Perceived Value, Place Identity, and Behavioral Intention: An Investigation on the Influence Mechanism of Sustainable Development in Rural Tourism

Abstract

Rural tourism has been a hot spot in tourism studies in recent years. This research uses Attitude Theory to investigate the influence mechanism of tourists’ perceived value and place identity on their behavioral intention in rural tourism in Zhejiang Province, China. The study adopts the PLS-SEM method to process the data. The results indicate that tourists’ behavioral intention is positively influenced by their perceived value and place identity. Additionally, perceived value has a positive impact on tourists’ place identity, and place identity plays a positive intermediary role between perceived value and behavioral intention. Meanwhile, cultural value is perceived as having the greatest influence on place identity and behavioral intention. Therefore, rural tourist destinations should focus on cultural value and the tourists’ sense of place to promote sustainable rural tourism development.

1. Introduction

The development of rural tourism helps to increase the non-agricultural income of residents, promote the realization of rural revitalization, and strengthen the sustainable development of rural areas [1,2]. In recent years, the income level of people in China has increased. Along with a series of negative impacts on people’s lives created by the development of urbanization, the attraction of rural tourism is growing [3]. China’s rural tourism has also induced a period of booming development. Especially during COVID-19, rural tourism has become the preferred destination for Chinese tourists’ leisure and vacation [3]. In 2019, China’s rural leisure tourism industry received 3.3 billion tourists, with an operating income of more than CNY 850 billion [4]. In China’s rural tourism industry, the development trend of Zhejiang Province is particularly good. Receiving 570 million tourists, rural tourism accounted for 65% in Zhejiang Province in 2020, realizing a total income of CNY 43.13 billion from tourism operations and employing 446,000 people [5]. In 2021, Yucun Village in Huzhou City, Zhejiang Province, became one of the “Best Tourism Villages of 2021 by United Nations World Tourism Organization”, which indicates that it is one of the best choices according to Chinese rural tourists. Zhejiang villages have become an “important window” to show China’s rural tourism to the world [5].

Rural tourism has always been an important area of tourism academic research, but the academic community has not yet formed a unified perception of the definition of rural tourism. The current broadest understanding is tourism activities in non-urban areas or rural areas [6]. In this context, rural areas refer to spaces that are remote from urban areas and can be further distinguished from urban areas by a number of indicators, including population density, demographics, commuting patterns, migration, and proximity to population centers of various sizes [7]. Rural tourism in tourism research is defined as benefiting the local economy and society by showcasing the rural life, art, culture, and heritage of rural areas and enriching the tourism experience through the interaction between tourists and locals [8]. Over the years, several scholars have studied rural tourism from the rural tourism motivation [9,10,11,12], rural tourism experience [1,13,14,15], rural tourism from the perspective of rural residents [16,17,18,19], rural tourism development [20,21,22,23], and changes created by rural tourism [24,25,26,27]. These studies have laid a sufficient theoretical foundation for this research.

Culture is one of the important attributes of a destination [28], and regional cultural elements can lead to changes in the regional cultural atmosphere [29]. With the promotion of the general trend of integrated development of culture and tourism, regional culture has become an essential resource element in tourism. The countryside is a place with cultural connotations [7]. China’s countryside, with its long history and rich folk culture, has the potential and market for the development of cultural tourism. Therefore, the degree of cultural development is bound to impact the development of rural tourism [30]. Tang and Xu (2023) believed that tourism activities that integrate local resources and culture in the countryside have a unique attraction to tourists [31]. Cultural elements are the tangible embodiment of regional culture, which can enrich tourists’ experience and satisfy their spiritual needs. In contrast, cultural value expresses tourists’ perceptions and evaluations of regional cultural elements [32]. However, in the study of perceived value, few researchers have explored the cultural value, and more research has been conducted on the impact of regional culture on tourists’ satisfaction [33,34] and behavioral intention [35], which indicates a lack of research on the possible impact of the cultural value on tourists’ place identity and behavioral intention in tourism destinations. In the tourism literature, the relationship between the three dimensions of perceived value, place identity, and behavioral intention has been identified by research [36,37]. However, fewer studies have been conducted on all three dimensions simultaneously [38]. Therefore, based on several studies on organizational culture, this study introduced cultural value as one of the components of perceived value and investigated its impact on tourists’ place identity and behavioral intention, thus enriching the content of the research field, which is also the main contribution of this paper.

Based on the above viewpoints, this study proposes a research model of rural tourists’ behavioral intention in Zhejiang Province based on Attitude Theory, and the conceptual model includes tourists’ perceived value, place identity, and behavioral intention. At the theoretical level, this study verifies the applicability of Attitude Theory in the field of rural tourism research and elaborates on the theoretical logic of generating behavioral intentions among rural tourists in Zhejiang Province. In addition, this study introduces cultural value as one of the variables of perceived value research. It investigates its potential impact on tourists’ place identity and behavioral intention, which enriches the dimension of theoretical research in this area. At the practical level, this study focuses on rural tourism development in Zhejiang Province, China. The selected Zhejiang villages serve as research cases, providing valuable insights for tourism enterprises (refers to those enterprises that specialize in providing tourism-related services or products), as well as the government, to formulate effective policies. This will help to achieve the vision of improving and upgrading the quality of China’s tourism industry, promoting the sustainable development of rural tourism.

