[Objective] Emergency sensemaking can control a situation by identifying the warning signs early and before the situation deteriorates further. However, the different benefit paths of multiagents in emergency sensemaking can easily lead to sensemaking failure and additional escalation of risk event losses. Therefore, it is vital to study how to influence the strategic choice of the relevant agents in sensemaking in the real world. [Methods] Based on the prospect theory-mental account, this report applied the evolutionary game model to study the following complex behavior mechanism among the multiagents in emergency sensemaking: the public (truthfully providing information or falsely providing information), frontline personnel (efficiently reporting or inefficiently reporting), and emergency command (group wisdom or group myth). According to different strategic choices, the payoff matrix is constructed, and the evolutionary replication dynamic equation is obtained using the matrix; however, the three evolutionary replication dynamic equations cannot directly determine the equilibrium point of the tripartite strategy. In this study, the Jacobian matrix is obtained by partial derivation of the forward decision probability of three differential equations, and the stability of the strategy choice of each game agent is analyzed by calculating the eigenvalues of the matrix. In order to further analyze the influence of key elements on the evolution process and results of the game. The computer simulation software MATLAB was used to establish a game model and assign initial values to each parameter in the model. The key parameters affecting the evolution path of decision-making behavior are extracted and analyzed by adjusting the initial values of the parameters. [Results] Solving the game model provides the following findings: 1) When the labor cost of frontline personnel is high, or the punishment is weak, the cost of the emergency command choosing a speculative strategy is substantially reduced. In this case, emergency sensemaking completely depends on the spontaneous behavior of the public, resulting in a lack of coordination efficiency and accurate judgment from frontline personnel and the emergency command. 2) By increasing the reward subsidies for positive decision-making by frontline personnel and increasing the penalties for negative decision-making, the signs of emergencies can be better understood and constructed by multiagents, and the emergency command can respond more rapidly. 3) When the perceived benefit of the emergency command to fully respond to the emergency is increased, the penalty of being tracked for choosing the speculative strategy is increased, and the system will stabilize at the optimal equilibrium point (1, 1, 1). 4) Simulation studies of the game model reveal that by adjusting the initial probabilities of the agents' strategies, perceptual reference points, and the intensity of punishment, the agents' strategic choices gradually tend toward positive choices. The convergence speed improves substantially with the increase of these parameters. [Conclusions] The results of this study showed that the perception of benefits influences the initial probability of the agents' strategy choice, and the initial probability of the choice is the factor that affects the agents' positive strategy choice. While expanding the incentive policy to encourage the agents' positive sensemaking behavior, the supervision and reporting measures should be increased to neglect the public interest behavior, and the corresponding agent should be severely punished. In addition to the established reward and punishment measures, subjective factors significantly influence decision-making. In practice, excellent individuals should be commended, and public welfare campaigns should be organized to reduce the perceptual reference points of income, allowing the agents to understand the necessity of emergency sensemaking work and make positive decisions spontaneously.
[1] 闪淳昌, 薛澜. 应急管理概论:理论与实践[M]. 北京:高等教育出版社, 2012.SHAN C C, XUE L. Introduction to emergency management:theory and practice[M]. Beijing:Higher Education Press, 2012. (in Chinese)
[2] LU X L, XUE L. Managing the unexpected:sense-making in the Chinese emergency management system[J]. Public Administration, 2016, 94(2):414-429.
[3] 莎日娜. 公共卫生重大风险研判机制的完善之策[J]. 领导科学, 2020(12):120-122.SHA R N. Measures to improve the mechanism of critical public health risk assessment[J]. Leadership Science, 2020(12):120-122. (in Chinese)
[4] 刘美萍. 重大突发事件网络舆情协同治理机制构建研究[J]. 求实, 2022(05):64-76, 111.LIU M P. Research on mechanism construction of collaborative governance of online public opinion on major emergencies[J]. Truth Seeking, 2022(05):64-76, 111. (in Chinese)
[5] 刘冰, 肖高飞, 晁世育. 重大突发公共卫生事件风险研判与决策模型构建研究[J]. 信息资源管理学报, 2021, 11(05):17-26, 37.LIU B, XIAO G F, CHAO S Y. Research on the construction of risk assessment and decision-making model of major public health emergency[J]. Journal of Information Resources Management, 2021, 11(05):17-26, 37. (in Chinese)
[6] 王剑, 司徒陈麒, 袁胜强. 基于多主体和前景理论的应急风险决策仿真研究[J]. 系统仿真学报, 2020, 32(03):353-361.WANG J, SITU C Q, YUAN S Q. Research on emergency risk decision simulation based on multi-agent and prospect theory[J]. Journal of System Simulation, 2020, 32(03):353-361. (in Chinese)
[7] 新华社. 国务院调查报告揭示青岛输油管道泄漏事故教训[EB/OL]. (2014-01-11)[2023-01-05]. https://www.gov.cn/govweb/jrzg/2014-01/11/content_256465
[8]南京邮电大学通达学院纪委办公室. 以案为鉴:近期疫情防控工作不力被问责的典型案例[EB/OL]. (2022-04-20)[2023-02-27]. https://jw.nytdc.edu.cn/2022/0420/c314a26376/pagem.htm. Office of Discipline Commission of Tongda College of Nanjing University of Posts and Telecommunications. Taking the case as a reminder:A typical case of accountability for ineffective epidemic prevention and control[EB/OL]. (2022-04-20)[2023-02-27]. https://jw.nytdc.edu.cn/2022/0420/c314a26376/ pagem. htm. (in Chinese)
[9]COMBE I A, CARRINGTON D J. Leaders' sensemaking under crises:Emerging cognitive consensus over time within management teams[J]. The Leadership Quarterly, 2015, 26(3):307-322.
