Construction and Evaluation of a Traditional Village Tourism Imagery Element System Based on Xidi Village

Abstract

Tourism imagery is one of the decision variables for tourists’ travel intentions and behavior. Traditional village tourism imagery studies mostly focus on tourist space, landscape imagery, etc. Few overall imagery studies have been conducted. This paper integrates non-structural and structural methods, uses three-level coding based on rooting theory, constructs a traditional village tourism place imagery element system through network text analysis, designs and analyzes questionnaires accordingly, and empirically evaluates the tourism imagery of Xidi village in Anhui Province. The results show that the overall satisfaction of tourists is less than important, indicating that there is a systematic deficiency in the perception of tourism place imagery of Xidi village. The dimensional IPA analysis shows that the three dimensions of natural landscape, social landscape, and physical cuisine are in the improvement area. According to the supplementary IPA factor analysis, factors such as natural phenomena, historical figures, clan history, watershed, accommodation, ticket systems, and guide services need important attention, improvement, and promotion. The results of the emotional analysis are dominated by positive images, but attention needs to be paid to the negative impact of negative images. Based on the above findings, recommendations are proposed to improve the layout of the development, and enhance the service facilities and quality based on these findings.

1. Introduction

Imagery is the psychological term for the individual perceptual result of the brain’s information (Li, 2004 [1]). Hunt (1971 [2]) first introduced imagery into tourism studies, and it is believed that tourist place imagery is the perception or impression of a particular tourist place, which is the sum of people’s impressions, imagination, and beliefs. Tourist place imagery is not only important for the development and construction of tourist places, but is also a decision variable that affects tourists’ willingness to choose tourism and will directly influence their tourism behavior (Schroeder and Sonmez S., 1999 [3]; Embacher and Buttle, 1989 [4]; Echtner and Ritchie [5]; Fakeye and Crompoton, 1991 [6]; Gartner W C., 1986 [7]). Pre-visit images of the destination influence their choice of destination, post-visit images of the destination shape their evaluation of the destination, and the comparison of pre-visit and post-visit images of the destination shapes tourists’ satisfaction with the destination (Beerli and Martin, 2004 [8]; O’Leary and Deegan, 2003 [9]). Therefore, conducting tourist image research is beneficial for the government and operators of rural tourism destinations. It helps them to gain a comprehensive understanding of tourists’ perceptions of the destinations, to identify both strengths and weaknesses in the development process of rural tourism, and to implement targeted improvement and promotion measures to achieve sustainable development of these tourism destinations.

As a microcosm of local historical development, traditional villages attract tourists with their rich natural and humanistic landscapes and have become an important type of tourist destination (Wen et al., 2021 [10]). Most studies on tourism images of traditional villages have focused on residents’ perceptions in the context of tourism development (Lu and Zhang, 2009 [11]; Tang et al., 2008 [12]), and some scholars have studied spatial and landscape images of traditional villages from the perspective of tourists (Wen et al., 2021 [10]; Qian et al., 2022 [13]), but there are few studies on the overall images of traditional village tourism. Only Cao X P. et al. (2020 [14]) have analyzed the image of tourist destinations through tourists’ photos on social networking sites, focusing on the landscape as an attraction. However, it is important to note that the traditional village is a relatively complete space with systematic components. In addition to attractions, it also includes infrastructure and tourist services. Therefore, it is necessary to study the overall picture of all the constituent elements of the traditional village.

Therefore, this paper adopts a research method that combines structural and non-structural methods from the perspective of tourists. Based on the network text data, the rooting theory is used to code layer by layer and construct the image element system of traditional village tourism destinations. The Importance and Satisfaction Analysis (IPA) is conducted through a questionnaire survey of tourists in Xidi village Anhui Province, followed by an overall image analysis of traditional village tourism destinations. The research results are valuable for traditional village destinations in optimizing their products, facilities, and services. They can also accurately develop the intellectual property (IP) of traditional villages and aid in implementing marketing strategies.

2. Literature Review

2.1. Concept and Composition of Tourist Place Imagery

Gunn (1972 [15]) stated that tourist place imagery is represented by the impressions that tourists build up in their minds in the process of tourism, and that it is the result of tourists’ internal emotional evaluation and perception based on their personal subjective awareness. This view focuses on the description of tourists’ images of the place after their visit. Assael (1984 [16]) stated that tourist place imagery is the overall perception of a tourist destination that individuals gather through conscious or unconscious information over time and then form, and this statement focuses on tourist place imagery prior to the tourist visit. In general, the process of constructing tourist place imagery is a subjective understanding process of the objective world by tourists [17]. Although scholars have different views, the core connotation is the same, that is, tourist place imagery is a synthesis of tourists’ cognition, attitude, and emotion towards the tourist destination.

