Influencing Factors of the Post-Relocation Support Policy’s Satisfaction Degree for Rural Household: A Case Study of County M, Sichuan Province

Abstract

With the decisive results of poverty alleviation in China, figuring out how to consolidate the results and transform them into the driving force of rural revitalization is an important adjustment for rural revitalization and high-quality development. The efficiency of policy implementation as well as the sustainable development of the areas out of poverty are both reflected in rural households’ satisfaction with the ex-suit poverty alleviation policy for relocation. Based on survey data collected from 293 households in County M, Sichuan Province, this paper selects 23 indicators of satisfaction with post-relocation support policies from livelihood capital, political trust, policy participation, and public service perception. On this basis, we use the multinomial logistic model to analyze the impact of each influencing factor on the post-relocation support policy’s satisfaction degree for rural households. The results show that the satisfaction degree of relocated households with post-relocation support policies is upper-middle. Among the livelihood capital of relocated households, the proportion of non-agricultural income, cultivated land area, infrastructure conditions, number of family workers, and number of civil servants are all factors that positively affect policy satisfaction. In addition, with regard to relocating households’ engagement in political trust, policy participation, and public service perception, it should be pointed out that policy results trust, policy understanding, opinions expressed, local government, back-up personnel, policy process, and support funds all have appreciably positive effects on policy satisfaction. These evaluation results can serve as a reference for the revision of post-relocation support policies in China and other developing countries.

1. Introduction

Governments all around the world have long struggled with the issue of poverty, and they are always looking for new solutions to aid people in escaping it. As a developing country in the world, China places a high priority on the issue of poverty. The ex-suit poverty alleviation relocation is a crucial step to promote rural poverty alleviation and ecological environment construction [1]. Through the implementation of relocation, the living and development conditions of the rural poor will be greatly improved [2]. Since the early 1980s, China has spent 40 years relocating to fight poverty. Rural household relocation efforts have significantly improved the living conditions of relocated households and increased their ability to survive. Ex-suit poverty reduction relocation is a crucial strategy to address the issue that “one land cannot feed one person” in underdeveloped places. The “two no worries, three guarantees” and other problems are being resolved gradually, and have broadened the development trend for democracy and public services. Post-relocation support for relocation is a systematic effort that is connected to rural revitalization and targeted poverty alleviation. It is beneficial to research better ways to begin the work.

In response to the persistent issues in rural areas, China first recommended the implementation of the rural revitalization strategy and encouraged the combined development of urban and rural areas in 2017. With the land project of land capacity construction as the technical support and rural land system reform as the policy support, China has built a theoretical framework of urban-rural integration of population-land-industry-rights [3]. Under the new normal of the economy, targeted poverty alleviation is an important way to expand domestic demand and promote high-quality economic development. China has made considerable strides in reducing poverty over the past 40 years. Poverty alleviation relocation has been suggested as a crucial policy option by the Chinese government to eliminate poverty [4]. The state encourages relocated individuals to select their own migration time, location, and method, while requiring all levels to implement the desire to relocate [5]. Liu et al. [6] provided development-oriented poverty alleviation strategies, focusing on improving the self-development capacity of the poor and encouraging the participation of multi-party actors to alleviate poverty. Scholars have suggested a number of strategies to successfully advance the Chinese government’s targeted approach to reducing poverty. From the perspective of poverty alleviation strategies, Liu et al. [7] recommended the creation of focused and distinctive poverty alleviation solutions. From the perspective of post-relocation support policies, Li et al. [8] proposed the creation of a comprehensive poverty tracking system and a dynamic adjustment mechanism, while Cheng et al. [9] advised creating a suitable accountability system for “follow-up inspections”. From the perspective of ecology, Wu and Jin [10] suggested the establishment of an ecosystem service payment system.

In the post-migration stage, subjective well-being is one of the metrics used to gauge the effectiveness of policy implementation, particularly in terms of improving living conditions, infrastructure, public services, etc. [11]. According to Dai et al. [12], targeted poverty alleviation policies have shown a negative impact on rural poor residents’ health status and health equity, which is detrimental to the enhancement of their subjective feeling of well-being. Moreover, Pan et al. [13] discovered that subjective well-being was positively impacted by psychological views of the physical environment, both at the individual and community levels. Tang et al. [14] suggested that income, dependence ratio, marriage status, and age all positively affect rural households’ subjective well-being, whereas disease has a negative impact. Li et al. [15] discovered that people’s subjective experiences of well-being were indirectly impacted by the lack of policy information. They focused on the poor population’s access to information, made improvements to the way that information about policies is disclosed, and helped people feel more democratic. Zhang et al. [16] also made the case that improving rural residents’ information access can have a significant positive impact on the effectiveness of poverty alleviation.

Ex-suit poverty alleviation relocation is frequently correlated with livelihood capital. “Livelihood” is a crucial research field in economics for examining issues related to rural development, poverty, and environmental conservation. It covers every aspect of rural households’ production and lives, explains the difficulties of enduring poverty, and enlightens us on how impoverished people survive. Changes in livelihood capital, context adjustments for livelihoods, and institutional environment changes all have impacts on the choice of livelihood options made by relocated rural households. Several academics have investigated the connection between relocated migrants’ portfolio of means of subsistence and livelihood strategies. Wang et al. [17] examined the relationship between livelihood strategies and the livelihood capital of rural households in the Min River of China based on 23 livelihood capital measures, and they discovered that livelihood strategies have various sensitivities to various livelihood capital measures. In the same vein, Xu et al. [18] investigated the sensitivity of farm households’ livelihood strategies to livelihood capital in different types of villages, and they found that the beneficial effects of human capital and financial capital were the strongest. Zhang et al. [19] discovered that human capital, natural capital, social capital, and material capital all had a minor but significant impact on the vulnerability of rural household poverty. According to Walelign [20], there are noticeable disparities across different livelihood groups in terms of reliance on the environment, rural poverty, and asset endowment. Hua et al. [21] discovered that livelihood capital was a factor in rural households’ livelihood strategies, and that human, natural, and financial assets had substantial influence on livelihood strategies. Additionally, Sun et al. [22] contended that the connections within the rural household as well as the status of the farmers’ personal capital holdings all influence the livelihood strategy decisions of relocated farmers. Li et al. [23] hold that external environmental changes such as climatic ones have an impact on rural households’ tactics for sustaining their livelihoods. Mai et al. [24] found that poverty often leads to the relocated rural households to choose a single livelihood strategy, which in turn makes them further poorer. Ding et al. [25] argued that the way to break this vicious cycle is to consider the multidimensionality of poverty and realize a diversity of living strategies.

