
3 and
Luisa Varriale
4
1
Department of Sport Sciences and Well-Being, University of Naples ‘Parthenope’, 40 Medina Street, 80133 Naples, Italy
2
Department of Sciences and Technology, University of Naples ‘Parthenope’, Centro Direzionale–Isola C4, 80143 Naples, Italy
3
Department of Management Studies and Quantitative Methods, University of Naples ‘Parthenope’, Palazzo Pacanowski 13 Generale Parisi Street, 80132 Naples, Italy
4
Department of Economics, Law, Cybersecurity, and Sports Sciences, University of Naples ‘Parthenope’, Guglielmo Pepe Rione Gescal Street, 80035 Nola, Italy
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(5), 4272; https://doi.org/10.3390/su15054272
Submission received: 6 December 2022 / Revised: 10 February 2023 / Accepted: 20 February 2023 / Published: 27 February 2023
(This article belongs to the Section Sustainable Management)
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Abstract

:
This study aims to provide a comprehensive framework for understanding citizens’ intentions to engage in environmentally sustainable behavior, thus making cities more sustainable. This article investigates environmentally sustainable behavior by adopting the Theory of Reasoned Action (TRA). Using Partial Least Square Path Modeling (PLS-PM), an analysis of survey data from 224 respondents in Italy revealed the salient role of attitudes, subjective norms, intentions, and urban sustainable policies in urban sustainable behavior. Our findings have important implications for theory and practice in this new area of inquiry.