2. Theoretical Background and Model Construction

2.1. Theoretical Background

Attitude Theory is frequently used to explain individual behavioral mechanisms [39]. This theory, proposed by Bagozzi (1992), examines the effects of emotional experiences on intentions or behaviors based on traditional behavioral theories such as the Theory of Reasoned Action, the Theory of Planned Behavior, and the Theory of Trying. Bagozzi summarized the self-regulating of tourists as follows: “Appraisal → Emotional response → Coping”. “Appraisal” refers to the outcome of a person based on a specific experience, which triggers an “Emotional response” that drives positive or negative “Coping” tendencies [40]. In tourism research, Attitude Theory has often been used to investigate the influence of factors on tourists’ behavior, such as civilized behavior [41] and environmental protection [42].

Tourists’ perceived value is an objective evaluation that has often been found to precede emotional reactions in previous research [43]. Place identity refers to the emotional attachment of tourists to a tourist destination [43]. Behavioral intention indicates the degree to which tourists are likely to behave in a certain way [44]. Therefore, this study applies Attitude Theory to the survey of behavioral intention among rural tourists in Zhejiang Province. This study categorizes the perceived value of rural tourists in the “Appraisal” stage, place identity in the “Emotional response” stage, and behavioral intention in the “Coping” tendency stage so as to study the relationship between rural tourists’ perceived value, place identity, and behavioral intention. Combined with previous research, the research hypothesis research model of this paper is proposed, as shown in Figure 1.

2.2. Perceived Value and Place Identity

Perceived value is a kind of comprehensive evaluation formed in the process of tourist experience, which is the real feeling of tourists about their current location [45]. Because of the complexity and diversity of the research object, academic research on the dimensional categorization of perceived value is constantly evolving and developing, and two main views, single-dimensional and multidimensional, have emerged. At the beginning of this area of study, scholars more often used single-dimension measurement and studied perceived value from the perspective of utilitarianism, perceived gain, and perceived loss [46]. However, an increasing number of scholars have questioned the validity of single-dimensional perceived value measurement, and a diversified multidimensional view of measurement has emerged. Nowadays, the main multidimensional perceived value measurements in academic research include “two-dimensional value theory” [47], “three-dimensional value theory” [48], “four-dimensional value theory” [49], and “five-dimensional value theory” [50]. Each dimension of the value theory has various combinations. In tourism research, the perceived value was first applied in hotel service research [44] and then in vacation, nature tourism, and other research fields [51,52,53]. It is often used to measure tourists’ feelings toward a certain form of tourism or a certain tourist destination.

Place identity is a positive emotion that an individual feels toward a place and an emotional attachment that results from it. It expresses the extent to which a place meets an individual’s expectations, needs, or standards for life and is a form of positive emotional feedback about the place [54]. The concept of place identity was derived from “place attachment”. Williams and Roggenbuck (1989) proposed the concept of “place attachment” [55], which consists of functional and affective attachments, of which affective attachment was defined as place identity in a subsequent study [56]. Hernández et al. (2007) defined place identity as the process by which a person interacts with a place during the tourism experience and describes himself or herself in terms of “belonging to a particular place”, which he considered to be part of the personal identity [57]. In tourism research, place identity is often used to explain tourist behavior or attitudinal intentions [58,59].

Attitude Theory suggests that tourists’ evaluations affect their emotional changes. Some scholars have studied the relationship between tourists’ perceived value and place identity and concluded that a certain tourism perception affects place attachment [60], tourism loyalty [37,61], and place identity [44]. Therefore, it is believed that perceived value positively affects place identity. That is, the higher the perceived value, the higher the degree of place identity of tourists. Therefore, the following hypotheses are proposed:

Hypothesis 1a (H1a).

Emotional value has a significant positive influence on place identity.

Hypothesis 1b (H1b).

Social value has a significant positive influence on place identity.

Hypothesis 1c (H1c).

Value for money has a significant positive influence on place identity.

Hypothesis 1d (H1d).

Cultural value has a significant positive influence on place identity.

2.3. Perceived Value and Behavioral Intention

Behavioral intention refers to the extent to which a tourist consciously decides to perform or not to perform a behavior in the future and is regarded as the “likelihood of action” [62]. The behavioral intention of tourists is a subjective judgment of the probability of tourists’ tendency to perform a behavior in the future [63]. According to Lin and Wang, (2012), behavioral intention is different from action, but closely related; if we can fully understand the behavioral intention of consumers, we can effectively predict their future behavior [64]. Academics have often measured tourists’ behavioral intentions in terms of revisit intentions, recommendation intentions, and payment intentions resulting from their experiences [65]. In previous tourism research, behavioral intention usually existed as an outcome variable, which was used to measure the real behavioral tendencies of tourists, such as the intention to revisit [66], recommendation intention [67], pro-environmental behavioral intention [68], and volunteering behavioral intention [69].

