Myths of Women and Their Reflection in a Therapy Group

One essential dilemma for modern clinical social work involves the relationship between the processes taking place inside the self and the social, cultural, and political developments affecting a person from the outside. The group-analysis approach focuses on four levels of relationships and communication within the group, among others a primordial level of shared myths, archetypical images, and the collective unconscious as an important component of psychotherapy. This article describes group-analysis therapy with women, analyzing a therapeutic process that used social myths to explore the formative institutionalization processes participants had undergone, thereby expanding themselves, growing, and changing.

An Experiment on the Social Facilitation of Gambling Behavior

Research and theory regarding the social facilitation effect generates the expectation that the presence of other gamblers (or co-actors) in a gaming venue is likely to intensify individual gambling behavior and magnify losses. Fifty male and 66 female participants (116 total) played a computer-simulated electronic gaming machine with a fixed winning sequence, followed by an indefinite losing sequence. Measures of the intensity of gambling behavior included the final payout (a direct measure of losses), average bet-size, number of trials played, and the speed of play. Some participants received false feedback from the computer designed to suggest that other gamers in adjacent rooms were playing and sometimes winning at the same game. Persons who received both sight and sound information, including winning bells and instant messages regarding the wins of other (fake) players, placed more bets and lost more money compared to the other conditions with less information.     

阿拉伯国家联盟决策机制研究

阿盟采取不同的决策程序和方式来满足成员国复杂的利益关系和要求,其决策机制由多种要素构成,拥有多层次决策机构.阿盟决策机制既具有自身的特点,又存在一定的缺陷.从阿盟决策机制的历史变迁、决策要素的权责分配、决策程序与方式等方面进行分析,有利于系统理解阿盟决策机制的本质,也有助于理解阿盟在阿拉伯国家间以及中阿关系中所能起到的真正作用.     

A Learning Curve Analysis of Expert System Use*

In this article, we study how an expert system affects novice problem solving in a financial risk analysis domain. We demonstrate that novice performance is improved after exposure to an expert system. Further, we show that novice performance continues to improve when the system is withdrawn. By comparing learning curves for people with exposure to those without, we can assess how much the system has benefitted its users. We demonstrate a quantitative methodology to measure the increment of learning due to the use of an information technology. We also explore the issue of how expertise is transferred from the system to the user.     

Marketing Communication Intensity Across Industries

Marketing communication intensity (i.e., the ratio of advertising and promotional expenditures to sales) has been an important topic for both business managers and academics. Here, we investigate cross-sectional and time-series variation of communication intensity due to: type of offering (product versus service) and type of market (consumer versus industrial). Overall, we find that both of these factors affect variation of communication intensity across industries and over time. However, the effect of market type is much more dramatic than the effect of offering type. Such knowledge about patterns in communication intensity levels helps managers make decisions about how much to spend on advertising and promotion.     

A Rejoinder to Forman on AHP,with Emphasis on the Requirements of Composite Ratio Scales*

In an earlier paper [11], the problems of rank reversals and invalid composite priorities in AHP were addressed by modifications to the AHP procedure. That solution was subsequently criticized [5]. In this paper, we rebut these criticisms, and we show how rank reversals in AHP can arise merely from the process of normalizing local priorities.     

Stochastic and Intransitive Behavior in a State-Preference Model of Asset Choice*

Most models of investor behavior assume a time-state independent utility function and result in a deterministic solution where a given set of inputs uniquely specifies the decision. In contrast, a state preference model using a time-state dependent utility function is derived in this paper. The model allows the investment choice decision to be analyzed in a game theoretic context. The general solution is a mixed strategy which allows for a probabilistic interpretation of the decision. The approach presented in this paper can accommodate anomalies such as intransitivity of preference and satisficing as rational behavior. An example of a possible implementation is given along with interpretations of the outcomes.     

Integrating Neural Networks and Semi-Markov Processes for Automated Knowledge Acquisition: An Application to Real-time Scheduling*

Recently, artificial neural networks (ANN) have gained attention as a promising modeling tool for building intelligent systems. A number of applications have been reported in areas varying from pattern recognition to bankruptcy prediction. In this paper, we present a creative methodology that integrates computer simulation, semi-Markov optimization, and ANN techniques for automated knowledge acquisition in real-time scheduling. The integrated approach focuses on the synergy between operations research and ANN in eliciting human knowledge, filtering inconsistent data, and building competent models capable of performing at the expert level. The new approach includes three main components. First, computer simulation is used to collect expert decisions. This step allows expert knowledge to be obtained in a non-intrusive way and minimizes the difficulties involved in interviewing experts, constructing repertory grids, or using other similar structures required for manual knowledge acquisition. The data collected from computer simulation are then optimized using a semi-Markov decision model to remove data redundancies, inconsistencies, and errors. Finally, the optimized data are used to build ANN-based expert systems. The integrated approach is evaluated by comparing it with the human expert and using ANN alone in the domain of real-time scheduling. The results indicate that ANN-based systems perform worse than human experts from whom the data were collected, but the integrated approach outperforms human experts and ANN models alone.     

The Design of a Knowledge-Based Decision Support System to Support the Information Analyst in Determining Requirements

Decision support system (DSS) researchers and designers continue to look for unstructured organizational tasks where there is a critical need for intelligent computer-based support. One such decision task is information requirements determination. Requirements determination is recognized as the most crucial phase of the systems development life cycle. Unfortunately, most methodologies and CASE tools focus only on how to specify the requirements once they are determined. There is very little computer support for the process of determining requirements. This paper discusses the conceptual design and development of a knowledge-based DSS to support information analysts in the critical decision task of determining requirements for the design of effective information systems. The expert modeling support system has the expertise to assist the analyst in studying the organization as a whole and in modeling the system under study in the context of the overall organization's goals and needs. The focus of the paper is on the problems associated with building the knowledge base component of the intelligent decision support system. A prototype implementation of the system is described.     

Fading Frames: Data Presentation and Framing Effects*

This article describes three experiments that investigate the impact of data presentation on framing, which is the differential evaluation of objectively equivalent information given different frames of reference. The experiments were designed to vary the amount of information and the format of presentation (tables versus graphs) provided to the decision maker to gain an understanding of the mechanism underlying framing. The inferred information model proposed by Johnson and Levin [11] is utilized to explain the results of the three experiments in terms of the redistribution of weights attached by the decision makers to the attributes of the prospective outcomes. The results of the three experiments indicate that framing effects are observed only when the presentation of data facilitates the shifting of weights among the attributes of the available alternatives. The results further indicate that framing is eliminated as more information is displayed. However, presentation of additional information does not eliminate framing when a graphical format is utilized. Finally, no framing effects are observed when uneven amounts of information are used to describe two alternatives in the same decision task.