Reinforcement-related neurons in the primate basal forebrain respond to the learned significance of task events rather than to the hedonic attributes of reward

The objective of this study was to determine if the responses of basal forebrain neurons are related to the cognitive processes necessary for the performance of behavioural tasks, or to the hedonic attributes of the reinforcers delivered to the monkey as

网上消费者购物动机、点击流行为及其之间的关系

Online shopping has been a growing phenomenon all over the world as well as China in the recent years. Studies on online shopping with clickstream data have become a new research stream. But it is a pity that the online conversion rate is low. Accordingly, we can study on online consumers focusing on their shopping motivation, and put their shopping motivation and clickstream behavior into an integrative frame, study on the both construction and their relationship, and then we can get insight in chinese online consumers. This study has two processes. First, this study will use the questionnaire to explore all kinds of consumers’ online shopping motivation, and then emend the questionnaire and form the ultimate one for the second process. Second, we will simulate a shopping site to get clickstream data, participants need to complete the ultimate questionnaire at the same time. We will analyse the integrated data from two measures, cluster analysis separately, and explore the correspondence between the two cluster methods. Results show that, first, Chinese online shoppers contain five steady motivation factors: usefulness, fashion involvement, ease of use on searching, ease of use on alternative evaluation, ease of use after trade. Fashion involvement is comparatively independent, while the other have correlations between each two. Second, Chinese consumers can be clustered into five steady clusters according to online shopping motivation: functional shoppers, following shoppers, surfing shoppers, conflicting shoppers, e-laggard. The five clusters have significant differences on job, monthly income and online shopping experience of late six months, while have no significant differences on gender, age and education. Third, Chinese consumers can be clustered into five steady clusters according to clickstream data: functional browsers, hedonic browsers, impulsive shoppers, comparative shoppers and knowledge building browsers. The five clusters have significant differences only on age, while have no significant differences on other demographic variables. Fourth, the cluster methods according to motivation and according to clickstream data are two comparatively independent cluster frame, but they have limit correspondence.

从赌博游戏中的损失厌恶行为看情感预测与体验在决策中的作用

In Kermer, Driver-Linn, Wilson and Gilbert’s (2006) study on affective forecast, they found that people have a tendency to overestimate affective reactions in gains and losses, and people expect losses to have greater hedonic impact than gains of equal magnitude. Because of thus affective forecasting error, people prefer to irrationally avoid losses. Loss aversion is then seen as both a wealth-maximizing error and an affect-maximizing error. The present study examined the relationships among affective forecast, affective experience and loss aversion, and tested Kermer et al.’s (2006) conclusion that people’s loss aversion is an affective forecasting error. In experiment 1, we examined the relationship between affective forecast and loss aversion. Kermer et al.’s (2006) hypothesized that when people expect losses to have greater hedonic impact than gains, they will accept the gambling task, and when people expect gains to have greater hedonic impact than losses, they will refuse the gambling task. We found that (1) individuals with lower loss aversion had a greater tendency to accept a gambling task than those with higher loss aversion; (2) individuals with lower loss aversion expected losses and gains to have smaller affective impacts than those with higher loss aversion. Thus, people never exactly calculated their forecasting affective. In experiment 2, we examined the relationship between affective forecast and affective experience. Consistent with Kermer et al.’s (2006) finding, we found that our participants tended to overestimate affective reactions in gains as well as losses. More interestingly, Kermer et al.’s (2006) found that participants’ predictions for a loss were significantly more distant from experienced emotions than were their predictions for a win, we, however, found the opposite —participants’ predictions for a win were significantly more distant from the experienced emotions than were their predictions for a loss. These experiments further validated the relations between affection and decision making, and contributed to our understanding on the affective reactions to future events. Our study imply that it was not the exact calculation of affective forecast on decision outcomes, but rather the magnitude of affection on outcomes, that influenced people’s affective decision making. It indicated that those with lower magnitude of affection would less like to avoid losses, and thus more like to accept a gambling task.