Next Article in Journal
An Econometric Analysis to Explore the Temporal Variability of the Factors Affecting Crash Severity Due to COVID-19
Previous Article in Journal
Beyond the Business Case for Responsible Artificial Intelligence: Strategic CSR in Light of Digital Washing and the Moral Human Argument
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Sustainability
Volume 16
Issue 3
10.3390/su16031231
sustainability-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Factors Influencing Tourists’ Intention and Behavior toward Tourism Waste Classification: A Case Study of the West Lake Scenic Spot in Hangzhou, China

by
Huan Hu
1,
Yu Zhang
2,3,*,
Chang Wang
4 and
Peng Yu
5
1
Alibaba Business School, Hangzhou Normal University, Hangzhou 311121, China
2
School of Geography and Tourism, Qufu Normal University, Rizhao 276827, China
3
Institute of Yellow River Ecology, Qufu Normal University, Qufu 273165, China
4
School of Social Development, Nanjing Normal University, Nanjing 210023, China
5
School of Tourism and Culinary Science, Yangzhou University, Yangzhou 225127, China
*
Author to whom correspondence should be addressed.
Sustainability 2024, 16(3), 1231; https://doi.org/10.3390/su16031231
Submission received: 28 December 2023 / Revised: 24 January 2024 / Accepted: 30 January 2024 / Published: 1 February 2024
(This article belongs to the Section Tourism, Culture, and Heritage)
Browse Figures
Versions Notes

Abstract

:
The increasing amount of tourism waste has been a headache for most tourist destinations in China. Guiding tourists to classify waste has become a key concern for tourism waste management. In this study, the TPB-AR-DH model was constructed for the first time to reveal the formation process of tourists’ participation in tourism waste classification. The data came from a questionnaire survey sample of 382 tourists to the West Lake Scenic Spot in Hangzhou. The results from the structural equation model and multiple group analysis showed that (1) attitude towards the tourism waste classification, subjective norm, perceived behavioral control, and ascription of responsibility positively affected tourists’ waste classification intention. Especially, the ascription of responsibility was the most influential factor; (2) perceived behavioral control had the largest effects on actual behavior, and waste classification intention played a partly mediating role between perceived behavioral control and actual behavior; (3) tourists’ daily habit of waste classification played a significant moderating role between tourists’ waste classification intention and actual behavior. On the whole, this study offered a theoretical explanation model to popularize the initiative of tourism waste classification and perfect waste management policies in tourist destinations.

1. Introduction

Waste management is a vital component of sustainable development around the world. Compared with non-tourist areas, tourist destinations have to face additional challenges related to waste management due to the large number of tourists, the seasonality of tourist flows, and geographical conditions [1,2]. Especially in some popular tourist destinations, tourists generate more waste than residents during the peak tourist season [3]. The increasing amount of tourism waste has been a headache for most tourist destinations, such as plastic, glass, and metal packaging, napkins, food scraps, and so on. For example, in some small island-developing states, such as the Caribbean, tourists produce twice as much waste as residents [4]. Large amounts of tourism waste increase the cost and strain of local municipal solid waste management systems. According to the “reduction, reuse, recycle” environmental protection concept, waste that is not source-separated is difficult or even impossible to recycle, and accurate waste classification means reducing impurities and improving the quality of recycling. The more waste that is sorted, the more material will be recycled instead of going directly to landfill sites or incinerators [5,6,7]. The waste classification system is related to reducing, reusing, and recycling waste.
Unlike the mature municipal solid waste classification system in developed countries such as Singapore, Japan, and Sweden, China is not yet mature. The history of domestic waste classification in China’s megacities dates back to 2000, with a total of eight cities listed as pilot cities. However, the implementation of waste classification is not satisfactory because the vast majority of the public’s awareness of waste classification has not been formed. Given this, China has been vigorously promoting mandatory municipal solid waste classification in 46 major cities since 2017, but specific classification policies and standards vary from city to city. Tourists from different cities need to follow the waste classification requirements in different destinations. Therefore, guiding tourists to classify tourism waste has become a key concern for tourist destinations.
Currently, most of the studies focused on Chinese residents’ intention and behavior to classify household solid waste and explained the reasons [8,9]. However, few studies focused on Chinese tourists’ intentions and behaviors regarding tourism waste classification. The tourism waste classification in this study mainly refers to the classification of waste generated by tourists at tourist destinations, which is mainly divided into four types. First, recyclable waste refers to uncontaminated waste suitable for recycling and resource use, mainly including paper (newspapers, leaflets, magazines, old books, cardboard boxes, and other uncontaminated paper products, etc.), metal (iron, copper, aluminum, and other products), and glass (glass bottles, glass cups, etc.). Secondly, food scrap waste refers to leftover food waste that is carried around, mainly including food remains, tea dregs, fruit remains, fruit shells, and melon peels. Thirdly, hazardous waste refers to waste that is directly or potentially harmful to human health or the natural environment, mainly including waste medicines, waste cosmetics, waste film, and waste photo paper. Fourthly, other waste refers to waste other than recyclables, food scrap, and hazardous waste, mainly including contaminated and non-renewable paper, contaminated or non-recyclable glass, plastic bags and other contaminated plastic products, worn-out ceramics, disposable tableware, cigarette butts, and so on. Unlike the implementation of residents’ household waste classification in some pilot cities, tourists come from all over the country, and many of them may not have the habit and cognition of waste classification. There is a long way to go to get full participation in the waste classification program and help tourists develop the habit. Hence, it is urgent to study the formation process of tourists’ intentions and behaviors toward tourism waste classification.
What is even more concerning is that there is a paradox between tourists’ pro-environmental intentions and their actual behavior. Tourists’ intention to engage in pro-environmental behavior tends to be high, but actual pro-environmental behavior is poorly performed. How can we minimize this gap? The habit received attention because of the potential impact of frequently performed behaviors [10,11]. MacInnes et al. [12] argued that tourists’ habits drove sustainable behaviors and proposed that pro-environmental behaviors that were strongly habitual were more likely to be enacted on vacation. Thus, the variable of the daily habit of waste classification was used to analyze reasons for the inconsistency between tourists’ intention to separate tourism waste and their actual behavior. In the process of implementing new environmental policies, the relevant research showed that the theory of planned behavior (TPB) could well explain the process of human practice of new policies [13]. To improve the explanatory power of the theory, other influencing factors were also added according to different objects and situations. Vaske et al. [14] found that individuals’ ascription of responsibility has significant impacts on their intention to practice new environmental policies. However, there is no relevant research on whether the ascription of responsibility in the tourism environment will affect tourists’ intentions to classify waste.
Given the limitations of existing research, this study investigates the factors influencing Chinese tourists’ intention and actual behavior to classify tourism waste with the extended TPB model by adding the ascription of responsibility and the daily habit of waste classification. Taking the case study of the West Lake Scenic Spot in Hangzhou, this study tries to solve three research objectives. First, to explore factors influencing tourists’ intention and actual behavior toward tourism waste classification. Second, to test whether the daily habit of waste classification plays a significant moderating role in explaining the differences between tourists’ waste classification intentions and their actual behavior. Third, to test whether the TPB-AR-DH model, which includes the ascription of responsibility and the daily habit of waste classification, has better explanatory power than the original TPB model. Based on these aims, the study hopes to provide effective suggestions for tourism waste classification management.