In terms of the composition of tourism place imagery, from the perspective of constituent elements, (Xiong, 1999 [18]) considered rural imagery as the overall atmosphere of the countryside and divided rural imagery into rural landscape imagery and rural activity imagery. Peng (2019 [19]) deconstructed tourism place imagery into landscape imagery, cultural imagery, local imagery, and emotional imagery (Peng and Huang, 2019 [19]), while Bing (2022 [20]), used a landscape perspective to refine tourism place imagery into natural landscapes, cultural landscapes and social landscapes. From the perspective of the tourism imagery formation process, Gunn (1972 [15]) proposed primordial and induced imagery based on whether tourists are influenced by commercialization, and Fakeye and Crompton (1991 [6]) argued that in addition to primordial and induced imagery, there is composite imagery contributed by tourists’ actual tourism experience. From the perspective of psychological perception, Baloglu and Mc Cleary (1999 [21]) argued that destination imagery includes cognitive imagery, emotional imagery, and composite imagery resulting from the interaction of the two, and that imagery formation is influenced by stimulating factors such as tourists’ personality traits and media messages. Gartner (1994 [22]) proposed the “cognitive-emotional-image” structural model, which has been widely used in subsequent studies of tourism place imagery.

2.2. Content and Evaluation Methods of Tourism Place Imagery Research

Tourism imagery characteristics and influencing factors are a focus of related research. Tourism imagery has composite, multiple, relative, and dynamic characteristics. The dynamic aspect is closely related to the marketing strategies of tourism destination imagery [23]. It changes in stages with individual tourism experiences, values, and external messages [24]. Tourism place imagery studies involve countries [25,26,27], cities [28,29,30], villages [14,18,31,32], and other regional scales. Early studies have identified ‘time’ and ‘distance’ as two fundamental factors that affect the dynamics of tourism imagery [7,33]. Subsequent research has expanded to include external environmental factors, such as the type and quantity of information sources, as well as factors relating to individual tourists, including demographic characteristics, tourism motivation, and cultural values [21]. Scholars have analyzed tourism marketing in various destinations based on tourism imagery research [34]. They have also examined the impact of tourism crises on tourism imagery from a destination perspective [27,34,35]. Chinese traditional villages refer to the villages built before the Republic of China. These villages are repositories of rich historical and cultural information, representing the significant heritage left by the Chinese agricultural civilization [36]. Research on the tourism imagery of traditional villages from the perspective of tourists is mainly focused on their satisfaction with sketching in ancient villages [37], as well as the correlation between crowding perception and recreation emotion among tourists visiting ancient villages [38]. In recent years, scholars have begun using User-Generated Content (UGC) data to analyze the tourism imagery of traditional villages [39,40].

There are many achievements in evaluations of tourism destination imagery [41,42] or examinations of its relationship with other variables such as motivation [43,44] to travel, satisfaction [45,46,47], and loyalty [48]. There are two main forms of structured and unstructured methods to evaluate the imagery of tourism places. Structured methods are based on closed-ended questionnaires that reflect different categories of destination imagery through different dimensions of attribute indicators, but this method has limitations for different types of destinations. Unstructured methods use free-form descriptions to measure destination images and collect data from respondents through methods such as focus groups or open-ended questionnaires (Cao X P et al., 2020 [14]). With the popularity of mobile internet, online travelogues (Cai and Song, 2019 [28]; Zhang 2022 [30]; Na and Xie, 2016 [49]), online reviews (Lidija Lalicic et al., 2021 [50]) and online photos (Xiao. X et al., 2022 [51]; Eleonora Crapolicchio et al. [52]; Li. C et al., 2022 [53]; Bi. J et al., 2021 [54]) are important sources of unstructured data. In this study, the unstructured method is combined with the structural method to build a system of tourism image elements through the non-structural method, and based on this, the structural method is used to assess tourism intentions.

