John Tydeman

Cross-impact analysis: Extended KSIM

Abstract The authors present an extension of Kanes cross-impact simulation model (ksim) that allows the inclusion of events and trends, and discuss the basic issues of forecasting and compatibility of forecasts.

Structuring the future—application of a scenario-generation procedure

Abstract Scenario generation is a fundamental technique of futures research. By providing a series of possible future contexts, it is a valuable tool for decision makers. A number of scenario generation procedures have been proposed and may all be appropriate in particular circumstances. These procedures differ in regard to their approach to structure, the nature of the scenario elements used, their handling of the time dimension, their approach to scenario probabilities, the scope or size of the scenarios, and a few other aspects. A number of suggested techniques are classified in regard to these characteristics and a case is described for a procedure that provides for large numbers of events and trends (over 100) in a multiperiod framework and that can produce a fairly small number of the most likely scenarios that contain a reasonable variety. An approach to this problem is described, and an application in the Western Australian Government Railway organization, Westrail, is presented.

Subjective conditional probability modelling

Abstract Cross-impact analysis is a technique for investigating the effect of interaction of events in future oriented studies. A fundamental difficulty with cross-impact analysis is to determine what respondents mean when they answer the “conditional probability” questions normally posed. This paper offers a heuristic alternative to traditional cross-impact analysis which is applicable to cross-impact situations where the object is to generate scenarios for decision making.

A note on the Kounias and Marin Method of Best Linear Bonferroni Bounds

Upper and lower probability bounds of degree two for the union (or intersection) of a sequence of n events are derived using a linear programming algorithm. The approach is compared to that suggested by Kounias and Mann and is shown to be the dual of their linear programming formulation. The new approach is simpler and more efficient.

An Interactive Computer-Based Approach to Aid Group Problem Formulation.

Abstract The size, cost, and complexity of quantitative modeling in the social and physical sciences demand that the modeler focus attention on premodeling phases of analysis, specifically on formulation and definition of “problems.” This is especially true in the “softer” or less “well-structured” problem areas of futures research and technology assessment. At this stage of modeling, a key factor is communication among modelers. This paper briefly discusses approaches to classifying and formulating problems that illustrate the role of communication in modeling. It then describes a computer-based communication system as one possible aid in the problem-formulation process.

Policy evaluation under uncertainty: An approach using subjective information

Abstract Approaches to policy analysis frequently ignore the complex, uncertain environment in which the proposals are being evaluated. An attempt is made in this article to outline a procedure which uses subjective information judgements of participants in the problem situation for including an uncertainty dimension in policy analysis. The approach is tested by way of an application to defence planning.

Health care in Australia 1980–2000☆

Abstract Subjective information, collected in this case by a modified Delphi method, can reduce uncertainty and clarify priorities for decision makers. Although Australian health care is likely to face increasing costs and a restriction of some services, a more flexible system will emerge—with community-based care, continuing professional education, and greater use of paramedical staff.