2. Theoretical Background and Hypotheses Development

2.1. Theory Background

2.1.1. The Theory of Planned Behavior

The TPB was developed on the basis of the theory of reasoned action (TRA) [15,16]. In order to further improve the predictive power, Ajzen added a new independent variable of perceived behavioral control on the basis of the two independent variables of attitude and subjective norm of the TRA. The TPB suggested that individual behavioral intention was influenced by three core variables, namely attitude, subjective norm, and perceived behavioral control, and that behavioral intention was the most important determinant of human social behavior. However, the individual behavioral intention did not always lead to the actual behavior, since the behavioral intention cannot be the sole determinant of the actual behavior when an individual has incomplete control over the actual behavior. When people felt they could perform certain behaviors successfully, they were more likely to intend to perform those behaviors. This means that perceived behavioral control affected the actual behavior not only directly but also indirectly through the behavioral intention.
As a social psychological theory, the TPB has been used as the basic theory to analyze the formation process of various human pro-environmental behaviors [17,18], such as energy saving [19,20], recycling [21,22], green purchasing [23,24], and so on. In particular, it is also used in the field of research on tourists’ pro-environmental behaviors related to waste management, for example, tourists’ intention to reduce plastic use after nature-based experiences (a humpback whale encounter) from Australia and Tonga [25], tourists’ intention about plastic waste reduction on beaches in Saudi Arabia [26], tourists’ waste reduction intention at general US hotels [27], tourists’ intention to reduce waste generation in mountainous tourism areas in China [1,13,28], and tourists’ waste classification intention in Chinese rural destinations [29]. A common feature of past studies was that scholars extended TPB in different forms according to different research backgrounds, purposes, and contents so as to improve the predictive power of the original TPB model on pro-environment intentions and behaviors. In the context of strengthening the management of household waste classification in China, more and more Chinese tourism scholars have begun to pay attention to the behavior of tourists participating in tourism waste classification. However, overall, the number and depth of research were still insufficient. Therefore, this study also attempted to construct an extended TPB model to explain tourists’ intentions and behaviors toward tourism waste classification.

2.1.2. The Extended TPB-AR-DH Model

The original TPB model is a single analysis of influencing factors on behavioral intentions and actual behaviors from the perspective of self-interested psychological factors, ignoring the role of altruistic psychological factors, situational factors, and other factors that work together to influence individual behavior. Existing empirical studies found that there were still many factors that could not be incorporated into the original TPB model to explain people’s various intentions and behaviors [30,31]. The current study extended the TPB model from altruistic motivation (ascription of responsibility) to habitual influence (daily habit of waste classification). Not only the rational self-interested motivations of individuals in the behavioral process are considered, but also the important role of irrational altruistic motivations and the spillover effects of the daily habit of waste classification. The TPB-AR-DH model constructed in this study aimed to develop feasible measures to guide tourists in implementing the behavior of tourism waste classification, providing theoretical references and policy references for tourism waste classification.

2.2. Hypotheses Development

2.2.1. Attitude, Subjective Norm, Perceived Behavioral Control, and Tourists’ Waste Classification Intention/Actual Behavior

According to Ajzen [16], in this study, the meaning of attitude towards behavior is the extent to which tourists have a good or bad evaluation of the behavior of tourism waste classification. The meaning of subjective norm is that tourists’ perceived social pressure to classify or not classify tourism waste comes from people who have important influences on them. The meaning of perceived behavioral control is that tourists perceive the ease or difficulty of classifying tourism waste in the tourist destination. Based on the existing studies on tourists’ pro-environment behavioral intention, in general, if the attitude towards the behavior was more positive, the subjective norm was more favorable, and the perceived behavior control was easier, then the behavioral intention would be stronger [16,28,32]. For example, Chinese tourists’ waste classification intention was positively influenced by attitude, subjective norm, and perceived behavioral control in rural tourism areas [29]. For tourists’ pro-environment behavior, in general, if perceived behavioral control was easier and the behavioral intention was stronger, then the actual behavioral performance would be stronger [16,33]. For example, Wang et al. [34] found that perceived behavioral control positively affected Chinese tourists’ responsible environmental intentions and behaviors, and the intention positively affected the behavior in the Huangshan Mountain scenic spot. However, the results varied depending on the choice of model and area of study [35,36]. For example, attitude did not significantly contribute to predicting tourists’ plastic waste reduction intention in Saudi Arabia [26]. Perceived behavioral control also had no significantly positive impacts on youth tourists’ waste reduction intentions in South Korea [37]. This is to say that the significance, direction, and magnitude of the influence of these variables in predicting intentions and behaviors will vary depending on situations and behaviors. Therefore, according to the background and purpose of this study, a new validation was necessary. The following hypotheses were proposed in this study:
H1. 
Tourists’ attitude towards the behavior positively affects their intention to classify tourism waste.
H2. 
Tourists’ subjective norm positively affects their intention to classify tourism waste.
H3. 
Tourists’ perceived behavioral control of tourism waste classification in the destination positively affects their intention to classify tourism waste.
H4. 
Tourists’ perceived behavioral control of tourism waste classification in the destination positively affects their actual behavior.
H5. 
Tourists’ intention to classify tourism waste positively affects their actual behavior.

2.2.2. Ascription of Responsibility and Tourists’ Waste Classification Intention

“Protecting the environment is everyone’s responsibility” is a value that China has long advocated. Among the various possible additional predictors in altruistic and pro-environmental spheres, the ascription of responsibility was a key variable that explained the formative process of individual intention and behavior [38,39]. Generally, people with strong perceptions of responsibility towards the environment were more likely to engage in environmentally friendly behaviors [40], such as low-carbon transportation usage [14], green lodging [41], and household waste classification [42]. For tourists, perceived destination social responsibility influenced their environmental behaviors [43]. In this study, based on previous research in the context of general pro-environmental and waste classification behavior [38,39], the meaning of the ascription of responsibility is tourists’ responsibility consciousness to tourism waste classification in tourist destinations.
The ascription of responsibility is a key factor in tourists’ intention to classify tourism waste for two reasons. First, throwing unsorted waste into bins is uncivilized behavior, but it is not illegal in China’s scenic areas, and there is no punishment for tourists who do not classify waste. Therefore, a sense of responsibility is one of the prerequisites for tourists to take the initiative to abide by the rules of tourism waste classification. Second, the sense of responsibility for the same behavior will be different from the tourism situation and the daily situation [44]. Tourists had a greater sense of responsibility when they were in the community compared with their sense of responsibility in tourist destinations [11,45]. The classification of domestic waste in most Chinese cities starts in urban residential communities, and the responsibility for domestic waste source classification is clearly vested in each household. People are more likely to consider the environmental impacts when making decisions at home. This was because the public sharing space and the co-existing public could lead to a weakening of individual responsibility [46]. In the tourist destination, the responsibility of source classification of tourism waste is shared by all tourists. Every tourist’s sense of responsibility may be reduced, which affects their willingness to classify tourism waste. Therefore, this study attempted to test the effect of tourists’ attribution of responsibility on the intention to classify waste in tourist destinations with the following hypotheses:
H6. 
Tourists’ ascription of responsibility positively affects their intention to classify tourism waste.

