Analysis of the Human Behavior trapped in the Fire Hazards based on Protective Action Decision Model [PADM] (Case Study: Office high-rise buildings in Tehran)

Document Type : مقاله پژوهشی

Authors

• Seyed yaser Mousavi
• Shahab Kariminia
• Shirin Toghyani

Islamic Azad University, Najafabad Branch

10.22067/geo.v0i0.75934

Abstract

Introduction

With the growth of urbanization and the construction of high-rise buildings, attention to the behavior of individuals during the evacuation is an important issue in the design of such buildings. The concerns in this regard are the lack of proper behavior patterns during evacuation from high-rise buildings and lack of attention to the risk perception of individuals in the fire, which is one of the key factors influencing individual's decision-making, especially in the pre-evacuation phase in Iran. This issue is especially important in high-rise buildings due to the height and number of people. Human behavior is one of the key factors, and how to behave in crisis and emergency situations has become one of the concerns of researchers in recent decades, especially after the terrorist attacks of September 11, 2001, in the United States (Kuligowski, 2008, 2009, 2013, 2016; Kuligowski & Hoskins, 2010, 2011; Nilsson & Johansson, 2009; Norazahar et al., 2014; Proulx, 1993; X. Zhang, 2017; Zhu & Shi, 2016 , which can be considered as the most important factor in the necessity of risk analysis that changes the risk pattern (Moghimi, 2015). There are various models and patterns to determine behavior when humans are at risk and how they perceive the danger of many models and patterns (Hackman & Knowlden, 2014; Heath et al., 2017; Ryu & Kim, 2015). Among these, Protective Action Decision Model-PADM is a model that can be found to determine the behavior and perceptions of the perceived individuals in the fire compared to other models for the type of termination, the duration of the implementation and the simultaneous transmission of information to individuals (Lindell & Perry, 2012) more influential. The purpose of this study was to explore the behaviors of individuals who are caught in fire in the pre-flight phase. Subsequently, by placing these behaviors in Protective Action Decision Model, the risk perception of individuals in the fire will be measured and ultimately the activities that take time to evacuation this time will be identified. Several studies have been conducted on conceptual frameworks and different types of pre-evacuation activities, but the studies have been limited; Firstly, discuss the relationship of this activity with risk perception of individuals, secondly: activities that spend more time in the evacuation phase have not been identified. Using the results of this research one can first identify activities before evacuation of individuals, as well as activities that spend more time in high-rise office buildings, secondly, with the placement of the given activities in Protective Action Decision Model, we can measure their risk perception and prioritize those activities; and thirdly, the results of the present study, which are a new way of using Protective Action Decision Model based on the factors of each question - instead of answering "yes" or "no" in each direction - can be useful in determining more accurate individual's behaviors trapped in a fire. In this regard, the present research can be an innovative one.

Materials and Methods

The research method in this study is of mixed Method and its scope includes high-rise office buildings in Tehran during 2011-2017.  The sample is consisted of 8 high-rise office buildings based on the Cochran formula, in which the sample size includes 245 people who are either trapped in fire or evacuation. Impact components on the model core of decision making were based on specific studies and the questionnaire was designed in two sections. The first part is an open-ended question: what was your first action after realizing the fire? And for analysis the data Colaizzi Method was used. In the second part, the decision-making questions of five-step spectrum maimed the views of individuals caught in the fire, and the scores earned were calculated for each indicator. Finally, using the SPSS 22, linear regression coefficient (R2), and path coefficient (Beta), the role of components of the decision model in relation to pre-evacuation activities was determined.

Results and Discussion

The results showed that, the behaviors formed in the pre-evacuation phase were divided into two functional tasks (for examples: moving to the window and terrace and opening them to ask for help, collecting properties ect.) and information tasks (for examples: Contacting the fire department, building management and services ect.). It also showed that, these behaviors were examined based on Protective Action Decision Model and extracted four models. ‌ It was found that the behavior of “unlocking the unit door due to the smoke in lobby and corridor”, “collecting assets”, and “finding the staircase according to the familiarity with the path”, have the highest relationship with risk perception and spending lesser time.