3. Case Site Overview

The ancient villages in southern Anhui province are representative of traditional Chinese villages, embodying values such as history, culture, aesthetics, tourism, and economy. Xidi village is renowned as ‘the museum of Chinese folk culture in the Ming and Qing dynasties’ due to the preservation of ancient buildings and its historical and cultural significance. It is considered the most typical representation of traditional villages in southern Anhui. Xidi village is a traditional village located in Yixian County, Huangshan City, Anhui Province. It was founded in 1047 A.D and is home to a cluster of individuals with the Hu surname who are linked by clan blood relations. Xidi ancient village is known as the ‘museum of Chinese Ming and Qing dynasty residential culture’ due to the preservation of its ancient buildings and their historical and culture value. It is a typical representative of the regional culture of southern Anhui, China. In 2000, Xidi village was added to the World Cultural Heritage List. In 2022, it was selected as one of the ‘World’s Best Tourism Villages’ by the United Nations World Tourism Organization. It has also been awarded the honorary titles of China’s national AAAAA (Tourist attractions in the People’s Republic of China are classified into five levels: AAAAA, AAAA, AAA, AA, and A, with AAAAA being the highest level and represents China’s world-class boutique tourist scenic spots. To be considered an AAAAA level scenic spot in China, 12 conditions must be met, including requirements for tourism traffic, safety, health, resources, and tourist satisfaction rates. The Ministry of Culture and Tourism of the People’s Republic of China assesses these conditions) tourist attractions, Chinese historical and cultural villages, Chinese traditional villages, and Chinese key villages of rural tourism. Due to the rapid development of tourism, local residents have increasingly participated in tourism-related business activities. As a result, many of the ancient buildings in Xidi village have been repurposed for commercial use, creating a unique space where production and tourism intersect. In 2022, Xidi village had 260 farmers involved in tourism operations, with over 1200 people employed in the industry. Tourism-related work engaged almost 80% of the local residents, and the village welcomed more than one million tourists annually (YU F F, 2024 [55]). Xidi village has been selected as the case study site for this research due to its regional cultural characteristics, cultural protection and inheritance, and tourism development achievements.

4. Study Design

This study is divided into two steps. The first step involves mining the content of tourists’ online reviews. The system of tourism imagery elements is then constructed through three-level coding and the application of the rooting theory. A total of 7255 comments were obtained from three online travel platforms: Ctrip “https://www.ctrip.com” (5 August 2022), Tongcheng Travel “https://www.ly.com” (5 August 2022), and CatTuYing “http://www.tripadvisor.com” (5 August 2022). After manually cleaning and filtering 5969 valid comments, a total word count of 27,916 was obtained, excluding duplicate, meaningless, and garbled comments. The design was based on the cognitive imagery elements in the constructed tourism imagery element system. The tourism imagery of Xidi village was assessed through field research, and the emotional imagery elements in the tourism imagery element system were evaluated through tourists’ online evaluations. The questionnaire comprises two modules. The first module covers basic information about tourists, including gender, age, occupation, and 11 other items. The second module is the Xidi tourist cognitive imagery questionnaire, which consists of 25 questions. Tourists rate their satisfaction and perceived importance using the Likert 5-point method. The research team conducted a three-day field research from 7 to 9, January 2023. A total of 340 questionnaires were distributed, and 321 were returned, resulting in a recovery rate of 94.41%. After excluding invalid questionnaires, 308 valid questionnaires were obtained, resulting in a questionnaire efficiency rate of 95.95%. The basic technical route of this study is illustrated in Figure 1.

5. Traditional Village Tourism Place Imagery System Construction

5.1. Open Coding

Open coding is the process of inductively analyzing, examining, comparing, conceptualizing, and categorizing source material and phenomena. In this study, we analyzed 5969 valid comments. Following the process of ‘defining phenomena-developing concepts-mining categories’, we summarized the basic information that can express the imagery of rural tourism places. We formed 128 initial concepts and labeled them (e.g., a1). Additionally, the 128 initial concepts were categorized, and analyzed to extract 30 initial categories based on their common features (e.g., A1). An example of the extraction process is provided in

Table 1. Examples of open coding extraction concepts.

