Abstract
Hikers’ intention for pro-environmental behavior (PEB) directly affects the sustainable development of protected areas, but few studies have been conducted from the perspective of theoretical integration. This study explores the intention of hikers’ PEB from the perspective of individual hikers, based on the theory of planned behavior and norm activation theory. Researchers surveyed 456 hikers in Wuyishan National Park, and the data analysis method employed was structural equation modeling. The results demonstrate that the model integrating TPB and NAM was accepted of hikers’ PEB in national park, and for the hiker, internal demand was found to precede external stimulus for their behavior. The study sheds light on how to better comprehend and advocate for PEB in national parks.
Introduction
The most rapidly developing outdoor activities are associated with trail use, resulting in many natural areas providing outdoor recreational opportunities such as hiking trails in the mountains (Rodrigues et al., 2010; Kim et al., 2021; Venter et al., 2021). Studies have shown that hiking in mountainous areas of different altitudes, can bring benefits to participants (Junot et al., 2017). It can improve people’s quality of life, and health, reduce the risk of heart disease, high blood pressure, diabetes, depression and anxiety, so an increasing number of people have begun participating in hiking (Pate et al., 1995; Bedimo-Rung et al., 2005; Coventry et al., 2021; Garvanova et al., 2021; Puhakka, 2021; Xue et al., 2022). As scenic mountain area attracts large numbers of tourists and hikers, the problem of environmental damage in these areas is becoming more serious, bringing issues such as tourists littering, breaking trees, and feeding small animals at will. Especially for mountain-type national parks with rugged mountain roads and large areas, the impact of irresponsible environmental behavior is more difficult to resolve (Line et al., 2018; Hu et al., 2019; Han, 2021; Esfandiar et al., 2022). China is an emerging and vast tourism destination, mountainous regions account for two thirds of China’s, which is also facing various environmental issues (Chen et al., 2006; Hu et al., 2019; Li and Wu, 2019). Therefore, enhancing PEB of Chinese hiker has become an important issue that needs to be solved urgently (Kaseva and Moirana, 2010; Hu et al., 2018, 2019; Zhang et al., 2022).
Protected areas are “Clearly defined geographical spaces recognized, dedicated, and managed, through legal, or other effective means, to achieve the long-term conservation of nature with associated ecosystem services and cultural values,” it includes national parks, nature reserves, and marine parks [International Union for Conservation of Nature (IUCN), 2008]. As of July 2022, China has a total of five national parks, Sanjiangyuan, Panda, Northeast Tiger and Leopard, Hainan Tropical Rainforest, Wuyishan National Parks. The management of national parks must be sustainable and successful in order to improve human connectivity with nature; establishing PEB programs for visitors is one of the national parks’ functions (Esfandiar et al., 2020; Esfandiar et al., 2022). Hiking is one of the most basic and important activities in national parks and other outdoor recreation areas, and has become a popular outdoor sport from the niche (Rogowski, 2017), it is popular among outdoor sports enthusiasts because of its function to promote hikers’ integration into nature, physical exercise, and healthy mood (Rodrigues et al., 2010; Hartig et al., 2014; Larson et al., 2016). According to statistics, the number of hikers in China has reached 60 million one year, poses a number of environmental problems (Han et al., 2018; Høyem, 2020; Zhang et al., 2020). Based on these concerns, one goal of this study is to identify strategies for encouraging hikers to China’s national parks to adopt environmentally friendly practices.
