模糊决策中决策偏好的情景依赖性
|
摘要
在面临确定选项和风险选项时大多数人都表现出了风险规避、安全寻求；在不确定决策领域,当面临风险选项和模糊选项时,大多人又表现出了模糊规避,风险寻求。Camerer和Weber (1992)提出了模糊保险金(ambiguity medium)的概念,发现个体甘愿付出一定的模糊保险金去寻求进一步的信息,从而减少模糊程度。Einhorn和Hogarth (1986)发现在面临损失时,模糊厌恶会出现反转。Heath (1991)提出当人们感到有能力或者当对不确定的来源有足够的认识时,模糊厌恶就不会发生。那么究竟在什么条件下,人们模糊厌恶,什么条件下,人们模糊寻求呢?针对这个问题,我们从不同的角度上进行了探讨。此外,我们还采用了各种不同的实验任务,选择任务、投注任务、出价任务、交易任务,分别对模糊决策的决策偏好进行了研究。当模糊厌恶发生时,这种模糊厌恶下的加工机制是怎样的呢?目前已有的模糊决策理论主要从变异性大小、需要的满足、启发式等角度去模拟了对模糊决策的心理加工。那么哪种理论更能有效地去解释模糊厌恶呢?模糊决策是特殊的、复杂的风险决策还是一种独立的决策类型,也是最近神经经济学里面争议的一个问题。一系列的fMRI的研究分别得出了不同的观点,但是目前为止没有人采用事件相关电位技术(ERP),从概率加工的角度,在决策时程上来探讨模糊决策和风险决策之间的关系。
根据上述的问题和存在的争论,我们制订了整个研究框架。首先是一个探索性实验,目的在于探索被试在完全模糊的情景下(没有相关知识经验的前提下),究竟是采用什么方式进行判断决策的。实验采用单因素的被试内实验设计,自变量为六种不同概率条件下的决策。因变量为被试作出决策的反应时和正确率。实验任务是一个关于输赢的判断任务。结果发现：被试是采用概率性的思维模式进行决策的。实验1探索了被试在不同的模糊程度下的模糊决策中的决策偏好,目的在于检验模糊厌恶是具有稳定性还是具有情景依赖性,当模糊程度发生变化时,人们对于模糊厌恶的程度以及决策的偏好是否也会发生变化。实验采用了3×4的两因素被试内设计,自变量1是球的数目,自变量2是模糊程度。因变量1是风险选备择项下和模糊备择项下的选择率和反应时；因变量2是对风险备择项下和模糊备择项下抽到红球的可能性进行的评定。实验任务为艾尔斯伯格选瓶任务的变式,采用了二择一的迫选式问题,让被试在风险备择项和模糊备择项里面作出选择。结果发现：球数的不同对决策的偏好基本上没有影响,变异性理论和启发式调整理论仅得到了部分的验证。模糊程度的不同,对决策的偏好有影响；模糊程度较高时,被试倾向于模糊厌恶,模糊程度较低时倾向于模糊寻求。对于两选项决策问题,决策过程更符合扩散模型。实验2是在实验1的基础上,对不同模糊程度的模糊决策的ERP研究,根据实验1的结果,我们选择了三种不同的概率区间。实验任务为艾尔斯伯格选瓶任务的变式,采用了二择一的追选式问题,让被试在风险备择项和模糊备择项里面作出选择。结果发现：对不同的模糊程度(概率区间)的加工,在脑电上是没有差异的,对模糊备择项的加工和对风险备择项的加工,在0-100%和50-50%的条件下以及在20-80%和50-50%的条件下,在脑电上是没有差异的,而在40-60%和50-50%的条件下,在脑电上是有差异的,差异波主要是一个晚期的正成分(LPC)。这些结果说明,从概率加工的角度来看(实验任务中,通过呈现概率区间的方式代表模糊备择项的模糊程度),模糊决策与风险决策下对概率的评估似乎是相同的,不同的只是决策过程上的差异,当两个备择项之间的差异较大时,能轻松的做出决策,而当两个备择项之间的差异较小时,会产生一个决策冲突,较难做出决策。通过上面三个实验,我们探索了被试在模糊决策情景下的思维方式,同时对不同的概率区间所代表的不同的模糊程度进行了脑机制的研究,在实验3里面,我们对不同概率所代表的不同的风险程度进行了脑机制的研究,与实验2进行对比,目的在于进一步验证模糊决策和风险决策之间存在的关系,判断模糊决策是否是特殊的、复杂的风险决策。实验的任务是进行数字判断,首先提供给被试一个数字,然后要求被试预测后面即将出现的数字是比前面提供的数字大还是小。将1-9,九个数字按不确定性程度的高低分成五类。行为结果发现：(1)反应时,随着不确定性程度的增强而逐渐增长；(2)正确率,被试决策的平均正确率基本上符合数字本身的可预测率。脑电结果发现：在200-300ms的时间窗口内,不确定和确定决策任务下的预测率都诱发了一个晚期的负成分(N2),五种任务之间(随着不确定程度的降低)存在着一个梯度的变化,其中50%和62.5%之间不存在着显著差异,其它预测率之间都存在着显著差异。这些结果表明被试在不确定决策任务中会对不同预测率进行归类表征,并对不同的不确定程度有不同的知觉。实验4是模糊决策中的禀赋效应的研究。本研究从模糊保险金和禀赋效应的角度出发,探讨了当模糊备择项变成自己的禀赋时,被试在模糊决策中的决策偏好。实验采取两因素的被试间实验设计。第一个因素为选择项,第二个因素为出价的顺序,先WTP后WTA和先WTA后WTP；WTP是指玩模糊备择项(或者风险备择项)愿意付出的最大价格,WTA是指放弃玩模糊备择项(或者风险备择项)愿意接受的最小价格。实验选取艾尔斯伯格选瓶任务的变式。被试需要完成三个任务：选择任务、投注任务和出价任务。结果发现：选择偏好、下赌注、出价三个角度上,都没有发现这种模糊厌恶效应。这说明模糊厌恶,并不具有稳定性。风险备择项和模糊备择项都没有出现了禀赋效应,也没有出现内隐的模糊保险金效应。实验5是在不同领域(得和失)对模糊决策偏好和模糊决策中的禀赋效应的检验。从得、失两个角度对模糊厌恶、模糊保险金和禀赋效应进行了研究。此外,在实验4里面,我们得到的结论与以往的研究是不一致的,不一致的原因可能是WTP和WTA分别要求给出的是价格的上限和下限,这种差异对被试的决策是有影响的。在实验5中,针对实验4里面存在的问题,通过改变指导语,要求被试给出愿意付出和愿意接受的价格,进一步探讨了被试的决策偏好、模糊保险金和禀赋效应问题。采用2×2×2的三因素被试间实验设计,自变量1：不同的情景。自变量2：出价条件(WTP和WTA)。自变量3：交易条件(模糊交易风险和风险交易模糊)。实验选取艾尔斯伯格选瓶任务的变式。结果发现：从选择偏好上来说,被试偏好于风险备择项,但输赢的情景对选择的偏好是有影响的。只有在赢钱情景下的WTP上存在着模糊厌恶和模糊保险金效应；在输钱情景下以及在赢钱情景下且模糊备择项是自己的禀赋时,被试都偏好于模糊备择项,认为模糊备择项更可能让自己获得收益或者减少损失。赢输对风险备择项的影响要大于对模糊备择项的影响。在交易条件下,有些被试是模糊厌恶的,愿意付出模糊保险金,但总体上来看,被试不是模糊厌恶的。而且输赢情景对被试的选择没有太大的影响,在损失领域,被试更倾向于模糊寻求的观点没有得到验证。对于模糊备择项而言,出现了禀赋效应；对于风险备择项而言,没有出现禀赋效应；本实验也没有发现内隐的模糊保险金效应。实验6探讨了自尊对模糊决策中的决策偏好的影响,实验采取3×3的两因素混合实验设计。自变量1：自尊水平,被试间变量；自变量2：为自己做决策需要承担责任、为自己的公司做决策需要承担责任和为自己的公司做决策而不需要承担责任,被试内变量。因变量：被试对风险方案(方案1)和不同模糊方案(方案2和方案3)的选择率。结果发现：对于低自尊的被试,在自己是决策主体的条件下,三种方案的选择率基本一致；在自己是一名员工,并需要对决策后果承担责任的条件下,则倾向于模糊规避；在自己是一名员工,但不需要对决策后果承担责任的条件下,倾向于模糊寻求。而对于高自尊的被试,在这三种条件下,都倾向于风险寻求,模糊规避。并且在需要对决策后果承担责任的条件下,高自尊被试与低自尊被试相比,更容易模糊规避；当不需要对决策的结果承担责任时,低自尊被试与高自尊被试相比,更容易模糊寻求。这些结果表明,高自尊的被试更担心模糊方案带来的负面损失,从而伤害自己的自尊。支持了高自尊个体比低自尊个体更具有防御反应的理论。
整合上述实验的结果,得出如下结论：模糊厌恶不是稳定不变的,在不同的情景下,被试的决策偏好是不相同的,因此模糊决策中的决策偏好是具有情景依赖性的；从概率加工的角度来看,模糊决策与风险决策下对概率的评估似乎是相同的,不同的只是决策过程上的差异,当两个备择项之间的差异较大时,能轻松的做出决策,而当两个备择项之间的差异较小时,会产生一个决策冲突,较难做出决策。