Code	Online Review Text (Phenomenon)	Conceptualization	Categorization
a2	More than 300 ancient houses of the Ming and Qing Dynasties are still preserved.	Residential architecture	A1 House construction
a3	The ancestral hall is beautifully built and has a profound meaning.	Ancestral hall
a6	Some of the more typical buildings are the South Lake Academy.	Architecture of the Academy
a9	In the courtyard, a cool breeze comes out into the alley under the blazing sun, and water flows past the door of every house.	Courtyard	A2 Accessory buildings
a12	Crossing the pond towards the observation deck on the hill provides a panoramic view.	Observation deck
a13	Surrounded by mountains on all sides, small bridges and flowing water, ancient and fragrant, I like this place very much.	Bridge
a15	The only pity is that the heads of the figures on the door cover were destroyed when the Four Olds were broken.	Door cover	A3 Architectural decoration
a17	There is also a very famous couplet on both sides: Happy every from hard, cheap will generally suffer.	Couplet
a18	At a relatively secluded alleyway, a large red lantern is suspended, bearing the “Three Fearful Halls”. This establishment is reputed to be a popular dining destination in the Xidi.	Red lantern

.

5.2. Main Axis Set Code

The categories initially extracted through open coding were subsequently compared and summarized multiple times to identify potential connections between them. Based on the theoretical framework of previous studies and incorporating the subjective evaluations of online reviewers, eight main categories were identified and labeled A–H (

Table 2. Main axis set code.

Category	Main Category
A1 housing construction; A2 accessory buildings; A3 building decoration	A Architectural landscape imagery
B1 waters; B2 fields; B3 woodlands; B4 plants; B5 animals; B6 natural phenomena	B Natural landscape Imagery
C1 people; C2 production life; C3 travel and tourism; C4 interactive communication	C Social landscape imagery
D1 historical figures; D2 cultural relics and monuments; D3 intangible cultural heritage; D4 clan history; D5 traditional culture	D Historical and cultural imagery
E1 gourmet Snacks; E2 souvenirs	E Food imagery
F1 road traffic; F2 accommodation; F3 infrastructure; F4 service facilities; F5 services	F Service facility imagery
G1 good service experience; G2 good travel sensory experience	G Positive emotional imagery
H1 low cost performance; H2 things do not work as expected; H3 poor environment	H Negative emotional imagery

). These categories include architectural natural, and social landscape imagery, as well as historical and cultural imagery, physical and gastronomic imagery, service facility imagery, positive emotion imagery, and negative emotion imagery.

5.3. Selective Coding

This study examined the coding process of 30 categories to determine the logical connection between the 8 main categories. The dimensions and core categories of the study were determined based on the three-level coding results presented in

Table 3. Selective coding.

Main Category	Dimensionality	Core Scope
A Architectural landscape imagery	Cognitive imagery	Rural tourism place imagery system
B Natural landscape imagery
C Social landscape imagery
D Historical and cultural imagery
E Food imagery
F Service facility imagery
G Positive emotional imagery	Emotional imagery
H Negative emotional imagery

. The imagery system of rural tourism places was constructed based on the existing studies that divide tourism imagery into two dimensions of ‘cognitive-emotional’ (Gartner, 1994 [22]).

6. Evaluation of Tourism Imagery in Traditional Villages

6.1. Cognitive Imagery Evaluation

6.1.1. Descriptive Statistical Analysis

Out of the 308 respondents, there were slightly more women than men. The age group of 18–44 years old accounted for a relatively high proportion of respondents, while the number of visitors of other age groups was relatively small. In term of education, visitors of Xidi village generally have higher education levels. Regarding occupation and income, the student group had the highest representation. This can be attributed to Xidi village being a popular rural study education destination and a sketching base. As a result, the majority of tourists interviewed had incomes below RMB 3000, leading to low tourism purchasing power for this group. This finding is consistent with the fact that Xidi village mainly offers inexpensive handicrafts as its primary tourism commodity (refer to

Table 4. Basic information statistics of visitors.

Categories	Options	Frequency (Number of People)	Percentage (%)	Categories	Options	Frequency (Number of People)	Percentage (%)
Gender	Male	148	48.1	Occupation	Government agencies and institutions	18	5.8
	Female	160	51.9		Enterprise workers	66	21.4
Age	Under 18 years old	8	2.6		Students	130	42.2
	18–44 years old	252	81.8		Self-employed or freelance	58	18.8
	45–59 years old	32	10.4		Farmers	10	3.2
	Over 60 years old	16	5.2		Retirees	24	7.8
Academic qualifications	Junior high school and below	18	5.8		Others	2	0.6
	Secondary and High School	36	11.7	Income	Less than RMB 3000	132	42.9
	College and undergraduate	196	63.6		RMB 3000–5000	50	16.2
	Master’s degree and above	58	18.8		RMB 5000–8000	66	21.4
					RMB 8000–12,000	36	11.7
					Over RMB 12,000	24	7.8

).

