Escalator-related incidents (EIs) have recently resulted in serious injuries and even deaths. Given the frequency and severity of EIs, a systematic exploration of factors influencing EIs is critical in order to identify preventive measures. Twenty-two factors influencing EIs were identified by analyzing 213 EI cases in China and related literatures. A combination of the Interpretive Structural Modeling (ISM) and Decision Making Trial and Evaluation Laboratory (DEMATEL) methods were utilized to establish a hierarchical structure of the influencing factors and to distinguish cause factors and effect factors. The results show: (i) behavior, emergency plan, safety rules, safety supervision, information exchange, safety culture, and safety education are the most important factors influencing EIs; (ii) safety education is the cause factor imposing the greatest influence on other factors while behavior is the effect factor that is the most influenced; and (iii) the structure of influencing factors has five hierarchies, and factors in the root cause layer are settings and components, safety rules, safety supervision, safety culture, and safety education. Management priority should be given according to the hierarchy level, and the interaction of factors should be considered when taking preventive measures. The corresponding five-layer countermeasures are proposed to reduce escalator-related injuries.

Purpose: The purpose of this paper is to propose a theoretical framework of applying the Internet of Things (IoT) technologies to the intelligent evacuation protocol in libraries at emergency situations. Design/methodology/approach: The authors conducted field investigations on eight libraries in Wuhan, China, analyzed the characteristics of crowd gathering in libraries and the problems of the libraries’ existing evacuation plans. Therefore, an IoT-based intelligent evacuation protocol in libraries was proposed. Its basic structure consisted of five components: the information base, the protocol base, the IoT sensors, the information fusion system and the intelligent evacuation protocol generation system. In the information fusion system, Dempster–Shafer (D-S) evidence theory was employed as the information fusion algorithm to fuse the multi-sensor information at multiple time points, so as to reduce the uncertainty of disaster prediction. The authors also conducted a case study on the Library L in Wuhan, China. A specific evacuation route was generated for a fire and the crowd evacuation was simulated by the software Patherfind. Findings: The proposed IoT-based evacuation protocol has four distinguishing features: scenario corresponding, precise evacuation, dynamic correction and intelligent decision-making. The case study shows that the proposed protocol is feasible in practice, indicating that the IoT technologies have great potential to be successfully applied to the safety management in libraries. Research limitations/implications: The software and hardware requirements as well as the Internet network requirements of IoT technologies need to be further discussed. Practical implications: The proposed IoT-based intelligent evacuation protocol can be widely used in libraries, which is one of the inspirations for the use of IoT technologies in modern constructers. Originality/value: The application of IoT technologies in libraries is a brand-new topic that has drawn much attention in academia recently. The crowd safety management in libraries is of great significance, and there is little professional literature on it. This paper proposes an IoT-based intelligent evacuation protocol, aiming at improving the safety management in libraries at emergency situations.