A Study on the Impact of Chinese Domestic Tourists’ Participation on Their Post-Travel Behaviors in Traditional Chinese Villages

Abstract

According to attitude–behavior theory, the emotions generated by tourists’ travel experiences can influence their subsequent behavioral intentions. This quantitative study analyzed 398 survey questionnaires using a structural equation model to explore the multiple chain mediating effects between tourists’ participation, perceived value, place attachment, and loyalty. The results show that the innovation and interaction dimensions of tourist participation significantly influence the generation of perceived value and place attachment, which is far greater than that of the information exchange dimension. Perceived value significantly affects the formation of place attachment, and the self-enhancement dimension of perceived value significantly influences tourists’ recommendations. Compared to ordinary perceived value, the emotional connection between tourists and the destination is more profound and important, and place attachment plays a crucial role in the formation of tourists’ loyalty. This study confirms the relevance of the attitude–behavior theory in the context of traditional village tourism and extends the theory’s application to encompass the emotional connection between individuals and places. It thoroughly investigates the mechanisms through which tourists’ participation, perceived value, and place attachment impact customer loyalty. The findings of this research hold significant importance in comprehending tourists’ behavioral intention and decision-making processes within destination settings, providing a theoretical basis for exploring and expanding diverse value activities in traditional village tourism.

1. Introduction

As globalization and technological advancements continue to shape the world, the tourism industry is also evolving and changing rapidly. Standardization of tourism services and homogenization of destinations have forced some tourist destinations to revive traditional cultures and innovate to maintain their unique characteristics and resist the trend of homogenization [1,2]. Furthermore, the needs and behaviors of young tourists are also changing, with a preference for flexible and free-style travel experiences that emphasize unique, shareable experiences and impressions through social media [3,4]. Thus, the tourism industry must continually innovate and adapt to provide diverse and personalized tourism products and services that meet the needs and expectations of different tourists.

Traditional Chinese villages are villages selected by six departments, including the Ministry of Housing and Urban-Rural Development, the Ministry of Culture, and the Ministry of Finance, based on local recommendations since 1992. In 2023, there are a total of 8155 traditional Chinese villages in China. These villages have a long history, well-preserved traditional architectural styles, traditional location and layout features, and actively inherit intangible cultural heritage. Traditional Chinese villages carry rich local culture, historical memory, architectural aesthetics, and the trajectory of social development [5]. They embody the spirit of the Chinese nation and serve as a link to maintain cultural identity among the descendants of the Chinese people. They have gained favor among both domestic and international tourists. In recent years, the development of ancient villages has focused on using the beautiful natural and cultural landscapes of rural areas as tourist attractions. However, this approach often overlooks the need to effectively preserve and pass on characteristic farming and handicraft skills, folk culture, and other aspects [6]; national tourism demand has shifted from focusing on beautiful scenery to experiences of a good life and sharing. Therefore, the tourist experience has become a critical indicator for measuring the attractiveness of tourist destinations. Hence, there is a pressing need to explore ways to enhance the diverse value attractiveness of historical and cultural tourist attractions and traditional villages, improve the tourist experience, and increase the willingness of tourists to revisit.

A tourism experience is a subjective experience that includes cognitive perception, sensory perception, and emotional experience [7,8]. The existing literature suggests that in generating satisfaction in historical and cultural tourism experiences, the emotional bond between people and places is equally important as tourists’ cognition and emotions in meeting tourists’ spiritual needs [9] and enhancing their heritage and cultural destination experience [10,11]. When tourists participate in activities, their energy is immersed in something or some activity, and this immersive state can bring them a pleasant and happy experience [12]. Further, tourists’ curiosity, interest, and questions about the destination may prompt them to participate more in activities, and high-level interaction and participation can enhance their tourism experience [13]. Given the importance of tourist participation in the tourism experience, this study employs attitude–behavior theory to investigate how tourist participation influences behavioral intention through place attachment and perceived value, providing a theoretical foundation for the multi-dimensional value activities of ancient villages.

2. Literature Review

2.1. Attitude–Behavior Theory

In psychology, attitude is a stable psychological system composed of an individual’s cognitive, affective, and behavioral tendencies external stimuli. The structure of attitudes involves three dimensions: cognition, affect, and behavioral intention. Behavioral intention refers to the outwardly expressed behavior of an individual toward an attitude object based on their cognitive and affective tendencies toward that object [14]. Therefore, the perceived value and local emotion of Chinese tourists after their tourism experience in traditional Chinese villages correspond to the cognition and emotion of attitude behavior theory, which in turn influence their subsequent behavioral intentions. The attitude–behavior relationship in social psychology describes how cognition and affect influence behavior through behavioral intention [15,16,17]. This relationship mainly includes the theory of reasoned action (TRA), the theory of planned behavior (TPB), and the theory of self-regulation (TSR).