2.2.3. Moderating Role of the Daily Habit of Waste Classification

In psychology, habits are defined as an automatically formed pattern of behaviors that have been repeatedly performed in consistent contexts [47,48,49]. In this study, the daily habit refers to tourists’ habitual behavior of waste classification in daily life. However, there is less understanding of the relationship between tourism practices and everyday pro-environmental activities at home. Some studies have shown that tourists’ behaviors in tourist destinations cannot directly influence their behaviors in daily life, but habits in daily life can have spillover effects on their behaviors in tourist destinations. Tourists’ pro-environmental behaviors in tourism have deteriorated compared with their everyday pro-environmental behaviors [45]. However, contrary to these studies, Barr et al. [50] found that tourists who had highly supportive environmental beliefs and behaviors in daily life behaved unsustainably when they traveled. For some tourists, travel was not seen as a context for pro-environmental behaviors [51]. The above studies show that the spillover effects of tourists’ habitual behaviors in daily life on their behaviors in destinations are a complex process. Based on inconsistent results, this study attempts to clarify the effect of tourists’ habits of waste classification in daily life on their behaviors of tourism waste classification in tourist destinations.
Moreover, the reason for the inconsistency between pro-environmental intentions and actual behaviors is a typical academic problem. Liu et al. [52] found that the daily green behavior of tourists at home was a moderator between pro-environmental intentions and actual behaviors in tourist destinations. Similar findings have been found for other behaviors. For example, Limayem et al. [53] found that the habit played a moderating role between the willingness of information systems continuance and actual behavior; when the habit was strong, the relationship between the intention and actual behavior was strong, and vice versa. Most previous studies have focused on generalized pro-environmental behaviors, and the single-specific behavior was relatively weak. There is no research to explore the factors that influence the inconsistency between tourists’ intentions and actual behavior to classify tourism waste. Accordingly, the following hypothesis was formulated:
H7. 
Tourists’ daily habit of waste classification has a moderating effect between tourism waste classification intention and actual behavior.
Based on the above hypotheses, this study proposed a conceptual model of factors influencing tourists’ intention and behavior to classify tourism waste (Figure 1).

3. Methodology

3.1. The Background of the Study Case

The West Lake scenic spot is located in Hangzhou City, Zhejiang Province, East China (Figure 2). West Lake is a major ornamental freshwater lake in China, surrounded by mountains on three sides and near the city on one side. The scenic area is about 59 square kilometers, of which the lake area is about 6.4 square kilometers; the width is about 2.8 km from east to west; the length is about 3.3 km from north to south; and the circumference is about 15 km (Figure 3). It was selected as one of the “National Top Ten Scenic Spots” in 1985, awarded “National A Grade Tourist Attractions” in 2007, and inscribed on the “World Cultural Heritage” by UNESCO in 2011. For ten centuries, it has been regarded as the spiritual home of the Chinese literatus and a perfect place for modern people to get away from the hustle and bustle of the city.
Regarding tourists’ behavior toward tourism waste classification at West Lake, the reality is that most tourists are accustomed to throwing unsorted waste into bins. However, tourism waste needs to be classified according to the requirements before it can be transported away by waste-cleaning vehicles. Therefore, the behavior of tourists not sorting waste has put great pressure on the cleaning personnel of the scenic spot, and it is necessary for the cleaning personnel to manually classify waste to ensure the smooth transportation and disposal of waste. In China’s scenic spots, throwing unsorted waste into bins is uncivilized behavior, but it is not illegal, and there is no punishment for tourists who do not classify waste. Therefore, there are always some tourists who cannot consciously abide by the regulations of waste classification. According to Hangzhou Daily, during the May Day holiday in 2023 (from 29 April to 3 May), West Lake received a total of 2,827,800 tourists, with a daily average of 565,600 tourists, making it one of the top ten popular scenic spots in China. Due to the increase in the number of tourists, the amount of tourism waste has also surged, with a daily average of nearly 150 tons of waste removed. This has become one of the scenic holiday challenges.
From the perspective of a tourist city, Hangzhou is one of the most popular tourist cities in China. It has to deal with a lot of tourism waste, especially at UNESCO World Heritage Sites, and also faces heritage conservation issues. Tourists are not clear about the waste classification system in tourist destinations, which will lead to improper waste disposal. From the perspective of a scenic spot, West Lake is a pilot scenic spot to create a zero-waste scenic spot in China. The zero-waste scenic spot refers to the scenic spot management mode that minimizes the environmental impact of waste by reducing, recycling, and harmless treatment. Waste classification is a key measure to create a zero-waste scenic spot. West Lake has been a pioneer in encouraging tourists to separate waste in recent years, but the desired effect has not been achieved in practice. Regarding the classification and management of tourist waste, West Lake is typical and representative, so it is chosen as a case study to investigate the factors affecting tourists’ intentions and the actual behavior of tourism waste classification.

3.2. Questionnaire Design

The questionnaire included three parts. The first part described the background and purpose of this research in words to help the respondents better understand the following questions: The second part was mainly demographic characteristics (a total of five questions, including sex, age, education level, personal monthly income, and whether the daily residence has a garbage sorting policy). The third part included 21 questions on seven latent variables of factors affecting tourists’ intention and actual behavior of tourism waste classification.
The measurement items of seven latent variables were mainly derived from existing research on individual environmental behavior in different situations [1,10,16,38,39,41,42,52], including attitude towards the behavior (ATT), subjective norm (SN), perceived behavioral control (PBC), ascription of responsibility (AR), daily habit of waste classification (DH), waste classification intention (WCI), and waste classification behavior (WCB) (Table 1). Minor modifications were then made to the original measurement items to make them appropriate for this study. The back translation method was used to ensure translation equivalence of measurement items [54]. Each of the seven latent variables was measured by three measurement items using a 5-point Likert scale. Specifically, ATT, SN, PBC, AR, DH, and WCI were from “strongly disagree” (1) to “strongly agree” (5), and WCB was from “never” (1) to “always” (5).

3.3. Data Collection

First of all, this study conducted a preliminary survey online. To ensure the representativeness of the respondents, a survey was conducted among 50 visitors who had been to the West Lake Scenic Spot in the past year, and a valid sample of 40 was obtained. After the preliminary survey, some ambiguous items and linguistic errors in the initial questionnaire were modified based on the suggestions. The Cronbach’s alpha coefficients were all greater than the threshold value of 0.7, which indicated that the scale has acceptable reliability. At this point, a formal questionnaire was formed.
The formal questionnaire was prepared and published on Wenjuanxing, which is a professional and widely used online questionnaire survey platform in China. This study adopted two sampling methods: convenience sampling and snowball sampling. Convenience sampling refers to the questionnaire link formed by Wenjuanxing being forwarded through the main social media platforms in China, such as WeChat, Weibo, and other means, so that a part of the subjects who meet the general characteristics of the research objectives can answer the questionnaire, and at the same time, the answering population can further forward and spread the questionnaire. Snowball sampling refers to the fact that some respondents were randomly selected through social media platforms first and then asked for recommendations from respondents who matched the overall characteristics of the research objectives. The two sampling methods were combined until the total target sample was recovered. Considering the timeliness of tourists’ travel memories, the research subjects are tourists who have visited Hangzhou West Lake in the past year. From 14 March to 5 April 2020, this survey distributed 400 questionnaires and collected 382 valid questionnaires, for an effective rate of 95.50%.

3.4. Data Analysis Methods

The study used the structural equation model (SEM) to analyze the influencing factors of tourists’ waste classification intention and their actual behavior [55]. First, the raw data were coded using SPSS 26.0 to analyze the respondents’ demographic characteristics. Second, confirmatory factor analysis was used to evaluate the measurement model in AMOS 26.0. Combined reliability (CR) was used to verify the internal consistency reliability of each measurement dimension [55]. The stronger the correlation between items, the stronger the explanatory power of the latent variables. The standardized factor loading and the average variance extracted (AVE) were used to test convergent validity [56]. Based on Fornell and Larcker [57], if the correlation coefficients between the paired latent variables were lower than the square root of the AVE of each latent variable, discriminant validity was good. Convergence validity and discriminant validity together explain the construct validity of the measurement model in this study. Thirdly, the bootstrap method was used to test whether waste classification intention played a mediating role between perceived behavior control and waste sorting behavior. The bootstrap was 2000 samples and 95% confidence intervals (CI). If 0 was not contained in the confidence interval of direct and indirect influences, the direct and indirect influences existed [58]. Finally, the paired samples t-test function of SPSS 26.0 was used to verify whether there was a statistically significant difference between tourists’ intention and actual behavior. If there was, it was necessary to explore the influencing factors leading to the difference. The moderating role of the daily habit of waste classification between tourists’ intention and actual behavior was tested by the multi-group analysis [59]. Since the moderator of the daily habit of waste classification was a continuous variable, the daily habit was separated into two subgroups according to the 27% and 73% principle [60]. The averages of the daily habit were ranked from highest to lowest, with the top 27% in the high-level subgroup (n = 144) and the bottom 27% in the low-level subgroup (n = 145). The chi-square (χ2) difference was used to compare the free model and the constrained model of the two subgroups [61]. If the χ2 difference between the two models is significant, the two path coefficients have a significant difference, indicating that the daily habit of waste classification has moderating effects.

