Consumers Felt Commitment Towards Retailers: Index Development and Validation

This work seeks to develop an index of the consumer's felt commitment towards the retailer through a formative scale. By using structural equation modeling (SEM), in particular the multiple indicators and multiple causes (MIMIC) model, as well as reflective and formative indicators, the methodology developed by Diamantopoulos and Winklhofer is applied in order to construct this index. To clarify the whole meaning of the concept, the article undertakes a thorough review of literature on felt commitment and formative index development. Several MIMIC models are developed in order to validate the index. The empirical study was carried out in the financial services sector.     

一种特殊的计算机指点装置追踪球的操作活动研究

探讨在指点定位中目标方向、大小和距离对食指和拇指操纵追踪球的运动时间的效应 ,并由此建立了两种追踪球的菲茨模型。用绩效指数比较了不同指点装置的操作绩效 ,对追踪球的优化设计提出了建议。     

优秀护士"Y-G人格测验"特异性指标的研究

采用“Y-G人格测验”问卷及自制职业自评、他评调查表,分析比较了优秀护士与一般护士的人格特质、性格类型的差异。结果表明：优秀护士与一般护士在2种性格类型、7个人格特质上存在显著差异或差异趋势;提示从“Y-G人格测验”中提取护士人格特异性指标具有可行性;优秀护士人格特质的特异性指标可折射其性格类型、对开发护士职业心理素质研究的应用工具有一定价值。     

基于等级反应模型的规则空间方法

本研究基于Tatsuoka的规则空间方法, 对理想反应模式与异常反应指标进行了扩展, 推导了多级评分项目下规则空间方法的算法公式。在4种属性层级结构(发散型、收敛型、线型与无结构型)×4种“失误”作答概率(2%、5%、10%与15%)测验情境下, 以属性模式判准率、被试属性判准率、敏感性与特异性为指标, 检验了多级评分项目下规则空间方法的分类准确性。结果表明：(1) 基于多级评分项目构建的异常反应指标, 能有效地对被试进行分类与解释, 且0-1评分项目下异常反应指标及其性质都是多级评分下的特例; (2) 随着“失误”作答概率的增加, 4种属性层级结构的分类准确性都会降低; (3) 线型和收敛型的分类准确性明显好于发散型与无结构型; (4) 纯规则点的分布对规则空间方法的分类准确性有显著影响。     

Representation over time: the effects of temporal distance on similarity

Similarity is central in human cognition, playing a role in a wide range of cognitive processes. In three studies, we demonstrate that subjective similarity may change as a function of temporal distance, with some events seeming more similar when considered in the near future, while others increase in similarity as temporal distance increases. Given the ubiquity of inter-temporal thought, and the fundamental role of similarity, these results have important implications for cognition in general.     

Similarity, kernels, and the triangle inequality

Similarity is used as an explanatory construct throughout psychology and multidimensional scaling (MDS) is the most popular way to assess similarity. In MDS, similarity is intimately connected to the idea of a geometric representation of stimuli in a perceptual space. Whilst connecting similarity and closeness of stimuli in a geometric representation may be intuitively plausible, Tversky and Gati [Tversky, A., & Gati, I. (1982). Similarity, separability, and the triangle inequality. Psychological Review, 89(2), 123-154] have reported data which are inconsistent with the usual geometric representations that are based on segmental additivity. We show that similarity measures based on Shepard’s universal law of generalization [Shepard, R. N. (1987). Toward a universal law of generalization for psychologica science. Science, 237(4820), 1317-1323] lead to an inner product representation in a reproducing kernel Hilbert space. In such a space stimuli are represented by their similarity to all other stimuli. This representation, based on Shepard’s law, has a natural metric that does not have additive segments whilst still retaining the intuitive notion of connecting similarity and distance between stimuli. Furthermore, this representation has the psychologically appealing property that the distance between stimuli is bounded.     

From universal laws of cognition to specific cognitive models

The remarkable successes of the physical sciences have been built on highly general quantitative laws, which serve as the basis for understanding an enormous variety of specific physical systems. How far is it possible to construct universal principles in the cognitive sciences, in terms of which specific aspects of perception, memory, or decision making might be modelled? Following Shepard (e.g., 1987 ), it is argued that some universal principles may be attainable in cognitive science. Here, 2 examples are proposed: the simplicity principle (which states that the cognitive system prefers patterns that provide simpler explanations of available data); and the scale‐invariance principle, which states that many cognitive phenomena are independent of the scale of relevant underlying physical variables, such as time, space, luminance, or sound pressure. This article illustrates how principles may be combined to explain specific cognitive processes by using these principles to derive SIMPLE, a formal model of memory for serial order ( Brown, Neath, & Chater, 2007 ), and briefly mentions some extensions to models of identification and categorization. This article also considers the scope and limitations of universal laws in cognitive science.     

过敏性皮肤病患者的生活质量分析及心理关怀

过敏性皮肤病的皮损和瘙痒给患者的心理带来了一系列的问题,分析患者的生活质量并关注其心理状态,对专业人员进行培训,给予患者心理关怀,对患者家属进行教育才能最终达到改善或治疗疾病的目。     

Beyond common features: the role of roles in determining similarity

Historically, accounts of object representation and perceived similarity have focused on intrinsic features. Although more recent accounts have explored how objects, scenes, and situations containing common relational structures come to be perceived as similar, less is known about how the perceived similarity of parts or objects embedded within these relational systems is affected. The current studies test the hypothesis that objects situated in common relational systems come to be perceived as more similar. Similarity increases most for objects playing the same role within a relation (e.g., predator), but also increases for objects playing different roles within the same relation (e.g., the predator or prey role in the hunts relation) regardless of whether the objects participate in the same instance of the relation. This pattern of results can be captured by extending existing models that extract meaning from text corpora so that they are sensitive to the verb-specific thematic roles that objects fill. Alternative explanations based on analogical and inferential processes are also considered, as well as the implications of the current findings to research in language processing, decision making, and category learning.