The theory of reasoned action (TRA) proposed by Ajzen and Fishbein [18] is the earliest version of the attitude–behavior relationship model. According to the TRA, attitudes are a person’s positive or negative evaluation of a behavior, while subjective norms refer to the individual’s perception of the social pressures from others to engage in the behavior. The theory posits that an individual’s intention to perform a behavior is a function of their attitudes and subjective norms. In other words, an individual’s behavior is likely to reflect their intention to engage in the behavior.

This study hypothesizes that the perceived value and place attachment of Chinese tourists after experiencing traditional village tourism correspond to the cognition and emotion of attitude–behavior theory, affecting their subsequent behavior. Subjective norms refer to normative beliefs and an individual’s tendency to comply with them, reflecting the social pressures an individual perceives to perform or not perform a specific behavior and indicating the influence of social factors on an individual’s behavior and decision-making. There may not be significant social pressure for tourists to perform or not perform tourism behavior. Therefore, this study primarily examines tourists’ behavioral intentions from the perspectives of cognition and emotion.

Recent studies suggest that customer participation and perceived value are important factors that influence customer loyalty in business activities [19]. Tourism destinations attract visitors as resources, so people tend to develop an emotional attachment to these places. Thus, this article explores the effects of customer participation, perceived value, and place attachment on customer loyalty in tourism.

2.2. Place Attachment, Perceived Value, and Loyalty

Place attachment is an emotional connection between a person and a specific location. From a constituent elements perspective, place attachment includes three dimensions: people, psychological processes, and places [20]. People are the subject of place attachment, and their experiences in a place create the meaning of that place [21]. Significant psychological activities in a particular location lead to emotional and cognitive changes. Therefore, the object of place attachment is a location with spatial, social, or physical characteristics. Place attachment is an emotional identification with a particular geographical space and identity that is derived from the specificity of the place and individual experiences [22].

The interaction between people, landscapes, objects, and environments alone cannot form a place attachment [23]. Instead, emotional bonds are formed through active participation among people, activities, and places [24]. Tourists often recall a place through past experiences and potential connections to local events and activities, contributing to a social connection. Such social connections strengthen the link and emotional attachment between tourists and a place, emphasizing the importance of activity participation in forming place attachment [25].

When a place’s material and social conditions satisfy people’s needs and preferences, it creates a sense of dependence [26]. Thus, place dependence encompasses the functional value of local resources and facilities. Tourists’ place dependence gradually evolves into preferences, individual values, and behavioral identification, culminating in place identity [27]. This implies that tourists’ place attachment involves place dependence, place identity, and social connections.

Existing research has found a strong positive correlation between tourists’ place attachment and loyalty [28]. The stronger the emotional connection tourists have with a destination, the more likely they are to revisit and recommend it to others.

Perceived value refers to the subjective evaluation of product attributes, functions, and performance in relation to the customer’s expectations in a specific context [29]. Therefore, it is a subjective, contextual, and relative evaluation that only the customer can perceive. It is a trade-off between what is gained and what is lost, perceived in comparison to expectations. From a consumer perspective, perceived value can be defined by dimensions such as functional, emotional, social, and cognitive values [29,30].

Research suggests that functional value is the most significant dimension. Considering that heritage tourism is often a cognitive experience [31]. Epistemic value is also an important value indicator. Social value motivates tourism by enhancing interpersonal connections and expanding personal social networks. Moreover, it increases individual social capital, especially in heritage tourism activities with strong cognitive elements, where social value is prominent. Emotion is the most influential factor in behavioral tendencies in the theory of planned behavior. Therefore, we believe that in traditional village tourism, functional, emotional, social, and cognitive values are essential dimensions that comprise tourists’ value perception.

The higher the perceived value of the functions or services of a tourist destination, the deeper the tourists’ love and dependence on the place will be [32,33]. Their attachment to the region will also correspondingly increase, making them more likely to (a) show loyalty to the place or its businesses, (b) recommend it to others, or (c) revisit it [34,35].

In summary, this study proposes the following hypotheses:

H₁: 

Place attachment has a positive impact on tourist loyalty.

H₂: 

Perceived value has a positive impact on place attachment.