Attitude Theory suggests that tourists’ positive or negative emotional responses cause changes in their behavioral tendencies. Many studies have examined the perceived value of tourism as an antecedent variable of tourists’ behavioral intention and confirmed that perceived value has a positive effect on tourists’ behavioral intention [70,71,72]. For example, Fu et al., (2018) surveyed souvenir consumers, and their study confirmed that consumer perceived value has a positive effect on behavioral intention [70]. That is to say, the higher the perceived value of tourists’ tourism, the clearer their behavioral intention. Therefore, the following hypotheses are proposed:

Hypothesis 2a (H2a).

Emotional value has a significant positive influence on behavioral intention.

Hypothesis 2b (H2b).

Social value has a significant positive influence on behavioral intention.

Hypothesis 2c (H2c).

Value for money has a significant positive influence on behavioral intention.

Hypothesis 2d (H2d).

Cultural value has a significant positive influence on behavioral intention.

2.4. Perceived Value, Place Identity, and Behavioral Intention

According to Attitude Theory, tourists’ perceived value produces negative or positive emotional responses, and the strength of the emotional response affects the individual’s behavioral tendencies [73]. The stronger the positive emotion, the more obvious the tendency to positive behavior [73]. Research has already shown that tourists create or counteract a sense of place identity in the process of interacting with tourist locations and generating personal preferences for emotional choices, which in turn affects individual actions or behaviors [74]. In other words, the higher the degree of place identity, the stronger the individual’s behavioral intention [74,75]. Therefore, it can be assumed that tourists’ place identity affects their behavioral intention, and the higher the tourists’ place identity is, the more obvious their willingness to pay, revisit, and recommend. Because tourists’ perceived value has a positive influence on both place identity and behavioral intention, it is believed that place identity mediates the relationship between tourists’ perceived value and behavioral intention, which has been confirmed in research. Zhang et al., (2023) studied place attachment as a mediating variable between tourists’ perceived value and behavioral intention, in which the place attachment dimension includes place identity and place dependence [38]. Their study confirmed that place identity has a mediating role between perceived value and behavioral intention. Therefore, the following hypotheses are proposed:

Hypothesis 3 (H3).

Place identity has a significant positive influence on behavioral intention.

Hypothesis 4a (H4a).

Place identity mediates between emotional value and behavioral intention.

Hypothesis 4b (H4b).

Place identity mediates between social value and behavioral intention.

Hypothesis 4c (H4c).

Place identity mediates between value for money and behavioral intention.

Hypothesis 4d (H4d).

Place identity mediates between cultural value and behavioral intention.

3. Method

3.1. Survey Instrument and Measures

The variables in this study include the three dimensions of tourists’ perceived value, place identity, and behavioral intention. In this study’s questionnaire, the 5-level Likert scale (1 = “totally disagree”, 5 = “totally agree”) is used for all variables. Referring to the existing research results [49,76,77,78] and considering the actual needs of the research, this paper categorizes the tourists’ perceived value into emotional value, value for money, social value, and cultural value. The measurements for emotional value and value for money were selected from the study by Sweeney and Soutar, (2001) [49]. The measurements for social value were adapted from the study by Dedeoğlu, (2019) [79], which is more relevant to rural tourism. There are fewer measurements for cultural value, and the question settings were selected from the studies of Chinese scholars Ma and Bao, (2012) [80] and Zhou et al., (2012) [81]. The scale questions for the place identity dimension were selected from the study by Williams and Roggenbuck, (1989) [55]. Lastly, behavioral intention scale questions were selected from a study by Zhou, Hu, and Cao, (2023) [82].

The scales selected for use in this questionnaire were from the existing literature, which had good reliability and validity. Taking into account the specific characteristics of rural tourism, the investigators made minor adjustments to the wording of the scales in order to better suit the needs of the survey. Experts were consulted after the questionnaire was developed to confirm that the adjusted questionnaire items still maintained the original intent. Since the survey respondents were basically from within China, the adjusted questionnaire items were translated into Chinese by professionals for subsequent distribution of the questionnaire. After collecting and translating the questionnaires back into English, the researchers compared them with the original English versions. Any discrepancies were discussed with experts in tourism and linguistics, and adjustments were made to ensure that the questionnaire’s meaning was conveyed accurately.