6.1.2. Dimensional IPA Analysis

The traditional Importance-Performance Analysis (IPA) uses respondents’ self-reported evaluation of satisfaction and importance to assess the significance of each evaluation factor in enhancing customer satisfaction. By considering satisfaction as a form of performance, IPA analysis becomes a comprehensive method for objectively analyzing the importance of influencing factors and the actual perception of tourism image (CHEN Xu, 2013 [56]). Importance-satisfaction analysis is a comprehensive method for objectively analyzing the importance and actual perception of factors that influence the perception of tourism imagery. The results of the IPA analysis of tourism imagery in Xidi village are presented in

Table 5. Results of dimensional importance-satisfaction analysis.

Dimensionality	Satisfaction (P)		Importance (I)		Mean Difference Value (P-I)	t Value	p Value
	Average Value	Sequence	Average Value	Sequence
Architectural landscape imagery	4.34	1	4.49	1	−0.15	−2.735	0.007
Natural landscape Imagery	3.80	4	4.16	5	−0.36	−6.419	0.000
Social landscape imagery	3.80	5	4.17	4	−0.38	−6.607	0.000
Historical and cultural imagery	4.05	2	4.37	3	−0.32	−5.692	0.000
Food imagery	3.32	6	3.88	6	−0.56	−7.309	0.000
Facility service imagery	3.89	3	4.41	2	−0.52	−8.918	0.000
Average value	3.87		4.21		−0.34

, with a mean satisfaction value of 3.87 and a mean importance value of 4.21. The satisfaction level for each dimension is lower than its corresponding importance level, indicating that the overall tourism image of Xidi village is still lacking systematically.

This study analyzed the importance of tourism intention elements and tourism imagery satisfaction using an IPA matrix chart (Figure 2). The vertical axis represents the importance of each index, while the horizontal axis represents the actual perception of each index. The mean value serves as the reference line. The result showed that quadrant I is the dominant area, indicating high satisfaction and high importance. This quadrant contains architectural, landscape, historical, and cultural imagery, as well as facility service imagery. Their levels of satisfaction and importance are higher than average, indicating that they occupy a dominant position, meet the psychological expectations of tourists, and are the core imagery of the scenic spot. Xidi village is a representative of the ancient villages in southern Anhui. It is favored by tourists for its architectural art and historical and cultural values. However, the level of satisfaction with facility service imagery is lower than overall satisfaction and needs improvement.

Quadrant III represents the opportunity zone, characterized by low satisfaction and low importance. This quadrant includes natural landscape imagery, social landscape imagery, and food imagery. The levels of satisfaction and importance for these aspects are lower than the average, indicating that they are not dominant and the actual perception by tourists is weak. However, this does not imply that such imagery can be ignored. In contrast, there is room for improving such imagery, which can be a new entry point for enhancing tourists’ satisfaction and a driving force for the sustainable development of scenic spots.

Quadrant II represents the maintenance area, which reflects high satisfaction but low importance. Its satisfaction level is higher than the average, but its importance is lower than the average. This indicates that although this type of imagery is not the main concern of tourists, it has received high evaluations in terms of its actual performance. Maintaining this type of imagery can play an additional role in ensuring tourists’ satisfaction.

Quadrant IV represents the improvement zone, characterized by low satisfaction and high importance. Visions have high expectations for the imagery in this zone but are dissatisfied with its actual performance. Therefore, it requires significant attention, improvement, and enhancement. Although no dimensions are located in this quadrant, factor refinement analysis is still necessary.

6.1.3. Factor IPA Analysis

Table 6. Factor importance-satisfaction analysis table.

