Study on the Coupling Coordination Relationships and Driving Factors of “Ecology–Humanities–Technology” in Traditional Villages of the Xinjiang Oasis

Abstract

During the advancement of modern rural construction, traditional villages in the Xinjiang Oasis face the problem that uncoordinated system development affects scientific development and protection. Therefore, this study derives and constructs a coupling framework for the “Ecology–Humanities–Technology” system. Taking 53 traditional villages in Xinjiang as research objects, it uses the comprehensive evaluation model, the coupling coordination degree (CCD) model, and the geographic detector model to reveal the coupling coordination relationships and driving factors of the “Ecology–Humanities–Technology” system. The research results provide reference for evaluation methods and theoretical guidance for the balanced development of traditional villages in arid regions such as the Xinjiang Oasis. The results show the following: (1) The majority of the traditional villages in the Xinjiang Oasis are in the mild imbalance stage (71.7%). (2) The CCD rankings in various regions of Xinjiang are as follows: eastern Xinjiang > southern Xinjiang > northern Xinjiang. Humanities and technology have significantly different impacts on the traditional villages in different regions. (3) The inheritance level of the technology dimension and other factors are the main internal driving factors. The density of village road networks, the number of conservation and development projects, Baidu Index, and other factors are the main external driving factors. Nonlinear enhancement interaction effects are significant.

1. Introduction

Traditional villages in oasis regions possess abundant ecological adaptation resources and cultural resources. These resources have continuously evolved during the formation of the traditional villages and serve as a vital repository for the inheritance and development of local traditional villages [1]. Taking Xinjiang as an example, the Xinjiang Oasis spans 143,000 square kilometers and hosts numerous traditional villages. Compared to the traditional villages in other regions, those in the Xinjiang Oasis exhibit a more remarkable adaptation to the ecological environment, reflecting their unique resilience and sustainability [2,3]. Under the unique natural environmental conditions of Xinjiang, multi-ethnic integration and coexistence have fostered abundant humanities resources and technological resources through daily production and living practices. The ecology of traditional villages in oasis regions reflects the habitability level of their locations. The humanities dimension encompasses traditional cultural characteristics and social organizational relationships of the local communities. Technology refers to the production and living facilities and craftsmanship developed by residents over time to adapt to ecological and cultural environments [4,5]. The ecology, humanities, and technology of traditional villages in oasis regions are intricately interconnected, exhibiting complex relationships of synergistic compatibility and mutual conflicts during village conservation and development. For instance, deterioration of the ecological environment triggers population migration and loss, further leading to the dissipation of traditional production and living technologies. Conversely, the development of tourism industries often reshapes village landscapes through the indiscriminate replacement of original architectural and hydraulic technologies. Such practices not only undermine the sustainability of oasis adaptation but diminish the aesthetic and cultural appeal of villages, hindering the process of industrial upgrading and transformation. Therefore, coordinating the relationships among ecology, humanities, and technology is essential to establish scientific pathways for the sustainable conservation and development of traditional villages in oasis regions.

The core of high-quality protection and development of traditional villages lies in the stable optimization of the relationships among village systems. Therefore, it is necessary to analyze the problems faced by traditional villages from the perspective of system relationships. Current research on the system relationships of traditional villages mainly covers five aspects, including resource analysis, protection strategies, adaptation mechanisms, stakeholder interactions, and theoretical frameworks. Resource analysis requires analyzing village resources from composite perspectives, such as traditional village ecological wisdom [5] and village spatial evolution from multiple viewpoints [6,7]. Protection strategies require formulating multi-system village protection strategies by analyzing rural heritage value creation [8], living utilization in the context of tourism industry [9,10], and cultural landscape protection [11]. Adaptation mechanisms require exploring the complex adaptation processes formed by village system interactions through analyzing tourism adaptability [12,13] and rural resilience [14,15]. Stakeholder interactions require constructing rural heritage management methods from the perspectives of multi-party engagement [16,17], clarifying the construction of social relationships under technological production [18,19], and sorting out the mutually reinforcing “group structure–resource” relationships. Theoretical frameworks require mapping the real-world issues of multi-system theoretical frameworks, such as “production–living–ecology” spaces [20], social–ecological systems [21,22], and conducting quantitative evaluations. These studies include an understanding of the essence of ecology, humanities, and technology in traditional villages, and their research systems and methods provide substantial theoretical guidance for the system construction and development of traditional villages. However, from the needs and characteristics of oasis traditional villages, the previous research lacks the construction of relationships among ecology, humanities, and technology. Additionally, although many related theoretical frameworks provide methodologies for understanding the system relationships of traditional villages, they have not been further deepened or specialized in a framework structure, which is unfavorable for explaining problems in combination with the characteristics of traditional villages as the research object.

Therefore, this study draws on the logical thinking demonstrated by the social–ecological system framework to construct the core operational logic of the traditional villages in the Xinjiang Oasis. The social–ecological system framework is characterized by highly complex interactions between regional social and ecological subsystems, as well as the influence relationships between internal and external systems of the region. Ostrom’s social–ecological system analysis framework divides its internal natural subsystem into resource units and resource systems, and the social subsystem into governance systems and actor systems. Actors carry out a series of interaction processes under the constraints of governance systems to maintain the stability of resource systems, thereby producing outcomes and feedback. The interaction processes and outcome outputs organically link human and natural systems, presenting the core action contexts in regional development [23]. It is evident that the human-centered social organization groups in the social subsystem are closely linked with the resources of the ecological subsystem; when viewing the operation of traditional villages from the perspective of social–ecological systems, we expect to focus the actor system on local residents as a social group. At this time, the actions and governance methods of local residents are constrained by historical, long-term, and group-specific factors, manifested as cultural forms such as production and lifestyle, local traditions and customs, and village regulations [24]. Therefore, the social subsystem of traditional villages can be regarded as a humanistic system in which the social organizational structure of local residents governs and operates the village through various cultural forms; in Ostrom’s social–ecological system analysis framework, the technologies used in the actor system are important tools for promoting the construction of resource systems and resource units, and resource systems and resource units also form influence mappings on technological forms. This is particularly evident in the traditional villages of the Xinjiang Oasis with prominent ecological constraints. This warns us of the need to examine the associative characteristics of traditional village technologies in village operation and development, distinguish the technical characteristics of traditional villages from other material cultures, and improve the theoretical composition of the technological dimension. Such a perspective helps highlight the particularity of oasis traditional villages and strengthen the status of technology in the process of protecting and developing them.

Furthermore, the individual scale of the social–ecological system in the traditional villages of oasis regions is very limited, which determines the differences in internal operation forms and the interactive effects between villages and the external environment. On the one hand, the differences in interaction effects between different actor subjects and their governance systems and the ecological subsystem are more significant. On the other hand, the social–ecological systems of traditional villages and external social–ecological systems have unequal degrees of mutual influence. This study argues that, when the actor subjects are local residents, governments, enterprises, and political contexts can be regarded as external social systems. This is significantly different from Ostrom’s social–ecological system analysis framework, which includes governments, enterprises, tourists, etc., in the actor system, and assigns them nearly equal influence weights [23]. This study emphasizes the core position of local residents in village development and protection, and distinguishes the impacts formed by the governance actions of local residents and other subjects. Supporting evidence for this view can be found in the development challenges of some villages; governments and enterprises have invested heavily in village protection and development, but progress has been limited due to the lack of vitality in the social structure of the local residents. Therefore, in the current policies for the protection and utilization of traditional villages, mobilizing the enthusiasm of local residents and promoting the development of endogenous forces have become top priorities [25].