Conclusion

In the study, using Colaizzi Method, first, ten behaviors were identified in the first protective action and then by placing the behaviors in the Protective Action Decision Model, four models were extracted. According to the results of the first model, it is suggested that in each high-rise building, exit patterns at the beginning of the entrance of elevators and stairs should be installed in order to increase the level of familiarity with the location. According to the results of the second model, it is suggested that the panel “The elevator is off during hazardous situations” and also emergency numbers written on it be installed. According to the results of the third model, it is recommended to make voice announcements in high-rise buildings and report exit status for individuals. Also, according to the results of the fourth model, it is suggested that in order to reduce the Normalcy bias and optimistic bias on exit, the intensity and validity of signs and warnings (for example, with flashing lights) be increased. In this way, the risk perception of individual's evacuation will increase and the time of evacuation from fire hazards will decrease.

Keywords

• Human Behavior
• Protective Action Decision Model [PADM]
• Fire Hazards
• High-rise Office Buildings

---

References

مقیمی، ابراهیم؛ 1394. دانش مخاطرات(برای زندگی با کیفیت بهتر). دانشگاه تهران، چاپ دوم، تهران.

مقیمی، ابراهیم؛ پاییز1395. «چرا دانش مخاطرات؟ (دیدگاهی جدید برای درک مخاطرات)». مدیریت مخاطرات محیطی، دوره3، شماره3، 197-191.

Akutsu, I., 2015. Evacuation notification terminal device and evacuation notification system. Google Patents.

Averill, J. D., Mileti, D. S., Peacock, R. D., Kuligowski, E. D., Groner, N., Proulx, G., Nelson, H. E., 2005. Federal Building and Fire Safety Investigation of the World Trade Center Disaster Occupant Behavior, Egress, and Emergency Communications (Draft). National Institute of Standards and Technology press.

Boyce, K., McConnell, N., Shields, J., 2017. Evacuation response behaviour in unannounced evacuation of licensed premises. Fire and Materials, 41(5): 454-466.

Bryan, J. L., 1983. A review of the examination and analysis of the dynamics of human behavior in the fire at the MGM Grand Hotel, Clark County, Nevada as determined from a selected questionnaire population. Fire safety journal, 5(3-4): 233-240.

Bryan, J. L., 2002. Behavioral response to fire and smoke. SFPE handbook of fire protection engineering, 2: 42.

BSI, P., 2004. The application of fire safety engineering principles to fire safety design of buildings. Part 6: human factors: life safety strategies—occupant evacuation, behaviour and conditions (sub-system 7974-6). British Standards Institute Google Scholar.

Cahyanto, I., Pennington-Gray, L., Thapa, B., Srinivasan, S., Villegas, J., Matyas, C., Kiousis, S., 2016. Predicting information seeking regarding hurricane evacuation in the destination. Tourism Management, 52: 264-275.

Dash, N., Gladwin, H., 2007. Evacuation decision making and behavioral responses: Individual and household. Natural Hazards Review, 8(3) : 69-77.

Day, R. C., Hulse, L. M., Galea, E. R., 2013. Response phase behaviours and response time predictors of the 9/11 World Trade Center evacuation. Fire technology, 49(3) : 657-678.

Galea, E. R., 2009. Evacuation Response Phase Behaviour. University of Greenwich.London: CMS Press.

Galea, E. R., Deere, S., Hopkin, C., Xie, H., 2017. Evacuation response behaviour of occupants in a large theatre during a live performance. Fire and Materials, 41(5) : 467-492.

Galea, E. R., Markus, S., Deere, S. J., Filippidis, L., 2015. Investigating the impact of culture on evacuation response behaviour. Paper presented at the 6th International Symposium on Human Behaviour in Fire.Interscience Communications Ltd, London.

Gwynne, S., Galea, E. R., Parke, J., Hickson, J., 2003. The collection and analysis of pre-evacuation times derived from evacuation trials and their application to evacuation modelling. Fire Technology, 39(2) : 173-195.

Gwynne, S., Kuligowski, E. D., Kinsey, M., Chisnell, R. M. D., Helton, J., Freedman, D., Lee, Y., 2015. Human behavior in fire-model development and application. Paper presented at the 6th International Symposium on Human Behaviour in Fire. Interscience Communications Ltd, London.

Hackman, C. L., Knowlden, A. P., 2014. Theory of reasoned action and theory of planned behavior-based dietary interventions in adolescents and young adults: a systematic review. Adolescent health, medicine and therapeutics, 5: 101-114.

Heath, R. L., Lee, J., Palenchar, M. J., Lemon, L. L., 2018. Risk communication emergency response preparedness: contextual assessment of the protective action decision model. Risk analysis, 38(2): 333-344.

