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<p>Against the backdrop of green transformation as a strategic priority in the hotel industry, the employee-driven mechanisms of green service innovation (GSI) remain insufficiently understood. Existing studies largely rely on linear pathways and fail to capture the complex interactions among ability, motivation, and opportunity. Drawing on the ability-motivation-opportunity framework, this study integrates necessary condition analysis (NCA), fuzzy-set qualitative comparative analysis (fsQCA), and artificial neural networks (ANN) to analyze two-wave survey data from frontline employees in Chinese upper-midscale hotels. The results reveal that no single factor constitutes a necessary condition for GSI. High-level GSI can be achieved through two sufficient pathways: “autonomy support and capability-driven pathway” and “organizational support and motivation-driven pathway”. ANN sensitivity analysis further confirms the important role of green human resource management (GHRM). This study advances beyond linear perspectives by uncovering the asymmetric configurational mechanisms of GSI and offers practical implications for integrating systematic GHRM practices with employee autonomy to foster sustainable green innovation.</p>

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A multi-method analysis of employee-driven green service innovation in hotels based on the ability-motivation-opportunity framework

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月17日

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  • Yifei Li,
  • Tianshu Li,
  • Yuanyi Ling,
  • Xinshu Feng,
  • Hailin Wang,
  • Caisheng Liao

摘要

Against the backdrop of green transformation as a strategic priority in the hotel industry, the employee-driven mechanisms of green service innovation (GSI) remain insufficiently understood. Existing studies largely rely on linear pathways and fail to capture the complex interactions among ability, motivation, and opportunity. Drawing on the ability-motivation-opportunity framework, this study integrates necessary condition analysis (NCA), fuzzy-set qualitative comparative analysis (fsQCA), and artificial neural networks (ANN) to analyze two-wave survey data from frontline employees in Chinese upper-midscale hotels. The results reveal that no single factor constitutes a necessary condition for GSI. High-level GSI can be achieved through two sufficient pathways: “autonomy support and capability-driven pathway” and “organizational support and motivation-driven pathway”. ANN sensitivity analysis further confirms the important role of green human resource management (GHRM). This study advances beyond linear perspectives by uncovering the asymmetric configurational mechanisms of GSI and offers practical implications for integrating systematic GHRM practices with employee autonomy to foster sustainable green innovation.