1. Introduction

Environmental sustainability represents an issue of global interest for scholars and practitioners. In 2015, in order to implement sustainable development, the United Nations (UN) General Assembly launched the 2030 Agenda for Sustainable Development (UN Agenda) “as a universal call to action to end poverty, protect the planet, and ensure that by 2030 all people enjoy peace and prosperity” [1] (p. 1). The UN Agenda 2030 introduces 17 sustainable development goals (SDGs) and calls upon all governments and private businesses to support the achievement of the specified SDGs [2].
Cities (known as human settlements in the UN Agenda 2030) and urban developments are included within the same UN Agenda 2030 through SDG 11, “make cities and human settlements inclusive, safe, resilient and sustainable” (https://sdgs.un.org/topics/sustainable-cities-and-human-settlements (accessed on 11 May 2022)). Therefore, the involvement of local governments seems to be relevant for the implementation of SDGs and for SDG 11 to contribute to the sustainable development of cities. Citizens can play a central role in the SDG implementation process, as noted by the European Green Deal, which states that “citizens will be the driving force behind a transition to sustainability” [3]. Thus, understanding how citizens make decisions about the adoption of environmentally sustainable behaviors is crucial [4].
The literature agrees with the need to investigate and develop managerial tools, frameworks, or drivers to better understand the engagement of citizens in contributing to environmental sustainability and, specifically, to the SDGs [5,6]. With reference to this issue, the focus on individual behavior continues to have considerable relevance, as well as the need to understand ways to motivate urban sustainable behavior [7,8]. Thus, relevant research usually investigates the application of behavioral psychological theory in the domain of environmental science to understand and manage individual behavior for improving social and environmental sustainability [5,9,10]. Much research on sustainable behavior draws from the Theory of Reasoned Action (TRA), identifying the factors underlying individuals’ cognition, attitudes, and intentions towards these behaviors [11,12]. TRA identifies the antecedents of behavior, thereby examining the relations among beliefs, attitudes, and intentions to perform the behavior [13,14,15]. The main assumption of the TRA is that social behavior, both reasoned and spontaneous, always follows the information and beliefs possessed by people regarding the behavior considered, where these beliefs guide the intention to perform or not perform a certain behavior. According to the TRA, attitudes towards both behaviors and subjective norms impact the intention to perform the behavior. Indeed, within this framework, these two variables, attitudes and subjective norms, represent the additive function of behavioral intention, which largely determines actual behavior, where attitudes can have a positive or negative evaluation of performing a behavior, and subjective norms correspond to the perceived influences from others [16]. In this direction, individuals present a stronger intention to perform a specific behavior in cases of increasing attitudes and subjective norms. Such beliefs are named behavioral beliefs, where individuals tend to perform specific behaviors if they evaluate those behaviors positively. Therefore, attitude towards behavior (ATT) is a person’s positive or negative feeling associating with performing a specific behavior (behavioral beliefs). In other words, a person will hold a favorable attitude towards a given behavior if he or she believes that performing this behavior will lead to predominantly positive outcomes. On the other hand, if the individual believes that the behavior will lead to mostly negative outcomes, then he or she will form an unfavorable attitude towards that behavior. In summary, attitude represents an individual’s important beliefs as to whether the outcome of his or her behavior will be positive or negative [16]. Subjective norms (SN) are a function of an individual’s beliefs that reference others’ (influential individuals or groups) thoughts that he or she should or should not engage in a given behavior, coupled with the individual’s willingness or motivation to comply with these external perceptions. Thus, SN are conceived as a function of beliefs that individuals approve or disapprove of the behavior, where normative beliefs represent the underlined beliefs of subjective norms. Otherwise, the influence of other people, which leads individuals to conform to be liked and accepted by others, consists of normative social influence, which places high pressure on individuals to comply with their group’s social norms, thus affecting their behavior. Indeed, everyone tends to perform a behavior considered and perceived to be important by others, such as close friends, parents, physicians, etc. This phenomenon occurs because individuals tend to perform a specific behavior if most people who are important to them would approve or disapprove of it [16]. Intention is the likelihood that a person will engage in a specific behavior and is the best predictor of behavior. Hence, to change a specific behavior, one must first change the intention to perform that behavior. Thus, according to the TRA, intention is the most immediate and important predictor of behavior.
Usually, the TRA has been used as a theoretical framework to understand behavior in environmental studies and work on sustainable behavior [17,18,19,20,21]. Specifically, numerous studies have used the TRA model to predict green behavior, with a focus on environmental attitudes toward green purchasing behavior [20], green textile and apparel consumption [22], consumer’s intentions to stay at green hotels [23], and purchasing energy-efficient products [24]. Additionally, most literature on environmental behavior has established the relevance of intentions as predictors of behavior [25]. The literature concerning green consumer behavior has highlighted the importance of TRA and its extended forms to explore their relative superiority in predicting consumers’ green product purchasing [20]. Mishra and colleagues [19] investigated behavior toward the adoption of green information technology by applying TRA among IT professionals, showing that behavioral intention positively influences actual behavior. Nadlifatin et al. [26] analyzed citizens’ behavioral intentions regarding ecolabel product usage considering two additional factors, perceived authority support and perceived environmental concern, to assess ecolabel usage from citizens’ perspectives.
TRA is widely accepted and can provide the theoretical basis for conceptualizing citizens’ intentions towards urban sustainable behavior. However, the factors that influence individual behavior, particularly from a sustainability or environmental perspective, are numerous and complex [27,28,29]. Consequently, most scholars have considered frameworks with integrated factors, extended factors, and control variables to conduct empirical research in environmental science and the related sustainability fields [5,20,26,30,31]. In addition to TRA constructs, some scholars [8,32,33] have proposed that environmental information sharing could be an important foundation for citizens to engage in environmental activities and motivate environmentally responsible behaviors [34]. For example, research highlights that specific environmental communication strategies by policymakers and local governments can favor public engagement towards urban sustainable behavior [35,36,37,38]. The literature on sustainability disclosure by local governments shows that environmental information favors critical thinking and a sense of environmental responsibility [35]. Environmental information disclosure can assume an important role in delivering changes in citizens’ attitudes and behavioral intentions in favor of greater urban sustainability [36,39]. Indeed, environmental communication is an important strategy for a municipality to share knowledge, engage stakeholders, and promote citizens’ behavioral changes [36]. Liao et al. [8] suggested that people’s attention toward pro-environmental media messages is associated with their attitudes toward pro-environmental behavior, perceived social norms, and pro-environmental behavioral intentions, both directly and indirectly. Nisbet and Scheufele [40] showed that news affects how people perceive and feel about environmental issues, which in turn influences how they act and respond to these issues. However, environmental information sharing can also generate undesirable effects, such as information overload [41,42,43]. Information overload refers “to the experience of feeling burdened by large amounts of information received at a rate too high to be processed efficiently or used effectively” [44] (p. 739). In this study, we consider the role of citizens’ perceived information overload from environmental information.
Some studies have highlighted that the government, particularly in cities, can support the realization of pro-environmental activities through regulations and infrastructure, thereby affecting the implementation of these activities and encouraging citizens to perform specific behaviors [26,45]. Therefore, according to Zhang and colleagues [46], public awareness of environmental issues should also be promoted by government through urban sustainable policies, such as regulations by local governments for supporting sustainability public engagement. These policies can reflect the measures through which a government may implement actions to motivate or change people’s behaviors [47]. In particular, Hansson et al. [37] observed that it is possible to evaluate the contribution of cities to achieving SDG 11 through urban sustainable policies. In this direction, Martínez-Córdoba et al. [48] investigated the commitment of Spanish local governments toward the implementation of SDG 11 through an analysis of local policies, with the aim of improving the sustainability of cities. Moreover, Mostovoy and colleagues [38] (p. 288) investigated the extent to which the level of municipal environmental management, as perceived by the residents, influences their own environmental behaviors, showing that “studies that examine residents’ perceptions of the environmental conduct of their municipal councils are still rare”. Therefore, research on the psychological determinants of urban sustainable behavior can inform policymakers about effective behavior change strategies for promoting sustainable lifestyle choices and enhancing environmental citizenship [49].
This study focuses on citizens’ roles in making cities sustainable in the context of the SDGs using the TRA framework. Our research aims to determine the relationships between attitudinal sustainability, subjective norms, intention toward sustainable behavior, and urban sustainable behavior. In agreement with prior research, this research uses the TRA as a theoretical basis and some of its extensions related to information overload on sustainability topics and urban sustainable policies to understand citizens’ sustainable behaviors. Specifically, the proposed integrated framework analyzes the moderating role of information overload from sustainability topics and urban sustainable policies in the relationships between TRA constructs. Primarily, the research question is as follows: Do environmental information overload and urban sustainable policies facilitate urban sustainable behavior, and if so, how?
The reminder of the paper is organized as follows. Section 2 describes the research model and hypotheses; then, we outline the research methodology (Section 3) and the results of the analysis (Section 4). In Section 5, we discuss our results. Finally, we present the study’s implications for research and practice (Section 6 and Section 7), and its limitations and conclusions (Section 8).