To achieve a more sustainable society, encouraging hikers to participate in a variety of PEB can subsequently increase favorable environmental outcomes and lessen the severity of global environmental challenges (Goh, 2020; Udall et al., 2020; Choi and Kim, 2021; Esfandiar et al., 2022). Previous studies about PEB have generally focused on personal factors regarding tourists, such as their attitude (ATT), subjective norm (SN), and perceived behavioral control (PBC) mechanisms as well as the environmental behavioral intention of theory of planned behavior (TPB) (De Leeuw et al., 2015; Han, 2020; Meng et al., 2020; Yuriev et al., 2020; Alzubaidi et al., 2021; Aziz et al., 2021; Fenitra et al., 2021; Panwanitdumrong and Chen, 2021; Singh and Kaur, 2021; Zhang et al., 2021; Loureiro et al., 2022; Zheng et al., 2022); awareness of consequences (AC), ascription of responsibility (AR), and personal norm (PN) of the norm activation theory (NAM) (Meng et al., 2020; Alzaidi and Iyanna, 2021; Bai and Zhang, 2021; O’Connor and Assaker, 2021; Han et al., 2021; Cao et al., 2022; Jeon et al., 2022; Kang, 2022; Long et al., 2022; Loureiro et al., 2022; Song et al., 2022; Zhang et al., 2022). However, there are many influencing factors of personal PEB, and there are complex interrelationships, there are both have direct and indirect effects (Han, 2021). Despite being a noteworthy segment in terms of size and spending, the existing literature has focused very little on Chinese hikers’ behavior, and few studies have looked at hikers’ PEB, particularly in popular locations in China (Li et al., 2017; Witte, 2021; Zhang et al., 2022). The majority of earlier studies used conventional tourists as their research subjects, but hikers have special qualities (Ng and Cheng, 2022). For instance, hikers tend to be more intelligent and concerned about the environment (Collins-Kreiner and Kliot, 2017; Lin and Lee, 2020). They promote nature conservation and cherish the surroundings’ natural beauty and landscape (Lin and Lee, 2020; Zhang et al., 2022). Moreover, less research pay attention into hikers’ PEB, particularly in regions that are protected, such national parks, nature reserves, and marine parks, and there were few articles take Chinese hikers as research objects (Esfandiar et al., 2022), as most of the research investigating PEBs in protected areas has been undertaken in Western cultures such as the USA, Australia, and Canada (Esfandiar et al., 2022).
To fill these research gaps, the TPB and NAM were used to study the influencing factors of hikers’ PEB. The study used Wuyishan national park as a case study. The main aims and objectives of the study were the following: (1) What are the main factors impacts on hikers’ PEB? (2) How much do they predict hikers’ PEB? (3) What are the relationships between these factors? The study attempted to propose an effective theoretical framework to explain the factors affecting hikers’ PEB and propose useful management suggestions to achieve environmentally friendly development in protected areas.
Materials and methods
Theory of planned behavior
The scholar Ajzen added the “perceived behavior control” variable to the rational behavior theory (TRA) in 1985 to form the TPB (Ajzen, 1991). Behavioral intention include three aspects, in particular, SN refers to the perceived social pressure from referents (such as friends, leaders, and family) to do or not do something. ATT refers to the attitudes people have about an action, whether they are favorable or unfavorable the action, PBC is the perceived difficulty or ease of performing the action.
Because the TPB has good predictive and explanatory capabilities in behavior research, it is widely used in various aspects, There have been many studies used the TPB model in the research area of environmental behaviors (Yuriev et al., 2020; Alzubaidi et al., 2021; Aziz et al., 2021; Fenitra et al., 2021; Han, 2021; Zhang et al., 2021; Zheng et al., 2022), green purchase (Emekci, 2019; Han, 2020; Liu et al., 2020), revisit behaviors (Manosuthi et al., 2020; Meng et al., 2020; Abbasi et al., 2021; Deng et al., 2021; Soliman, 2021), food delivery services (Troise et al., 2020; Choe et al., 2021), destination choose (Juschten et al., 2019b; Liu et al., 2021; Azhar et al., 2022; Mohamad et al., 2022), digital currency (Radic et al., 2022) these studies have shown that ATT, SN, and PBC positively affected the behavioral intention. Accordingly, this research proposes the hypothesis as follows:
Hypothesis 1 (H1). Attitude (ATT) has a positive influence on behavioral intention (BI).
Hypothesis 2 (H2). Perceived behavior control (PBC) has a positive influence on behavioral intention (BI).
Hypothesis 3 (H3). Subjective norm (SN) has a positive influence on behavioral intention (BI).
One of the changes believed by academics to have a favorable effect on attitude is the subjective norm (Ryu and Jang, 2006; Wu and Lin, 2007). The subjective norm can be defined as the social cohesion that binds an individual to society; this connection captures a person’s attitude (Joynt and Warner, 2002). The subjective norm directly affects attitude and perceived behavior control (Quintal et al., 2010; López-Mosquera et al., 2014; Park and Ha, 2014; Zhou et al., 2014; Manosuthi et al., 2020). Research projects have used Xixi Wetland as an example to verify that subjective norm are an effective influencing factor driving behavior and attitudes (Zhou et al., 2014), volunteer tourists’ subjective norm influences their attitude on revisit intention (Manosuthi et al., 2020), and other also confirmed this point (Li et al., 2013). The environmental complaints of Chinese residents have also verified that subjective norm have a positive impact on attitude and perceived behavior control (Zhang and Wang, 2018). Accordingly, this research proposes the hypothesis as follows:
Hypothesis 4 (H4). Subjective norm (SN) has a positive influence on attitude (ATT).
