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Time lag and communication in changing unpopular norms.

ABSTRACT: Humans often coordinate their social lives through norms. When a large majority of people are dissatisfied with an existing norm, it seems obvious that they will change it. Often, however, this does not occur. We investigate how a time lag between individual support of a norm change and the change itself hinders such change, related to the critical mass of supporters needed to effectuate the change, and the (im)possibility of communicating about it. To isolate these factors, we utilize a laboratory experiment. As predicted, we find unambiguous effects of time lag on precluding norm change; a higher threshold for a critical mass does so as well. Communication facilitates choosing superior norms but it does not necessarily lead to norm change when the uncertainty on whether there will be a norm change in the future is high. Communication seems to help coordination on actions at the present but not the future. Hence, the uncertainty driven by time lag makes individuals choose the status quo, here the unpopular norm.

SUBMITTER: Gerxhani K

PROVIDER: S-EPMC4399934 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Time lag and communication in changing unpopular norms.

Gërxhani Klarita K Bruggeman Jeroen J

PloS one 20150416 4

Humans often coordinate their social lives through norms. When a large majority of people are dissatisfied with an existing norm, it seems obvious that they will change it. Often, however, this does not occur. We investigate how a time lag between individual support of a norm change and the change itself hinders such change, related to the critical mass of supporters needed to effectuate the change, and the (im)possibility of communicating about it. To isolate these factors, we utilize a laborat ...[more]

PMID: 25880200

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Project description:BackgroundIn microsimulation models of diseases with an early, acute phase requiring short cycle lengths followed by a chronic phase, fixed short cycles may lead to computational inefficiency. Examples include epidemic or resource constraint models with early short cycles where long-term economic consequences are of interest for individuals surviving the epidemic or ultimately obtaining the resource. In this article, we demonstrate methods to improve efficiency in such scenarios. Furthermore, we show that care must be taken when applying these methods to epidemic or resource constraint models to avoid bias.MethodsTo demonstrate efficiency, we compared the model runtime among 3 versions of a microsimulation model: with short fixed cycles for all states (FCL), with dynamic cycle length (DCL) defined locally for each state, and with DCL features plus a discrete-event-like hybrid component. To demonstrate bias mitigation, we compared discounted lifetime costs for 3 versions of a resource constraint model: with a fixed horizon where simulation stops, with a fixed entry horizon beyond which new individuals could not enter the model, and with a fixed entry horizon plus a mechanism to maintain a constant level of competition for the resource after the horizon.ResultsThe 3 versions of the microsimulation model had average runtimes of 515 (95% credible interval [CI]: 477 to 545; FCL), 2.70 (95% CI: 1.48 to 2.92; DCL), and 1.45 (95% CI: 1.26 to 2.61; DCL-pseudo discrete event simulation) seconds, respectively. The first 2 resource constraint versions underestimated costs relative to the constant competition version: $20,055 (95% CI: $19,000 to $21,120), $27,030 (95% CI: $24,680 to $29,412), and $33,424 (95% CI: $27,510 to $44,484), respectively.LimitationsThe magnitude of improvements in efficiency and reduction in bias may be model specific.ConclusionChanging time representation in microsimulation may offer computational advantages.HighlightsShort cycle lengths may be required to model the acute phase of an illness but lead to computational inefficiency in a subsequent chronic phase in microsimulation models.A solution is to create state-specific cycle lengths so that cycle lengths change dynamically as the simulation progresses.Computational efficiency can be enhanced further by using a hybrid model containing discrete-event-simulation-like features.Hybrid models can efficiently handle events subsequent to exit from an epidemic or resource constraint model provided steps are taken to mitigate potential bias.

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Time lag and communication in changing unpopular norms.

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Time lag and communication in changing unpopular norms.

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