2. Research Model

In the TRA model, the attitude concept represents individuals’ overall evaluation of their performance of a given behavior. The concept of subjective norms concerns individuals’ perceptions of whether the behavior in question is approved by other important individuals in their lives [14,15]. Drawing from the TRA, research examining sustainable behavioral has provided mixed findings. The TRA has also been extended by the theory of Pro-Environmental Reasoned Action (PERA), largely used as a predictive model by several scholars [18,19,26,50,51]. Many studies have suggested that environmental attitudes affect behavioral intention toward sustainability [52,53]. Indeed, some scholars have noted that those individuals are more willing to engage in sustainable behavior and, specifically, participate in environmental protection behavior if they maintain positive attitudes toward such behavior and if others provide normative pressure in anticipating the performance of this behavior [14]. Thus, the more positive an individual’s attitude is towards a behavior, the stronger the individual’s intention to perform that behavior will become [14]. On the other hand, some studies in the green purchase behavior context [54,55,56] have stressed that a positive attitude does not always result in the desired behavioral intention. For example, Joshi and Rahman’s [57] review related to attitude—behavior inconsistencies in the context of green purchase behavior revealed a discrepancy, or “gap”, between consumers’ expressed favorable attitudes and actual purchasing practices (“green attitude-behavior gap”). Despite these mixed findings on the roles of attitudes, and in line with the TRA model, this construct remains a major predictor of intention toward sustainability behavior and, consequently, sustainable behavior [58]. Under this background, we propose the following hypothesis:
Hypothesis 1 (H1). 
Attitudes (ATT) positively influence intention toward sustainability behavior (ISB).
In accordance with the TRA, the second antecedent of behavior is the subjective norm construct, which indicates the perceived social pressure (i.e., the influence of others who are important, such as, friends, colleagues, or partners) to perform or not perform a specific behavior. Within the literature on sustainability, research has highlighted a positive link between subjective norms and intentions [23,24,59,60,61,62]. For example, Alexa and colleagues [63] investigated the intention of buying sustainable and local brands due to the COVID-19 lockdown, which would serve to predict their engagement in concrete behavior in the future. Their study showed that the subjective norms influenced the intention to purchase sustainable brands favorably. Based on the previous findings, the following hypothesis was formulated:
Hypothesis 2 (H2). 
Subjective norms (SN) positively influence intention towards sustainability behavior (ISB).
Sustainability research provides empirical support for the relationship between behavioral intention and behavior [64,65,66]. However, some studies consider this relationship to be uncertain, investigating only behavioral intention and omitting actual behavior [67,68]. A meta-analysis of the underlying determinants of pro-environmental behavior highlighted the importance of intention as a predictor of behavior, confirming the mediating role of behavioral intentions on these behaviors [25]. Thus, in line with the TRA model, we propose the following:
Hypothesis 3 (H3). 
Intention toward sustainability behavior (ISB) positively influences urban sustainable behavior (USB).
Many studies have investigated the effects of environmental information sharing on people’s environmental attitudes and behaviors, showing that such information can also generate information overload [41,42,43]. Information overload refers to the negative impact of receiving too much information. Information overload occurs when many messages are received [69], and the information received becomes a burden, rather than a benefit [70]. Some scholars have analyzed information overload in the health and work contexts [33,71,72] as an antecedent to behavior, alongside the TRA variables. This study investigates how information overload indirectly shapes individuals’ intentions to engage in sustainable behavior through their attitudes and subjective norms. Therefore, the following hypotheses were formulated:
Hypothesis 4a (H4a). 
The relationship between attitudes (ATT) and intention toward sustainability behavior (ISB) is moderated by information overload (IO), such that the relationship is weaker with an increase in information overload (IO).
Hypothesis 4b (H4b). 
The relationship between subjective norms and intention toward sustainability behavior (ISB) is moderated by information overload (IO), such that the relationship is weaker with an increase in information overload (IO).
With respect to sustainability policies, some scholars have highlighted the importance of focusing on city residents and citizens’ perceptions of the actions taken by local authorities in influencing their environmental behavior [38]. For example, Li et al. [73] revealed that public environmental policy and subjective norms positively affected behavioral intention and behavior toward purchasing environmentally friendly agricultural food. In a review of pro-environmental behavior, Steg and Vlek [9] noted that the perceived effectiveness of policy instruments is likely correlated with recycling behavioral intentions. Under this background, Wan, Shen and Yu [74] proposed an integrated framework for investigating recycling attitudes and behaviors, focusing on the relationship between perceived policy effectiveness and recycling behavior. Moreover, environmental policy can encourage environmentally friendly behavior if the residents believe that the government is making reasonable efforts towards resolving environmental issues [75,76]. Song, Zhao, and Zhang’s study [77] highlighted that environmental policy moderates the relationship between personal norms and purchasing behavior for energy-saving products, thereby affecting green consumption. Thus, we suggest the following:
Hypothesis 5 (H5). 
The relationship between intention toward sustainability behavior (ISB) and urban sustainable behavior (USB) is moderated by urban sustainable policies (USP), such that the relationship is stronger with an increase in urban sustainable policies (USP). Figure 1 displays our research model.

