Person–organization fit and employee outcomes: test of a social exchange model

Data obtained from subordinate–supervisor dyads (N = 314) of a large manufacturing company in South Korea were used to test a moderated mediation model of the processes linking person–organization (P–O) fit and employee work attitudes and behaviors. The results revealed that the influence of P–O fit on work attitudes and behaviors was indirect through perceived social exchange with organization. In addition, the relationship between P–O fit and perceived social exchange with organization was moderated by leader–member exchange (LMX) quality. Specifically, a high-quality LMX enhanced the positive effects of P–O fit on perceived social exchange with organization.     

Traceable Regressions

In this paper, we define and study the concept of traceable regressions and apply it to some examples. Traceable regressions are sequences of conditional distributions in joint or single responses for which a corresponding graph captures an independence structure and represents, in addition, conditional dependences that permit the tracing of pathways of dependence. We give the properties needed for transforming these graphs and graphical criteria to decide whether a path in the graph induces a dependence. The much stronger constraints on distributions that are faithful to a graph are compared to those needed for traceable regressions.     

垃圾分类处理与清运方案设计的模型

本文对深圳市南山区垃圾分类处理与清运方案进行分析,主要从三个方面去着手探究问题。一是在数量和选址上配置大小型橱余垃圾设备,二是设计四类垃圾的清运线路,通过这两个方面的研究最终达到最佳经济效益和环保效果。     

Perceptions of electricity-use communications: effects of information,format, and individual differences

Electricity bills could be an effective strategy for improving communications about consumers’ electricity use and promoting electricity savings. However, quantitative communications about electricity use may be difficult to understand, especially for consumers with low energy literacy. Here, we build on the health communication and graph comprehension literature to inform electricity bill design, with the goal of improving understanding, preferences for the presented communication, and intentions to save electricity. In a survey-based experiment, each participant saw a hypothetical electricity bill for a family with relatively high electricity use, covering information about (a) historical use, (b) comparisons to neighbors, and (c) historical use with appliance breakdown. Participants saw all information types in one of three formats including (a) tables, (b) bar graphs, and (c) icon graphs. We report on three main findings. First, consumers understood each type of electricity-use information the most when it was presented in a table, perhaps because tables facilitate simple point reading. Second, preferences and intentions to save electricity were the strongest for the historical use information, independent of format. Third, individuals with lower energy literacy understood all information less. We discuss implications for designing utility bills that are understandable, perceived as useful, and motivate consumers to save energy.     

脂肪酶催化的研究进展

本文简单介绍了脂肪酶的立体结构和催化机理,综述了非水相的有机溶剂体系中脂肪酶催化的特点与性质,并对微水的无溶剂体系、微乳液体系和超临界体系进行了简单的论述。定向进化技术有助于改善酶的催化特点和应用范围,酶交联晶体的制备和生物印迹方法的采用对提高脂肪酶的活性、热稳定性和选择性也有较大的促进作用。     

Text mining a decade of progress in hospitality human resource management research: Identifying emerging thematic development

The authors identified the emerging research streams based on the published research literature in human resource management (HRM) from 1994 to 2003 in the International Journal of Hospitality Management. Textual data were collected and content-analyzed by a text-mining program aided by human judgments. The results from the content analysis of both the computer-aided and human judgmental methods were then integrated and conceptually graphed to map meaningful findings that were logically precise, humanly readable, and computationally tractable. Through this unique approach, nine major HRM research themes emerged and each thematic development based on time and country was interpreted and discussed.     

Bayesian Model Selection of Gaussian Directed Acyclic Graph Structures

During the last years, graphical models have become a popular tool to represent dependencies among variables in many scientific areas. Typically, the objective is to discover dependence relationships that can be represented through a directed acyclic graph (DAG). The set of all conditional independencies encoded by a DAG determines its Markov property. In general, DAGs encoding the same conditional independencies are not distinguishable from observational data and can be collected into equivalence classes, each one represented by a chain graph called essential graph (EG). However, both the DAG and EG space grow super exponentially in the number of variables, and so, graph structural learning requires the adoption of Markov chain Monte Carlo (MCMC) techniques. In this paper, we review some recent results on Bayesian model selection of Gaussian DAG models under a unified framework. These results are based on closed-form expressions for the marginal likelihood of a DAG and EG structure, which is obtained from a few suitable assumptions on the prior for model parameters. We then introduce a general MCMC scheme that can be adopted both for model selection of DAGs and EGs together with a couple of applications on real data sets.     

Causality and Causal Models: A Conceptual Perspective*

This paper aims at displaying a synthetic view of the historical development and the current research concerning causal relationships, starting from the Aristotelian doctrine of causes, following with the main philosophical streams until the middle of the twentieth century, and commenting on the present intensive research work in the statistical domain. The philosophical survey dwells upon various concepts of cause, and some attempts towards picking out spurious causes. Concerning statistical modelling, factorial models and directed acyclic graphs are examined and compared. Special attention is devoted to randomization and pseudo‐randomization (for observational studies) in view of avoiding the effect of possible confounders. An outline of the most common problems and pitfalls, encountered in modelling empirical data, closes the paper, with a warning to be very cautious in modelling and inferring conditional independence between variables.     

Text Analysis for Knowledge Graphs

The concept of knowledge graphs is introduced as a method to represent the state of the art in a specific scientific discipline. Next the text analysis part in the construction of such graphs is considered. Here the ‘translation’ from text to graph takes place. The method that is used here is compared to methods used in other approaches in which texts are analysed.