Rethinking electoral reform in New Zealand: the benefits of citizens' assemblies

In 2011, New Zealanders decided by referendum to retain the mixed member proportional representation voting system. This article investigates the benefits of including a deliberative, participatory process in electoral reform to encourage collective debate and an informed choice by voters. In the last decade, Canada and the Netherlands have used citizens' assemblies, a form of participatory democracy, for electoral reform. This paper argues that a similar process would have been appropriate and valuable for New Zealand. Moreover, the discussion highlights the value of citizens' assemblies for minorities who can be outvoted in a referendum. This is considered with specific reference to voters in the Māori seats who had much at stake in the electoral reform. In addition to the general benefit of citizens' assemblies for electoral reform, a New Zealand assembly would have allowed for collective deliberation that ensured the inclusion of the perspectives of voters in the Māori seats.     

供应链环境下低碳物流运作研究

随着全球经济一体化运作的实施,全球供应链物流运作正成为推动全球经济发展的关键。针对建立高服务水平、高响应速度和低运作成本的供应链物流,依据供应链管理理论,采取在供应链上设置物流集结商、供应链信息共享、整合物流资源、优化运输路线、实施JIT配送等手段。提出了以物流集结商为供应链上游生产和配送协同决策主体的理念,从而达到在低碳经济下的供应链物流运作的目的。     

Precision,bias, and uncertainty for state population forecasts: an exploratory analysis of time series models

Many researchers have used time series models to construct population forecasts and prediction intervals at the national level, but few have evaluated the accuracy of their forecasts or the out-of-sample validity of their prediction intervals. Fewer still have developed models for subnational areas. In this study, we develop and evaluate six ARIMA time series models for states in the United States. Using annual population estimates from 1900 to 2000 and a variety of launch years, base periods, and forecast horizons, we construct population forecasts for four states chosen to reflect a range of population size and growth rate characteristics. We compare these forecasts with population counts for the corresponding years and find precision, bias, and the width of prediction intervals to vary by state, launch year, model specification, base period, and forecast horizon. Furthermore, we find that prediction intervals based on some ARIMA models provide relatively accurate forecasts of the distribution of future population counts but prediction intervals based on other models do not. We conclude that there is some basis for optimism regarding the possibility that ARIMA models might be able to produce realistic prediction intervals to accompany population forecasts, but a great deal of work remains to be done before we can draw any firm conclusions.     

低介入度产品迷惑式品牌名称的原产地认知研究——以瓶装水、洗发水、服装为例

以瓶装水、洗发水、服装为研究对象测量中国消费者对低介入度产品的品牌原产地识别准确度(BORA低),发现消费者的BORA低比较低;教育、经济收入、性别直接影响BORA低,并且教育、年龄通过民族中心主义观念这个中介变量间接影响BORA低。研究揭示中国消费者不清楚低介入度产品的原产地信息,说明原产地研究的隐含假设值得商榷,对国内原产地研究提出建议,并且建立消费者对于BORA低的认知模型。     

The Impact of Modular Assembly on Supply Chain Efficiency

This article studies the impact of modular assembly on supply chain efficiency. In the modular assembly approach, a manufacturer acquires pre‐assembled modules from its suppliers, rather than the individual components, as in the traditional assembly approach. We analyze the competitive behavior of a two‐stage modular assembly system consisting of a manufacturer, and a supplier who pre‐assembles two components into a module. The firms can choose their own inventory policies and we show the existence of Nash equilibrium in the inventory game. Moving from the traditional to the modular approach has a twofold effect on the supply chain. First, we investigate the effect of centralizing the component suppliers. It can be shown that when there is no production time shift, the module supplier always holds more component inventories than suppliers do in the traditional approach, which yields a lower cost for the manufacturer. However, the suppliers, and therefore the supply chain may incur a higher cost in the modular approach. Second, we study the effect of a shift in production time from the manufacturing stage to the supplier stage. From numerical studies, it has been found that such a lead time shift always benefits a centralized supply chain, but not necessarily so for a decentralized system. Combining the two effects, we find that the modular approach generally reduces the cost to the manufacturer and the supply chain, which explains the prevalence of modular assembly from the perspective of inventory management. These results also provide some insight into how firms can improve supply chain efficiency by choosing the right decision structure and lead time configuration.     