The sustainable livelihood of rural households should be fully considered. From the perspective of sustainable livelihood, Liu et al. [26] explored the effective mechanisms of government poverty alleviation measures. Liu et al. [27] investigated how ecological resettlement affected agricultural households’ livelihoods. Li et al. [28] and Huan et al. [29] suggested that governments can coordinate ecological transfer through restoring environmental services to prevent poverty from affecting rural communities. Li et al. [30] made the connection between ecological services and human well-being, creating a new foundation for policies aimed at reducing poverty and promoting migration. In terms of the research methods, Zhang et al. [31] used propensity score matching (PSM) and difference-in-differences (DID) to examine the impact of multi-dimensional poverty alleviation on poor households with different rural land consolidation models, and they aimed to alleviate multi-dimensional relative poverty paths. In the same way, Liu and Yang [32] investigated how precise poverty alleviation interventions affected measures of household welfare. Liu et al. [33] calculated the effect of industrial development on rural households’ capital for livelihood. Using panel data, Su et al. [34] utilized a fixed-effects two-difference model to measure the impact of poverty alleviation programs on the urban-rural income gap. Liang et al. [35] used ordinary least squares (OLS) regression to explore the impact of social capital on the sustainable livelihood capacity of rural households in three dimensions: social network, social participation, and social trust. Moreover, Liu et al. [5] employed a multinomial logistic model to examine the connection between the use of fundamental public health services and the social integration of internal migrants. Hua et al. [21] conducted a quantitative analysis of the connection between livelihood resources and livelihood methods.

As mentioned above, ex-suit poverty alleviation relocation is a long-term project. According to the existing literature, it is rare to study the connections between livelihood capital, policy participation, political trust, public service satisfaction, and the satisfaction of the post-relocation support policies of the rural household. Academic communities have various interests and areas of study, as well as various research methodologies. From the perspective of relocation groups, this study combines the subjective feelings and objective indicators of the relocated groups. On this basis, it builds a model of the impact factors for the satisfaction of policies, and continues to enrich the content of the subsequent support for relocation. This paper intends to address the following three research questions:

(1)

How do the relocated households evaluate the post-relocation support policies of ex-suit poverty alleviation relocation?

(2)

Does the implementation of the post-relocation support policies for relocation influence the differences between relocated and non-relocated households?

(3)

What factors affect the satisfaction of the post-relocation support policies for relocation?

To answer the aforementioned questions, this study analyzes the impact factors of post-relocation support policy satisfaction from the perspective of subjective feelings and sustainable livelihoods. On this basis, the impact of each influencing factor to the post-relocation support policy’s satisfaction degree for rural households is analyzed using the multinomial logistic model. The results show that the satisfaction degree of relocated households with post-relocation support policies is upper-middle. Among the livelihood capital of relocated households, the proportion of non-agricultural income, cultivated land area, infrastructure conditions, number of family workers, and number of civil servants are all factors that positively affect policy satisfaction. In addition, regarding relocating households’ engagement in political trust, policy participation, and public service perception, it should be pointed out that the policy results of trust, policy understanding, opinions expressed, local government, back-up personnel, policy process, and support funds all have appreciably positive effects on policy satisfaction.

The rest of the paper is organized as follows: Section 2 introduces the evolution of China’s poverty alleviation policy. Section 3 contains a logical analysis of the relevant theories, along with the measurement index. Section 4 contains the research area, the data sources, the selection of independent and dependent variables, and the descriptions of the empirical model. Section 5 includes the main part of the paper, which measures the post-relocation support policy’s satisfaction degree for rural households. On this basis, it uses multinomial regression analysis to analyze the sample data and quantify the impact of the relationship between the independent and dependent variables. Section 6 analyzes the problems existing in the post-relocation support policies in County M and puts forward measures to optimize the post-relocation policies for ex-suit poverty-alleviation relocation.

2. Evolution of Poverty Alleviation Policy in China

Poverty is a global issue, and eradicating it is a historical responsibility that all of humanity must complete. The Chinese government has been actively working to reduce poverty for many years [6]. Since the early 1980s and for more than 30 years, poverty alleviation and migration have been used as successful solutions to China’s unique poverty problem. The integration of rural construction promotion through migration and poverty alleviation is crucial. By examining the history of implementation and the evolution pattern, it is easier to understand the focus and direction of pro-poor and poverty reduction policy innovation. Therefore, this paper reviews China’s poverty alleviation policies since 1983 and divides the anti-poverty process into four periods.

2.1. The First Period (1983–1993): The Poverty Alleviation Migration Exploration Stage

With reform and liberalization, the home contract responsibility system has accelerated rural economic growth and significantly reduced poverty. However, in other locations, the hard natural conditions seriously limit socioeconomic development, and poverty is still a problem. At the beginning of the reform and opening up, China started to implement the “Three West” agricultural building plan, namely Hexi, Dingxi, and Xihaigu. The initiative was an early attempt to alleviate poverty in China through encouragement of agricultural growth, which helped to alleviate local poverty and backwardness. Since 1983, the central government has planned to allocate CNY 200 million every year for 10 years for agricultural development in the Hexi and Hetao areas. In addition, part of the population of the Dingxi and Xihaigu mountain areas will be moved to the Hexi and Hetao areas to develop wasteland and restore the ecological environment in the three western regions. In the “Three West” plan, “Hanging Village Emigration” was introduced, which means that peasant families go to areas with better production conditions to dig and plant land and then build a temporary shelter. The peasant families move between their original residence and the two villages in the land. In the early stages of relocation sites, inhabitants’ voluntary cooperation is primarily upheld and movement is encouraged, but a long-lasting and organized system of easy relocation has yet to be established.

2.2. The Second Period (1994–2000): The Poverty Alleviation Immigration Experiment Stage

In the 1990s, with the gradual deepening of rural construction development, the population in absolute poverty in China decreased significantly, the population in poverty alleviation changed significantly in terms of poverty type, and the distribution also clearly displayed geological characteristics. Therefore, the state issued the “National Eight-Seven Poverty Alleviation Program (1994–2000)” in 1994, which lists developmental migration as one of the primary strategies for reducing poverty and promoting development. In 1996, “The Decision of the CPC Central Committee and the State Council on Solving the Problem of Food and Clothing for the Rural Poor as Soon as Possible” was again emphasized by encouraging voluntary farmers to implement open migration. It was also noted that a few instances of extreme poverty can be used to strategically execute immigration development in 1998’s “The Decision of the CPC Central Committee on Several Major Issues Concerning Agriculture and Rural Work”. Throughout this time, developmental migration was a useful form. From 1991 to 2000, under the guidance of national policy, more provinces started to try to support ex-suit poverty alleviation nationwide. Among them, the typical provinces are Guangxi, Yunnan, Hubei, and Fujian.

2.3. The Third Period (2001–2010): The Poverty Alleviation Immigration Scale Promotion Stage

With the implementation of the poverty alleviation program, the issue of food and clothes for the rural poor in China has essentially been resolved, but the phenomenon of poverty persists, and the difficulties of working to alleviate it have grown. The state released several documents to effectively combat poverty, while constructing a moderately prosperous society. In 2001, the government published the Outline of China’s Rural Poverty Alleviation and Development (2001–2010), continuing the complete deployment of the 21st century’s approach to governing poverty. The 11th Five-Year Plan for the Ex-Suit Poverty Alleviation Relocation, published in 2007 by the National Development and Reform Commission, noted that the ex-suit poverty alleviation relocation is also known as ecological migration. China’s relocation efforts to reduce poverty officially became a national-level system project with the adoption of the plan. The field of poverty alleviation and immigration work is currently undergoing a rapid expansion; the application areas have grown, the management approach has been enhanced, and the outcomes of the implementation have been made available to the public. As of 2011, over 5 million people had migrated, and numerous examples of migrants who have local characteristics and work to alleviate poverty have been identified. In 2001, the Inner Mongolia Autonomous Region began to implement the ecological migration and poverty alleviation pilot project. Guizhou Province has carried out a poverty alleviation relocation project in rocky desertification areas. Jiangxi Province has implemented poverty alleviation relocation in the mountainous area of northwest Jiangxi Province.