3. Materials and Methods

The data in this study were collected through a survey carried out between 2 January and 30 April 2022. The data were collected using a structured questionnaire, built online using Google. A total of 224 respondents were interviewed using non-probability convenience sampling techniques. The participants were University students aged between 19 and 25, who were asked to participate through the link to the questionnaire.
Based on a power of 0.90 [78] and a significance level of 0.05, the minimum required sample size is 205 for model testing. Therefore, given that our sample size exceeded 205, the power value in this study exceeds 0.90 [79]. The majority of the respondents were female (69.64%) and employed (47%), with an average age of 31 years (SD 12.96); more than 80% had a higher education (57% high school and 28.57% a university degree).
The measurement variables used were derived from previous empirical research on sustainable behavior. For each of the six constructs, multiple item scales were developed.
The original scales were in English and have been translated into Italian to administer the questionnaire in the Italian context. All items were measured on a 7-point Likert scale, ranging between 1 = “strongly disagree” and 7 = “strongly agree”.
Attitudinal Sustainability (ATT) was measured using a composite of 16 items (α = 0.951, M = 5.747, SD = 1.394) by adapting the work of Muriuki, Dowd and Ashworth [80]. An example of the items used to assess ATT is “The issue of climate change is important to me”.
The scale of Subjective Norms (SN) was adapted from Wang et al. [81] and assessed using a 3-item measure (α = 0.889, M = 5.906, SD = 1.164). An example of the items used to assess SN is “People who are very important to me think that I should have sustainable behaviors”.
The items of Intention Toward Sustainable Behavior (ISB) were adapted from Swaim et al. [82] and assessed using a 4-item measure (α = 0.891, M = 5.215, SD = 1.268). An example of the items used to assess ISB is “I plan to support environmental initiatives”.
The scale of Urban Sustainable Behavior (USB) was adapted from Muriuki, Dowd, and Ashworth [80] and measured using a composite of 21 items (α = 0.845, M = 4.301, SD = 1.728). An example of the items used to assess USB is “Engaging in pro-environmental activities is important in my life”.
The Information Overload (IO) items were evaluated with questions adapted from Crook et al. [71] and measured using a composite of 5 items (α = 0.782, M = 4.579, SD = 1.551). An example of the items used to assess IO is “The information I received about correct behaviors was too much information for me to process”.
The items for Urban Sustainable policy (USP) were measured by Huang, Wong, and Chen [83] and assessed using an 18-item measure (α = 0.958, M = 5.522, SD = 1.582). An example of the items used to assess USP is “Loss of habitat due to urban expansion causes unsustainable development”.
All of the Cronbach’s alpha measures exceed 0.70 and ranged between 0.782 and 0.958, indicating that the scales are accurate [84].
To evaluate our model, we employed Partial Least Square Path Modeling (PLS-PM). PLS-PM is a nonparametric technique that can be used in a small-sample study, in which normally distributed data are not needed [84]. This method combines both factor and path analysis. In this work, the PLS-PM involved a two-step approach. In the first step, a measurement model was estimated to evaluate the relationship between the items and their unobservable (latent) constructs. Each construct examined in this study was reflective. In the second step of the analysis, a structural model was estimated to assess the significance of the relationships between the latent constructs. Significance was tested by bootstrapping with 500 re-samples.

