12·31上海外滩踩踏事件后,高聚集游客群的安全问题备受关注.借助百度新闻和新浪微博搜集高聚集游客群安全案例,采用扎根理论探究高聚集游客群安全的影响因素,并分析影响因子之间的相互作用关系.研究发现:(1)高聚集游客群安全受到客流压力、游客行为状态、强化管理响应等28个因素的影响.其中,多源压力、状态变异、优质管理响应、劣质管理响应和管理响应缺失是影响高聚集游客群安全的5大因子.(2)各因子之间相互作用,形成高聚集游客群安全的不同发展路径.其中,"多源压力-状态变异-优质管理响应"是高聚集游客群安全的实现路径.%In recent years, tourism activities have been mainstreamed and popularized, leading to a sharp rise in numbers of tourists. Consequently, a distinctive phenomenon, described by terms such as"a bursting forth of tourists,""tourist break out,"a"crowded explosion in scenic tourist spots,"and"crowds of tourists"has been apparent at many popular scenic tourist spots, tourist attractions, and some acclaimed tourist sites. Following the"Bund Stampede"incident that occurred on December 31, 2014, there has been heightened concern regarding the issue of security in the context of highly aggregated tourist crowds (HATCs). Groups of tourists constituting maximal agglomerations, both in terms of numbers and density, are characterized by considerable degrees of uncertainty and complexity relating to changes within them. Consequently, controlling and evacuating these groups presents considerable challenges and entails numerous risks and hidden difficulties, with accidents being likely to occur. Thus, more extensive research on HATCs is necessary to strengthen their management. For this study, cases highlighting security issues associated with HATCs were extracted from the Baidu News and Sina Weibo websites. Subsequently, Grounded Theory was applied to identify factors that influence the security of HATCs, and the interactive relationships among these factors were analyzed. The following process was applied. Open coding analysis was performed based on the following logical analytical procedure:"Define the Phenomenon-Develop the Concept-Extract the Category."The results revealed that there were 28 influencing factors that affected the security of HATCs, including tourist flow pressure, tourist behavior status, and enhanced management response. The application of a typical grounded theory analytical framework, namely "causal condition-phenomenon-context-mediating condition-action/interaction strategy-result"revealed that the following five factors influenced the security of HATCs: multiple source pressure, state variation, quality management response, poor management response, and management response loss. A core category was identified through selective coding and used to develop a story on how these factors influence the safety of HATCs. Different implementation paths relating to the security of HATCs emerged as a result of the interactions between the various factors. Among these, the"multiple source pressure-state mutation-quality management response"was found to be the safest path for achieving the security of HATCs. Security-related mishaps occurring within HATCs were attributed to a lack of efficient coordination of and interaction between multiple source pressure, state variability, and management responses. Thus, specific factors that influence the safety of HATCs were identified in this study. These findings can provide insights and help to promote further studies on this topic that may contribute to the development of effective safety management in relation to HATCs.
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