Hypothesis 5 (H5). Subjective norm (SN) has a positive influence on perceived behavior control (PBC).
Norm activation theory
Schwartz (1977) proposed the norm activation theory (NAM) with individual norms as the core factor, which is mainly used to predict and understand pro-social and altruistic behaviors. Norm activation theory is mainly composed of three variables, AC, AR, and PN. Personal norm represents a moral duty to engage in a particular conduct or refrain from doing so, AC is defined as people’s understanding of how pro-social behavior benefits others or their estimations of other things, and the AR shows how responsible people feel about the effects of their pro-social behavior. NAM is regarded as the most influential theory in explanation of pro-environmental decision-making process and behavior (Steg and Nordlund, 2018; Esfandiar et al., 2019, 2022; Han, 2021; Mikuła et al., 2021; O’Connor and Assaker, 2021; Gao et al., 2022), households’ waste separation (Goh et al., 2022), purchase food (Faletar et al., 2021; Lafontaine et al., 2021; Yang et al., 2021; Le and Nguyen, 2022), waste separation behavior (Esfandiar et al., 2021; Setiawan et al., 2021; Shen et al., 2022), these studies have shown that AR, AC positively affected PN, and AR can be triggered by AC. Accordingly, this research proposes the hypothesis as follows:
Hypothesis 6 (H6). Ascription of responsibility (AR) has a positive influence on personal norm (PN).
Hypothesis 7 (H7). Awareness of consequences (AC) has a positive influence on personal norm (PN).
Hypothesis 8 (H8). Awareness of consequences (AC) has a positive influence on ascription of responsibility (AR).
Personal norm is closely integrated with ethics in environmental protection, which has a direct impact on behavioral intention (Shin et al., 2018; Wang et al., 2018). Research has shown that personal norm has an impact on behavior intention in rural tourism (Li et al., 2013). A theory of green purchase behavior displayed that customers’ personal norm influence environmentally responsible buying behavior for green hospitality products (Han, 2020). When combined with the TPB framework, personal norm is thought to increase the exploratory potential to predict pro-social behavioral intention (Manosuthi et al., 2020). The outcomes of numerous meta-analytic studies also confirm this (Bamberg and Möser, 2007; Klöckner, 2013; Han and Stoel, 2017; Morren and Grinstein, 2021). Accordingly, this research proposes the hypothesis as follows:
Hypothesis 9 (H9). Personal norm (PN) has a positive influence on behavioral intention (BI).
Integrating theory of planned behavior and norm activation model
In the literature on environmental responsibility behavior, The TPB was widely used in the field of tourists’ environmental behaviors, but the adequacy of model explanatory power has been questioned (Han, 2021). TPB ignores the irrational and altruistic motivations of role-building behavior (Kaiser et al., 1999; Sparks and Shepherd, 2002). Therefore, this model has certain flaws in the study of environmental responsibility behavior (Bamberg et al., 2007; Bamberg and Möser, 2007; Han and Hyun, 2017). NAM is a reliable model for explaining environmental behaviors, but it ignores voluntary and involuntary processes, which are the basic dimensions of rational choice models (i.e., TRA and TPB), and its sufficiency is often questioned (Onwezen et al., 2013; Han, 2015; Shin et al., 2018). There maybe have a moderating effect of environmental responsibility behaviors. Therefore, the integrated model of TPB-NAM includes rational choice, morality, and altruistic behavior, which helps to clarify the interaction between the two models and increase the model’s predictive power (Han, 2021).
Subjective norm have an impact on PN (Quintal et al., 2010; López-Mosquera et al., 2014; Park and Ha, 2014), a high level of AC will help highly SN and more positive attitude and intention (Park and Ha, 2014; Han and Hwang, 2016; Zhang et al., 2016; Han et al., 2019). Personal norm is socially constrained, rather than socially free. Due to social dependence, travelers frequently value the places they travel to differently based on the opinions of their peers. Therefore, the personal norm might develop progressively from the subjective norm. Meta-analytic investigations have supported this assumption in empirical research (Klöckner, 2013; Manosuthi et al., 2020). The finding of Meng et al. (2020) also showed that travelers’ awareness of consequences influence the attitude and subjective norm in volunteer tourism. Some research also confirmed that the AC will positively affect attitudes and SN by studying residents’ participation in environmental governance (Wang et al., 2021). Studies with the theory of green purchase behavior found that if awareness of consequences was high, the attitude toward green purchase also high (Han, 2020). Accordingly, this research proposes the hypothesis as follows:
Hypothesis 10 (H10). Subjective norm (SN) has a positive influence on personal norm (PN).
