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Article

From Health Risks to Environmental Actions: Research on the Pathway of Guiding Citizens to Participate in Pocket-Park Governance

1
College of Management Science, Chengdu University of Technology, Chengdu 610059, China
2
Chengdu Park City Demonstration Zone Construction Research Center, Chengdu 610059, China
3
School of Management, Sichuan University of Science & Engineering, Yibin 644000, China
*
Author to whom correspondence should be addressed.
Land 2024, 13(10), 1612; https://doi.org/10.3390/land13101612
Submission received: 4 September 2024 / Revised: 2 October 2024 / Accepted: 3 October 2024 / Published: 4 October 2024

Abstract

:
The COVID-19 pandemic has heightened the demand for urban pocket parks near residential areas, posing new challenges for environmental governance. However, there is a lack of research on how to engage citizens in pocket-park governance to address both potential and unforeseen risks. This study combines social information processing theory with a norm activation model to develop a framework that identifies the shaping stages and influencing factors of citizens’ intentions to participate in pocket-park governance. Using partial least squares structural equation modeling, this research analyzed the relationships among external factors, attitudes, moral norms, and intentions to participate based on 719 responses from an online survey targeting Chinese citizens in November and December 2023. Results indicate that health risks and pocket-park environmental quality positively affect perceived usefulness. Attitudes and moral norms are indeed important factors mediating the positive effect of the external environment on the intention to participate. The pathway of guiding citizens to participate in pocket-park governance is clarified, which helps bolster the resilience of urban green spaces and improve the quality of life of residents after public crises.

1. Introduction

The outbreak of COVID-19 at the end of 2019 had a profound impact on global public health systems and personal lifestyles. By 2023, more than 760 million people worldwide had reportedly contracted the virus [1]. To curb its spread, many countries implemented lockdowns and social distancing measures, with China being no exception [2]. As a result, residents were confined to their homes, working and studying online, with limited mobility [3]. Urban green spaces (UGS) have been recognized as essential for enhancing cities’ resilience against health emergencies like COVID-19, significantly contributing to public health [4,5,6]. Unfortunately, during COVID-19, the closure of large parks made it difficult for residents to access nature [5]. Even under lockdown policies, using UGS should not be a privilege reserved for those with private gardens [5]. Consequently, in the context of normalized pandemic prevention and control, residents expressed a growing demand for equitable access to parks near their communities. Reconstructing these spaces can help mitigate spatial distribution disparities [7]. However, as high-density urban development continues, issues related to ecological degradation and public health become increasingly prominent [8]. Expanding large urban parks faces numerous challenges. According to the World Bank, in 2022, the global urban population ratio reached 57% [9]. In the same year, China’s urbanization rate stood at 65.22%, reflecting a 0.5% increase from 2021 [10]. The United Nations Human Settlements Programme (UN-Habitat) has projected that the global urban population will grow by 2.2 billion by 2050 [11]. In densely populated urban areas, the focus should shift towards developing smaller and more accessible UGS, such as pocket parks, which can enhance urban environmental equity and bring residents closer to nature, particularly in fragile contexts like COVID-19 [12,13].
Pocket parks are developed or converted from underutilized urban spaces to satisfy the increasing demand for quality parks and recreational areas [14]. These parks are sporadically and flexibly integrated into high-density neighborhoods without specific shapes or surroundings. In China, pocket parks are defined as “park and greening activity venues open to the public, small in size, diverse in shape, and possessing certain recreational functions” [15]. Scholars have advocated for incorporating small-scale UGS into communities to ensure safe green-space coverage for all citizens [6,16,17]. In July 2022, the Ministry of Housing and Urban–Rural Development (MHURD) issued a notice on advancing the development of pocket parks, mandating cities nationwide to establish environmentally friendly pocket parks and standardize their management practices [15]. It can be seen that the expansion of pocket parks has become a significant aspect of urban habitat construction in China. Figure 1 demonstrates pocket parks in China situated close to residential neighborhoods where citizens exercise, socialize, and enjoy leisure activities. Over the past three years, the need for research on pocket parks has gained recognition among scholars [16,18,19]. Despite the increasing volume of literature on pocket parks, most studies have primarily focused on topics such as ecosystem service value [20,21,22], physical landscape design [23,24], and usage patterns [14,25]. Yet, there remains a significant gap in the research concerning the sustainable governance of pocket parks, particularly from the perspective of citizen participation.
On the other hand, a highly concentrated population presents more severe challenges for the governance of UGS [26]. Research has shown that public participation can effectively contribute to the governance of urban environments [27]. There is an assertion that encouraging public participation offers a more inclusive approach to strengthening urban resilience and implementing crisis adaptation strategies [28]. However, as Csomós et al. point out, many citizens are reluctant to commit themselves to environmental protection efforts for pocket parks, often perceiving it as the government’s unavoidable duty [29]. This reluctance may stem from a lack of knowledge and environmental awareness regarding pocket parks. In larger environments, individuals may fulfill their environmental obligations due to transparent external monitoring and regulatory constraints [30,31]. However, the absence of strict management in pocket parks can result in various environmental problems like degradation. Amidst COVID-19, research unexpectedly uncovered increased environmental damage in UGS, including trampling on lawns to avoid close contact with pedestrians [32] and a surge in waste due to overuse [33]. Relying solely on government efforts to maintain clean pocket-park environments in rapidly urbanizing cities and high-density neighborhoods is insufficient. Consequently, it is crucial to inspire citizens to acknowledge the usefulness of pocket parks, raise their environmental awareness and norms, and actively participate in environmental governance.
From a comprehensive perspective, environmental citizenship behavior can be seen as a form of pro-environmental behavior (PEB) [34], with participation in environmental governance classified as a type of participatory PEB [26]. According to Steg and Vlek, PEB refers to actions that either minimize environmental harm or restore the natural environment [35]. This behavior spans two spheres: private (Pr-PEB) and public (Pu-PEB) [36]. Pu-PEB involves engaging in activities that benefit the environment within public spaces [37]. Participating in pocket-park governance serves to preserve the community environment, benefiting all nearby residents. As such, this study posits that citizens’ intention to participate in pocket-park governance represents a Pu-PEB intention driven by altruistic motives. Although previous studies have explored the residents’ and tourists’ environmental behavioral intentions in national parks or UGS [26,38,39], this study identifies a research gap concerning how to encourage citizens’ participation in pocket-park governance after health crises. Specifically, there is a limited understanding of the relationship between external characteristics in risk situations and citizens’ attitudes and behavioral intentions. Given that health crises have highlighted the importance of UGS, implementing a sustainable development strategy for pocket parks is essential for ensuring suitable habitats. With the risk of emerging or recurring diseases persisting after COVID-19, promoting pro-environmental actions to mitigate future health threats is perhaps the most important lesson learned from this crisis [40]. While prior studies have qualitatively discussed how COVID-19 has increased the value of pocket parks and altered citizens’ attitudes, usage patterns, and visit frequencies, there remains a lack of research on the key drivers behind citizens’ PEB in pocket parks post-pandemic.
The norm activation model claims that moral dimensions are significant predictors of environmentally relevant behaviors or intentions [41,42,43]. Likewise, public attitudes toward the environment play a critical role in predicting PEB [44]. In the wake of COVID-19, risk has emerged as a key driver influencing individual PEB [42] as people actively take steps to mitigate health risks from external environments. Additionally, environmental quality, including the physical condition of a place, may also be another significant factor [45,46], as it signals “whether environmentally damaging behaviors are permissible”. The current study views health risks and environmental quality as contextual factors representing external environmental information. According to social information processing theory [47], individuals can adjust their perceptions, attitudes, and behaviors by absorbing and processing external information pertinent to specific situations. Given that citizens’ participatory PEB can enhance the resilience of UGS at source in risky situations, this study posits that further research is needed to fully understand whether external environmental information from crises enables people to perceive the usefulness of pocket parks, activate their moral norms, and ultimately inspire their intention to participate in environmental governance.
This study aims to develop a framework to delve into the factors affecting the intention to participate in pocket-park governance after health crises by incorporating social information processing theory into a norm activation model. The proposed framework innovatively divides the process of shaping citizens’ intention to participate after health crises into three stages: the information processing stage, the norm activation stage, and the behavioral intention transformation stage. The model links health risks, environmental quality (external environmental information), perceived usefulness (specific attitudes toward the environment), awareness of consequences, ascription of responsibility, personal norms (internal moral norms), and intention to participate in pocket-park governance (PEB intention). Moreover, the study performs empirical tests to foster the understanding of inherent mechanisms and address limitations in prior literature. The findings will assist urban planning and management authorities in developing effective policies that enhance citizens’ attitudes and awareness, strengthen individual norms, and thus promote the sustainable management of UGS.
The main contributions of this research are threefold. First, this study shifts the focus from the traditional emphasis on managing pocket parks to exploring residents’ PEB in relation to their participation in pocket-park governance. Second, by combining social information processing theory and a norm activation model, a novel and holistic theoretical framework is developed to identify the external contextual and psychosocial determinants of intention to participate in environmental governance. Finally, we empirically examine how residents experiencing the COVID-19 crisis re-examined the value of pocket parks and protected them. This provides meaningful insights for the management of UGS. The empirical evidence generated is critical for improving the sustainability of urban environments after health crises.

2. Theoretical Background and Hypotheses Development

2.1. Norm Activation Model

The norm activation model (NAM) [48] is one of the most widely used theories for studying behavioral intentions [49,50,51]. The model comprises three key constructs: awareness of consequences, ascription of responsibility, and personal norms. Awareness of consequences is described as “a person’s ability to realize the negative consequences of being in an antisocial situation for others or for things that others value” [52]. Ascription of responsibility refers to an individual’s sense of responsibility for performing a particular behavior [53]. Personal norms are moral obligations aligned with an individual’s internal value system [48], which reflect internalized standards that help the right course of action [40]. NAM emphasizes the process of activation or triggering of object norms and focuses on a “pro-social/moral” aspect, which is an expression of altruism [51,54,55].