In summary, it can be seen that there are close relationships among the ecology, humanities, and technology of traditional villages in oasis regions, which reflect the scientific nature of internal development and utilization. Additionally, by sorting out the compositional logic of different actors and their governance relationships in the traditional village system, the differences in the impacts of social subjects inside and outside the village are clarified. Based on the characteristics of the traditional villages in the Xinjiang Oasis, this study draws on the analytical approach of the social–ecological system framework and combines it with system coupling theory [26] to further deepen the “Ecology–Humanities–Technology” system framework. As shown in Figure 1, ecology, as the system foundation, provides the resource needs for humanistic development and core guidance for technological composition; humanities, as the internal hub, provide management guarantees for the ecology and external communication channels for technology; technology, as the practical carrier, provides supporting tools for ecological construction and bond connections for humanistic construction. The three interact to form the internal system of village development. At the same time, the internal village system is driven by external social systems to develop.

The coupling coordination degree (CCD) model aims to quantify the balanced coordination level between closely interconnected systems, reflecting the degree of their interdependence. This model has been widely applied to study the interrelationships among ecology, economy, culture, and society at macro-regional scales [27], demonstrating strong practical utility. In recent years, scholars have utilized the CCD model to explore the protection and development levels of traditional villages from a system coupling perspective. The existing research indicates that the CCD model retains excellent performance even when applied to micro-regional contexts such as traditional villages [28]. The geographic detector model is a classical method for identifying the driving forces behind geographical phenomena. It can not only assess the explanatory power of individual factors on the spatial differentiation of dependent variables but detect the interactive effects of dual factors on these variables [29]. By integrating the geographic detector model with the CCD model, researchers can effectively identify the driving factors of the coupling coordination, thereby supporting scientific decision-making for planning interventions in system coupling.

Based on the construction of the system framework, this study focuses on the traditional villages in the Xinjiang Oasis to analyze the coupling coordination relationships of “Ecology–Humanities–Technology”. We employ a comprehensive evaluation model, the coupling coordination degree (CCD) model, the Pearson correlation analysis, and the geographic detector model as analytical tools to quantify the coupling coordination level of the three dimensions and identify the driving factors from both internal and external perspectives. From the new perspective of “Ecology–Humanities–Technology” system coupling, this study provides a methodology for researching the sustainable conservation and development of traditional villages in arid regions such as the Xinjiang Oasis.

2. Materials and Methods

2.1. Study Area

The study area is located in Xinjiang, spanning from 34°25′ N to 49°10′ N latitude and 73°40′ E to 96°18′ E longitude. Characterized by its “three mountain ranges enclosing two basins” topography and arid climate, Xinjiang has numerous oasis regions. These oases are primarily distributed along the northern and southern foothills of mountain ranges and the banks of rivers originating from these mountains, constituting a typical “mountain–oasis–desert” ecosystem. Over a long historical evolution process, multiple ethnic groups in Xinjiang have settled, migrated, and integrated within these oases, creating a rich cultural landscape. Based on geographical isolation and climatic differences, Xinjiang can be further divided into eastern Xinjiang, northern Xinjiang, and southern Xinjiang [30]. Specifically, eastern Xinjiang includes Hami (HM) and Turpan (TRP), where some of the sampled villages are located; northern Xinjiang encompasses Ili (IL), Changji (CJ), Bortala (BRTL), and Altay (ALT); southern Xinjiang covers Aksu (AKS), Kizilsu (KZLS), Bayingolin (BYGL), Kashgar (KS), and Hotan (HT).

This study takes the traditional villages in the Xinjiang Oasis as the research object, specifically selecting all 53 traditional villages from six batches of the National List of Traditional Villages as samples. These villages were jointly evaluated by the Ministry of Housing and Urban–Rural Development, the Ministry of Culture and Tourism, the National Cultural Heritage Administration, the Ministry of Finance, the Ministry of Natural Resources, and the Ministry of Agriculture and Rural Affairs, comprehensively examining their historical, cultural, ecological, and socioeconomic values [31]. All sampled villages originated within the oasis environments, reflecting strong traditional agriculture practices and ethnic historical–cultural characteristics. The 53 villages exhibit varying levels of conservation and development, making them representative cases for exploring the “Ecology–Humanities–Technology” coupling coordination relationships in the Xinjiang Oasis traditional villages (Figure 2). The name and number of the sample villages are listed in Appendix A 

Table A1. Name and number of sample villages.

Region		Village Name	Village Code
Eastern Xinjiang	Hami (HM)	Aletun Village	HM_1
		Bositan Village	HM_2
Eastern Xinjiang	Turpan (TRP)	Maza Village	TRP_1
		Baiximaili Village	TRP_2
		Saierkefu Village	TRP_3
		Kuonaxia Village	TRP_4
		Yingxiamaili Village	TRP_5
		Dihansu Village	TRP_6
		Tugemanboyi Village	TRP_7
		Sangeqiao Village	TRP_8
		Mukam Village	TRP_9
Northern Xinjiang	Ili (IL)	Qiongkushitai Village	IL_1
		Yichegashan Village	IL_2
	Changji (CJ)	Hebayan Village	CJ_1
		Shuimogou Village	CJ_2
		Tunzhuangzi Village	CJ_3
		Jiejiezi Village	CJ_4
		Machangwozi Village	CJ_5
		Yinggebao Village	CJ_6
		Yueliangdi Village	CJ_7
		Daquanhu Village	CJ_8
		Guoshuyuanzi Village	CJ_9
		Miao’ergou Village	CJ_10
	Bortala (BRTL)	Mingetaoleha Village	BRTL_1
		Jiegedebulage Village	BRTL_2
		Aliongbai New Village	BRTL_3
		Huhehaxia North Village	BRTL_4
		Arishate Village	BRTL_5
	Altay (ALT)	Hemu Village	ALT_1
		Baihaba Village	ALT_2
		Hezilehaying Village	ALT_3
		Talate Village	ALT_4
		Ulast Village	ALT_5
Southern Xinjiang	Aksu (AKS)	Jiayi Village	AKS_1
	Kizilsu (KZLS)	Aijieke Village	KZLS_1
		Azihan Village	KZLS_2
	Bayingolin (BYGL)	Huo’erge Village	BYGL_1
		Guolewusitang Village	BYGL_2
		Ruoqiang County Tuogelakuleke Village	BYGL_3
		Baluntai Village	BYGL_4
		Haoerhate Village	BYGL_5
		Baxilige Village	BYGL_6
		Outula Airike Village	BYGL_7
		Qiemo County Tuogelakuleke Village	BYGL_8
		Kulamuleke Village	BYGL_9
		Akya Village	BYGL_10
		Jianggalesayi Village	BYGL_11
	Kashgar (KS)	Qiakerikuyi Village	KS_1
		Kalabashilangan Village	KS_2
Southern Xinjiang	Hotan (HT)	Buda Village	HT_1
		Kang’azi Village	HT_2
		Pulu Village	HT_3
		Asigan Village	HT_4

.