2.4. The Fourth Period (2011–Present): The Poverty Alleviation Immigration Comprehensive Promotion Stage

After economic growth and poverty reduction throughout the first ten years of the twenty-first century, China’s efforts with regard to development and poverty reduction has moved into a new phase. The “12th Five-Year Plan” of 2011 proposed expanding ex-suit poverty alleviation relocation in nearby areas with unique challenges. The Outline of China’s Rural Poverty Alleviation Development (2011–2020) placed poverty alleviation and migrants in a prominent position of special poverty alleviation in the same year. The document emphasizes the ex-suit poverty alleviation relocation with poor living conditions, indicating that poverty alleviation migrants have reached a level of thorough promotion. At the end of 2013, the state proposed a targeted poverty alleviation strategy. In April 2015, at the 12th Group Study session of the Political Bureau of the CPC Central Committee, the General Secretary stressed that the implementation of an action plan for reducing poverty should be reviewed with a consideration of regional circumstances. In October of the same year, the Proposal of the CPC Central Committee on Formulating the 13th Five-Year Plan for National Economic and Social Development suggested the implementation of targeted poverty eradication and alleviation. By 2020, there were 9.515 million registered residents that lived in poverty, with a 99.4% occupancy rate. The relocation initiative for China’s fight against poverty has made significant progress.

In summary, the evolution of China’s poverty alleviation and migration policies has evolved from the goal of solving the problem of absolute poverty to the current increasingly diversified policy objectives. It will develop into a significant project for coordinated regional economic and social development, as well as integrated urban and rural development.

3. Analytical Framework

3.1. Theoretical Background

Political trust theory places an emphasis on how people and the political system interact [36], which has an impact on citizens’ desire to participate in the public sector, and is connected to the complicity of households that relocated with the policies. According to research, political trust has a positive impact on how well individuals perceive government policies. People who have more political trust are more likely to participate actively in public affairs and to be able to follow and put policies into practice. The degree of relocation families’ trust in the policy influences the policy evaluation as a crucial step in combining the benefits of poverty alleviation and relocation. Therefore, this study examines the political trust issue within the context of satisfaction with the aftercare policies affecting poverty alleviation and relocation. Accordingly, the first hypothesis of the this paper is designed as follows:

Hypothesis 1 (H1).

Under the dimension of political trust, there are positive factors that affect rural households’ satisfaction with the post-relocation support policy’s satisfaction degree.

With the development of new public service theory, Denhardt and Denhardt supplemented the new public management theory, emphasizing the government’s service role of providing citizens with better services in the public interest [37]. With regard to people, administrative staff, government, and the design of mechanisms, the new public service philosophy has high standards. Citizens should be aware of their importance in the construction of public services in order to participate in public construction. Administrative staff should actively promote joint consultation with the public sector and improve the efficiency of services. Governments should actively promote citizen participation and create mechanisms to encourage it. Following the new public service theory, this study incorporates policy participation and public service perception into the post-relocation support policy as research dimensions. Therefore, the second and third hypothesis of this study can be explained as follows:

Hypothesis 2 (H2).

Under the dimension of policy participation, there are positive factors that affect rural households’ satisfaction with the post-relocation support policy’s satisfaction degree.

Hypothesis 3 (H3).

Under the dimension of public service perception, there are positive factors that affect rural households’ satisfaction with the post-relocation support policy’s satisfaction degree.

The UK Department for International Development (DFID) established a framework for sustainable development in 1998 [38]. Vulnerability context, livelihood capital, structural and process alterations, livelihood solutions, and livelihood outcomes make up the five elements of the sustainable livelihood framework. According to this theoretical framework, natural, material, human, financial, and social capital are the five forms of capital that make up livelihood capital, which is the conceptual underpinning of the sustainable livelihoods framework. Livelihood capital influences the choice of livelihood for relocated households. When a rural households’ one source of livelihood capital is absent, that capital can make the livelihood capital remain in a reasonably stable state through complementary effects with other livelihood capital, thus making the rural household’s livelihood sustainable. Therefore, relocation of family human capital, natural capital, material capital, financial capital, and social capital are the focal point of this study’s framework. Based on this, we hypothesize that:

Hypothesis 4 (H4).

Under the dimension of human capital, there are positive factors that affect rural households’ satisfaction with the post-relocation support policy’s satisfaction degree.

Hypothesis 5 (H5).

Under the dimension of natural capital, there are positive factors that affect rural households’ satisfaction with the post-relocation support policy’s satisfaction degree.

Hypothesis 6 (H6).

Under the dimension of material capital, there are positive factors that affect rural households’ satisfaction with the post-relocation support policy’s satisfaction degree.

Hypothesis 7 (H7).

Under the dimension of financial capital, there are positive factors that affect rural households’ satisfaction with the post-relocation support policy’s satisfaction degree.

Hypothesis 8 (H8).

Under the dimension of social capital, there are positive factors that affect rural households’ satisfaction with the post-relocation support policy’s satisfaction degree.

3.2. Analysis Framework Construction

Public policy performance is the result of policy implementation. On the one hand, measuring policy inputs and outputs can help determine the effectiveness of a policy’s implementation and serve as a foundation for improving it [39]. On the other hand, by accumulating knowledge, spotting leaks, keeping tabs on those involved in the policy-making process, and enhancing accountability, public decision-making can become more democratic [8]. To some extent, the effectiveness of the policy’s execution can be seen in how satisfied the relocated persons are with the post-relocation assistance policy, which is a crucial factor in evaluating the effectiveness of the policy. Based on the framework construction for the satisfaction research of scholars [40,41], we constructed the satisfaction analysis framework of the post-relocation support policy of ex-suit poverty alleviation relocation.

According to Li and Li [42], the level of political trust among the general public is positively impacted by the transparency of policy decisions and the fairness in their implementation. The post-relocation support policy is based on poverty alleviation and relocation. The actual effect of the prior relocation policy has a direct impact on the trust and hopes of the relocation masses in the ensuing support policy. Positive policy achievements can contribute to an increase in political trust in governments and relocation organizations, and political trust has a favorable effect on people’s subjective well-being [43]. Thus, the study defines political trust is an evaluation of rural households’ expectations and the results of post-relocation support policies, which are measured by two metrics, namely, policy expectation trust and policy results trust. Policy expectation trust is based on the item “Your satisfaction with the post-relocation support policies for ex-suit poverty alleviation relocation to achieve family prosperity”. It is divided into five items: ‘very dissatisfied’, ‘dissatisfied’, ‘average’, ‘satisfied’, and ‘very satisfied’. The score is from 1 to 5, and the higher the score, the higher the expectation. For the policy results of trust selection of “Do you think the post-support policy is more helpful to you and your family”, no effect is 1, a small effect is 2, an average effect is 3, a large effect is 4, and a very large effect is 5. The higher the score, the higher the degree of trust.