2.2. Social Information Processing Theory

Social information processing theory (SIPT) falls under the umbrella of cognitive psychology. Social information is acquired through individual observations or interactions with the social environment and others [56]. Salancik and Pfeffer suggest that individuals are highly adaptive, continually adjusting their attitudes and behaviors in response to the external environment and personal experiences [47]. When people receive information from the environment, they encode and store it in their brains, then perceive and interpret it in subsequent stages. This process affects final attitudes and behaviors [47]. Recently, SIPT has been applied to the study of environmental behaviors. For example, Zhang et al. hypothesize that when residents perceive an environmentally friendly image, they will consider and direct their environmentally responsible behaviors by absorbing and organizing these cues to adapt to this supportive environment [57]. However, the literature on this topic is limited, and more evidence is needed to demonstrate the applicability of SIPT in studying PEB.
By innovatively drawing on SIPT to extend the NAM, this study intends to categorize the pre-process of citizen participation in pocket-park governance into three stages: the information-processing stage, the norm-activation stage, and the behavioral-intention-transformation stage. This framework will explain how external contextual factors affect attitudes, internal norms, and the intention to participate. The goal is to provide evidence-based support for understanding the complex decision-making process behind environmental citizenship behavior.

2.3. The Information-Processing Stage: Influences of Health Risks and Environmental Quality on Perceived Usefulness

“Perceived usefulness” is originally defined as “the degree to which a person believes that using a particular system would enhance his or her job performance” [58] (p. 320). The fact that an item/thing is useful to a person indicates that the person has gotten the needed value. Thus, perceived usefulness is a perception of value [58]. It can also be understood as the degree to which a particular valued goal is achieved [59]. It is a psychologically subjective perception [60]. In UGS research, “usefulness” is conceptualized as “the perceived benefits of using urban green spaces by individuals” [61] (p. 289). Perceived usefulness is used to measure specific attitudes toward the environment, also called instrumental attitudes. It is more specific than an individual’s general attitudes toward UGS [61,62]. Arnberger and Eder measured the perceived importance of UGS in terms of their role in quality of life, urban climate, and other aspects [63]. Referring to Wan et al.’s proposal, the perceived usefulness of pocket parks in this study will be measured by perceived improvements in physical and mental health and quality of life, as well as the benefits of coping with health risks [62].
Contextual factors are essentially individuals’ perceptions of the environment [36]. Perceived risk is a subjective assessment of objective risk, which reflects individuals’ judgment of how significantly the risk affects them [64,65]. In this study, health risks are defined as the concerns that people who have experienced COVID-19 have about their future health status and susceptibility. This can also be described as the perception of possible and potential health risks. Risk perception theory suggests that people’s perceptions of risk outcomes influence their final attitudes and decisions [66]. SIPT proposes that an individual’s interpretation of external social information shapes perceptions, attitudes, and behaviors [47]. The outbreak of COVID-19 is an opportunity to examine changes in perceptions and attitudes and, in turn, reconsider human behaviors toward the natural environment [65,67]. In risky environments, people may be more convinced that pocket parks help increase resistance to viruses, considering that people with healthy lifestyles who are physically active outdoors often have less severe reactions and symptoms after contracting the disease [68]. The current global situation has highlighted the importance of spending time in UGS more than ever. Greenings provide even more value to citizens in maintaining good physical and mental health during times of global chaos, especially such accessible and safe green spaces on a tiny scale [17]. This study hypothesizes that citizens will perceive unprecedented health risks and develop favorable attitudes toward pocket parks after experiencing a major crisis like COVID-19. Given the evidence, the hypotheses are proposed as follows:
H1. 
Health risks positively affect perceived usefulness.
Attributes of UGS, such as facilities, aesthetics, and cleanliness, can shape human behavior [62]. In studies of urban parks, most researchers have identified perceived environmental quality as an antecedent of visiting and using intentions. Only a few authors have explored the role of environmental quality on PEB [45,46]. Liu et al. surveyed Chinese tourists, proposing that environmental quality is an antecedent of attitudes [46]. Good environmental quality may change an individual’s perceptions of pocket parks and make people perceive the benefits provided by parks as “useful”. Thus, we propose the following hypothesis:
H2. 
Environmental quality positively affects perceived usefulness.
In addition, SIPT claims that an individual’s attitudes and behaviors are not only influenced by external information but may also be affected by complex changing environments [47]. Uncertain health risks may moderate the effect of environmental quality on perceived usefulness. Specifically, the more serious the health risks, the more likely citizens are to realize the importance of clean pocket parks in improving quality of life and defending against diseases. Therefore, we propose that:
H3. 
Health risks positively moderate the effect of environmental quality on perceived usefulness.

2.4. The Norm-Activation Stage: Relationships between External Environmental Information, Attitudes, and Moral Norms

2.4.1. Influences of Health Risks, Environmental Quality, and Perceived Usefulness on Components of the NAM

Prior literature provides two insights into how perceived risk affects an individual’s moral norms for this study. The first viewpoint asserts that health crises are related to climate and environmental issues such as global warming, pollution, and degradation. Risks motivate people to be in awe of nature and to take these issues seriously. People may worry about whether such environmental threats will continue to cause health crises in the future, thus adopting environmentally responsible behaviors and preventing destructive events from occurring as much as possible [67]. Another potential mechanism is that global health crises may trigger altruistic moral standards. The presence of empathy pushes people to think about others’ feelings and exercise self-restraint to protect the well-being of others [69]. Accordingly, the following hypotheses are developed:
H4. 
Health risks positively affect awareness of consequences.
H5. 
Health risks positively affect the ascription of responsibility.
H6. 
Health risks positively affect personal norms.
SIPT suggests that individuals perceive and interpret the state of their surroundings as an external signal and thus develop a set of behavioral rules to determine whether such behavior will be received and endorsed by the surrounding environment [70]. Therefore, individuals’ normative constraints to protect the environment are possibly influenced by environmental qualities, such as convenience and a clean environmental infrastructure. From the perspective of broken-window theory, scholars argue that a dirty environment implies to individuals that disruptive behaviors are not prohibited and protecting the environment may not achieve the desired results [46]. Based on this proposition, we postulate the following hypotheses:
H7. 
Environmental quality positively affects awareness of consequences.
H8. 
Environmental quality positively affects the ascription of responsibility.
H9. 
Environmental quality positively affects personal norms.
Many researchers have investigated public attitudes toward small urban parks near homes during COVID-19. It is reported that parks helped residents escape from loneliness, breathe fresh air, engage in physical activity, and relax their brains [71]. If a person believes that green space is important in some function, it means that he or she will also recognize it as useful. This study argues that, while enjoying the benefits of pocket parks, people will worry about whether the destruction will lead to terrible consequences and view participating in governance as their responsibility. Likewise, a pleasing environment makes individuals believe that environmentally responsible behaviors are recognized norms in the community [46], which in turn leads to the internalization of these norms and ultimately promotes the intention to participate. Based on the above viewpoints, we propose the following hypotheses:
H10. 
Perceived usefulness positively affects awareness of consequences.
H11. 
Perceived usefulness positively affects the ascription of responsibility.
H12. 
Perceived usefulness positively affects personal norms.

2.4.2. Relationships among Variables within the NAM

When people realize that crises may have negative impacts on what they value, they reflect on the responsibilities they should assume [40]. Personal norms are moral obligations to perform or avoid particular behaviors after becoming aware of consequences and responsibilities. Stimulated by awareness of consequences and ascription of responsibility, individuals feel the need to take positive actions. On the contrary, a person may be reluctant to take actions if he or she believes that an issue is irrelevant or that his or her contribution is not sufficient to solve it [51]. Much of the literature supports the interrelationship between awareness of consequences, ascription of responsibility, and personal norms [49,51,72]. If citizens realize that environmentally destructive behaviors such as littering may result in the loss of pocket parks and recognize the severity of this consequence, they may pick up the responsibility to protect pocket parks and then regulate moral standards. Therefore, the following hypotheses are proposed:
H13. 
Awareness of consequences positively affects the ascription of responsibility.
H14. 
Awareness of consequences positively affects personal norms.
H15. 
The ascription of responsibility positively affects personal norms.

2.5. The Behavioral-Intention-Transformation Stage: Predictors of Intention to Participate in Pocket-Park Governance

Since the COVID-19 pandemic, health has become a widespread concern. Koleva et al. claim that the public expressed strong intentions to adopt PEB after the pandemic [73]. Bouman et al. make a valuable point that individuals’ supportive response to COVID-19 stems in large part from strong personal norms [40]. That is, whether proactively or under compulsion, they feel moral obligations to exhibit environmentally responsible behaviors. They are equipped with an awareness of the consequences of crises and think risks are inextricably linked to their own lives. As such, we propose the following hypotheses:
H16. 
Health risks positively affect the intention to participate.
Additionally, a positive physical environment provides sufficient resources to enable people to cope with the stress brought on by COVID-19 [74,75]. Some researchers suggest that if small UGS are properly maintained, residents are more likely to look after the area and less likely to vandalize and neglect it [76]. Conversely, if the UGS is overgrown, residents may litter on the lawn. In tourism, destination image is affirmed to play an important role in promoting PEB [45]. Investigative evidence suggests that perceived environmental quality affects PEB through the mediation of environmental engagement [77]. When the perceived environmental quality is good enough to improve the quality of life, residents may rally to maintain this comfortable status [71]. The finding of Corrado et al. states that the logic behind the “environmental poverty traps” is that residents living in dirty environments are less likely to participate in governance because they think it to be more costly to improve a degraded environment (make up for the loss) than to protect a clean environment (avoid the loss) [78]. Thus, we propose the following:
H17. 
Environmental quality positively affects the intention to participate.
In addition, perceived usefulness has emerged as a predictor of environmental behavior [59,60,79]. It is also considered to be an important antecedent of using UGS [63,80]. This specific attitude, representing the perceived value of the environment, is found to be a better predictor compared to general environmental attitudes. A study claims that when visitors perceive value from a location, they may give back to the place by protecting its environment [81]. Accordingly, favorable attitudes toward pocket parks may also predict intention to participate in governance, yielding the following proposal:
H18. 
Perceived usefulness positively affects intention to participate.
Furthermore, awareness of negative consequences makes individuals recognize the necessity of taking action to mitigate such consequences [82]. The responsibility toward the environment also drives them to engage in environmental behaviors rather than deferring to others [26]. Likewise, personal norms, as a type of intrinsic motivator, help citizens self-regulate and align their actions with moral standards [40,72]. Accordingly, we can infer that those with stronger moral norms are likely to be more willing to participate in the governance of pocket parks. From this conclusion, we hypothesize the following:
H19. 
Awareness of consequences positively affects the intention to participate.
H20. 
Ascription of responsibility positively affects intention to participate.
H21. 
Personal norms positively affect intention to participate.
Figure 2 illustrates the proposed framework for shaping intention to participate in governance.

