Preference Structures and Co-comparability Graphs

Order structures such as linear orders, weak orders, semiorders and interval orders are often considered as models of a decision maker's preferences. In this paper we introduce and study new order structures characterized by their symmetric part belonging to certain classes of co-comparability graphs. We outline possible interpretations and suggest special representations of these structures and we point out their potential use for approximating relations obtained through a multicriteria aggregation procedure. We provide various characterizations of the new structures (as well as of older ones) in terms of minimal forbidden configurations and by algebraic conditions.     

An adaptive approach for modelling multiattribute choice

An adaptive approach for modelling individual-level choice among multiattribute alternatives using the binary logit model is presented. The algorithm involves the collection of paired comparison data. In an effort to maximize the amount of information obtainable from each response, it is based on the experimental design criterion of D-optimality. A simulation study indicates that the proposed algorithm outperforms other sequential selection approaches in terms of estimation accuracy and predictive efficiency under certain circumstances. The results appear to encourage the use of such an adaptive algorithm for individual-level modelling in light of the potential reduction in data requirements without significant loss in predictive accuracy.     

Opium of the people? National identification predicts well-being over time

Social group membership and its social-relational corollaries, for example, social contact, trust, and support, are prophylactic for health. Research has tended to focus on how direct social interactions between members of small-scale groups (i.e., a local sports team or community group) are conducive to positive health outcomes. The current study provides evidence from a longitudinal cross-cultural sample (N = 6,748; 18 countries/societies) that the prophylactic effect of group membership is not isolated to small-scale groups, and that members of groups do not have to directly interact, or in fact know of each other to benefit from membership. Our longitudinal analyses suggest that national identification (strength of association with the country/society of which one is a citizen) predicts lower anxiety and improved health; national identification was in fact almost as positively predictive of health status as anxiety was negatively predictive. The findings indicate that identification with large-scale groups, like small-scale groups, is palliative, and are discussed in terms of globalization and banal nationalism.     

计算模型在道德认知研究中的应用

道德认知关注道德心理背后的信息加工。近年来, 研究者开始将计算模型应用于道德认知研究, 以探索道德认知如何在大脑中实现。但目前研究者对道德认知进行计算建模的研究处于起步阶段。计算模型(漂移扩散模型、效用模型、强化学习模型和分层高斯过筛器模型)在道德认知行为和生理研究上的运用量化了道德决策、道德判断和道德推理背后的认知过程和神经机制。此外, 这一新进展对理解反社会行为和精神障碍等有所助益。最后, 计算建模有待完善, 未来研究需要关注其潜在的问题。     

Novice construction of chess memory

Novice acquisition of skilled recall of chess positions was studied in an experiment in which two novices studied a series of five hundred chess positions during a period of several months. They spent fifteen minutes to half an hour a day teaching themselves these positions. As a result their skill in recalling chess positions rose from sixteen percent to somewhere between forty to fifty percent. The learning curve proved to have a shape which indicates that in the beginning learning is very fast but after some 100-150 studied positions the speed of learning decreases substantially. A computer simulation was used to model the results and analyse alternative explanations. Two alternative ways of thinking were tested. In the first, chunk construction was assumed to be based on the neighbourhood of associated pieces. The second model assumed a frequency-based correlative association process. Although the learning curves of the two models are very similar in shape to those of the subjects, the frequency-based associative model gave a better explanation for the data. This is why it is natural to suggest that common co-occurrence in addition to easily recognizable chess-specific characteristics, like colour and type of pieces, guide associative processes during chess players' learning of chess-specific chunks.     

