What makes better rural economic development: from endogenous development perspective

Jiayi Wang

International Journal of Development Issues2026https://doi.org/10.1108/ijdi-01-2025-0014article
AJG 2ABDC C
Weight
0.50

What the paper says

Purpose This study aims to dissect the factors contributing to rural economic development from the sustainable endogenous development perspective. Design/methodology/approach This research leverages integration of the econometric modeling and machine learning methodologies (Ordered Probit model and Random Forest model) to uncover the factors’ marginal effect, relative contribution and dynamic process, employing 420 farm households data in Guizhou Province, China. Findings The findings highlight village leadership, social capital, collective action and collective property rights system reform as significant facilitators of rural economic development. The reform of the rural collective property rights system exerts a paramount relative contribution to rural economic development, followed by social capital, collective action and village leadership. The impacts of collective action, social capital and leadership on rural economic development reveal a pattern of oscillatory rise, eventually stabilizing. Originality/value This research contributes to a nuanced understanding of rural economic development and offers insights into the strategic prioritization of policy formulation to achieve sustainable development in rural communities.

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https://doi.org/https://doi.org/10.1108/ijdi-01-2025-0014

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@article{jiayi2026,
  title        = {{What makes better rural economic development: from endogenous development perspective}},
  author       = {Jiayi Wang},
  journal      = {International Journal of Development Issues},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1108/ijdi-01-2025-0014},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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