4. Results

4.1. Demographic Characteristics

The demographic characteristics of the 382 tourists from West Lake scenic spot are shown in Table 2.

4.2. Reliability and Validity Analysis

The goodness-of-fit of the measurement model was good (χ2/df = 2.394, RMSEA = 0.060, GFI = 0.906, CFI = 0.950, IFI = 0.950, TLI = 0.937, NFI = 0.917) [62]. The CR values were between 0.746 and 0.916, indicating that the internal consistency of these variables was acceptable, which was above the critical value of 0.6 [55]. The standardized factor loadings were between 0.626 and 0.903 (p < 0.001) and exceeded the critical value of 0.60 [63], indicating that the observed variables could effectively explain the latent variables [61]. Meanwhile, the AVE values varied from 0.496 to 0.785, which exceeded the minimum of 0.36 [64], suggesting that the scale had accepted convergent validity. As shown in Table 3, convergent and discriminant validity were satisfied in this study. Finally, the results showed that this scale had acceptable reliability and validity.

4.3. Structural Model Evaluation

The goodness-of-fit of the TPB-AR-DH model (χ2/df = 2.740, RMSEA = 0.068, GFI = 0.906, NFI = 0.919, IFI = 0.947, TLI = 0.934, CFI = 0.947) and the TPB model (χ2/df = 2.988, RMSEA = 0.072, GFI = 0.915, NFI = 0.926, IFI = 0.950, TLI = 0.935, CFI = 0.949) were acceptable based on [62]. The TPB-AR-DH model (χ2/df = 2.740) had a better fit than the TPB model (χ2/df = 2.988). In addition, the TPB-AR-DH model (R2 = 0.608) had a greater predictive ability for waste sorting intentions than the TPB model (R2 = 0.559). However, the TPB-AR-DH model (R2 = 0.424) had lower predictive power for the actual waste classification behavior than the TPB model (R2 = 0.433). Overall, the TPB-AR-DH model had better predictive power than the TPB model.
For hypothesized relationships (Figure 4), attitude towards the behavior (βATT→WCI = 0.268, t = 3.508, p < 0.001), subjective norm (βSN→WCI = 0.166, t = 2.166, p < 0.05), perceived behavioral control (βPBC→WCI = 0.212, t = 3.002, p < 0.01), and ascription of responsibility (βAR→WCI = 0.293, t = 3.699, p < 0.001) positively influenced tourists’ waste classification intention. Thus, H1, H2, H3, and H6 were supported. Perceived behavioral control (βPBC→WCB = 0.387, t = 4.835, p < 0.001) and waste classification intention (βWCI→WCB = 0.341, t = 4.139, p < 0.001) positively influenced tourists’ actual behavior. Thus, H4 and H5 were supported.

4.4. The Mediating Test of Waste Classification Intention

In this study, the CI of indirect effects ranged from 0.023 to 0.206, and 0 was not contained, so the mediating effects existed. The CI of direct effects (0.245–0.659) did not contain 0, so the direct effects also existed. Thus, waste classification intention played a partial mediating role. The indirect effects were 0.072 (βPBC→WCI→WCB = 0.072), the direct effects were 0.387 (βPBC→ WCB = 0.387), and the total effects were 0.459 (βPBC→WCI→WCB + PBC→ WCB = 0.459). All results are shown in Table 4.

4.5. The Moderating Test of the Daily Habit of Waste Classification

The results of the paired samples t-test showed the mean values of tourists’ intention and behavior were 4.276 and 3.489, respectively. The mean difference between tourists’ intention and behavior was −0.787, the 95% confidence interval was −0.867 to −0.707, and the t-value was −19.418 (p < 0.001). Thus, there existed a statistically significant difference between the mean values of tourists’ intentions and the actual behavior of tourism waste classification in West Lake (Table 5).
This finding of the multi-group analysis indicated that the χ2 difference between the two models was significant (Δχ2 = 9.696, p = 0.002, df = 1). For those tourists with a high level of daily habit, waste classification intention had significantly positive influences on the behavior (βDHH = 0.530, t = 3.668, p < 0.001), while for those tourists with a low level of daily habit, the significantly positive influences did not exist (βDHL = 0.012, t = 0.100, p > 0.05). For tourists with high-level daily habits, the positive impact of the waste classification intention on their actual behavior was significantly higher than that of low-level tourists. As a result, H7 was supported.

5. Discussion

5.1. Factors Influencing Tourists’ Waste Classification Intention

The attitude towards the tourism waste classification, the subjective norm from people who had important influences on tourists, and the perceived behavioral control had significant positive influences on tourists’ waste classification intention. This finding was consistent with recent studies of Chinese tourists’ waste reduction and classification behavior [28,29]. Especially, the ascription of responsibility was the most influential factor in promoting the formation of tourists’ intentions in the TPB-AR-DH model. This result confirmed that this study was effective in expanding TPB. The previous study found that the ascription of responsibility had an indirect impact on tourists’ pro-environmental intentions in a green lodging context [41].Therefore, this study further expanded the cognition of the relationship between ascription of responsibility and tourists’ pro-environmental intention. According to the important influence of the above four variables, specific measures should be taken to improve tourists’ waste classification intentions.
First, how can tourists form a positive attitude towards tourism waste classification? Studies have shown that tourists’ environmental knowledge has a positive impact on their attitude towards tourism waste management [1]. Hence, to improve tourists’ knowledge of tourism waste classification, tourism management departments can distribute the waste classification manual to tourists, which can help tourists quickly understand guidelines for waste classification in the destination. The relevant knowledge can be propagated through various network communication channels, such as the official website, the official application, the WeChat/Alipay mini program, and the radios of the tourist destination. In short, when tourists have enough knowledge of waste classification, it is helpful to form positive attitudes and then increase their willingness to participate in tourism waste classification.
Second, improving the subjective norm through increasing social pressures that tourists feel on whether to classify waste in tourist destinations can be an effective way to encourage higher intentions to classify tourism waste. Tourist destinations are public, shared open spaces, and individual behaviors are monitored by surrounding tourists. Therefore, it is necessary to improve the recognition and enthusiasm of all tourists for the necessity of tourism waste classification and to form an atmosphere of mutual supervision, all of which will help to improve tourists’ subjective norms.
Third, to improve tourists’ perceived behavioral control, tourism management departments should pay more attention to perfecting public facilities related to waste classification, such as providing enough bins for segregated waste collection, and the bins should be located in such a way that they are easy to find. In addition, as some tourists are not aware of the standards of waste classification in tourist destinations, waste classification promoters should be arranged to help tourists with waste classification. These measures will help to improve tourists’ perceived behavioral control.
Finally, the perception of social responsibility for environmental protection in tourist destinations affects tourists’ intentions toward waste classification. According to the result of this survey, the average score of the ascription of responsibility was between 4.411 and 4.476 points, indicating that tourists had a strong sense of responsibility to participate in waste classification in West Lake. This also confirmed that the value of “Protecting the environment was everyone’s responsibility” was deeply rooted in the hearts of Chinese people. According to some previous research, tourists had a greater sense of responsibility when they were in the community compared with their sense of responsibility in tourist destinations [11,45]. The result of this study was not exactly the same as the existing conclusions, to some extent. The ascription of responsibility was the most influential factor in the intention of this study. The study showed that when tourists had a strong perception of responsibility for promoting resource recycling and environmental protection, reducing the work pressure of sanitation workers, and protecting sanitation and cleanliness, their willingness to classify tourism waste would increase. Thus, it is effective to increase tourists’ waste classification intention by increasing a sense of responsibility for the positive impact of sorting tourism waste in tourist destinations.

