Productive Efficiency of the Swine Industry in Hawaii: Stochastic Frontier vs. Data Envelopment Analysis

Improving productive efficiency is an increasingly important determinant of the future of the swine industry in Hawaii. This paper examines the productive efficiency of a sample of swine producers in Hawaii by estimating a stochastic frontier production function and the constant returns to scale (CRS) and variable returns to scale (VRS) output-oriented DEA models. The technical efficiency estimates obtained from the two frontier techniques are compared. The scale properties are also examined under the two approaches. The industry's potential for increasing production through improved efficiency is also discussed.     

Aspects of statistical analysis in DEA-type frontier models

In Grosskopf (1995) and Banker (1995) different approaches and problems of statistical inference in DEA frontier models are presented. This paper focuses on the basic characteristics of DEA models from a statistical point of view. It arose from comments and discussions on both papers above. The framework of DEA models is deterministic (all the observed points lie on the same side of the frontier), nevertheless a stochastic model can be constructed once a data generating process is defined. So statistical analysis may be performed and sampling properties of DEA estimators can be established. However, practical statistical inference (such as test of hypothesis, confidence intervals) still needs artifacts like the bootstrap to be performed. A consistent bootstrap relies also on a clear definition of the data generating proces and on a consistent estimator of it: The approach of Simar and Wilson (1995) is described. Finally, some trails are proposed for introducing stochastic noise in DEA models, in the spirit of the Kneip-Simar (1995) approach.     

Localized Innovation and Productivity Growth in Asia: An Intertemporal DEA Approach

Recent contributions to growth theory stress the importance of localized innovation for the performance of more backward countries. In earlier papers, analyses by means of DEA techniques confirmed this intuition. In this paper, we extend this type of analysis by relaxing the macroeconomic viewpoint adopted until now. New databases on output, labor and capital input in the agricultural and manufacturing sectors are developed for 40 countries. Using intertemporal DEA, it is found that changes in the global production frontier are localized at high levels of capital intensity. This result is stronger in agriculture than in manufacturing. Further, a decomposition of labor productivity growth in eight Asian countries for the period 1975–1992 into the effects of capital intensification, learning and innovation is made. The results suggest that there is a particular development path in which increases in capital intensity appear to be a prerequisite to benefit from international technology spillovers.JEL Classification: O14, O30, O40, O47     

危险品运输及其决策支持系统研究

参考了20世纪80年代以来有关危险品运输风险分析与决策支持系统的主要研究文献,总结和介绍了风险评估的标准、决策支持系统的主要框架,以及GIS等现代信息技术在危险品运输管理中的应用。     

从供需层面看中国第三方物流问题

随着中国经济的发展，提供第三方物流服务的物流公司纷纷涌现出来。同时，与第三方物流相关的一些问题也随之出现．针对这种情况．我们建立了第三方物流经济模型，从供需层面来分析中国第三方物流中存在的问题．找出问题存在的根本原因，并且对物流企业的建设提出一些建议和解决方案。     

Lower Bound Restrictions on Intensities in Data Envelopment Analysis

We propose an extension to the basic DEA models that guarantees that if an intensity is positive then it must be at least as large as a pre-defined lower bound. This requirement adds an integer programming constraint known within Operations Research as a Fixed-Charge (FC) type of constraint. Accordingly, we term the new model DEA_FC. The proposed model lies between the DEA models that allow units to be scaled arbitrarily low, and the Free Disposal Hull model that allows no scaling. We analyze 18 datasets from the literature to demonstrate that sufficiently low intensities—those for which the scaled Decision-Making Unit (DMU) has inputs and outputs that lie below the minimum values observed—are pervasive, and that the new model ensures fairer comparisons without sacrificing the required discriminating power. We explain why the low-intensity phenomenon exists. In sharp contrast to standard DEA models we demonstrate via examples that an inefficient DMU may play a pivotal role in determining the technology. We also propose a goal programming model that determines how deviations from the lower bounds affect efficiency, which we term the trade-off between the deviation gap and the efficiency gap.     

Optimising a Probabilistic Model of the Development of Play in Soccer

We present a probabilistic model based on the one developed by Hernández Mendo and Anguera (Revista de Psicologíca Social, 16(1), 71–93, 2001). Here we have tried to break down the interaction contexts that the opposing teams are able to generate and transform during the game. We are aware that a given player or team does not produce consistent behaviour in similar situations. However, a degree of uncertainty is assumed to exist regarding whether the results obtained are a specific function of the analysis used. In order to carry out this research a category system which optimized that used in the previous model was developed. This system should enable the interaction between teams to be observed within the actual play of a soccer game. A lag sequential analysis was performed on the basis of a coding of the behavioural flow. After describing the behavioural patterns obtained a probabilistic model of the development of play in soccer is proposed.     

基于顾客导向的物流企业风险预警

文中通过回顾企业风险预警管理相关文献,分析了物流企业风险形成主要影响因素,并结合物流企业运营特征,建立基于顾客导向的物流企业预警指标体系,运用灰关联分析方法评价物流企业顾客满意度,对物流企业的风险进行预警。     

Preventing HIV in injection drug users: exploring the tradeoffs between interventions

Injection drug users (IDUs) transmit the human immunodeficiency virus (HIV) via both needle sharing and sex. Available interventions for this population have varying costs and effectiveness and focus on different risk behaviors. In this analysis, we look at two interventions. One is inexpensive, broad-based and provides modest risk reductions (street outreach (SO)); the other is narrowly focused, expensive and relatively effective (methadone maintenance). This analysis explores the effects of population risk behavior, intervention effectiveness, intervention costs, and decision constraints when allocating funds between these two interventions to maximize effectiveness. We develop a model of the spread of HIV, dividing IDUs into susceptibles (uninfected) and infectives, and separately portraying sex and injection risk. We simulate the epidemic in New York City for time periods from the mid-1980s to the early 1990s, and incorporate the behavioral effects of two interventions performed singly or in combination to find the allocation that maximizes the number of infections averted in the IDUs and their noninjecting sex partners, assuming interventions have increasing marginal costs. We find that the optimal allocation nearly always involves spending the maximum allowable amount on SO. This result is largely insensitive to variations in risk parameters, intervention efficacy, or cost. The model's structure, however, makes clear that many factors contribute to this insensitivity, namely the scope of the interventions, the dual drug/sex nature of HIV risk in the population, the asymmetry of sexual risk for men and women, and the potential benefits to nonIDUs.     

Selecting Sites for New Facilities Using Data Envelopment Analysis

This paper develops a mathematical programming model for obtaining a best set of sites for planned facilities. The model is concerned with those situations where resource constraints are present. The specific setting for the paper involves the selection of sites for a set of retail outlets, wherein the ratio of aggregate outputs to inputs for the selected set is maximal among all possible sets that could be chosen. At the same time, the model guarantees that the only sets of stores allowable are those for which the available resources are used to the maximum extent possible.