Most people showed risk aversion, safety seeking when facing with safety option and risky option. In uncertain decision-making, when faced with the risky option and ambiguity option, most of them are also demonstrated ambiguity aversion and risk seeking. Camerer and Weber (1992) proposed conception of ambiguity medium, found that individuals are willing to pay a certain amount of ambiguity medium to seek further information, thus reducing the degree of ambiguity. Einhorn and Hogarth (1986) found that in the face of loss, ambiguity aversion will appear reversed. Heath (1991) found that the ambiguity aversion would not have happened when people have the ability or have sufficient knowledge to the sources of uncertainty. So under what conditions, it is ambiguity aversion, and under what conditions, it is ambiguity seeking? To address this issue, we discussed the problem from different opinion. The decision preference under different ambiguity degree, the decision preference when the ambiguity alternatives becoming the endowment of oneself, the effect on the decision preference whether decision-makers is a player or not, the decision preferences of the subjects in the different self-esteem levels. In addition, we also used a variety of different experimental task, choice task, betting task, bidding task and exchange task, respectively. The decision preferences were studied under different tasks. When the ambiguity aversion occurs, what the processing mechanism is? At present, there existed some ambiguity decision-making theories, mainly including variability theory, to meet peoples'needs, the heuristic theory. They simulate the mental process of the decision-making in different perspective. Which is more effective to explain the ambiguity aversion? Ambiguity decision-making is a special, complex risk decision-making or an independent decision-making type, which is a controversial issue in recent neuroeconomics, a series of fMRI studies reached a different opinion, respectively. But so far no one using event-related potentials technique, from the perspective of probability process, explores the relationship between ambiguity decision-making and risk decision-making
Based on the above issues and the existed debate, we have developed a research framework as a whole. An exploratory experiment was studied, the purpose to explore how subjects make the judgment and decision in the complete ambiguous scenarios (no relevant knowledge and experience). Single factor experiment within subjects was tested, the independent variable:the six different probability of decision-making. The dependent variable was the response time and the accuracy when made the decision. Experimental task is a task of judging winning or losing. The results showed that the participants made the decision using probabilistic thinking. Experiment 1 is to explore the decision-making preferences under different ambiguity degree. The purpose was to examine that the ambiguity aversion is stable or scenario-dependent. When the ambiguity degree changed, would the degree of ambiguity aversion and decision-making preference also change? In addition, this study further validate the theory of variability and anchoring adjustment heuristic theory, the bottle size effect and decision-making model was examined. Two factor experiment within subjects were tested, the independent variable 1 is the number of balls; the independent variables 2 is the degree of ambiguity, that is the possibility of pumping red ball from the bottle. The dependent variable 1 is the choice rate and the response time under the risky option and the ambiguity option. The dependent variable 2 is the assessment to the possibility of pumping the red ball from the bottle under the risky option and the ambiguity option. Experimental task was the variant of the Ellsberg paradox, using a forced-choice between two alternatives, so that subjects made a choice between the risky option and the ambiguity option. The results showed that:the different number of balls basically had no difference to the decision preferences, variability theory and heuristic adjustment theory has been only a part of the verification. The different ambiguity degree had influence on decision-making preferences; a higher degree of ambiguity, the subjects were inclined to dislike ambiguity, a lower degree of ambiguity; the subjects were inclined to ambiguity seeking. For a choice between two alternatives, decision-making process was more in line with the diffusion model. Experiment 2 was based on experiment 1, was an ERP research for different degree of ambiguity. According to the results of Experiment 1, we have chosen three different probability intervals. Experimental task