Hypothesis 11 (H11). Awareness of consequences (AC) has a positive influence on attitude (ATT).
Hypothesis 12 (H12). Awareness of consequences (AC) has a positive influence on subjective norm (SN).
Propose research model
In this study, integrating TPB and NAM, a model of influencing factors of hikers’ PEB intention was constructed (Figure 1). It mainly analyzes the influence of hikers’ PEB attitude, subjective norm, perceived behavior control, AC, AR, PN on hikers’ PEB intention in Wuyishan National Park.
FIGURE 1
Methodology
Study sites
Wuyishan National Park is in Nanping City, Fujian Province, China. The total area of the southeast foot of the northern section of the Wuyishan range is 999.75 square kilometers. It is a famous scenic hiker area and summer resort in China. It is a typical Danxia landform and is one of the first batch of national key scenic spots and one of four World Heritage of Nature and Culture in China.
Survey design
All variables were measured with previously validated scales that have been widely employed in environmental research. Some items were slightly modified according to the research context to make them easier for the respondents to understand. By using the back-translation method, the English scales were converted into Chinese versions and then translated back into English with a team that consisted of three professors (two Chinese and one English) to ensure content validity. The questionnaire used a five-point Likert scale for measurement, “Strongly disagree” (1) to “Strongly agree” (5).
The questionnaire comprised two parts: the first included demographic characteristics of residents (gender, age, education, and monthly incomes); and the second was the scales for seven variables. The measurement items in present study were mainly from previous environmental behavior studies, measures of behavior attitude, SN and perceived behavior control, followed by ATT1–ATT4 to measure attitude, SN1–SN3 measure subjective norm, and PBC1–PBC3 measure perceived behavior control, and BI1–BI3 measure PEB intention (Ajzen, 2011; Zhou et al., 2014; Li and Wu, 2019). AC1–AC3 measurement AC, AR1–AR3 Attribution of measurement AR, PN1–PN3 measurement PN (Schwartz, 1977; Zhang et al., 2016, 2017, 2022; Li and Wu, 2019).
Data collection
Before the questionnaire was officially released, A pilot survey was conducted to further test the rationality and scientific of the questionnaire. In total, 50 questionnaires were issued, 45 questionnaires were collected, and 5 unqualified questionnaires were excluded. The effective response rate was 80%. Based on some feedback information on the content of the questionnaire design, the questionnaire was revised, so that the questionnaire filled in the questionnaire would have a better understanding of the questionnaire information and the questionnaire language was more accessible. Next, ambiguous items were revised, and then the reliability of the survey was measured using Cronbach’s alpha coefficient (alpha > 0.70) and the item-total statistics, the results indicated that the reliability was acceptable.
The questionnaire was distributed to hikers in the Wuyishan national park. A three-research assistant team gathered questionnaires in-person for the offline survey. The team received training on how to use anonymity protections, select respondents, and understand the goal of the study. If the survey results in the sample are extended to a population of more than one million, then the study needs 384 samples (Krejcie and Morgan, 1970), So a total of 500 questionnaires were distributed and 482 were collected. After screening and excluding some invalid questionnaires with inconsistent answers, incompleteness, and the same score, there are 456 valid questionnaires, and the effective response rate of the questionnaire is 91.2%.
Before analyzing the original data collected by the questionnaire, we first conducted descriptive statistics on hiker information. The results of 456 sample surveys showed that the gender distribution of respondents was 60.7% males, 39.3% females, and slightly more males; age is concentrated between 25 and 54 years old (70.4%); monthly income is mainly 3000–9000 RMB (78.9%); most of the hikers have college degree or above (63.1%).
Results
Measurement model testing
In this study, structural equation model (SEM) was used for analysis. Confirmatory Factor Analysis (CFA) was used as part of SEM analysis. Before SEM analysis, CFA analysis measurement model should be applied. The reduction of the measurement model variables in this study is based on the two-stage model correction of Kline (Kline, 2005). The measurement model is tested before the SEM analysis. If the fit of the measurement model was found to be acceptable, then the second step was performed. Perform a complete SEM model evaluation. Through the application of SPSS24.0 and AMOS21.0 software for analysis, the Cronbach’s α coefficient of the total measurement scale in this study is 0.879 and the Cronbach’s α value of each latent variable is between 0.820 and 0.859, which indicates that the scale has better reliability and internal consistency.
