An Evaluation of the Implementation Effect and Enhancement Countermeasures of Rural Living Environment Improvements: Taking Environmental Demonstration Villages in Shaanxi Province as an Example

Abstract

Improving the living environment in rural areas is an important task and a key breakthrough point in implementing the rural revitalization strategy. It not only directly affects the vital interests and health protection of farmers, but is also an important measure to promote ecological civilization construction and achieve the development goal of a beautiful China. Taking environmental demonstration villages in Shaanxi Province as the research object, questionnaire data were obtained through field research and face-to-face interviews. This study constructs an evaluation index system covering five dimensions: village appearance, domestic sewage treatment, rural toilet renovation, domestic waste treatment, and construction and management mechanism. The entropy method is used to determine indicator weights, and fuzzy comprehensive evaluation is applied to measure the implementation effect. The research results indicate that the overall effect is between “average” and “good” (score 3.924), with domestic sewage treatment scoring highest and construction and management mechanism lowest. The study identifies key problems such as low farmer participation, insufficient funding sources, inadequate infrastructure maintenance, and weak environmental awareness. Based on these findings, countermeasures are proposed: enhancing farmers’ environmental awareness and participation; diversifying capital investment; improving infrastructure and establishing long-term management mechanisms; cultivating social capital; and strengthening the leading role of the government. This study provides empirical evidence and policy recommendations for improving rural environmental governance.

1. Introduction

Rural ecological civilization construction, as a key area and core aspect of China’s ecological civilization construction, is related to the overall process of the country’s ecological civilization construction. Improving the rural living environment is not only an inevitable requirement for ecological civilization construction but also an important approach to promoting rural development. It not only concerns the improvement in farmers’ quality of life but also relates to the construction of beautiful, livable, and prosperous villages. In the context of the implementation of the rural revitalization strategy in the new era, although the rural living environment has achieved remarkable results in contributing to the construction of ecological and livable villages, it still faces a series of challenges.

With the acceleration of China’s economic and social development and urbanization process, changes in the rural population structure have exacerbated problems such as the living environment, infrastructure, and public services. To address the long-standing challenges in rural areas, such as disorderly planning, drinking water safety, and environmental sanitation, the focus of national governance has gradually shifted to rural areas. The Three-Year Action Plan for improving the rural living environment in 2018 marked a new stage of standardization in rural environmental governance and systematically deployed special governance projects. The 2021 Five-Year Action Plan for Improving the Rural Living Environment (2021–2025), as a continuation and upgrade of the policy, emphasizes the establishment of a long-term mechanism to promote the transformation of governance towards regularity and refinement. Subsequent reports of the 20th National Congress of the Communist Party of China and the No. 1 Central Document for 2023–2025 continue to focus on and deepen rural ecological environment governance, highlighting its core position in the rural revitalization strategy.

In response to the national deployment, Shaanxi Province has successively implemented three-year and five-year action plans, established a rectification system focusing on garbage management, toilet revolution, sewage treatment, and village appearance improvement, and explored a mechanism of “government-led, village-participated, multi-party collaboration”, emphasizing the creation of characteristic models in combination with regional differences in Guanzhong, northern Shaanxi, and southern Shaanxi. Although significant achievements have been made, such as the transformation of several villages from “ecological poverty alleviation” to “ecological revitalization” and the upgrading of “clean village appearance” to “ecological livability”, there are still challenges such as insufficient funds, unsustainable effects, weak environmental awareness, and imperfect management mechanisms.

Despite the proliferation of policies and programs, systematic evaluations of their implementation effects at the micro level remain scarce. Existing studies often rely on macro-level statistics or focus on single dimensions (e.g., waste management or toilet renovation), lacking an integrated framework that captures both objective outcomes and farmers’ perceptions. Moreover, the role of institutional mechanisms (e.g., farmer participation, long-term maintenance) in sustaining improvements has been underexplored. Therefore, this study aims to answer the following research questions: (1) What is the overall implementation effect of rural living environment improvement in demonstration villages? (2) Which dimensions perform well and which lag behind? (3) What factors contribute to the observed disparities?

This study contributes to the literature in three ways. First, it develops an integrated evaluation framework combining entropy weighting and fuzzy comprehensive evaluation, which captures both objective weights and subjective perceptions, overcoming the limitations of single-method approaches. Second, it incorporates “construction and management mechanism” as a core dimension, reflecting the importance of institutional factors in sustaining environmental improvements. Third, based on first-hand survey data from 359 households in 10 demonstration villages, it provides micro-level evidence on the heterogeneous effects across different dimensions, offering insights for targeted policy interventions.

2. Literature Review and Theoretical Framework

2.1. Theoretical Foundations: Human Settlements Theory and Social–Ecological Systems

The concept of human settlements, originating from the work of Doxiadis [1], emphasizes the interdependence between human communities and their built and natural environments. In the rural context, human settlements encompass not only physical infrastructure (housing, roads, water supply) but also social, economic, and institutional dimensions [2]. More recently, the social–ecological systems (SES) framework [3] has been applied to understand the dynamic interactions between human actions and environmental outcomes in rural areas. This framework highlights the role of governance systems, resource users, and institutional arrangements in shaping the sustainability of environmental interventions [4].

