Multicultural Connections: Using Stories to Transcend Cultural Boundaries in Supervision

Stories have long been used in various cultures and settings to help make meaning and enhance awareness. The authors describe how reflection on and discussion of myths and fairy tales in supervision may help transcend cultural boundaries and increase multicultural understanding. Las historias se han utilizado durante mucho tiempo en diversas culturas y escenarios para facilitar la comprensión de significado y aumentar el nivel de conciencia. Los autores describen cómo la reflexión y la discusión de mitos y cuentos en la supervisión pueden ayudar a trascender barreras culturales y elevar el entendimiento multicultural.     

Fuzzy MCDM based on the concept of α‐cut

In a fuzzy multiple criteria decision‐making (MCDM) problem, with a hierarchical structure of more than two levels and involving multiple decision‐makers (DMs), to find the exact membership functions of the final aggregation ratings of all feasible alternatives is almost impossible. Thus, ranking methods based on exact membership functions cannot be utilized to rank the feasible alternatives and complete the optimal selection. To resolve the above‐mentioned complexity and to incorporate assessments of all DMs' viewpoints, in this paper a fuzzy MCDM method with multiple DMs, based on the concepts of fuzzy set theory and α‐cut, is developed. This method incorporates a number of perspectives on how to approach the fuzzy MCDM problem with multiple DMs, as follows: (1) combining quantitative and qualitative criteria as well as negative and positive ones; (2) using the generalized means to develop the aggregation method of multiple DMs' opinions; (3) incorporating the risk attitude index β to convey the total risk attitude of all DMs by using the estimation data obtained at the data input stage; (4) employing the algebraic operations of fuzzy numbers based on the concept of α‐cut to calculate the final aggregation ratings and develop a matching ranking method for proposed fuzzy MCDM method with multiple DMs. Furthermore, we use this method to survey the site selection for free port zone (FPZ) in Taiwan as an empirical study to demonstrate the proposed fuzzy MCDM algorithm. The result of this empirical investigation shows that the port of Kaohsiung, the largest international port of Taiwan as well as the sixth container port in the world in 2004, is optimal for the Taiwan government in enacting the plan of FPZ. Copyright © 2005 John Wiley & Sons, Ltd.     

程序公正作用机制中的调节变量

程序公正是指用于决定分配的过程是否公正。回顾近年来程序公正作用机制的相关理论以及实证研究结果发现, 对程序公正的效果起调节作用的主要有四类因素, 分别为情景因素、个体特征因素、分配结果因素以及领导者因素。今后该主题的研究应进一步关注发言权效应的跨文化验证、探索本土化程序公正原则、进一步考察情景变量的调节效应、加强领导者因素的研究、结合分配公正进行研究, 并应加强程序公正的应用性研究。     

多元动机网格测验（MMG-S）中文版的修订报告

对Sokolowski等人编制的简版多元动机网格测验（MMG-S）作了中文版的修订。MMG-S的验证性因素分析表明：中文修订版MMG-S仍保持英文版的六因子结构,修订后六因子的α系数在0.70~0.84之间。中文修订版MMG-S具有良好的心理学测量指标,可用于测量企业管理人员的三种社会性动机。     

内隐记忆中的神经机制研究方法

知觉启动与语义启动神经机制的研究是内隐记忆神经机制研究的两条重要途径。本文介绍了内隐记忆神经机制的研究途径之一：知觉启动神经机制的研究进展情况,并对研究中存在的问题及解决方法提出建议。     

组织公正氛围的理论机制、研究视角及研究框架

组织公正是员工对工作场所公正环境的心理感知, 研究层面有个体与群体之分。以往研究多集中在个体层面, 以致研究结果缺乏对群体现象的有效解释。进入新世纪学者们开始关注群体层面的公正氛围研究, 并在理论和实证方面取得了较大突破。通过回顾相关研究可以发现：(1)在理论机制上, 公正氛围的形成可以通过社会信息加工理论、吸引-选择-磨合模型、公正传染概念和公正启发理论来解释; (2)在研究视角上, 主要存在维度视角、整体视角、感知来源视角、氛围属性视角和第三方视角; (3)在研究主题上, 主要涉及领导、团队和组织三方面对公正氛围的影响, 以及公正氛围对个体、团队和组织三个层面的影响效果。未来研究可着重从多种领导行为对不同公正氛围影响的比较、其他领导因素对公正氛围的影响、不同公正氛围对结果变量影响的比较、新视角公正氛围测量方法的尝试, 以及文化因素对公正氛围的影响研究等方面入手。     

具身认知视角的饮食消费行为——基于心理模拟“具身”方式

随着具身认知理论的发展, 基于心理模拟“具身”方式的饮食消费行为研究得到了一些新颖、有趣的研究结果, 为过食与肥胖、食品营销等问题的解决提供了新视角。心理模拟既能促进进食也能抑制进食; 心理模拟容易性因素与动机性因素是影响心理模拟程度的两大类主要前因变量; 未来需要进一步探索心理模拟的容易性因素与动机性因素、心理模拟提高消费欲望与产生腻厌反应的边界条件, 以及利用心理模拟探讨肥胖高危人群——高奖赏敏感性个体过食的深层次内在机制等。     

Bayesian generalized structured component analysis

Generalized structured component analysis (GSCA) is a component-based approach to structural equation modelling, which adopts components of observed variables as proxies for latent variables and examines directional relationships among latent and observed variables. GSCA has been extended to deal with a wider range of data types, including discrete, multilevel or intensive longitudinal data, as well as to accommodate a greater variety of complex analyses such as latent moderation analysis, the capturing of cluster-level heterogeneity, and regularized analysis. To date, however, there has been no attempt to generalize the scope of GSCA into the Bayesian framework. In this paper, a novel extension of GSCA, called BGSCA, is proposed that estimates parameters within the Bayesian framework. BGSCA can be more attractive than the original GSCA for various reasons. For example, it can infer the probability distributions of random parameters, account for error variances in the measurement model, provide additional fit measures for model assessment and comparison from the Bayesian perspectives, and incorporate external information on parameters, which may be obtainable from past research, expert opinions, subjective beliefs or knowledge on the parameters. We utilize a Markov chain Monte Carlo method, the Gibbs sampler, to update the posterior distributions for the parameters of BGSCA. We conduct a simulation study to evaluate the performance of BGSCA. We also apply BGSCA to real data to demonstrate its empirical usefulness.     

从山东地名解读齐鲁文化

地名是一种特殊的文化现象,可以反映特定地域的自然和人文条件。山东地名与齐鲁地理文化、齐鲁历史文化、齐鲁居民生活、齐鲁方言文化等方面密切相关。本文从这些方面解读山东地名所反映的齐鲁文化。     

Why best cannot last: Cultural differences in predicting regression toward the mean

Four studies were conducted to investigate cultural differences in predicting and understanding regression toward the mean. We demonstrated, with tasks in such domains as athletic competition, health and weather, that Chinese are more likely than Canadians to make predictions that are consistent with regression toward the mean. In addition, Chinese are more likely than Canadians to choose a regression‐consistent explanation to account for regression toward the mean. The findings are consistent with cultural differences in lay theories about how people, objects and events develop over time.