4. Results

First, the measurement model evaluated the internal consistency and convergent and discriminant validity of the constructs through factor loadings, composite reliability (CR), average variance extracted (AVE), and the Heterotrait–Monotrait ratio [85]. To achieve convergent validity, a general rule is ≥0.6 for factor loadings [49], ≥0.70 for CR, ≥0.5 for AVE, and ≤0.85 for the Heterotrait–Monotrait ratio of correlations [85]. The initial estimated model had some loadings lower than 0.60 (USB1-8 and USB 15-21 for Urban Sustainable Behavior and IO 5 for Information Overload). These items were removed, and the model was re-estimated without them. In this second model, all of the indicators had a loading factor value greater than 0.6, with a p-value < 0.05. Therefore, it can be said that convergent validity was achieved (Table 1). All of the latent variables had a composite reliability value of ≥ 0.7. Consequently, it can be concluded that the composite reliability was met.
In addition, the measurement of the discriminant validity of the constructs (i.e., the extent to which a construct is truly distinct from other constructs) was tested by applying the Fornell–Larcker criterion [86] and Heterotrait–Monotrait ratio (HTMT). According to the Fornell–Larcker method, the square root of an AVE value of a variable should be higher than its highest correlation with every other model variable [84]. In this study, the square root of AVE for each variable was greater than the correlation with other variables; thus, discriminant validity was achieved (Table 2). Additionally, the variance inflation factor (VIF) for all constructs was below the threshold of five or lower.
Similarly, the Heterotrait–Monotrait ratio (HTMT) is a measure of the correlation between the constructs (Table 3). In this study, all of the constructs did not exceed the threshold value of 0.85, indicating discriminant validity [87].
To assess the structural model, the R2 coefficients were checked. The R2 coefficients for ISB and USB were 0.137 and 0.218, respectively. In behavioral studies, a value of 0.2 for R2 is generally considered acceptable [84]. Additionally, we assessed the model fit by analyzing six indicators: the average path coefficient (APC) = 0.79, p = 0.002; average R2 (ARS) = 0.177, p = 0.002; average adjusted R2 (AARS) = 0.166, p = 0.003; average block variance inflation factor (AVIF) = 1.212 (acceptable if ≤ 5, ideally ≤ 3.3); average full collinearity variance inflation factor (AFVIF) = 1.478 (acceptable if ≤ 5, ideally ≤ 3.3); and Tenenhaus GoF (GoF) = 0.372 (small ≥ 0.1, medium ≥ 0.25, large ≥ 0.36). These fit indices suggested that the model data fit was more than acceptable. The relationships between attitudes, subjective norms, and intention, as well as intention and behavior, were positive and significant (p-value ≤ 0.01). Therefore, the corresponding hypothesis was supported. H1 was supported because the direct effect of attitude on intention was positive (path = 0.228) and significant (p < 0.001). In addition, subjective norms had a significant and positive effect on intention (path = 0.236, p < 0.001); thus, H2 was supported. H3 was tested to investigate the relationship between intention and behavior. The findings were positive (path = 0.292) and significant (p < 0.001). Furthermore, attitude and subjective norms had an indirect effect on behavior through intention, but these effects were not significant (Table 4).
H4a, H4b, and H5 tested the moderating effect of IO on the relationship between ATT and ISB, SN, and ISB, as well as the moderating effect of USP on the relationship between ISB and USB. The findings of this study demonstrated that the moderating effect of IO was not significant, while USP moderated the relationship between ISB and USB (Figure 2).