In this study, we integrate human settlements theory with the SES framework to conceptualize rural living environment improvement as a multi-dimensional process involving physical infrastructure (village appearance, sewage treatment, waste management), behavioral change (toilet renovation, waste sorting), and institutional mechanisms (farmer participation, policy implementation, long-term maintenance). The five dimensions in our evaluation index system correspond to these components, enabling a comprehensive assessment.

2.2. International Experiences in Rural Environmental Governance

Internationally, rural environmental governance has been studied from various perspectives, including participatory development [5], community-based natural resource management [6], and sustainable rural livelihoods [7]. Studies in Europe and North America emphasize the importance of multi-stakeholder partnerships, local knowledge, and adaptive management in achieving lasting environmental improvements [8,9]. In developing countries, research highlights challenges such as limited financial resources, weak institutional capacity, and low community engagement [10,11]. These insights inform our interpretation of findings and the formulation of policy recommendations.

2.3. Evaluation Methods for Rural Environmental Interventions

Various methods have been employed to evaluate rural environmental interventions, including cost–benefit analysis [12], multi-criteria decision making [13], structural equation modeling [14], and participatory approaches [15]. Fuzzy comprehensive evaluation has gained popularity in Chinese studies due to its ability to handle uncertainty and subjective judgments [16,17]. However, its application often lacks transparency in weight determination and membership function construction. This study addresses these gaps by combining entropy weighting (objective) with fuzzy evaluation (subjective) and explicitly documenting the calculation process.

3. Research Methods

3.1. Construction of Evaluation Index System

3.1.1. Selection of Indicators

Based on the theoretical framework and a systematic review of policy documents and academic literature, an evaluation index system was constructed covering five dimensions: village appearance (B1), domestic sewage treatment (B2), rural toilet renovation (B3), domestic waste management (B4), and construction and management mechanism (B5). The selection process followed the principles of comprehensiveness, representativeness, and data availability.

For each dimension, secondary indicators were selected through literature research. For village appearance, indicators include road leveling (C1), village greening (C2), public lighting facilities (C3), and housing conditions (C4), drawing from studies on rural infrastructure and esthetics [18,19]. For domestic sewage treatment, indicators are sewage discharge method (C5), construction of treatment facilities (C6), and treatment of black and odorous water bodies (C7), based on guidelines from the Ministry of Ecology and Environment [20,21]. For rural toilet renovation, indicators include sanitary toilet renovation (C8), satisfaction with renovation (C9), and toilet sewage treatment method (C10), reflecting the “toilet revolution” policy [22,23]. For domestic waste management, indicators are waste classification (C11), collection frequency (C12), and disposal method (C13), aligned with national waste management targets [24,25]. For construction and management mechanism, indicators include farmer recognition (C14), farmer participation (C15), environmental improvement publicity (C16), and environmental management and maintenance (C17), capturing institutional and participatory dimensions [26,27].

3.1.2. Meaning of Indicators

Each indicator was clearly defined to ensure consistent interpretation. For example, “road leveling” refers to the smoothness and quality of village roads, measured on a five-point scale from “very poor” to “very good”. “Farmer participation” measures the frequency and intensity of villagers’ involvement in environmental improvement activities. Detailed definitions are provided in the questionnaire (Supplementary Materials S1).

3.2. Questionnaire Design and Data Collection

3.2.1. Questionnaire Design

A structured questionnaire was designed consisting of three parts. Part I collected demographic information (gender, age, education, occupation). Part II contained 17 items corresponding to the evaluation indicators, each rated on a five-point Likert scale (1 = very poor, 5 = very good). Part III investigated factors influencing the implementation effect (e.g., environmental awareness, infrastructure, economic level, social capital, grassroots work efficiency), also using a five-point Likert scale. The five-point scale was chosen because it provides sufficient granularity for respondents to express gradations of perception while remaining easy to understand, and it is widely used in satisfaction and perception studies [28,29].

3.2.2. Data Collection

Field research was conducted in July–August 2024 in 10 environmental demonstration villages in Shaanxi Province, selected from the national list published in 2017. Face-to-face household interviews were conducted with household heads. A total of 363 questionnaires were distributed, and 359 valid questionnaires were obtained (effective rate 98.89%). In addition, semi-structured interviews were conducted with village cadres and two knowledgeable villagers per village to gain deeper insights (Supplementary Materials S2 and S3).

3.2.3. Reliability and Validity Tests

To assess the reliability of the questionnaire, Cronbach’s alpha was computed for each dimension and the overall scale. The overall alpha was 0.86, exceeding the recommended threshold of 0.7, indicating high internal consistency [30]. The Kaiser–Meyer–Olkin (KMO) measure of sampling adequacy was 0.79, and Bartlett’s test of sphericity was significant (p < 0.001), confirming the suitability of the data for factor analysis [31].

