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Development of a smart tourism integration model to preserve the cultural heritage of ancient villages in Northern Guangxi

Abstract

The modern rural areas represent a vulnerable category that is in special need of sustainable development these days. However, the practice shows that, in the twenty-first century, this sustainability can be assured through the construction of smart villages. The ultimate goal of this study was to create a model for the development of ancient Guangxi villages that will take into account the cultural and tourist dimensions and will be based on the Smart Village concept. Analysis of existing approaches to the implementation of the Smart Village initiatives as well as of regional and local regulatory documents in force allowed identifying key aspects (factors) in this respect. Local government officials, service providers, and local residents were surveyed, and the sample was 586 people. They were asked to rate the implementation in their village of key aspects of the Smart Village concept from 1 to 5 on a Likert scale (from "very bad" to "excellent"). According to the assessments collected, the top-rated and, accordingly, the most developed, was the Technological factor group, followed by the groups encompassing Culture and Tourism, then Economic, then Environmental, and Social factors. These data provided a good foundation for building a Smart Village-based model for the development of six ancient Guangxi villages, known for their unique cultural heritage (Xingping, Daxu, Huangyao, Jixiang, Fuli, and Longji Zhuang). In the future, it can be taken advantage of by government representatives and managers in respect to rural areas with conditions similar to those discussed within the limits of the current study (with certain regional adjustments).

Introduction

In recent years, art, food, fashion, music, tourism have become a driving force promoting the development of the “new economy” in many cities and regions. As a result, towns and rural areas in decline regained their viability and made the transition to this new economy type due to the creation of new tourist spots [1]. The People’s Republic of China has as many as 220 ancient villages and towns with a history of over 100 years old. All of them are unique and have a deep cultural and historical heritage [2]. Rural tourism is a key driving force for rural revival and fight against poverty [3].

Historic villages have become attractive destinations for rural tourism, combining leisure, recreation, and education [4]. “Ancient town culture” is the deposition of natural features, morphological structure, cultural style, human resources, craft buildings, historical heritage, and landscape image that are unique to the development of towns [2]. Ancient villages are the carriers of traditional culture, lifestyle, and social ideology based on a specific economic and social structure. They represent the integration of humans and nature and the accumulation of history for thousands of years [5]. Consequently, the ancient villages of China have become regions of tourism value and market importance, while rural tourism became a driving force for their sustainable development [6].

These days, rural areas are redefined as “places of consumption” where agricultural production, history, and traditions become the main elements of their identification and development [7]. Most cities and regions began to compete in the promotion of tourism [8,9,10,11,12,13].

By stimulating regional initiatives, the Administration of Cultural Relics of China designated the first group of historic and cultural villages, which reflect traditional features, local ethnic characteristics, and carry rich historical values or commemorative importance within certain historical periods [14]. In 2013, the Ministry of Agriculture launched the Beautiful Village Project to promote rural areas, which led to a socio-economic revitalization of the countryside, owing to the comprehensive development of production, life, and ecology [15]. Beautiful village construction has changed the traditional agricultural production structure, rural planning and layout, as well as rural culture and ecological environment. Thus, it remains an important part of Beautiful China construction [16], as well as a significant way to realize rural revitalization [17]. The development of “production, life, and ecology” during the construction of beautiful villages is equivalent to the integrated development of “production, village, and scenery” in which the “village and scenery” are the substantiation expression of the concept of “life and ecology” [18]. Under the stimulation of rural tourism, the rural area is no longer a simple material space but a social space with economic value [19]. Beautiful village construction is a typical example of China’s rural revitalization strategy and is an important way to promote rural economic development, yet it is not the only way [20]. The construction of beautiful villages in China has effectively prevented the widening gap between urban and rural areas and alleviated the social crisis [21]. Nevertheless, it has not fundamentally established a benign interaction mechanism between urban and rural areas [22, 23].