According to Xiong et al. [44], policy participation enhances the quality of life for agricultural households. Many cities have formed local immigrant councils to increase the political rights of immigrants. These councils give immigrants the opportunity to participate in policy establishment, monitor governmental operations, and make public policies more representative of people’s true needs [45]. The results of the “ultimatum game” demonstrate that participants place a higher importance on procedural fairness than tangible advantages when making decisions [46]. This means that the public sector should actively communicate with farmers to increase their level of policy satisfaction, while also considering the actual needs of households that have relocated. Therefore, this study divides policy participation into three aspects: policy understanding, policy establishment, and opinions expressed. Policy understanding sets “Your understanding of the post-relocation support policy”, from ‘very unaware’ to ‘very aware’ on five levels, from 1 to 5 points; the higher the score indicated, the greater the understanding. Opinions expressed sets “Staff members were asked to conduct a household survey” on five levels, from ‘very dissatisfied’ to ‘very satisfied’, from 1 to 5 points; the higher the score, the higher the satisfaction. Policy establishment sets “Your satisfaction with your participation in the post-relocation support policy formulation”, and this is divided into five levels: ‘very dissatisfied’, ‘dissatisfied’, ‘average’, ‘satisfied’, and ‘very satisfied’. The higher the score, the higher the satisfaction.

With the conclusion of the relocation project and the resolution of the fundamental problems with living security, the needs of the residents of the resettlement region have also changed. In the stage of post-relocation support, the relocated people’s demand for the capacity and level of local public services gradually increased. Rural households’ satisfaction with the post-relocation support policy directly depends on the local government’s capacity to implement the policy, the staff’s efficiency, and the fairness and transparency of the support process [47]. Therefore, this study divides the satisfaction of relocated households with the public service perception into five parts: the satisfaction of the local government, back-up personnel, the policy process, support funds, and the feedback mechanism. Local government is evaluated based on “Your satisfaction with the local government”. Back-up personnel is evaluated based on “Your staff satisfaction with the service provided”. The policy process is evaluated based on “Do you think the fairness of the implementation process of post-relocation support for ex-suit poverty alleviation relocation is satisfactory”. Support funds is evaluated based on “Are you satisfied to support funds use conditions”. Feedback mechanism is evaluated based on “Satisfaction with the complaint channel for complaints”. There are five levels, from ‘very dissatisfied’ to ‘very satisfied’, with values from 1 to 5, with higher scores meaning higher satisfaction.

Relocation livelihood areas face issues such as a singular approach to livelihood and a dearth of livelihood options for relocated households. The aim of the post-relocation support relocation is resource integration, which includes giving rural households access to employment opportunities and raising the standard of living for those who have relocated [47,48]. According to several studies, livelihood capital enhances the quality of life for rural households, and the condition of rural households’ livelihood capital also influences how poverty alleviation measures are implemented [44]. As a result, the degree of improvement in the livelihood capital of the relocated people influences how satisfied policymakers are with the post-relocation assistance programs for the relocation of rural households. Human capital, natural capital, material capital, financial capital, and social capital are commonly used to characterize and measure the livelihood capital [19,49,50]. Therefore, this study breaks down livelihood capital into human capital, natural capital, material capital, financial capital, and social capital.

Human capital refers to the relocated households’ capacity for sustained subsistence, which serves as the foundation for the other four categories of capital. This can be evaluated in terms of earning potential and employment options, including the number of family workers and the opportunities to obtain training.

Natural capital, which is defined as the natural resources employed in livelihood activities and is connected to the local endowment of agricultural resources, has a significant impact on households with agricultural income that have been relocated. Examples of this are the cultivated land area and the quality status of the cultivated land.

Material capital is the material basis of the life of the relocated, and the capital index is positively connected with the quality of life. The material capital of peasant households can be divided into two parts: one part are the material assets of the relocated household, including the area of housing, the availability of production tools, and the number of household durable goods; the other part includes the infrastructure conditions in the community.

Financial capital is the term for households’ available economic resources, consisting mainly of two aspects: their own economic income and the ability to resist economic risks. The disposable income, the proportion of non-agricultural income, and the availability of deposits are selected in this study.

Social capital is the invisible capital, which refers to the social network of the relocated households, including the degree of connection among relatives and friends, the social breadth of family members, and their social status level. Therefore, we chose household communication consumption and the number of civil servants as indicators.

In summary, based on eight aspects of political trust, policy participation, public service perception, and five types of livelihood capital, this study selected 23 indicators to measure rural households’ satisfaction with the post-relocation support policy. This is depicted in Figure 1.

4. Methods

4.1. Research Area

This research selects the poverty-alleviation relocation area in County M, Sichuan Province, as the research object. Sichuan Province, located in the southwest of China, has a population of 5.688 million ethnic minorities. In 2020, the ratio of the tertiary industrial structure in the province was 11.4:36.2:52.4, while that in the ethnic autonomous areas was 22.1:30.2:47.7. This shows that the proportion of agricultural production in ethnic minority areas is higher than the overall proportion in the province, and agricultural production also occupies an important position in ethnic autonomous areas. This study takes County M, Sichuan Province, as the research object, and selects several resettlement areas for poverty alleviation relocation in County M as the investigation area. County M is in the Xiaoliangshan District, southwest Sichuan Province, which is made up of 54 poor counties (districts) in Sichuan ethnic areas, 88 poor counties (districts) in the “four major areas”, and 45 very poor counties, with a jurisdiction over 19 towns and 129 villages.

4.2. Data Source

This survey employs a multi-stage stratified sampling technique [51]. We create a structured questionnaire, schedule semi-structured one-on-one interviews, and conduct face-to-face data collection. The rural household sampling should be divided into four stages. The first stage is that the county conducts the whole sampling. The second stage is a township and village committee sampling. We select the immigrants sample size of the sample village in the third stage. In the fourth stage, household sampling is divided into three types: high, medium, and low income.

The study selects the poverty alleviation relocation area of County M in Sichuan Province as the research object. From August to September of 2021, the study team conducted field interviews with the resettlement region of poverty alleviation in County M (3983 people in 858 families). There were 320 anonymous surveys distributed in total. In order to get the most accurate information from the subjects and to guarantee the reliability and integrity of the data obtained, the members of the research team led the rural household as they filled out each section one at a time. In the end, 300 questionnaires were located, of which 293 were legitimate, yielding a validity percentage of 91.56%. These data made up the foundation of this study.

4.3. Variable Selections

4.3.1. Dependent Variable

The dependent variable is the degree of post-relocation support policy satisfaction of ex-suit poverty alleviation relocation among rural households. According to the five levels of “1 = Very dissatisfied, 2 = Dissatisfied, 3 = Average, 4 = Satisfied, 5 = Very satisfied”, the higher the score, the higher the evaluation.