H₃: 

Perceived value has a positive impact on tourist loyalty.

2.3. Participation, Perceived Value, and Place Attachment

Tourist participation refers to the degree of effort and emotion that customers invest in a consumption experience, reflecting their involvement in a particular activity, related products, or experiences. Scholars have described and defined dimensions of customer participation from different perspectives in various studies. For instance, Silpakit and Fisk [36] believed that customer participation involves intellectual, physical, and emotional effort and involvement. Snyder and Fromkin [37] proposed four forms of customer participation: pre-purchase preparation, relationship establishment, information exchange, and behavioral intervention. Likewise, Ennew and Binks [38] divided customer participation into three dimensions: information exchange, responsible behavior, and interpersonal interaction. These perspectives have become the primary basis for describing and measuring customer participation in subsequent research. This study identified three dimensions of participation: information exchange, interpersonal interaction, and innovative behavior, based on previous research.

Preparing for a trip by gathering information is an integral part of tourist participation and one of the ways tourists invest their energy. When tourists have sufficient knowledge about their destination before the trip, including the local attractions, cultural features, and available activities, it can increase their satisfaction with the destination. Additionally, obtaining information about the relevant products and services at the destination can enhance tourists’ understanding and awareness of the details and unique features [39], thereby increasing their liking for the products.

Interpersonal interaction is a critical factor influencing tourists’ participation and perceived value in tourism activities. Existing research has shown that when tourists participate in tourism activities, interaction with peers, locals, and other tourists can enhance their perceived value of the tourism experience. This interaction can bring about better emotional experiences, increase knowledge and information exchange, and create more profound cultural and social experiences [13]. Additionally, tourists’ perceived value of tourism products relates to the frequency and quality of their interactions with local residents and other tourists [40]. Positive interactions with locals and tourists during the activity can enhance tourists’ participation and increase their perceived value of the experiences.

The mode of participation is a crucial factor affecting customer participation’s effectiveness. If the mode of participation does not meet the customers’ expectations, it may not significantly impact them. Thus, allowing customers to participate in their preferred ways can somewhat meet their expectations. According to the uniqueness theory proposed by [41], everyone has a need for conformity to assimilate themselves into the external world and a need for uniqueness to distinguish themselves from it. The need for uniqueness can prompt customers to purchase unique products or communicate to meet their unique needs. Some customers satisfy their need for uniqueness by engaging in their own participatory behavior. From the perspective of motivation, active participation is more meaningful than passive participation, and the key is for customers to be innovative in their ideas and behaviors. Under the Chinese government’s impetus, the Chinese people’s attitude and willingness toward innovation are constantly being strengthened [42]. Therefore, innovative ideas, practices, or new works of tourists during the tourism process may also become their preferences over time, and these can influence the effectiveness of their participation during the activity process.

Compared to low-participation cultural tourists, high-participation tourists perceive more personal relevance from their experiences [43]. Tourists’ particular interest focus (motivation) and a certain degree of continued participation also stimulate emotional attachment [44]. Many scholars argue that individual participation is a prerequisite for place.

In summary, tourists’ activity participation affects perceived value and the degree of place attachment, mediating their impact on destination loyalty. Therefore, this study proposes the following hypotheses:

H₄: 

Tourist participation positively affects perceived value.

H₅: 

Tourist participation positively affects place attachment.

3. Research Design

This study utilized a questionnaire survey to gather data on tourists’ participation in activities, perceived value, place identity, and loyalty in traditional villages. The collected data was analyzed using AMOS 24.0 structural equation modeling. The relationship between tourist participation, perceived value, place attachment, and tourist loyalty in traditional villages was examined using multiple stepwise regression analysis.

3.1. Scale Variables and Measurement Items

The questionnaire contains three main sections. The first section reviews the situational and travel behaviors, including specific activities in traditional villages, tourism motivations, and related questions. The second section mainly utilizes Likert scales ranging from “not true at all” (1) to “very true” (5) to measure tourists’ participation, perceived value, sense of place attachment, loyalty, and other variables. The third section includes basic demographic information questions about the surveyed tourists.