Factors	Satisfaction (P)		Importance (I)		Mean Difference (P-I)	t Value	p Value
	Average Value	Sequence	Average Value	Sequence
A1 Building construction	4.53	1	4.64	1	−0.11	−1.813	0.072
A2 Annexes	4.17	4	4.36	8	−0.19	−2.728	0.007
A3 Architectural decoration	4.32	2	4.45	6	−0.13	−1.906	0.059
B1 Water area	3.83	15	4.42	7	−0.59	−7.056	0.000
B2 Idyllic	3.88	12	4.22	16	−0.34	−4.803	0.000
B3 Woodland	3.68	22	4.06	22	−0.38	−5.231	0.000
B4 Plants	3.81	18	4.14	20	−0.33	−4.072	0.000
B5 Animals	3.49	23	3.87	24	−0.38	−4.026	0.000
B6 Natural phenomena	4.08	6	4.24	15	−0.16	−1.965	0.051
C1 Characters	3.82	17	4.19	18	−0.37	−4.097	0.000
C2 Production life phenomenon	3.76	20	4.06	23	−0.30	−3.95	0.000
C3 Travel and tourism activities	3.76	21	4.26	13	−0.50	−5.913	0.000
C4 Interactive communication	3.84	14	4.18	19	−0.34	−4.491	0.000
D1 Historical figures	3.97	9	4.26	14	−0.29	−4.082	0.000
D2 Heritage Sites	4.19	3	4.49	3	−0.30	−4.717	0.000
D3 Intangible cultural heritage	4.11	5	4.4	8	−0.29	−4.28	0.000
D4 Clan history	3.96	10	4.22	17	−0.26	−3.282	0.001
D5 Traditional culture	4.01	7	4.47	4	−0.46	−6.507	0.000
E1 Gourmet snacks	3.34	24	4.08	21	−0.74	−8.003	0.000
E2 Souvenirs	3.31	25	3.69	25	−0.38	−4.673	0.000
F1 Road traffic	4.01	8	4.4	9	−0.39	−4.794	0.000
F2 Accommodation	3.77	19	4.46	5	−0.69	−7.348	0.000
F3 Service facilities	3.95	11	4.52	2	−0.57	−7.495	0.000
F4 Ticketing system	3.88	13	4.31	12	−0.43	−4.935	0.000
F5 Guided tour service	3.83	16	4.35	11	−0.52	−5.299	0.000
Average value	3.89		4.27		−0.38

shows the results of the IPA refinement supplemented by the 25 cognitive imagery categories in the tourism imagery system constructed in this study, to further refine the analysis of the specific performance of each factor.

The scatter plot of the factor IPA analysis (Figure 3) shows the following:

Quadrant I is the dominant area, housing buildings (A1), accessory buildings (A2), architectural decoration (A3), cultural relics and monuments (D2), intangible cultural heritage (D3), traditional culture (D5), road traffic (F1), and service facilities (F5). The location of these elements is consistent with the dimensional IPA analysis. Factors A1, A2, and A3 represent architectural landscape imagery, indicating that architectural landscape is the primary landscape imagery of Xidi village, recognized by tourists. Factors D2, D3, and D5 are part of the historical and cultural imagery. As a world cultural heritage site, historical and cultural aspects are important tourism resources of Xidi village, appreciated by tourists. Factors F1 and F5 are part of the facility service imagery, indicating that the level of infrastructure services in Xidi village has significantly improved after years of tourism development.

Quadrant II is the maintenance area, containing natural phenomena (B6), historical figures (D1), and clan history (D4), which belong to the natural landscape and historical culture dimensions, respectively. While natural phenomena may not be the primary focus for tourists visiting Xidi village, the sunrise and sunset, as well as the seasonal changes between cloudy and sunny weather, provide a unique and memorable experience. Similarly, while historical figures and clan history may not be the most prominent aspects of Xidi’s culture and history, they still contribute significantly to the high levels of visitor satisfaction.

Quadrant III is the opportunity area, containing ten factors: fields (B2), woodlands (B3), plants (B4), animals (B5), people (C1), production and life (C2), tourism (C3), interaction and communication (C4), food and snacks (E1), and souvenirs (E2). These factors belong to the three dimensions of natural landscape, social landscape, and products and food, respectively. They are consistent with dimensions B2-B5, which belong to natural landscape imagery. Compared to Huizhou’s ancient architecture, tourists tend to overlook Xidi’s natural landscapes. These landscapes are not adequately represented, indicating a lack of opportunities for tourists to experience them and resulting in low recognition. It is important to highlight the natural beauty of Xidi to attract more visitors. C1-C4 are part of the social landscape imagery. As most villagers in Xidi are involved in tourism development, tourists have a weak experience of the originality of production life in Xidi village. Additionally, there are fewer experiential tourism projects in the village, resulting in low importance and satisfaction of these elements. E1 and E2 belong to the imagery of food and products. The buildings in Xidi village primarily serve as cultural displays, with limited space for food and beverage operations. Due to the village’s small size, tours typically last only 1–2 h, resulting in low demand for food and beverages among tourists. Additionally, the high price of specialty foods further contributes to low tourist satisfaction. The village’s tourist souvenirs consist mainly of inexpensive handicrafts, lacking variety and distinctive characteristics. This makes it difficult to capture the attention and recognition of tourists in the area.