3.2. Data Collection and Participants

The study sample included only tourists living in mainland China who had experienced rural tourism in Zhejiang Province within the past three years. There are many rural tourist attractions in Zhejiang Province, and to maximize the generality of the study, this study took the form of an online distribution of questionnaires to collect data. This study was distributed through wenjuanxing.cn (a major survey platform in China), and to ensure the validity of the sample, two measures were taken in the formal survey: (1) The researchers ensured that all data from this survey were only used for this academic study to ensure the objectivity and neutrality of the answers. (2) All participants were asked to fill in the restrictive question before completing the full questionnaire, namely, whether the participant had experienced rural tourism in Zhejiang Province within the last three years, to ensure that the participants met the requirements of the survey respondents.

After removing invalid questionnaires with problems such as not meeting the target audience, inconsistent answers (e.g., all select option “5”), and a short answer time (less than 1 s per question), a total of 295 valid questionnaires were collected, with a ratio of the number of measurement dimensions greater than 10:1, which meets the requirement for a stable amount of sample [83]. The sample was considered representative of the average rural tourist because the questionnaire was randomly distributed (for a more detailed discussion of improving sample representativeness, please refer to Section 5.4). The demographics of the participants are detailed in

Table 1. General information of the respondents.

Variables	Frequency	%
1. Gender
Male	106	35.93
Female	189	64.07
2. Age
≤18	10	3.39
19–30	175	59.32
31–45	71	24.07
46–60	37	12.54
≥61	2	0.68
3. Education
High school and below	25	8.47
Vocational education	24	8.14
Undergraduate	146	49.49
Master’s degree or above	100	33.90
4. Monthly income level (CNY)
≤3000	96	32.54
3001–5000	56	18.98
5001–7500	56	18.98
7501–10,000	36	12.20
10,001–20,000	39	13.22
≥20,001	12	4.07
5. Occupation
Students	100	33.90
Government employees and institutions	86	29.15
Corporate employees	58	19.66
Self-employed	11	3.73
Freelancers	19	6.44
Retirees	8	2.71
Other	13	4.41
6. Origin *
Zhejiang Province	207	70.17
East China	25	8.47
South China	23	7.80
Western China	11	3.73
North China	15	5.08
Central China	8	2.71
Northeast China	6	2.03
7. Number of times involved in rural tourism (time)
1	41	13.90
2–3	141	47.80
4–5	27	9.15
>5	86	29.15
8. Duration of stay for a single visit (days)
<1	118	40.00
1–3	156	52.88
>3	21	7.12
9. Sources of information
Recommendations from friends and family	190	64.41
Internet Search	193	65.42
Media Recommendations	146	49.49
Celebrity Effect	36	12.20
Other Channels **	65	22.03

* East China includes Shanghai, Jiangsu, Anhui, Fujian, Jiangxi, and Shandong; South China includes Guangdong, Guangxi Zhuang Autonomous Region, and Hainan; West China includes Xinjiang, Qinghai, Gansu, Ningxia, Shaanxi, Tibet, Sichuan, Chongqing, Yunnan, and Guizhou; North China includes Beijing, Tianjin, Hebei, Shanxi, and Inner Mongolia; Central China includes Henan, Hubei, and Hunan); and Northeast China (including Jilin, Liaoning, and Heilongjiang. ** e.g., recommended by tourism agencies, rural tourism-related organizations.

. Among the respondents, 64.07% were females, and 83.39% held a Bachelor’s degree or higher. The age group with the largest share (59.32%) was 19 to 30 years old. It has been indicated that young people show a greater interest in rural tourism. Meanwhile, the age group between 31 and 45 accounted for 24.07%, indicating that middle-aged individuals also have a certain demand for rural tourism. 12.54% of the respondents were aged between 46 and 60, suggesting that the elderly demographic could also be a potential market for rural tourism. In terms of per capita monthly household income, 50.16% of tourists earned between CNY 3000 and 10,000, while 32.54% said they earned less than CNY 3000. This indicated that the rural tourism market attracts a diverse range of tourists, including those with varying income levels. People who are employed full-time were an important source of rural tourists, accounting for 48.81%. The source of tourists was relatively comprehensive in terms of coverage, with tourists from all regions within mainland China (the People’s Republic of China excluding Hong Kong and Macao). Among them, 70.17% of the tourists came from within Zhejiang Province, 8.47% from East China, and 7.80% from South China. The other tourist sources were evenly distributed in West China, North China, Central China, and Northeast China. About half of the tourists had two to three rural tourism experiences, and more than half of them stayed for one to three days on a single trip. This indicated that the respondents had a certain amount of tourism experience. Recommendations from friends and family, internet searches, and media recommendations were the main sources of information for tourists.

