Consumer processing of hazard warning information

Using data obtained from a field experiment involving 957 consumers, this study investigates the linkage between hazard warnings and precautionary behavior, as well as the structure of the information about product usage and risks that consumers store in their memories. Through the use of a methodology based on an open-ended memory recall task, we measure how consumer recall of information on product labels is affected by the type and format of the information and infer the structure by which this information is stored in their memory. The methodology also allows us to explore the importance of limitations on consumers' cognitive abilities. In particular, we find that consumers substitute greater recall of risk information for recall of usage information, indicating a tradeoff among the different types of information conveyed on a product label. We also found that in the case of cluttered labels, as typified by many existing product labels, information overload results, which may make labeling ineffective in achieving its intended informational objective.     

Maximum and Minimum Prediction Variance for Spherical and Cuboidal Split Plot Designs

The impact of restricted randomization on the information matrix has created challenges for the computation of design optimality criteria. This article focuses on the computation of the maximum and minimum prediction variance for Central Composite (CCD) and Box–Behnken (BBD) split plot designs (SPD). The approach is to analytically determine the exact maximum and minimum prediction variance for both spherical and cuboidal second-order SPD. A particular feature of these analytical functions is that they are functions of the design parameters. Finally, the application of these analytical functions is demonstrated for a CCD SPD.     

LOCUS OF CONTROL,TRUST, AND DECISION MAKING*

A theoretical connection was proposed between certain social personality variables, namely locus of control (Internal or External) and trust (High and Low) and the formal decision-making model of Subjective Expected Utility (SEU). Rather than adopting the traditional definition of these variables as “generalized expectancies” for behavior of self and others, locus of control and trust were reconceptualized as intrapersonal tendencies to favor, prefer, or otherwise bias the subjective probabilities entering into a decision computation. S's high in external control orientation did not differ from internals overall, but external males were more risk averse under certain choice conditions (female-sex-role appropriate dilemma, probability-estimate form). Low-trust S's were also more risk averse than high-trust S's, overall. Low-trust males generated maximally risk-averse choice solutions under the choice condition of feminine role problem appropriateness and probability estimation. In general, female S's made choices that were more consistent with SEU-predicted solutions than males.     

Policy Learning for Flood Mitigation: A Longitudinal Assessment of the Community Rating System in Florida

Floods continue to inflict the most damage upon human communities among all natural hazards in the United States. Because localized flooding tends to be spatially repetitive over time, local decisionmakers often have an opportunity to learn from previous events and make proactive policy adjustments to reduce the adverse effects of a subsequent storm. Despite the importance of understanding the degree to which local jurisdictions learn from flood risks and under what circumstances, little if any empirical, longitudinal research has been conducted along these lines. This article addresses the research gap by examining the change in local flood mitigation policies in Florida from 1999 to 2005. We track 18 different mitigation activities organized into four series of activities under the Federal Emergency Management Agency's (FEMA) Community Rating System (CRS) for every local jurisdiction in Florida participating in the FEMA program on a yearly time step. We then identify the major factors contributing to policy changes based on CRS scores over the seven-year study period. Using multivariate statistical models to analyze both natural and social science data, we isolate the effects of several variables categorized into the following groups: hydrologic conditions, flood disaster history, socioeconomic and human capital controls. Results indicate that local jurisdictions do in fact learn from histories of flood risk and this process is expedited under specific conditions.