3. Methods

3.1. Study Area and Data Collection

We selected China as the study area for two primary reasons. Firstly, China stands as the largest developing country globally, characterized by a dense population, which presents unique challenges in managing and maintaining UGS. Secondly, China places significant emphasis on pocket-park construction as part of its efforts to promote ecological civilization. As of 2022, nearly 30,000 pocket parks have been developed and renovated in China, with the urban per capita park and green-space area averaging approximately 15 square meters [83]. Respondents were required to be at least 18 years old because this age group is capable of making independent decisions and bearing the consequences thereof. To avoid potential distortion in responses from participants who may lack interaction with pocket parks, the question “Have you ever visited a pocket park in your city?” was used to select appropriate respondents for the study.
The initial data was collected online using a simple random sampling method between November and December 2023. All procedures adhered strictly to ethical standards. The first part of the data was collected through the Credamo platform (www.credamo.com, accessed on 11 November 2023), a professional online questionnaire survey company in China boasting a sample base of over 3 million users. This platform enabled the precise distribution of e-questionnaires to a large respondent pool, which has been well-regarded and frequently utilized by scholars [84,85]. To uphold data quality standards, the paid sample service offered by Credamo was employed, and all responses were anonymized. The second part of the data was collected by sharing the e-questionnaire link on social media platforms such as WeChat and Weibo. Respondents were provided with information about the survey’s objectives and relevant concepts, such as pocket parks, to ensure the reliability and accuracy of responses. Apart from this, participants were instructed that their answers should range from at least 1 min to no more than 6 min in duration. Apart from this, attention-detection questions were included to filter out responses that did not meet the required level of engagement.
After the questionnaires were returned, each piece of data underwent automated review through the system and subsequent manual verification by researchers. Responses were then either accepted or rejected based on predefined criteria to determine the samples used for formal analysis: (a) responses from individuals who have never visited a pocket park; (b) responses from individuals younger than 18 years old; (c) responses that did not meet the requirement for the length of time required to fill in; (d) responses that did not pass attention-check questions; and (e) responses with high consistency across options. For each adopted response, the respondent received a payment of 2 RMB. In total, 842 respondents completed the questionnaire. Following stringent data cleaning procedures, 123 invalid questionnaires were removed. 719 valid and available responses were finally retained, yielding a validity rate of 85.39%. The formal survey was not restricted to specific geographic districts, as urban parks are being developed across all provinces in China, and all citizens have been impacted by COVID-19.

3.2. Measurement

All items in the questionnaire were adapted from existing scales and tailored to fit the specific requirements of the research context. The original scales were initially developed in English and subsequently translated into Chinese. We invited two distinguished experts, one in the field of environmental management and the other in behavioral psychology, to assess the validity of the items. A pilot survey was conducted involving 60 participants from Chengdu, China, representing different genders and ages (27 males and 33 females, aged 18–70). Based on feedback and issues during the pilot survey, researchers made necessary adjustments and modifications to improve clarity and relevance. Finally, all items were re-translated back into English to verify the semantic equivalence between the third version of the Chinese scale and the original English version.
As shown in Appendix A, a seven-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree) was employed for all measurement items in the questionnaire. Four items addressing health risks were derived from O’Connor and Assaker and Wen and Liu-Lastres [42,86]. The measurement of environmental quality was developed based on Liu et al. and Wan et al. [46,62]. To assess the perceived usefulness of pocket parks, descriptions from Wan et al. and Wang et al. were integrated and adjusted, resulting in a set of five measurement items [62,80]. Awareness of consequences was evaluated using four items modified from He and Zhan [55]. Measurements for ascription of responsibility and personal norms were derived from Zhang et al. [51]. Items of intention to participate were designed based on Huang et al. [26]. In addition, a categorical scale was used to collect basic demographic information (including gender, age, education level, and monthly income). Respondents were asked to report their average monthly frequency of visiting or using pocket parks near their homes during COVID-19.

3.3. Respondents’ Profile

The specific regional distribution of the sample is illustrated in Figure 3. In China, the top ten provinces with the highest coverage of urban parks and green spaces are Guangdong, Shandong, Jiangsu, Zhejiang, Sichuan, Henan, Hubei, Beijing, Anhui, and Liaoning [10], primarily located in the eastern and southern regions of the country. The distribution of the sample size mirrors this geographic pattern. Residents living in cities with an ample supply of UGS find it easier to connect with nature. Also, the regional distribution characteristics of the sample size are consistent with the distribution pattern of the population of Chinese provinces in 2022 [87]. Therefore, we can consider that these samples are representative of the overall population of China.
Table 1 shows the demographic characteristics of the respondents, of which 347 (48.26%) were male and 372 (51.74%) were female, indicating a relatively balanced gender distribution. The largest age group was 25–34 years (32.27%), followed by 35–44 years (25.73%), 18–24 years (21.28%), 45–59 years (14.05%), and over 60 years (6.67%). A significant majority of respondents reported having a university education (70.65%). One possible reason for this is that individuals with higher education tend to have greater awareness and willingness to engage with environmental issues and social public affairs. Regarding income, 29.07% of respondents reported a monthly income of 3001–5000 RMB, and 27.12% reported earning 5001–8000 RMB per month. Most respondents reported that they visit pocket parks five or more times per month on average (68.15%), indicating that pocket parks have become indispensable venues for daily activities and leisure for citizens. To ascertain if there is a risk of non-response bias affecting statistical results, we conducted a difference test between early and late respondents using respondents’ demographic characteristics. Assuming that late responders are closer to non-responders, we classified late responders as non-responders, while early responders were considered responders. The Chi-square test results showed that gender (χ2 = 0.360, p = 0.549), age (χ2 = 7.770, p = 0.103), education level (χ2 = 5.200, p = 0.257), and monthly income (χ2 = 6.737, p = 0.241). Accordingly, the non-response bias has no serious impact on this study.

4. Analysis and Results

4.1. Measurement Model Assessment

Partial least squares structural equation modeling (PLS-SEM) is widely used for predictive and exploratory studies [88]. Therefore, this study applied the PLS-SEM method for empirical analysis. A confirmatory factor analysis (CFA) was conducted to assess the reliability and validity of the variables. Cronbach’s α and composite reliability (CR) are indicators for testing reliability. Table 2 demonstrates the high reliability and validity of the total scale (Cronbach’s α = 0.945, KMO = 0.946, Bartlett’s sphericity test p < 0.001). The Cronbach’s α values for all constructs range from 0.841 to 0.908, exceeding the criterion of 0.7 [89]. The CR values for each latent variable are above 0.9 (0.900–0.933). This indicates the strong internal consistency and reliability of the measurement model. The average variance extraction (AVE) values are all above the threshold of 0.5 (0.694–0.778). Standardized factor loadings for all items are significant and range from 0.756 to 0.899, surpassing the recommended level of 0.7 [90]. In the exploratory factor analysis (EFA), seven principal components with eigenvalues exceeding 1.0 were extracted using the maximum variance rotation method. The cumulative variance explained is 75.012%, well above the threshold of 50%. The first factor accounts for merely 12.89% of the total variance, indicating ideal structural validity.
The results of discriminant validity tests are presented in Table 3 and Table 4. The correlation coefficients of each pair of latent variables are less than the square root of their respective AVE values and do not exceed 0.7, satisfying the criteria established by Fornell and Larcker [91]. Additionally, all constructs’ heterotrait–monotrait (HTMT) values are below the criterion of 0.85 [92], confirming excellent discriminant validity for the model. Moreover, the variance inflation factor (VIF) values for the measurement model range from 1.626 to 2.914, which are below the criterion of 4 [93]. This indicates that there is no collinearity between the latent variables.