was a variant of Ellsberg paradox, using a forced-choice between two alternatives, subjects made the choice between the ambiguity option and the risky option. The results showed that:there was no difference in the ERPs when processing the ambiguity of different degree. When processing the ambiguity alternative and the risky alternative, there was no difference in the ERPs in 0-100% and 50-50% conditions, as well as in the 20-80% and 50-50% conditions. The ERPs in 40-60% and 50-50% conditions was different. The difference wave is primarily a late positive component (LPC).These results show that from the perspective of the probability process (we represents the ambiguity degree of the alternative items by showing the probability of ambiguity interval in the experiment), the decision-making process of ambiguity decision-making and risk decision-making seems to be the same. The difference only existed in the decision process. When the difference between the two alternatives was large, decision-making was easy, and when he difference between the two alternatives was small, will produce a decision-making conflicts, and the decision-making was difficulty. Experiment 3 is a ERP study of risky decision-making under different predictive rate, through the above three experiments, we explored the way of thinking of the subjects' in the ambiguity scenarios, while explored the brain mechanisms of the ambiguity of different degree represented by the different probability interval.In the experiment 3, we made a ERP research on the different risk degree represented by different probabilities, comparing two studies aimed at further validation of the relationship between ambiguity decision and risk decision to determine whether the ambiguity decision-making is a special complex risk decision-making or not. The task is to make the judgment to the nine numbers, first of all, we give subjects a figure, soon give them a feedback figure, and subjects were asked to predict the feedback figure will be bigger or smaller than the figure provided in front.The number from one to nine was divided in to five categories according to the degree of uncertainty. Behavior results showed that the response time was increased with the strength of the uncertainty degree by contrasting the data of two conditions. The results showed that the mean correct percentage of the decision was accord with the percentage of prediction. The ERPs result indicated that both the uncertain decision and the certain decision elicited a later negative ERP component (N2) from 200 ms to 300 ms. There was a change in the mean amplitude among the five tasks and there was no difference between the probability of 50% and the probability of 62.5%. These results indicated the participants would make the representation of categorization when facing the uncertain decision and have the different perception to the different uncertainty degree. Experiment 4 is a research on endowment effect in ambiguous decision making. In this study, in the ambiguity medium and endowment effects perspective, we future discussed subjects' decision preference, when ambiguity alternative became into ones' own endowment. Two factors experimental design between subjects was taken. The first factor was the choice option; the second factor was the order for the bid, first WTP post WTA and first WTA post WTP. The experiment task was a variant of Ellsberg paradox. Subjects were required to complete three tasks:selection task, betting tasks, and pricing tasks. The results showed that:the ambiguity aversion effect have not found in the three tasks. This shows that the ambiguity aversion does not have stability. Subjects didn't show the endowment effect for the risky alternative and ambiguity alternative. Experiment 5 is a research on the endowment effect for the risky alternative and ambiguity alternative in different domains (gain and loss). People' attitudes towards ambiguity would change with the size of the income and the probability. When the profit value is positive, and the probability of gaining the profit value is also high, people will tend to risk decision-making at