A Simulation Study of Human Risk Infection Behavior in Airport Flight Area

doi:10.3969/j.issn.1007-7375.e17-3031

Abstract

Abstract:

A dynamic model of human risk infection behavior in airport flight area is constructed by the factors such as the change rate, the susceptibility coefficient (the exposure coefficient, the genetic immunity) and the ratio of sharp attitude group in order to explore the change law of human risk infection behavior and to control the risk factors scientifically and reasonably. Genetic immunity is composed of four parts:physiological state, psychological state, business skills and interpersonal relationship of the staff. Matlab software is used to simulate the variation of the average attitude of the system with different factors. The results show that the initial attitude of the system determines the average attitude tendency of equilibrium state. And the effects of exposure coefficient and genetic immunity on the average attitude change are different under different initial attitudes. The higher the proportion of the sharp attitude group in the system, the slower the average attitude tends to balance. The conclusion provides the theoretical basis for the risk control strategy of the system under different initial conditions.

Key words: human risk, risk infection behavior, airport flight area, imitation infection

CLC Number:

X923

TANG Xinxin, LUO Fan. A Simulation Study of Human Risk Infection Behavior in Airport Flight Area[J]. Industrial Engineering Journal , 2017, 20(4): 108-115.

References

[1] 李宁. 群体心理学[M]. 广州: 暨南大学出版社, 2000: 6-7.
[2] 古斯塔夫·勒庞. 乌合之众——大众心理研究[M]. 冯克利, 译. 北京: 中央编辑出版社, 2000: 15-38.
[3] LADLEY D. Contagion and risk-sharing on the inter-bank market[J]. Journal of Economic Dynamics & Control, 2013, 37(7): 1384-1400.
[4] 陈庭强, 何建敏. 基于复杂网络的信用风险传染模型研究[J]. 软科学, 2014, 28(2): 111-117.CHEN Tingqiang, HE Jianmin. Credit risk contagion model based on complex network[J]. Soft Science, 2014, 28(2): 111-117.
[5] 谢赤, 王彭, 杨姣姣, 等. 基于DCC-MSV-KMV模型的第三产业行业信用风险传染效应度量[J]. 湖南大学学报(自然科学版), 2013, 40(10): 111-116.XIE Chi, WANG Peng, YANG Jiaojiao, et al. Measurement of the credit risk contagion effects between the sectors in the tertiary industry based on DCC-MSV-KMV model[J]. Journal of Hunan University (Natural Sciences), 2013, 40(10): 111-116.
[6] BOWEN F, BLACKMON K. Spirals of silence: the dynamic effects of diversity on organizational voice[J]. Journal of Management Studies, 2003, 40(6): 1393-1417.
[7] FELPS W, MITCHELL T R, BYINGTON E. How, when, and why bad apples spoil the barrel: negative group members and dysfunctional groups[J]. Research in Organizational Behavior, 2006, 27: 181-230.
[8] HASHIM J, WOK S, GHAZALI R. Organisational behaviour associated with emotional contagion among direct selling members[J]. Direct Marketing: An International Journal, 2008, 2(3): 144-158.
[9] HOBFOLL S E. Social and psychological resources and adaptation[J]. Review of General Psychology, 2002, 6(4): 307-324.
[10] HIES R I, WAGNER D T, MORGESON F P. Explaining affective linkages in teams: individual difference in susceptibility to contagion and individualism-collectivism[J]. Journal of Applied Psychology, 2007, 92(4): 1140-1148.
[11] BONO J E, ILIES R. Charisma, positive emotions and mood contagion[J]. The Leadership Quarterly, 2006, 17(4): 317-334.
[12] 殷雁君, 唐卫清, 李蔚清. 基于社会网络的群体情绪模型[J]. 计算机应用研究, 2015, 32(1): 80-84.YIN Yanjun, TANG Weiqing, LI Weiqing. Emotion modeling of crowd based on social network[J]. Application Research of Computers, 2015, 32(1): 80-84.
[13] 王雷. 基于系统动力学的群体情绪传播机制与影响因素研究[D]. 北京: 首都师范大学, 2013.WANG Lei. Study on the communication mechanism and influencing factors of group emotion based on system dynamics[D]. Beijing: Capital Normal University, 2013.
[14] 于力鹏, 刘箴, 刘婷婷, 等. 一种基于速度采样的恐慌人群情绪感染模型[J]. 计算机应用研究, 2015, 32(10): 3171-3178.YU Lipeng, LIU Zhen, LIU Tingting, et al. Sampling speed based emotion contagion model for panic crowd[J]. Application Research of Computers, 2015, 32(10): 3171-3178.
[15] 熊国强, 赵昕. 耦合情绪因素的群体性突发事件SD模型与演化仿真[J]. 系统工程, 2016, 34(5): 112-120.XIONG Guoqiang, ZHAO Xin. The system dynamics model and evolution simulation on coupling-emotional group events[J]. Systems Engineering, 2016, 34(5): 112-120.
[16] 邓欢, 胡平, 李振兴. 情绪模仿在情绪感染中的作用: 重读模仿-反馈机制[J]. 中国临床心理学杂志, 2016, 24(2): 225-228.DENG Huan, HU Ping, LI Zhenxing. The role of emotional mimicry in emotional contagion: re-reading the mechanism of mimicry-feedback[J]. Chinese Journal of Clinical Psychology, 2016, 24(2): 225-228.
[17] 王春雪, 吕淑然, 杨凯. 突发事件中恐惧情绪感染概率研究[J]. 中国安全科学学报, 2015, 25(9): 14-19.WANG Chunxue, LYU Shuran, YANG Kai. Research on probability of fear contagion in emergency[J]. China Safety Science Journal, 2015, 25(9): 14-19.
[18] 陶锋, 邢会歌. 创新与模仿行为的进化博弈分析[J]. 科技进步与对策, 2008, 25(11): 35-37.TAO Feng, XING Huige. An evolutionary game analysis of innovation and imitative behavior[J]. Science & Technology Progress and Policy, 2008, 25(11): 35-37.
[19] 肖欣荣, 刘健, 赵海健. 机构投资者行为的传染——基于投资者网络视角[J]. 管理世界, 2012(12): 35-45.XIAO Xinrong, LIU Jian, ZHAO Haijian. Contagion of institution investor behavior[J]. Management World, 2012(12): 35-45.
[20] CHIANG T C, ZHENG D. An empirical analysis of herd behavior in global stock markets[J]. Journal of Banking & Finance, 2010, 34(8): 1911-1921.
[21] 段冀阳. 驾驶员的跟驰风险错觉与无意识行为模仿[D]. 北京: 清华大学, 2012.DUAN Jiyang. Driver’s risk illusions in car following and unconscious imitation behavior[D]. Beijing: Tsinghua University, 2012.
[22] 沈洪涛, 苏亮德. 企业信息披露中的模仿行为研究[J]. 南开管理评论, 2012, 15(3): 82-90.SHEN Hongtao, SU Liangde. A study on the imitation in corporate information disclosure: based on institutional theory[J]. Nankai Business Review, 2012, 15(3): 82-90.