3.3. Data Analysis

In this study, structural equation modeling (SEM) was analyzed using the partial least squares (PLS) technique. PLS-SEM has lower data requirements than general SEM structural analysis methods [84]. PLS-SEM provides better interpretation and prediction capabilities [84]. There were two main reasons for choosing PLS-SEM in this study. On the one hand, the distribution of rural tourists in Zhejiang Province was uneven, and using PLS-SEM can efficiently process the survey data. On the other hand, this study aimed to explore the role of cultural value in perceived value, which was more meaningful in conducting the exploratory search than doing the validation of hypotheses. PLS-SEM can also solve the complex variable relationships in the model. This was more suitable for the application of prediction. In addition, to guarantee the stability of the analysis, the data were analyzed using the bootstrapping checking procedure with a set number of 5000 iterations [85].

4. Data Analysis Results

4.1. Multicollinearity and Common Method Variance

Multicollinearity is the high correlation between constructs, which leads to distortion in model estimation. To avoid biasing the study’s results, this study adopted the variance inflation factor (VIF) to test the multicollinearity problem [84]. Analysis using Smart PLS 4.0 software revealed that the internal model VIF values were 1.635–2.440, which were all less than the threshold value of 3.3, indicating that the data in this study did not suffer from the problem of multicollinearity [86].

Common method variance refers to the bias of the research results due to the same testing environment, data source, question context, and other issues. This study adopted Harman’s single-factor test to avoid the bias of data homogeneity in the study results [87]. The results of the study showed that the maximum factorial variance was 48.980%, which is less than the threshold of 50%, so there is no serious common method bias in this study [88].

4.2. CFA Results, Validity, and Reliability of Measurements

Prior to factor analysis, Kaiser–Meyer–Olkin (KMO) and Bartlett’s test of sphericity (BTS) were used to verify whether the data had a basis for factor analysis. The KMO value of the data of this study was 0.944, and Bartlett’s test of sphericity significance statistic value was 0.000 (<0.001), indicating that the data of this survey are suitable for factor analysis [89].

In this study, Smart PLS 4.0 software was used to measure the reliability and validity of the data structure, as shown in

Table 2. Measurement of key variables.

	Scales and Items	Standardized Factor Loadings	Cronbach’s Alpha	Composite Reliability (CR)	Average Variance Extracted (AVE)
	Emotional value (EV)		0.893	0.926	0.759
EV1	I love the countryside as my travel destination.	0.789
EV2	This trip makes me feel happy and pleasant.	0.913
EV3	I feel relaxed and comfortable on this trip.	0.899
EV4	This tour is a happy experience for me.	0.878
	Social value (SV)		0.789	0.877	0.704
SV1	The choice of rural tourism is socially acceptable.	0.797
SV2	Choosing rural tourism can increase the number of topics I have in common with others.	0.877
SV3	Choosing rural tourism can make me leave a good impression on others (e.g., helping farmers, loving nature, etc.).	0.841
	Value for Money (VFM)		0.860	0.905	0.704
VFM1	The tour was affordable.	0.797
VFM2	The money spent on this tour is worth it.	0.849
VFM3	The time and effort spent on this tour was worth it.	0.851
VFM4	For the same budget, I think this tour is a good choice.	0.857
	Cultural Value (CV)		0.883	0.915	0.683
CV1	I think experiencing the local culture can make this trip more meaningful for me.	0.829
CV2	It is meaningful to visit the historical sites on this trip.	0.814
CV3	It is meaningful to experience the countryside on this trip.	0.865
CV4	It is meaningful to visit rural architecture on this trip.	0.850
CV5	It is meaningful to participate in rural festivals/temple fairs and other special folk activities on this trip.	0.770
	Place Identity (PI)		0.881	0.918	0.737
PI1	I like to do rural tourism in Zhejiang.	0.847
PI2	Rural tourism activities in Zhejiang have special significance for me.	0.887
PI3	I am fascinated by the countryside tour in Zhejiang.	0.886
PI4	Compared with other places, I prefer to choose Zhejiang as a rural tourism destination.	0.812
	Behavioral Intention (BI)		0.931	0.951	0.830
BI1	I would choose to do rural tourism activities in Zhejiang again.	0.894
BI2	I would recommend people around me to do rural tourism activities.	0.911
BI3	I would like to share my rural tourism experience with others.	0.915
BI4	I would recommend Zhejiang as a rural tourism destination to others.	0.923

. The reliability analysis was represented by the factor loadings of the latent variable items, Cronbach’s α of the variables, and composite reliability (CR) by testing the internal consistency of the items. The average variance extracted (AVE) was used to test the convergent validity of the data. The results showed that the standardized factor loadings of the items were in the range of 0.770–0.923, Cronbach’s α was in the range of 0.789–0.931, and CR was in the range of 0.877–0.951, all of which were greater than 0.7, indicating that the convergent validity of this study was good and that there was a good internal consistency within the latent variables [84]. The values of AVE were in the range of 0.683–0.830, which were greater than the recommended value of 0.5, indicating that the latent variables of this study have good reliability [84].