[10]COMFORT L K, HAASE T W. Communication, coherence, and collective action:The impact of hurricane Katrina on communications infrastructure[J]. Public Works management & policy, 2006, 10(4):328-343.
[11]吕孝礼, 付帅泽, 朱宪, 等.突发事件协同研判行为研究:研究进展与关键科学问题[J]. 中国科学基金, 2020, 34(6):693-702. LV X L, FU S Z, ZHU X, et al. Joint crisis sensemaking:A review and research agenda[J]. Bulletin of National Natural Science Foundation of China, 2020, 34(6):693-702. (in Chinese)
[12]刘冰, 肖高飞, 霍亮. 重大突发疫情风险研判与决策柔性协同机制研究:基于信息聚合与知识发现[J]. 图书与情报, 2021(05):1-8. LIU B, XIAO G F, HUO L. Research on flexible collaboration mechanism of risk assessment and decisionmaking for major epidemics:Based on information aggregation and knowledge discovery[J]. Library & Information, 2021(05):1-8. (in Chinese)
[13]European Centre for Disease Prevention and Control.Operational tool on rapid risk assessmentmethodology-ECDC 2019[EB/OL]. (2019-03-14)[2023-08-28]. https://ecdc.europa.eu/en/publications-data/operational-tool-rapid-risk-assessment-methodology-ecdc-2019.
[14]白羽轩. 双信度下考虑专家风险态度和研判调整行为的群体性突发事件等级确定方法[D]. 大连:大连理工大学, 2022. BAI Y X. A method for determining the level of mass emergencies considering experts' risk attitude and adjustment behavior under double reliability[D]. Dalian:Dalian University of Technology, 2020. (in Chinese)
[15]赫伯特·A.西蒙. 管理决策新科学[M]. 李柱流, 汤俊澄, 译. 北京:中国社会科学出版社, 1982. SIMON H A. The new science of management decision[M]. LI Z L, TANG J C, Trans. Beijing:China Social Sciences Press, 1982. (in Chinese)
[16]KAHNEMAN D, TVERSKY A. Prospect theory:An analysis of decision under risk[M]//MACLEAN L C, ZIEMBA W T. Handbook of the Fundamentals of Financial Decision Making. Hackensack:World Scientific Publishing, 2013:99-127.
[17] 胡欢, 郭晓剑, 梁雁茹. 基于前景理论的重大疫情网络谣言管控三方演化博弈分析[J]. 情报科学, 2021, 39(07):45-53.HU H, GUO X J, LIANG Y R. Game analysis of the three-way evolution of network rumor control under the major epidemic based on prospect theory[J]. Information Science, 2021, 39(07):45-53. (in Chinese)
[18] THALER R. Mental accounting and consumer choice[J]. Marketing Science, 1985, 4(3):199-214.
[19] ZHAO H, LIU X, WANG Y T. Tripartite evolutionary game analysis for rumor spreading on Weibo based on MA-PT[J]. IEEE Access, 2021, 9:90043-90060.
[20] 张子鸣, 王新平, 苏畅. 差序氛围视角下知识型矿工安全行为研究——基于PT-MA理论的演化博弈分析[J]. 安全与环境工程, 2022, 29(06):1-9.ZHANG Z M, WANG X P, SU C. Research on the safety behavior of knowledge miners from the perspective of chaxu climate-An evolutionary game analysis based on PT-MA theory[J]. Safety and Environmental Engineering, 2022, 29(06):1-9. (in Chinese)
[21] 庄丽, 马婷婷, 刘硕, 等. 基于PT-MA理论的装配式建筑施工安全管理行为演化博弈分析[J]. 工业工程, 2021, 24(02):68-76, 11; 8. ZHUANG L, MA T T, LIU S, et al. An evolutionary game analysis of behaviors management of prefabricated building safety groups based on PT-MA theory[J]. Industrial Engineering Journal, 2021, 24(02):68-76, 118. (in Chinese)
[22] ZHANG Z M, WANG X P, SU C, et al. Evolutionary game analysis of shared manufacturing quality synergy under dynamic reward and punishment mechanism[J]. Applied Sciences, 2022, 12(13):6792.
[23] WU B, CHENG J, QI Y Q. Tripartite evolutionary game analysis for "Deceive acquaintances" behavior of e-commerce platforms in cooperative supervision[J]. Physica A:Statistical Mechanics and Its Applications, 2020, 550:123892.
[24] 马婷婷. 基于前景理论的建筑施工安全群体行为演化博弈分析[D]. 青岛:青岛理工大学, 2020.MA T T. Evolutionary game analysis of construction safety group behavior based on prospect theory[D]. Qingdao:Qingdao University of Technology, 2020. (in Chinese)
[25] FRIEDMAN D. On economic applications of evolutionary game theory[J]. Journal of Evolutionary Economics, 1998, 8(1):15-43.
[26] TVERSKY A, KAHNEMAN D. Advances in prospect theory:Cumulative representation of uncertainty[J]. Journal of Risk and Uncertainty, 1992, 5(4):297-323.
[27] GUREVICH G, KLIGER D, LEVY O. Decision-making under uncertainty-A field study of cumulative prospect theory[J]. Journal of Banking & Finance, 2009, 33(7):1221-1229.
[28] HEINRICH H W, PETERSON D, ROOS N. Industrial accident prevention[M]. New York:Mcgraw-Hill Book Company, 1980.