4.3.2. Independent Variables

Here, the independent variables include core variables and control variables. The focus of this paper is the satisfaction of rural households with the post-relocation support policy. Therefore, political trust, policy participation, and public service perception are the core variables. At the same time, we also introduce livelihood capital as a control variable in this paper, including human capital, natural capital, material capital, financial capital, and social capital. In

Table 1. Descriptions of variables and assignments.

Variable		Variable Name	Assignments
Dependent variable		Overall policy satisfaction	1 = Very dissatisfied, 2 = Dissatisfied, 3 = Average, 4 = Satisfied, 5 = Very satisfied
Core variables	Political trust	Policy expectation trust	1 = Very dissatisfied, 2 = Dissatisfied, 3 = Average, 4 = Satisfied, 5 = Very satisfied
		Policy results trust	1 = No effect, 2 = Small effect, 3 = Average, 4 = Large effect, 5 = Very large effect
	Policy participation	Policy understanding	1 = Very unaware, 2 = Unaware, 3 = Average, 4 = Aware, 5 = Very aware
		Policy establishment	1 = Very dissatisfied, 2 = Dissatisfied, 3 = Average, 4 = Satisfied, 5 = Very satisfied
		Opinions expressed	1 = Very dissatisfied, 2 = Dissatisfied, 3 = Average, 4 = Satisfied, 5 = Very satisfied
	Public service perception	Local government	1 = Very dissatisfied, 2 = Dissatisfied, 3 = Average, 4 = Satisfied, 5 = Very satisfied
		Back-up personnel	1 = Very dissatisfied, 2 = Dissatisfied, 3 = Average, 4 = Satisfied, 5 = Very satisfied
		Policy process	1 = Very dissatisfied, 2 = Dissatisfied, 3 = Average, 4 = Satisfied, 5 = Very satisfied
		Support funds	1 = Very dissatisfied, 2 = Dissatisfied, 3 = Average, 4 = Satisfied, 5 = Very satisfied
		Feedback mechanism	1 = Very dissatisfied, 2 = Dissatisfied, 3 = Average, 4 = Satisfied, 5 = Very satisfied
Control variables	Human capital	Number of family workers	Number of household members who are employed (in persons)
		Opportunity of obtaining training	Whether household members participates in the training program No = 0, Yes = 1
	Natural capital	Cultivated land area	Family-owned cultivated land area (mu)
		Quality status of cultivated land	1 = Very poor, 2 = Poor, 3 = Average, 4 = Good, 5 = Very good
	Material capital	Area of housing	1 = Less than 60 m2, 2 = 60 to 80 m2, 3 = 80 to 100 m2
		Availability of production tools	Whether rural households have production tools No = 0, Yes = 1
		Number of household durable goods	Number of home durable goods possessed (pcs)
		Infrastructure conditions	1 = Very bad, 2 = Bad, 3 = Average, 4 = Good, 5 = Very good
	Financial capital	Disposable income	Relocating families’ annual income (CNY 10,000 a)
		Proportion of non-agricultural income	Agricultural income/gross income
		Availability of deposits	Situation with household deposits No = 0, Yes = 1
	Social capital	Household communication consumption	The total annual communication consumption of family members (yuan a)
		Number of civil servants	Number of civil servants in a clan (people)

Note: ^a During the study period, 1 U.S. dollar was equal to 6.96 Chinese Yuan.

, the explanations of the results of assigning each type of variable are presented.

4.4. Econometric Method

Based on objectives and structures, and extending earlier academic research [5], this study establishes an empirical model of the impact factors on the satisfaction of the post-relocation support policies of rural household ex-suit poverty alleviation relocation, as follows:

$$Y=\varnothing \left(x_1+x_2+x_3+\dots +x_i\right)+\epsilon ,\dots$$

(1)

where $Y$ refers to the satisfaction of the post-relocation support policy, according to five levels: 1 = Very dissatisfied, 2 = Dissatisfied, 3 = Average, 4 = Satisfied, 5 = Very satisfied; $\varnothing$ is a normal distribution function; $x_i$ refers to the independent variables, including core variables and control variables. $\epsilon$ refers to the random interference item, which reflects other unobservable factors.

The ordered dependent variable “satisfaction of the post-relocation support policies of rural household ex-suit poverty alleviation relocation” includes numerous choices. To solve this issue, we draw from the method of Wang [17]. The basic form of the model is as follows:

$$Ln \left(\frac{p\left(Y\le j|x\right)}{1-p\left(Y\le j|x\right)}\right)={\mu }_j-\left(\alpha +{\displaystyle \sum }_{i=1}^k{\beta }_i{x}_i\right),\dots$$

(2)

where $p(Y\le j|x)$ stands for the cumulative probability of classifying categories j and higher:

$$p(Y\le j|x)=\frac{e^{{\mu }_j-\left(\alpha +{{\displaystyle \sum }}_{i=1}^k{\beta }_i{x}_i\right)}}{1+e^{{\mu }_j-\left(\alpha +{{\displaystyle \sum }}_{i=1}^k{\beta }_i{x}_i\right)}}$$

(3)

in Equations (2) and (3), $j$ stands for the five levels of satisfaction with the post-relocation support policy, and its values are 1, 2, 3, 4, and 5. The dependent variable is $Y$. $x_i$ refers to the i-th factor affecting the satisfaction with the post-relocation support policy, $i$= 1, 2, …, $k$. $\mathsf{\alpha }$ is the intercept term; ${\beta }_i$ is the partial regression coefficient; and ${\mu }_1$, ${\mu }_2$, …, and ${\mu }_j$ are the cut-off points.

5. Results

5.1. Descriptive Statistics of the Samples

In terms of gender, males accounted for 64.2% of the total sample and females for 35.8% of it, with the higher percentage of males resulting from the fact that the sample was based on households, which were associated with male-headed households in the resettlement region. Geographically, there were 172 households in the first region, 61 households in the second region, and 60 households in the third region. The total number of samples is proportionally related to differences in sample area distribution. In terms of age distribution, since the sample consisted of household members, their average age was over 18, with 223 people aged 18–60 years old and 70 people aged 60 years old or older. In terms of household income, 12 households had a budget of 5000–10,000 yuan, making up 4.1% of the total; 59 had a budget of 10,000–30,000 yuan, making up 20.1% of the total; 124 has a budget of 30,000–60,000 yuan, making up 42.3% of the total; and 98 had a budget of more than 60,000 yuan, making up 33.4% of the total. Overall, low-income households are on the low side, and more than 30,000 households accounted for 75.7% of the total.

In terms of political trust, the score of the policy results trust is 3.31, indicating that the majority of relocated households have increased their productivity and income through active participation in pertinent support projects. The better off the relocated households are, the more appreciation they show for the post-relocation support in terms of relocation and poverty alleviation. At the same time, the relocated households benefited from the policies, and the policy expectation trust is 3.45. It is important to note that a tiny percentage of households that relocated were unsatisfied, probably because some support initiatives did not benefit them and the post-relocation support effect did not live up to their expectations.

