非形式推理的研究及展望

非形式推理目前被界定为对结构不良的、用自然语言表述的、没有固定答案的、需要进行归纳的问题的推理,推理的结果是个体对问题形成一定的态度和观点。已有研究探讨了非形式推理的一般特征、衡量标准、影响推理的个体特征,以及学生非形式推理能力的培养方式等问题。作者认为开展非形式推理及其影响因素的研究将促进人格特征与认知关系的研究,并有广泛的教育意义,同时提出了有待深入研究的课题。     

国外人格障碍五因素模型研究述评

近些年来,国外许多心理学家致力于将基础的人格理论和人格障碍研究相结合的工作,其中将五因素模型引入人格障碍的研究已经取得了很大进展。文章主要总结了这方面的研究成果,探讨了将五因素模型应用于临床诊断和干预的可能性,最后讨论了未来人格障碍的研究方向     

The impact of beliefs about face recognition ability on memory retrieval processes in young and older adults

This study examined whether beliefs about face recognition ability differentially influence memory retrieval in older compared to young adults. Participants evaluated their ability to recognise faces and were also given information about their ability to perceive and recognise faces. The information was ostensibly based on an objective measure of their ability, but in actuality, participants had been randomly assigned the information they received (high ability, low ability or no information control). Following this information, face recognition accuracy for a set of previously studied faces was measured using a remember–know memory paradigm. Older adults rated their ability to recognise faces as poorer compared to young adults. Additionally, negative information about face recognition ability improved only older adults' ability to recognise a previously seen face. Older adults were also found to engage in more familiarity than item-specific processing than young adults, but information about their face recognition ability did not affect face processing style. The role that older adults' memory beliefs have in the meta-cognitive strategies they employ is discussed.     

Career success criteria and locus of control as indicators of adaptive readiness in the career adaptation model

The present research had two goals. The first goal was to identify additional individual characteristics that may contribute to adaptive readiness. The second goal was to test if these characteristics fit the career adaptation model of readiness to resources to responses. We examined whether career success criteria (measured at Time 1) and career locus of control (measured at Time 1) would contribute to adaptivity and predict university students’ career decision-making self-efficacy (measured at Time 2) through the mediation of career adaptability (measured at Time 1). Results based on a two-wave survey among a sample of 437 Chinese university students showed that the criteria of intrinsic fulfillment and work-life balance, as well as internal career locus of control positively predicted Chinese university students' career adaptability, which in turn predicted career decision-making self-efficacy. These findings support the career adaption model and carry implications for career construction theory and university students' career development.     

A Fuzzy Topsis Method for Prioritized Aggregation in Multi‐Criteria Decision Making Problems

Aggregation in a decision making environment requires the fusion of opinions of a group of decision makers. The group of decision makers are required to analyse a set of interrelated criteria that are usually measured on a linguistic scale. This process requires, in many instances, to capture experts experience, intuition and thinking that are traditionally expressed in a linguistic fashion rather than a numerical fashion. Furthermore, the necessity of considering the relationship between the criteria to the overall decision must be considered by the group of decision makers. This paper extends the application of fuzzy numbers, fuzzy relative importance scores (FRIS), fuzzy relative weights (FRW) and the fuzzy technique of order preference by similarity to ideal solution (TOPSIS) in prioritized aggregation. This extension provides a mean to systematically aggregate a group of decision makers' views for a set of interrelated criteria that are measured on a linguistic scale. First, an overview of the application of fuzzy numbers and the characteristics of aggregating fuzzy numbers in multi‐criteria decision making problems are presented. Then, the application of TOPSIS in fuzzy environments is presented. Next, past research is highlighted to present prioritized aggregation and the different aggregation operators' classes. Subsequently, a new prioritized aggregation method is presented. This method utilizes fuzzy TOPSIS with prioritized aggregation in fuzzy environments. Finally, the fuzzy prioritized aggregation method presented in this paper is applied on an actual case study. According to the results, the method presented in this paper provides a systematic approach to capture the uncertainty and imprecision associated with quantifying linguistic measurements in multi‐criteria decision making problems. Furthermore, it considers the relationship between the set of linguistically measured criteria undergoing prioritized aggregation in a fuzzy environment. Lastly, findings, conclusions and future work are presented. Copyright © 2016 John Wiley & Sons, Ltd.     

