Social distancing is one of the most recommended policies worldwide to reduce diffusion risk during the COVID-19 pandemic. Based on a risk management perspective, this study explores the mechanism of the risk perception effect on social distancing in order to improve individual physical distancing behavior. The data for this study were collected from 317 Chinese residents in May 2020 using an internet-based survey. A structural equation model (SEM) and hierarchical linear regression (HLR) analyses were conducted to examine all the considered research hypotheses. The results show that risk perception significantly affects perceived understanding and social distancing behaviors in a positive way. Perceived understanding has a significant positive correlation with social distancing behaviors and plays a mediating role in the relationship between risk perception and social distancing behaviors. Furthermore, safety climate positively predicts social distancing behaviors but lessens the positive correlation between risk perception and social distancing. Hence, these findings suggest effective management guidelines for successful implementation of the social distancing policies during the COVID-19 pandemic by emphasizing the critical role of risk perception, perceived understanding, and safety climate.

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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.

Due to the highly developed rail transit over the past decades, the phenomena of complex individual self-organized behaviors and mass crowd dynamics have become a great concern in the train station. In order to understand passengers’ walking-edge effect and analyze the relationship between the layout and sustainable service abilities of the train station, a heuristics-based social force model is proposed to elaborate the crowd dynamics. Several evacuation scenarios are implemented to describe the walking-edge effect in a train station with the evacuation efficiency, pedestrian flow, and crowd density map. The results show that decentralizing crowd flow can significantly increase the evacuation efficiency in different scenarios. When the exits are far away from the central axis of the railway station, the walking-edge effect has little influence on the evacuation efficiency. Obstacles can guide the movement of passengers by channelizing pedestrian flows. In addition, a wider side exit of the funnel-shaped corridors can promote walking-edge effect and decrease the pressure among a congested crowd. Besides providing a modified social force model with considering walking-edge effect, several suggestions are put forward for managers and architects of the train station in designing sustainable layouts.

Purpose The purpose of this paper is to take advantage of Internet of Things (IoT) for intelligent route programming of crowd emergency evacuation in metro station. It is a novel approach to ensure the crowd safety and reduce the casualties in the emergency context. An evacuation route programming model is constructed to select a suitable evacuation route and support the emergency decision maker of metro station. Design/methodology/approach The IoT technology is employed to collect and screen information, and to construct an expert decision model to support the metro station manager to make decision. As a feasible way to solve the multiple criteria decision-making problem, an improved multi-attributive border approximation area comparison (MABAC) approach is introduced. Findings The case study indicates that the model provides valuable suggestions for evacuation route programming and offers practical support for the design of an evacuation route guidance system. Moreover, IoT plays an important role in the process of intelligent route programming of crowd emergency evacuation in metro station. A library has similar structure and crowd characteristics of a metro station, thus the intelligent route programming approach can be applied to the library crowd evacuation. Originality/value The highlights of this paper are listed as followings: the accuracy and accessibility of the metro station’s real-time information are improved by integrating IoT technology with the intelligent route programming of crowd emergency evacuation. An improved MABAC approach is introduced to the expert support model. It promotes the applicability and reliability of decision making for emergency evacuation route selection in metro station. It is a novel way to combine the decision-making methods with practice.

In China, crowd stampede accidents usually take place within crowded areas in middle and primary schools. The crowd stampede risk is particularly related to the architectural design such as the staircase design, the layout of crowded places, obstacles, etc. Through the investigation of building design in several primary schools, the relationship between the sustainable layout of crowded places (e.g., toilets, canteens, playgrounds, staircases) and the crowd stampede risk of students are introduced via agent-based simulations. In particular, different experimental scenarios are conducted on stairs in the primary buildings. The evacuation processes are recorded by video camera and spatial stepping characteristics (e.g., foot clearance, step length, mass center, the distance between the mass center and ankle, and etc.) are extracted from the video. Dynamic steady ability is investigated by adopting the margin of stability, quantified by the instantaneous difference between the edge of the base of support and extrapolated vertical projection of the mass center. Based on the sustainable built environment principles and historical data of students, this paper focuses on an in-depth analysis of the staircase design aiming at preventing the crowd stampede risk.

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