Article(id=1281608055376810779, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1281608054340829934, articleNumber=null, orderNo=null, doi=10.16265/j.cnki.issn1003-3033.2026.04.1224, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1761753600000, receivedDateStr=2025-10-30, revisedDate=1767974400000, revisedDateStr=2026-01-10, acceptedDate=null, acceptedDateStr=null, onlineDate=1783488771527, onlineDateStr=2026-07-08, pubDate=1777305600000, pubDateStr=2026-04-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1783488771527, onlineIssueDateStr=2026-07-08, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1783488771527, creator=13701087609, updateTime=1783488771527, updator=13701087609, issue=Issue{id=1281608054340829934, tenantId=1146029695717560320, journalId=1146031787341344770, year='2026', volume='36', issue='4', pageStart='1', pageEnd='286', issueExtLink='null', onlineDate='null', pubDate='1777305600000', pubDateStr='2026-04-28', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1783488771281, creator='13701087609', updateTime=1783588648031, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1282026967885124001, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1281608054340829934, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1282026967885124002, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1281608054340829934, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=49, endPage=56, ext={EN=ArticleExt(id=1281608056135979804, articleId=1281608055376810779, tenantId=1146029695717560320, journalId=1146031787341344770, language=EN, title=Configurational paths and enhancement strategies for risk cognitive ability of enterprise safety professionals, columnId=1277328386947150682, journalTitle=China Safety Science Journal, columnName=Safety Science Theories and Methods, runingTitle=null, highlight=null, articleAbstract=

To improve the risk decision-making effectiveness of enterprise safety professionals and curb the occurrence of unsafe behaviors, the theoretical connotation and improvement paths of risk cognitive ability were explored in this study. Based on SRK cognitive theory, the antecedent conditions of risk cognitive ability were classified into skill-based, rule-based, and knowledge-based cognitive abilities. The analysis of risk cognitive dimensions was combined from the perspectives of management systems, cognitive load, and cognitive tasks. Subsequently, a cognitive theoretical model was constructed, covering hazard identification ability, equipment operation ability, hidden danger inspection ability, hidden danger management ability, scenario decision-making ability, and case reasoning ability. NCA and fsQCA were applied to conduct data calibration, necessity analysis, sufficiency analysis, and robustness analysis on the multi-dimensional risk cognitive abilities of 100 safety professionals. Furthermore, the configurational paths of the antecedent conditions were analyzed, and targeted strategies for improving cognitive abilities were proposed. The results show that there are four configurational paths for both high risk cognitive competence and non-high risk cognitive competence. Specifically, high risk cognitive competence encompasses three configurational types: the rule-knowledge dual-driven type, the multi-dimensional cognitive ability synergistic type, and the emergency management ability dominated type. Accordingly, a "precision empowerment-multidimensional synergy-dynamic adaptation" path for improving risk cognitive ability is put forward, thereby enhancing the level of enterprise safety management.

, authors=Qian Wang, Xinru Tong, Angbin Yang, Ruipeng Tong^**, authorsList=Qian Wang, Xinru Tong, Angbin Yang, Ruipeng Tong, authorCompany=null, correspAuthors=Ruipeng Tong, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1281608056505078557, articleId=1281608055376810779, tenantId=1146029695717560320, journalId=1146031787341344770, language=CN, title=企业安全专业人员风险认知能力的组态路径与提升策略, columnId=1277328387270112092, journalTitle=中国安全科学学报, columnName=安全科学理论与方法, runingTitle=null, highlight=null, articleAbstract=

为提高企业安全专业人员的风险决策效能，遏制不安全行为发生，探析风险认知能力的组态路径和提升策略。基于技能-规则-知识（SRK）认知理论将风险认知能力的前因条件划分为技能型、规则型、知识型认知能力，结合管理体系、认知负荷、认知任务来解析风险认知维度，构建涵盖危险源辨识能力、设备操作能力、隐患排查能力、隐患治理能力、情景决策能力、案例推理能力的认知理论模型；运用必要条件分析（NCA）和模糊集定性比较分析法（fsQCA）对100名安全专业人员的多维风险认知能力开展数据校准、必要性分析、充分性分析和稳健性分析；解析风险认知能力前因条件的组态路径，提出针对性的认知能力提升策略。结果表明：高风险认知能力和非高风险认知能力各有4条组态路径，其中，高风险认知能力涵盖规则和知识双驱动型、多维认知能力协同型、应急管理能力主导型3种组态类型，得出“精准赋能-多维协同-动态适配”风险认知能力提升策略，从而提高企业安全管理水平。

, authors=王乾, 童心茹, 杨昂滨, 佟瑞鹏教授^**, authorsList=王乾, 童心茹, 杨昂滨, 佟瑞鹏教授, authorCompany=null, correspAuthors=佟瑞鹏教授, authorNote=, correspAuthorsNote=, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=+xX7YhESzGZZCeW0DZpTSQ==, magXml=Ggetoa4un+9rZbraz30z2g==, pdfUrl=null, pdf=W6h7l69a0RnrdVieJAlE/A==, pdfFileSize=2422883, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=NWnlvUuREQAkXSyG3pUSJg==, mapNumber=null, fund=null)}, authors=[Author(id=1281608058279269155, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1281608055376810779, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=wangqian19990825@163.com, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1281608058379932453, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1281608055376810779, authorId=1281608058279269155, language=EN, stringName=Qian Wang, firstName=Qian, middleName=null, lastName=Wang, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=School of Emergency Management and Safety Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1281608058480595750, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1281608055376810779, authorId=1281608058279269155, language=CN, stringName=王乾, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=中国矿业大学（北京） 应急管理与安全工程学院，北京 100083, bio={"content":"

王乾（1999—），男，河北秦皇岛人，博士研究生，主要研究方向为安全管理、风险评估。E-mail: wangqian19990825@163.com。

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王乾（1999—），男，河北秦皇岛人，博士研究生，主要研究方向为安全管理、风险评估。E-mail: wangqian19990825@163.com。

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