Quadrant IV is the area for improvement, with four factors located in this quadrant belonging to the natural landscape and facility services dimensions. The water landscape is a crucial element of traditional villages in southern Anhui. However, the water landscape in Xidi village is relatively small compared to the nearby Hongcun water landscape, resulting in lower tourist satisfaction. It is important to note that this is a subjective evaluation. F2, F4 and F5 are part of the facility service imagery, which are the elements that tourists are most concerned about. However, the satisfaction level is lower than average due to factors such as poor hygiene conditions and the cost performance of the accommodation. These factors need to be improved and enhanced.

6.2. Emotional Imagery Evaluation

Tourism emotional imagery refers to the visual representation of tourists’ satisfaction with tourism. In this study, we conducted sentiment analysis of the online review text materials of Xidi village (

Table 7. Statistical table of sentiment analysis of online reviews.

Emotional Tendencies	Number of Comments	Number Share	Intensity	Number of Comments	Number Share
Positive emotions	4763	77.20%	High (above 20)	1276	20.68%
			Moderate (10–20)	1497	24.26%
			General (0–10)	1990	32.25%
Neutral emotions	708	11.47%
Negative emotions	699	11.33%	High (below −20)	12	0.19%
			Moderate (−20–10)	117	1.90%
			General (−10 to 0)	536	8.69%

) using the sentiment analysis function in the ROST (version CM6) software to determine tourists’ emotional tendencies, including positive, neutral, and negative sentiments.

The evaluation of Xidi village tourism by tourists is predominantly positive, with positive emotions accounting for 77.20%, the highest percentage. Neutral emotions account for 11.47%, and negative emotions account for 11.33%, the smallest percentage. The positive emotion score is mainly reflected in the admiration and praise of the scenery, folk style, food, experiences, etc. For instance, some tourists have described Xidi folk style as simple and beautiful, with stunning scenery that is definitely worth a visit. They also come to shop and eat, making it an ideal place for a vacation. The text maintains a neutral tone throughout, providing objective descriptions of the scenic locations. For example, ‘The ancient villages in southern Anhui Province are located in the east of Yixian County, Anhui Province, represented by Xidi Village and Hongcun Village’. The negative emotion score is negative, indicating tourists’ dissatisfaction with the scenic spots and touring experience. This dissatisfaction is mainly due to several factors, including product differentiation, ticket prices, environmental health, and commercialization. Additionally, some tourists have also provided feedback: “the high cost of tickets and poor cost performance are major drawbacks”, “the whole Xidi to my feeling is dirty, more mosquitoes, more insects”, “too much commercialization, each attraction is basically a store, selling more or less the same thing”. These negative emotions were generated in addition to the subjective reasons of tourists. In addition to the subjective reasons of tourists, the feedback shows that Xidi village is in urgent need of upgrading in these aspects.

7. Conclusions, Discussion and Recommendations

7.1. Research Conclusions

(1) The study employs a rooted theory approach to construct an image system of rural tourism destinations, comprising two dimensions, “cognition and emotion”. This is achieved through data mining and analysis of tourists’ online evaluations. A three-level coding approach was employed to extract 6 main categories of cognitive images from 25 specific categories. These included architectural landscape, natural landscape, social landscape, history and culture, product and food, and service facilities. The cognitive dimension of tourist destination image was established, while the affective dimension included two main categories: positive emotion and negative emotion. The construction of the system serves to reinforce image theory and establishes a theoretical framework for the study of tourism image. At the same time, the research results provide a basis for the practice of systematic promotion of rural tourism destinations.

(2) An IPA analysis method was employed to evaluate the tourism image of Xidi village through a questionnaire survey of tourists. The findings indicate that overall tourist satisfaction is lower than its importance, suggesting a need for improvement in the perception of the tourist destination image in Xidi village. The analysis using the dimension IPA indicates that the three dimensions of natural landscape image, social landscape image, and product food image are situated within the opportunity area, presenting a significant scope for further development and improvement. Furthermore, the results of the factor IPA indicate that the four factors of water, accommodation, ticket systems, and tour guide services require improvement. Tourists have high expectations for these aspects, yet the actual performance is not ideal. This discrepancy between expectation and reality requires significant attention, improvement, and promotion.