3.3. Evaluation Methods

3.3.1. Determination of Indicator Weights: Entropy Method

The entropy method was used to determine objective weights for the indicators. This method avoids subjective bias by measuring the dispersion of each indicator. The steps are as follows:

(1)

Build the evaluation matrix:

$$\mathrm{W}={\left({\mathrm{W}}_{\mathrm{i}\mathrm{j}}\right)}_{\mathrm{m}\times \mathrm{n}}\left(0\le \mathrm{i}\le \mathrm{m},0\le \mathrm{j}\le \mathrm{n}\right)$$

(1)

In the formula, i is the index value of the JTH indicator in the i-th evaluation unit to be evaluated, m is the number of evaluation units to be evaluated, and n is the number of evaluation indicators.

Second, define the standardization matrix based on the range standardization method:

$${\mathrm{Z}}_{\mathrm{i}\mathrm{j}}=\left\{\begin{array}{c}{(\mathrm{W}}_{\mathrm{i}\mathrm{j}}-{\mathrm{W}}_{\mathrm{j}\mathrm{m}\mathrm{i}\mathrm{n}})∕{(\mathrm{W}}_{\mathrm{j}\mathrm{m}\mathrm{a}\mathrm{x}}-{\mathrm{W}}_{\mathrm{j}\mathrm{m}\mathrm{i}\mathrm{n}})\mathrm{K}\\ ({\mathrm{W}}_{\mathrm{j}\mathrm{m}\mathrm{a}\mathrm{x}}-{\mathrm{W}}_{\mathrm{i}\mathrm{j}})/{(\mathrm{W}}_{\mathrm{j}\mathrm{m}\mathrm{a}\mathrm{x}}-{\mathrm{W}}_{\mathrm{j}\mathrm{m}\mathrm{i}\mathrm{n}})\mathrm{K}\end{array}\right\}$$

(2)

The formula shows the range standardized value (0≤≤1) of the sample i indicator, and represents the maximum and minimum values of the indicator item, respectively.

(2)

Calculation of indicator weights

First, the calculation of indicator entropy, the calculation of the indicator value of item i under item j:

$${\mathrm{P}}_{\mathrm{i}\mathrm{j}}={\mathcal{X}}_{\mathrm{i}\mathrm{j}}/\sum _{\mathrm{i}=1}^{\mathrm{m}}{\mathcal{X}}_{\mathrm{i}\mathrm{j}}$$

(3)

Second, calculate the entropy of the JTH indicator:

$${\mathrm{e}}_{\mathrm{j}}=-\mathrm{k}\sum _{\mathrm{i}=1}^{\mathrm{m}}({\mathrm{p}}_{\mathrm{i}\mathrm{j}}\ln {\mathrm{p}}_{\mathrm{i}\mathrm{j}}),\mathrm{k}=1∕\ln \mathrm{m}$$

(4)

Third, calculate the difference coefficient of the evaluation indicator j:

$${\mathrm{g}}_{\mathrm{j}}=1-{\mathrm{e}}_{\mathrm{j}}$$

(5)

Fourth, calculate the weights of the evaluation index j:

$${\mathrm{W}}_{\mathrm{j}}=\mathrm{g}/\sum _{\mathrm{j}=1}^{\mathrm{n}}{\mathrm{g}}_{\mathrm{j}}$$

(6)

The resulting weights are presented in

Table 1. Living environment improvement implementation effect evaluation index system.

Target Layer	First-Level Indicators	Secondary Indicators
Evaluation of the implementation effect of rural human settlement improvement A	Village appearance B1	Road leveling condition C1
		Greenery in the village C2
		Public lighting facilities C3
		Residential housing situation C4
	Domestic sewage treatment B2	Domestic sewage discharge method C5
		Construction of sewage treatment facilities C6
		Treatment of black and odorous water bodies C7
	rural toilet renovation B3	Sanitary toilet renovation situation C8
		Toilet renovation satisfaction C9
		Toilet sewage treatment C10
	Domestic waste management B4	Household waste classification C11
		Frequency of domestic waste collection C12
	Construction management mechanism B5	Domestic waste disposal method C13 Farmer acceptance C14
		Farmer engagement C15
		Environmental improvement publicity C16
		Environmental management and maintenance C17

.

3.3.2. Fuzzy Comprehensive Evaluation

Fuzzy comprehensive evaluation was chosen because it can handle the vagueness and subjectivity inherent in perceptual assessments, and it is well-suited for multi-criteria decision problems where criteria are qualitative [32]. Compared to alternative methods such as structural equation modeling (which requires large samples and assumes linear relationships) or principal component analysis (which reduces dimensions but may lose interpretability), fuzzy evaluation allows for intuitive interpretation of membership degrees across rating levels [33].

• Step 1: Establish factor sets and evaluation sets

The factor set is hierarchical: first level (target A), second level (five dimensions B1–B5), third level (17 indicators C1–C17). The evaluation set V = {very poor, poor, average, good, very good} with corresponding scores 1–5.

Establish a set of comments and divide them into five grades, namely V = (V1, V2, V3, V4, V5) = (very poor, poor, average, good, very good), and assign 1, 2, 3, 4, 5 points respectively (

Table 2. Evaluation grade table of rural living environment improvement.

Grade	Very Bad	Poor	General	Better	Very Good
Score	1	2	3	4	5

), and recover the corresponding data.