Discriminant validity measures the variability of the concepts measured by the question items under different variables—that is, whether there are differences in the dimensional connotations of the measures between different latent variables [90]. Discriminant validity was evaluated using the Fornell–Lacker criterion, which states that discriminant validity exists when the square root of the AVE is greater than the correlation coefficient between the variable and other variables [91]. The discriminant results are shown in

Table 3. Fornell–Lacker criterion.

	EV	SV	VFM	CV	PI	BI
EV	0.871
SV	0.532	0.839
VFM	0.538	0.619	0.839
CV	0.532	0.643	0.548	0.826
PI	0.539	0.612	0.564	0.611	0.858
BI	0.580	0.660	0.626	0.677	0.683	0.911

Note: Bold numbers are utilized to mark the square root of the AVE for every construct, whereas the interconstruct correlations are presented diagonally.

, and since the correlation coefficients between all variables are less than the square root of the AVE of the corresponding variable, the discriminant validity is considered good.

Since the calculation method of PLS-SEM overestimates the standardized factor loadings, resulting in high AVE values, and underestimates the correlations between variables, this study added the heterotrait–monotrait ratio (HTMT) method as a basis for discriminant validity [92]. The discriminant results are shown in

Table 4. Heterotrait–monotrait ratio.

	EV	SV	VFM	CV	PI	BI
EV	-
SV	0.633	-
VFM	0.607	0.742	-
CV	0.598	0.768	0.623	-
PI	0.603	0.731	0.638	0.685	-
BI	0.636	0.770	0.692	0.744	0.752	-

, and all values were less than 0.85, indicating good discriminant validity between variables, which is consistent with the results of the Fornell–Lacker criterion.

4.3. Hypothesis Testing

The fit of the structural model must be evaluated before hypothesis testing. The results of the evaluation showed that the SRMR = 0.054 (<0.08) [93] and NFI = 0.862 (>0.80) [94], which proved that the model has a good fit.

4.3.1. Direct Effects Test

After verifying the reliability, validity, and model fit of the study, this study tested the path hypothesis in the structural model, and the results are shown in

Table 5. Path coefficients for each variable.

	Path	Sample Mean (M)	Original Sample (O)	Standard Deviation (STDEV)	T Statistics (|O/STDEV|)	p Values	Results
H1a	EV → PI	0.175	0.178	0.066	2.664	**	Supported
H1b	SV → PI	0.238	0.236	0.072	3.301	**	Supported
H1c	VFM → PI	0.175	0.176	0.072	2.438	*	Supported
H1d	CV → PI	0.269	0.269	0.078	3.445	**	Supported
H2a	EV → BI	0.126	0.129	0.062	2.023	*	Supported
H2b	SV → BI	0.165	0.163	0.068	2.445	*	Supported
H2c	VFM → BI	0.170	0.169	0.057	2.987	**	Supported
H2d	CV → BI	0.247	0.249	0.070	3.513	***	Supported
H3	PI → BI	0.268	0.265	0.061	4.404	***	Supported

Note: * p < 0.05, ** p < 0.01 and *** p < 0.001.

. Emotional value (β = 0.178, p < 0.01), social value (β = 0.236, p < 0.01), value for money (β = 0.176, p < 0.05), and cultural value (β = 0.269, p < 0.01) all had a significant positive effect on place identity, supporting H1a–H1d. Emotional value (β = 0.129, p < 0.05), social value (β = 0.163, p < 0.05), value for money (β = 0.169, p < 0.01), and cultural value (β = 0.249, p < 0.001) all had significant positive effects on behavioral intention, and H2a–H2d were supported. There was a significant positive influence effect of place identity on behavioral intention (β = 0.265, p < 0.001), and H3 was supported. In summary, hypotheses H1a–H1d, H2a–H2d, and H3 were supported.

4.3.2. Mediated Effects Test

Based on the path analysis, this study continued to test the mediating effect. We tested the impact of tourists’ perceived value on behavioral intention through place identity, and the direct effects were combined to determine the mediating role of place identity. The results of the analysis are shown in

Table 6. Mediating effect testing.

	Path	Sample Mean (M)	Original Sample (O)	Standard Deviation (STDEV)	T Statistics (|O/STDEV|)	p Values	Results
H4a	EV→ PI → BI	0.047	0.047	0.021	2.202	*	Supported
H4b	SV → PI → BI	0.062	0.064	0.024	2.702	**	Supported
H4c	VFM → PI → BI	0.047	0.047	0.023	2.084	*	Supported
H4d	CV → PI → BI	0.071	0.072	0.026	2.718	**	Supported

Note: * p < 0.05, and ** p < 0.01.

. According to the test results, it can be seen that emotional value (β = 0.047, p < 0.05), social value (β = 0.062, p < 0.01), value for money (β = 0.047, p < 0.05), and cultural value (β = 0.071, p < 0.01) had a significant indirect effect on behavioral intention, and H1a–H1d were supported. The results suggested that place identity plays an important role, partially mediating between tourists’ perceived value and behavioral intention.