The tourist participation scale in this study includes aspects such as information exchange, interpersonal communication, communication, and innovative behavior. The scale is primarily based on relevant scales developed by [38,45] and includes 13 items adapted to this study. Perceived value encompasses functional, emotional, epistemic, and social values. Functional value perception serves as the foundation of place attachment and is, therefore, included in the content of place dependence in the sense of place attachment. The perceived value scale combines research results on perceived value, such as Chen and Tsai [46] and Rintamaki and Kirves [30] It considers contextual analyses of traditional villages Kang, Huang and Xia [47], resulting in 10 measurement items. Place attachment refers to the emotional connection, attachment, and degree of identification tourists have with traditional villages. This study drew inspiration from Williams, Patterson and Watson [48], design of the place attachment scale, which includes five measurement items. Furthermore, this study explores tourists’ recommendation behavior and how they evaluate specific traditional villages to others in different scenarios. The relevant scale includes four measurement items.

3.2. Data Collection [46]

An initial questionnaire was designed based on a literature review and research hypotheses and considering traditional Chinese villages and expert opinions. The questionnaire was evaluated and tested by 20 people, including research team members, university students, tour guides, and tourists, to revise any unclear or esoteric statements and improve the questionnaire’s reliability and content validity. Data were collected using the WeChat platform, and the Wenjuanxing website was used to collect questionnaire data from tourists who had visited traditional villages and participated in specific activities in the past two years. Only one questionnaire was allowed per IP address. In the first phase, a pre-survey was conducted in January 2023, and 66 valid questionnaires were collected. The Cronbach’s α coefficient = 0.937, the KMO = 0.799, and Bartlett’s test Sig. = 0.000 indicate that the questionnaire results passed the tests of reliability and validity.

Next, the questionnaire’s content was further modified, adjusted, and improved based on the specific results of the pre-survey to form the final formal survey questionnaire. The survey was conducted in February 2023 and utilized a combination of convenience sampling and judgmental sampling techniques. Convenience sampling involves selecting participants who are readily available and accessible, while judgmental sampling involves selecting participants based on the researcher’s knowledge and judgment of the population being studied. The key survey cities were Chengdu, Nanning, and Guilin, which are national historical and cultural cities. Local tour guides were entrusted to distribute the questionnaires randomly to their WeChat tourism groups and customer groups, and request that tourists who had visited traditional villages in the past two years fill them out. The research team monitored the Wenjuanxing website and deleted questionnaires completed by individuals who had not participated in specific traditional village tourism activities. During the formal survey, 460 questionnaires were collected after excluding 62 invalid questionnaires completed in less than 120 s; 398 valid questionnaires were obtained, with a rate of 86.5%.

4. Research Results

4.1. Demographic Characteristics of the Sample

Regarding the gender ratio, males accounted for 47.8% of respondents, while females accounted for 52.2%. The sample had a relatively young average age of 27.8 years, which aligns with the overall low level of accessibility to traditional villages, characterized by limited transportation options and high transportation time costs [49]. Taking Yunnan Province as an example, the average travel time to reach traditional villages is 2.38 h, which is higher compared to other types of scenic areas [50]. As a result, the main visitor demographic to these villages consists of young and middle-aged adults. The majority of the sample had education ranging from high school or equivalent to college or equivalent, accounting for 84.6% of the total sample, indicating a generally higher level of education among the respondents. Regarding traditional village tourism, 61.1% of visitors had experienced it twice or less, while 38.9% had experienced it more than two times. The proportion of tourists participating in production-oriented activities was 24.8%, while those participating in service-oriented activities accounted for 39.3%, and those participating in experience-oriented activities accounted for 35.9%. Tourists mainly participated in experience and service-oriented activities. In terms of income, tourists with income below RMB 4000 accounted for 70.4%, while those with income between RMB 4000–6999 accounted for 15.2%, those with income between RMB 7000–9999 accounted for 7.0%, those with income between RMB 10,000–12,999 accounted for 4.8%, and those with income of RMB 13,000 and above accounted for 2.6% (as shown in

Table 1. Demographic profile of sample.

Variable	Category	Sample Size	Percentage
Gender	Male	190	47.80%
	Female	208	52.20%
Age	Mean Age	27.8
Education	Junior or Equivalent	0	0
	High school or Equivalent	38	9.6%
	College or Equivalent	337	84.6%
	Master degree and above	23	5.8%
Travel experience	2 times or less	243	61.1%
	More than 2 times	155	38.9%
Types of activities to participate in	Production-oriented activities	99	24.8%
	Service-oriented activities	156	39.3%
	Experience-oriented activities	143	35.9%.
Income	Less than RMB 4000	280	70.4%
	RMB 4000–6999	61	15.2%
	RMB 7000–9999	28	7.0%
	RMB 10,000–12,999	19	4.8%
	RMB 13,000 and above	10	2.6%

).