2.2. Research Methods

2.2.1. Construction of the Indicator System

From the framework of the indicator system, the coupling coordination degree of “ecology–humanities–technology” reflects the state of the sustainable conservation and development of the villages [32]. Therefore, based on the existing research on the conservation and utilization of the traditional villages, this study proposes to examine three dimensions: the degree of ecological adaptation, the affinity of humanities, and the level of technological inheritance and conservation. Through a literature review, theoretical deduction, and expert interviews, this study established an indicator system for the traditional villages in the Xinjiang Oasis, composed of 3 system layers (Layer B), 9 criterion layers (Layer C), and 40 indicator layers (Layer D) within the “Ecology–Humanities–Technology” framework (

Table 1. Indicator system.

A Layer	B Layer	C Layer		D Layer	Indicator Type
EHT Coupling	Ecology (B1)	Terrain Selection (C1)	Village Topography	Average Slope of Village (D1)	-
				Average Relief of Village (D2)	-
				Average Elevation of Village (D3)	-
			Topography of Building Sites	Coverage Ratio of Buildings (D4)	+
				Morphology of Building Clusters (D5)	-
				Cohesion Degree of Buildings (D6)	+
		Water–Green Space Layout (C2)	Morphology of Water–Green Spaces	Coverage Rate of Water–Green Spaces (D7)	+
				Aggregation Degree of Water–Green Spaces (D8)	+
				Proportion of Largest Water–Green Patch in Landscape (D9)	+
			Connectivity between Water–Green Spaces and Buildings	Proximity Level between Water–Green Spaces and Buildings (D10)	+
				Connectivity Level between Water–Green Spaces and Buildings (D11)	+
		Climatic Environment (C3)	Macro-climatic Environment	Annual Average Precipitation at County Level (D12)	+
				Annual Average Temperature at County Level (D13)	-
				Annual Average PM2.5 Concentration at County Level (D14)	-
			Micro-climatic Environment	Temperature Stability of Village (D15)	+
				Wind Environment Stability of Village (D16)	+
				Frequency of Natural Disasters in Village (D17)	-
	Humanities (B2)	Coordination of Lifestyles (C4)		Annual Average Income of Villagers (D18)	+
				Diversity of Village Industries (D19)	+
				Synchronization of Villagers’ Production and Living Schedules (D20)	+
				Proportion of Population Practicing Traditional Dialect, Attire, and Diet (D21)	+
		Atmosphere of Ethnic–Cultural Customs (C5)		Frequency of Traditional Festivals and Rituals (D22)	+
				Richness of Traditional Music and Dance (D23)	+
				Continuity Rate of Traditional Etiquette (D24)	+
				Dissemination Degree of Village Regulations and Conventions (D25)	+
		Vitality of Social Structures (C6)		Ethnic Composition Ratio (D26)	+
				Cohesion of Social Organizations (D27)	+
				Permanent Population Rate of Village (D28)	+
				Population Mobility within Village (D29)	+
	Technology (B3)	Inheritance Level of Production Technology (C7)		Continuity Rate of agriculture Production Models (D30)	+
				Continuity Rate of agriculture Techniques (D31)	+
				Continuity Rate of Manufacturing Production Models (D32)	+
				Authenticity of Manufacturing Techniques (D33)	+
		Inheritance Level of Architectural Technology (C8)		Authenticity of Architectural Structural Types (D34)	+
				Authenticity of Building Materials (D35)	+
				Continuity Rate of Architectural Spatial Patterns (D36)	+
				Continuity Rate of Architectural Decorative Techniques (D37)	+
		Inheritance Level of Hydraulic Technology (C9)		Continuity Rate of Water Transport and Storage Facilities (D38)	+
				Continuity Rate of Water Transport and Storage Models (D39)	+
				Maintenance Quality of Hydraulic Facilities (D40)	+

Note: “+” indicates a positive indicator, and “-” indicates a negative indicator.

).

The ecological representation of traditional villages is primarily composed of the suitability levels of terrain selection (C1), water–green space layout (C2), and climatic environment (C3), a view that has gained wide academic consensus [19,33]. Current quantitative evaluations of traditional village ecology primarily focus on two approaches. Some studies assess the ecological suitability of traditional villages using objective data on regional climate and topography within their administrative jurisdictions [27], while others employ questionnaire surveys or expert evaluations to score the ecological suitability of village spatial configurations [34,35,36]. Notably, these studies tend to analyze ecological suitability from either a macro or micro perspective. However, Xinjiang’s “mountain–oasis–desert” ecosystem exhibits significant ecological heterogeneity between oasis interiors and exteriors [37]. Consequently, a sole reliance on either macro-ecological or micro-ecological analyses fails to accurately represent the ecological suitability of oasis traditional villages. Based on the above analysis and previous research findings, this study conducts a comprehensive analysis of terrain selection suitability (C1) by integrating the macro-topographic conditions (D1–D3) at the village level and the micro-topographic conditions (D4–D6) of building site selection. For water–green space layout suitability (C2), the research examines both the intrinsic spatial patterns (D7–D9) and the connectivity performance between water–green spaces and built environments (D10–D11). Regarding climatic environment assessment (C3), this study focuses on both the macro-climatic environment of the regions (D12–D14) where the traditional villages are located and the micro-climatic environment shaped by settlement patterns (D15–D17).

In the preceding text, this study drew on social–ecological system theory to advance the derivation and understanding of the humanistic system in traditional villages. In traditional villages, humanistic elements can be regarded as a system through which core subjects—local residents—develop and utilize the village via various governance methods. These governance methods are specifically manifested as cultural forms related to daily production and life. Therefore, this study argues that the evaluation of the humanistic system in traditional villages should include the coordination of lifestyles (C4), atmosphere of ethnic–cultural customs (C5), and the vitality of social structures (C6). Combining the existing evaluation studies on cultural landscape construction and revitalization protection in traditional villages [8,9,10,11,38], this study analyzes the coordination status of the residents’ lifestyles from the economic foundation of life (D18–D19) and the unity of production and living forms (D20–D21), examines the atmosphere of ethnic customs through the vitality of intangible cultural elements, such as songs, dances, activities, and etiquette (D22–D25), and finally reflects the vitality of social structures through ethnic composition and resident correlation characteristics (D26–D29). It is worth noting that the traditional villages in the Xinjiang Oasis have social organizations or groups linked by geography, professional ties, or blood relations. These social organizations are specialized forms through which local residents adapt to daily production and life, and they constitute an important foundation for constructing the humanistic heritage of the Xinjiang Oasis traditional villages. Therefore, this study incorporates the unity of social organizations (D27) into the evaluation layer of social structure vitality.

Currently, the indicators related to technologies in traditional villages are mostly subsumed under cultural heritage and landscape construction, and have not been systematically discussed. Based on the previous research [39,40,41] and the current status of the traditional villages in the Xinjiang Oasis, this study analyzes the compositional content of the technology layer from the inheritance levels of three aspects, including production technology (C7), architectural technology (C8), and hydraulic technology (C9). Among these, production technology is associated with the basic agriculture and manufacturing industries of traditional villages (D30–D33), while architectural technology forms an important component of traditional village heritage resources, manifested in four forms, such as types, materials, spatial patterns, and decorative techniques (D34–D37). Additionally, the traditional villages in the Xinjiang Oasis exhibit prominent “water-dependence” characteristics [42], and the full utilization of water resources is fundamental for villages to survive in barren regions. Therefore, it is necessary to fully understand the inheritance of local hydraulic technology, which includes investigations into water storage and conveyance technologies, as well as maintenance quality (D38–D40). Currently, the inheritance forms of these traditional villages have undergone significant changes (Figure 3). Notably, with the influx of modern production and living technologies, some villages have adopted new technologies while retaining traditional practices, whereas others have fully transitioned to modern modes. Therefore, this research evaluates technological content through two aspects, craftsmanship and operational models, and assesses the inheritance and conservation levels of technologies based on their continuity rate and authenticity.