4.2. Structural Model Assessment

The structural model was evaluated using the coefficient of determination values (R2), predictive relevance (Q2), normed fit index (NFI), and standardized root mean square residual (SRMR) values. R2PU was 0.353, implying that HR and EQ explain 35.3% of the variance of PU. R2AC, R2AR, and R2PN were 0.319, 0.302, and 0.398, respectively. R2IPPPG was 0.441, implying that all of the external dependent variables explained 44.1% of its variance. Cohen argues that R2 values of 0.02, 0.13, and 0.26 represent, in order, weak, moderate, and substantial explanatory power [94]. Consequently, the structural model had a strong explanatory power. All Q2 values exceeded 0 (Q2PU = 0.258, Q2AC = 0.248, Q2AR = 0.232, Q2PN = 0.299, and Q2IPPPG = 0.339), proving robust predictive power [95]. The SRMR value was 0.038, which was below the threshold of 0.08 [96]. The value of NFI was 0.912, surpassing the criterion of 0.9 [97]. Hence, the structural model exhibited a satisfactory fit and was suitable for explaining the actual observed data.
Empirical tests were executed employing 5000 resample bootstrap calculations of Smart PLS 3.0. Table 5 displays the testing results of direct relationships among the variables. At the information processing stage, HR (β = 0.380, t = 8.964, p < 0.001) and EQ (β = 0.338, t = 7.972, p < 0.001) were positively associated with PU, thus providing support for H1 and H2. Moreover, HR had a higher influence than EQ. At the norm activation stage, we examined whether HR, EQ, and PU could help the formation of moral norms and tested the relationship among AC, AR, and PN. HR was found to have a significant positive effect on AC (β = 0.309, t = 6.757, p < 0.001) and AR (β = 0.266, t = 5.535, p < 0.001), which supported H4 and H5. However, the findings show that HR had no direct effect on PN (β = 0.077, t = 1.458, p > 0.05), so H6 was not supported. As expected, EQ was found to have positive effects on AC (β = 0.210, t = 4.398, p < 0.001), AR (β = 0.108, t = 2.212, p < 0.05), and PN (β = 0.109, t = 2.444, p < 0.05), thereby supporting H7, H8, and H9. Additionally, PU had positive effects on AC (β = 0.190, t = 3.797, p < 0.001), AR (β = 0.150, t = 2.842, p < 0.01) and PN (β = 0.298, t = 5.229, p < 0.001), thereby demonstrating that H10, H11, and H12 were supported. In terms of the component of the NAM, AC positively affected AR (β = 0.269, t = 5.474, p < 0.001), which supported H13. Similarly, AC (β = 0.189, t = 3.565, p < 0.001) and AR (β = 0.163, t = 3.253, p < 0.01) also had positive effects on PN. Thus, H14 and H15 were supported. Finally, the hypotheses at the behavioral intention transformation stage were tested. The significant effect between HR and IPPPG was absent (β = 0.076, t = 1.658, p > 0.05), thus rejecting H16. EQ was a positive and significant predictor of IPPPG (β = 0.101, t = 2.098, p < 0.05). Consequently, H17 was supported. Additionally, the results show that PU had a positive impact on IPPPG (β = 0.141, t = 2.377, p < 0.05), thus confirming H18. Constructs of the NAM, AC (β = 0.185, t = 3.602, p < 0.001), AR (β = 0.111, t = 2.177, p < 0.05), and PN (β = 0.274, t = 4.486, p < 0.001) were positively associated with IPPPG. Therefore, H19, H20, and H21 were fully supported.
Hierarchical multiple regression was employed to test the moderating effect of HR on the relationship between EQ and PU. The results did not support H3 (β = −0.024, t = −1.169, p = 0.243), indicating that HR did not moderate the relationship between EQ and PU.
This study tested the chain-mediated relationship using the bootstrap method proposed by Preacher and Hayes [98]. The SPSS PROCESS MODEL 6, developed by Hayes [99], was used for this analysis, with a bootstrap sample of 5000 and a confidence interval of 95%). We focused on analyzing the chain mediation with IPPPG as the dependent variable, HR and EQ as the independent variables, and PU, AR, AC, and PN as the mediating variables. Table 6 presents the results of the chain-mediated analysis. Confidence intervals (CI) for indirect effects that do not contain 0 indicate significant mediation effects. The total effect value is equal to the sum of the direct effect value and the total indirect effect value. The results indicate a significant mediated relationship between HR and IPPPG (β = 0.389, 95% CI = [0.312, 0,477]). Likewise, the mediating relationship between EQ and IPPPG was also significant (β = 0.346, 95% CI = [0.277, 0.425]). Regarding total effects, HR had a more significant impact on IPPPG than EQ through a series of mediating variables. Additionally, the variable with the largest mediating effects of both HR and EQ on IPPPG was PU (β = 0.094, 95% CI = [0.034, 0.159] and β = 0.083, 95% CI = [0.025, 0.144], respectively).

5. Discussion

Encouraging citizens to use vital green space resources in a sustainable way is essential for coping with health risks, improving quality of life, and enhancing the sustainability of urban environments. This study combines social information processing theory and a norm activation model to develop and empirically test a theoretical framework for understanding citizens’ intentions to participate in pocket-park governance after COVID-19. It uncovers the complex associations among health risks, the environmental quality of pocket parks, perceived usefulness, moral norms, and behavioral intentions. The key findings are as follows.
First, in the information-processing stage, health risks and environmental quality positively impact the perceived usefulness of pocket parks. This finding indicates that citizens’ concerns about risks and their perceptions of environmental quality significantly influence their attitudes toward pocket parks. Contextual information helps individuals assess the value of pocket parks. This study aligns with Wan et al. [61], who consider perceived usefulness as a specific “instrumental attitude”. By focusing on specific attitudes like perceived usefulness, the study provides deeper insights into how external environmental factors and contextual information affect PEB intentions, offering a nuanced perspective compared to general attitude assessments. Interestingly, health risks do not moderate the relationship between environmental quality and perceived usefulness. This implies that the transformation from physical environmental appearance to cognitive attitudes may not be affected by complex environmental changes. Given that pocket parks have become indispensable places in citizens’ daily lives, even amid low-risk scenarios, a well-maintained pocket park is still conducive to helping citizens recognize its benefits [46].
Second, in the norm-activation stage, environmental quality and perceived usefulness all positively affect moral norm factors. A positive environmental appearance signals that the park should not be subject to pollution, akin to a social norm. Citizens may internalize the external pressure into personal norms. These findings are consistent with previous studies [46]. Similarly, perceiving pocket parks as useful leads individuals to recognize the potential costs of polluting them, reinforcing their sense of responsibility and personal norms. Surprisingly, the influence of health risks on personal norms is not significant, which may contradict some existing perspectives [43]. In response to this finding, this study offers a unique interpretation: health risks are typically short-term and urgent, prompting individuals to take immediate, reactive measures such as reducing travel or wearing masks. In contrast, personal norms related to environmental governance are rooted in long-established internal values and a sense of moral duty. In a crisis situation, individuals are likely to prioritize self-protection over considerations of benefiting others. This temporal difference weakens the significant positive influence of health risks on personal norms. However, results do support significant positive relationships between health risks and awareness of consequences, as well as ascription of responsibility, which are consistent with prior viewpoints [40]. Increased knowledge about health risks enhances individuals’ understanding of the consequences of damaging pocket parks.
Furthermore, this study provides evidence supporting the positive impact of pocket-park environmental quality and perceived usefulness on behavioral intentions to participate in pocket-park governance, thereby validating the applicability of SIPT in PEB research. External contextual information indeed alters individuals’ perceptions and attitudes, ultimately translating into behavioral intentions. These findings are in line with previous studies [46,67]. When citizens recognize the benefits provided by USG, they are motivated to prevent pocket parks from harm. Nevertheless, contrary to expectations, this study found that health risks do not directly affect intention to participate, which contrasts with findings from several studies [100]. Some evidence suggests that health-related risks may not drive environmentally responsible behaviors, possibly due to overwhelming fear [101,102] or being discouraged by limited conditions [103]. It is plausible that citizens may not sufficiently associate health risks with the importance and urgency of protecting pocket parks, indicating a potential gap in public understanding.
Finally, the components of the NAM positively affect the intention to participate. Awareness of consequences positively influences the ascription of responsibility. Personal norms are also positively influenced by the above two factors. These findings align with the underlying assumptions of the NAM, as extensively validated in earlier studies [51,55]. Furthermore, chain-mediated effects involving specific attitudes (i.e., perceived usefulness), along with moral norm factors, have also been supported. Health risks and environmental quality ultimately contribute to the formation of intention to participate in governance by altering individual attitudes toward pocket parks and activating moral norms. Notably, perceived usefulness emerges as the pivotal factor among all indirect effects, underscoring its critical role in shaping citizens’ intention to participate in pocket-park environmental governance.

5.1. Theoretical Contributions

Firstly, the current study reveals the mechanism influencing citizens’ intention to participate in pocket-park governance, while recent studies have highlighted the importance of preserving pocket parks in densely populated cities and communities after COVID-19 [12,19]. Nevertheless, empirical research from the PEB perspective remains unprecedented. Addressing this gap, the present study responds to scholars’ calls by framing participation in pocket-park governance as an altruistic Pu-PEB. The empirical findings elucidate how citizens’ intentions to voluntarily participate in pocket-park environmental governance are shaped. We provide a theoretical basis for clarifying the pathway of guiding citizen participation. To the best of our knowledge, while some scholars have explored citizens’ intentions to participate in green-space governance, this has not been conducted in the context of health risks [26]. Therefore, this study contributes significantly to the literature on sustainable governance of small urban parks in response to post-COVID-19 risks from the perspective of environmental psychology.
Secondly, this study extends prior literature by developing a new conceptual model integrating SIPT and the NAM. We take external environmental information (health risks and environmental quality), cognitive attitudes (perceived usefulness), and internal moral norms as antecedents of intention to participate. A novelty compared to previous studies is that we clarify the three-stage process through which the intention to participate in environmental governance is formed after health crises, particularly in terms of activating perceived usefulness and moral norms. Integrating these two theories allows for a comprehensive and thorough understanding of the underlying mechanisms. Consequently, the findings expand the application of SIPT within the domain of PEB research.
Last but not least, the findings empirically substantiate the critical roles of health risks and UGS attributes in the context of crises in predicting citizens’ attitudes and intentions to participate, with attitudes and norms mediating these effects. Departing from Wan et al.’s assertion that “perceived usefulness”, rather than “behavioral attitudes” [61], serves as an independent variable for measuring specific environmental attitudes, this study focuses on the role of risks in shaping perceptions and recognizing the value of specific environments in health crises scenarios, moving beyond general “environmental knowledge” [68]. Another unique contribution lies in examining the direct impact of environmental quality on perceived usefulness. By constructing these variables and exploring their interrelationships, this study enhances the precision of predictive models to explain PEB.