4.2. An Exploratory Factor Analysis and a Confirmatory Factor Analysis

The overall Cronbach’s α of the questionnaire was 0.924, and the KMO value was 0.937. Bartlett’s test was significant at p = 0.000, indicating that the questionnaire is suitable for factor analysis with good reliability and validity. Harman’s single-factor test was used for common method bias in the scale. Five factors were extracted without rotation, with the first common factor explaining 48.6% of the variance, less than the critical value of 50% [51]. Therefore, this study does not suffer from significant common method bias.

This study first conducted an exploratory factor analysis (EFA) on the sample data to confirm whether each item could be included in its corresponding construct. Then, different combinations of dimensions in which customers participated were tested using a confirmatory factor analysis (CFA) model to compare the advantages and disadvantages among various dimension divisions, as follows:

In this study, we conducted factor analysis using SPSS 24.0 to explore the underlying factors of the predetermined independent variables: participation, perceived value, and place attachment. Principal component analysis (PCA) was employed to maximize the variance, and orthogonal rotation was performed to extract factors with eigenvalues greater than 1. The criterion for extracting common factors was based on the factor loading of each item greater than 0.5 on a single factor. The analysis resulted in the exclusion of one item (pattachment2) due to not meeting the criterion. Five common factors were extracted, showing differences from the original dimensionality. The dimensions of interpersonal interaction and innovative behavior were merged into a single factor, which we renamed innovation and interaction. To some extent, this illustrates the similarity between the tourism industry and other service sectors, where communication of tourists brings about innovation [52]. The dimensions of epistemic value (vep) and social value (vsocial) were merged into another factor, which we renamed self-enhancement. The cumulative variance explained by the five common factors was 76.87%, which are information exchange (INFOR), innovation and interaction (INNO&INTER), emotional value (V-EM), self-enhancement value (V-SE), and place attachment (PA), respectively, as shown in

Table 2. Exploratory factor analysis result.

Factors	Code	Mean Value	Factor Loadings	Characteristic Value	Percentage of Variance	Cumulative Variance Explained	Cronbach’s α
INNO& INTER	innovation1	3.93	0.705	5.093	19.588	19.588	0.908
	innovation2	3.88	0.746
	innovation3	4.10	0.650
	innovation4	3.80	0.784
	interact1	4.030	0.717
	interact2	4.010	0.648
	interact3	3.910	0.742
INFOR	information1	4.03	0.920	3.708	14.261	52.653	0.952
	information2	3.89	0.899
	information3	4.01	0.900
	information4	3.94	0.876
V-SE	vep1	4.140	0.794	4.889	18.804	38.392	0.944
	vep2	4.200	0.815
	vep3	4.110	0.760
	vep4	4.260	0.748
	vsocial1	4.050	0.622
	vsocial2	4.040	0.553
	vsocial3	4.030	0.578
V-EM	vem1	3.650	0.897	3.184	12.246	64.899	0.940
	vem2	3.220	0.889
	vem 3	3.570	0.925
PA	pttachment1	4.030	0.623	3.113	11.972	76.871	0.892
	pattachment3	3.720	0.622
	pattachment4	3.830	0.691
	pattachment5	3.880	0.709

.

After conducting PCA on the 398 response sets using the maximum likelihood method, we performed confirmatory factor analysis on the five factors obtained. First, we used the original model, including eleven items with two factors for participation, three items with one factor for emotional value, seven items with one factor for self-improvement, and four items with one factor for recommendation intention, as analyzed by AMOS 24.0. However, the model fit index CMIN/DF was 26.24, and the model was probably unidentified. The overall result may be because there were too many measurement items for the variables, resulting in a test that was too long and complex to identify the model. Previous research results have shown that using four to six items to measure a latent variable can obtain relatively accurate and reliable measurement results. We deleted items with factor loads less than 0.7 from factors with more than four measurement items, and the model fit improved, as shown in M1 (

Table 3. Structural model fitting index.

Model	CMIN/DF	GFI	NFI	RFI	IFI	TLI	CFI	RMSEA
M1	3.655	0.792	0.898	0.885	0.924	0.194	0.923	0.082
M2	2.94	0.860	0.915	0.901	0.942	0.933	0.942	0.070

), but it was still not ideal.

