An ABM model of Organizational Performance in Emergency Environments

An article in JASSS reports a model of emergency response and concludes that organisations respond more efficiently when they communicate freely at working level.

The article, by Zagorecki, Ko and Comfort, is called “Interorganizational Information Exchange and Efficiency: Organizational Performance in Emergency Environments”. The authros built “a simulated operations environment using agent-based modeling to test the efficiency of six different organizational designs that varied the exercise of authority, degree of uncertainty, and access to information. Efficiency is measured in terms of response time, identifying time as the most valuable resource in emergency response.” In other words, the model tests how quickly units respond to one of five different emergencies: “fire, transportation, utility, hazardous materials (HazMat), and explosion emergencies, moderate events that disrupt normal operations in a community. Each of these incident types has unique characteristics in terms of frequency and severity of events.” (In other words, explosions happen quickly but dont last long, whereas Hazmats may take some time to reach their full potential and even longer to clear up.

Agents simulate police, fire, emergency medical services, public works and utility companies. They can have one of six different structures – broadly, this is a different set of assumptions about information flow between Executives, Managers and Agents. Not surprisingly perhaps, the model found that “When agents are permitted to search for information more broadly and when they are more likely to share this information with other agents, the response system can react to demands more quickly.”

It also found that “efficient response does not necessarily assume controlled communication among high level officers. Our simulation results suggest that information exchange among the lowest level agents is more efficient than that among managers and executives…. Given that many emergency response organizations prefer hierarchical communication as a means of control, permitting flexible communication among lower level agents may contribute to better cooperation not only within an organization but also between jurisdictions”.

The model of course over-simplifies a lot of issues, as the authors imply: “Our simulation findings also suggest that the information capacity of individual agencies and legal constraints should be considered in designing the communication structure. Further, if the network is overloaded with information, the quality, not the quantity, of information processing will become crucial. Therefore, the contextual differences that organizations face should not be underestimated.” You cant, for instance, just turn up at a Hazmat incident – you need to know which way the wind is blowing, for example, and whilst the Fire Service may put on BA and pile in, other agencies will hang back.

But this is a worthwhile and sensible simulation (and I see it as some supporting evidence for the argument in my own paper in Simulation and Gaming, which argued that “successful large exercises help improve the nature of trust between individuals and the organizations they represent, changing it from a situational trust to a personal trust”, ie that if you know someone you can have better and more flexible
communications with them at working level, rather than having to go through the hierarchy.)

Incidentally, the authors cite an article by Miller and Moser which analyses the effect of communicaqtion on coordination between agents, and finds that “communication plays a key role in the ability of agents to reach and maintain superior coordination. In the absence of communication, agents tend to get trapped at the inferior coordination point. However, once agents reach a particular strategic threshold, sending even a priori meaningless messages serves to increase the likelihood that the population will coordinate on the superior outcome.”

Their model uses the Stag Hunt game, which they do not explain full but which Wikipedia defines thus: “two individuals go out on a hunt. Each can individually choose to hunt a stag or hunt a hare. Each player must choose an action without knowing the choice of the other. If an individual hunts a stag, he must have the cooperation of his partner in order to succeed. An individual can get a hare by himself, but a hare is worth less than a stag.”

Miller and Moser add “Note that agents were only allowed to send a priori meaningless messages and thus the meaning of the tokens had to arise endogenously via the decentralized
interactions of the agents, shaped only by indirect, adaptive pressures taking place across a time scale of several generations.” I think by this they mean that “Once both agents have selected final moves (signaled by the simultaneous emission of 0 tokens), a single-shot game is conducted using the payoffs given in Table 1. It is possible for one, or both, of the agents to not choose a final move.” In other words, even saying I have not made my mind up is useful information.

Of course in practice humans have much richer interactions – expression, gesture, tone of voice, etc. Whilst ABM modelling cant cope with all of these, the messages conveyed can be meaningfully simplified, at least in an emergency response context where subtlety is less important.

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