Rural in-migration is a growing global trend, significantly impacting rural areas socially and spatially. While prior research acknowledges the influence of economic, environmental, and social factors on settlement intentions, it often relies on stated-preference approaches that oversimplify the complex and fluid decision-making process. This study, based in Dali, China – a popular rural destination – addresses this limitation. Dali's diverse migrant population provides a rich context for understanding the nuanced interplay of factors influencing settlement decisions. The research employs a three-stage model (desire, expectation, plan) derived from the Theory of Planned Behavior (TPB) to capture the dynamic nature of decision-making, moving beyond simple intention measures. The study aims to identify key factors influencing settlement decisions, focusing on rural economic conditions, natural environment quality, and public service facility standards. Analyzing socio-demographic characteristics adds depth to understanding variations in influencing factors across different migrant groups. The study's findings are essential for addressing rural vitality challenges in China and encouraging active migrant participation in rural development.

Existing literature highlights the multifaceted nature of rural in-migration, encompassing various characteristics and motivations across different contexts. While offering potential benefits like improved well-being, challenges such as economic barriers, integration difficulties, and precarious work can also influence settlement decisions. Research on migrant settlement intentions often focuses on economic factors (e.g., employment, income), aligning with neo-classical and Todaro's theories. Socio-cultural factors and policies (like China's household registration system) also play significant roles. Environmental factors, such as public service facility quality and natural amenities, show mixed results in influencing settlement intentions, with some studies demonstrating positive correlations, others showing no significant relationship. Socio-demographic factors such as age, education, gender, and marital status also exhibit varied impacts on settlement intentions. However, existing studies often rely on stated preferences, neglecting the dynamic and evolving nature of the decision-making process. This study aims to address these gaps using a more nuanced approach.

This study uses a mixed-methods approach, combining quantitative and qualitative data analysis. The quantitative data were obtained from field surveys and questionnaires administered in May 2021 to 338 rural in-migrants in four villages surrounding Dali: Dali Ancient Town (known for commercial development), Shuanglang (a control group with balanced factors), Shaxi, and Xizhou (noted for preserved natural landscapes). The questionnaire assessed settlement decision-making in three stages (desire, expectation, plan) using a five-point Likert scale, drawing on the Theory of Planned Behavior (TPB). Social and environmental factors (economy, natural environment, public service facilities) were also measured using a five-point Likert scale. Socio-demographic characteristics (gender, age, marital status, education, household registration, length of residence, prior travel/residence experience, etc.) were collected for comprehensive analysis. Exploratory factor analysis was conducted to reduce the dimensionality of the social and environmental factors. Multiple linear regression analyses were then used to examine the relationships between these factors and settlement decision-making, both overall and across the three stages. Further regression analyses were conducted to assess the impact of socio-demographic characteristics (gender, age, education) on settlement decision-making. IBM SPSS Statistics 25 was used for all statistical analyses.

The overall settlement decision-making score for rural in-migrants was 3.81 (out of 5), indicating a positive tendency to settle. Scenario 1 (desire) had the highest score (3.96), while Scenario 3 (plan) had the lowest (3.66), suggesting a decline in commitment as the decision progresses. Regression analysis revealed significant positive effects of a strong rural economy, pleasant natural environment, and adequate public service facilities on overall settlement decision-making (Model 1). Economic and environmental factors were most influential in the desire and expectation stages (Models 2 and 3), while public service facilities became significantly influential at the planning stage (Model 4). Socio-demographic characteristics also played a role. Females showed lower tendencies to plan for long-term settlement, while those aged 25-49 exhibited more positive expectations and plans. Those with urban household registration displayed more negative settlement attitudes. Prior travel/residence experience positively influenced settlement decisions. Further analysis revealed that the importance of each factor changed across different groups: * **Gender:** Females emphasized public service facilities more than males. * **Education:** Those with junior high or below focused on the economy; high school graduates considered the economy and environment; and college graduates considered all three factors. * **Age:** Younger migrants (under 25) prioritized the economy; those aged 25-49 considered all three factors; and older migrants (50+) prioritized the natural environment.

The study's findings confirm that rural in-migrant settlement decisions are dynamic and context-dependent, evolving across different stages. The critical role of public service facilities at the planning stage contrasts with the emphasis on economic and environmental factors in earlier stages. This highlights the need for integrated rural planning considering diverse migrant needs and aspirations. The differences observed across gender, age, and education levels indicate that tailored strategies are necessary for different migrant groups. Female migrants’ prioritization of public services emphasizes the importance of family-oriented facilities. The shifting priorities across age groups underscore the need for life-cycle-based planning strategies. The findings also suggest that prior experience with a location significantly influences settlement decisions, highlighting the value of promoting familiarity and engagement with rural communities. This research contributes to a deeper understanding of migrant decision-making, moving beyond simplified intention measures to a more holistic and dynamic view.

This study provides valuable insights into the complex settlement decision-making of rural in-migrants in Dali, China. The findings highlight the crucial role of public service facilities in long-term settlement planning, particularly for female migrants. The interplay of economic, environmental, and socio-demographic factors underscores the need for comprehensive and context-specific rural development strategies. Future research could explore the role of specific aspects within the three main factors (economy, environment, public services) and expand the geographical scope to enhance generalizability.

The study's focus on Dali, China, might limit the generalizability of the findings to other regions. The reliance on self-reported data could introduce biases. While the three-stage model captures the dynamism of the decision-making process, it could benefit from further refinement. The study primarily focused on the three major factors (economy, environment, public services), leaving room to explore more detailed influences within these categories.