Structural model testing
The results of the overall fit index of the measurement model (Figure 2) show that χ2/df = 2.238 (<3), RMSEA = 0.052 (<0.08), GFI = 0.924, AGFI = 0.902, TLI = 0.939, NFI = 0.910, IFI = 0.948, CFI = 0.948, all reaching the criterion is greater than 0.9, indicating that the overall model fits well (Hu and Bentler, 1999). The standard loading value corresponding to each latent variable is 0.704∼0.866 and above the limitation of 0.6, all composite reliability (CR) is between 0.775 and 0.868 and greater than 0.6, average variance extracted (AVE) is between 0.625 and 0.709 (Table 1) and the upper limit of 0.5, which shows that the convergence validity is good (Fornell and Larcker, 1981; Hair, 2009), the results showed that the reliability and the convergent validity was sufficient. Path analysis (Table 2) shows that there is a significant influence among the latent variables. The discriminative validity table (Table 3) also shows that the AVE root sign values of latent variables are all greater than the correlation coefficients between the various latent variables, and the discriminant degree is valid and conforms to the reference standard of Fornell and Larcker (1981). In general, the reliability, convergence validity and discriminative validity of the measurement model are acceptable, and the collected data are suitable for the measurement model.
FIGURE 2
TABLE 1
| Constructs and scale items | Factor loading | CR | AVE |
| I think do pro-environmental behavior in national park hiking trails is wise (ATT1) | 0.781 | 0.869 | 0.625 |
| I think do pro-environmental behavior in national park hiking trails is good (ATT2) | 0.790 | ||
| I think do pro-environmental behavior in national park hiking trails is worthwhile (ATT3) | 0.775 | ||
| I think do pro-environmental behavior in national park hiking trails is beneficial (ATT4) | 0.815 | ||
| My friend’s support for my pro-environmental behavior (SN1) | 0.833 | 0.871 | 0.693 |
| People who are important to me think I should do pro-environmental behavior (SN2) | 0.808 | ||
| People who are important to me would want me to do pro-environmental behavior (SN3) | 0.855 | ||
| I have enough physical strength to participate in pro-environmental behavior (PBC1) | 0.855 | 0.865 | 0.682 |
| I am confident that I can do something helpful to protect the environment (PBC2) | 0.816 | ||
| It’s easy for me to take actions to protect environment in this national park (PBC3) | 0.805 | ||
| Hikers’ activities have negative impacts on natural environment (AC1) | 0.844 | 0.880 | 0.709 |
| Hikers’ activities have negative impacts on wild animals and plants (AC2) | 0.868 | ||
| Hikers’ activities lead to water pollution (AC3) | 0.814 | ||
| Every hiker is jointly responsible for environmental deteriorations in this national park (AR1) | 0.830 | 0.868 | 0.686 |
| Every hiker is partly responsible for environmental problems in this national park (AR2) | 0.844 | ||
| Every hiker must take responsibility for environmental problems in this national park (AR3) | 0.811 | ||
| I feel guilty for not doing pro-environmental behavior (PN1) | 0.818 | 0.852 | 0.657 |
| I think pro-environmental behavior is a moral obligation (PN2) | 0.834 | ||
| Pro-environmental behavior is part of my ethics (PN3) | 0.779 | ||
| I am willing to participate in pro-environmental behavior currently (BI1) | 0.820 | 0.844 | 0.643 |
| I am plan to participate in pro-environmental behavior currently (BI2) | 0.801 | ||
| I am willing to ask my relatives and friends to participate in pro-environmental behavior currently (BI3) | 0.785 |
Results of the confirmative factor analysis (CFA).
TABLE 2
| Constructs | ATT | SN | PBC | AC | AR | PN | BI |
| ATT | 0.791 | ||||||
| SN | 0.303*** | 0.832 | |||||
| PBC | 0.138*** | 0.454*** | 0.826 | ||||
| AC | 0.376*** | 0.287*** | 0.130*** | 0.842 | |||
| AR | 0.117*** | 0.089*** | 0.040*** | 0.311*** | 0.828 | ||
| PN | 0.160*** | 0.271*** | 0.123*** | 0.325*** | 0.295*** | 0.811 | |
| BI | 0.334*** | 0.388*** | 0.338*** | 0.223*** | 0.106*** | 0.300*** | 0.802 |
Test of discriminant validity of the study constructs.