2.2.2. Data Acquisition and Processing

The data sources for this study include the following five aspects: ① DEM Data from NASA’s Earth Science Data Portal: Acquired 12.5-m resolution DEM data for Xinjiang Uyghur Autonomous Region. Village-level DEM data were extracted using ArcGIS, and average values (D1–D3); ② Landscape Pattern Index Calculations: Leveraged landscape pattern indices at both landscape and class levels following established methodologies [43,44]. Land use data (1-m or 10-m resolution) for Xinjiang were obtained, village boundaries were delineated using ArcGIS, and patch boundaries were refined with satellite imagery. Fragstats 4.2 software was used to compute landscape level (D4–D9) and class level indicators (D10–D11); ③ Meteorological Data from the National Tibetan Plateau Data Center: Retrieved 5-year average meteorological data for the counties hosting the studied villages (D12–D14); ④ Official Documentation and Field Surveys: Official statistical materials, including traditional village application documents, conservation planning texts, village-level statistical bulletins, and the China Traditional Village Digital Museum; field survey data collected in January, May, July–August 2023, and July–August 2024 (D18–D19, D22–D27, D32–D35); ⑤ Interviews and Questionnaire Surveys: Primary data collected through structured interviews and questionnaire responses (D15–D17, D20–D21, D28–D31, D38–D40).

To eliminate differences in scale and units among the research data, this study applies the range standardization method for normalization. This method ensures that all data are transformed into positive indicators. The normalization formula for positive indicators is defined as Formula (1), while the formula for negative indicators is defined as Formula (2), as follows:

$$Y_{ij}={\displaystyle \frac{X_{ij}-Min(X_{ij})}{Max(X_{ij})-Min(X_{ij})}}$$

(1)

$$Y_{ij}={\displaystyle \frac{Max(X_{ij})-X_{ij}}{Max(X_{ij})-Min(X_{ij})}}$$

(2)

where X_ij is the original value and Y_ij is the standardized value.

To test the internal consistency of the research data and to ensure data reliability, this study employs Cronbach’s reliability analysis to assess the reliability of the data [19], as follows:

$$\alpha ={\displaystyle \frac{K}{K-1}}\left(1-{\displaystyle \frac{{\displaystyle \sum {S_i}^2}}{{S_x}^2}}\right)$$

(3)

where K is the total number of items, S_i² represents the variance of the i-th indicator, and S_x² represents the total variance. The results are shown in

Table 2. Cronbach Reliability Analysis Results.

D Layer	Cronbach’s Alpha	D Layer	Cronbach’s Alpha
D1	0.702	D21	0.699
D2	0.701	D22	0.704
D3	0.691	D23	0.697
D4	0.699	D24	0.685
D5	0.699	D25	0.699
D6	0.708	D26	0.704
D7	0.697	D27	0.701
D8	0.710	D28	0.718
D9	0.693	D29	0.715
D10	0.697	D30	0.681
D11	0.721	D31	0.684
D12	0.711	D32	0.671
D13	0.737	D33	0.685
D14	0.720	D34	0.663
D15	0.697	D35	0.664
D16	0.697	D36	0.683
D17	0.729	D37	0.671
D18	0.706	D38	0.661
D19	0.694	D39	0.675
D20	0.713	D40	0.681

.

As shown in Table 2, the Cronbach’s Alpha coefficients for all indicators are all greater than 0.6. Additionally, the overall reliability coefficient value is 0.703. Therefore, the research data in this paper exhibits high internal consistency and good reliability.

2.2.3. Entropy Weighting Method and Determination of Weights

This study applies the entropy weight method for objective weighting. The specific formulas are as follows:

$$P_{ij}={\displaystyle \frac{X_{ij}}{{\displaystyle {\sum }_{i=1}^m{X}_{ij}}}}$$

(4)

$$E_j=-{\displaystyle \frac{1}{lnm}}{\displaystyle \sum _{i=1}^m{P}_{ij}ln(P_{ij})}$$

(5)

$$W_j={\displaystyle \frac{1-E_j}{{\displaystyle {\sum }_{j=1}^n(1-E_j)}}}$$

(6)

where m is the total number of samples, E_j is entropy, n is the number of indicators, and W_j is the weight value.

2.2.4. Comprehensive Evaluation Model

This model is used to assess the comprehensive level of each system. The specific formula is as follows:

$$U_j={\displaystyle {\sum }_{j=1}^n{W}_{ij}}\times X_{ij}$$

(7)

2.2.5. Revised Coupling Coordination Degree Model

This study constructs an “Ecology–Humanities–Technology” coupling coordination degree model for the traditional villages in the Xinjiang Oasis. The traditional coupling coordination degree model has limitations in maintaining the validity of the coupling degree. To address this issue, we adopt the revised coupling coordination degree model [45].

The formula for calculating the three-dimensional coupling degree of “Ecology–Humanities–Technology” is as follows:

$$C=\sqrt{[1-{\displaystyle \frac{{\displaystyle \sum _{i>j,j=1}^n\sqrt{{(U_i-U_j)}^2}}}{{\displaystyle \sum _{m=1}^{n-1}m}}}]\times {\left({\displaystyle \prod _{i=1}^n\frac{U_i}{max(U_i)}}\right)}^{{\displaystyle \frac{1}{n-1}}}}$$

(8)

To analyze the coupling characteristics of the “Ecology–Humanities–Technology” system, this study calculates pairwise coupling coordination degrees (n = 3). The simplified formula for the coupling coordination degree is as follows:

$$C=\sqrt{\left[1-{\displaystyle \frac{\sqrt{{\left(U_3-U_1\right)}^2}+\sqrt{{\left(U_2-U_1\right)}^2}+\sqrt{{\left(U_3-U_2\right)}^2}}{3}}\right]\times \sqrt{{\displaystyle \frac{U_1}{U_3}}\times {\displaystyle \frac{U_2}{U_3}}}}$$

(9)

$$T={\alpha }_1{U}_1+{\alpha }_2{U}_2+{\alpha }_3{U}_3,{\alpha }_1+{\alpha }_2+{\alpha }_3=1$$

(10)

$$D=\sqrt{C\times T}$$

(11)

where C is the CD, α is the undetermined coefficient, T is the comprehensive development index, and D is the CCD.

Considering the data correlation patterns at the traditional village level and the current status of the Xinjiang Oasis traditional villages, this study draws on Zhao’s classification of coupling coordination types [46]. The specific classification types are detailed in

Table 3. Classification of the CCD.

Type of CCD	CCD Value Range	Type of CCD	CCD Value Range
Severe Imbalance	0.000–0.200	Basic Coordination	0.401–0.600
Moderate Imbalance	0.201–0.300	Moderate Coordination	0.600–0.800
Mild Imbalance	0.301–0.400	High Coordination	0.801–1.000

.