this time. But when faced with negative incomes, that is losses, and the probability of loss is also high, people will tend to ambiguity decision-making at this time. So it is necessary to study the ambiguity aversion, ambiguity medium and endowment effect from the perspective of gain and loss. The conclusions we drawed in the experiment 4 were inconsistent with the previous studies. The reason maybe that WTP gave a cap of price and WTA gave a floor to the price. The deviation of prices received is questionable. The decision-making is influential by this difference. In experiment 5, for which the problems in Experiment 4, by changing the guidance of language, the decision preference was further explored, which required subjects to give the price willing to pay and willingness to accept with choice tasks, pricing task and exchange tasks, in gain and lost domains. Three factors experimental design between subjects were tested. The independent variable 1:different scenarios. The independent variable 2:pricing conditions. The three independent variables:exchange conditions. The experimental task was a variant of Ellsberg paradox. The results showed that the subjects were risky preferences from the choice preferences, but win or lose scenario are influential to the choice preferences. There existed ambiguity aversion and ambiguity medium effect when subjects were asked to offer the price of "willing to pay" only in the winning WTP scenario. The subjects were ambiguity seeking when the ambiguous alternative is one's own endowment in losing scenarios as well as in winning scenarios. They thought they are more likely to make a return or reduce their losses in the ambiguity alternative. The impact of losing or winning scenario on the risky alternative should be more than on the ambiguity alternative. In the exchange condition, some subjects were ambiguity aversion, and are willing to pay ambiguity medium; but on the whole, they were not ambiguity aversion. And win or lose scenario had not much impact on the subjects'choice. The opinion that subjects were more inclined to ambiguity seeking in the loss has not been verified. There has been endowment effect for the ambiguity alternative. For the risky alternative, there was no endowment effect. There was no implicit ambiguity medium effect in this experiment. We explored the influence of the self-esteem on the decision-making preferences in the experiment 6. The two factors of mixed experimental design were adopted. The independent variable 1:self-esteem level was the between-subjects variable. The second independent variables: make decision for oneself and need to take responsibility for their own decision; make decision for their own companies and need to take responsibility for their own decision; make decision for their own companies and need not to take responsibility for their own decision; was the within-subjects variable. The dependent variable:the subjects' choice rate to the risky program (Program 1) and the ambiguity program (program 2 and program 3). The results showed that:the choice rate of three programs was basically the same for the subjects of the low self-esteem when they were decision-maker. They tend to ambiguity aversion when they are employee and need to take responsibility for the consequences of the decision-making. They tend to ambiguity seeking when they are employee and need not to take responsibility for the consequences of the decision-making. The subjects of the high self-esteem tend to risk seeking and ambiguity avoiding in these three conditions. Subjects of high self-esteem compared with the low self-esteem ones and medium self-esteem were more likely to ambiguity avoiding when need to bear the responsibility for the consequences of decision-making. Subjects of low self-esteem compared with the high self-esteem ones and medium self-esteem were more likely to ambiguity seeking when need not to bear the responsibility for the consequences of decision-making. The theory of defensive response that high self-esteem individuals were more defensive than individuals of low self-esteem was supported in this study.