The numbers in the diagonal row (bold) are the average variance extracted by each latent construct. The numbers above diagonal are the squared correlation coefficients between the constructs.
***p < 0.001.
TABLE 3
| Path | Standardized path coefficient | t-value | Results |
| ATT → BI | 0.222*** | 4.237 | Supported |
| PBC → BI | 0.204*** | 3.545 | Supported |
| SN → BI | 0.176** | 2.801 | Supported |
| SN → ATT | 0.213*** | 3.837 | Supported |
| SN → PBC | 0.454*** | 7.993 | Supported |
| AR → PN | 0.214*** | 3.756 | Supported |
| AC → PN | 0.202*** | 3.460 | Supported |
| PN → BI | 0.192*** | 3.680 | Supported |
| AC → AR | 0.311*** | 5.571 | Supported |
| SN → PN | 0.194*** | 3.467 | Supported |
| AC → ATT | 0.315*** | 5.658 | Supported |
| AC → PN | 0.202*** | 3.467 | Supported |
Standardized path coefficients of the structural model and hypotheses testing.
**p < 0.01, ***p < 0.001.
Correlation analysis
The maximum likelihood method is used to estimate the parameters of the structural model, and the model fitting indexes all meet the criteria. Path analysis with significance p < 0.05 as the standard to obtain hypothesis test results (Table 3): ATT, PBC, SN have a positive effect on BI (β1 = 0.222, p < 0.001; β2 = 0.204, p < 0.001; β3 = 0.176, p < 0.05), H1–H3 were all supported; SN has a positive effect on ATT and PBC (β4 = 0.213, p < 0.001; β5 = 0.454, p < 0.001), H4 and H5 were all supported; AR and AC have a positive impact on PN (β6 = 0.214, p < 0.001; β7 = 0.202, p < 0.001), H6 and H7 were all supported; AC has a positive influence on AR (β8 = 0.311, p < 0.001), H8 was supported; PN has a positive influence on BI (β9 = 0.192, p < 0.001), H9 was supported; SN has a positive influence on PN (β10 = 0.194, p < 0.001), H10 was supported; AC has a positive effect on ATT and SN (β11 = 0.315, p < 0.01; β12 = 0.287, p < 0.001), H11 and H12 were all supported.
Conclusion
The negative effects on the environment have gotten more attention as tourism has grown so quickly. Finding the variables that affect the environmental behavior of hikers is therefore becoming more and more important. From the perspective of the behavioral setting, this study examined the TPB and NAM that affect hikers’ PEB and came up with some significant conclusion. After the analysis and model verification of this research, H1–H9 have been verified.
First, the results revealed that both the TPB model and NAM model displayed explanatory capacity on hikers’ PEB in Wuyishan National Park in China. Scholars from a variety of disciplines have regularly evaluated the suitability of utilizing TPB or NAM models to explain PEB (Han, 2015, 2021; Alzubaidi et al., 2021; Aziz et al., 2021; Singh and Kaur, 2021; Cao et al., 2022; Kang, 2022; Long et al., 2022; Song et al., 2022; Zheng et al., 2022).
Second, attitude, subjective norm, PBC, AC, AR, and PN all influence hikers’ PEB. AC directly affect SN and ATT, SN directly affect ATT, PBC, and PN. This conclusion is consistent with the original research.
Discussion
In the context of tourism, which includes places with a focus on nature, NAM and TPB are both traditional theories for analyzing people’s PEB. This study displayed that for the hiker, attitude is most important (Han, 2015). Hikers frequently desire to act in a pro-environmental manner while they are hiking since one’s pro-environmental attitude is favorably related to one’s personal connection to nature (Tarrant and Green, 1999; Ng and Cheng, 2022). Strong connections to the natural world make hikers more likely to actively engage in environmentally sustainable purchase patterns (Dutcher et al., 2007). Indeed, when customers feel connected to the natural world, they engage in more environmentally responsible behaviors (Mayer and Frantz, 2004; Poon et al., 2015; Han and Hyun, 2017). Compared to the tourist, hikers will have more perceived connection to nature, so their pro-environmental attitude will be stronger. This finding is different from other research, that holds attitude is an insignificant predictor for behavioral intention (Juschten et al., 2019a).