The structure of the rural space and industrial relations enrich rural culture. Thus, the revitalization of the countryside is not only production environment optimization but also integrated development of “production, village, and scenery” [24]. Under the background of rural revitalization, the new integrated development mode is not isolated and is a mutually promoting symbiotic system. Based on the “production, village, and scenery,” on the example of Qinganshu village, the AMD development model was proposed (Aims, Measures, and Demands) [19]. This model takes into account the diagnosis of the rural situation and combines the various elements of the village development. The model opens the prospect of maximizing the use of existing agricultural resources, the development of characteristic agriculture, and the integration of “production, village, and scenery” into the synergetic system [25]. The integrated development mode considers the happiness of residents, prosperity of industry, and beautiful environment as the criteria with which to evaluate the rural community construction [19].

The Smart City and Smart Village concepts imply new technological solutions and innovative approaches to planning, life support, and infrastructure development to increase the welfare of the population and ensure sustainable development [9, 26]. Originally, the idea of smart planning was elaborated for cities to solve emerging problems and improve their dwellers’ life quality. However, over time it has moved to the provinces and villages [27]. The very concept of a Smart Village was first adopted in India [28]. Such models were a natural extension of the models developed for cities but implemented in more or less remote areas with allowances made for their regional characteristics—geographical location, recreational resources, cultural heritage, ethnic composition, and economic indicators. Nevertheless, while smart cities have similar problems (transport, management, waste, services), smart villages are more different in this respect. Some of them are characterized by developed tourism; others are economically supported by agriculture; still others suffer from natural disasters [9]. The basis for the implementation of Smart City and Smart Village concepts is information and communication technologies (ICT) [12, 29]. Though, apart from ICT, elements most frequently incorporated by the Smart Village model are governance, technology, resources, village service, living, tourism [26], energy, economy, people, and environment [9]. In the great scheme of things, the Smart Village model is the foundation allowing the full-fledged implementation of corresponding strategies [30]. In Europe, Smart Village initiatives are worked upon and realized by the Thematic Group of the European Network for Rural Development. It explores opportunities for the revitalization of rural areas through digital and social innovation, develops guidelines to facilitate the emergence and development of smart villages, acts as an information platform, and provides support to governing bodies [31,32,33]. In Indonesia, there are two considerable undertakings in the area. The first is the 100 Smart City movement developed in 2017 to implement the concept of Smart. The second, in turn, is represented by the Smart Kampung initiative (launched in Banyuwangi Regency) combining ICT, economic, healthcare, and education directions with poverty alleviation and serving as an example for other regions of Indonesia [26]. As for China, to achieve sustainable rural development through informatization and smart initiatives, the country’s government proposed the implementation of the Rural Revitalization Strategy (2017) and formulated the National Rural Revitalization Strategic Plan (2018–2022) and the Outline of the Smart Village Development Strategy (2019) [11].

To date, there are many theoretical studies and systematic reviews on smart villages, but the number of practice-oriented and well-reasoned studies is still not enough. Many scientific works have already taken a close look at the matters of the Smart Tourism Destinations initiative of the European Commission. What is more, the present study authors agree that tourism is the driving force of the economic development of certain areas (including the six Guangxi villages under study). However, at the same time, the authors see the need to analyze the development path of the selected villages more broadly than from the perspective of tourism alone. Therefore, this paper aims to create a model for the development of ancient Guangxi villages that will take into account the cultural and tourist dimensions and will be based on the Smart Village concept. For this purpose, several tasks are to be accomplished one by one:

  • Analyze already existing approaches from previous studies to build similar models.

  • Get acquainted with the current regulatory documentation.

  • Determine the main components of the questionnaire for the survey of local residents.

  • Summarize all the information obtained to build the final model for the development of ancient villages in northern Guangxi based on the Smart Village concept.

Methodology

Study area

Traditional villages of the northern part of Guangxi have unique historical features and cultural heritage, remaining an integral component of Chinese culture and art. For the present research, six ancient villages of Northern Guangxi, rich in tourist recreational resources and unique ethnic customs, were chosen. Among them are Xingping, Daxu, Huangyao, Jiuxian, Fuli, and Longji Zhuang villages (Fig. 1) [34].