5. Discussion

This study aimed to provide a more comprehensive framework for understanding citizens’ roles in making cities sustainable from the perspective of the SDGs. Specifically, this research applied the TRA model to effectively predict citizens’ intentions to engage in environmentally sustainable behavior, making cities, overall, much more sustainable. The TRA model provides greater insights with higher explanatory power for citizens’ intentions to behave sustainably. Indeed, this model is commonly applied to predict behavior, especially sustainable behavior [88].
This study builds upon the TRA model through behavioral rational choice theory to understand how attitudes and subjective norms influence intention toward engaging in sustainable behavior. This study also extends the knowledge about TRA model applications, investigating the moderating effect of information overload and urban sustainable policy. In detail, in this study, we aimed to verify whether the TRA model better explains and predicts citizens’ intentions to behave sustainably, assuming an active role in promoting sustainable cities, from the perspective of the SDGs. The results revealed that attitudes and social norms positively affect intention toward engaging in sustainability behavior (H1 and H2) and that the intention toward sustainable behavior affects urban sustainable behavior (H3).
The first and second hypotheses are in line with some previous studies on the topic. Indeed, Jung and colleagues [89] aimed to empirically identify the drivers and barriers able to influence the attitude–behavior gap, outlining the moderating impacts of consumption values and social norms on the relationship between Chinese consumers’ attitudes and behavioral intentions toward sustainable apparel products. Similarly, these results related to H1 and H2 are fully consistent with Vermeir and Verbeke’s survey study [55], which outlines that, among several features, attitudes and social norms significantly impact consumers’ attitudes and intentions towards sustainable food products. The same results were confirmed by Fang and colleagues [90], who reported that social norms and attitudes, when positively affected by normative beliefs, significantly impacted behavioral intentions. Some scholars have also investigated the relationship between intention toward sustainable behavior and urban sustainable behavior, showing that there is a strict link between the behavioral determinants (attitudes, self-efficacy belief, and social norms) and the intention to adopt sustainable behavior, where the community radio plays a key role by positively increasing the acceptability of sustainability communications and enabling rural people to perceive that no communication medium other than community radio would be a more effective intervener [91].
Moreover, the hypothesized relationships in H4a and H4b, concerning the moderating role of information overload on the previous relationships between ATT and ISB and between SN and ISB, were not significant compared to H5, which was supported, thereby confirming the significant moderating effect of USP on the relationship between ISB and USB. These results can be explained by considering some previous studies on the topic, which have outlined the negative relationships between perceived vulnerability and intention to exercise and behave in a certain way in regard to sustainability issues [92]. Some other scholars have outlined that consumers with greater knowledge or information about green products tend to be more inclined and motivated to follow and perform pro-environmental behaviors because they have a better ability to adequately evaluate the same products [20]. Moreover, significant knowledge about a product engenders much more positive attitudes toward green purchase intentions [93], and favorable attitudes directly contribute to green product consumption [94], translating consumers’ feelings into concrete and tangible actions. However, as shown in our study, the excessive availability of information and knowledge about sustainable behavior can confuse citizens, rather than having a strong positive impact on their intentions toward sustainable behavior, because of the difficulties met in managing a high quantity and quality of information and knowledge.

6. Theoretical Implications

This study provides theoretical implications to better describe the determinants of citizens’ behaviors to promote environmental sustainability. In this work, we employed the TRA model, while reinforcing its theoretical constructs to investigate the influencing factors underlying intention formation in the urban environmental sustainability field. Indeed, the TRA model can explain the influence of those factors clearly and insightfully, particularly considering their possible moderating effects on citizens’ intentions to behave sustainably.
We focused our attention on the specific variables that affect intention toward sustainable behavior, as well as urban sustainable behavior, following several studies that identified other factors able to influence pro-environmental behavior, including “demographic factors, institutional factors, economic factors, social and cultural factors, motivation, environmental knowledge, awareness, values, attitudes, emotion, responsibility, priorities and so forth” [95] (p. 29). Among these factors, recent studies have focused much more on psychological aspects, such as attitudes, beliefs, and subjective norms, defined by Ajzen [96] as the perceived pressure from society to perform (or not) a behavior, as well as perceived behavioral control, which corresponds to whether it is easy or difficult to perform a particular behavior based on what an individual perceives. The TRA model allows us to consider these psychological factors much more effectively and usefully in predicting pro-environmental behavior and, more generally, sustainable behavior.
In summary, the present findings show that the TRA is a useful model to predict potential sustainable behavior intentions. In the literature, numerous studies have already applied the TRA and the Theory of Planned Behavior (TPB), in addition to combining them to predict sustainable behavior, especially pro-environmental behavior in different countries [97,98,99,100,101]. Although the present investigation found large considerations in previous research on this topic using the TRA or TPB models, there are still few studies investigating this topic using the TRA model in Italy and many other developed countries [102,103,104]. This data gap is especially noteworthy considering that attitudes and subjective norms are significant predictors of intentions to engage in sustainable behavior to make cities sustainable.

7. Practical Implications

Previous studies also argue that “cities tend to integrate sustainable development into their dynamic planning” [31] (p. 3), although it is very difficult to guarantee absolute sustainable development when cities are involved in urban expansion. For this reason, collaboration and cross-border teamwork among several organizational actors are required to enhance the degree of resource usage and to carry out sustainable urban development. In this scenario, urban sustainability behavior acquires a key role and represents the result of collective action considering environmental, economic, and social equity issues. Thus, it is fundamental to evaluate urban sustainability behavior in planning, developing, and preserving sustainable cities. In this direction, citizens can play a crucial role in making cities sustainable, where urban resilience and sustainability behavior are associated with urban transformation from the perspective of sustainability and the achievement of the SDGs. In addition, most academics have paid increasing attention to the pro-environmental behavior of citizens by adopting several theoretical frameworks to investigate the main factors able to drive people to adopt pro-environmental behaviors [95].
Based on the empirical research findings, we suggest the following policy and managerial prescriptions. First, the growing urban environmental development creates a requirement to assimilate sustainability determinants into urban planning and development arrangements. From the perspective of sustainable urban development, going beyond some specific interventions by local authorities and policymakers is necessary. These measures could include carefully planning transportation systems, monitoring pollution and energy use sources, stimulating the adoption of sustainable energy resources, and waste recycling. Policymakers should adopt an approach that is able to include sustainable policy in every aspect of citizens’ daily activities, enabling the populace to acquire habits to act sustainably. Sustainable urban development is vital to strategic city planning, in which citizens’ sustainability behavior represents a crucial feature of environmental sustainability related to social interconnection and economic growth [31,88,105]. Thus, policymakers need to make effective appeals that cannot be too extreme or exaggerated, which risk being counterproductive and do not motivate or stimulate citizens to behave sustainably. Strategic communication programs and education programs are necessary because citizens need to be accurately informed and trained. However, an overload of information, as well as non-specific and approximate information, can have a negative influence.
Policymakers must also promote specific communication programs and appeals that are able to directly involve citizens in developing their attention and interest in their city, thereby stimulating them to behave sustainably by respecting the overall community and considering future generations, for instance, it would be effective to plan specific events for promoting urban sustainability involving testimonials from celebrities who have a clear strong commitment to preserve the urban environment. It would also be useful to create and manage social media to share data and information about the status quo of the urban environment, as well as plan programs for recognizing incentives for citizens who behave sustainably (e.g., shopping vouchers for waste recycling). Otherwise, citizens usually present strong resistance toward changing their habits (e.g., consuming plastic and engaging in activities with a high level of pollution). For this reason, it is necessary to guide citizens to change the way they behave by affecting their attitudes and subjective norms. Consequently, government authorities and environmental organizations should educate people on their active roles in making cities sustainable, outlining how their behavior is relevant to achieving environmental sustainability and could have dangerous consequences. Such education should be enacted through the promotion and implementation of educational and training programs that also involve education institutions, applying practical actions and innovative techniques such as role playing, learning by doing, and simulations. Thanks to targeted programs and interventions, including specific measures to decrease the negative effects of citizens’ behaviors on environmental sustainability, attitudes toward reducing unsustainable actions, subjective norms, and perceived self-efficacy strongly support citizens’ intentions to behave sustainably. This result indicates that more people must be instilled with a positive attitude toward sustainable behavior. Once many citizens hold a positive view toward sustainable behavior, there will be spontaneous and mutual social influence. In this direction, programs and actions can be formulated to propose strategies for stimulating and motivating citizens to behave sustainably, although there are objective difficulties, both theoretical and practical, regarding the implementation of policy measures in the city context to stimulate and support citizens to behave sustainably.
In summary, this study has important implications for practitioners and policy makers in terms of capacity-building programs, communication strategies, and education programs, which should seek to significantly influence people’s attitudes toward behavior in a positive way. In this framework, the intrinsic reward should be promoted with the extrinsic motivation of citizens to become engaged in sustainable behavior. Through adequate and effective communication strategies, appeals, and education programs, it would be possible to facilitate change in beliefs and intentions, thereby informing and training citizens in performing sustainably and making cities completely sustainable.

8. Conclusions

The topic of urban sustainable behavior is receiving increasing levels of attention because of the numerous problems caused by the rapid decay of the natural environment and the social and economic emergencies in recent decades. This study mainly contributes to the existing research by identifying factors that can explain citizens’ intentions to behave sustainably. We achieved this goal by analyzing the moderating effects of some specific variables. Practically speaking, this research will enable policymakers and individuals to consider these factors in stimulating and motivating citizens to behave sustainably and significantly assume an active role in promoting and making cities sustainable.
This study possesses several limitations that could be addressed in future research. First, this study did not use data on actual citizens’ environmentally sustainable behaviors. The data were instead collected from a subjective self-reported questionnaire used to investigate citizens’ intentions toward engaging in sustainable behavior. Second, the study used convenience sampling, and the data pool was not very large. Moreover, the same cross-sectional data analysis did not track the changes in citizens’ perceptions and intentions over time, limiting the generalizability of the results. Third, the cross-sectional design of this study does not allow causal inference; thus, it is necessary to interpret the results with caution. Finally, the research sample investigated in this study included only Italian people. Therefore, we may not be able to generalize the findings to other populations. In this direction, future research could apply and compare theories across different cultural settings to obtain more consistent research findings. Future research could also empirically and more deeply investigate the extent of environmentally sustainable behavior among citizens and adopt longitudinal or experimental designs, applying several theoretical models to explore causal relationships.
Overall, this study provides empirical evidence supporting use of the TRA model in investigating predictors of citizens’ sustainable behavior for the development of sustainable cities and can be considered a useful contribution to the application of the TRA for suggesting useful and stimulating ideas for developing interventions to promote sustainable behavior. The findings show that the TRA is a good model for predicting intention toward sustainable behavior, as well as urban sustainable behavior. Although our results only partially supported the influence of TRA constructs on the tendency toward engaging in sustainable behavior based on the moderating effects of some variables, the TRA could be a promising approach for further research that focuses much more strongly on the psychological determinants of citizens’ sustainable behavior.

