Purpose Drawing from cognitive and emotional perspectives, the purpose of this paper is to theorize and test a dual-pathway model in which moral disengagement and anger toward organization act as two explanatory mechanisms of the association between perceived overqualification and employee cyberloafing. The authors further proposed that the strengths of these two mediating mechanisms depend on employee moral identity. Design/methodology/approach The authors used hierarchical linear modeling to examine the hypotheses by analyzing a sample of 294 employees working in 71 departments in China. Findings Results revealed that moral disengagement and anger toward organization mediated the positive link between perceived overqualification and cyberloafing beyond the influence of social exchange. Furthermore, moral identity attenuated the association between the mediators (i.e. moral disengagement and anger) and cyberloafing and the indirect relationship between perceived overqualification and cyberloafing. Originality/value Extant studies have examined the effects of perceived overqualification on employee behaviors in terms of task performance, organizational citizenship behavior, proactive behavior, as well as withdrawal behavior. The study expands this line of research by empirically investigating whether and how perceived overqualification influences cyberloafing.

Previous researchers have documented that the color red enhances one's sexual attraction to the opposite sex. The current study further examined the moderating role of sexual dimorphism in red effects. The results indicated that red enhanced men's sexual attraction to women with more feminine facial characteristics but had no effect on ratings of perceived general attractiveness. Red clothing also had a marginally significant effect on men's sexual attractiveness. In addition, regardless of sexual dimorphism cues, male participants rated women with red as warmer and more competent. The underlying mechanisms of the red effect, the limitations of the current study, and suggestions for future directions are discussed.

Social categorization is the foundation of stereotype activation, and the process from social categorization to stereotype activation is rapid. However, the time from social categorization to stereotype activation is unknown. This study involves a real-time measurement of the time course of gender-stereotype activation beginning with gender categorization using event-related potential technology with a face as the priming stimulus. We found that 195 ms after a face stimulus was presented, brain waves stimulated by male or female gender categorization showed a clear separation, with male faces stimulating larger N200 waves. In addition, 475 ms after a face stimulus appeared or 280 ms after the gendercategorization process occurred, gender-stereotype-consistent and gender-stereotype-inconsistent stimuli were distinct, with gender-stereotype-inconsistent stimuli inducing larger N400 waves. These results indicate that during gender-stereotype activation by face perception, gender categorization occurs approximately 195 ms after seeing a face stimulus and a gender stereotype is activated at approximately 475 ms.

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Discrete choice models typically incorporate product/service attributes, many of which are categorical. Researchers code these attributes in one of two ways: dummy coding and effects coding. Whereas previous studies favor effects coding citing that it resolves confounding between attributes, our analysis demonstrates that such confounding does not exist in either method, even when a choice model contains alternative specific constants. Furthermore, we show that because of the lack of understanding of the equivalence between the two coding methods, a sizeable number of previously published articles have misinterpreted effects coded results. The misinterpretation generates conflicting preference ordering and renders t‐statistics, marginal willingness to pay, as well as consumer surplus/compensating variation estimates invalid. We show that severe misinterpretation occurs for any categorical attribute that contains more than two discrete levels. The frequency of two‐level attributes used in discrete choice analyses may have led some past studies to overlook this error. Given its equivalence and lower likelihood of misinterpretation, we recommend dummy coding.