5.2. Managerial Implications

From a practical standpoint, this study provides critical insights for the government to devise strategies that can change citizens’ attitudes, strengthen moral norms, encourage citizens to protect pocket parks, and thereby promote sustainable management of pocket parks after health crises. Firstly, health risks significantly enhance the perceived usefulness of pocket parks, subsequently boosting intentions to participate in governance. Notably, the effect size of health risks on perceived usefulness is the largest (β = 0.380). This effect underscores the heightened sense of fear and personal relevance citizens feel when confronted with information about health crises. It highlights the importance for managers to emphasize the utilitarian value of pocket parks, particularly during disease outbreaks. Despite residents’ preference for small parks close to their homes, the concept of “pocket parks” remains relatively unfamiliar. Hence, governmental efforts should prioritize educational campaigns, community activities, and innovative initiatives to encourage local use of pocket parks and to reap physical and mental benefits [104].
Secondly, awareness of consequences, ascription of responsibility, and personal norms have positive effects on the intention to participate in governance. These variables also mediate the influences of health risks and environmental quality on PEB intention. In light of these findings, managers should emphasize to citizens that behaviors such as spitting and littering in parks (e.g., discarded masks and leftover food) can directly cause virus transmission. It is crucial to help citizens connect the pocket-park environmental governance with reducing physical illness and improving quality of life while also realizing that clean and comfortable green spaces are beneficial for preparing for future health emergencies. The most essential work remains extensive environmental education, particularly in addressing intentional destruction during COVID-19 [33]. Once citizens understand that polluting pocket-park environments may adversely affect their health and daily lives, they are likely to adjust their behaviors. Additionally, anthropomorphic slogans in pocket parks can remind people to keep these spaces clean and reinforce feelings of guilt about negative actions. However, avoiding excessive usage is equally important as this might lead to reduced greenery.
Furthermore, research findings indicate that good environmental quality is also conducive to enhancing perceived usefulness, moral norms, and intentions to participate. Apart from this, the effect of environmental quality on perceived usefulness is not moderated by health risks. Thus, maintaining the clean and attractive appearance of all pocket parks scattered in the city should be a priority for governments, even during health crises. Post-pandemic, high-quality urban parks have become ideal destinations. However, due to lockdown policies, sanitation staff may have been neglectful in cleaning pocket parks. As it turns out, elegant landscapes can heighten citizens’ potential environmental responsibility and deter undesirable behaviors. As noted by Liu et al. [46], initial impressions are more impactful than subsequent interventions. On another note, the conversion of urban vacant land into pocket parks is an effort to improve the management of unforeseen risks and the resilience of UGS. The supply of adequate infrastructure, such as bins for convenience of waste disposal, can increase citizens’ commitment to maintaining the cleanliness of pocket parks [33,46]. This study emphasizes that both environmental protection agencies and neighborhood committees must improve their daily management and cleaning practices of pocket parks, even though these areas are just small and unassuming corners within a large city.

5.3. Limitations and Future Research

It must be acknowledged that this study has certain limitations, which can be improved in future research. First, we only examined citizens’ intentions to participate in pocket-park governance rather than actual behaviors. Some previous studies have demonstrated that there are often gaps between intention and behavior [105]. Thus, future research could employ longitudinal or experimental approaches to investigate citizens’ actual participation behaviors. Notably, although this research extends the NAM by considering external environmental information and specific attitudes, future studies could introduce additional factors, such as media influence and self-efficacy in coping with risks. In addition, the measurement of the environmental quality of pocket parks could be divided into multiple dimensions, enabling a more detailed discussion on which green-space attributes are more likely to stimulate citizens to engage in PEB. It would also be valuable to use multi-source data to collect the specific residential location of respondents to determine whether the severity of health risks in different areas (e.g., the number of confirmed cases) moderates the relationship between citizens’ attitudes and intentions. Finally, due to the unpredictable nature of public health emergencies, we recommend that researchers could extend this study when a new crisis occurs to comprehensively discuss whether more meaningful results emerge.

6. Conclusions

PEB is a long-lasting topic in urban governance issues, particularly in the context of frequent public crises and high-density urbanization. Focusing on pocket parks, which are small but important components of UGS, this study identifies the factors and yields a conceptual framework for shaping citizens’ intention to participate in governance after experiencing COVID-19 based on the NAM and SIPT. We shed light upon the relationships between the external environmental factors, attitudes, norms, and intentions using PLS-SEM method. The findings indicate that health risks and environmental quality have positive impacts on citizens’ perceptions and attitudes towards pocket parks. Perceived usefulness and moral norms significantly mediate the relationship between the external environment and the intention to participate. This paper advances the growth of the theoretical literature on pocket parks from citizens’ participatory PEB perspective and provides empirical evidence for pocket-park governance policies through a quantitative approach. In conclusion, urban greening authorities should build pocket parks with better landscape quality, such as fresh air, lush vegetation, clean trails, and convenient facilities. It is also essential to publicize that using pocket parks is an effective strategy to counteract urban public crises and health risks. These measures will increase citizens’ perception of the usefulness of pocket parks and thus encourage active participation in the UGS governance process.

Author Contributions

Conceptualization, J.Z. (Jing Zhang) and Z.L.; methodology, J.Z. (Jing Zhang) and Z.L.; software, J.Z. (Jing Zhang) and J.Z. (Jialong Zhong); validation, J.Z. (Jing Zhang), Z.L. and J.Z. (Jialong Zhong); formal analysis, Z.L.; investigation, J.Z. (Jing Zhang); resources, Z.L. and J.Z. (Jialong Zhong); data curation, J.Z. (Jing Zhang); writing—original draft preparation, J.Z. (Jing Zhang); writing—review and editing, Z.L.; visualization, J.Z. (Jialong Zhong); supervision, Z.L.; project administration, Z.L.; funding acquisition, Z.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Social Science Fund of China, grant number 19XJY003, and the Project of Chengdu Park City Demonstration Zone Construction Research Center, grant number GYCS2024-YB004.

Data Availability Statement

The data presented in this study are available on request.

Conflicts of Interest

The authors declare no conflicts of interest.

Appendix A

Table A1. Items to measure the study constructs.
Table A1. Items to measure the study constructs.
ConstructsItemsItemsSources
Health risksHR1Infectious diseases are likely to negatively affect my daily routine/life.[42,86]
HR2There is a high risk of contracting diseases.
HR3The consequence of getting infected by diseases is severe.
HR4I am worried I might contract diseases.
Environmental qualityEQ1I think this pocket park is very clean.[46,62]
EQ2I think the eco-landscapes of this pocket park are protected pretty well.
EQ3The greening efforts of this pocket park are good.
EQ4I think the air quality of this pocket park is pretty good.
EQ5This pocket park provides sufficient environmental facilities (e.g., garbage bins).
Perceived usefulnessPU1Pocket parks provide usable green spaces during the pandemic.[62,80]
PU2Pocket parks provide opportunities to do physical exercise.
PU3Pocket parks provide opportunities for recreation and relaxation.
PU4Using pocket parks helps with physical health and reduces disease risk.
PU5Pocket parks contribute to my quality of life during the pandemic.
Awareness of consequencesAC1Environmentally unfriendly behaviors will damage the environment of pocket parks.[51,55]
AC2Environmentally unfriendly behaviors in pocket parks greatly increase the probability of disease transmission.
AC3Environmentally unfriendly behaviors in pocket parks may have negative impacts on physical health.
AC4Environmentally unfriendly behaviors in pocket parks are not conducive to resisting disease risks.
Ascription of responsibilityAR1I feel joint responsibility for environmental harm in pocket parks.
AR2I feel jointly responsible for the environmental pollution problems in pocket parks.
AR3I believe that every citizen is partly responsible for the environmental damage of pocket parks.
AR4I feel that every citizen must take responsibility for the environmental pollution of pocket parks.
Personal normsPN1I feel obliged to protect pocket parks.[51]
PN2I would feel guilty about not taking pro-environmental behaviors in pocket parks.
PN3It would be against my moral principles not to take pro-environmental behaviors in pocket parks.
Intention to participate in pocket-park governanceIPPPG1I am willing to take environmental behaviors to maintain the cleanliness of pocket parks.[26]
IPPPG2I would certainly think about participating in pocket-park environmental governance.
IPPPG3I think I would like to participate in pocket-park environmental governance.
IPPPG4I will participate in pocket-park environmental governance if I have an opportunity.