We examined factors with more than four measurement items, selected items with high factor loads, and after multiple attempts, found that model M2 had a better fit. The model includes a single factor with four items for information exchange, a single factor with four items for communication and innovation, a single factor with three items for emotional value, a single factor with four items for self-improvement value, a single factor with four items for place attachment, and a single factor with four items for recommendation intention. The fit indices for Model 2 are as follows(as shown in Table 3): CMIN/DF = 2.94, GFI = 0.860, NFI = 0.915, RFI = 0.901, TLI = 0.942, CFI = 0.942, RMSEA = 0.07. Overall, the structural model demonstrates a high degree of explanatory power.

The latent variables in model M2 exhibit Cronbach’s α coefficients ranging from 0.846 to 0.983, all exceeding 0.6, and composite reliabilities (CR) ranging from 0.848 to 0.954, all exceeding 0.7. These results suggest that the data in this study meet the requirements for good reliability and exhibit strong internal consistency. As shown in

Table 4. Analysis results of measurement model.

Latent Variable	Code	Std. Factor Loading	Cronbach’s α	AVE	CR
INFOR	information1	0.935	0.952	0.838	0.954
	information2	0.929
	information3	0.891
	information4	0.905
INNO&INTER	innovation4	0.835	0.859	0.659	0.885
	interact3	0.763
	innovation2	0.838
	innovation1	0.809
V-EM	vem3	0.975	0.94	0.884	0.942
	vem2	0.896
	em1	0.883
V-SE	vep4	0.82	0.927	0.763	0.908
	vep3	0.853
	vep2	0.899
	vep1	0.919
PA	pattachment1	0.796	0.846	0.588	0.848
	pattachment3	0.804
	pattachment4	0.863
	pattachment5	0.572
REC	recommend1	0.966	0.983	0.983	0.934
	recommend2	0.973
	recommend3	0.978
	recommend4	0.949

, the square root of the average variance extracted (AVE) for each latent variable was greater than the correlation coefficient between the latent variables, indicating strong discriminated validity and convergent validity among the five latent variables in this study, and demonstrating the good internal quality of the measurement scale [53].

The results, as shown in Figure 1, indicate that information exchange has a significant direct and positive effect on self-enhancement value (β = 0.117, p < 0.01) and place attachment (β = 0.166, p < 0.001). This demonstrates that the pre-trip information collection and information consultation at the destination have an influence on tourists’ expectations, the destination’s image, and understanding the destination [54,55]. Overall, information exchange has no significant effect on tourists’ perception of emotional value. Merely relying on information collection and consultation is not sufficient to shape tourists’ emotional perception. This finding is inconsistent with the research conducted by Man Lai Cheung, which suggests that social media destination brand communities (SMDBC) play a significant role in shaping tourists’ joy, fondness, and positive surprise emotions [56]. This may be related to the concentration and type of information available.

Innovation and interaction have significant direct and positive effects on self-enhancement value (β = 0.653, p < 0.001), emotional value (β = 0.226, p < 0.001), and place attachment (β = 0.469, p < 0.001). Self-enhancement value has significant direct and positive effects on place attachment (β = 0.279, p < 0.001) and recommendation (β = 0.349, p < 0.001). Communication and innovation activities are processes through which people engage in communication, exchange, sharing, and creation. They provide opportunities for tourists to learn, grow, and develop personally, thus enabling them to gain a sense of self-improvement value. The process of communication and innovation allows individuals to establish positive interpersonal relationships [57], leading to emotional value. Additionally, individuals can better understand and experience the culture, environment, and community of a place, fostering emotional connections and a sense of place attachment [58]. However, the path coefficient of innovation and communication on emotional value has a much smaller impact compared to the path coefficient of personal value enhancement. This may be related to the type of scenic spot. For instance, when Chinese families travel to cultural heritage sites, there is a high demand for learning about cultural and historical knowledge [59]. According to Yu and Liu [60], understanding the history and culture, experiencing local customs, appreciating nature, and admiring the architectural features of local residences are important for Chinese tourists when visiting traditional villages. Emotional needs and motivations are particularly strong among elderly tourists, while self-realization and self-enhancement motivations are stronger among middle-aged and younger tourists [61].

Emotional value has a significant direct and positive effect on place attachment (β = 0.127, p < 0.01). This is consistent with the findings of Oliveira et al., which indicate that emotional states can explain the long-lasting relationship between tourists and a place [62]. Emotional value mediates the effect of place attachment on recommendation intention, while self-enhancement value has a direct and mediated effect on recommendation intention via place attachment. However, perceived value does not have a direct significant effect on tourist revisit intention. Research shows that perceived value can have an important impact on tourists’ recommendation intention. When tourists perceive a high value in tourism products or services, they are more likely to recommend them to others. Not all high-perceived-value tourism products or services can promote tourists’ revisit intention. The single factor of perceived value does not significantly influence tourists’ intention to revisit. Tourists’ intention to revisit is also influenced by factors such as geographical convenience, tourism expenditure, and the desire for novelty-seeking [63].