• Step 2: Construct membership matrices

The core idea of constructing the membership matrix is to calculate the membership degree of each indicator for evaluating the implementation effect of rural human settlement improvement based on the data from the field research and questionnaire survey mentioned above. For each evaluation index Ui, calculate the membership degree Rij of each index Ui to the evaluation level Vj to form the single-factor evaluation vector Ri = [Ri1, Ri2, Ri3, …, Rim] (i = 1,2, … n). Arranging n single-factor evaluation vectors in order constitutes the fuzzy relation matrix R of the system.

$$\begin{gathered} R_1=\left[\begin{array}{c}\mathrm{0.172,0.689,0.077,0.038,0.024}\\ \mathrm{0.297,0.555,0.096,0.019,0.033}\\ \mathrm{0.258,0.483,0.125,0.129,0.005}\\ \mathrm{0.125,0.612,0.168,0.086,0.009}\end{array}\right] \\ {R}_2=\left[\begin{array}{c}\mathrm{0.660,0.254,0.072,0.009,0.005}\\ \mathrm{0.339,0.388,0.225,0.024,0.024}\\ \mathrm{0.421,0.402,0.125,0.033,0.019}\end{array}\right] \\ {R}_3=\left[\begin{array}{c}\mathrm{0.383,0.349,0.187,0.076,0.005}\\ \mathrm{0.191,0.613,0.148,0.043,0.005}\\ \mathrm{0.622,0.245,0.115,0.009,0.009}\end{array}\right] \\ {R}_4=\left[\begin{array}{c}\mathrm{0.158,0.363,0.134,0.158,0.187}\\ \mathrm{0.225,0.689,0.081,0.005,0}\\ \mathrm{0.669,0.273,0.053,0},0.005\end{array}\right] \\ {R}_5=\left[\begin{array}{c}\mathrm{0.177,0.656,0.134,0.024,0.009}\\ \mathrm{0.086,0.344,0.163,0.187,0.220}\\ \mathrm{0.273,0.278,0.191,0.143,0.115}\\ \mathrm{0.239,0.627,0.096,0.014,0.024}\end{array}\right] \end{gathered}$$

(7)

• Step 3: Perform fuzzy composition

First, calculate the weight vectors of each level of indicators. According to the steps for calculating the weights of the indicators mentioned above, standardize the weights of the indicators under each evaluation criterion, and finally obtain the normalized weight vectors of the six evaluation dimensions. The specific results are as follows.

$$\begin{gathered} \mathrm{W}=\left[\mathrm{0.2068,0.2063,0.191,0.1625,0.2334}\right] \\ {\mathrm{W}}_1=\left[\mathrm{0.208,0.289,0.305,0.198}\right] \\ {\mathrm{W}}_2=\left[\mathrm{0.321,0.328,0.351}\right] \\ {\mathrm{W}}_3=\left[\mathrm{0.386,0.216,0.398}\right] \\ {\mathrm{W}}_4=\left[\mathrm{0.467,0.183,0.350}\right] \\ {\mathrm{W}}_5=\left[\mathrm{0.159,0.260,0.379,0.202}\right] \end{gathered}$$

Next, calculate the fuzzy comprehensive evaluation of the secondary indicators. Based on the operation rules of fuzzy comprehensive evaluation, the results are used as input variables to construct the fuzzy relation matrix of the second-level fuzzy comprehensive evaluation.

$$\begin{gathered} {\mathrm{B}}_1={\mathrm{W}}_1·{\mathrm{R}}_1=\left[\mathrm{0.225,0.572,0.115,0.070,0.018}\right] \\ {\mathrm{B}}_2={\mathrm{W}}_2·{\mathrm{R}}_2=\left[\mathrm{0.471,0.350,0.141,0.022,0.016}\right] \\ {\mathrm{B}}_3={\mathrm{W}}_3·{\mathrm{R}}_3=\left[\mathrm{0.437,0.365,0.150,0.042,0.006}\right] \\ {\mathrm{B}}_4={\mathrm{W}}_4·{\mathrm{R}}_4=\left[\mathrm{0.349,0.391,0.096,0.075,0.089}\right] \\ {\mathrm{B}}_5={\mathrm{W}}_5·{\mathrm{R}}_5=\left[\mathrm{0.202,0.426,0.156,0.109,0.107}\right] \end{gathered}$$

Finally, calculate the membership degree of the fuzzy comprehensive evaluation.

$$\begin{gathered} \mathrm{B}=\mathrm{W}·\mathrm{R}=\left[\mathrm{0.2068,0.2063,0.191,0.1625,0.2334}\right]· \\ \left[\begin{array}{c}\mathrm{0.225,0.572,0.115,0.070,0.018}\\ \mathrm{0.471,0.350,0.141,0.022,0.016}\\ \mathrm{0.437,0.365,0.150,0.042,0.006}\\ \mathrm{0.349,0.391,0.096,0.075,0.089}\\ \mathrm{0.202,0.426,0.156,0.109,0.107}\end{array}\right]=\left[\mathrm{0.331,0.423,0.133,0.065,0.048}\right] \end{gathered}$$

• Step 4: Calculate comprehensive scores

Based on the above calculation steps, convert according to the five-point system and the weighted average algorithm to obtain the final comprehensive evaluation score.