Hopkin, C., Galea, E. R., Deere, S., 2015. A study of response behaviour in a theatre during a live performance. Paper presented at the 6th International Symposium on Human Behaviour in Fire. Interscience Communications Ltd, London.

Huang, S. K., Lindell, M. K., Prater, C. S., Wu, H.-C., Siebeneck, L. K., 2012. Household evacuation decision making in response to Hurricane Ike. Natural Hazards Review, 13(4) : 283-296.

Kinateder, M. T., 2013. Social influence in emergency situations–studies in virtual reality. PhD Thesis, Wurzburg University,pp 128.

Kinateder, M. T., Kuligowski, E. D., Reneke, P. A., Peacock, R. D., 2014. A review of risk perception in building fire evacuation, National Institute of Standards and Technology press.

Kinateder, M. T., Kuligowski, E. D., Reneke, P. A., Peacock, R. D., 2015. Risk perception in fire evacuation behavior revisited: definitions, related concepts, and empirical evidence. Fire science reviews, 4(1) : 1.

Kuligowski, E. D., 2013. Predicting human behavior during fires. Fire Technology, 49(1) : 101-120.

Kuligowski, E. D., 2017. Burning down the silos: integrating new perspectives from the social sciences into human behavior in fire research. Fire and materials, 41(5) : 389-411.

Kuligowski, E. D., Hoskins, B. L., 2011. Analysis of Occupant Behavior During a Highrise Office Building Fire. pedestrian and evacuation dynamics (pp. 685-697): Springer. Boston, MA.

Kuligowski, E. D., 2008. Modeling human behavior during building fires. National Institute of Standards and Technology press.

Kuligowski, E. D., 2009. The process of human behavior in fires. US Department of Commerce, National Institute of Standards and Technology.

Kuligowski, E. D., 2011. Terror defeated: occupant sensemaking, decision-making and protective action in the 2001 World Trade Center disaster. Ph.D Thesis,University of Colorado at Boulder, pp 218.

Kuligowski, E. D., 2016. Human behavior in fire. SFPE Handbook of Fire Protection Engineering (pp. 2070-2114): Springer.

Kuligowski, E. D., Hoskins, B. L., 2010. Occupant behavior in a high-rise office building fire. National Institute of Standards and Technology.

Kuligowski, E. D., Mileti, D. S., 2009. Modeling pre-evacuation delay by occupants in World Trade Center Towers 1 and 2 on September 11, 2001. Fire Safety Journal, 44(4) : 487-496.

Lindell, M. K., Perry, R. W., 2004. Communicating Environmental Risk in Multiethnic Communities (Communicating Effectively in Multicultural Contexts. Sage Publications Thousand Oaks, CA.

Lindell, M. K., Perry, R. W., 2012. The protective action decision model: theoretical modifications and additional evidence. Risk Analysis: An International Journal, 32(4) : 616-632.

Lindell, M. K., Prater, C. S., 2007. A hurricane evacuation management decision support system (EMDSS). Natural Hazards, 40(3) : 627-634.

Liu, S., Murray‐Tuite, P., Schweitzer, L., 2014. Incorporating household gathering and mode decisions in large‐scale no‐notice evacuation modeling. Computer‐Aided Civil and Infrastructure Engineering, 29(2) : 107-122.

Lo, S., Liu, M., Zhang, P., Yuen, R. K., 2009. An artificial neural-network based predictive model for pre-evacuation human response in domestic building fire. Fire Technology, 45(4), 431-449.

Lovreglio, R., 2016. Modelling decision-making in fire evacuation based on random utility theory. PhD PhD Thesis, Politecnico of Bari University, Italy, pp 192.

Lovreglio, R., Borri, D., Ronchi, E., Fonzone, A., Dell’Olio, L., 2015. The need of latent variables for modelling decision-making in evacuation simulations. Paper presented at the IX International Workshop on Planning and Evaluation, Bari.

McConnell, N., Boyce, K., Shields, J., Galea, E. R., Day, R., Hulse, L., 2010. The UK 9/11 evacuation study: Analysis of survivors’ recognition and response phase in WTC1. Fire Safety Journal, 45(1) : 21-34.

Mu, H., Wang, J., Mao, Z., Sun, J., Lo, S., Wang, Q., 2013. Pre-evacuation human reactions in fires: An attribution analysis considering psychological process. Procedia Engineering, 52:290-296.