5.2. Factors Influencing Tourists’ Waste Classification Behavior

The results showed that perceived behavioral control and waste classification intention directly affected tourists’ decision-making in actual waste classification behavior, and perceived behavioral control also indirectly affected actual waste classification behavior through waste classification intention. Waste classification intention played a partly mediating role between perceived behavioral control and actual waste classification behavior. It is also worth noting that perceived behavioral control had the largest effects on actual behavior in the TPB-AR-DH model. The result showed that non-volitional variables (perceived behavioral control) were more important than volitional variables (attitude, subjective norm, ascription of responsibility, and waste classification intention), namely, control beliefs (e.g., knowledge and time of waste sorting) and perceived facilitations (e.g., location and number of classified waste bins) were the key influencing factors for tourists’ waste classification behavior. This result was consistent with recent studies that stressed the important role of perceived behavioral control [33,34].

5.3. The Moderating Role of the Daily Habit of Waste Classification

The difference between the intention to classify tourism waste and actual behavior was statistically significant, and tourists’ daily habit of waste classification played a significant moderating role between the intention and actual behavior. For tourists with a high-level sorting habit in daily life, the positive impact of waste classification intention on actual behavior was greater than the low-level subgroup. In line with the previous studies [44,45,52], these studies showed that tourists’ habitual behavior in daily life can have spillover effects on their behaviors at tourist destinations. Based on this survey, more than half of the respondents (60.7%) have implemented the waste classification policy in their daily residences, and 39.4% of respondents have not implemented the waste classification policy in their daily residences. If tourists had the habit of waste classification, paid attention to waste classification policies, and learned about the knowledge of waste classification in daily life, they would be more likely to continue to do so in tourist destinations than people who do not have these habits. Therefore, for China’s waste classification policy to be fully implemented in various contexts, whether in habitual environments (e.g., home or work) or non-habitual environments (e.g., tourist destinations), it is crucial to strengthen daily management so that everyone develops the habit of waste classification.

5.4. Research Significance

5.4.1. Theoretical Significance

Based on the original TPB model, the TPB-AR-DH model incorporated the ascription of responsibility to explain the formation of tourists’ intention of tourism waste classification and added the moderator variable of the daily habit of waste classification to explain the inconsistency between tourists’ intention and the actual behavior of tourism waste classification. Overall, this study provided a new research perspective on tourists’ waste classification behavior in China.
For the TPB-AR-DH model, the explanatory power was better than that of the original TPB model. On the one hand, the newly added variable of the ascription of responsibility was the most influential factor in the form of tourists’ intention for tourism waste classification. The result enriched our understanding of the relationship between the ascription of responsibility and the intention of tourism waste classification. On the other hand, the study found that the daily habit of waste classification significantly moderated the relationship between tourists’ intention to classify tourism waste and their actual behavior, and the high level of daily habit contributed to the conversion from tourists’ intention to classify tourism waste into actual behavior. This may be because waste classification is an activity that is repeated with a high frequency for tourists who have already developed the habit of waste classification in their daily lives. Hence, the habit of waste classification in daily life had spillover effects on their behaviors in tourist destinations.

5.4.2. Practical Significance

The initiative of waste classification is related to whether waste can be effectively reduced, recycled, and reused. This study focused on tourists’ willingness and actual behaviors to participate in the initiative and provided effective experiences and suggestions to improve tourists’ willingness for tourism waste classification.
To begin with, tourists should be strengthened in environmental knowledge education so that they have a positive attitude towards tourism waste classification and an enhanced sense of responsibility for environmental problems. In addition, more waste bins should be supplied to lower tourists’ perceived difficulties with waste classification. Furthermore, tourists often travel with family, friends, partners, colleagues, classmates, etc., and are often surrounded by other tourists in the travel situation, so their pro-environmental behavior while traveling is visible to others. Based on this, from the tourists’ point of view, they should monitor each other while traveling to better leverage subjective norms. All of the above measures will help increase tourists’ willingness to separate waste for disposal.
In particular, this study highlights how tourists’ habits of waste sorting in daily life affect tourism waste classification behavior in tourist destinations. Therefore, the practical challenge is to guide the public to develop the habit of household waste sorting in their daily lives and then to narrow the gap between intention and actual behavior in the context of tourism. Everyone should strengthen the sense of ownership of waste classification, establish the concept of “waste classification, starting from me”, take waste classification as their unshirkable responsibility, develop the good habit of waste classification in daily life, and use their exemplary behavior to motivate people around them to form a good atmosphere in which everyone is responsible for, participates in, and benefits from waste classification. Tourists’ habit of waste classification in daily life is helpful to maximize the spillover effect of daily habitual behavior on tourism waste classification behavior and improve the consistency of intention and actual behavior in a tourism context. These results have practical significance for improving the tourism waste management system and perfecting waste management policies in tourist destinations.

5.5. Research Limitations and Prospects

This study theoretically explored the factors influencing tourists’ intention and actual behavior to classify tourism waste in tourist destinations, which can help tourism managers take relevant measures to improve tourists’ waste classification behavior. However, it also included some limitations.
First of all, regarding the location of the case study, this study is conducted in West Lake, Hangzhou, which is a popular tourist destination for all Chinese. In general, for high and scarce tourism resources, tourists are more inclined to carry out pro-environmental behavior. In other tourist areas, tourists’ intentions and actual behavior toward tourism waste classification may be different. Therefore, in future studies, the influence of different tourism regions and cultural contexts on the TPB-AR-DH model could be considered.
Secondly, in terms of model construction and variable selection, the TPB-AR-DH model is successfully used to explain tourists’ decision-making process of waste classification in tourist destinations and has better explanatory power than the original TPB model, but there is still room for improvement. Therefore, future research could try to use other psychosocial models (such as value-belief norms) or explore other valid variables (such as peer pressure, incentives, cultural backgrounds, etc.) to build models with higher explanatory power.
Finally, regarding data collection, this study relied on self-reported data. Respondents were influenced by social expectations and tended to overestimate their intentions. Therefore, to overcome these limitations, future studies can focus on tourists’ actual behaviors of tourism waste classification with other data sources, such as observed data and experimental data. Despite these limitations, the study hopes that the findings from this empirical study can better reveal the influencing factors and mechanisms of tourists’ waste classification behavior. Moreover, this study can serve as a reference for related studies in different countries, cultures, and tourist destinations.

6. Conclusions

To meet the needs of theory and practice, the TPB-AR-DH model was developed to explore the influencing factors and formation mechanisms of tourists’ waste classification behavior in tourist destinations. First, for tourists’ waste classification intention, there were four significant factors, which were attitude towards the tourism waste classification, subjective norms from people who have important influences on tourists, perceived behavioral control, and ascription of responsibility for the tourism waste classification. Especially, the ascription of responsibility was the most influential factor in promoting the formation of tourists’ intentions of tourism waste classification in the TPB-AR-DH model. Second, for actual behavior, perceived behavioral control had the largest effects on actual behavior in the TPB-AR-DH model, and waste classification intention played a partly mediating role between perceived behavioral control and actual waste classification behavior. Finally, the difference between waste classification intention and actual behavior was statistically significant, and tourists’ daily habit of waste classification played a significant moderating role between tourists’ waste classification intention and actual behavior. For tourists with a high-level habit of waste classification in daily life, the positive impact of waste classification intention on actual behavior was greater than the low-level subgroup. On the whole, this study offered a theoretical explanation model to popularize the initiative of tourism waste classification and perfect waste management policies in tourist destinations.