Integration of the above-mentioned experimental results, we draw the following conclusions: ambiguity aversion is not stable. Subjects'decision-making preferences are not the same in different scenarios, so the ambiguity decision-making preference is a scenario-dependent. From the perspective of the probability process, the decision-making process of ambiguity decision-making and risk decision-making seems to be the same. The difference only existed in the decision process. When the difference between the two alternatives was large, decision-making was easy, and when he difference between the two alternatives was small, will produce a decision-making conflicts, and the decision-making was difficulty.This demonstrated that the ambiguity decision-making seems to be a unique, complex risky decision-making.
根据上述的问题和存在的争论,我们制订了整个研究框架。首先是一个探索性实验,目的在于探索被试在完全模糊的情景下(没有相关知识经验的前提下),究竟是采用什么方式进行判断决策的。实验采用单因素的被试内实验设计,自变量为六种不同概率条件下的决策。因变量为被试作出决策的反应时和正确率。实验任务是一个关于输赢的判断任务。结果发现：被试是采用概率性的思维模式进行决策的。实验1探索了被试在不同的模糊程度下的模糊决策中的决策偏好,目的在于检验模糊厌恶是具有稳定性还是具有情景依赖性,当模糊程度发生变化时,人们对于模糊厌恶的程度以及决策的偏好是否也会发生变化。实验采用了3×4的两因素被试内设计,自变量1是球的数目,自变量2是模糊程度。因变量1是风险选备择项下和模糊备择项下的选择率和反应时；因变量2是对风险备择项下和模糊备择项下抽到红球的可能性进行的评定。实验任务为艾尔斯伯格选瓶任务的变式,采用了二择一的迫选式问题,让被试在风险备择项和模糊备择项里面作出选择。结果发现：球数的不同对决策的偏好基本上没有影响,变异性理论和启发式调整理论仅得到了部分的验证。模糊程度的不同,对决策的偏好有影响；模糊程度较高时,被试倾向于模糊厌恶,模糊程度较低时倾向于模糊寻求。对于两选项决策问题,决策过程更符合扩散模型。实验2是在实验1的基础上,对不同模糊程度的模糊决策的ERP研究,根据实验1的结果,我们选择了三种不同的概率区间。实验任务为艾尔斯伯格选瓶任务的变式,采用了二择一的追选式问题,让被试在风险备择项和模糊备择项里面作出选择。结果发现：对不同的模糊程度(概率区间)的加工,在脑电上是没有差异的,对模糊备择项的加工和对风险备择项的加工,在0-100%和50-50%的条件下以及在20-80%和50-50%的条件下,在脑电上是没有差异的,而在40-60%和50-50%的条件下,在脑电上是有差异的,差异波主要是一个晚期的正成分(LPC)。这些结果说明,从概率加工的角度来看(实验任务中,通过呈现概率区间的方式代表模糊备择项的模糊程度),模糊决策与风险决策下对概率的评估似乎是相同的,不同的只是决策过程上的差异,当两个备择项之间的差异较大时,能轻松的做出决策,而当两个备择项之间的差异较小时,会产生一个决策冲突,较难做出决策。通过上面三个实验,我们探索了被试在模糊决策情景下的思维方式,同时对不同的概率区间所代表的不同的模糊程度进行了脑机制的研究,在实验3里面,我们对不同概率所代表的不同的风险程度进行了脑机制的研究,与实验2进行对比,目的在于进一步验证模糊决策和风险决策之间存在的关系,判断模糊决策是否是特殊的、复杂的风险决策。实验的任务是进行数字判断,首先提供给被试一个数字,然后要求被试预测后面即将出现的数字是比前面提供的数字大还是小。将1-9,九个数字按不确定性程度的高低分成五类。行为结果发现：(1)反应时,随着不确定性程度的增强而逐渐增长；(2)正确率,被试决策的平均正确率基本上符合数字本身的可预测率。脑电结果发现：在200-300ms的时间窗口内,不确定和确定决策任务下的预测率都诱发了一个晚期的负成分(N2),五种任务之间(随着不确定程度的降低)存在着一个梯度的变化,其中50%和62.5%之间不存在着显著差异,其它预测率之间都存在着显著差异。这些结果表明被试在不确定决策任务中会对不同预测率进行归类表征,并对不同的不确定程度有不同的知觉。实验4是模糊决策中的禀赋效应的研究。本研究从模糊保险金和禀赋效应的角度出发,探讨了当模糊备择项变成自己的禀赋时,被试在模糊决策中的决策偏好。实验采取两因素的被试间实验设计。第一个因素为选择项,第二个因素为出价的顺序,先WTP后WTA和先WTA后WTP；WTP是指玩模糊备择项(或者风险备择项)愿意付出的最大价格,WTA是指放弃玩模糊备择项(或者风险备择项)愿意接受的最小价格。实验选取艾尔斯伯格选瓶任务的变式。被试需要完成三个任务：选择任务、投注任务和出价任务。结果发现：选择偏好、下赌注、出价三个角度上,都没有发现这种模糊厌恶效应。这说明模糊厌恶,并不具有稳定性。风险备择项和模糊备择项都没有出现了禀赋效应,也没有出现内隐的模糊保险金效应。实验5是在不同领域(得和失)对模糊决策偏好和模糊决策中的禀赋效应的检验。从得、失两个角度对模糊厌恶、模糊保险金和禀赋效应进行了研究。此外,在实验4里面,我们得到的结论与以往的研究是不一致的,不一致的原因可能是WTP和WTA分别要求给出的是价格的上限和下限,这种差异对被试的决策是有影响的。在实验5中,针对实验4里面存在的问题,通过改变指导语,要求被试给出愿意付出和愿意接受的价格,进一步探讨了被试的决策偏好、模糊保险金和禀赋效应问题。采用2×2×2的三因素被试间实验设计,自变量1：不同的情景。自变量2：出价条件(WTP和WTA)。自变量3：交易条件(模糊交易风险和风险交易模糊)。实验选取艾尔斯伯格选瓶任务的变式。结果发现：从选择偏好上来说,被试偏好于风险备择项,但输赢的情景对选择的偏好是有影响的。只有在赢钱情景下的WTP上存在着模糊厌恶和模糊保险金效应；在输钱情景下以及在赢钱情景下且模糊备择项是自己的禀赋时,被试都偏好于模糊备择项,认为模糊备择项更可能让自己获得收益或者减少损失。赢输对风险备择项的影响要大于对模糊备择项的影响。在交易条件下,有些被试是模糊厌恶的,愿意付出模糊保险金,但总体上来看,被试不是模糊厌恶的。而且输赢情景对被试的选择没有太大的影响,在损失领域,被试更倾向于模糊寻求的观点没有得到验证。对于模糊备择项而言,出现了禀赋效应；对于风险备择项而言,没有出现禀赋效应；本实验也没有发现内隐的模糊保险金效应。实验6探讨了自尊对模糊决策中的决策偏好的影响,实验采取3×3的两因素混合实验设计。自变量1：自尊水平,被试间变量；自变量2：为自己做决策需要承担责任、为自己的公司做决策需要承担责任和为自己的公司做决策而不需要承担责任,被试内变量。因变量：被试对风险方案(方案1)和不同模糊方案(方案2和方案3)的选择率。结果发现：对于低自尊的被试,在自己是决策主体的条件下,三种方案的选择率基本一致；在自己是一名员工,并需要对决策后果承担责任的条件下,则倾向于模糊规避；在自己是一名员工,但不需要对决策后果承担责任的条件下,倾向于模糊寻求。而对于高自尊的被试,在这三种条件下,都倾向于风险寻求,模糊规避。并且在需要对决策后果承担责任的条件下,高自尊被试与低自尊被试相比,更容易模糊规避；当不需要对决策的结果承担责任时,低自尊被试与高自尊被试相比,更容易模糊寻求。这些结果表明,高自尊的被试更担心模糊方案带来的负面损失,从而伤害自己的自尊。支持了高自尊个体比低自尊个体更具有防御反应的理论。
整合上述实验的结果,得出如下结论：模糊厌恶不是稳定不变的,在不同的情景下,被试的决策偏好是不相同的,因此模糊决策中的决策偏好是具有情景依赖性的；从概率加工的角度来看,模糊决策与风险决策下对概率的评估似乎是相同的,不同的只是决策过程上的差异,当两个备择项之间的差异较大时,能轻松的做出决策,而当两个备择项之间的差异较小时,会产生一个决策冲突,较难做出决策。