The execution of policy participation is a crucial step in defending the legitimate rights and interests of relocated households. The process through which the relocated households participate in policy not only gives the group a subjective sense of respect and value, but it also somewhat normalizes the support system. Regarding policy participation, the value of each indicator is basically around 3. It is clear that more communication needs to be established between local governments and the households that have relocated.

The public sector’s performance in offering a variety of services during the post-relocation support phase is the main emphasis of the quality of public services. The local administration of County M oversees facilitating relocation and providing any necessary help. Local government, back-up personnel, the policy process, support funds, and the feedback mechanism all influence the satisfaction with post-relocation support policy. Regarding public service perception, the average score for satisfaction of the relocated families with the caliber of services given by the public sector post-relocation is approximately 3.5. Among them, the highest satisfaction level concerns the policy process, indicating that the policy covers all relocated households in the resettlement area, and each household receives appropriate support according to its actual situation. However, the lowest satisfaction levels concern local government, which may be attributed to the fact that households that have relocated have more contact with local support staff and less engagement with local government. Descriptive statistics of the core variables are shown in

Table 2. Descriptive statistics for the core variables.

Name		Mean	Standard Deviation	Least Value	Crest Value
Political trust	Policy expectation trust	3.45	1.14	1	5
	Policy results trust	3.31	1.18	1	5
Policy participation	Policy understanding	3.19	1.43	1	5
	Policy establishment	3.17	1.18	1	5
	Opinions expressed	3.38	1.27	1	5
Public service perception	Local government	3.35	1.32	1	5
	Back-up personnel	3.5	1.15	1	5
	Policy process	3.6	1.16	1	5
	Support funds	3.53	1.07	1	5
	Feedback mechanism	3.53	1.05	1	5

.

In terms of human capital, there are 1.57 stable jobs among relocated households in County M, with an average of just one member per household holding a steady job. Additionally, only a small percentage of family households participate in career training. Due to their lack of education, the survey indicated that many rural households are not interested in training, and those who did engage in training felt that it was less useful and not very helpful to them.

Arable land resources are a key measure of a household’s natural capital when agricultural output is the primary source of rural households’ income. Natural capital households have an average arable land area of 2.86 mu, and their agricultural land quality is 2.71, which is poor. These numbers are connected to the area’s position in the mountains and the scarcity of arable land.

Material capital mainly includes the area of housing, the availability of production tools, the number of household durable goods, and infrastructure conditions. The relocation site in County M follows the principle of “one case for one village”, and the housing area for convenient relocation is chosen in accordance with consistent requirements. Few relocated households have automated farming equipment, and while the production circumstances for these households to establish enterprises are generally favorable, there is still potential for development. With a standard deviation of 1.97 and a mean of 4.14, the number of household durable consumption quantity for relocated households reveals a wide variation in household material capital.

In terms of livelihood capital, financial capital is mainly related to disposable income, the proportion of non-agricultural income, and the availability of deposit. Based on the research, County M combined production elements including support projects, support policies, and support funding, while also mobilizing a significant number of migration groups to participate. The average income of relocated households is CNY 53,000, of which 29% comes from sources other than agriculture, with agriculture accounting for a far larger portion of household income. However, the household income of relocated households with primarily agricultural production is still affected by the issues of instability and slow growth. Eighty percent of rural households have savings, and the high percentage of savings indicates that farmers have a strong sense of economic risk protection. However, the savings are little, and the risk resistance is weak.

Social capital refers to the social resources that relocated households can employ to achieve sustainable livelihood goals. Examples include the social standing of family members and the frequency of interactions between friends and family. The indicator value of the number of civil servants in the household is 0.18, indicating that there are fewer social resources available. The yearly cost of household communication consumption is CNY 1941.48, which is expensive, indicating that relocated families may utilize information technology tools such as mobile phones to access information and grow their social networks. The descriptive statistics of the control variables are shown in

Table 3. Descriptive statistics for the control variables.

Name		Mean	Standard Deviation	Least Value	Crest Value
Human capital	Number of family workers	1.57	1.45	0	6
	Opportunity of obtaining training	0.24	0.43	0	1
Natural capital	Cultivated land area	2.86	2.47	0	12
	Quality status of cultivated land	2.71	1.29	1	5
Material capital	Area of housing	2.49	0.72	1	3
	Availability of production tools	0.06	0.23	0	1
	Number of household durable goods	4.14	1.97	0	12
	Infrastructure conditions	2.29	1.21	1	5
Financial capital	Disposable income	5.30	3.40	0.27	25.22
	Proportion if non-agricultural income	0.29	0.36	0	1
	Availability of deposits	0.80	0.40	0	1
Social capital	Household communication consumption	1941.48	1474.66	200	8000
	Number of civil servants	0.18	0.53	0	3

.

5.2. Measurement Results Analysis

When evaluating the precision of answers to quantitative data, a reliability analysis is frequently utilized. By examining the coefficients, the confidence level is ascertained. If the value is greater than 0.8, the reliability is high; if the value is between 0.7 and 0.8, the reliability is good; if the value is in the range of 0.6 to 0.7, the reliability is acceptable; if the value is less than 0.6, the reliability is poor. The reliability coefficient value is 0.911 (>0.8) by using SPSS 25 for the analysis, showing the high reliability of the study data.

The analysis of the research items’ reasonableness and significance is done through validity studies. The validity of this study was examined by using factor analysis. All study items had commonality values higher than 0.4 according to the results of the analysis, proving that the data could be efficiently extracted. The KMO value was 0.905 (>0.6), indicating that the data can be effectively extracted information. The sample is eligible for factor analysis if the value is more than 0.6, and the higher the value, the stronger the correlation between the variables in the data set.

The overall policy satisfaction as the dependent variable in an ordered logistic regression analysis and the 23 indicators listed above served as independent variables. First, the model was tested for parallelism, and it was determined whether the effects of each level of the independent variable on the dependent variable were consistent across all regression equations. The original hypothesis of the parallelism test is that the model satisfies parallelism, and the results show that the p value is 1.000 (>0.05). The model analysis conclusion is credible if the value is more than 0.05, suggesting that the model accepts the original hypothesis and can be analyzed further. The likelihood ratio test was then conducted on the validity of the whole model. The original hypothesis was that there was no change in model quality whether or not the independent variables were put in. The analysis results show that the p value was 0.000 (<0.05), so the original hypothesis is rejected. This means that the selected independent variables have validity, and the construction of the research model is meaningful.

As seen in

Table 4. Results of the orderly logistic regression model for policy satisfaction.