4. Data Sources and Processing

4.1. Data Sources

According to the “Notice on the Publication of the List of Model Villages for Improving the Rural Living Environment in 2017” jointly issued by five ministries, including the Ministry of Housing and Urban-Rural Development in 2017, through a strict selection process, 295 model villages for comprehensive improvement of the rural living environment with typical demonstration significance were finally selected from across the country. Among them, 10 administrative villages in Shaanxi Province were selected for the demonstration list. This study constructed an evaluation system and designed questionnaires. Field research was conducted in Shaanxi Province’s model villages from July to August 2024 using face-to-face household interviews with household heads as the main interviewees to obtain first-hand detailed information. A total of 363 questionnaires were distributed, and 359 valid questionnaires were obtained, with a questionnaire validity rate of 98.89%. Through field research on the improvement of the rural living environment in environmental demonstration villages in Shaanxi Province, the main basis for the comprehensive evaluation of the implementation effect and influencing factors of the village living environment improvement was obtained.

4.2. Data Processing

4.2.1. Research Design

(1)

Questionnaire Design

This paper designs a questionnaire on the implementation effect of human settlements improvement in environmental demonstration villages in Shaanxi Province (Supplementary Materials S1), which consists of three parts. The first part focused on collecting demographic data of the respondents, including gender, age, educational attainment and occupation. The second part mainly focuses on the evaluation of the implementation effect of rural living environment improvement, covering five aspects: village appearance, domestic sewage treatment, rural toilet renovation, domestic waste management, and construction and management mechanism. The third part mainly investigates the factors that affect the evaluation of the implementation effect of the improvement of the living environment in villages, including five aspects: farmers’ environmental awareness, village infrastructure, village economic level, village social capital and the efficiency of grassroots work. Both the second and third parts use the internationally recognized five-level Likert scale as the standardized measurement tool, and are ranked from low to high in the order of 1 to 5.

(2)

Interview Design

The purpose of the questionnaire survey is to evaluate the implementation effect of human settlement improvement in environmental demonstration villages in Shaanxi Province and to explore its influencing factors. In view of the actual situations, such as differences in villagers’ educational levels and physical conditions that may be encountered during the survey process, communication difficulties or inaccurate expressions may occur, resulting in the survey members being unable to fully understand the specific cognitive level of villagers regarding human settlement improvement. Therefore, in order to gain a more comprehensive understanding of the improvement of the living environment in the environmental demonstration villages of Shaanxi Province, this paper first obtained the basic situation of the village through the investigation of prefectural-level cadres and village committees. Secondly, structured interviews were used as an auxiliary means to conduct face-to-face interviews with villagers who had a deep understanding of the improvement of the living environment in the village, and in-depth interviews were conducted with two villagers in each village. Detailed interview outlines and in-depth interviews can be found in Supplementary Materials S2 and S3.

4.2.2. Descriptive Statistics

The questionnaire first collected basic information from the respondents, and the statistics are shown in

Table 3. Sample basic information statistics.

Variables	Options	Sample Size	Proportion (%)
Gender	Male	187	52.1
	Female	172	47.9
Age	18–25 years old	48	13.4
	26–35 years old	58	16.1
	36–45 years old	55	15.3
	46–60 years old	90	25.1
	Over 60	108	30.1
Educational attainment	Primary school and below	116	32.3
	Junior high school	125	34.8
	High school/technical secondary school	52	14.5
	Junior college	36	10.0
	Bachelor’s degree and above	30	8.4
Occupation	Farm at home	137	38.2
	Farm and work	60	16.7
	Go out to work	35	9.7
	Others	127	35.4

. Among the 359 respondents, 187 were male, accounting for 52.1%, and 172 were female, accounting for 47.9%, indicating a relatively balanced number of male and female respondents. In terms of age groups, the largest number of respondents were over 60 years old, accounting for 30.1% of the total sample, followed by the 46–60 age group. This is in line with the current situation in villages where the elderly are in the majority and the young are mostly working outside. The educational attainment of the respondents showed a clear concentration trend, mainly distributed in primary school and below and junior high school, accounting for 32.3% and 34.8% respectively. The largest number of respondents, 38.2% of the total sample, were those who had been farming at home all year round. They were participants involved in the improvement of rural living environments and were able to experience the changes brought about by the implementation of the rural living environment improvement system and were therefore able to make an accurate evaluation of the implementation effects.

Based on the descriptive statistics of the questionnaire survey data (as shown in

Table 4. Descriptive statistics for each item.

