ISO 9000/1994, ISO 9001/2000 and TQM: The performance debate revisited

The debate about the impact of ISO 9000/1994 on performance has been waging since its inception. While there is a general agreement regarding the positive impact of TQM on performance, there has been less agreement among the academics about the impact of ISO 9000/1994. Perhaps in response to such debate, the new ISO 9001/2000 has appeared purporting to be more in line with the TQM philosophy. As of now, how this 2000 version actually affects performance is yet to be explored. In this study, we compare the implementation of ISO 9000/1994 and ISO 9001/2000 as representing two different efforts to implement quality management practices. We evaluate its impact on company performance with a sample of 713 Spanish industrial companies. We also examine if the 2000 version of ISO is taking us closer to the implementation of TQM. Further, we depart from the past studies methodologically by considering performance as a formative construct rather than a reflective construct. Based on the mean and covariance structural (MACS) analyses, we conclude that ISO 9001/2000 certified companies do not perform noticeably better than ISO 9000/1994 or non-certified companies. However, we find that ISO 9001/2000 certified companies apply TQM at a higher level than ISO 9000/1994 certified companies, but whether they actually perform better is less clear.     

The comparative forecast performance of univariate and multivariate models: an application to real interest rate forecasting

Does the use of information on the past history of the nominal interest rates and inflation entail improvement in forecasts of the ex ante real interest rate over its forecasts obtained from using just the past history of the realized real interest rates? To answer this question we set up a univariate unobserved components model for the realized real interest rates and a bivariate model for the nominal rate and inflation which imposes cointegration restrictions between them. The two models are estimated under normality with the Kalman filter. It is found that the error-correction model provides more accurate one-period ahead forecasts of the real rate within the estimation sample whereas the unobserved components model yields forecasts with smaller forecast variances. In the post-sample period, the forecasts from the bivariate model are not only more accurate but also have tighter confidence bounds than the forecasts from the unobserved components model.     

Service Guarantee Strength: The key to service quality

While most authors describe a service guarantee as a “zero-one variable” indicating the presence or absence of an explicit written service guarantee, this paper develops a construct called “Service Guarantee Strength” (SGS) that is a continuous variable. This construct measures the degree to which a firm sets clear service quality standards for itself on dimensions that customers care about, and has an formal policy for quickly giving meaningful compensation to customers when these standards are not met.The paper builds upon established micro-level behavioral theory to develop the “Service Guarantee Strength Framework”. This framework posits that high Service Guarantee Strength leads to improved service quality, customer satisfaction, and loyalty through three intervening variables—marketing communications impact, employee motivation and vision, and learning through service failure.An empirical investigation was conducted to test the SGS Framework using both employee and customer data from three pairs of firms, with each pair in a different industry. None of these firms had an explicit service guarantee. Unlike many behavioral research studies, this study measured both employee and customer perceptual data and compared the two. The research finds that Service Guarantee Strength is positively related to customer perceptions of service quality, customer satisfaction, and loyalty.     

Beyond improved quality: the motivational effects of statistical process control

The deployment of statistical process control (SPC) in manufacturing environments is a prominent global phenomenon. Managers have frequently justified investments in SPC by citing and/or demonstrating the improvements in quality and costs from the effective implementation and practice of SPC. This paper complements this rationalization by presenting conceptual arguments and empirical evidence to further our understanding of the motivational effects that result from the deployment of SPC within production environments. Several hypotheses derived from relating the deployment of SPC to process operators’ jobs and their affective reactions to work are tested using data provided by 100 process operators. The empirical results, generated from applying path analysis, suggest that the effective implementation and practice of SPC, in fact, would create more enriched jobs for process operators that lead to higher levels of work motivation and job satisfaction.     

The evolving theory of quality management: The role of Six Sigma

While Six Sigma is increasingly implemented in industry, little academic research has been done on Six Sigma and its influence on quality management theory and application. There is a criticism that Six Sigma simply puts traditional quality management practices in a new package. To investigate this issue and the role of Six Sigma in quality management, this study reviewed both the traditional quality management and Six Sigma literatures and identified three new practices that are critical for implementing Six Sigma's concept and method in an organization. These practices are referred to as: Six Sigma role structure, Six Sigma structured improvement procedure, and Six Sigma focus on metrics. A research model and survey instrument were developed to investigate how these Six Sigma practices integrate with seven traditional quality management practices to affect quality performance and business performance. Test results based on a sample of 226 US manufacturing plants revealed that the three Six Sigma practices are distinct practices from traditional quality management practices, and that they complement the traditional quality management practices in improving performance. The implications of the findings for researchers and practitioners are discussed and further research directions are offered.     

Comparing forecasts from fixed and variable coefficient models: The case of money demand

In this paper we introduce a class of tentatively plausible, fixed-coefficient models of money demand and evaluate their forecast performance. When these models are reestimated allowing all coefficients to vary over time, the forecasting performance improves dramatically. Aside from offering insights about improved methods of analyzing time series data, the most promising direct use for point estimates derived from time-varying coefficients is as an aid in calibrating proposed models of the kind discussed here.     

On the forecasting performance of a small-scale DSGE model

Dynamic stochastic general equilibrium (DSGE) models have recently become standard tools for policy analysis. Nevertheless, their forecasting properties have still barely been explored. In this article, we address this problem by examining the quality of forecasts of the key U.S. economic variables: the three-month Treasury bill yield, the GDP growth rate and GDP price index inflation, from a small-size DSGE model, trivariate vector autoregression (VAR) models and the Philadelphia Fed Survey of Professional Forecasters (SPF). The ex post forecast errors are evaluated on the basis of the data from the period 1994–2006. We apply the Philadelphia Fed “Real-Time Data Set for Macroeconomists” to ensure that the data used in estimating the DSGE and VAR models was comparable to the information available to the SPF.Overall, the results are mixed. When comparing the root mean squared errors for some forecast horizons, it appears that the DSGE model outperforms the other methods in forecasting the GDP growth rate. However, this characteristic turned out to be statistically insignificant. Most of the SPF's forecasts of GDP price index inflation and the short-term interest rate are better than those from the DSGE and VAR models.     

The performance of alternative forecasting methods for SETAR models

We compare a number of methods that have been proposed in the literature for obtaining h-step ahead minimum mean square error forecasts for self-exciting threshold autoregressive (SETAR) models. These forecasts are compared to those from an AR model. The comparison of forecasting methods is made using Monte Carlo simulation. The Monte-Carlo method of calculating SETAR forecasts is generally at least as good as that of the other methods we consider. An exception is when the disturbances in the SETAR model come from a highly asymmetric distribution, when a Bootstrap method is to be preferred.An empirical application calculates multi-period forecasts from a SETAR model of US gross national product using a number of the forecasting methods. We find that whether there are improvements in forecast performance relative to a linear AR model depends on the historical epoch we select, and whether forecasts are evaluated conditional on the regime the process was in at the time the forecast was made.     

知识经济与“两型社会”的构建——以武汉城市圈为例

在应对知识经济发展的大潮流下,阐述了世界城市圈中心城市的新模式.针对武汉城市圈的现状,提出了知识经济推动城市圈"两型社会"建设的模型基础及条件,并基于世界大城市圈的发展经验,对武汉城市圈"两型社会"的建设提出了若干意见.     

西方资本结构理论的新发展:一个理论综述

资本结构理论是现代公司财务理论研究中十分重要的部分。西方资本结构理论研究的目的在于从理论上解释决定企业资本结构的主要因素,揭示企业资本结构与企业市场价值及企业财务行为的内在关系,为企业投融资决策提供理论基础。从20世纪70年代开始,以产权理论、代理理论、信息不对称理论及产业组织理论为核心的新资本结构理论,突破了MM定理研究框架的束缚,开拓了资本结构理论研究的一个更为广阔的领域。本文对自20世纪70年代中期以来西方资本结构理论的新发展作一综述,以期为转轨时期的我国公司的投融资决策提供一些有益的启示和借鉴。     

组织模式变迁的一个新研究框架——基于信息技术革命与高素质组织参与者对组织与环境关系的介入

组织与环境的关系,是组织动态性、开放性和能动性的综合体现。组织与环境关系的发展促使了组织模式的转变。信息技术革命和高素质组织参与者对组织与环境的关系具有重要的影响,弄清楚它们对组织与环境关系的具体影响过程,是了解组织模式演变的基础。因此,一个基于信息技术革命和高素质组织参与者的行为给组织与环境之间的动态性、开放性和能动性带来的影响的全面分析框架,是研究组织模式变化与组织与环境关系之间联系的合适选择。     

Interpreting the results of studies using latent variable models to assess data quality: an empirical example using confirmatory factor analysis

Latent variable models (LVMs) offer one route to examine the quality of data collected in surveys. The possibility exists that individuals equivalent in their true level of a construct or variable being measured are unlikely to have equivalent observed responses as a function of an extraneous variable, e.g., group membership. This potential is labeled here as differential item functioning (DIF). Survey methods generally considers measurement bias to be estimators that do no not accurately reflect true values. DIF may be thought of as differential measurement bias, i.e., measurement bias conditional on group membership. As a function of group membership, the degree, amount, or type of measurement bias changes. DIF has the potential to negatively affect the quality of data. LVMs, e.g., confirmatory factor analysis (CFA), offer one tool to assess DIF. However, few published examples exist in the survey research field and training in the interpretation of these models is lacking. The purpose of the current paper is to describe CFA sufficiently for interpretive purposes and demonstrate an empirical application of CFA to assess survey data quality to provide further interpretive guidance. References are provided for analysts wishing to conduct analyses of this type.     

Automatic leading indicators versus macroeconometric structural models: A comparison of inflation and GDP growth forecasting

This paper compares the forecast performance of automatic leading indicators (ALIs) and macroeconometric structural models (MESMs) commonly used by non-academic macroeconomists. Inflation and GDP growth form the forecast objects for comparison, using data from China, Indonesia and the Philippines. ALIs are found to outperform MESMs for one-period-ahead forecasts, but this superiority disappears as the forecast horizon increases. It is also found that ALIs involve greater uncertainty in choosing indicators, mixing data frequencies and utilizing unrestricted VARs. Two ways of reducing the uncertainty are explored: (i) give theory priority in choosing indicators, and include theory-based disequilibrium shocks in the indicator sets; and (ii) reduce the VARs by means of the general-to-specific modeling procedure.     

参观者素质的提升与上海世博会的风险防范

上海世博会的风险防范与安全管理早已引起了相关机构和研究者的高度重视,本文试图从提升参观者素质的角度考察其与世博会风险防范与控制的关系,并找出难点和重点所在,进而提供一些具体的建议,希望能为有关机构提供参考。     

Improving the performance of random coefficients demand models: The role of optimal instruments

We shed new light on the performance of Berry, Levinsohn and Pakes’ (1995) GMM estimator of the aggregate random coefficient logit model. Based on an extensive Monte Carlo study, we show that the use of Chamberlain’s (1987) optimal instruments overcomes many problems that have recently been documented with standard, non-optimal instruments. Optimal instruments reduce small sample bias, but they prove even more powerful in increasing the estimator’s efficiency and stability. We consider a wide variety of data-generating processes and an empirical application to the automobile market. We also consider the gains of other recent methodological advances when combined with optimal instruments.     

Simultaneous Models for Contingency Tables: A Reanalysis of Heatherton et al. (1997) Data on Eating Behavior

In panel studies, where a categorical response is measured attwo points in time, we can examine two kind of hypotheses regardingthe nature of change. The first is related with change at theindividual level (gross change) through the modelling of joint distributionof responses. The second is related with aggregate change (netchange) through the modelling of marginal distributions of responses.This paper describes a general approach to the analysis of two-wavepanel data based on Lang and Agresti's work (1994) that simultaneouslypermits the modelling of marginal and joint distributions of responses.This approach is illustrated with data from Heatherton et al.(1997) about change in dieting behaviour. These data were originallyanalyzed using the ² statistic to test independenceof responses. This paper shows how it is possible toobtain a better understanding of these data using the proposedmethodological approach.     

Advertising,avoiding, disrupting,and tabooing: The discursive construction of diversity subjects in the Turkish context

This study investigates organizational diversity discourses in Turkey – a non-Western, politically relevant, yet underrepresented context. Using a Foucauldian perspective on power and discourse, we scrutinize how power relations in the Turkish context are (re)produced. Based on our analysis of company websites and semi-structured interviews with various actors (e.g., HR managers), we propose a conceptual framework of the discursive construction of diversity subjects at work along the dimensions of (1) visibility of organizational diversity discourses and (2) contestation of meaning within organizational diversity discourses. The combination of these dimensions yields four discursive dynamics as illustrated in our data (Advertising, Avoiding, Disrupting, Tabooing). This framework may inspire future context- and power-sensitive investigations on diversity discourses at the workplace.     

人力资源管理在企业中的角色

文章对人力资源在企业发展中的作用和角色进行了阐述,尤其是在新形势下的人力资源管理职能成为企业战略性伙伴的作用产生了实践意义。