Fig. 1
figure 1

Ancient villages of Guangxi [34]

Xingping Ancient Town is located on the east bank of the Li River, 63 km from Guilin, and 25 km from Yangshuo. Xingping attracts tourists with its famous landscapes, the preserved architecture of the Ming era, and the planning in accordance with strict Feng Shui rules. The highlights of Xingping Ancient Town include the Li River, landscapes of the Guilin Karst relief, an old fishing village, and the traditional ancient architecture of the Ming and Qing Dynasties.

Daxu Ancient Town is located in the southwest of the Guilin region. The ancient settlement preserved samples of traditional Chinese architecture and flagstone streets. Along the Li River, old buildings, dated from the Ming and Qing periods, with decorated cornices and carvings on doors and windows are located. Among the must-visit highlights in Daxu Ancient Town are Wanshaw Bridge (Longevity Bridge), old dwellings of locals, flagstone roads, and a 100-year-old dock. Daxu Ancient Town, with its more than 1800 years of history, is the best of the four largest market cities in Guangxi Province.

Huangyao Ancient Town is situated in the northeast of Guangxi Zhuang Autonomous Region, on the lower reaches of Li River and 200 km from Guilin. The charm of Huangyao lies in the water cities of the Jiannan area in the Jiangsu and Zhejiang Provinces with the featured old houses, alleys, little bridges, and chanting streams crossing the town.

Jiuxian Old Town is located between Guilin and Yangshuo on the banks of the Yulong River. The main tourist attractions of the village are the Ancestor Hall of Li Family, the Guangxi oldest stone arch bridge (Xiangui Bridge), the idyllic sceneries of the Yulong River, and countryside life of Yangshuo people.

Fuli Old Town is 8 km away from Yangshuo in Guilin. Known as the “hometown of painted paper fans” in China, Fuli is one of the few best-preserved ancient towns in Guilin. People there still keep their traditional way of living. Fuli also preserves its unique old culture and the very primitive, though fascinating and mysterious, tribe culture of Nuo music, Nuo dance, and Nuo masks. The town is surrounded by mountains on three sides. To the north, the legendary Donglanshan Mountain is located.

Longji Old Zhuang Village is 100 km from Guilin. This village is famous for its colorful hills with rice terraces and the ethnic settlements of the Zhuang people. Longji Old Zhuang Village preserves the most extensive number of Diaojiaolou wooden houses and stone carvings that demonstrate the culture of the Zhuang ethnic group. Longji Rice Terraces (or Dragon Ridge Terraces) are located 27 km south of Longsheng Town. Layer by layer, they cover hills and mountains, resulted from the centuries-old agricultural activity of the Yao, Miao, and Zhuang peoples, whose culture and folklore are among the highlights of this region.

Research methods

To build a Smart Village model, the following steps were taken in accordance with the already described approach [26]:

  • Literature review of similar studies touching upon the Smart Village topic.

  • Analysis of existing regional and local regulatory documents and acts.

  • Population survey.

For the study purposes, more than 200 scientific articles recently published in Scopus and Web of Science electronic databases, including in the journals of Springer Nature, Elsevier, IOP Publishing, IEEE, Emerald Insight, Wiley-Blackwell, and SAGE publishers, were analyzed for the “Smart Village” query. Of this number, 45 works were selected that, in the authors’ opinion, most fully meet the goals and objectives of this research. They are mentioned in the list of references, with 11 of them directly related to the Smart Village concept [9, 11, 26, 27, 29, 30, 33, 35,36,37,38,39].

Within the next step, ISO 37122:2019 (Sustainable Cities and Communities-Indicators for Smart Cities) [40], National Rural Revitalization Strategic Plan (2018–2022), the Outline of the Smart Village Development Strategy (2019), and the information from Guangxi official website and Guangxi statistical yearbook were analyzed. This allowed identifying the main factors that were to be assessed by means of the questionnaire. Table 1 lists the literary sources from which the main groups of smart factors were taken. In the next study phase, they were evaluated through questionnaires.