An Approach for Determining the Mix between Human and Automated Service Providers

With the growing popularity of self‐service technologies (SST), businesses have to determine how to combine traditional human service with SST technologies. These mix problems have not received adequate attention in the research literature. This paper offers a decision model for solving mix problems between human service channels and SSTs. The decision problem cannot be determined as a traditional max or min problem and it is fuzzy. In fuzzy problems, the decision maker (DM) is considered as the focal point with the relevant knowledge and preferences and therefore, the objective is to maximize the DM's preferences. This paper develops a decision support system for eliciting a DM's value function when the service channels are considered to be substitutes, but when the rate of substitution may change and then uses a linear‐fractional model to fit the DM's data and optimize the DM's preferences. A service mix problem for a grocery store with human service providers and SSTs is used to demonstrate how the decision model can be employed to analyze and solve service mix decision making problems. Copyright © 2014 John Wiley & Sons, Ltd.     

Integration of Analytic Hierarchy Process with Regression Analysis to Identify Attractive Locations for Market Expansion

Selection of new geographies in which to expand is a key decision for businesses aspiring to go beyond the opportunities in the existing markets. The conventional approaches of market selection can only provide a set of systematic steps for problem solving without considering the relationships between the decision factors. Decision models based on statistical techniques are able to examine the relationship between decision factors but are unable to effectively assist decision makers in identifying the most promising market, particularly in terms of prioritizing across decision factors. Analytic Hierarchy Process (AHP) is a commonly used approach for choosing alternatives by prioritizing across multiple decision factors. The typical AHP modelling requires knowledge of criteria and/or alternatives along with their relative weights, generally elicited from field experts. Quite often, firms encounter situations where decision makers are aware of only the overall objective and a set of earmarked geographies for setting up market locations while being relatively unaware of decision criteria and relative weights. This precludes using AHP to identify promising market locations. This paper conceptualizes a market selection decision model that integrates AHP with statistical modelling techniques to identify the attractive market locations for the purpose of expansion. The model first uses principal component analysis and multiple regression to determine significant decision criteria and their weights. Thereafter, it applies AHP to prioritize the market locations across the decision criteria. This integrative approach is illustrated for identifying the attractive locations in rural markets for a steel firm in India. The major advantage of this approach is that unlike the existing models, it works in situations when firms have not enough knowledge about factors for evaluating alternative market locations. Another key advantage of the proposed model is that of economizing resources for data collection on variables representing decision factors. Copyright © 2012 John Wiley & Sons, Ltd.     

Cluster Analysis Examination of Serial Killer Profiling Categories: A Bottom‐Up Approach

Two studies explored the validity of dichotomous classification of organised/disorganised serial killers and the four typologies (visionary, mission, hedonistic, and power/control) adopted by the Federal Bureau of Investigation (FBI). Tables documenting crime scene criteria were devised consisting of 50 typifying different crime scenes (Study 1) and 48 crime scenes (taken from the 50 crime scene criteria) with a further 10 motive‐based crime scene criteria (Study 2). Adopting content analysis, crime scenes depicted for 40 (Study 1) and 40 (Study 2) serial killers using secondary sources of data were dichotomously coded for the presence or absence of the crime scene criteria. These data were inputted for agglomerative hierarchical cluster using Ward's method as the clustering algorithm. Differences in the nature of clusters were found for male and female serial killers; however, there was no empirical support for the organised/disorganised classifications or the four typologies. The ‘bottom‐up’ approach resulted in clusters from the different crime scene criteria that helped to understand how these criteria were associated within the serial killer cohort considered. It is concluded that the resulting clusters in both studies support the notion of there being an underlying organised element to most serial murder and that serial murders differ according to the nature of disorganised crime scene criteria present. Copyright © 2011 John Wiley & Sons, Ltd.