Murray, A. T., 2013. Optimising the spatial location of urban fire stations. Fire Safety Journal, 62: 64-71.

Nakatani, K., Okuyama, Y., Hasegawa, Y., Satofuka, Y., Mizuyama, T., 2013. Influence of housing and urban development on debris flow flooding and deposition. Journal of Mountain Science, 10(2) : 273-280.

Nilsson, D., Johansson, A., 2009. Social influence during the initial phase of a fire evacuation—Analysis of evacuation experiments in a cinema theatre. Fire Safety Journal, 44(1) : 71-79.

Norazahar, N., Khan, F., Veitch, B., MacKinnon, S., 2014. Human and organizational factors assessment of the evacuation operation of BP Deepwater Horizon accident. Safety science, 70 : 41-49.

Olander, J., Ronchi, E., Lovreglio, R., Nilsson, D., 2017. Dissuasive exit signage for building fire evacuation. Applied ergonomics, 59: 84-93.

Proulx, G., 1993. A stress model for people facing a fire. Journal of Environmental Psychology, 13(2) : 137-147.

Proulx, G., 1995. Evacuation time and movement in apartment buildings. Fire safety journal, 24(3) :229-246.

Purser, D. A., Bensilum, M., 2001. Quantification of behaviour for engineering design standards and escape time calculations. Safety science, 38(2) :157-182.

Ronchi, E., Nilsson, D., Gwynne, S., 2012. Modelling the impact of emergency exit signs in tunnels. Fire Technology, 48(4) : 961-988.

Ryu, Y., Kim, S., 2015. Testing the heuristic/systematic information-processing model (HSM) on the perception of risk after the Fukushima nuclear accidents. Journal of Risk Research, 18(7) : 840-859.

Sime, J. D., 1992. Human behaviour in fires: Summary report. Central Fire Brigades Advisory Council for England and Wales London.

Stein, R., Buzcu‐Guven, B., Dueñas‐Osorio, L., Subramanian, D., Kahle, D., 2013. How risk perceptions influence evacuations from hurricanes and compliance with government directives. Policy Studies Journal, 41(2) : 319-342.

Sufianto, H., Green, A. R., 2012. Urban fire situation in Indonesia. Fire Technology, 48(2), 367-387.

Trumbo, C., Meyer, M. A., Marlatt, H., Peek, L., Morrissey, B., 2014. An assessment of change in risk perception and optimistic bias for hurricanes among Gulf Coast residents. Risk analysis, 34(6) : 1013-1024.

Tsai, W. K., 2012. Emergency exit indicator and emergency exit indicating system. Google Patents.

Tyshchuk, Y., Wallace, W. A., 2013. The use of social media by local government in response to an extreme event: Del norte county, CA response to the 2011 Japan tsunami. Paper presented at the 10th International ISCRAM Conference, Baden-Baden, Germany.

Wedig, K. J., Parent, D. R., Vermaak, A., 2014. Evacuation system with sensors. Google Patents.

Xie, H., Filippidis, L., Galea, E. R., Blackshields, D., Lawrence, P. J., 2012. Experimental analysis of the effectiveness of emergency signage and its implementation in evacuation simulation. Fire and Materials, 36(5-6) : 367-382.

Xin, J., Huang, C., 2013. Fire risk analysis of residential buildings based on scenario clusters and its application in fire risk management. Fire Safety Journal, 62: 72-78.

Yamazaki, T., Tamai, H., Owada, Y., Hattori, K., Taira, S. i., Hamaguchi, K., 2016. Urban Disaster Simulation Incorporating Human Psychological Models in Evacuation Behaviors. Paper presented at the International Conference on Information Technology in Disaster Risk Reduction,Sofia,Bulgaria.

Zhang, X., 2017. Study on rapid evacuation in high-rise buildings. Engineering science and technology, an international journal, 20(3) : 1203-1210.

Zhang, Y., 2013. Analysis on comprehensive risk assessment for urban fire: The case of Haikou City. Procedia Engineering, 52: 618-623.

Zhao, C., Lo, S. M., Zhang, S., Liu, M., 2009. A post-fire survey on the pre-evacuation human behavior. Fire Technology, 45(1) : 71.

Zhu, K.-j., Shi, Q., 2016. Experimental study on choice behavior of pedestrians during building evacuation. Procedia Engineering, 135: 207-216.