Place attachment has direct positive effects on recommendation (β = 0.454, p < 0.001) and revisit intention (β = 0.38, p < 0.001).

4.3. Multiple Mediating Effect Test

Mediation analysis was conducted using AMOS 24.0 with the maximum likelihood method used for model fitting. The analysis was performed using the bias-corrected non-parametric percentile Bootstrap method with 2000 repetitions of random sampling conducted under 95% confidence interval conditions. The mediation effect was evaluated using the bias-corrected and percentile test methods. According to the mediation effect judgment criteria proposed by [64], a variable’s value range is considered significant if it does not include 0 in the 95% confidence interval. The structural equation model was used in this study to analyze the mediation effect.

The results of the mediation analysis indicate that (as shown in

Table 5. Multiple mediating effect test.

Parameter	Estimate	BC 95%CI			PC 95%CI
		Lower	Upper	P	Lower	Upper	P
Information exchange—Self-enhancement value—Place attachment—Recommendation	0.017	0.005	0.04	0.002	0.003	0.037	0.006
Information exchange—Self-enhancement value—Place attachment—Revisit intention	0.014	0.004	0.041	0.002	0.002	0.031	0.012
Information exchange—Place attachment—Recommendation.	0.078	0.031	0.16	0.003	0.028	0.147	0.004
Information exchange—Place attachment—Revisit intention	0.063	0.024	0.172	0.002	0.019	0.142	0.005
Innovation and interaction—Self-enhancement value—Place attachment—Recommendation	0.083	0.036	0.157	0.003	0.033	0.151	0.004
Innovation and interaction—Self-enhancement value—Place attachment—Revisit intention	0.069	0.026	0.17	0.002	0.013	0.139	0.008
Innovation and interaction—Place attachment—Recommendation	0.213	0.13	0.3	0.008	0.139	0.313	0.004
Innovation and interaction—Place attachment—Revisit intention	0.178	0.063	0.302	0.005	0.053	0.286	0.008
Innovation and interaction—Emotional value—Place attachment—Recommendation	0.013	0.003	0.038	0.012	0.001	0.034	0.025
Innovation and interaction—Emotional value—Place attachment—Revisit intention	0.011	0.002		0.007		0.03	0.032

) information exchange contributes to the formation of place attachment among tourists, indirectly influencing their recommendations and intention to revisit. Innovation and interaction emerge as the most significant factors influencing tourists’ perception of value, the formation of place attachment, and indirectly impacting their recommendations and intention to revisit. Place attachment plays a significant mediating role in the chain structure of participation–perceived value–place attachment–behavioral intention, further supporting the importance of emotional factors in maintaining long-term relationships between tourists and the destination, particularly in the context of traditional village tourism.

5. Conclusions and Implications

5.1. Conclusions

This article highlights the impact of tourist participation, perceived value, and place attachment on customer loyalty in ancient village tourism. Using a multiple mediation model, with tourist participation as the starting point and perceived value and place attachment as mediators, we explored multiple paths to investigate the dimensions of variables that influence customer loyalty. Our findings suggest that tourist participation significantly impacts perceived value and place attachment, influencing recommendation and revisit intentions. Notably, the information exchange dimension of tourist participation has a weaker impact on customer loyalty than the innovation and communication dimensions. Tourists’ information preparation, innovation, and communication positively influence perceived value and place attachment. However, the impact of information preparation on emotional value is not significant. Innovation and communication have a significant impact on emotional value, but the path coefficient is much smaller compared to the impact of personal value enhancement. Place attachment plays a significant role in generating loyalty among tourists. Information preparation, innovation, and communication significantly affect place attachment and mediate its impact on both tourists’ recommendation intention and revisit intention. Compared to general value perception, the emotional connection between tourists and the destination is more profound and crucial, and place attachment greatly influences tourist loyalty. In this study, place attachment was the only predictor of tourists’ revisit intention.

