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<p>Rural B&amp;Bs play an important role in promoting high-quality rural tourism and rural revitalization. However, unregulated expansion often leads to over-agglomeration in some areas and underdevelopment in others. Taking Quanzhou as a case study, this study constructs a six-dimensional driving system from a self-organization perspective. By combining GeoDetector and interpretable machine learning, it develops a spatial analytical framework to reveal the nonlinear agglomeration process, driving mechanisms, and threshold effects of rural B&amp;B clustering. Ecological factors make the greatest contribution and constitute the prerequisite for other factors to exert their effects. Gentle slopes, low-to-medium elevations, and proximity to water promote agglomeration within certain thresholds but become constraints beyond them. Cultural and economic factors show strong synergy, with intangible cultural heritage exerting greater effects in economically developed areas. Although policy and economic factors have limited independent effects, they significantly enhance agglomeration when interacting with ecological and cultural advantages. Rural B&amp;B development also depends on nearby living and recreational facilities. Based on these findings, suitable agglomeration areas are identified and differentiated policy recommendations are proposed, providing quantitative support for spatially targeted development.</p>

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Revealing the Nonlinear Driving Mechanisms and Thresholds of Rural B&B Clustering: A Spatial Analysis Approach Integrating Machine Learning

  • 期刊论文

  • 发表日期：

    2026年5月19日

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  • Lianlian Liu,
  • Xinrui Gao

摘要

Rural B&Bs play an important role in promoting high-quality rural tourism and rural revitalization. However, unregulated expansion often leads to over-agglomeration in some areas and underdevelopment in others. Taking Quanzhou as a case study, this study constructs a six-dimensional driving system from a self-organization perspective. By combining GeoDetector and interpretable machine learning, it develops a spatial analytical framework to reveal the nonlinear agglomeration process, driving mechanisms, and threshold effects of rural B&B clustering. Ecological factors make the greatest contribution and constitute the prerequisite for other factors to exert their effects. Gentle slopes, low-to-medium elevations, and proximity to water promote agglomeration within certain thresholds but become constraints beyond them. Cultural and economic factors show strong synergy, with intangible cultural heritage exerting greater effects in economically developed areas. Although policy and economic factors have limited independent effects, they significantly enhance agglomeration when interacting with ecological and cultural advantages. Rural B&B development also depends on nearby living and recreational facilities. Based on these findings, suitable agglomeration areas are identified and differentiated policy recommendations are proposed, providing quantitative support for spatially targeted development.