Author Contributions

Conceptualization, H.H. and Y.Z.; methodology, H.H.; software, H.H. and Y.Z.; validation, H.H.; formal analysis, H.H.; investigation, H.H.; resources, H.H.; data curation, H.H. and C.W.; writing—original draft preparation, H.H.; writing—review and editing, H.H.; visualization, H.H. and P.Y.; supervision, H.H., C.W. and P.Y.; project administration, H.H. C.W. and P.Y.; funding acquisition, H.H. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Natural Science Foundation of China, grant number 42101220; the Zhejiang Provincial Philosophy and Social Sciences Planning Project, grant number 23NDJC276YB; the Scientific Research Fund of Zhejiang Provincial Education Department, grant number Y202044813; and the National Natural Science Foundation of China, grant number 42201238 and 42301245.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data used in the current study are available from the corresponding author on reasonable request.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Hu, H.; Zhang, J.; Chu, G.; Yang, J.; Yu, P. Factors influencing tourists’ litter management behavior in mountainous tourism areas in China. Waste Manag. 2018, 79, 273–286. [Google Scholar] [CrossRef]
  2. Chaabane, W.; Nassour, A.; Bartnik, S.; Bünemann, A.; Nelles, M. Shifting towards sustainable tourism: Organizational and financial scenarios for solid waste management in tourism destinations in Tunisia. Sustainability 2019, 11, 3591. [Google Scholar] [CrossRef]
  3. Muñoz, E.; Navia, R. Waste management in touristic regions. Waste Manag. Res. 2015, 33, 593–594. [Google Scholar] [CrossRef]
  4. Wilson, D.C.; Rodic, L.; Modak, P.; Soos, R.; Rogero, A.C.; Velis, C.; Iyer, M.; Simonett, O. Global Waste Management Outlook; United Nations Environment Programme: Nairobi, Kenya, 2015. [Google Scholar]
  5. Li, L.; Yue, G.; Xinquan, G.; Yingmei, Y.; Hua, C.; Jianping, H.; Jian, Z. Exploring the residents’ intention to separate MSW in Beijing and understanding the reasons: An explanation by extended VBN theory. Sust. Cities Soc. 2018, 37, 637–648. [Google Scholar] [CrossRef]
  6. Chen, Y.; Wu, W. Constructing an effective prevention mechanism for MSW lifecycle using failure mode and effects analysis. Waste Manag. 2015, 46, 646–652. [Google Scholar] [CrossRef] [PubMed]
  7. Gaeta Bernardi, A.; Parente, V. Organic municipal solid waste (MSW) as feedstock for biodiesel production: A financial feasibility analysis. Renew. Energy. 2016, 86, 1422–1432. [Google Scholar] [CrossRef]
  8. Ge-Zhang, S.; Cai, T.; Hu, Z.; Zhu, H.; Mu, P.; Cui, J. Investigation and Suggestions regarding Residents’ Understanding of Waste Classification in Chinese Prefecture-Level Cities—A Case Study of Maanshan City, Anhui Province, China. Sustainability 2023, 15, 11124. [Google Scholar] [CrossRef]
  9. He, J.; Yu, Z.; Fukuda, H. Extended theory of planned behavior for predicting the willingness to pay for municipal solid waste management in Beijing. Sustainability 2021, 13, 13902. [Google Scholar] [CrossRef]
  10. Knussen, C.; Yule, F. “I’m not in the habit of recycling” The role of habitual behavior in the disposal of household waste. Environ. Behav. 2008, 40, 683–702. [Google Scholar] [CrossRef]
  11. Ouellette, J.A.; Wood, W. Habit and intention in everyday life: The multiple processes by which past behavior predicts future behavior. Psychol. Bull. 1998, 124, 54–74. [Google Scholar] [CrossRef]
  12. MacInnes, S.; Grün, B.; Dolnicar, S. Habit drives sustainable tourist behaviour. Ann. Touris. Res. 2022, 92, 103329. [Google Scholar] [CrossRef]
  13. Hu, H.; Zhang, J.; Wang, C.; Yu, P.; Chu, G. What influences tourists’ intention to participate in the Zero Litter Initiative in mountainous tourism areas: A case study of Huangshan National Park, China. Sci. Total Environ. 2019, 657, 1127–1137. [Google Scholar] [CrossRef] [PubMed]
  14. Vaske, J.J.; Jacobs, M.H.; Espinosa, T.K. Carbon footprint mitigation on vacation: A norm activation model. J. Outdo. Recreat. Tour. Res. Plan. 2015, 11, 80–86. [Google Scholar] [CrossRef]
  15. Ajzen, I.; Fishbein, M. A Bayesian analysis of attribution processes. Psychol. Bull. 1975, 82, 261. [Google Scholar] [CrossRef]
  16. Ajzen, I. The theory of planned behavior. Organ. Behav. Hum. Decis. Process. 1991, 50, 179–211. [Google Scholar] [CrossRef]
  17. Gansser, O.A.; Reich, C.S. Influence of the new ecological paradigm (NEP) and environmental concerns on pro-environmental behavioral intention based on the theory of planned behavior (TPB). J. Clean. Prod. 2023, 382, 134629. [Google Scholar] [CrossRef]
  18. Yuriev, A.; Dahmen, M.; Paillé, P.; Boiral, O.; Guillaumie, L. Pro-environmental behaviors through the lens of the theory of planned behavior: A scoping review. Resour. Conserv. Recycl. 2020, 155, 104660. [Google Scholar] [CrossRef]
  19. Gao, L.; Wang, S.; Li, J.; Li, H. Application of the extended theory of planned behavior to understand individual’s energy saving behavior in workplaces. Resour. Conserv. Recycl. 2017, 127, 107–113. [Google Scholar] [CrossRef]
  20. Chen, M. Extending the theory of planned behavior model to explain people’s energy savings and carbon reduction behavioral intentions to mitigate climate change in Taiwan–moral obligation matters. J. Clean. Prod. 2016, 112, 1746–1753. [Google Scholar] [CrossRef]
  21. Aboelmaged, M. E-waste recycling behaviour: An integration of recycling habits into the theory of planned behaviour. J. Clean. Prod. 2021, 278, 124182. [Google Scholar] [CrossRef]
  22. Mak, T.M.; Iris, K.; Wang, L.; Hsu, S.C.; Tsang, D.C.; Li, C.; Yeung, T.L.; Zhang, R.; Poon, C.S. Extended theory of planned behaviour for promoting construction waste recycling in Hong Kong. Waste Manag. 2019, 83, 161–170. [Google Scholar] [CrossRef]
  23. Liu, M.T.; Liu, Y.; Mo, Z. Moral norm is the key: An extension of the theory of planned behaviour (TPB) on Chinese consumers’ green purchase intention. Asia Pac. J. Market. Logist. 2020, 32, 1823–1841. [Google Scholar] [CrossRef]
  24. Yadav, R.; Pathak, G.S. Determinants of consumers’ green purchase behavior in a developing nation: Applying and extending the theory of planned behavior. Ecol. Econ. 2017, 134, 114–122. [Google Scholar] [CrossRef]
  25. Clark, E.; Mulgrew, K.; Kannis-Dymand, L.; Schaffer, V.; Hoberg, R. Theory of planned behaviour: Predicting tourists’ pro-environmental intentions after a humpback whale encounter. J. Sustain. Tour. 2019, 27, 649–667. [Google Scholar] [CrossRef]
  26. Badawi, A.N.; Adelazim Ahmed, T.S.; Alotaibi, E.K.; Abbas, I.S.; Ali, E.R.; Shaker, E.S.M. The Role of Awareness of Consequences in Predicting the Local Tourists’ Plastic Waste Reduction Behavioral Intention: The Extension of Planned Behavior Theory. Sustainability 2024, 16, 436. [Google Scholar] [CrossRef]