	Item	Minimum Value	Maximum	Average	Standard Deviation	Variance
	Road surface condition	1	5	2.05	0.786	0.617
	Greenery in the village	1	5	1.94	0.878	0.770
	Public lighting facilities	1	5	2.14	0.963	0.928
	Housing conditions	1	5	2.24	0.816	0.666
	Domestic sewage treatment situation	1	5	1.44	0.713	0.508
	Construction of sewage treatment facilities	1	5	2.00	0.938	0.880
	Treatment of black and odorous water bodies	1	5	1.83	0.909	0.826
	Renovation of sanitary toilets	1	5	1.97	0.960	0.922
	Satisfaction with toilet renovation	1	5	2.06	0.745	0.554
	Toilet sewage treatment	1	5	1.54	0.808	0.653
	Household waste sorting	1	5	2.85	1.374	1.887
Frequency of domestic waste collection		1	5	1.87	0.556	0.309
Garbage disposal methods		1	5	1.40	0.636	0.404
Satisfaction with environmental remediation		1	5	2.03	0.703	0.494
Environmental participation		1	5	3.11	1.324	1.752
Environmental improvement publicity		1	5	2.55	1.333	1.778
Environmental improvement management and maintenance		1	5	1.96	0.780	0.609

), this study used statistics such as extreme values, central tendency, and degree of dispersion to conduct a comprehensive analysis of sample characteristics. The data showed that the scores for the 17 measurement items designed in the questionnaire ranged from 1 to 5 points. By calculating the arithmetic mean of the scores of each item, it was found that the mean distribution range of the evaluation results was 1.40–3.11, with the highest mean being “participation in environmental remediation” and the lowest mean being “methods of domestic waste treatment”. At the same time, the standard deviation of the evaluation for each item ranged from 0.556 to 1.374, and the item with the largest standard deviation was “domestic waste classification”, reflecting significant differences in the evaluation of the respondents on this issue. The item with the smallest standard deviation was “frequency of domestic waste collection”, indicating that respondents’ opinions were most concentrated in this dimension.

5. Results of the Implementation Effect of Rural Living Environment Improvement

Based on the calculation steps in Section 3.3.1 and Section 3.3.2, the score table for each index layer of the implementation effect of rural human settlement improvement was obtained (

Table 5. Evaluation and value of the implementation effect of the rural living environment improvement system.

Combi-Ned Score	Target Layer	First-Level Indicators	First-Level Indicator Weights	First-Level Indicator Score	Secondary Indicators	Secondary Indicator Weights	Secondary Index Mark Score
3.924	Evaluation of the implementation effect of rural human settlements improvement A	Village appearance B1	0.2068	3.916	Road leveling condition C1	3.924	Evaluation of the implementation effect of rural human settlements improvement A
					Greenery in the village C2	0.0597	4.064
					Public lighting facilities C3	0.0632	3.86
					Residential housing situation C4	0.0409	3.604
		Domestic sewage treatment B2	0.2063	4.238	Domestic sewage discharge method C5	0.0662	4.555
					Conditions of sewage treatment facilities C6	0.0676	3.994
					Treatment of black and odorous water bodies C7	0.0725	4.173
		Rural Toilet Renovation B3	0.191	4.185	Sanitary toilet renovation situation C8	0.0737	4.029
					Toilet renovation satisfaction C9	0.0412	3.942
					Toilet sewage treatment C10	0.0761	4.462
		Domestic waste management B4	0.1625	3.836	Household waste classification C11	0.0759	3.147
					Frequency of domestic waste collection C12	0.0297	4.134
					Domestic waste disposal method C13	0.0569	4.601
		Construction and management mechanism B5	0.2334	3.507	Farmer recognition C14
					Farmer engagement C15
					Environmental improvement publicity C16

). It can be seen from Table 5 that the comprehensive evaluation score of the implementation effect of rural human settlement improvement is 3.924, which falls between average and good, indicating that the human settlements of environmental demonstration villages in Shaanxi Province have achieved good results after several years of improvement. The effect evaluation values of village appearance, domestic sewage treatment, rural toilet renovation, domestic waste management and construction management mechanism among the first-level indicators were 3.916, 4.238, 4.185, 3.836 and 3.507 respectively, but village appearance, domestic waste management and construction management mechanism were all below the comprehensive evaluation value. Among the 17 secondary indicators, 12 were rated above the comprehensive evaluation, while the five aspects of public lighting facilities, housing conditions, domestic waste classification, farmers’ participation, and environmental improvement publicity were rated below the comprehensive evaluation, indicating that the environmental improvement work in the environmental demonstration villages of Shaanxi Province has achieved phased results, but there are still some deficiencies. There is still much room for improvement in the future.

5.1. Village Appearance

From the perspective of village appearance, the evaluation value of its improvement implementation effect is 3.916, which is lower than the comprehensive evaluation value. Among its secondary indicators, road leveling, village greening, public lighting facilities, and residential housing were rated at 3.947, 4.064, 3.86, and 3.604 respectively. According to the survey results, the roads in the surveyed villages are mainly paved with cement, and 86.1% of the villagers think that the roads in the villages are relatively smooth and there is no damage. New plants such as roses have been planted on both sides of the main roads in the village. Additionally, 85.1% of the villagers think the village has a high green coverage rate and the greening improvement effect on the main roads and in front of the villagers’ houses is quite obvious. But the public lighting facilities and the housing conditions were lower than the comprehensive assessment value, mainly due to the uneven quality of construction. The village lighting facilities have limited coverage. Only solar streetlamps have been installed on the main roads of the village. There are still widespread lighting blind spots in the residential areas of villagers. Moreover, there are problems such as short lighting time and vandalism of streetlamps in the village, which seriously affect villagers’ night travel. The villagers’ houses are mainly self-built, and the exterior walls were uniformly painted by the government a few years ago, but villagers have reported leakage and safety hazards in their own houses, severe paint peeling on the exterior walls and idle houses in the village affecting the appearance of the village.