Table 1 Factor group in the context of the smart village, and the articles supporting the identification of the factor groups

The survey of local residents was conducted to obtain information on the level of economic development, technology, culture and tourism, environment, natural resources, and the social sphere of Xingping (n = 99), Daxu (n = 102), Huangyao (n = 95), Jixiang (n = 93), Fuli (n = 97), and Longji Zhuang villages (n = 100). Officials, service personnel (including those engaged in IT), as well as average local population were invited as respondents. The sample consisted of 95–102 people for each village (586 people in total), with 75–80% of the people being average locals and 20–25% being officials and service workers. Survey items were asked to be rated from 1 to 5 points on a Likert scale (from “very bad” to “excellent”). The wording of the items was exceptionally straightforward and implied respondents to rate the implementation in their village of the Smart concept elements (hereinafter referred to as “factors”) highlighted during the literature analysis. Those factors that were predominantly rated as “very bad” and “bad” were excluded from the analysis, so only the answers starting from 1173 points (1173–1758—gradations “average”, 1759–2344—“good”, and 2345–2930—“excellent”) were considered.

The total score by factor \({S}_{f}\) for six villages is calculated by the formula:

$${S}_{f}=\sum_{n=1}^{6}{f}_{n}$$
(1)

where, \({f}_{n}\) – a score for factor f in each village.

Group average (GA) is calculated as the average between the number of factors m in the group:

$$\mathrm{GA}= \frac{1}{m}\sum_{i=1}^{m}{S}_{fi}$$
(2)

Results

The conducted literature analysis enabled the conclusion that the use of ICT can sustain and notably improve rural services, but this requires policy reforms and legislative initiatives, as well as action-oriented proposals from governing bodies and all the stakeholders. The driving force of the Smart Village concept lies in the fact that novel technologies should catalyze the development of the village, opening up opportunities for local businesses, bettering health and well-being, and promoting democratic participation in the life of the village and overall advancement of residents’ lives.

The survey outcomes unveiled that the technological factor group is of the highest weight within the six villages studied. The next most popular groups were Cultural and Tourism and Economic, followed by Environmental, and the Social group had the lowest points.

See Appendix 1 for a complete table of respondent scores from each village for each factor.

Calculations for the other groups are made in the same way. The results for each of the factor groups are summarized in Tables 2, 3, 4, 5, 6. The first column shows the factor, the second the explanation for it, the third—the total score by factor for 6 villages by the formula (1), the fourth the sample variance (D), and the fifth the standard deviation (SD). The group average was calculated by the formula (2). The variance and standard deviation are also given for the 6 villages, but for the group of factors as a whole.

Table 2 Technology factor group
Table 3 Economic factor group
Table 4 Cultural and tourism factor
Table 5 The Environmental factor group
Table 6 The Social factor group

This group had 2353 points on average (SD = 90.64), indicating an “excellent” level (Fig. 2). Concurrently, the first place within its limits was given to the Internet Availability factor—2457 points (Table 2).

Fig. 2
figure 2

Distribution of factor groups according to respondents' estimates (average for a factor group)

The results for the Economic factor group are shown in Table 3.

The highest points in the Economic group were obtained for the Productivity factor—2394, while the group’s mean was on the level of 1993.2 (SD = 224.0) (Table 3). The leading factor in the Cultural and Tourism group (M = 2020.3, SD = 33.38) was the Tourist Destinations with 2064 points. Simultaneously, quite fascinating is that all factors were defined to be in a very close range of values (Table 4). As concerns the mean points, for both groups they correspond to the gradation “good” (Fig. 2).

The mean result for Environmental group factors [1847.2 (SD = 149.16)] and the overall state were defined as “good” (Fig. 2). The highest points within the group were given to the Energy Efficiency factor—2032 points (Table 5). In contrast, the worst group-wide assessments were assigned to the Social group. It received 1508.8 points on average (SD = 271.34) and correspondingly was characterized as the one with the “average” development level (Fig. 2). The Social Initiative and Openness factor was determined as the one rated best within its limits—it had as many as 1815 points (Table 6).

The final points of all indicators, sorted from smallest to largest, are shown in Fig. 3.

Fig. 3
figure 3

Respondents’ final points

The data obtained allowed forming a model of ancient villages’ development, consisting of the following components (Fig. 4):

Fig. 4
figure 4

The final model for ancient villages’ development based on the Smart Village concept

The survey showed that the studied villages have technological potential, technology factors received the highest ratings from respondents (2335.5 on average, 2457 max). At the same time, the economic factor of well-being was estimated by the respondents at 1815 points, while the average for the economic factor group was 1993.2. The previous studies found what indicators can ensure the well-being of rural areas. The literature review allowed forming indicators of smartness that lead to the economic well-being of rural areas, applicable to 6 villages in Guangxi (Fig. 5).

Fig. 5
figure 5

Indicators of smartness that lead to the economic well-being of rural areas

First, it is the interaction and joint participation of residents, government, and knowledge institutions in improving well-being through IT infrastructure and other technological innovations [35, 41, 42]; second, digital capabilities that enhance the activities of all stakeholders in well-being through IT [35, 43, 44]; third, coordination in technology services provision [35, 42, 44].

Discussion

The Smart Village is a kind of innovative concept that uses modern technological capabilities to improve the quality of life, increase the efficiency of all socio-economic interactions and production processes. Society is developing rapidly and has achieved various successes in improving the quality of life. Civilization remains a witness to many changes associated with its development through industrial, environmental, scientific, and technological catalysts. The modern era is complemented by information and communication technologies that have proven their potential in various sectors of urban and rural development. Urban areas appear to be more inclined to adopt and develop information and communication technologies because of the benefits of population literacy and better infrastructure than in rural areas [32].

The Smart Village concept has been increasingly heralded as a development strategy for the countryside but with no clear understanding as to what comprises a smart village. Smartness frequently is associated with the quality of IT infrastructure and the ability to use it. An alternative perspective argues that smartness can be understood as a phenomenon connected with self-organized, bottom-up community action that either addresses the weaknesses of both state and market to contribute to local people’s well-being or exploits emergent opportunities through collective means.

Colleagues report that rural smartness has an impact on the economy and business processes, namely:

  • Facilitates collaboration and promotes productivity in business [43];

  • Promotes a more productive use of available resources [44];

  • Encourages citizens to engage in entrepreneurial activities [42];

  • Introduces creativity and innovation;

  • Facilitates the creation of new products and services;

  • Provides access not only to a broader national market but also to a global market [44];

  • Increases jobs and opportunities for economic growth [35, 41].

There is a stable opinion in the world practice that in order to implement the concept of Smart Village, it is necessary to develop a model that would take into account all the regional characteristics of the territory [11]. Such a model was proposed within the limits of the current research for six ancient villages of northern Guangxi. It identified five key groups of factors: Technological, Economic, Environmental, Social, and Cultural and Tourism. Some researchers allocate more factor groups [9]; however, the central difference here is that they rely on the theoretical material (literature reviews), while in the present work, factors for the model were selected grounding on both the conducted survey and already available findings. In view of this, the authors believe that the model proposed is more suitable for the regional characteristics of these rural areas. Researchers emphasize that it is necessary to reckon with the geographical, socio-cultural, and economic components of the Smart concept [44]. The current research work is fully in line with this point as it is this principle that the authors tried to implement. This study adds to the international knowledge of Smart Village factors, taking into account the regional characteristics of six ancient Chinese villages with their unique nature and rich cultural heritage. Architectural solutions, art, philosophical and literary works in symbiosis with the unique rural natural landscapes can be confidently deemed the calling card of China and the key to improving the well-being of the local population [45] if rational management and technological solutions are introduced.

Conclusions

The aim of this study was to build a model for the development of ancient villages in Guangxi province (Xingping, Daxu, Huangyao, Jiuxian, Fuli, and Longji Zhuang) that will allow for the cultural and tourist components of those territories and will be grounded on the Smart Village concept. The model’s construction presupposed a grounded review of studies on the topic and a comprehensive analysis of regional and local regulatory documents. Such a strategy made it possible to determine the key model’s factors, which were then included in the questionnaire to survey ordinary people, officials, and service providers living and working there. The survey outcomes enabled slight adjustments to theoretically assumed elements of the model—only those factors remained, the level of development of which was assessed by respondents as “average,” “good,” and “excellent.” Thus, the proposed model demonstrates the state of certain indicators of the Smart Village strategy within the studied villages. It is assumed that this model will become the foundation for more effective implementation of Smart Village principles in relation to each group of factors (Technological, Economic, Cultural and Tourism, Environmental, Social) as all of them are closely linked with each other. For example, Technological factors, depending on their intended purpose, are highlighted as a separate group, but are also included in the Economic factor group (Innovation factor) and Social factor group (High-quality Information Transmission factor). The group of Culture and Tourism also does not go without them. In general, this implies the criticality of technology in implementing Smart Village initiatives. The carried-out survey confirmed the dominance of technology in practice—the Internet Availability factor had 2457 points, while the mean value of the Technological factor group was 2353 points (it was generally assessed as “excellent” with SD = 90.65). The IT Infrastructure and Cloud Computing factors were rated as “excellent” (2365 points) and “good” (2354 points), respectively, and gave way only to the Productivity factor from the Economic group, which got 2394 points (“excellent”). The remaining factors of the Economic group (Employment, Efficiently, Innovation, Financial stability, Welfare) were considered to be developed on the “good” level (2085–1789 points, SD = 224.02). Next in the respondents’ rating was the Cultural and Tourism group, which included Tourist Destinations, Integration of Ethnic Cultures, Support of Local Cultural Initiatives, and Cultural Preservation factors. On average, it was assessed as “good” with 2031.3 points and SD = 33.4. The Environmental factor group encompassing Energy Efficiency, Waste Management, Biodiversity, Environmental Planning, and Efficient Use of Landscapes, Water, and Land Resources factors had on average 1847.2 points (also considered “good” with SD = 149.2). Social group factors (Social Initiative and Openness, In-touch Capabilities, Open Educational Environment, High-quality Information Transmission, Effective Social Protection and Support System) had only 1508.8 points (SD = 271.3). Thus, it can be inferred that within the villages under study, technology, economy, environment, and culture and tourism should only be maintained at a stable level in the direction of smart development, whereas the social sphere should be brought up to a higher level. These conclusions are important for implementing the Smart Village strategy not only in the six villages in question but also in other rural areas with a similar state of economic development and cultural and tourist potential. Future research can focus on building Smart Village development models for rural areas having unfavorable natural conditions or relying upon industry or agriculture in their economic advancement instead of tourism as those in the current work.

Availability of data and materials

Data will be available on request.

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Acknowledgements

Western China project of National Social Science Foundation of China “Identification and activation paths of cultural genes in traditional villages in Yunnan, Guizhou, and Guangxi province ethnic tourism area” (Item no. 19XMZ097).

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The authors received no financial support for the research, authorship, and/or publication of this article.

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Authors and Affiliations

Authors

Contributions

WZL and HZ contributed equally to the experimentation. WZL wrote and edited the article. HZ designed and conducted the experiment. WZL and HZ studied scientific literature about the topic. Both authors read and approved the final manuscript.

Corresponding author

Correspondence to Hong Zhong.

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Appendix 1

Appendix 1

Respondent scores from each village for each factor.

Factor group Factor   Points
Technology Internet availability Xingping 445.3
Daxu 424.6
Huangyao 406.4
Jixiang 389.7
Fuli 396.2
Longji Zhuang 394.8
Total score 2457
IT infrastructure Xingping 426.5
Daxu 398
Huangyao 416.4
Jixiang 403.6
Fuli 338.3
Longji Zhuang 382.2
Total score 2365
Cloud computing Xingping 373.8
Daxu 407.5
Huangyao 412.4
Jixiang 354.2
Fuli 361.1
Longji Zhuang 327
Total score 2236
Suitability of technological services Xingping 378.4
Daxu 376.2
Huangyao 399.6
Jixiang 410.3
Fuli 408.6
Longji Zhuang 380.9
Total score 2354
Group average 2353
Economic Productivity Xingping 414.2
Daxu 428.1
Huangyao 369.5
Jixiang 396.3
Fuli 381.2
Longji Zhuang 404.7
Total score 2394
Employment Xingping 316.5
Daxu 338.9
Huangyao 356.4
Jixiang 374.2
Fuli 349.7
Longji Zhuang 349.3
Total score 2085
Efficiency Xingping 312.6
Daxu 340.8
Huangyao 298.4
Jixiang 320.5
Fuli 316.4
Longji Zhuang 315.3
Total score 1972
Innovation Xingping 330.3
Daxu 324.8
Huangyao 326.4
Jixiang 316.5
Fuli 305.2
Longji Zhuang 300.6
Total score 1904
Financial stability Xingping 313.7
Daxu 340.4
Huangyao 289.6
Jixiang 271.5
Fuli 299.3
Longji Zhuang 274.7
Total score 1789
Welfare Xingping 287.6
Daxu 315.5
Huangyao 298.9
Jixiang 312.3
Fuli 306.5
Longji Zhuang 294.2
Total score 1815
Group average 1993.2
Culture and tourism Tourist destinations Xingping 349.5
Daxu 356.8
Huangyao 329.7
Jixiang 341.6
Fuli 346.2
Longji Zhuang 340.2
Total score 2064
Integration of ethnic cultures Xingping 313.8
Daxu 332.4
Huangyao 350.6
Jixiang 378.5
Fuli 319.2
Longji Zhuang 352.1
Total score 2046
Support of local cultural initiatives Xingping 346.9
Daxu 341.9
Huangyao 343.6
Jixiang 345.8
Fuli 331.2
Longji Zhuang 319.6
Total score 2029
Cultural preservation Xingping 326.5
Daxu 319.8
Huangyao 333.4
Jixiang 340.8
Fuli 339.6
Longji Zhuang 325.9
Total score 1986
Group average 2031.3
Environmental Energy efficiency Xingping 332.6
Daxu 324.8
Huangyao 345.5
Jixiang 331.2
Fuli 329.6
Longji Zhuang 368.3
Total score 2032
Waste management Xingping 329.3
Daxu 321.1
Huangyao 338.5
Jixiang 336.9
Fuli 312.8
Longji Zhuang 306.4
Total score 1945
Biodiversity Xingping 298.5
Daxu 313.9
Huangyao 316.9
Jixiang 296.5
Fuli 324.8
Longji Zhuang 312.4
Total score 1863
Environmental planning Xingping 282.6
Daxu 294.8
Huangyao 289.5
Jixiang 278.5
Fuli 286.4
Longji Zhuang 282.2
Total score 1714
Efficient use of landscapes, water, and land resources Xingping 266.5
Daxu 271.9
Huangyao 253.4
Jixiang 288.3
Fuli 282.4
Longji Zhuang 319.5
Total score 1682
Group average 1847.2
Social Social initiative and openness Xingping 288.8
Daxu 312.5
Huangyao 302.2
Jixiang 286.4
Fuli 340.3
Longji Zhuang 284.8
Total score 1815
In-touch capabilities Xingping 274.5
Daxu 280.1
Huangyao 298.2
Jixiang 352.6
Fuli 284.5
Longji Zhuang 282.1
Total score 1772
Open educational environment Xingping 224.5
Daxu 237.7
Huangyao 224.5
Jixiang 218.3
Fuli 239.8
Longji Zhuang 249.2
Total score 1394
High-quality information transmission Xingping 239.4
Daxu 212.3
Huangyao 198.9
Jixiang 231.5
Fuli 241.6
Longji Zhuang 245.6
Total score 1368
Effective social protection and support system Xingping 186.4
Daxu 198.5
Huangyao 216.4
Jixiang 176.3
Fuli 195.6
Longji Zhuang 222
Total score 1195
Group average 1508.8

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Li, W.Z., Zhong, H. Development of a smart tourism integration model to preserve the cultural heritage of ancient villages in Northern Guangxi. Herit Sci 10, 91 (2022). https://doi.org/10.1186/s40494-022-00724-3

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Keywords

  • Cultural heritage
  • Economic growth
  • Guangxi ancient villages
  • Tourism development
  • Smart Village concept