  27. Han, H.; Chua, B.-L.; Hyun, S.S. Eliciting customers’ waste reduction and water saving behaviors at a hotel. Int. J. Hosp. Manag. 2020, 87, 102386. [Google Scholar] [CrossRef]
  28. Wang, S.; Ji, C.; He, H.; Zhang, Z.; Zhang, L. Tourists’ waste reduction behavioral intentions at tourist destinations: An integrative research framework. Sustain. Prod. Consum. 2021, 25, 540–550. [Google Scholar] [CrossRef]
  29. Cao, J.; Qiu, H.; Morrison, A.M.; Wei, W. The role of social capital in predicting tourists’ waste sorting intentions in rural destinations: Extending the theory of planned behavior. Int. J. Environ. Res. Public Health 2022, 19, 12789. [Google Scholar] [CrossRef] [PubMed]
  30. Ulker Demirel, E.; Ciftci, G. A systematic literature review of the theory of planned behavior in tourism, leisure and hospitality management research. J. Hosp. Tour. Manag. 2020, 43, 209–219. [Google Scholar] [CrossRef]
  31. Soorani, F.; Ahmadvand, M. Determinants of consumers’ food management behavior: Applying and extending the theory of planned behavior. Waste Manag. 2019, 98, 151–159. [Google Scholar] [CrossRef] [PubMed]
  32. Si, H.; Shi, J.; Tang, D.; Wu, G.; Lan, J. Understanding intention and behavior toward sustainable usage of bike sharing by extending the theory of planned behavior. Resour. Conserv. Recycl. 2020, 152, 104513. [Google Scholar] [CrossRef]
  33. Wang, C.; Zhang, J.; Cao, J.; Hu, H.; Yu, P. The influence of environmental background on tourists’ environmentally responsible behaviour. J. Environ. Manag. 2019, 231, 804–810. [Google Scholar] [CrossRef] [PubMed]
  34. Wang, C.; Zhang, J.; Yu, P.; Hu, H. The theory of planned behavior as a model for understanding tourists’ responsible environmental behaviors: The moderating role of environmental interpretations. J. Clean. Prod. 2018, 194, 425–434. [Google Scholar] [CrossRef]
  35. Botetzagias, I.; Dima, A.F.; Malesios, C. Extending the theory of planned behavior in the context of recycling: The role of moral norms and of demographic predictors. Resour. Conserv. Recycl. 2015, 95, 58–67. [Google Scholar] [CrossRef]
  36. Razali, F.; Daud, D.; Weng Wai, C.; Jiram, W.R.A. Waste separation at source behaviour among Malaysian households: The Theory of Planned Behaviour with moral norm. J. Clean. Prod. 2020, 271, 122025. [Google Scholar] [CrossRef]
  37. Han, H.; Yu, J.; Kim, W. Youth travelers and waste reduction behaviors while traveling to tourist destinations. J. Travel Tour. Mark. 2018, 35, 1119–1131. [Google Scholar] [CrossRef]
  38. 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]
  39. Zhang, B.; Lai, K.H.; Wang, B.; Wang, Z. From intention to action: How do personal attitudes, facilities accessibility, and government stimulus matter for household waste sorting? J. Environ. Manag. 2019, 233, 447–458. [Google Scholar] [CrossRef]
  40. Lin, M.T.B.; Zhu, D.; Liu, C.; Kim, P.B. A meta-analysis of antecedents of pro-environmental behavioral intention of tourists and hospitality consumers. Tour. Manag. 2022, 93, 104566. [Google Scholar] [CrossRef]
  41. Han, H. Travelers’ pro-environmental behavior in a green lodging context: Converging value-belief-norm theory and the theory of planned behavior. Tour. Manag. 2015, 47, 164–177. [Google Scholar] [CrossRef]
  42. Wang, S.; Wang, J.; Yang, S.; Li, J.; Zhou, K. From intention to behavior: Comprehending residents’ waste sorting intention and behavior formation process. Waste Manag. 2020, 113, 41–50. [Google Scholar] [CrossRef]
  43. Su, L.; Swanson, S.R. The effect of destination social responsibility on tourist environmentally responsible behavior: Compared analysis of first-time and repeat tourists. Tour. Manag. 2017, 60, 308–321. [Google Scholar] [CrossRef]
  44. Xu, F.; Huang, L.; Whitmarsh, L. Home and away: Cross-contextual consistency in tourists’ pro-environmental behavior. J. Sustain. Tour. 2020, 28, 1443–1459. [Google Scholar] [CrossRef]
  45. Miller, D.; Merrilees, B.; Coghlan, A. Sustainable urban tourism: Understanding and developing visitor pro-environmental behaviours. J. Sustain. Tour. 2014, 23, 26–46. [Google Scholar] [CrossRef]
  46. De Young, R. Promoting conservation behavior in shared spaces: The role of energy monitors. J. Environ. Syst. 1989, 19, 265–273. [Google Scholar] [CrossRef]
  47. Verplanken, B.; Aarts, H. Habit, attitude, and planned behaviour: Is habit an empty construct or an interesting case of goal-directed automaticity? Eur. Rev. Soc. Psychol. 1999, 10, 101–134. [Google Scholar] [CrossRef]
  48. Wood, W.; Neal, D.T. The habitual consumer. J. Consum. Psychol. 2009, 19, 579–592. [Google Scholar] [CrossRef]
  49. Lally, P.; Gardner, B. Promoting habit formation. Health Psychol. Rev. 2013, 7, S137–S158. [Google Scholar] [CrossRef]
  50. Barr, S.; Shaw, G.; Coles, T.; Prillwitz, J. ‘A holiday is a holiday’: Practicing sustainability, home and away. J. Transp. Geogr. 2010, 18, 474–481. [Google Scholar] [CrossRef]
  51. Becken, S. Tourists’ perception of international air travel’s impact on the global climate and potential climate change policies. J. Sustain. Tour. 2007, 15, 351–368. [Google Scholar] [CrossRef]
  52. Liu, A.; Ma, E.; Qu, H.; Ryan, B. Daily green behavior as an antecedent and a moderator for visitors’ pro-environmental behaviors. J. Sustain. Tour. 2020, 28, 1390–1408. [Google Scholar] [CrossRef]
  53. Limayem, M.; Hirt, S.G.; Cheung, C.M. How habit limits the predictive power of intention: The case of information systems continuance. MIS Q. 2007, 31, 705–737. [Google Scholar] [CrossRef]
  54. Mullen, M.R. Diagnosing measurement equivalence in cross-national research. J. Int. Bus. Stud. 1995, 26, 573–596. [Google Scholar] [CrossRef]
  55. Bagozzi, R.P.; Yi, Y. On the evaluation of structural equation models. J. Acad. Market. Sci. 1988, 16, 74–94. [Google Scholar] [CrossRef]
  56. Hair, J.F.; Ringle, C.M.; Sarstedt, M. PLS-SEM: Indeed a silver bullet. J. Martet. Theory Pract. 2011, 19, 139–152. [Google Scholar] [CrossRef]
  57. 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]
  58. Preacher, K.J.; Hayes, A.F. Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behav. Res. Methods 2008, 40, 879–891. [Google Scholar] [CrossRef]
  59. Byrne, B.M. Structural Equation Modeling with AMOS: Basic Concepts, Applications, and Programming, 3rd ed.; Routledge: New York, NY, USA, 2016. [Google Scholar] [CrossRef]
  60. Ross, J.; Weitzman, R. The twenty-seven per cent rule. Ann. Math. Statist. 1964, 35, 214–221. [Google Scholar] [CrossRef]
  61. Anderson, J.C.; Gerbing, D.W. Structural equation modeling in practice: A review and recommended two-step approach. Psychol. Bull. 1988, 103, 411–423. [Google Scholar] [CrossRef]
  62. Hu, L.; Bentler, P.M. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Struct. Equ. Model. 1999, 6, 1–55. [Google Scholar] [CrossRef]