References

  1. WHO. Coronavirus Disease (COVID-19). 2023. Available online: https://www.who.int/news-room/fact-sheets/detail/coronavirus-disease-(covid-19) (accessed on 23 September 2024).
  2. Ma, F. Assessing Immediate and Lasting Impacts of COVID-19-Induced Isolation on Green Space Usage Patterns. GeoHealth 2024, 8, e2024GH001062. [Google Scholar] [CrossRef] [PubMed]
  3. Lin, B.B.; Chang, C.-C.; Astell-Burt, T.; Feng, X.; Gardner, J.; Andersson, E. Nature experience from yards provide an important space for mental health during COVID-19. NPJ Urban Sustain. 2023, 3, 14. [Google Scholar] [CrossRef]
  4. Labib, S.; Browning, M.H.; Rigolon, A.; Helbich, M.; James, P. Nature’s contributions in coping with a pandemic in the 21st century: A narrative review of evidence during COVID-19. Sci. Total Environ. 2022, 833, 155095. [Google Scholar] [CrossRef]
  5. Marchi, V.; Speak, A.; Ugolini, F.; Sanesi, G.; Carrus, G.; Salbitano, F. Attitudes towards urban green during the COVID-19 pandemic via Twitter. Cities 2022, 126, 103707. [Google Scholar] [CrossRef] [PubMed]
  6. Suligowski, R.; Ciupa, T. Five waves of the COVID-19 pandemic and green–blue spaces in urban and rural areas in Poland. Environ. Res. 2023, 216, 114662. [Google Scholar] [CrossRef]
  7. Wu, N.; Tian, Q.; Cui, M.; He, M. A delicacy evaluation method for park walkability considering multidimensional quality heterogeneity. J. Transp. Geogr. 2023, 112, 103688. [Google Scholar] [CrossRef]
  8. Ding, X.; Zhao, Z.; Zheng, J.; Yue, X.; Jin, H.; Zhang, Y. Community Gardens in China: Spatial distribution, patterns, perceived benefits and barriers. Sustain. Cities Soc. 2022, 84, 103991. [Google Scholar] [CrossRef]
  9. WB. Urban Population (The Percentage of Total Population). 2022. Available online: https://data.worldbank.org.cn/indicator/SP.URB.TOTL.IN.ZS?end=2022&start=1960&view=chart (accessed on 10 November 2023).
  10. NBS. China Statistical Yearbook. 2022. Available online: https://www.stats.gov.cn/sj/ndsj/2022/indexch.htm (accessed on 22 November 2023).
  11. UN-Habitat. World Cities Report. 2022. Available online: https://unhabitat.org/world-cities-report-2022 (accessed on 22 November 2023).
  12. Li, H.; Wei, Y.D. COVID-19, cities and inequality. Appl. Geogr. 2023, 160, 103059. [Google Scholar] [CrossRef]
  13. Khalilnezhad, M.R.; Ugolini, F.; Massetti, L. Attitudes and Behaviors toward the Use of Public and Private Green Space during the COVID-19 Pandemic in Iran. Land 2021, 10, 1085. [Google Scholar] [CrossRef]
  14. Kerishnan, P.B.; Maruthaveeran, S.; Maulan, S. Investigating the usability pattern and constraints of pocket parks in Kuala Lumpur, Malaysia. Urban For. Urban Green. 2020, 50, 126647. [Google Scholar] [CrossRef]
  15. MHURD. Notice on Promoting the Construction of Pocket Parks. 2022. Available online: https://www.mohurd.gov.cn/gongkai/zhengce/zhengcefilelib/202208/20220808_767496.html (accessed on 22 November 2023).
  16. Maury-Mora, M.; Gómez-Villarino, M.T.; Varela-Martínez, C. Urban green spaces and stress during COVID-19 lockdown: A case study for the city of Madrid. Urban For. Urban Green. 2022, 69, 127492. [Google Scholar] [CrossRef] [PubMed]
  17. Ugolini, F.; Massetti, L.; Calaza-Martínez, P.; Cariñanos, P.; Dobbs, C.; Ostoić, S.K.; Marin, A.M.; Pearlmutter, D.; Saaroni, H.; Šaulienė, I.; et al. Effects of the COVID-19 pandemic on the use and perceptions of urban green space: An international exploratory study. Urban For. Urban Green. 2020, 56, 126888. [Google Scholar] [CrossRef] [PubMed]
  18. Chen, L.; Liu, L.; Wu, H.; Peng, Z.; Sun, Z. Change of Residents’ Attitudes and Behaviors toward Urban Green Space Pre- and Post- COVID-19 Pandemic. Land 2022, 11, 1051. [Google Scholar] [CrossRef]
  19. Liu, S.; Wang, X. Reexamine the value of urban pocket parks under the impact of the COVID-19. Urban For. Urban Green. 2021, 64, 127294. [Google Scholar] [CrossRef]
  20. Lin, P.; Lau, S.S.Y.; Qin, H.; Gou, Z. Effects of urban planning indicators on urban heat island: A case study of pocket parks in high-rise high-density environment. Landsc. Urban Plan. 2017, 168, 48–60. [Google Scholar] [CrossRef]
  21. Ma, D.; Wang, Y.; Zhou, D.; Zhu, Z. Cooling effect of the pocket park in the built-up block of a city: A case study in Xi’an, China. Environ. Sci. Pollut. Res. 2023, 30, 23135–23154. [Google Scholar] [CrossRef]
  22. Zhong, J.; Liu, J.; Xu, Y.; Liang, G. Pedestrian-level gust wind flow and comfort around a building array–Influencing assessment on the pocket park. Sustain. Cities Soc. 2022, 83, 103953. [Google Scholar] [CrossRef]
  23. Naghibi, M.; Faizi, M.; Ekhlassi, A. Design possibilities of leftover spaces as a pocket park in relation to planting enclosure. Urban For. Urban Green. 2021, 64, 127273. [Google Scholar] [CrossRef]
  24. Rosso, F.; Pioppi, B.; Pisello, A.L. Pocket parks for human-centered urban climate change resilience: Microclimate field tests and multi-domain comfort analysis through portable sensing techniques and citizens’ science. Energy Build. 2022, 260, 111918. [Google Scholar] [CrossRef]
  25. Kerishnan, P.B.; Maruthaveeran, S. Factors contributing to the usage of pocket parks―A review of the evidence. Urban For. Urban Green. 2021, 58, 126985. [Google Scholar] [CrossRef]
  26. Huang, Y.; Aguilar, F.; Yang, J.; Qin, Y.; Wen, Y. Predicting citizens’ participatory behavior in urban green space governance: Application of the extended theory of planned behavior. Urban For. Urban Green. 2021, 61, 127110. [Google Scholar] [CrossRef]
  27. Ge, T.; Hao, X.; Li, J. Effects of public participation on environmental governance in China: A spatial Durbin econometric analysis. J. Clean. Prod. 2021, 321, 129042. [Google Scholar] [CrossRef]
  28. Jones, J.; Russo, A. Exploring the role of public participation in delivering inclusive, quality, and resilient green infrastructure for climate adaptation in the UK. Cities 2024, 148, 104879. [Google Scholar] [CrossRef]
  29. Csomós, G.; Farkas, J.Z.; Szabó, B.; Bertus, Z.; Kovács, Z. Exploring the use and perceptions of inner-city small urban parks: A case study of Budapest, Hungary. Urban For. Urban Green. 2023, 86, 128003. [Google Scholar] [CrossRef]
  30. Chen, L.; Zhou, Q.; Yue, L.; Wu, M.; Huang, R.; Yuen, K.F.; Su, R. A theoretical model for preventing marine litter behaviour: An empirical evidence from Singapore. J. Clean. Prod. 2023, 427, 139109. [Google Scholar] [CrossRef]
  31. Pham, T.B.N.; Vu, B.P.; Huynh, T.T.H.; Vu, D.H. Factors driving plastic-related behaviours: Towards reducing marine plastic waste in Hoi An, Vietnam. J. Clean. Prod. 2023, 427, 139179. [Google Scholar] [CrossRef]
  32. Primack, R.B.; Terry, C. New social trails made during the pandemic increase fragmentation of an urban protected area. Biol. Conserv. 2021, 255, 108993. [Google Scholar] [CrossRef]
  33. Tansil, D.; Plecak, C.; Taczanowska, K.; Jiricka-Pürrer, A. Experience Them, Love Them, Protect Them—Has the COVID-19 Pandemic Changed People’s Perception of Urban and Suburban Green Spaces and Their Conservation Targets? Environ. Manag. 2022, 70, 1004–1022. [Google Scholar] [CrossRef] [PubMed]
  34. Li, D.; Zhao, L.; Ma, S.; Shao, S.; Zhang, L. What influences an individual’s pro-environmental behavior? A literature review. Resour. Conserv. Recycl. 2019, 146, 28–34. [Google Scholar] [CrossRef]
  35. Steg, L.; Vlek, C. Encouraging pro-environmental behaviour: An integrative review and research agenda. J. Environ. Psychol. 2009, 29, 309–317. [Google Scholar] [CrossRef]
  36. Ertz, M.; Karakas, F.; Sarigöllü, E. Exploring pro-environmental behaviors of consumers: An analysis of contextual factors, attitude, and behaviors. J. Bus. Res. 2016, 69, 3971–3980. [Google Scholar] [CrossRef]
  37. Sun, J.; Ma, B.; Wei, S. Same gratitude, different pro-environmental behaviors? Effect of the dual-path influence mechanism of gratitude on pro-environmental behavior. J. Clean. Prod. 2023, 415, 137779. [Google Scholar] [CrossRef]
  38. Esfandiar, K.; Dowling, R.; Pearce, J.; Goh, E. Personal norms and the adoption of pro-environmental binning behaviour in national parks: An integrated structural model approach. J. Sustain. Tour. 2020, 28, 10–32. [Google Scholar] [CrossRef]
  39. Zhang, Y.; Moyle, B.D.; Jin, X. Fostering visitors’ pro-environmental behaviour in an urban park. Asia Pac. J. Tour. Res. 2018, 23, 691–702. [Google Scholar] [CrossRef]
  40. Bouman, T.; Steg, L.; Dietz, T. Insights from early COVID-19 responses about promoting sustainable action. Nat. Sustain. 2021, 4, 194–200. [Google Scholar] [CrossRef]
  41. Nketiah, E.; Song, H.; Cai, X.; Adjei, M.; Obuobi, B.; Adu-Gyamfi, G.; Cudjoe, D. Predicting citizens’ recycling intention: Incorporating natural bonding and place identity into the extended norm activation model. J. Clean. Prod. 2022, 377, 134425. [Google Scholar] [CrossRef]
  42. O’connor, P.; Assaker, G. COVID-19’s effects on future pro-environmental traveler behavior: An empirical examination using norm activation, economic sacrifices, and risk perception theories. J. Sustain. Tour. 2021, 30, 89–107. [Google Scholar] [CrossRef]