Variable	Index Item	Regression Coefficient	Standard Error	p Price	OR Price	An OR Value of 95% CI
Thresholds for dependent variables	1	8.275	1.587	0	0	0.000~0.006
	2	13.162	1.67	0	0	0.000~0.000
	3	17.07	1.833	0	0	0.000~0.000
	4	21.119	2.025	0	0	0.000~0.000
Core variables	Policy understanding	0.414 **	0.148	0.005	1.512	1.130~2.023
	Policy establishment	0.135	0.178	0.448	1.144	0.808~1.622
	Opinions expressed	0.369 *	0.186	0.047	1.446	1.005~2.081
	Local government	0.375 **	0.144	0.009	1.455	1.096~1.931
	Back-up personnel	1.323 **	0.199	0.000	3.754	2.543~5.540
	Policy Process	0.575 **	0.22	0.009	1.777	1.155~2.733
	Support funds	0.704 **	0.263	0.008	2.021	1.206~3.387
	Feedback mechanism	0.225	0.223	0.313	1.252	0.809~1.937
	Policy expectation trust	−0.045	0.157	0.775	0.956	0.703~1.301
	Policy results trust	0.395 **	0.145	0.006	1.484	1.118~1.971
Control variables	Proportion of non-agricultural income	1.151 *	0.476	0.016	3.162	1.243~8.041
	Disposable income	0.058	0.061	0.342	1.06	0.940~1.194
	Availability of deposits	−0.181	0.343	0.597	0.834	0.426~1.633
	Quality status of cultivated land	0.248	0.129	0.055	1.281	0.995~1.650
	Cultivated land area	0.202 **	0.07	0.004	1.224	1.067~1.404
	Opportunity of obtaining training	−0.007	0.379	0.985	0.993	0.473~2.085
	Number of family workers	0.296 *	0.134	0.027	1.345	1.035~1.748
	Number of civil servants	0.711 *	0.326	0.029	2.036	1.074~3.859
	Household communication consumption	0	0	0.081	1	1.000~1.000
	Area of housing	−0.193	0.206	0.348	0.825	0.551~1.234
	Availability of production tools	0.26	0.627	0.678	1.297	0.380~4.429
	Number of household durable goods	−0.074	0.078	0.339	0.928	0.797~1.081
	Infrastructure conditions	0.497 **	0.169	0.003	1.644	1.181~2.291

Note: *, ** represent * p < 0.05, ** p < 0.01, respectively. McFadden R-Square: 0.509.

, the model pseudo R-square value (McFadden R-square) is 0.509. This means that the independent variables can explain 50.9% of the change in overall satisfaction with the post-relocation support policies.

5.2.1. Core Variable Analysis

1.

Political Trust on Policy Satisfaction Analysis Results

The satisfaction with post-relocation support policies for relocation is significantly positively influenced by political trust. Policy satisfaction is significantly influenced favorably by indicators of policy results trust. People in resettlement regions gain from post-relocation support measures, which boost their sense of well-being. As a result of the absence of a reliable mechanism for increasing output and revenue, which would prevent them from becoming rich, the relocated masses generally assume that post-relocation support work only improves their living conditions.

2.

Policy Participation on Policy Satisfaction Analysis Results

The satisfaction with post-relocation support policies for relocation is significantly positively influenced by rural households’ participation in policy. Policy satisfaction is significantly positively impacted by both the measures of policy understanding and the opinions expressed. The relocation groups have a thorough awareness of the support program thanks to government promotion with regard to the diversification policy. The post-relocation support policy is therefore more suited to the relocation masses, enhancing the policy satisfaction of the resettlement family. At the same time, the support staff is fully aware of the actual circumstances and true demands of the moving households.

3.

Public Service Perception on Policy Satisfaction Analysis Results

The satisfaction with post-relocation support policies for relocation is significantly positively impacted by rural households’ experiences with public services. Policy satisfaction is greatly influenced by the four factors of local government, back-up personnel, policy process, and support funds. The rationale is that the relocated households interact with the employees more and have a better awareness of the post-relocation support policies of the local government, which influences how satisfied the relocation groups are with the support policies. With the aid of post-relocation support for relocation, some relocated households actively take part in the project of boosting output and income. The higher the recognition level of the moved households for the post-support policy, the more advantages and improvements that the post-relocation support has brought about. The satisfaction with the policy and the sense of benefit among the relocated groups can both be directly impacted by the proper distribution of support funds.

5.2.2. Control Variable Analysis

1.

Human Capital

The regression coefficient value of the opportunity of obtaining training index is −0.007, although it is not statistically significant (p = 0.985 > 0.05). This indicates that satisfaction with the post-relocation support policies as a whole is unaffected by whether anyone in the family participated in the training. The number of family workers index’s regression coefficient value is 0.296, with a significance level of 0.05 (p = 0.027 < 0.05). It follows that the proportion of stable workers in the relocated households has a significant impact on how satisfied people are with the post-relocation support policies. Our attention is required in terms of how to better integrate industrial development and skill development to improve the household livelihood.

2.

Natural Capital

The cultivated land area index’s regression coefficient value is 0.202, with a significance level of 0.01 (p = 0.004 < 0.05). This implies that the amount of cultivable land owned by the households that have relocated has a considerable beneficial impact on the general satisfaction with the post-relocation support policies. The quality status of cultivated land indicator’s regression coefficient is 0.248, which is not significant (p = 0.055 > 0.05). This indicates that general satisfaction with the post-relocation support measures is unaffected by the state of the households’ gardens, which have been cultivated. The main source of income for households relocated to the County M settlement area is still agriculture, and the more cultivated land a family owns, the greater the benefit from post-relocation support measures for agricultural industry production and the potential for greater happiness. As a result of the lack of scientific and technological investment in agricultural production in the resettlement area of County M, the effect on the enhancement of mu yield is small, and agricultural science and technology needs to focus on increasing investment.

3.

Material Capital

The area of the housing index’s regression coefficient value is −0.193, which is not statistically significant (p = 0.348 > 0.05). That means that the overall satisfaction with the post-relocation support programs is unaffected by the housing area of the households that were relocated. The infrastructure conditions index’s regression coefficient value is 0.497, with a significance level of 0.05 (p = 0.003 < 0.01). This implies that overall satisfaction with the post-relocation support policies is significantly positively impacted by the infrastructural conditions in the area of resettlement. The number of household durable goods index’s regression coefficient value is −0.074, which is not statistically significant (p = 0.339 > 0.05). This indicates that the overall satisfaction with the post-relocation support policies is unaffected by the number of household durable consumer goods. The regression coefficient value of the availability of production tools index item is 0.260, although it is not statistically significant (p = 0.678 > 0.05). This indicates that the general satisfaction with the post-relocation support programs is unaffected by the relocated family’s possession of production machinery. The infrastructure of relocation settlement areas has been further upgraded by County M settlement zones through post-relocation support projects, which have also improved the living conditions of relocated households and increased their satisfaction with the policy.

4.

Financial Capital

The proportion of the non-agricultural income index’s regression coefficient value is 1.151, with a significance level of 0.05 (p = 0.016 < 0.05). This implies that the percentage of non-agricultural income generated after relocation has a considerable positive impact on how satisfied people are with post-relocation support measures. The disposable income index’s regression coefficient is 0.058, which is not significant (p = 0.342 > 0.05). This implies that overall satisfaction with the post-relocation support policy is unaffected by disposable income. The regression coefficient value of the availability of the deposit index is −0.181, which is not significant (p = 0.597 > 0.05). This means that the overall satisfaction with the post-relocation support policies will not be impacted by whether the relocated household has a deposit. The variety of household livelihoods in County M has a big impact on how satisfied people are with the policies.