5.2. Treatment of Domestic Sewage

From the perspective of domestic sewage, the evaluation value of its treatment implementation effect is 4.238, which is the highest among the five first-level indicators. The values of the secondary indicators, namely the discharge mode of domestic sewage, the construction of sewage treatment facilities, and the treatment of black and odorous water bodies, were 4.555, 3.994, and 4.173 respectively, all higher than the comprehensive evaluation value. As of now, Shaanxi Province has completed the treatment of domestic sewage in 6733 administrative villages and 159 rural black and odorous water bodies. According to the survey, 91.4% of the villagers reported that their daily domestic sewage was discharged uniformly into the sewage network. The sewage treatment facilities in the villages were relatively complete, and the treatment of black and odorous water bodies was particularly obvious, which led to a good improvement effect in the treatment of domestic sewage in the surveyed villages.

5.3. Rural Toilet Renovation

From the perspective of rural toilet renovation, the evaluation value of its implementation effect was 4.185, ranking second. Among its secondary indicators, the values of toilet renovation, toilet renovation satisfaction, and toilet sewage treatment methods were 4.029, 3.942, and 4.462 respectively. In recent years, counties (cities and districts) in Shaanxi Province, based on local realities, have actively explored diversified toilet renovation models. Through the working approach of “equal emphasis on construction and management, scientific planning, and classified measures”, they have steadily advanced the “toilet revolution” in rural areas, completing a total of 5.003 million new and renovated household sanitary toilets. According to the results of the field investigation, the coverage rate of sanitary toilets in villages has reached a relatively high level. Most households’ toilet types have been changed from dry toilets to water toilets; such toilets have been popularized in hospitals, leading to their usage in households and even inside houses. Villagers are extremely satisfied with the toilet renovation, and 62% of households reported that the treatment method of toilet sewage is directly discharged into the sewage network. There are still a few households that have not carried out toilet renovations due to conceptual and financial issues.

5.4. Domestic Waste Management

From the perspective of domestic waste management, the evaluation value of its implementation effect is 3.836, which is lower than the comprehensive evaluation value. Among its secondary indicators, the classification of domestic waste, the frequency of domestic waste collection and transportation, and the methods of domestic waste treatment were valued at 3.147, 4.134, and 4.601 respectively. In recent years, Shaanxi Province has vigorously implemented a major improvement project for rural environmental sanitation, established a grid-based management system for environmental cleaning in villages, assigned dedicated cleaners to each street and equipped with garbage classification bins, and the frequency of garbage collection meets the daily needs of villagers. But the assessment value of household waste classification is lower than the comprehensive assessment value, mainly due to the relatively weak environmental awareness of villagers. Most of the current residents in the village are elderly people, who generally have a low level of education and are not familiar with garbage classification knowledge, resulting in the phenomenon of littering garbage, which makes the problem of domestic garbage management still rather serious.

5.5. Construction and Management Mechanism

From the perspective of the construction and management mechanism, the evaluation value of its rectification implementation effect is 3.507, which is the lowest among the five first-level indicators. The evaluation values of its secondary indicators, namely farmers’ recognition, farmers’ participation, environmental improvement publicity, and environmental improvement management, were 3.968, 2.889, 3.451, and 4.043 respectively. Additionally, 83.2% of the villagers were satisfied with the current improvement of the living environment in the village, and 86.5% of the villagers believed that the village had a dedicated maintenance mechanism and maintenance personnel. But the participation of farmers and the publicity of environmental improvement were both lower than the overall assessment value. Furthermore, 40.6 percent of the villagers said they had occasionally or never participated in the improvement of the village’s living environment, which was largely carried out with the government taking the lead and the village committee assisting. Moreover, 44.8 percent of the villagers reported that there were few publicity campaigns for the improvement of the living environment in their villages.

6. Discussion

6.1. Comparison with Previous Studies

The overall score of 3.924 is consistent with findings from other studies on rural environmental governance in China. The low score for construction and management mechanism (3.507) echoes concerns raised by Qi et al. [34] about the lack of participatory governance and post-construction maintenance in rural China. This pattern—strong hardware, weak software—is also observed in other developing countries [35].

6.2. Explaining the Disparities: Why Participation Lags Despite High Satisfaction

One intriguing finding is the contrast between high farmer recognition (C14, mean 3.968) and low participation (C15, mean 2.889). This suggests a “satisfaction-participation gap” commonly seen in public goods provision: beneficiaries appreciate the outcomes but are unwilling to contribute effort [36]. Possible reasons include: (1) the perception that environmental improvement is the government’s responsibility; (2) lack of time or energy, especially among elderly residents; (3) insufficient mobilization by village committees; and (4) absence of incentives or sanctions to encourage participation [37].

6.3. The Role of Institutional Factors

The low score for environmental publicity (C16) highlights a weakness in communication strategies. Effective environmental governance requires not only infrastructure but also awareness-raising and behavior change campaigns [38]. International experiences show that participatory approaches, such as community-led total sanitation, can significantly enhance ownership and sustainability [39]. In contrast, top-down implementation in Chinese villages may limit local engagement [40].