2.2.6. Z-Score Standardization and Pearson Correlation Analysis

To analyze the degree of association among the “Ecology–Humanities–Technology” systems, this study conducts a Pearson correlation analysis on the coupling results. The results are standardized using Z-score normalization to ensure comparability across different outcomes.

The formula for the Z-score standardization is as follows:

$$x^{*}={\displaystyle \frac{x-\overline{x}}{\sigma }}$$

(12)

where x is the original value of the coupling results, σ is the standard deviation of the original values, and x* is the standardized value.

The Pearson correlation coefficient is as follows:

$$r={\displaystyle \frac{{\displaystyle \sum _{i=1}^n\left(A_i-\overline{A}\right)}\left(B_i-\overline{B}\right)}{\sqrt{{\displaystyle \sum _{i=1}^n{\left(A_i-\overline{A}\right)}^2}}\sqrt{{\displaystyle \sum _{i=1}^n{\left(B_i-\overline{B}\right)}^2}}}}$$

(13)

where A and B represent different types of the CCD results and r is the correlation coefficient.

2.2.7. Geographic Detector

The geographic detector model is a spatial statistical method for detecting spatial heterogeneity and identifying its dominant driving factors [28]. In this study, the factor detector and interaction detector are employed to analyze the differentiation of the “Ecology–Humanities–Technology” coupling coordination degree. The results of the factor detector are expressed using the q-value [0, 1], where a higher q-value indicates the stronger explanatory power of the independent variable X on the dependent variable Y. The formula for calculating q is as follows:

$$q=1-{\displaystyle \frac{{\displaystyle {\sum }_{i=1}^L\left(N_i{{\sigma }_i}^2\right)}}{N{\sigma }^2}}$$

(14)

where N_i and N are the number of units in stratum i and the total number of units, respectively, and σ_i² and σ² are the variance of stratum i and the variance of all factors, respectively.

The interaction detector can identify the explanatory power of interactions between different independent variables on the dependent variable.

Table 4. Interaction type and Judgment basis.

Interaction Type	Judgment Basis
Reduction of nonlinearity	q(x1 ∩ x2) < min[q(x1), q(x2)]
Single factor nonlinear weakening	min[q(x1), q(x2)] < q(x1 ∩ x2) < max[q(x1), q(x2)]
Two-factor enhancement	q(x1 ∩ x2) > max[q(x1), q(x2)]
Enhancement of nonlinearity	q(x1 ∩ x2) > q(x1) + q(x2)
Mutual independence of factors	q(x1 ∩ x2) = q(x1) + q(x2)

Note: x₁ and x₂ represent the driving factors of the CCD; “∩” denotes the interaction between x₁ and x₂.

presents the interaction types between the factors and their judgment criteria.

3. Results

3.1. Comprehensive Evaluation Results

A comprehensive evaluation of the EHT (Ecology–Humanities–Technology) of 53 traditional villages in the Xinjiang Oasis was conducted. In terms of the EHT comprehensive scores, the traditional villages in eastern Xinjiang generally received higher scores, while those in Ili (northern Xinjiang) and Kashgar and Hotan (southern Xinjiang) also showed favorable results. Overall, the B1 layer (ecological dimension) scored the highest among the three EHT dimensions. This indicates that the oasis environment, which sustains the survival of Xinjiang’s traditional villages, has been prioritized during village development.

Within the B1 (Ecology) layer, the sample villages in Ili, Bortala, and Altay (northern Xinjiang) achieved particularly outstanding scores. Compared to eastern and southern Xinjiang, northern Xinjiang’s favorable macro-ecological environment provides more abundant ecological resources for the traditional villages. Interestingly, the ecological scores of some sample villages in Changji (northern Xinjiang) were significantly lower than those in Hami (eastern Xinjiang), Hotan, and Kashgar (southern Xinjiang). This is because the villages in Hami, Hotan, and Kashgar have effectively improved their micro-ecological environments through dense vegetation coverage, close integration of buildings with water–green spaces, and robust windbreak and sand fixation measures, thereby mitigating the adverse impacts of macro-ecological conditions. Thus, micro-scale settlement environments are critical for enhancing ecological suitability in the Xinjiang Oasis traditional villages.

For the B2 (Humanities) layer, the scores varied minimally across the villages. This result suggests that the humanities and historical resources of the Xinjiang Oasis traditional villages have followed a relatively consistent inheritance trajectory. It also reflects the resilience of ethnic cultures in maintaining the stable transmission of traditional humanities resources despite modern cultural influences.

In the B3 (Technology) layer, the villages in Hami and Turpan (eastern Xinjiang) and Aksu, Kashgar, and Hotan (southern Xinjiang) demonstrated higher levels of technological inheritance and conservation. These villages are often located on the edges of oases or within isolated small oases, where the demand for environmentally adaptive technologies is greater. Additionally, they have benefited earlier from tourism development, necessitating strong technological inheritance to sustain tourism attractiveness. By contrast, the villages in northern Xinjiang lag in technological inheritance and conservation, which correlates with their transition toward modern production and lifestyles (Figure 4).

3.2. CCD Measurement Results

3.2.1. EHT CCD Results

The EHT (Ecology–Humanities–Technology) CCD results are shown in Figure 5. Among the 53 Xinjiang Oasis traditional villages studied, 7 villages are in the basic coordination stage (>0.401), 38 in the mild imbalance stage (>0.301), and 8 in the moderate imbalance stage (>0.201). Regional differences are evident: the villages in eastern Xinjiang exhibit higher scores, all classified as either basic coordination or mild imbalance; the villages in southern Xinjiang span all three stages; while those in northern Xinjiang are limited to mild or moderate imbalance. Notably, some villages in southern and northern Xinjiang have CCD scores near the threshold of moderate imbalance, indicating a risk of further decline. These patterns highlight significant disparities in the CCD levels among the villages across eastern, northern, and southern Xinjiang.

However, the CCD levels also vary among villages within the same prefecture. Geographically, cluster protection benefits exhibit a strong correlation with higher CCD levels. Specifically, Lukqin Town in Shanshan County, Turpan (including TRP_3 to TRP_7), was selected as the only region in Xinjiang for the 2023 National Traditional Village Clustered Conservation and Utilization Demonstration Program. By fully leveraging its traditional village resources and assigning differentiated development positioning to each village, the county has established a foundation for regional synergy. This approach has prevented homogeneous reconstruction of villages sharing similar historical backgrounds, instead fostering complementary and coordinated functions across the cluster. Consequently, all seven sample villages under its jurisdiction achieved high CCD levels. Similarly, Changji’s 10 villages addressed limited development attractiveness caused by resource constraints through close regional linkages and extensive experience sharing in conservation practices, demonstrating how collaborative governance enhances the CCD outcomes.

The seven villages in the moderate imbalance stage exhibit consistently low scores in the technological dimension (B3). This reflects that excessive technological replacement is detrimental to the conservation and development of the traditional villages. Therefore, achieving an effective balance between traditional techniques and modern technologies is crucial for sustainable progress.