(3) The results of the emotion analysis indicate that positive and neutral emotions are the most prevalent in the online comments, accounting for 77.20% and 11.47%, respectively. In contrast, negative emotions only account for 11.33%. This suggests that tourists’ overall satisfaction with Xidi village tourism is positive, but there is still room for improvement in several areas, including cost performance, difference, environmental health and service attitude. Although the proportion of negative emotion in the whole emotion is not high, the negative image formed has a significant impact on the development of tourism destinations. Therefore, the results of the sentiment analysis can assist in identifying the optimal direction for the improvement of scenic spots.

7.2. Discussion

The data used to construct the tourist image element system in this study were sourced from online travel notes. It is important to note that the majority of travel note writers are young and middle-aged, which may limit the study’s coverage of tourist groups and impact research results. To enhance the objectivity of research conclusions, future studies should combine sampling survey methods, such as questionnaires and interviews, with online data. Moreover, the southern region of Anhui Province boasts numerous traditional Hui-style ancient villages. However, due to variations in location, environment, layout, and scale, tourists may perceive each village differently. Therefore, future research should explore the use of multi-case sites.

7.3. Development Suggestions

7.3.1. Optimizing Development Layout with Protection in Mind

Xidi village’s core tourism attractions are its Huizhou architecture, profound folk culture, non-foreign heritage culture, Huizhou merchant culture, and clan culture. These should be protected, as they are highly valued by tourists. However, the commercialization resulting forming tourism development can negatively impact the tourist experience and cultural preservation. Thus, the layout of Xidi village can be enhanced by establishing core protection zones, special commercial zones, and leisure experience zones. The core protection zone primarily showcases the uniqueness of Anhui Southern Anhui Huizhou architecture and historical culture while also integrating the daily production and life of its residents. The special commercial zone highlights local cuisine and handicrafts to enrich the tourism experience. The leisure experience zone primarily utilizes the ecological and natural landscapes and environments surrounding the core experience of tourists and expands the new tourism mode.

7.3.2. Seeking Different Development Based on Its Own Strengths

Southern Anhui boasts numerous ancient villages, but it can be challenging to innovate the development mode. Replicating the same ideas and approaches can result in a lack of uniqueness, leading to a generic tourist experience devoid of charm. Some tourists have expressed that they have seen too many ancient villages and feel that they are almost identical. This is particularly true for Xidi and Hongcun, both of which are World Heritage Sites. They have extremely similar architectural landscapes, natural landscapes, historical cultures, and geographical locations, and their target markets also converge. Therefore, differentiated development that seeks common ground while preserving differences is an important direction for their future development. Compared to Hongcun, Xidi is less commercialized, which limits the development of scenic spots while maintaining the original flavor of ancient villages. In the future, new areas should be planned for tourism development to guide tourists and capital diversion, strengthen heritage repair, improve infrastructure construction, and meet the interests of enterprises, residents, tourists, and other multi-interest subjects. Compared to Hongcun, Xidi offers unique ‘water screen movie’ and ‘music fountain’ activities, making full use of existing resources. The town vigorously develops night tour projects, plans and develops special night leisure neighborhoods and tourism products, and cultivates special night time activities.

7.3.3. Improve Service Facilities and Improve Service Quality

The IPA results show that service facilities and scenic service elements are predominantly located in quadrant IV, which reflects their high importance. However, visitor satisfaction is not correspondingly high, and this is an area that requires improvement. Factors such as signage and trash cans should be addressed to enhance visitor satisfaction. According to sentiment analysis, tourists are primarily concerned with the ticket price of the scenic spot. Many online comments mention that while the scenery is good, the ticket price is too expensive, and the cost performance is extremely low. To meet the needs of tourists with different demands, scenic areas should consider implementing diversified ticket-pricing models. This could involve developing different ticket prices within the existing ‘three-day ticket’ model, based on the increase in a ‘single day ticket’ or ‘time ticket’. It is important to ensure that the suggestions for improving scenic spots include adjusting the economic structure, changing the operation mode to prioritize project experience fees over entrance fees, and developing more popular tourism products. It is important to avoid relying solely on entrance fees as the main source of income.