5. Discussion and Conclusions

5.1. Discussion

First, H1a–H1d confirmed that emotional value, social value, value for money, and cultural value all positively influenced place identity, which was consistent with the results of previous research on the relationship between perceived value and place identity [44]. As seen in the correlation coefficient, social value and cultural value had a higher degree of influence on place identity. It was confirmed that socialization is one of the main motives of rural tourists [10], and socialization and nostalgia were the key factors influencing the subjective well-being of Chinese rural tourists [95]. In typical rural tourism, interpersonal interactions during socialization can fully satisfy tourists’ needs for nostalgic experiences and social relationships [96]. Therefore, China’s rural tourism can satisfy the social value of the attributes to attract many tourists, which was in line with the viewpoint of this study. In the process of China’s urbanization, many rural people migrated to the cities, and therefore, rural areas also bore a lot of tourists’ emotional needs [96]. The current study argued that rural tourism can enhance tourists’ social identity (increase their perceived level of social value), promoting their place identity with rural areas. Similarly, in different cultural contexts, tourists experienced different environments and human and interactive elements, and culture was a key factor in distinguishing different rural tourism destinations [97]. This study found that the cultural value of the perceived value dimension has the greatest impact on place identity, indicating that Chinese rural tourists now pay more attention to culture when choosing rural destinations. It also showed that the Zhejiang provincial government achieved initial success in the excavation of rural culture and that the creation of a congenial atmosphere and the development of cultural heritage can promote tourists’ positive emotions toward tourist destinations, which in turn leads to the emergence of place identity among tourists.

Second, H2a–H2d confirmed that emotional value, social value, value for money, and cultural value all positively influenced tourists’ behavioral intention, which was consistent with the results of previous research on the relationship between perceived value and behavioral intention [71]. As seen in the correlation coefficient, emotional value, social value, and value for money had approximately the same degree of influence on behavioral intention, and cultural value had the highest degree of influence on tourists’ behavioral intention. Previous studies have shown that culture is an important and indispensable factor for rural tourism to flourish and that dispensing culture in tourism development hinders the sustainable development of local tourism [98]. Culture has a great influence on tourists’ tourism experience; that is, regional culture has a certain influence on tourists’ experience, which in turn affects their future behavioral choices [99,100]. About 70% of cultural resources are identified in China’s rural areas, making them highly valuable for cultural tourism development. It is important to note the potential for development in these areas while also acknowledging their cultural significance. In recent years, China has paid more attention to the integration of culture and tourism, especially in the field of rural tourism. A series of relevant documents has been issued to explore rural culture and promote tourism development and rural prosperity. This study found that cultural value is the most influential factor in tourists’ behavioral intention. This suggested that Chinese rural tourists increasingly value cultural experience in tourism and that improving the cultural atmosphere and developing regional culture in rural tourism destinations is conducive to promoting local tourists’ intention to revisit, share, and recommend the destination, leading to tourist growth and sustainable development of the tourism destination.

Third, H3 and H4a–H4d confirmed that place identity positively influenced tourists’ behavioral intention and its mediating role between tourists’ perceived value and behavioral intention, which is consistent with the results of previous research [74,75]. Additionally, this study found that tourists’ positive emotions are important predictors of their positive behavior. When tourists develop a sense of identification with a place, they are more likely to revisit, share, and recommend it. This conclusion was also found to be true for rural tourists in Zhejiang Province. Place identity partially mediated the relationship between emotional value, social value, value for money, cultural value, and behavioral intention. Moreover, this study demonstrated that the perceived value of a rural tourist destination has a direct impact on tourists’ behavioral intentions, including their intention to revisit, share, and recommend the place by influencing their emotions toward it. This study confirmed that place identity plays a crucial role as a mediating variable in the relationship between tourists’ perceived value and their behavioral intention, and the findings applied to rural tourists in Zhejiang Province.

5.2. Theoretical Contributions

Rural tourism is widely acknowledged as a crucial strategy for promoting rural development in China [101], and rural tourists are believed to play a vital role in promoting rural tourism. Therefore, investigating the behavioral intentions of rural tourists is meaningful and beneficial to the development of the China’s countryside. The main theoretical contribution of the study is the development of the research model to investigate China’s rural tourism development.