3.2.2. Pairwise CCD Results

The pairwise CCD results of “Ecology–Humanities–Technology” are shown in Figure 6. Among the three pairwise coupling relationships, Ecology–Technology (E-T) demonstrates the highest coordination, with 18.9% of the villages classified in the basic coordination stage. However, nine villages fell into the moderate imbalance stage due to technological practices exceeding ecological thresholds. By contrast, Ecology–Humanities (E-H) exhibits milder conflicts, with 84.9% of the villages in the mild imbalance stage; although the proportion of villages achieving basic coordination is low (5.7%), the minimal moderate imbalance rate suggests that contradictions remain unresolved but not yet acute. The weakest coordination is observed in Humanities–Technology (H-T), where 20.8% of the villages are in the moderate imbalance stage, reflecting a systemic disconnect between technological advancements and the needs of the humanities.

Geographically, similarities exist in the pairwise CCD results across different regions. For the traditional villages in eastern and southern Xinjiang (HM_1~TRP_9, AKS_1~HT_4), the E-H_CCD and H-T_CCD show high similarity, with the majority classified as mild imbalance or higher. This indicates that the rich cultural characteristics of these villages serve as a critical link between natural and artificial resources. By contrast, the villages in northern Xinjiang (IL_1~ALT_5) exhibit high similarity between the E-T_CCD and H-T_CCD, with some in the moderate imbalance stage. This reflects the low level of technological inheritance as a prominent barrier to the high-quality development of the traditional villages in northern Xinjiang.

3.2.3. Pearson Correlation of CCD Results

Table 5. Pearson Correlation.

Dimension	EHT_CCD	E-H_CCD	E-T_CCD	H-T_CCD
EHT_CCD	1	0.506 **	0.926 **	0.923 **
E-H_CCD	0.506 **	1	0.156	0.392 **
E-T_CCD	0.926 **	0.156	1	0.867 **
H-T_CCD	0.923 **	0.392 **	0.867 **	1

Note: ** indicates significant correlation at the 0.01 level (two-tailed).

presents the results of the Pearson correlations between the EHT CCD and the pairwise CCDs. The results indicate that all pairwise CCDs exhibit strong correlations with the EHT CCD at the 0.01 significance level. Additionally, the H-T_CCD shows strong correlations with both the E-H_CCD and the E-T_CCD (0.01 significance level). Compared to the comprehensive evaluation results, the Pearson correlation analysis reveals distinct directional insights into system relationships. Although the humanities and technology dimensions contribute less to the comprehensive scores than ecology, the coupling relationship between humanities and technology (H-T_CCD) acts as a crucial bridge in the functioning of the Xinjiang Oasis traditional villages. These results further underscore the significance of balanced system development across all dimensions.

3.3. Driving Factor Analysis

The persistence of the Xinjiang Oasis traditional villages has been influenced by numerous factors. This study investigates the driving factors of the “Ecology–Humanities–Technology” coupling coordination degree (CCD) from both internal and external perspectives. Internal driving factors reflect the influence of ecological, humanities, and technological indicators within the villages on the CCD, while external driving factors reflect the influence of the villages’ external social interactive dynamics on the CCD. This study employs the geographic detector model to perform factor detection and interaction detection on the driving factors.

3.3.1. Internal Driving Factors

(1)

Factor Detection Results

This study selects the C-layer indicators as internal driving factors to scientifically guide the optimization of the Xinjiang Oasis traditional villages. As shown in

Table 6. Factor Detection Results of Internal Driving Factors.

Dimension	Code	q-Value
Ecology	C1	0.217
	C2	0.137
	C3	0.157
Humanities	C4	0.213
	C5	0.139
	C6	0.021
Technology	C7	0.562
	C8	0.553
	C9	0.539

, the factor detection identifies production technology inheritance (C7, q = 0.562), architectural technology inheritance (C8, q = 0.553), hydraulic technology inheritance (C9, q = 0.539), terrain selection (C1, q = 0.217), and lifestyle coordination (C4, q = 0.213) as the primary internal driving factors.

Overall, technological inheritance is the most critical factor influencing system coupling in the Xinjiang Oasis traditional villages. This is because traditional technologies, deeply intertwined with local culture and livelihoods, have historically driven village formation and development. The results validate that indiscriminate replacement or insufficient protection of traditional technologies undermines the foundational stability of coordinated development.

Terrain selection (C1) and lifestyle coordination (C4) reflect the most fundamental ecological and humanities resources, respectively. These findings highlight the essential roles of “land” and “population” in shaping the oasis villages. Balancing these core attributes is crucial for establishing a sustainable foundation for conservation and utilization.

(2)

Interaction Detection Results

In the interaction detection results, nonlinear enhancement significantly outnumbers two-factor enhancement, with 32 groups and 13 groups identified, respectively.

Among the nonlinear enhancement interactions, the combination of terrain selection (C1) and hydraulic technology inheritance level (C9) achieves the highest joint explanatory power (q = 0.787), followed by ethnic–cultural atmosphere (C5) and hydraulic technology inheritance level (C9) (q = 0.774), and thirdly, by ethnic–cultural atmosphere (C5) with architectural technology inheritance level (C8) (q = 0.771).

For two-factor enhancement interactions, the highest explanatory power is observed in the combination of terrain selection (C1) and architectural technology inheritance level (C8) (q = 0.769), followed by lifestyle coordination (C4) with hydraulic technology inheritance level (C9) (q = 0.744), and thirdly, by production technology inheritance level (C7) with hydraulic technology inheritance level (C9) (q = 0.725) (Figure 7).

3.3.2. External Driving Factors

Based on the constructed “Ecology–Humanities–Technology” system coupling framework, this study argues that the external social system exerts a significant driving effect on the traditional villages in the Xinjiang Oasis. To further analyze the external driving factors of the Xinjiang Oasis traditional villages, this study selects indicators from five perspectives, including location conditions, transportation conditions, government policies, enterprise quantity, and online exposure level. Location conditions and transportation infrastructure establish material communication channels between villages and external systems, while government policies and enterprise participation reflect institutional and economic support. Online exposure level represents information connectivity with broader societies, collectively shaping the external driving forces that influence village conservation and utilization. These indicators reflect the driving effects of external social subjects, such as governments, enterprises, tourists, and media, as well as their resources, on village conservation and utilization (

Table 7. Selection and Factor Detection Results of External Driving Factors.

Dimension	Indicator	Code	q-Value
Location Conditions	Distance to Township	X1	0.028
	Distance to County Seat	X2	0.020
	Distance to City	X3	0.139
Transportation Conditions	Distance to Nearest National Highway	X4	0.109
	Distance to Nearest Expressway Interchange	X5	0.125
	Village Road Network Density	X6	0.453
Government Policies	Fiscal Funding Allocation	X7	0.317
	Number of Conservation and Development Projects	X8	0.393
Enterprise Quantity	Number of Limited Liability Companies	X9	0.164
	Number of Cooperatives	X10	0.147
	Number of Individually-owned Businesses	X11	0.211
Online Exposure	Baidu Index	X12	0.347

).

(1)

Factor Detection Results

In the factor detection results (Table 6), this study prioritizes village road network density (X6, q = 0.453), number of conservation and development projects (X8, q = 0.393), Baidu Index (X12, q = 0.347), fiscal funding allocation (X7, q = 0.317), and quantity of individually-owned businesses (X11, q = 0.211) as the primary external driving factors influencing the CCD.

Specifically, the proactive initiatives by the Xinjiang government, including open policies, fiscal funding, and village infrastructure development, have effectively promoted the coordinated development of ecology, humanities, and technology in the oasis traditional villages, laying a solid foundation for future conservation and utilization.

