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 Further, we show that novice performance continues to improve when the system is withdrawn.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.     

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.     

A Comment on Second-Order Polynomial Regression Models

In a recent article, Chatterjee and Greenwood [1] addressed the problem of multicollinearity in polynomial regression models. They noted that there is a high correlation between X and X²; therefore, a second-order polynomial model suffers the consequences of collinearity. Chatterjee and Greenwood [1] suggested a method they believe will overcome the problem. The contention of the present comment is that the suggested method accomplishes nothing and, indeed, has the potential to lead the unwary researcher to the wrong inference and misinterpretation of his results.     

A VARIANCE-REDUCTION STRATEGY FOR RSM SIMULATION STUDIES

The application of optimization techniques in digital simulation experiments is frequently complicated by the presence of large experimental error variances. Two of the more widely accepted design strategies for the resolution of this problem include the assignment of common pseudorandom number streams and the assignment of antithetic pseudorandom number streams to the experimental points. When considered separately, however, each of these variance-reduction procedures has rather restrictive limitations. This paper examines the simultaneous use of these two techniques as a variance-reduction strategy in response surface methodology (RSM) analysis of simulation models. A simulation of an inventory system is used to illustrate the application and benefits of this assignment procedure, as well as the basic components of an RSM analysis.     

MARKET PENETRATION AND LOCATIONAL CONFLICT IN FRANCHISE SYSTEMS*

This paper addresses the questions of market penetration and locational conflict in a franchise system of distribution. The models developed provide a means to evaluate alternative scenarios and the effects of various franchise policies. It is shown that the market penetration and location goals of the members of a franchise system coincide only under a very limited set of circumstances.     

出口贸易与省域TFP空间维度分析

作为衡量一国科技进步的重要指标,全要素生产率的高低决定着一国生产率水平的先进与落后。在不断深化改革开放的过程中,如何利用开放倒逼我国技术水平的提高成为一项较为紧迫的任务。为此,我们运用面板DEA-Malmquist指数法可以测算出2002—2011年我国29个省份(含自治区、直辖市)全要素生产率,并在此基础上建立空间面板数据模型(SPDM),实证分析出口贸易、基础设施等对我国省域全要素生产率及其空间溢出效应的影响。经研究发现,我国省域全要素生产率存在较为明显的空间自相关性,即出口贸易、基础设施等经济活动通过影响本省TFP,并通过空间溢出效应进一步将其作用传递和迭加到邻近省域全要素生产率上,基础设施对我国省域全要素存在较为显著的负向关系,出口依存度、出口贸易及FDI对我国省域全要素生产率具有显著的推动作用。     

中国各地区市场化进程区位分布的空间效应研究

 本文从空间分析的角度研究各地区市场化进程的空间效应及其对区域经济增长绩效的影响,空间计量经济分析的结果表明市场化进程的空间分布在整个样本区间与GDP、资本和劳动一样呈现出集聚的趋势,区域差异显著,各地区的市场化进程在地理空间上存在显著的自相关关系,证实了各地区市场化进程存在制度溢出效应。因此,在研究各地区市场化进程与经济增长关系时必须考虑其空间效应的影响,基于此结论本文运用空间计量模型测算了各地区市场化进程对经济增长的贡献。结果证实,考虑了空间效应后,市场化进程在1998～2001年阶段对经济增长的贡献约为6.2％,在2002～2005年阶段约为10.8％,这表明了市场化对中国的经济增长起到了重要的作用,而且近年来的贡献愈加显著。     

Characterization of Unacceptable Solutions in LP Discriminant Analysis*

Many linear programming models have been proposed for performing discriminant analysis. Partial characterizations for unacceptable solutions have been presented and new models proposed to circumvent these problems. In this paper those conditions leading to unacceptable solutions for all two-group models are characterized.     

Modeling Synergy and Learning under Multiple Advanced Manufacturing Technologies

The advent of the wide variety of new, highly integrated, advanced manufacturing technologies available for acquisition by a firm's managers has brought to light an accompanying set of unexpected issues. These issues include expectations for the benefits and costs of these technologies, determining the appropriate order of implementation and finding a way to justify acquisition when many of the benefits are a function of the technology's learning and synergistic effects on other operations and technologies. We present here a model that captures the interaction effects of these highly integrated technologies and discuss the data requirements for application of the construct. We then illustrate the model's workings with a number of multitechnology examples and show the danger of ignoring the synergistic and learning effects of these technologies when considering their acquisition.