Catching nonconscious goals in the act of decision making

Research has consistently found that goals triggered by environmental cues can influence decision making processes outside of conscious awareness. This lack of awareness led naturally to the presumption that decision makers could not report the activation level of nonconsciously primed goals. This paper shows that goal activation levels can be reported, so long as the report is made during the decision process on a continuous goal activation scale. These results indicate that default lack of awareness is less a limitation of the cognitive system and more a function of the method used to recover goals during a decision process.     

Assessing the Validity of Data Synthesis Methods to Estimate Religious Populations

The present study tests the validity of a data synthesis approach to population estimates of religiously defined groups. This is particularly important in places like the United States, where there is no definitive source of official data on its population's religious composition, and researchers must rely on costly, large‐scale surveys, or congregational membership studies. Each approach has limitations, especially for estimation of small religious groups and for estimation within small geographic areas. Without official statistics, the degree of bias in estimates is unknown. Data synthesis, specifically Bayesian multilevel estimation with poststratification, offers a useful alternative that maximizes the utility of data across all sources to estimate multiple groups from the same sources of data. This method also facilitates comparison of groups. This study provides evidence of the validity of the approach by synthesizing data from Canada, a country that includes questions about religious identification in its national census.     

The development and validation of a measure of character: The CIVIC

The present research study sought to develop and validate a character scale – the Comprehensive Inventory of Virtuous Instantiations of Character using a total sample size of 3679 across five studies. In Study 1, character trait items were generated using an integrative classification system. In Study 2, character trait scales were further refined and their factor structure examined, revealing eight higher-order character dimensions or character cores: appreciation, intellectual engagement, fortitude, interpersonal consideration, sincerity, temperance, transcendence, and empathy. Study 3 established convergent validity of character traits with extant measures and discriminability from personality facets, social desirability, and moral cognitive development. Study 4 revealed that character cores were more strongly related to evaluative constructs than personality dimensions. Study 5 demonstrated that character cores predicted performance and psychological well-being outcomes above and beyond personality. The implications of our findings for the assessment and taxonomy of character are discussed.     

The chameleon effect,the temporal aspects of mimicry and their impact on service measurement

BackgroundIn an experiment conducted in a natural setting, we test the link between mimicry, the amount of time during which the mimicry behavior takes place, and its impact on service quality.MethodsCable TV clients (n = 120) were randomly assigned to six experimental conditions (2 mimicry conditions: verbal mimicry vs. no mimicry x 3 interaction time: 5 vs. 10 vs. 15 minutes). Perceived service quality served as the dependent measurement.ResultsA main effect of mimicry was found on service quality: a cable TV representative was perceived more favorably when he mimicked the customer. Importantly, it was shown that even small portions of mimicry are beneficial, meaning that practitioners do not have to mimic someone for a long time to achieve benefits.ConclusionThe paper shows new benefits for the mimicker: more positive judgments by the mimickee regarding the impact on several different levels of service quality.     

中国情境下公共服务动机的理论构建与绩效转换机制

准确把握基层公职人员的公共服务动机是提升工作绩效、完善人力资源管理的重要前提。现有公共服务动机研究忽略了中国情景的特殊性, 对公共服务动机的微观激发机制及其消极绩效影响也关注不足。本研究从中国情景下公共服务动机的概念、核心构成要素、激发机制以及绩效结果入手, 从三个方面系统地构建适合中国场景的公共服务动机理论：第一, 将公共服务动机视为混合动机概念, 基于扎根理论的定性方式识别基层公务员公共服务动机的构成要素与核心内涵, 并据此开发本土化、多维度的公共服务动机量表; 第二, 从微观激发机制出发, 探讨受益人接触、自我倡议、观念反思等机制对个体公共服务动机的激发作用; 第三, 从积极影响和消极影响两个方面探讨公共服务动机与个体公务员行为间的关联及其机理。本研究既响应了国内公共管理学界长期以来发展本土理论的呼声, 亦为政府部门完善公共人事政策提供切实思路和实证依据。     

对齐法在单因子和三因子多组比较中允许的不等参数率

在传统的多组验证性因子分析中,进行因子均值比较的前提条件是模型满足强测量不变性假设,但该假设在实证研究中很难满足。这时,Asparouhov和Muthén(2014)提出的对齐法是一种可供备选的多组分析法。通过蒙特卡洛模拟研究,探究了在对齐法精确估计模型参数前提下所允许的不等参数率范围。研究发现：在平均组样本量充足,识别算法为固定识别算法等理想状态下,对齐法在单因子模型多组比较中所允许的不等参数率可以是100%;在三因子模型中所允许的不等参数率上限是20%至30%;在此范围内,对齐法允许更多高程度不等参数;在组数目从30、15或9降至3时,对齐法能允许更多的不等参数在模型中。     

‘Additive difference’ models without additivity and subtractivity

This paper studies conjoint measurement models tolerating intransitivities that closely resemble Tversky's additive difference model while replacing additivity and subtractivity by mere decomposability requirements. We offer a complete axiomatic characterisation of these models without having recourse to unnecessary structural assumptions on the set of objects. This shows the pure consequences of several cancellation conditions that have often been used in the analysis of more traditional conjoint measurement models. Our models contain as particular cases many aggregation rules that have been proposed in the literature.     

归属需要的研究进展

归属需要的概念经历长时间的演化和发展,并有其进化的心理机制。自Baumeister在1995年提出归属需要作为人类的基本动机后,归属需要与认知,情感和行为的相关研究也得到发展,部分结论得到进一步的证实,但也出现不一致的研究结果。同时也开始了对归属需要与行为后果之间内部过程的探讨。对归属需要的测量主要采用量表法,但未出现一个统一的测量工具,易造成测量的差异,剥夺归属需要的研究常采用实验法,未来的研究可注重提高其生态效度。     

An Adaptive Algorithm for Pairwise Comparison‐based Preference Measurement

The Pairwise Comparison‐based Preference Measurement (PCPM) approach has been proposed for products featuring a large number of attributes. In the PCPM framework, a static two‐cyclic design is used to reduce the number of pairwise comparisons. However, adaptive questioning routines that maximize the information gained from pairwise comparisons promise to further increase the efficiency of this approach. This paper introduces a new adaptive algorithm for PCPM, which accounts for several response errors. The suggested approach is compared with an adaptive algorithm that was proposed for the Analytic Hierarchy Process as well as a random selection of pairwise comparisons. By means of Monte Carlo simulations, we quantify the extent to which the adaptive selection of pairwise comparisons increases the efficiency of the respective approach. Copyright © 2011 John Wiley & Sons, Ltd.