Most people showed risk aversion, safety seeking when facing with safety option and risky option. In uncertain decision-making, when faced with the risky option and ambiguity option, most of them are also demonstrated ambiguity aversion and risk seeking. Camerer and Weber (1992) proposed conception of ambiguity medium, found that individuals are willing to pay a certain amount of ambiguity medium to seek further information, thus reducing the degree of ambiguity. Einhorn and Hogarth (1986) found that in the face of loss, ambiguity aversion will appear reversed. Heath (1991) found that the ambiguity aversion would not have happened when people have the ability or have sufficient knowledge to the sources of uncertainty. So under what conditions, it is ambiguity aversion, and under what conditions, it is ambiguity seeking? To address this issue, we discussed the problem from different opinion. The decision preference under different ambiguity degree, the decision preference when the ambiguity alternatives becoming the endowment of oneself, the effect on the decision preference whether decision-makers is a player or not, the decision preferences of the subjects in the different self-esteem levels. In addition, we also used a variety of different experimental task, choice task, betting task, bidding task and exchange task, respectively. The decision preferences were studied under different tasks. When the ambiguity aversion occurs, what the processing mechanism is? At present, there existed some ambiguity decision-making theories, mainly including variability theory, to meet peoples'needs, the heuristic theory. They simulate the mental process of the decision-making in different perspective. Which is more effective to explain the ambiguity aversion? Ambiguity decision-making is a special, complex risk decision-making or an independent decision-making type, which is a controversial issue in recent neuroeconomics, a series of fMRI studies reached a different opinion, respectively. But so far no one using event-related potentials technique, from the perspective of probability process, explores the relationship between ambiguity decision-making and risk decision-making
Based on the above issues and the existed debate, we have developed a research framework as a whole. An exploratory experiment was studied, the purpose to explore how subjects make the judgment and decision in the complete ambiguous scenarios (no relevant knowledge and experience). Single factor experiment within subjects was tested, the independent variable:the six different probability of decision-making. The dependent variable was the response time and the accuracy when made the decision. Experimental task is a task of judging winning or losing. The results showed that the participants made the decision using probabilistic thinking. Experiment 1 is to explore the decision-making preferences under different ambiguity degree. The purpose was to examine that the ambiguity aversion is stable or scenario-dependent. When the ambiguity degree changed, would the degree of ambiguity aversion and decision-making preference also change? In addition, this study further validate the theory of variability and anchoring adjustment heuristic theory, the bottle size effect and decision-making model was examined. Two factor experiment within subjects were tested, the independent variable 1 is the number of balls; the independent variables 2 is the degree of ambiguity, that is the possibility of pumping red ball from the bottle. The dependent variable 1 is the choice rate and the response time under the risky option and the ambiguity option. The dependent variable 