The significant effect of the Baidu Index (X12) underscores the critical role of enhancing online visibility in village conservation and utilization. In 2024, Xinjiang ranked second nationally in tourism popularity. Increasing the online exposure of the oasis traditional villages can attract more developmental opportunities. Furthermore, the findings indicate that an over-reliance on traditional agricultural practices hinders the coordinated development of the traditional villages in the Xinjiang Oasis. The targeted promotion of individually-owned businesses should be implemented to enhance the villages’ external communication capacities, thereby advancing their coordinated development.

(2)

Interaction Detection Results

In the interaction detection results, nonlinear enhancement significantly outnumbers two-factor enhancement, with 67 groups and 11 groups identified, respectively.

Among the nonlinear enhancement interactions, the combination of distance to city (X3) and village road network density (X6) achieves the highest explanatory power (q = 0.726), followed by fiscal funding allocation (X7) with Baidu Index (X12) (q = 0.713), and thirdly, by distance to nearest national highway (X4) with fiscal funding allocation (X7) (q = 0.690).

For two-factor enhancement interactions, the highest explanatory power is observed in village road network density (X6) with number of conservation and development projects (X8) (q = 0.703), followed by village road network density (X6) with fiscal funding allocation (X7) (q = 0.698), and thirdly, by number of conservation and development projects (X8) with Baidu Index (X12) (q = 0.691) (Figure 8).

4. Discussion and Policy Recommendations

4.1. Discussion

As representative traditional villages in arid and semi-arid regions, the Xinjiang Oasis traditional villages possess unique natural and socio-cultural resources distinct from other areas. Therefore, this study examines their conservation and utilization through the “Ecology–Humanities–Technology” system framework. Compared to the existing studies focusing on generalized systemic relationships [47] or isolated theoretical frameworks [38], this research constructs a technology dimension based on the agriculture and drought-adaptive characteristics of the Xinjiang Oasis villages, emphasizing the essential role of traditional technologies in conservation and development. Furthermore, considering the spatially fragmented and isolated ecological environments of the local villages, the ecological dimension is analyzed at both the macro and micro levels. By applying the coupling coordination degree (CCD) model, we precisely explore the relationships among “Ecology–Humanities–Technology” in the Xinjiang Oasis traditional villages. Finally, the geographic detector model is employed to analyze the internal and external driving factors, revealing their antagonistic and synergistic interactions.

To fully sort out and construct the systematic relationships among “Ecology–Humanities–Technology” in the traditional villages of the Xinjiang Oasis, this study draws on the social–ecological system framework and deepens the humanistic and technological systems based on the social characteristics of these villages. Combining system coupling theory, a theoretical framework for the coupling of “Ecology–Humanities–Technology” in the Xinjiang Oasis traditional villages is constructed. This framework not only expounds the intra-village system relationships among “ecology, humanities, and technology” but clarifies the interaction logic between external social systems and intra-village systems. Compared with the existing theoretical frameworks, such as the five major systems of human settlements science, human-land relationship theory, and the “social–economic–natural” composite ecological system, the “Ecology–Humanities–Technology” system coupling framework constructed in this study has the following characteristics: (1) focusing on the core subject of traditional villages—local residents—to construct corresponding humanistic and technological systems; (2) differentiating the system composition between internal and external village environments and clarifying their asymmetrical interaction relationships; (3) deepening the composition of the technological system to highlight the critical role of technology in traditional villages. These three points represent a specialization for the meso–micro scale research object of traditional villages, facilitating the optimization of the adaptability and problem-orientation of existing theoretical frameworks. Additionally, the “Ecology–Humanities–Technology” system coupling framework can be adapted to analyze other types of villages. On the one hand, the corresponding humanistic systems and the internal–external village system relationships can be constructed based on differences in the village subject status and governance systems; on the other hand, by focusing on region-specific technologies, content can be correspondingly replaced to achieve targeted optimization.

The comprehensive evaluation results of the case study show that ecological elements are an important component of the traditional villages in the Xinjiang Oasis. The villages in northern Xinjiang exhibit exceptionally high ecological scores, demonstrating the dominance of macro-ecological elements. However, the ecological scores of the villages in Changji (northern Xinjiang) are significantly lower than those in Kashgar and Hotan (southern Xinjiang), highlighting the critical role of micro-ecological environments in ecological sustainability [48]. This finding corroborates the ecological complexity of the traditional villages in the Xinjiang Oasis, demonstrating similar concepts to relevant research results in arid regions such as India and Egypt [49,50,51,52]. However, territorial disparities also indicate that, within the same macro-environment, the difficulties and focal points of micro-ecological construction vary across different regions, a dimension rarely addressed in the other studies.

In the EHT CCD results, the traditional villages in eastern Xinjiang exhibit the highest CCD scores, all classified as basic coordination or mild imbalance. The villages in southern Xinjiang encompass all three CCD types, while those in northern Xinjiang have the lowest scores, falling entirely within the mild imbalance or moderate imbalance stages. These findings underscore significant regional disparities in the CCDs across Xinjiang. Notably, the villages in eastern Xinjiang are distinguished by their high level of clustered protection and contiguous conservation. For example, Lukqin Town in Turpan was the only region in Xinjiang selected for the 2023 National Demonstration Program for Clustered Conservation and Utilization of Traditional Villages. Lukqin Town proactively excavated the historical and cultural resources of each village and established a regional protection system. By implementing cultural positioning, industrial specialization, and optimized public resource allocation across the villages, it enhanced the overall depth of historical–cultural heritage and industrial attractiveness. These efforts created a “regional upgrading–village development” virtuous cycle, providing a model for sustainable growth [53]. This phenomenon also reflects the dual nature of the Xinjiang Oasis traditional villages: relatively independent yet interconnected [54], offering theoretical support for identifying internal and external driving factors.

An integrated CCD analysis reveals that humanities constitute the core resource in the traditional villages of eastern and southern Xinjiang, while technological constraints emerge as a limiting factor in northern Xinjiang. Regarding tourism development, the villages in eastern and southern Xinjiang capitalize on their sociocultural attributes to facilitate ecological restoration and preservation of traditional technologies. By contrast, although northern Xinjiang has established a diversified tourism framework leveraging its ecological advantages, it has inadequately integrated traditional cultural and historical resources into tourism practices [55]. This mismatch has resulted in the technological inheritance failing to align with tourism demands. Consequently, the rigid “eco-tourism” model in northern Xinjiang’s traditional villages has restricted the diversified development of the tourism industry to some extent.

This study employs the geographic detector model to identify driving factors. Focusing on the traditional villages in the Xinjiang Oasis, this study proposes analyzing driving factors through endogenous resources and external social interaction capacities, establishing a dual-perspective framework for systematic investigation. This approach represents a marked departure from traditional single-perspective methodologies for detecting driving factors. By delineating driving boundaries, this study provides a robust foundation for constructing differentiated policy frameworks.