Author Contributions

Methodology, M.M.P.; writing—original draft, P.B., C.M. and L.V. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

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Sustainability 15 04272 g001 550
Figure 1. Research model.
Figure 1. Research model.
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Figure 2. Path Coefficients and moderating effects. Note: *** p-value < 0.01.
Figure 2. Path Coefficients and moderating effects. Note: *** p-value < 0.01.
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Table
Table 1. Construct Reliability and Validity of the re-estimated model.
Table 1. Construct Reliability and Validity of the re-estimated model.
Theoretical ConstructsVariablesLoadingsCRAVE
Attitudinal Sustainability (ATT)DE10.7020.9570.572
DE20.733
DE30.827
DE40.85
DE50.778
DE60.828
DE70.803
DE80.802
DE90.857
DE100.857
DE 110.669
DE 120.68
DE 130.627
DE140.69
DE 150.747
DE160.716
Subjective Norms (SN)SN10.9040.9320.819
SN20.946
SN30.865
Intention toward sustainable behavior (ISB)ISB10.8450.9240.753
ISB20.895
ISB30.873
ISB40.859
Urban sustainable behavior (USB)USB100.7620.8680.527
USB110.685
USB120.774
USB130.812
USB140.84
USB150.68
Information Overload (IO)IO10.8190.857 0.684
IO20.91
IO30.85
IO40.759
Urban Sustainable policy (USP)USP10.6960.962 0.580
USP20.724
USP30.722
USP40.773
USP50.716
USP60.767
USP70.798
USP80.745
USP90.702
USP100.725
USP110.639
USP120.809
USP130.848
USP140.862
USP150.832
USP160.843
USP170.707
USP180.803
Table
Table 2. Correlations among latent variables with square roots of average variances extracted and the variance inflation factor (VIF).
Table 2. Correlations among latent variables with square roots of average variances extracted and the variance inflation factor (VIF).
ATTSNISBUSBIOUSPFull Collinearity VIF
ATT0.756 1.938
SN0.320.905 1.325
ISB0.3110.3210.868 1.307
USB0.5470.2910.4680.726 1.907
IO0.2980.1370.2880.2470.827 1.259
USP0.4410.3130.3460.4970.4090.7621.480
Note: Diagonals represent the square root of the average variance extracted, while the other entries represent the correlations.
Table
Table 3. Heterotrait–Monotrait ratio.
Table 3. Heterotrait–Monotrait ratio.
ATTSNISBUSBIOUSP
ATT
SN0.336
ISB0.2950.355
USB0.5290.2980.452
IO0.3080.1580.3010.379
USP0.4260.3300.3530.4550.427
Table
Table 4. Path Coefficients and Hypothesis Testing.
Table 4. Path Coefficients and Hypothesis Testing.
Hypotheses Path CoefficientsStatus
H1ATT → ISB0.228 ***Supported
H2SN → ISB0.236 ***Supported
H3ISB → USB0.292 ***Supported
Note: *** p-value < 0.01.
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MDPI and ACS Style

Briganti, P.; Metallo, C.; Pagliuca, M.M.; Varriale, L. Exploring Citizens’ Behavior to Promote Environmental Sustainability: The Role of Information Overload and Urban Sustainable Policies. Sustainability 2023, 15, 4272. https://doi.org/10.3390/su15054272

AMA Style

Briganti P, Metallo C, Pagliuca MM, Varriale L. Exploring Citizens’ Behavior to Promote Environmental Sustainability: The Role of Information Overload and Urban Sustainable Policies. Sustainability. 2023; 15(5):4272. https://doi.org/10.3390/su15054272

Chicago/Turabian Style

Briganti, Paola, Concetta Metallo, Maria Margherita Pagliuca, and Luisa Varriale. 2023. "Exploring Citizens’ Behavior to Promote Environmental Sustainability: The Role of Information Overload and Urban Sustainable Policies" Sustainability 15, no. 5: 4272. https://doi.org/10.3390/su15054272

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