This study developed a structural research model based on Attitude Theory and used the PLS method to test the proposed model. Specifically, this study examined the relationship among perceived value, place identity, and behavioral intention of rural tourists in Zhejiang Province. Three main conclusions were drawn. The first was to verify the applicability of attitude theory in rural tourism research. The empirical test demonstrated the hierarchical relationship between the three dimensions of tourists’ perceived value, place identity, and behavioral intention, and verified the effectiveness of attitude theory in predicting tourists’ behavioral intention. It offered a fresh perspective on the correlation between tourists’ perceived value, place identity, and behavioral intention, enriched the research methodology of tourism and behavioral science and provided a deeper understanding of the decision-making process of tourists. Second, this study incorporated cultural value as a measurement dimension of rural tourists’ perceived value, confirming its significance as an antecedent variable of place identity. It is important to note that tourists’ perceived value can directly impact their behavioral intention, as well as their place identity. Data analysis revealed that cultural value had the greatest influence on tourists’ place identity and behavioral intention. Additionally, it was found that the cultural awareness of rural tourists in Zhejiang Province has improved. These findings provided new insights for research on integrating rural culture and tourism in Zhejiang Province. Finally, this study combined the concepts of structural equation modeling, attitude theory, and place identity to conduct an interdisciplinary study. The interdisciplinary approach synthesized knowledge and theories from different disciplines, promoted cross-disciplinary research in tourism, and provided a more comprehensive perspective for tourism research.

5.3. Managerial Implications

This study aims to promote the development of rural tourism in Zhejiang by raising awareness among relevant departments and enterprises about the cultural value of tourist destinations and the importance of tourists’ sense of belonging and identity. The ultimate goal is to provide a benchmark and model for improvement and upgrading China’s rural tourism industry in conjunction with the research results.

On the one hand, the importance of cultural value should be properly recognized. Research has shown that cultural value is the dimension of perceived value that has the greatest influence on place identity and behavioral intention, and culture is also a key component of tourism development in China at this stage. Correctly recognizing the importance of cultural value for tourists can help protect and inherit rural culture and promote the sustainable development of rural tourism. First of all, we should actively carry out the cultural development of rural tourism sites, including history, folklore, art, and architecture. Cultural elements with uniqueness and attractiveness should be identified to improve the competitive differences between rural tourism destinations. Second, the existing tourism development should pay attention to the protection and inheritance of rural culture, avoid excessive commercialization, and maintain the originality and authenticity of rural culture. Finally, it is necessary to innovate cultural tourism products based on inheritance, combining the characteristics of rural culture and innovating rural tourism products, such as cultural experience, folk performance, and handicraft production. In this way, we can enrich the atmosphere of cultural experience, attract more tourists to come and experience rural destinations, and promote the sustainable development of rural tourism.

On the other hand, the importance of tourists’ sense of belonging and identity should be properly recognized. This study has shown that place identity has an obvious influence on the behavioral intention of tourists in rural tourism destinations, and place identity is considered to be a kind of positive emotional feedback to the tourism destination, which can enhance the satisfaction and loyalty of tourists. First of all, tourism destination-related parties should strengthen interaction with tourists. Through interaction and communication with tourists, such parties can understand tourists’ needs and feedback, introduce tourists to the process of tourism destination improvement through the concept of value co-creation, continuously improve tourism products and services, and enhance tourists’ service experience. Second, the construction of a humanized tourism environment should be strengthened. People involved in such a process should focus on details and humanized design in tourism facilities, services, and other aspects to create a warm, friendly tourism environment to meet the emotional and social needs of tourists and ensure they feel the warmth of home. Finally, the different consumption needs of different consumer groups should be clarified. Through market research and analysis, the needs and preferences of target tourist groups should be clarified, and different tourism products and services should be designed for different tourist groups to improve the satisfaction and loyalty of customer groups in different market segments.

To summarize, the relevant government departments should actively formulate a series of policies and regulations to support the protection and development of rural tourism culture, and continuously monitor and evaluate the effectiveness of the policies to ensure the implementation of the policy provisions. Relevant localities and enterprises should strengthen the concept of integrated development of rural tourism and culture, and strive to improve the experience and satisfaction of tourists. It is hoped that these measures will promote the healthy and sustainable development of rural tourism.

5.4. Limitations and Prospects

Future studies may consider addressing some of this study’s limitations to enhance the generalization of the study results. First, the sample was collected through an online survey, which may introduce bias towards certain groups of tourists. This may limit the representativeness of the sample for all rural tourists. Future research can consider combining online and offline surveys to achieve a more comprehensive sample. Secondly, the study’s sample size was sufficient for PLS-SEM testing, but overall it was still limited. To reduce research errors, subsequent studies may consider enlarging the number of surveyed tourists and incorporate other research methods to further improve the credibility and reliability of the study. Thirdly, though Zhejiang is not large in terms of land size, there may still be some segments of rural tourism. Thus, future research may consider the segmentation issue and further enhance the usability of study findings. Fourthly, the study’s findings may not be generalizable as only tourists from mainland China were selected. To improve the application of the findings in different cultural contexts, subsequent studies should include tourists from different regions. In addition, based on the PLS-SEM research methodology, this study chose linear regression to test the relationships between the regression variables at each level rather than a multiple regression, so there is a risk of omitted variable bias, which may lead to biased estimates in the simple regression. Future studies could consider constructing composite indicators and regressing the relationships between variables at each level through multiple regressions to minimize the impact of omitted variable bias. It is also hoped that future authors will extend the model by adopting other theories [102,103] or constructs [104,105].