  43. Zhang, J.; Quoquab, F.; Mohammad, J. The role of pandemic risk communication and perception on pro-environmental travel behavioral intention: Findings from PLS-SEM and fsQCA. J. Clean. Prod. 2023, 429, 139506. [Google Scholar] [CrossRef]
  44. Dipeolu, A.A.; Ibem, E.O.; Fadamiro, J.A.; Fadairo, G. Factors influencing residents’ attitude towards urban green infrastructure in Lagos Metropolis, Nigeria. Environ. Dev. Sustain. 2021, 23, 6192–6214. [Google Scholar] [CrossRef]
  45. Lee, W.; Jeong, C. Effects of pro-environmental destination image and leisure sports mania on motivation and pro-environmental behavior of visitors to Korea’s national parks. J. Destin. Mark. Manag. 2018, 10, 25–35. [Google Scholar] [CrossRef]
  46. Liu, J.; Wu, J.S.; Che, T. Understanding perceived environment quality in affecting tourists’ environmentally responsible behaviours: A broken windows theory perspective. Tour. Manag. Perspect. 2019, 31, 236–244. [Google Scholar] [CrossRef]
  47. Salancik, G.R.; Pfeffer, J. A social information processing approach to job attitudes and task design. Adm. Sci. Q. 1978, 23, 224–253. [Google Scholar] [CrossRef] [PubMed]
  48. Schwartz, S.H. Normative influences on altruism. Adv. Exp. Soc. Psychol. 1977, 10, 221–279. [Google Scholar]
  49. Rosenthal, S.; Yu, M.S. Anticipated guilt and anti-littering civic engagement in an extended norm activation model. J. Environ. Psychol. 2022, 80, 101757. [Google Scholar] [CrossRef]
  50. Wang, S.; Wang, J.; Zhao, S.; Yang, S. Information publicity and resident’s waste separation behavior: An empirical study based on the norm activation model. Waste Manag. 2019, 87, 33–42. [Google Scholar] [CrossRef]
  51. Zhang, X.; Liu, J.; Zhao, K. Antecedents of citizens’ environmental complaint intention in China: An empirical study based on norm activation model. Resour. Conserv. Recycl. 2018, 134, 121–128. [Google Scholar] [CrossRef]
  52. De Groot, J.I.M.; Steg, L. Morality and Prosocial Behavior: The Role of Awareness, Responsibility, and Norms in the Norm Activation Model. J. Soc. Psychol. 2009, 149, 425–449. [Google Scholar] [CrossRef] [PubMed]
  53. Onwezen, M.C.; Antonides, G.; Bartels, J. The Norm Activation Model: An exploration of the functions of anticipated pride and guilt in pro-environmental behaviour. J. Econ. Psychol. 2013, 39, 141–153. [Google Scholar] [CrossRef]
  54. Esfandiar, K.; Dowling, R.; Pearce, J.; Goh, E. What a load of rubbish! The efficacy of theory of planned behaviour and norm activation model in predicting visitors’ binning behaviour in national parks. J. Hosp. Tour. Manag. 2021, 46, 304–315. [Google Scholar] [CrossRef]
  55. He, X.; Zhan, W. How to activate moral norm to adopt electric vehicles in China? An empirical study based on extended norm activation theory. J. Clean. Prod. 2018, 172, 3546–3556. [Google Scholar] [CrossRef]
  56. Ferguson, M.; Barry, B. I Know What You Did: The Effects of Interpersonal Deviance on Bystanders. J. Occup. Health Psychol. 2011, 16, 80–94. [Google Scholar] [CrossRef] [PubMed]
  57. Zhang, J.; Xie, C.; Morrison, A.M.; Zhang, K. Fostering resident pro-environmental behavior: The roles of destination image and Confucian culture. Sustainability 2020, 12, 597. [Google Scholar] [CrossRef]
  58. Davis, F.D. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 1989, 13, 319–340. [Google Scholar] [CrossRef]
  59. Wang, S.; Wang, J.; Li, J.; Wang, J.; Liang, L. Policy implications for promoting the adoption of electric vehicles: Do consumer’s knowledge, perceived risk and financial incentive policy matter? Transp. Res. Part A Policy Pract. 2018, 117, 58–69. [Google Scholar] [CrossRef]
  60. Rajaee, M.; Hoseini, S.M.; Malekmohammadi, I. Proposing a socio-psychological model for adopting green building technologies: A case study from Iran. Sustain. Cities Soc. 2019, 45, 657–668. [Google Scholar] [CrossRef]
  61. Wan, C.; Shen, G.Q.; Choi, S. The moderating effect of subjective norm in predicting intention to use urban green spaces: A study of Hong Kong. Sustain. Cities Soc. 2018, 37, 288–297. [Google Scholar] [CrossRef]
  62. Wan, C.; Shen, G.Q. Encouraging the use of urban green space: The mediating role of attitude, perceived usefulness and perceived behavioural control. Habitat Int. 2015, 50, 130–139. [Google Scholar] [CrossRef]
  63. Arnberger, A.; Eder, R. The influence of green space on community attachment of urban and suburban residents. Urban For. Urban Green. 2012, 11, 41–49. [Google Scholar] [CrossRef]
  64. Pennings, J.M.E.; Smidts, A. The shape of utility functions and organizational behavior. Manag. Sci. 2003, 49, 1251–1263. [Google Scholar] [CrossRef]
  65. Xie, Y.; Ma, W.; Tong, Z. How counterfactual thinking affects willingness to consume green restaurant products: Mediating role of regret and moderating role of COVID-19 risk perception. J. Hosp. Tour. Manag. 2023, 55, 344–354. [Google Scholar] [CrossRef]
  66. Garretson, J.A.; Burton, S. Highly coupon and sale prone consumers: Benefits beyond price savings. J. Advert. Res. 2003, 43, 162–172. [Google Scholar] [CrossRef]
  67. Zebardast, L.; Radaei, M. The influence of global crises on reshaping pro-environmental behavior, case study: The COVID-19 pandemic. Sci. Total Environ. 2022, 811, 151436. [Google Scholar] [CrossRef] [PubMed]
  68. Filgueira, T.O.; Castoldi, A.; Santos, L.E.R.; de Amorim, G.J.; de Sousa Fernandes, M.S.; do Nascimento Anastacio, W.d.L.; Campos, E.Z.; Santos, T.M.; Souto, F.O. The relevance of a physical active lifestyle and physical fitness on immune defense: Mitigating disease burden, with focus on COVID-19 consequences. Front. Immunol. 2021, 12, 587146. [Google Scholar] [CrossRef] [PubMed]
  69. Sassenrath, C.; Diefenbacher, S.; Pfattheicher, S.; Keller, J. The potential and limitations of empathy in changing health-relevant affect, cognition and behaviour. Eur. Rev. Soc. Psychol. 2022, 33, 255–288. [Google Scholar] [CrossRef]
  70. Si, W.; Jiang, C.; Meng, L. The Relationship between Environmental Awareness, Habitat Quality, and Community Residents’ Pro-Environmental Behavior—Mediated Effects Model Analysis Based on Social Capital. Int. J. Environ. Res. Public Health 2022, 19, 13253. [Google Scholar] [CrossRef] [PubMed]
  71. Addas, A.; Maghrabi, A. How did the COVID-19 pandemic impact urban green spaces? A multi-scale assessment of Jeddah megacity (Saudi Arabia). Urban For. Urban Green 2022, 69, 127493. [Google Scholar] [CrossRef]
  72. Lee, S.S.; Kim, Y.; Roh, T. Pro-environmental behavior on electric vehicle use intention: Integrating value-belief-norm theory and theory of planned behavior. J. Clean. Prod. 2023, 418, 138211. [Google Scholar] [CrossRef]
  73. Koleva, S.; Chankov, S. The Impact of the COVID-19 Pandemic on e-Commerce Consumers’ Pro-Environmental Behavior BT—Dynamics in Logistics; Freitag, M., Kinra, A., Kotzab, H., Megow, N., Eds.; Springer International Publishing: Berlin/Heidelberg, Germany, 2022; pp. 474–485. [Google Scholar]
  74. Corral-Verdugo, V.; Corral-Frías, N.S.; Frías-Armenta, M.; Lucas, M.Y.; Peña-Torres, E.F. Positive Environments and Precautionary Behaviors During the COVID-19 Outbreak. Front. Psychol. 2021, 12, 624155. [Google Scholar] [CrossRef]
  75. Zhu, W.; Yan, R.; Song, Y. Analysing the impact of smart city service quality on citizen engagement in a public emergency. Cities 2022, 120, 103439. [Google Scholar] [CrossRef]
  76. Macintyre, V.G.; Cotterill, S.; Anderson, J.; Phillipson, C.; Benton, J.S.; French, D.P. “I Would Never Come Here Because I’ve Got My Own Garden”: Older Adults’ Perceptions of Small Urban Green Spaces. Int. J. Environ. Res. Public Health 2019, 16, 1994. [Google Scholar] [CrossRef]
  77. Pourhossein, M.; Baker, B.J.; Dousti, M.; Behnam, M.; Tabesh, S. Embarking on the trail of sustainable harmony: Exploring the nexus of visitor environmental engagement, awareness, and destination social responsibility in natural parks. J. Destin. Mark. Manag. 2023, 30, 100821. [Google Scholar] [CrossRef]
  78. Corrado, L.; Fazio, A.; Pelloni, A. Pro-environmental attitudes, local environmental conditions and recycling behavior. J. Clean. Prod. 2022, 362, 132399. [Google Scholar] [CrossRef]
  79. Cudjoe, D.; Zhang, H.; Wang, H. Predicting residents’ adoption intention for smart waste classification and collection system. Technol. Soc. 2023, 75, 132399. [Google Scholar] [CrossRef]
  80. Wang, S.; Yung, E.H.K.; Jayantha, W.M.; Chan, E.H.W. Elderly’s intention and use behavior of urban parks: Planned behavior perspective. Habitat Int. 2023, 134, 102780. [Google Scholar] [CrossRef]
  81. He, X.; Hu, D.; Swanson, S.R.; Su, L.; Chen, X. Destination perceptions, relationship quality, and tourist environmentally responsible behavior. Tour. Manag. Perspect. 2018, 28, 93–104. [Google Scholar] [CrossRef]
  82. Wan, C.; Shen, G.Q.; Choi, S. The place-based approach to recycling intention: Integrating place attachment into the extended theory of planned behavior. Resour. Conserv. Recycl. 2021, 169, 105549. [Google Scholar] [CrossRef]
  83. MHURD. The Rapid Development of “Pocket Parks” in China. 2022. Available online: https://www.mohurd.gov.cn/xinwen/gzdt/202208/20220823_767673.html (accessed on 22 November 2023).
  84. Guo, W.; Chen, T.; Wei, Y. Intrinsic need satisfaction, emotional attachment, and value co-creation behaviors of seniors in using modified mobile government. Cities 2023, 141, 104529. [Google Scholar] [CrossRef]