2 is the assessment to the possibility of pumping the red ball from the bottle under the risky option and the ambiguity option. Experimental task was the variant of the Ellsberg paradox, using a forced-choice between two alternatives, so that subjects made a choice between the risky option and the ambiguity option. The results showed that:the different number of balls basically had no difference to the decision preferences, variability theory and heuristic adjustment theory has been only a part of the verification. The different ambiguity degree had influence on decision-making preferences; a higher degree of ambiguity, the subjects were inclined to dislike ambiguity, a lower degree of ambiguity; the subjects were inclined to ambiguity seeking. For a choice between two alternatives, decision-making process was more in line with the diffusion model. Experiment 2 was based on experiment 1, was an ERP research for different degree of ambiguity. According to the results of Experiment 1, we have chosen three different probability intervals. Experimental task was a variant of Ellsberg paradox, using a forced-choice between two alternatives, subjects made the choice between the ambiguity option and the risky option. The results showed that:there was no difference in the ERPs when processing the ambiguity of different degree. When processing the ambiguity alternative and the risky alternative, there was no difference in the ERPs in 0-100% and 50-50% conditions, as well as in the 20-80% and 50-50% conditions. The ERPs in 40-60% and 50-50% conditions was different. The difference wave is primarily a late positive component (LPC).These results show that from the perspective of the probability process (we represents the ambiguity degree of the alternative items by showing the probability of ambiguity interval in the experiment), the decision-making process of ambiguity decision-making and risk decision-making seems to be the same. The difference only existed in the decision process. When the difference between the two alternatives was large, decision-making was easy, and when he difference between the two alternatives was small, will produce a decision-making conflicts, and the decision-making was difficulty. Experiment 3 is a ERP study of risky decision-making under different predictive rate, through the above three experiments, we explored the way of thinking of the subjects' in the ambiguity scenarios, while explored the brain mechanisms of the ambiguity of different degree represented by the different probability interval.In the experiment 3, we made a ERP research on the different risk degree represented by different probabilities, comparing two studies aimed at further validation of the relationship between ambiguity decision and risk decision to determine whether the ambiguity decision-making is a special complex risk decision-making or not. The task is to make the judgment to the nine numbers, first of all, we give subjects a figure, soon give them a feedback figure, and subjects were asked to predict the feedback figure will be bigger or smaller than the figure provided in front.The number from one to nine was divided in to five categories according to the degree of uncertainty. Behavior results showed that the response time was increased with the strength of the uncertainty degree by contrasting the data of two conditions. The results showed that the mean correct percentage of the decision was accord with the percentage of prediction. The ERPs result indicated that both the uncertain decision and the certain decision elicited a later negative ERP component (N2) from 200 ms to 300 ms. There was a change in the mean amplitude among the five tasks and there