5.

Social Capital

The household communication consumption index’s regression coefficient is −0.000, although it is not statistically significant (p = 0.081 > 0.05). This indicates that the general satisfaction with the post-relocation support measures is unaffected by the communication costs incurred by the relocated households. The regression coefficient of the number of civil servants in the household is 0.711, with a significance level of 0.05 (p = 0.029 < 0.05). This indicates that the number of leaders or public officials in the households has a significant positive impact on the overall satisfaction with the post-relocation support policies. In some ways, the proportion of corporate cadres or public officials in moved homes is a good indicator of how well-equipped these households are to receive assistance when they are in danger and, consequently, how well-versed they are in policy.

6. Conclusions and Policy Recommendations

6.1. Conclusions

Using survey data from 293 households in County M, Sichuan Province, a multinomial logistic model was employed to explore the impact of each influencing factor on the post-relocation support policy’s satisfaction degree for a rural household. The results were as follows:

The post-relocation support policies are highly rated, with a mean satisfaction score of 3.64 and a positive attitude of 59.04%. This demonstrates how successful and well-liked the post-relocation support policies are by the relocation group. The post-support policy still has to be improved, so attention must be paid to that 25.94% of the group that believes that the post-support strategy has not significantly improved their existing circumstances, and 15.02% of the relocated households still have a negative outlook. This shows that various groups have different perceptions and assessments of the expectations for policies, the implementation process, and the impacts of policies.

In terms of the analysis of the relocated households’ political trust and policy participation, three types of indicators positively affect policy satisfaction. They are policy results trust, policy understanding, and opinions expressed. Therefore, the first hypothesis and second hypothesis are validated. Among them, the policy results of trust and the policy understanding index on rural households’ satisfaction with the post-relocation support policies were significant at the 1% significance level. Additionally, the regression coefficients were 0.395 and 0.414, respectively. Opinions expressed with regard to the index on rural households’ satisfaction with the post-relocation support policies was significant at the 5% significance level, and the regression coefficient was 0.369. This demonstrates that the satisfaction of relocated households with a post-relocation support policy is more sensitive to these indicators.

In the public service perception of relocated households, four types of indicators positively affected policy satisfaction. These were local government, back-up personnel, the policy process, and support funds. Therefore, the third hypothesis is validated. These four types of indicators on rural households’ satisfaction with the post-relocation support policies were all at the 1% significance level. Additionally, the regression coefficients were 0.375, 1.323, 0.575 and 0.704, respectively. This indicated that the public service perception was conducive to improving rural households’ satisfaction with post-relocation support policies.

Among the livelihood capital of relocated households, five types of indicators positively affected policy satisfaction. They were the proportion of the non-agricultural income of financial capital, the cultivated land area of the natural capital, the infrastructure conditions of material capital, the number of family workers of human capital, and the number of civil servants of social capital. Therefore, the fourth to eighth hypotheses are validated. Among them, the impact of cultivated land area and the infrastructure conditions index on rural households’ satisfaction with the post-relocation support policies was significant at the 1% significance level. Additionally, the regression coefficients were 0.202 and 0.497, respectively. This suggested that these indicators of relocated households may improve rural households’ satisfaction with the post-relocation support policies.

Based on the empirical results, it is possible to successfully increase the satisfaction with the post-relocation support policy for rural households by utilizing the aspects that have a strong positive impact on it.

6.2. Policy Recommendations

The government has developed and released related policy papers at various stages of the long-term project of relocating to reduce poverty. From the existing literature, few studies have been done on the connection between relocated households’ livelihood capital, political trust, policy participation, public service perception, and satisfaction with post-relocation support policies. The academic community’s emphasis, research agenda, and methodologies for tackling poverty reduction and relocation vary greatly from each other. The novelty of this research is based on the viewpoint of relocation groups, combining subjective and objective indicators, and using households’ satisfaction with the post-relocation support policy as the anchor point to develop a model of factors that influence it. In addition, Sichuan Province’s typical and representative ethnic minority settlements were chosen as survey objects, which may continually improve the content of post-relocation assistance for poverty reduction and migration.

Four policy suggestions are provided resulting from this research. First and foremost, the policy should be focused on enhancing the ability of rural households to support themselves, effectively enhancing internal vitality and adjusting the employment structure. The difficulty of executing skill training programs conflicts with the enhancement of the relocated households’ own ability to generate income. Thus, skill training programs are created to match local characteristics based on local resources. They can effectively develop knowledge skills into the production process and stimulate the interest of surrounding rural households in relocation skills training. Furthermore, the strategy might rely on regional development, expand job avenues, offer advantages for development, and support distinctive sectors. Second, the policy must consider the expanding non-material requirements of relocated rural households. The rural grassroots service system needs to be improved, as well as the grassroots sector’s ability to govern itself and the promotion of public service initiatives. Additionally, the government must increase the effectiveness of post-relocation support workers, develop the basic public service talent team in resettlement areas, cultivate a positive reputation, and better serve the displaced population. Third, the policy needs to focus on enhancing the participation of the relocated population. Strengthen the staff’s policy comprehension so that they can convey to rural households the correct policy requirements and accelerate their integration into the local communities in the resettlement regions. Furthermore, the relocated people are inspired to take pride in their new town, engage in active community participation, take part in local community governance, and fully utilize the benefits of the system through the guidance and publicity provided by the local government. Fourth, the local administration must increase public political trust in the resettlement area. The primary determinant of whether post-relocation support policies are satisfied is the realistic feeling. In order to improve the political trust of rural households in resettlement areas, the support policy should be fully integrated with the real needs of local relocation groups, and support measures should be targeted.

Relocation is a crucial tactical move to address the “Three Rural” issues in China’s underdeveloped regions. The ex-suit poverty alleviation relocation is currently approaching the stage of solidifying the poverty reduction successes and is putting the rural revitalization strategy into practice. Due to the uneven social development across China and the disparities in ethnic history and culture, how to modernize rural rehabilitation in impoverished areas should be a development priority for the entire population. The sample size for this study’s centralized resettlement locations in County M was 293 valid questionnaires, which was sufficient in terms of research and analysis. However, other regions and counties did not receive the same amount of survey data collection, which contributed to some sample inequality. To ensure that the research findings are more representative, we aim to widen the sampling area in the future.

With the comprehensive implementation of rural revitalization, the group of poverty-stricken people relocated from inhospitable areas will continue to increase and attract more social attention. In future research, we will continue to concentrate on the historical process of rural modernization and the implementation of a rural revival strategy. First, we will further improve the performance evaluation index system of satisfaction with the policy of ex-suit poverty alleviation relocation and better consolidate China’s targeted poverty alleviation program. We will then further explore the social spatial characteristics of rural households’ ex-suit poverty alleviation relocation in to have get a deeper understanding of the ex-suit poverty alleviation relocation policy from a multi-dimensional perspective [52,53,54]. In addition, we will pay more attention to the research dynamics in related fields and carry out extended research with a broader vision and a higher research intensity.