  85. Tan, F.; Kuang, T.; Yang, D.; Jia, Z.; Li, R.; Wang, L. The higher the cuteness the more it inspires garbage sorting intention? J. Clean. Prod. 2023, 426, 139047. [Google Scholar] [CrossRef]
  86. Wen, H.; Liu-Lastres, B. Consumers’ dining behaviors during the COVID-19 pandemic: An Application of the Protection Motivation Theory and the Safety Signal Framework. J. Hosp. Tour. Manag. 2022, 51, 187–195. [Google Scholar] [CrossRef]
  87. NBS. The China Statistical Yearbook (CSY). 2023. Available online: https://www.stats.gov.cn/sj/ndsj/2023/indexch.htm (accessed on 23 September 2024).
  88. Hair, J.F.; Ringle, C.M.; Sarstedt, M. PLS-SEM: Indeed a silver bullet. J. Mark. Theory Pract. 2011, 19, 139–152. [Google Scholar] [CrossRef]
  89. Hair, J.F.; Hauff, S.; Hult, G.T.M.; Richter, N.F.; Ringle, C.M.; Sarstedt, M. A Primer on Partial Least Squares Structural Equation Modeling, 2nd ed.; SAGE Publications, Inc.: Los Angeles, CA, USA, 2016. [Google Scholar]
  90. Hair, J.F.; Sarstedt, M.; Pieper, T.M.; Ringle, C.M. The Use of Partial Least Squares Structural Equation Modeling in Strategic Management Research: A Review of Past Practices and Recommendations for Future Applications. Long Range Plan. 2012, 45, 320–340. [Google Scholar] [CrossRef]
  91. Fornell, C.; Larcker, D.F. Evaluating structural equation models with unobservable variables and measurement error. J. Mark. Res. 1981, 18, 39–50. [Google Scholar] [CrossRef]
  92. Henseler, J.; Ringle, C.M.; Sarstedt, M. A new criterion for assessing discriminant validity in variance-based structural equation modeling. J. Acad. Mark. Sci. 2015, 43, 115–135. [Google Scholar] [CrossRef]
  93. Hair, J.F.; Anderson, R.E.; Tatham, R.L.; Black, W.C. Multivariate Data Analysis, 5th ed.; Pearson Education: Upper Saddle River, NJ, USA, 1998. [Google Scholar]
  94. Cohen, J. Statistical Power Analysis for the Behavioral Science, 2nd ed.; Lawrence Erlbaum: Mahwah, NJ, USA, 1988. [Google Scholar]
  95. Hair, F.J., Jr.; Sarstedt, M.; Hopkins, L.; Kuppelwieser, V.G. Partial least squares structural equation modeling (PLS-SEM). Eur. Bus. Rev. 2014, 26, 106–121. [Google Scholar] [CrossRef]
  96. Hu, L.-T.; Bentler, P.M. Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification. Psychol. Methods 1998, 3, 424–453. [Google Scholar] [CrossRef]
  97. Hu, L.T.; Bentler, P.M. Cutoff Criteria for Fit Indexes in Covariance Structure Analysis: Conventional Criteria Versus New Alternatives. Struct. Equ. Model. Multidiscip. J. 1999, 6, 1–55. [Google Scholar] [CrossRef]
  98. Preacher, K.J.; Hayes, A.F. SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behav. Res. Methods Instrum. Comput. 2004, 36, 717–731. [Google Scholar] [CrossRef]
  99. Hayes, A.F. Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach; The Guilford Press: New York, NY, USA, 2013. [Google Scholar]
  100. Lucarelli, C.; Mazzoli, C.; Severini, S. Applying the Theory of Planned Behavior to Examine Pro-Environmental Behavior: The moderating effect of COVID-19 beliefs. Sustainability 2020, 12, 10556. [Google Scholar] [CrossRef]
  101. Ceccato, R.; Baldassa, A.; Rossi, R.; Gastaldi, M. Potential long-term effects of COVID-19 on telecommuting and environment: An Italian case-study. Transp. Res. Part D Transp. Environ. 2022, 109, 103401. [Google Scholar] [CrossRef]
  102. Dang, Q. Research on the Impact of Media Credibility on Risk Perception of COVID-19 and the Sustainable Travel Intention of Chinese Residents Based on an Extended TPB Model in the Post-Pandemic Context. Sustainability 2022, 14, 8729. [Google Scholar] [CrossRef]
  103. Jiang, Y.; Wu, Q.; Chen, B.; Long, Q.; Song, Y.; Yang, J. How is the acceptance of new energy vehicles under the recurring COVID-19—A case study in China. J. Clean. Prod. 2023, 430, 139751. [Google Scholar] [CrossRef]
  104. Mouratidis, K. How COVID-19 reshaped quality of life in cities: A synthesis and implications for urban planning. Land Use Policy 2021, 111, 105772. [Google Scholar] [CrossRef] [PubMed]
  105. Sadiq, M.; Adil, M.; Paul, J. Organic food consumption and contextual factors: An attitude–behavior–context perspective. Bus. Strat. Environ. 2023, 32, 3383–3397. [Google Scholar] [CrossRef]
Figure 1. Examples of pocket parks in China (photos were taken by the authors).
Figure 1. Examples of pocket parks in China (photos were taken by the authors).
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Figure 2. Proposed research model.
Figure 2. Proposed research model.
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Figure 3. Sample area distribution.
Figure 3. Sample area distribution.
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Table 1. Respondents’ demographic profile.
Table 1. Respondents’ demographic profile.
DemographicsCategoryFrequencyPercent (%)
GenderMale34748.26
Female37251.74
Age18–24 years old15321.28
25–34 years old23232.27
35–44 years old18525.73
45–59 years old10114.05
60 years old and above486.67
Education levelPrimary school and less233.20
High school18826.15
University40556.33
Master’s degree and above10314.32
Monthly incomeBelow 2000 RMB7910.99
2001–3000 RMB8311.54
3001–5000 RMB20929.07
5001–8000 RMB19527.12
8000–15,000 RMB11916.55
15,001 RMB and above344.73
Average monthly frequency of using pocket parksFewer than 3 times588.07
3–5 times17123.78
5–10 times15821.97
10–15 times19827.54
More than 15 times13418.64
Total719100.00
Table 2. Construct reliability and validity.
Table 2. Construct reliability and validity.
ConstructsItemsLoadingsCronbach’s αrho_ACRAVE
Health risksHR10.8680.9050.9070.9330.778
HR20.870
HR30.832
HR40.756
Environmental qualityEQ10.8590.9040.9050.9290.722
EQ20.840
EQ30.849
EQ40.848
EQ50.853
Perceived usefulnessPU10.8710.8410.8470.9040.760
PU20.828
PU30.860
PU40.863
PU50.855
Awareness of consequencesAC10.8520.8530.8670.9000.694
AC20.894
AC30.899
AC40.883
Ascription of responsibilityAR10.8900.9080.9100.9320.732
AR20.881
AR30.843
AR40.896
Personal normsPN10.8940.9010.9040.9310.770
PN20.831
PN30.888
Intention to participate in pocket-park governanceIPPPG10.8920.9030.9040.9320.775
IPPPG20.885
IPPPG30.867
IPPPG40.876
Table 3. Discriminant validity (Fornell–Larcker’s method).
Table 3. Discriminant validity (Fornell–Larcker’s method).
ConstructsHREQPUACARPNIPPPG
HR0.833
EQ0.3740.850
PU0.5060.4800.856
AC0.4840.4170.4470.882
AR0.4300.3600.4150.4690.878
PN0.4290.4170.5400.4810.4470.871
IPPPG0.4390.4280.5050.5100.4470.5630.880
Table 4. Discriminant validity (HTMT method).
Table 4. Discriminant validity (HTMT method).
ConstructsHREQPUACARPNIPPPG
HR
EQ0.425
PU0.5730.530
AC0.5450.4600.492
AR0.4830.3960.4560.518
PN0.5000.4800.6190.5470.483
IPPPG0.4910.4730.5570.5640.4950.643
Table 5. Standardized path coefficients of the structural model and hypotheses testing.
Table 5. Standardized path coefficients of the structural model and hypotheses testing.
HypothesisRelationshipβSEt-ValueDecision
H1HR→PU0.3800.0428.964 ***Supported
H2EQ→PU0.3380.0427.972 ***Supported
H4HR→AC0.3090.0466.757 ***Supported
H5HR→AR0.1830.0493.744 ***Supported
H6HR→PN0.0770.0531.458Not supported
H7EQ→AC0.2100.0484.398 ***Supported
H8EQ→AR0.1080.0492.212 *Supported
H9EQ→PN0.1090.0442.444 *Supported
H10PU→AC0.1900.0503.797 ***Supported
H11PU→AR0.1500.0532.842 **Supported
H12PU→PN0.2980.0575.229 ***Supported
H13AC→AR0.2690.0495.474 ***Supported
H14AC→PN0.1890.0533.565 ***Supported
H15AR→PN0.1630.0503.253 **Supported
H16HR→IPPPG0.0760.0461.658Not supported
H17EQ→IPPPG0.1010.0482.098 *Supported
H18PU→IPPPG0.1410.0592.377 *Supported
H19AC→IPPPG0.1850.0513.602 ***Supported
H20AR→IPPPG0.1110.0512.177 *Supported
H21PN→IPPPG0.2740.0614.486 ***Supported
*** represents p < 0.001, ** represents p < 0.01, * represents p < 0.05.
Table 6. Testing results of chain-mediated effects.
Table 6. Testing results of chain-mediated effects.
PathStandard EffectEstimationSELLCIULCI
PR→PU→AC→PR→PN→IPPPGTotal effect0.4680.0370.3960.541
Direct effect0.0790.0380.0040.154
Total indirect effects0.3890.0420.3120.477
EQ→PU→AC→PR→PN→IPPPGTotal effect0.4580.0360.3870.529
Direct effect0.1120.0360.0410.182
Total indirect effects0.3460.0390.2770.425
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Zhang, J.; Li, Z.; Zhong, J. From Health Risks to Environmental Actions: Research on the Pathway of Guiding Citizens to Participate in Pocket-Park Governance. Land 2024, 13, 1612. https://doi.org/10.3390/land13101612

AMA Style

Zhang J, Li Z, Zhong J. From Health Risks to Environmental Actions: Research on the Pathway of Guiding Citizens to Participate in Pocket-Park Governance. Land. 2024; 13(10):1612. https://doi.org/10.3390/land13101612

Chicago/Turabian Style

Zhang, Jing, Zhigang Li, and Jialong Zhong. 2024. "From Health Risks to Environmental Actions: Research on the Pathway of Guiding Citizens to Participate in Pocket-Park Governance" Land 13, no. 10: 1612. https://doi.org/10.3390/land13101612

APA Style

Zhang, J., Li, Z., & Zhong, J. (2024). From Health Risks to Environmental Actions: Research on the Pathway of Guiding Citizens to Participate in Pocket-Park Governance. Land, 13(10), 1612. https://doi.org/10.3390/land13101612

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