To address the current challenges, this study proposes a technology dimension deeply integrated with local ecology and humanities. This represents a marked departure from conventional studies that conflate technology and humanities within socio-cultural systems [56], emphasizing the unique importance of technology in the oasis villages. The evaluation results reveal significantly greater individual variation in the technological dimension compared to the humanities dimension, supporting our proposed framework. These variations starkly expose issues in the conservation and utilization of traditional technologies, such as the inconsistent preservation of hydraulic systems or architectural techniques. The results of internal driving factors indicate that the technology dimension is the primary driving factor. Through a comparative analysis of the comprehensive evaluation results, it is found that, although ecology constitutes an important component of the traditional villages in the Xinjiang Oasis, it does not occupy a core position. This is closely linked to China’s years of effort in desertification control and the implementation of the rural revitalization strategy, which have significantly reduced the ecological constraints on traditional village development. This demonstrates significant differences from other arid regions, though strategies for constructing basic agriculture [57,58,59] and social frameworks [60,61,62] under ecological contexts can still be referenced. Additionally, among pairwise coupling coordination degree results, the humanistic–technology CCD level is the lowest. This outcome reflects the social challenges inherent in technological utilization and conservation, a dilemma identified in rural development studies across numerous arid regions [63,64]. Therefore, it is necessary for academia to conduct more in-depth and systematic discussions in the future.

The findings of this study still have limitations. Due to constraints in the research area scale and sample selection, there is considerable room for optimization in the detailed analysis of spatial differences. Additionally, in the construction of indicators, the formulation of some indicators has not yet broken through the limitations of single-year characteristics. Therefore, it is hoped that this shortcoming can be addressed in future research to achieve the goal of analyzing stage characteristics.

4.2. Policy Recommendations

The findings of the comprehensive evaluation demonstrate the foundational role of ecology in traditional villages. The traditional villages in Xinjiang require enhanced water–green space systems. Existing studies have confirmed that water–green spaces in arid-region villages significantly regulate micro-climatic conditions [65,66,67], providing an effective approach to mitigate adverse macro-ecological environmental impacts.

The EHT CCD results indicate that the clustered protection of the traditional villages facilitates their high-quality development. Currently, the number of national level traditional villages in Xinjiang remains significantly lower than in other provinces. Most of these villages are scattered across the regions, with neighboring villages receiving insufficient policy attention. Therefore, local governments should proactively organize applications for national and provincial level traditional village designation to establish a foundation for building a clustered protection system [68]. The comprehensive evaluation results reveal inter-village disparities in ecological and technological dimensions, which contribute to variations in the CCD. To address this, the cross-village symbiotic network should be optimized during the clustered conservation process to enhance regional synergy. This can be achieved by connecting surrounding villages through ecological corridors, establishing joint management agencies to coordinate the functional allocation of water sources, green spaces, and other ecological resources, and fostering the inter-village exchange of traditional technologies.

The traditional villages in eastern Xinjiang and the Kashgar, Hotan, and Aksu regions of southern Xinjiang exhibit relatively high CCD levels, predominantly in the basic coordination stage or mild imbalance stage approaching basic coordination. These villages are characterized by high population density, rich cultural heritage, and substantial tourism revenue. Their profound cultural landscapes have become focal points for conservation and utilization. However, the homogenization of cultural tourism remains a significant challenge, with many villages failing to achieve innovative development [56]. Following the COVID-19 pandemic, the tourism industry in some traditional villages has been severely impacted. These regions should refine their cultural compensation mechanisms by directing tourism revenues toward the preservation of traditional crafts and ecological maintenance, thereby revitalizing cultural innovation capacity. Such measures will facilitate long-term strategic development of the tourism sector [69].

The traditional villages in the Kizilsu and Bayingolin regions of southern Xinjiang and northern Xinjiang exhibit relatively low CCD levels, predominantly in the mild imbalance or moderate imbalance stages. In recent years, these villages have experienced polarized development trajectories in agriculture and tourism, with some achieving rapid economic growth while others face stagnant productivity [70]. However, these villages have yet to balance the pace of industrial development with conservation efforts, leading to the compression of traditional rural landscape spaces [71]. Therefore, governments must strictly monitor the industrial growth rates in these villages and optimize future land-use planning and public resource allocation. Local authorities should further advance the integration of traditional and modern technologies. Specifically, the convenience and efficiency of modern technologies should be harmonized with the historical and cultural values of traditional practices to promote their adaptive evolution. Additionally, village spatial planning should adopt a “conservation–utilization” gradient based on the villagers’ preferences, the disparities in industrial development levels, and the distribution of traditional technological resources [72]. These proactive policies will enhance the villagers’ initiative in coordinating industrial development with technological preservation.

Currently, most traditional villages in the Xinjiang Oasis still require government-led initiatives to stimulate productive and livelihood vitality. The detection of external driving factors reveals that infrastructure development remains a critical component in advancing conservation and development efforts [40]. Governments should strengthen support for villages with underdeveloped local industries and implement proactive industrial development policies. Such initiatives will help unlock the developmental potential and promote the villagers’ engagement in local sideline industries [47]. Furthermore, traditional villages should leverage internet-driven opportunities to establish a robust online presence at county, township, and village levels, thereby enhancing digital visibility. These measures will stimulate employment opportunities and provide greater potential for the sustainable conservation and development of the traditional villages.

5. Conclusions

This study takes the traditional villages in the Xinjiang Oasis as the research object, integrates the social–ecological system framework and system coupling theory, derives the relationships among various system components of the Xinjiang Oasis traditional villages, constructs an “Ecology–Humanities–Technology” system coupling framework, and explores theoretical paths to optimize the conservation and development of these villages. This study effectively reveals the coupling coordination relationships among “Ecology–Humanities–Technology” (EHT) in the traditional villages of the Xinjiang Oasis through the coupling coordination degree (CCD) model. The findings indicate that 71.7% of the Xinjiang Oasis traditional villages are in a mild imbalance stage, while 13.2% and 15.1% are classified as basic coordination and moderate imbalance stages, respectively. Geographically, eastern Xinjiang exhibits the highest CCD levels, followed by southern Xinjiang, with northern Xinjiang ranking the lowest. The coordination between Ecology–Technology (E-T) is optimal, followed by Ecology–Humanities (E-H) coordination, while Humanities–Technology (H-T) coordination is the weakest. The ecological and social attributes of technological inheritance in the Xinjiang Oasis traditional villages exhibit distinct differences. When combining the comprehensive evaluation results, paired coupling coordination degree (CCD) outcomes, and Pearson correlation results, the differential impacts of ecology, humanities, and technology on the conservation and development of the Xinjiang Oasis traditional villages become evident. Although ecology serves as a critical component of these villages, it does not play a decisive role in their conservation and development. The impacts of humanities and technology on the traditional villages vary distinctly across eastern, southern, and northern Xinjiang. Overall, scientific conservation and utilization of the Xinjiang Oasis traditional villages require further enhancement.

By employing the geographic detector model, this study identifies the driving factors affecting the CCD from both internal and external perspectives. The factor detection results demonstrate that terrain selection (ecological dimension), lifestyle coordination (humanities dimension), and technology dimension are the primary internal driving factors. Key external driving factors include village road network density, number of conservation and development projects, Baidu Index, fiscal funding allocations, and quantity of individually-owned businesses. The interaction detection further elucidates the synergistic effects among these dominant drivers. In the interaction detection results of internal and external driving factors, the number of groups showing non-linear enhancement is larger than those with two-factor enhancement. This result demonstrates that the protection and development path of traditional villages requires synergistic gain from all systems.

This research provides a transferable methodology for evaluating the coordination levels of traditional village conservation and utilization in arid and semi-arid regions, exemplified by Xinjiang. The proposed framework offers actionable insights for governmental management and village construction, facilitating efficient and sustainable conservation and utilization of local traditional villages.