The Influence of Functional Experience on Perceptions of Strategic Priorities

This paper reviews three previous studies of functional bias (Dearborn and Simon, 1958; Walsh, 1988; Nystrom, 1991) which have produced conflicting evidence. The results of a study into functional bias in perceptions of strategic priorities are presented. These results, which provide evidence of functional bias, are discussed and some suggestions for future research are made.     

Differences in Managerial Cognitions of Competition1

It has been assumed that strategic decision making and implementation are both achieved through managers' sharing homogeneous cognitions of competition (e.g. Porac and Thomas, 1990). This paper tested the assumption of homogeneity of cognitions of competition, using a sample of 24 managers from the off-shore pumps industry. A variety of cognitive mapping techniques were used and maps were compared using a self-rating methodology. The results indicated that managers' mental models of competition are diverse, rather than homogeneous, but that this diversity increases as company boundaries are crossed and as functional boundaries are crossed. Therefore, it is concluded that future cognitive studies of competitive industry structures should assume diversity of cognitions rather than homogeneity. Specific propositions with regard to such research are drawn from the findings.     

Retirement financial preparation:implications for policy

Financial preparation for retirement is key to positive outcomes for future cohorts. Studies suggest that insufficient preparation is occurring among Baby Boomers. Data from community-dwelling adults (N = 1508, ages 40-70) show that most respondents (22-75%) had taken four specific preparation steps, and few reported negative attitudes toward planning. Five correlates (gathering information, locus of control, self-definition as household planner, financial worries, and negative attitudes) and demographic variables tested in bivariate analyses showed most having associations with preparation. In multivariate analyses, however, only two correlates (gathering information and negative planning attitudes) and demographics (race/ethnicity, education, income, health, age, and education) explained planning behavior.     

Updating Uncertainty in an Integrated Risk Assessment: Conceptual Framework and Methods

Bayesian methods are presented for updating the uncertainty in the predictions of an integrated Environmental Health Risk Assessment (EHRA) model. The methods allow the estimation of posterior uncertainty distributions based on the observation of different model outputs along the chain of the linked assessment framework. Analytical equations are derived for the case of the multiplicative lognormal risk model where the sequential log outputs (log ambient concentration, log applied dose, log delivered dose, and log risk) are each normally distributed. Given observations of a log output made with a normally distributed measurement error, the posterior distributions of the log outputs remain normal, but with modified means and variances, and induced correlations between successive log outputs and log inputs. The analytical equations for forward and backward propagation of the updates are generally applicable to sums of normally distributed variables. The Bayesian Monte-Carlo (BMC) procedure is presented to provide an approximate, but more broadly applicable method for numerically updating uncertainty with concurrent backward and forward propagation. Illustrative examples, presented for the multiplicative lognormal model, demonstrate agreement between the analytical and BMC methods, and show how uncertainty updates can propagate through a linked EHRA. The Bayesian updating methods facilitate the pooling of knowledge encoded in predictive models with that transmitted by research outcomes (e.g., field measurements), and thereby support the practice of iterative risk assessment and value of information appraisals.