A stochastic model of consideration set sizes

This paper proposes a new model of consideration set sizes, which relies on a stochastic modelling approach to better understand data patterns. The paper combines the Poisson distribution with the lognormal distribution proposed by Hauser and Wernerfelt (1990) to create the Poisson lognormal (PLN) model of consideration set sizes. An advantage of PLN is that it allows variance within a given individual consumer. This is a crucial factor for brand managers who wish to choose a particular market to promote their brand, as a higher within‐individual variance suggests that there is more chance for a consumer to change their consideration set size, whereas a lower within‐individual variance indicates that a consumer tends to stick to his/her consideration set size. The paper then uses 10 datasets including service, durable and fast‐moving consumer goods across four countries to validate the new model and compare it with the lognormal model. The results show that PLN gives a good fit to these data. It outperforms the lognormal model. The average mean absolute percentage error of the PLN model is 12 per cent, whereas that of the lognormal model is 26 per cent. For managerial implications, the paper proposes a better tool to help brand managers analyse the nature and intensity of competition that is facing their brands. Also, relying on its stochastic element, the proposed model can help brand managers predict future brand consideration by their consumers, as well as evaluate any change in brand consideration, caused by marketing activity such as sales promotion and advertising. Copyright © 2014 John Wiley & Sons, Ltd.     

The role of moral commitment within the Investment Model

The Investment Model (Rusbult, 1980) defines general commitment as a long‐term orientation towards relationship maintenance and feelings of psychological attachment, influenced by satisfaction, quality of alternatives and intrinsic/extrinsic investments. We suggest the importance of additionally assessing moral commitment, defined by an intrapersonal predisposition to remain in the relationship (Johnson, 1991). We argue moral commitment's association to perceived intrinsic investments acting as internal barriers influencing general commitment and promoting relationship maintenance. A correlational study resorting to structural equation modelling showed that moral commitment predicted intrinsic investments, which in turn predicted general commitment (Model 1). No direct paths emerged from moral commitment to satisfaction or quality of alternatives (Model 2), nor it emerged as a fourth direct predictor of general commitment (Model 3). Results are discussed under relationships maintenance and dissolution frameworks.     

Executive function and psychosocial adjustment in healthy children and adolescents: A latent variable modelling investigation

The objective of this study was to establish latent executive function (EF) and psychosocial adjustment factor structure, to examine associations between EF and psychosocial adjustment, and to explore potential development differences in EF-psychosocial adjustment associations in healthy children and adolescents. Using data from the multisite National Institutes of Health (NIH) magnetic resonance imaging (MRI) Study of Normal Brain Development, the current investigation examined latent associations between theoretically and empirically derived EF factors and emotional and behavioral adjustment measures in a large, nationally representative sample of children and adolescents (7–18 years old; N = 352). Confirmatory factor analysis (CFA) was the primary method of data analysis. CFA results revealed that, in the whole sample, the proposed five-factor model (Working Memory, Shifting, Verbal Fluency, Externalizing, and Internalizing) provided a close fit to the data, χ²(66) = 114.48, p < .001; RMSEA = .046; NNFI = .973; CFI = .980. Significant negative associations were demonstrated between Externalizing and both Working Memory and Verbal Fluency (p < .01) factors. A series of increasingly restrictive tests led to the rejection of the hypothesis of invariance, thereby precluding formal statistical examination of age-related differences in latent EF-psychosocial adjustment associations. Findings indicate that childhood EF skills are best conceptualized as a constellation of interconnected yet distinguishable cognitive self-regulatory skills. Individual differences in certain domains of EF track meaningfully and in expected directions with emotional and behavioral adjustment indices. Externalizing behaviors, in particular, are associated with latent Working Memory and Verbal Fluency factors.     

Psychological ownership in relation to workplace trust and turnover intent

The study investigated the relationship between workplace trust, psychological ownership and turnover intent within a South African professional services organisation. A cross-sectional quantitative survey design was used to collect data from a purposive sample (n = 302) of skilled, highly skilled and professional employees in a professional services industry. The participants completed the Psychological Ownership Questionnaire, Workplace Trust Survey, and Turnover Intentions Scale. The results from structural equation modelling (SEM) suggest psychological ownership to be significantly related to workplace trust (positively) and turnover intent (negatively). In addition, the findings indicate psychological ownership to fully mediate the relationship between workplace trust and turnover intent. By implication, work environments that fostered workplace trust would increase the level of psychological ownership that employees’ experienced, which, in turn, would reduce employees’ intent to leave their workplace.