Assessing the Accuracy of Self-Reported Data: an Evaluation of the Toxics Release Inventory

Self-reported regulatory data are hard to verify. This article compares air emissions reported by plants in the Toxics Release Inventory with chemical concentration levels measured by EPA pollution monitors. We find that the large drops in air emissions reported by firms in the TRI are not always matched by similar reductions in measured concentrations from EPA monitors. When the first digits of the monitored chemical concentrations follow a monotonically decreasing distribution, we expect (via Benford's Law) a similar distribution of first digits for the TRI data. For lead and nitric acid the self-reported data do not follow the expected first digit pattern. This suggests that for these two heavily regulated chemicals plants are not reporting accurate estimates of their air emissions. JEL Classification K32, Q53     

Properties of simultaneous confidence intervals for multinomial proportions

Inversion of Pearson's chi-square statistic yields a confidence ellipsoid that can be used for simultaneous inference concerning multinomial proportions. Because the ellipsoid is difficult to interpret, methods of simultaneous confidence interval construction have been proposed by Quesenberry and hurst,goodman,fitzpatrick and scott and sison and glaz . Based on simulation results, we discuss the performance of these methods in terms of empirical coverage probabilities and enclosed volume. None of the methods is uniformly better than all others, but the Goodman intervals control the empirical coverage probability with smaller volume than other methods when the sample size supports the large sample theory. If the expected cell counts are small and nearly equal across cells, we recommend the sison and glaz intervals.     

Optimal Binning Strategies under Squared Error Loss in Selective Assembly with Measurement Error

Selective assembly is an effective approach for improving a quality of a product assembled from two types of components, when the quality characteristic is the clearance between the mating components. Mease et al. (2004 Mease , D. , Nair , V. N. , Sudjianto , A. ( 2004 ). Selective assembly in manufacturing: statistical issues and optimal binning strategies . Technometrics 46 : 165 – 175 .[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]) have extensively studied optimal binning strategies under squared error loss in selective assembly, especially for the case when two types of component dimensions are identically distributed. However, the presence of measurement error in component dimensions has not been addressed. Here we study optimal binning strategies under squared error loss when measurement error is present. We give the equations for the optimal partition limits minimizing expected squared error loss, and show that the solution to them is unique when the component dimensions and the measurement errors are normally distributed. We then compare the expected losses of the optimal binning strategies with and without measurement error for normal distribution, and also evaluate the influence of the measurement error.     

A fast Monte Carlo expectation–maximization algorithm for estimation in latent class model analysis with an application to assess diagnostic accuracy for cervical neoplasia in women with atypical glandular cells

In this article, we use a latent class model (LCM) with prevalence modeled as a function of covariates to assess diagnostic test accuracy in situations where the true disease status is not observed, but observations on three or more conditionally independent diagnostic tests are available. A fast Monte Carlo expectation–maximization (MCEM) algorithm with binary (disease) diagnostic data is implemented to estimate parameters of interest; namely, sensitivity, specificity, and prevalence of the disease as a function of covariates. To obtain standard errors for confidence interval construction of estimated parameters, the missing information principle is applied to adjust information matrix estimates. We compare the adjusted information matrix-based standard error estimates with the bootstrap standard error estimates both obtained using the fast MCEM algorithm through an extensive Monte Carlo study. Simulation demonstrates that the adjusted information matrix approach estimates the standard error similarly with the bootstrap methods under certain scenarios. The bootstrap percentile intervals have satisfactory coverage probabilities. We then apply the LCM analysis to a real data set of 122 subjects from a Gynecologic Oncology Group study of significant cervical lesion diagnosis in women with atypical glandular cells of undetermined significance to compare the diagnostic accuracy of a histology-based evaluation, a carbonic anhydrase-IX biomarker-based test and a human papillomavirus DNA test.     

Challenges in telemedicine equivalence studies

As the number of telemedicine programs continues to grow, the accuracy of diagnosis over interactive televideo is a central concern. Although investigators have begun to address diagnostic equivalency in telehealth clinics, few published studies reflect strong research design. The two presented telehealth programs completed randomized controlled trials in real-world clinical settings that addressed some of the methodologic shortcomings of prior studies. Diagnostic equivalency studies were completed across five telehealth specialty clinics: physical therapy, speech therapy, ambulatory pediatrics, child psychiatry, and developmental disabilities services. The two research teams encountered similar decision points in designing and implementing the equivalency protocols. This article addresses methodologic issues in choosing design, participants, technology, and evaluation measures. Although the paper focuses on interactive televideo, the issues raised are pertinent across telehealth technologies.