  63. Chin, W.W.; Peterson, R.A.; Brown, S.P. Structural equation modeling in marketing: Some practical reminders. J. Martet. Theory Pract. 2008, 16, 287–298. [Google Scholar] [CrossRef]
  64. Chin, W.W. Commentary: Issues and opinion on structural equation modeling. MIS Q. 1998, 22, vii–xvi. [Google Scholar]
Sustainability 16 01231 g001
Figure 1. Proposed conceptual model. Note 1: ATT = attitude towards the behavior, SN = subjective norm, PBC = perceived behavioral control, AR = ascription of responsibility, WCI = waste classification intention, WCB = waste classification behavior, and DH = the daily habit of waste classification.
Figure 1. Proposed conceptual model. Note 1: ATT = attitude towards the behavior, SN = subjective norm, PBC = perceived behavioral control, AR = ascription of responsibility, WCI = waste classification intention, WCB = waste classification behavior, and DH = the daily habit of waste classification.
Sustainability 16 01231 g001
Sustainability 16 01231 g002
Figure 2. The location of the study area.
Figure 2. The location of the study area.
Sustainability 16 01231 g002
Sustainability 16 01231 g003
Figure 3. The map of the study area.
Figure 3. The map of the study area.
Sustainability 16 01231 g003
Sustainability 16 01231 g004
Figure 4. Results of the structural equation model. Note 1: DHH = the high level of daily habit; DHL = the low level of daily habit. Note 2: *** significance at p < 0.001, ** significance at p < 0.01, * significance at p < 0.05.
Figure 4. Results of the structural equation model. Note 1: DHH = the high level of daily habit; DHL = the low level of daily habit. Note 2: *** significance at p < 0.001, ** significance at p < 0.01, * significance at p < 0.05.
Sustainability 16 01231 g004
Table 1. Measurement items.
Table 1. Measurement items.
Variable Items and Sources
ATTAttitude toward the behavior [1,16,42].
ATT1I think it is worthwhile for tourists to classify waste in West Lake.
ATT2I think it is wise for tourists to classify waste in West Lake.
ATT3I think it is beneficial for tourists to classify waste in West Lake.
SNSubjective norm [1,16,42].
SN1People who are important to me agree with me about classifying waste in West Lake.
SN2People who are important to me want me to classify waste in West Lake.
SN3People who are important to me think I should classify waste in West Lake.
PBCPerceived behavioral control [1,16,42].
PBC1It is easy to classify waste for me in West Lake.
PBC2I had the time and ability to classify waste in West Lake.
PBC3It is convenient to classify waste for me in West Lake.
ARAscription of responsibility [38,39,41].
AR1I have the responsibility to promote resource recycling and environmental protection through waste classification in West Lake.
AR2I have the responsibility to relieve the pressure on sanitation workers through waste classification in West Lake.
AR3I have the responsibility to protect the sanitation of West Lake through waste classification.
DHDaily habit of waste classification [10,52].
DH1I have the habit of classifying waste in my daily life.
DH2I have paid attention to waste classification policies in my daily life.
DH3I have learned about the knowledge of waste classification in my daily life.
WCIWaste classification intention [16,39].
WCI1I am willing to abide by the waste classification policy in West Lake.
WCI2I am willing to persuade travel companions to classify their waste in West Lake.
WCI3I am willing to learn about waste classification in West Lake.
WCBWaste classification behavior [16,39].
WCB1I     classified waste in West Lake.
WCB2I     persuaded your travel companions to classify their waste at West Lake.
WCB3I     learned about waste classification in West Lake.
Table 2. Demographics of respondents (n = 382).
Table 2. Demographics of respondents (n = 382).
Variablen%Variablen%
Sex Age
Male18648.69<1782.09
Female19651.3118–3025466.49
Education Level 31–458823.04
Less than High School328.3846–60318.12
High School/Technical School8321.73>6110.26
Undergraduate Degree21957.33Monthly Income (RMB)
Postgraduate Degree4812.56Under 3000 17445.55
Does the daily residence have a waste sorting policy? 3001–60009424.61
Yes23260.736001–90007218.85
No15039.279000–12,000225.76
Over 12,000205.23
Table 3. Convergent and discriminant validity of latent variables.
Table 3. Convergent and discriminant validity of latent variables.
DimItem ReliabilityComposite ReliabilityConvergence ValidityDiscriminate Validity
Std. LoadingCRAVEWCBWCIARDHPBCSNATT
WCB0.626–0.8290.7860.5540.744
WCI0.690–0.7140.7440.4920.6090.701
AR0.783–0.8380.8590.670.3600.6970.819
DH0.690–0.8560.8340.6290.5260.5580.5080.793
PBC0.702–0.8230.8200.6040.5920.6010.5310.5570.777
SN0.817–0.8990.8890.7270.4670.6390.6330.5090.6150.853
ATT0.856–0.9030.9170.7860.3100.6780.6310.3620.5040.5730.887
Note 1: Diagonal values indicated the square root of AVE of each latent variable. Note 2: Underneath of diagonal indicated the correlation matrix of latent variables.
Table 4. The result of the mediating effect of waste classification intention.
Table 4. The result of the mediating effect of waste classification intention.
PathEffectBias-Corrected PercentilePercentile
LowerUpperLowerUpper
PBC→WCBTotal effects0.3320.7220.3460.737
Indirect effects0.0230.2060.0120.186
Direct effects0.2450.6590.2520.666
Note: 2000 bootstrap samples; 95% confidence intervals.
Table 5. The results of paired samples t-test.
Table 5. The results of paired samples t-test.
Paired Differences
MeanStd. DevS.E. Mean95% CI of the DifferencetdfSig. (2-Tailed)
LowerUpper
WCB–WCI−0.7870.7920.041−0.867−0.707−19.4183810.000
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Hu, H.; Zhang, Y.; Wang, C.; Yu, P. Factors Influencing Tourists’ Intention and Behavior toward Tourism Waste Classification: A Case Study of the West Lake Scenic Spot in Hangzhou, China. Sustainability 2024, 16, 1231. https://doi.org/10.3390/su16031231

AMA Style

Hu H, Zhang Y, Wang C, Yu P. Factors Influencing Tourists’ Intention and Behavior toward Tourism Waste Classification: A Case Study of the West Lake Scenic Spot in Hangzhou, China. Sustainability. 2024; 16(3):1231. https://doi.org/10.3390/su16031231

Chicago/Turabian Style

Hu, Huan, Yu Zhang, Chang Wang, and Peng Yu. 2024. "Factors Influencing Tourists’ Intention and Behavior toward Tourism Waste Classification: A Case Study of the West Lake Scenic Spot in Hangzhou, China" Sustainability 16, no. 3: 1231. https://doi.org/10.3390/su16031231

APA Style

Hu, H., Zhang, Y., Wang, C., & Yu, P. (2024). Factors Influencing Tourists’ Intention and Behavior toward Tourism Waste Classification: A Case Study of the West Lake Scenic Spot in Hangzhou, China. Sustainability, 16(3), 1231. https://doi.org/10.3390/su16031231

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop