LKJ2000型屏显故障原因分析及其启示

文章通过对2000屏显主要故障原因的分析,提出了处理各种问题的解决方案,以作为现场LKJ2000型监控装置维护人员的参考和提高屏显可靠性的一些建议。     

Sociological classification and cluster analysis

Quality & Quantity -     

HR flexibility and firm performance: analysis of a multi-level causal model

Human resource flexibility as a construct, how it develops, and its effect on firm performance have not received adequate attention in strategic HRM literature in spite of their obvious importance in today's dynamic competitive environment. Based on a study of 98 manufacturing and 103 service firms in India, this paper addresses these issues by developing and testing a multi-level model that attempts to explore the ‘black box’ of the interlinkages between the various components of HR flexibility and firm-level human, operational, and financial outcomes. The results suggest that a certain set of ambidextrous HR practices constitute a distinct dimension of HR flexibility, beyond the dimensions of flexibilities of skill, behaviour and HR practices as already identified in the existing literature. Evidences from both manufacturing and service sectors support the notion of HR value chain that suggests that HR system has a direct impact on firm-level HR outcomes which are most proximal, and its effects on increasingly more distal operational and financial outcomes are mediated by HR outcomes that it produces. Another important finding is that HR practices as a system have both direct and indirect (mediated by behavioural flexibility) effects on firm-level HR outcomes. Existence of significant direct effects highlights the important role that HR practices play as a structural mechanism in achieving superior firm performance.     

Logit and multinomial logit models for discrete-time event-history analysis: a causal analysis of interdependent discretestate processes

This paper introduces a new direction of methodological elaborations in event-history analysis based on discrete-time logit and multinomial logit models. The methodological elaborations address (1) simultaneous analysis of two-way transitions between two states, and (2) its extension for a causal analysis of two interdependent two-state processes. The former elaboration permits a more parsimonious and unambiguous expression for the effects of covariates on the dependent process than can be obtained by separate analyses of each direction of transition. The latter elaboration provides an extension for a log-linear causal analysis of 16-fold tables presenting two-wave-two-variable panel data, and relates the log-linear analysis to event-history analysis. An illustrative application, focusing on the dynamic relationship between premarital cohabitation and marijuana use, demonstrates the usefulness of the new models and methods.     

The causal analysis of contingency tables: A return to first principles

Given the undoubtedly major advances in the analysis of contingency tables which have been achieved over the past ten years or so (see for example, Fienberg, 1980; Upton, 1978; Everitt, 1977; Haberman, 1978, 1979), it might seem rather unnecessary to want to return to first princples again. However, the need arises precisely because of these advances; for progress in the specifically causal analysis of contingency tables has not matched the other advances at all. Whilst Fienberg devoted a chapter to causal analysis, he made it clear that he views “the assignment of numerical values [to the arrows in a path diagram] as problematic, and [he] would limit [the analysis] to an indication of sign for causal relationships, in a fashion similar to that described by Blalock (1964)” (Fienberg, 1980, pp. 91–92). Considering how far quantitative-variable causal analysis has developed since Blalock (1964), it becomes clear that the causal analysis of qualitative data is still at a rather primitive stage. Indeed, Haberman (1978, 1979), in his two-volume survey of the analysis of qualitative data, does not mention it at all. The problem, I believe, is that log-linear and logit methodology are not particularly suited to the logic of causality in contingency tables. In order to derive a suitable method, it is necessary to uncover the logic underlying causality when applied to qualitative variables. A few others have taken seriously the idea that a direct analysis of the form of a contingency table can lead to fruitful results (see, especially, for example, Boudon, 1967), but their work has been overshadowed by the statistically more profound advances made in log-linear methods. This article is an attempt to provide a statistically rigorous analysis based on the direct interpretation of causality embodied in a contingency table.     

Graphical analysis and financial classification: A case study

This paper illustrates the use of graphical analysis as a complementary diagnostic tool in financial classification problems. For more than two decades statistical models have been used frequently to understand the information content of multivariate data in the context of financial classification. These statistical classification models can be complemented by the use of computer-generated multidimensional data displays and graphical analysis. We illustrate the use of the scatterplot matrix, which is the simplest and very effective form of graphical analysis on a sample of bankrupt and non-bankrupt firms. The paper demonstrates the complementary nature of the scatterplot matrix for tree-structured classification models.     

Measurement error in causal analysis of panel data: Attenuated versus inflated relationships

The presence of random measurement error is commonly thought to cause attenuation of statistical relationships. While this is an unquestionable truth in bivariate analysis, it cannot be generalized to the multivariate case without qualification. This paper shows that measurement error may give rise to overestimates of parameters in causal analysis whenever there is more than one independent variable and the independent variables are correlated. If the independent variables are not measured with the same amount of reliability, there may also be considerable error in estimates of the relative magnitude of their impact. Both problems are particularly serious when the amount of measurement error is large relative to some of the causal effects such as in panel analysis with lagged dependent variables.     

中国房价与地价的关系——基于相关分析和因果分析的实证研究

近年,中国房价持续迅猛上涨引发了不少讨论和争议,其中房价和地价的关系也是热点之一。本文以中国房地产为研究对象,借助SPSS16．0和Eview5．0,采用实证研究方法,对中国自1999年第一季度到2009年第四季度的房价和地价数据进行相关分析和格兰杰因果分析,揭示房价与地价的相关性和两者之间的协整关系,以及中国房价和地价在短期乃至长期相互影响的状况,为房价调控策略选择提供科学依据。     

Environmental dynamism,human resource flexibility,and firm performance: analysis of a multi-level causal model

While strategic HRM scholars have conceptualized HR flexibility as an important source of sustainable superior firm performance in dynamic environments, the process through which HR flexibility creates value for the firm has not been empirically investigated. Based on a study of 98 manufacturing and 103 service firms from a wide array of industries in India, this paper attempts to illuminate the black box of causal linkages between environmental dynamism, flexibility of human assets, and firm level human-, operational-, and financial-outcomes by developing and testing a multi-level causal model. Evidence indicates that HR flexibility mediates the influence of environmental dynamism on firm performance and that irrespective of the nature of the industry and the degree of environmental turbulence, superior firm performance ensues when HR flexibility as actually possessed by the firm matches the environmental demands for such flexibility as perceived by the firm managers. The results also support the notion of HR value chain that postulates that HR system has direct impact on firm-level HR outcomes which are most proximal, and its effects on increasingly more distal operational- and financial-outcomes are mediated by HR outcomes. The findings of the study suggest that HR practices as a system have both direct and indirect (mediated by behavioral flexibility) effects on firm-level HR outcomes. Existence of significant direct effects signifies that HR practices play an important role as a structural mechanism in achieving superior firm performance.