Subjective norm was found to be a minimal influencer to BI, which is consistent with previous research (Sheppard et al., 1988; Bamberg and Möser, 2007). This is probably due to the fact that SN means that friends or relatives must want to do this, and this is an external influence (Ming-Shen et al., 2007; Bang et al., 2014). Hikers’ PEB comes mainly from internal demand, as they love nature and want to protect the natural environment. These findings were in accordance with previous tourism literature that indicated that internal demand was particularly important for behavior (Fluker and Turner, 2000; Park and Yoon, 2009; Buckley et al., 2014). The result is on the contrary with some research (Han and Stoel, 2017; Manosuthi et al., 2020).
Personal norm does not have a strong significant impact (Zhang et al., 2022), it is different from some research that thought PN offer the greatest potential in terms of activating pro-environmental behavior in tourism (Kiatkawsin and Han, 2017). Because PN differ from attitudes since they tend to be steady over time (Juvan and Dolnicar, 2016), it will be impact by information from social media (Han et al., 2021). Some hiker frequently seeks more hedonistic experiences, and as a result, their PN is not completely activated to undertake PEB in the context of tourism (Li and Wu, 2020; Gao et al., 2021; Zhang et al., 2022). Additionally, some novice trail users believe that it is the government’s duty, not an individual’s, to protect the environment (Zarei et al., 2020).
Perceived behavioral control plays a secondary role to BI (Han et al., 2010; Han, 2020; Zarei et al., 2020). With the limited supply of hiking destinations, the impact of PBC is strengthened (Han and Stoel, 2017). The significance of how people perceive their capacity to engage in PEB acts is shown by this link. Informing people of their prospective abilities that can have a substantial impact on nature conservation is one example of an approach that may boost people’s perceptions of their capacities to engage in PEB. The hiker would then understand that it is simple to protect wildlife and clean up after themselves in the mountains (Zarei et al., 2020).
Awareness of consequences directly affects AR, PN, SN, and ATT; in the other words, internal demand was considered to precede external stimulus (Kim et al., 2003; Zoltan and Masiero, 2012). Awareness of environmental consequences can be viewed as people’s general attitude toward preserving the environment, playing a crucial role in making attitudes toward the pro-environmental behavior and subjective norm of performance (Park and Ha, 2014; Zhang et al., 2017; Meng et al., 2020). Behavioral beliefs, or beliefs about the consequences of engaging in a certain behavior, are one of the main constructs of individuals’ attitude toward the behavior (Rezaei et al., 2019). From a different perspective, it can be argued that when people are highly aware of the effects on the environment, they become more perceptive to how other people perceive or evaluate environmental issues (Park and Ha, 2014; Meng et al., 2020).
Subjective norm directly affect ATT, PBC, and PN, it same with some research (Quintal et al., 2010; López-Mosquera et al., 2014; Zhang et al., 2017). Particularly, it may be argued that the absence of an ideal standard for the proper attitudes is what causes subjective norms to have a positive impact on attitudes (Festinger, 1954; Rezaei et al., 2019). Consequently, people’s perceptions of what significant individuals believe they should do will influence how they feel about a specific behavior (Park and Ha, 2014; Zhang et al., 2017). Attitudes are influenced by the people and environment around us. When forming their own attitudes, people take into account the demands of others and their willingness to comply (Quintal et al., 2010).
Theoretical and practical implications
This study is one of the first attempts to evaluate hikers’ PEB in China’s Wuyishan national park while using the TPB mode and NAM model together. The following theoretical additions to the existing literature are illustrated by this investigation. Firstly, the study found that both the TPB and NAM models demonstrate significant explaining capacity on hikers’ PEB in the protected areas, which further validates the findings of previous studies PEB (Han, 2015, 2021; Alzubaidi et al., 2021; Aziz et al., 2021; Singh and Kaur, 2021; Cao et al., 2022; Kang, 2022; Long et al., 2022; Song et al., 2022; Zheng et al., 2022). Therefore, it is demonstrated that integrating TPB and NAM models is useful and effective for examining hikers’ PEB in the protected areas and for understanding more fully the influence mechanism underlying such behavior.
Second, the result of this study demonstrate that there are many influencing factors on hikers’ PEB in protected areas; additionally, there are intricate linkages that have both direct and indirect consequences within these factors (Han, 2021). In other words, to examine hikers’ behavioral intention in national park, we need consider the irrational and altruistic factor, such as AC, AR, PN and the rational choice factor, like PBC, SN, and ATT.