The study is based on the context of traditional village tourism and explores attitude–behavior theory, validating its applicability in this specific context. The research extends the emotional aspect of attitude–behavior theory to the emotional connection between individuals and places, thereby expanding the theoretical scope of attitude–behavior theory. By examining the relationships among tourist participation, perceived value, place attachment, and customer loyalty in traditional village tourism, the study further reveals the associations between attitudes and behaviors. This research is of significant importance for understanding tourists’ behavioral intentions and decision-making processes in destinations, and it provides a theoretical foundation for exploring and expanding diverse activities in traditional villages.

5.2. Implications

Improving Information Exchange: The research findings indicate that information exchange has a significant positive impact on self-enhancement and place attachment. This suggests that managers should focus on providing comprehensive and accurate information to visitors before their arrival, as well as on-site information consultation and feedback. Ensuring that visitors have access to comprehensive, positive, and relevant information about the destination is crucial in shaping their expectations, cultivating the destination’s image, and enhancing visitors’ understanding and appreciation of the cultural and historical aspects of the attraction. Ultimately, these efforts contribute to enhancing visitors’ overall experience.

Promoting Innovation and Communication: The research findings indicate that innovation and communication have a significant direct positive impact on self-enhancement perception, emotional perception, and place attachment. This underscores the importance of creating opportunities for tourists to engage in innovative and interactive activities. Tourists are no longer satisfied with passively receiving various products and services provided by enterprises but increasingly expect and demand services that meet their own ideas and needs. Customers are gradually willing to participate in the process of providing service products. This calls for enterprises to prioritize customer needs and facilitate communication, sharing, and encourage visitors’ creative behavior. Managers should encourage the promotion of tourists’ learning, personal growth, and the development of interpersonal relationships. Additionally, assisting tourists in understanding and experiencing the local culture, environment, and community strengthens emotional connections and place attachment.

Identifying the differential impact of factors: The research findings highlight the differences in the impact of innovation and communication on various factors. This finding indicates the importance of considering the significance of different factors in policy-making and management. For instance, while emphasizing information exchange, equal attention should be given to innovation and communication to comprehensively enhance tourists’ experiences and emotional value. Additionally, the mediating role of place attachment in the chain structure underscores the importance of emotional factors in maintaining long-term relationships between tourists and destinations. Managers should prioritize fostering emotional connections between tourists and destinations, such as preserving cultural heritage, promoting sustainable practices, and encouraging authentic local experiences.

Providing different environmental support: Tourists’ motivation for self-enhancement can be divided into intrinsic and extrinsic motivations. Extrinsic motivation for seeking knowledge is imposed by external forces rather than arising from the tourists’ autonomous desire, which may lead to more substantial time constraints and more direct objectives. Therefore, it is important to provide different types of environmental support for self-enhancement driven by different motivations. For example, tourists with extrinsic motivation for self-enhancement may prefer to obtain necessary information quickly and intuitively through tangible and functional explanatory media [65], while tourists with intrinsic motivation may prioritize experiential attachments. Scenic areas should emphasize experiential, exploratory learning of traditional knowledge for tourists and gradually integrate smart tourism development with the Internet of Things and project-based learning experiences into traditional villages. Meanwhile, tourism product development aided by high tech should demonstrate diversification, such as informatization, intelligence, hands-on experience, and learning exploration.

In policy formulation, it is important to consider setting diverse objectives that go beyond mere information exchange, and instead foster cooperation and coordination among various stakeholders, including government agencies, destination managers, industry practitioners, and community residents. Policies should encourage the establishment of partnerships and collaborative efforts to promote innovation and interaction, ultimately aiming for sustainable development. Although this study supports the impact of participatory behaviors, perceived value, and place attachment on tourists’ post-visit behavior, it is important to consider other possible factors and variables that may influence tourist behavior, such as destination marketing and symbolic communication. By doing so, it will further facilitate the development of tourism destination management and marketing, and provide more effective strategies and methods to meet the needs and expectations of tourists.

6. Limitations and Future Directions

The questionnaire data in this study were collected online, primarily from middle-aged and young adults. However, elderly tourists are also one of the main tourist groups in Chinese traditional villages. Therefore, in future research, it is important to pay more attention to and conduct further studies on these demographic groups. The depth of the research findings needs to be strengthened. This study’s findings reveal that the factors influencing recommendation intentions differ from those influencing revisit intentions. Besides local attachment, other unidentified factors may influence tourists’ revisit intentions. While this study supports the influence of participation behavior, perceived value, and place attachment on tourists’ post-travel behavior, it is worth considering other potential factors and variables that might influence tourist behavior, including destination image and transmitted communication signals. Therefore, further exploration of the mechanisms underlying the tourist experience in Chinese ancient villages is warranted.