随着智慧矿山建设的推进，矿山企业逐步引入信息化、智能化技术，以提高生产效 率和安全管理水平。然而，在这一转型过程中，矿工的不安全行为仍是制约矿山安全生 产的重要因素。相比传统矿山，智慧矿山的作业环境更加复杂，技术设备更新速度加快， 矿工需要适应智能化系统、自动化设备和数据驱动的管理方式。其中矿工不安全行为意 向是导致不安全行为的主要原因。因此，理解并预测矿工不安全行为意向是有效预防和 减少煤矿事故的前提和基础。探索智慧矿山环境下矿工不安全行为意向的影响因素及其 形成机制，对于提升矿山安全管理水平、优化矿工行为具有重要的理论价值和实践意义。 首先，基于技术接受模型（TAM）和计划行为理论（TPB），本研究从态度、主观 规范、知觉行为控制方面提出矿工不安全行为意向影响因素的假设模型，构建了智慧矿 山背景下矿工不安全行为意向的形成机制理论分析框架。其次，为了验证理论模型的合 理性，本研究采用元分析方法，对国内外相关文献进行系统检索和筛选，最终纳入 25 篇符合标准的研究。分析结果表明，矿工对智慧矿山技术的感知有用性和感知易用性、 违章处罚、班组氛围、群体压力、工作压力、不安全心理、作业环境显著影响其不安全 行为意向。进一步地，为了探究矿工不安全行为意向的多因素耦合机制，本研究采用模 糊集定性比较分析（fs QCA）方法，识别出3条高不安全意向组态路径和3条非高不安 全意向组态路径，揭示了影响矿工行为意向的多因素联动效应。研究表明，矿工的不安 全行为意向并非由单一变量主导，而是由多种因素协同作用形成的复合型结构，不同路 径表现出认知缺失、制度真空、心理压力等典型机制。 本研究的结论进一步证实：影响矿工不安全行为意向的机制具有非线性特征。研究 不仅明确了关键影响因素，也划分了典型风险路径类型，并提出了针对性管理建议，如 强化技术认知支持、优化制度激励机制与群体文化引导等。研究成果为智慧矿山背景下 安全行为干预提供了实证支撑与路径依据，具有较强的理论创新性与现实指导意义。

With the advancement of smart mining construction, mining enterprises are increasingly adopting information-based and intelligent technologies to enhance production efficiency and safety management. However, during this transformation process, unsafe behaviors among miners remain a critical factor constraining mine safety. Compared with traditional mining, smart mines present a more complex operational environment and faster technological updates, requiring miners to adapt to intelligent systems, automated equipment, and data-driven management modes. Among the underlying causes, miners' unsafe behavioral intention is identified as a primary driver of actual unsafe behaviors. Therefore, understanding and predicting such intentions is a necessary precondition for effectively preventing and reducing coal mine accidents. Investigating the influencing factors and formation mechanisms of unsafe behavioral intention in the context of smart mining holds significant theoretical and practical relevance for improving safety management and optimizing miner behavior. This study, grounded in the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB), proposes a hypothetical model incorporating attitude, subjective norms, and perceived behavioral control to examine the factors influencing miners’ unsafe behavioral intention. A theoretical framework was constructed to analyze its formation mechanisms under smart mining conditions. To validate this model, a meta-analysis was conducted based on a systematic review and screening of domestic and international literature, yielding 25 eligible studies. The results indicate that perceived usefulness, perceived ease of use, punishment for violations, team atmosphere, group pressure, work stress, unsafe psychology, and the working environment all have significant effects on unsafe behavioral intention. Furthermore, to explore the configurational mechanisms of these factors, this study employed fuzzy-set Qualitative Comparative Analysis (fsQCA). Six configuration paths were identified, including three leading to high unsafe behavioral intention and three leading to non high intention, revealing the synergistic interactions among multiple factors. The findings suggest that miners' unsafe behavioral intention is not shaped by a single variable but rather emerges from complex combinations of interrelated conditions, such as cognitive deficiencies, institutional voids, and psychological stress. The conclusions further confirm that the mechanism influencing unsafe behavioral intention is characterized by nonlinearity and heterogeneity. The study not only clarifies key influencing factors but also categorizes typical high-risk behavioral paths. Based on this, targeted managerial strategies are proposed, such as enhancing technological cognition, refining institutional incentives, and shaping constructive group norms. These findings provide empirical evidence and strategic direction for behavioral intervention under the smart mining paradigm and offer valuable theoretical and practical contributions.

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