Third, awareness of consequences is very important. In particular, the degree to which a person is aware of the need to assist others is shown by hikers who have a stronger sense of problem awareness, such as the awareness of consequence (Littlejohn et al., 2016). The ties to PEB intention, TPB and NAM are therefore logically related since awareness of consequences links to three predictors in TPB and the construct of the personal norm, which includes the sense of obligation to altruistic action in the current study. Tourism or hiking researchers should pay more attention on awareness of consequence when conducting do pro-social research (Meng et al., 2020).
This study provides management implications to national park. The study constructs integrate two models based on TPB theory and NAM theory. A more systematic analysis explains the influencing factors on hikers’ PEB in China. National park are created to protect the ecological environment and the protected areas of individual countries form an important part of the global ecological protection. First, hikers’ attitude is important, to urge hikers to participate in PEB, we need to increase hikers’ positive attitudes and help them to acquire social support from other hikers. Individuals’ attitude toward a particular conduct will be influenced by their impressions of what influential others want them to do (Park and Ha, 2014; Zhang et al., 2017). In other words, people’s attitudes are molded by their surroundings and the people in them, and while forming their own attitudes, individuals take into account other people’s expectations and willingness to conform (Quintal et al., 2010; Rezaei et al., 2019). Second, awareness of consequences is a key factor. It connects the TPB and NAM, and it impacts many factors. Therefore, any feasible tactics that can raise problem awareness should be developed and used in order to achieve a trickle-down effect in order to cause a chain reaction (Meng et al., 2020). In addition to this, national park serve the function of national nature education, whereby visitors learn about the importance of biodiversity and the protection of the ecological environment, thus promoting the their PEB (Bushell and Bricker, 2017; Klein and Hilbig, 2018; Esfandiar et al., 2022). As more and more people enjoy hiking, national parks need to make the most of nature education to move people’s PEB from external behavior to intrinsic behavior. In other words, this change from external to internal needs requires a process, and national parks need to play an important role in this process.
Limitations and future research
There are several limitations that call for additional research, despite the fact that this work offers a fresh viewpoint on the investigation of hikers’ electroreceptor bands in China’s Wuyishan national park. First off, there are a variety of elements that have direct or indirect effects on hikers’ PEBs. This study didn’t consider how all the variables interacted (López-Mosquera et al., 2014; Park and Ha, 2014). Secondly, this study is based on self-administered survey about environmental behavior. Therefore, there may be certain deviation of the self-reported behavior and real behavior due to respondents’ social desirability bias. Alternative research approaches such as experimental research, qualitative interviews or focus groups should be employed to improve the validation and rigor of the study results. Thirdly, the environmental background of a protected area as a significant contextual factor needs to be considered along with the internal psychological process, such as emotion, environmental knowledge, habit needs to be taken into account as a crucial contextual aspect.
Statements
Data availability statement
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
Ethics statement
This study was approved by the Laboratory Ethics Committee of the School of Tourism, Wuyi University (LY2020016, 14 May 2020). The patients/participants provided their written informed consent to participate in this study.
Author contributions
QZ and HS: conceptualization. QZ: methodology, software, and writing – original draft preparation. HS: formal analysis and data curation. WG: investigation, writing – review, and editing. KL: funding acquisition. HS and KL: review and revision. All authors read and agreed to the published version of the manuscript.
Funding
This study was funded by the Fujian Social Science Planning Project (FJ2020X010).
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
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Summary
Keywords
pro-environmental behavior, theory of planned behavior, norm activation theory, national park, integrating theory
Citation
Sun H, Zhang Q, Guo W and Lin K (2022) Hikers’ pro-environmental behavior in national park: Integrating theory of planned behavior and norm activation theory. Front. For. Glob. Change 5:1068960. doi: 10.3389/ffgc.2022.1068960
Received
13 October 2022
Accepted
24 November 2022
Published
15 December 2022
Volume
5 - 2022
Edited by
Heesup Han, Sejong University, South Korea
Reviewed by
Jin-Soo Lee, The Hong Kong Polytechnic University, Hong Kong SAR, China; Jongsik Yu, Cheongju University, South Korea
Updates
Copyright
© 2022 Sun, Zhang, Guo and Lin.
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*Correspondence: Qing Zhang, jamking5@163.com
This article was submitted to Frontiers in Forests and Global Change Forest Ecophysiology, a section of the journal Frontiers in Forests and Global Change
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