6.4. Theoretical Implications

Our findings support the social–ecological systems framework by demonstrating that physical improvements (infrastructure) must be coupled with institutional strengthening (governance, participation) to achieve lasting outcomes. The “construction and management mechanism” dimension, which captures these institutional aspects, emerged as the weakest link, underscoring the need for adaptive governance that involves multiple stakeholders and fosters social capital [41].

6.5. Policy Implications

In light of the actual situation of rural human settlements improvement in environmental demonstration villages in Shaanxi Province and the analysis of the implementation effect and influencing factors of rural human settlements improvement in the previous text, the current rural human settlements improvement work in environmental demonstration villages in Shaanxi Province has achieved phased results, but with the progress of the practical work, some problems are also faced. In order to effectively enhance the effect of rural human settlement improvement, this chapter proposes some practical and feasible countermeasures specifically to ensure the comprehensiveness and continuity of the governance work.

(1) Farmers, as the core stakeholders of rural environmental governance, play the dual roles of participants and beneficiaries. Scientific and systematic publicity and education play a significant role in enhancing farmers’ awareness of environmental governance. It can effectively stimulate their initiative in participating in rural environmental improvement, thereby significantly strengthening and continuously consolidating the achievements of village environmental improvement. To optimize the effectiveness of rural living environment governance, it is necessary to adopt diversified communication means to deeply popularize the core content and basic concepts of environmental improvement, and help villagers fully recognize the social value and practical significance of this work.

(2) The effective implementation of the rural living environment improvement project must be based on a stable supply of funds. Field research found that the current governance level is far from the expectations of villagers, and the fundamental reason lies in the large gap in special funds for environmental governance. The comprehensive environmental governance project encompasses multiple subsystems such as the construction of sewage treatment systems and the improvement of village appearance, and requires a huge amount of funds. However, the current source of funds for rural living environment governance is still highly dependent on government financial support, showing a significant single-source feature. Therefore, a diversified and sustainable financing model of “financial input + social capital + corporate sharing” needs to be constructed to relieve financial pressure and ensure the sustainable advancement of environmental improvement efforts.

(3) Infrastructure construction is the first leg of rural development and an important part of rural living environment improvement. Improving rural infrastructure is a long-term task, covering a series of facilities such as domestic waste facilities, fecal sewage treatment facilities, and public lighting facilities. Although the coverage of rural infrastructure has increased under the impetus of the rural revitalization strategy, the phenomenon of idleness and vandalism still has an adverse impact on the effectiveness of rural living environment governance. Therefore, establishing the modern governance concept of “multi-subject collaborative governance” helps to improve the long-term management and maintenance mechanism of village infrastructure.

(4) As the bastion of the Party at the grassroots level, the organizational and mobilization capabilities and resource integration efficiency of the grassroots government directly affect the effectiveness of rural environmental improvement. By improving policy supply, innovating governance models, and strengthening technical support, we can fully mobilize the participation enthusiasm of grassroots organizations such as villagers’ committees, farmers’ cooperatives, and social organizations, and attract enterprises and returning entrepreneurs to actively engage in the improvement of the rural living environment.

(5) As a key resource for rural development, social capital not only provides endogenous impetus for village governance, but also constitutes the social foundation for its operation. When the cultural life of the village shows diverse characteristics, the enthusiasm of residents to participate will increase significantly, thereby enhancing the intensification of social networks, which can increase the frequency of interaction among villagers, thereby fostering mutual trust relationships, and transforming into a strong collective cohesion at the community level.

7. Conclusions

7.1. Main Findings

This chapter mainly analyzes the evaluation of the implementation effect of human settlement improvement in environmental demonstration villages in Shaanxi Province. First, organize and conduct descriptive analysis of the collected research data and interview records. Secondly, it was determined to use the fuzzy comprehensive evaluation method to evaluate the implementation effect of rural human settlements improvement. Again, quantitative assessment and qualitative analysis were conducted on the implementation results of each dimension. The results show that an evaluation index system for the implementation effect of rural living environment improvement was established from five dimensions: village appearance, domestic sewage treatment, rural toilet renovation, domestic waste treatment, and construction and management mechanism. The entropy method was used to determine the weights of each level of indicators, and the fuzzy comprehensive evaluation method was used to quantitatively evaluate each dimension and the overall governance effect. The improvement of the living environment in the environmental demonstration villages in Shaanxi Province has achieved phased results, but the three aspects of village appearance, domestic waste management and construction management mechanism are all below the comprehensive evaluation value, and there is still much room for improvement in the future.

7.2. Limitations and Future Research

This study has several limitations. First, the sample is confined to model villages in Shaanxi Province, which may not represent the situation in non-demonstration or other regions. Second, the evaluation relies on farmers’ subjective perceptions, which could be influenced by social desirability bias or varying expectations. Third, the cross-sectional design captures only a snapshot, not the dynamics of change over time. Future research should combine subjective with objective indicators (e.g., water quality measurements, waste treatment rates) and adopt longitudinal designs to track changes. Comparative studies across regions and village types would also enhance generalizability.