Probabilistic Risk Analysis and Terrorism Risk

Since the terrorist attacks of September 11, 2001, and the subsequent establishment of the U.S. Department of Homeland Security (DHS), considerable efforts have been made to estimate the risks of terrorism and the cost effectiveness of security policies to reduce these risks. DHS, industry, and the academic risk analysis communities have all invested heavily in the development of tools and approaches that can assist decisionmakers in effectively allocating limited resources across the vast array of potential investments that could mitigate risks from terrorism and other threats to the homeland. Decisionmakers demand models, analyses, and decision support that are useful for this task and based on the state of the art. Since terrorism risk analysis is new, no single method is likely to meet this challenge. In this article we explore a number of existing and potential approaches for terrorism risk analysis, focusing particularly on recent discussions regarding the applicability of probabilistic and decision analytic approaches to bioterrorism risks and the Bioterrorism Risk Assessment methodology used by the DHS and criticized by the National Academies and others.     

An Introduction to Joint Control

Lowenkron and colleagues (Lowenkron, 1984; 1991; 1998; 2006; Lowenkron and Colvin, 1992) describe a model that explains complex behavior using only well-established behavioral principles, concepts and terms. The model, called joint control, is especially useful for understanding complex and delayed discriminations within a purely behavioral framework and with no appeal to hypothetical concepts or structures. In it the listener is an active behaver rather than a processor of information. In fact, on this account the listener becomes a speaker. Several examples of the relevance of this approach to the explanation of complex behavior are provided, including cases of stimulus selection, conditional discrimination, and generalized identity matching.     

A Longitudinal Analysis of Immigrant Occupational Mobility: A Test of the Immigrant Assimilation Hypothesis1

This article develops a model of the occupational mobility of immigrants and tests the hypotheses using data on males from the Longitudinal Survey of Immigrants to Australia, Panel I. The theoretical model generates hypotheses regarding a U‐shaped pattern of occupational mobility from the “last job” in the origin, to the “first job” in the destination, to subsequent jobs in the destination, and regarding the depth of the “U.” The survey includes data on pre‐immigration occupation, the “first” occupation in Australia (at six months) and the occupation after about three‐and‐a‐half years in Australia. The hypotheses are supported by the empirical analysis.     

Geography of Twitter networks

The paper examines the influence of geographic distance, national boundaries, language, and frequency of air travel on the formation of social ties on Twitter, a popular micro-blogging website. Based on a large sample of publicly available Twitter data, our study shows that a substantial share of ties lies within the same metropolitan region, and that between regional clusters, distance, national borders and language differences all predict Twitter ties. We find that the frequency of airline flights between the two parties is the best predictor of Twitter ties. This highlights the importance of looking at pre-existing ties between places and people.     

Marketing: The prospects for the 1980s

The article describes a research project whose purpose was to investigate the operating environment of the 1980s for the marketing executive and the strategic responses appropriate to that environment. The survey found that marketing executives were optimistic in their view of the future decade but felt the need for greater precision in marketing strategies to deal with the attendant high risks.