was no difference between the probability of 50% and the probability of 62.5%. These results indicated the participants would make the representation of categorization when facing the uncertain decision and have the different perception to the different uncertainty degree. Experiment 4 is a research on endowment effect in ambiguous decision making. In this study, in the ambiguity medium and endowment effects perspective, we future discussed subjects' decision preference, when ambiguity alternative became into ones' own endowment. Two factors experimental design between subjects was taken. The first factor was the choice option; the second factor was the order for the bid, first WTP post WTA and first WTA post WTP. The experiment task was a variant of Ellsberg paradox. Subjects were required to complete three tasks:selection task, betting tasks, and pricing tasks. The results showed that:the ambiguity aversion effect have not found in the three tasks. This shows that the ambiguity aversion does not have stability. Subjects didn't show the endowment effect for the risky alternative and ambiguity alternative. Experiment 5 is a research on the endowment effect for the risky alternative and ambiguity alternative in different domains (gain and loss). People' attitudes towards ambiguity would change with the size of the income and the probability. When the profit value is positive, and the probability of gaining the profit value is also high, people will tend to risk decision-making at this time. But when faced with negative incomes, that is losses, and the probability of loss is also high, people will tend to ambiguity decision-making at this time. So it is necessary to study the ambiguity aversion, ambiguity medium and endowment effect from the perspective of gain and loss. The conclusions we drawed in the experiment 4 were inconsistent with the previous studies. The reason maybe that WTP gave a cap of price and WTA gave a floor to the price. The deviation of prices received is questionable. The decision-making is influential by this difference. In experiment 5, for which the problems in Experiment 4, by changing the guidance of language, the decision preference was further explored, which required subjects to give the price willing to pay and willingness to accept with choice tasks, pricing task and exchange tasks, in gain and lost domains. Three factors experimental design between subjects were tested. The independent variable 1:different scenarios. The independent variable 2:pricing conditions. The three independent variables:exchange conditions. The experimental task was a variant of Ellsberg paradox. The results showed that the subjects were risky preferences from the choice preferences, but win or lose scenario are influential to the choice preferences. There existed ambiguity aversion and ambiguity medium effect when subjects were asked to offer the price of "willing to pay" only in the winning WTP scenario. The subjects were ambiguity seeking when the ambiguous alternative is one's own endowment in losing scenarios as well as in winning scenarios. They thought they are more likely to make a return or reduce their losses in the ambiguity alternative. The impact of losing or winning scenario on the risky alternative should be more than on the ambiguity alternative. In the exchange condition, some subjects were ambiguity aversion, and are willing to pay ambiguity medium; but on the whole, they were not ambiguity aversion. And win or lose scenario had not much impact on the subjects'choice. The opinion that subjects were more inclined to ambiguity seeking in the loss has not been verified. There has been endowment effect for the ambiguity alternative. For the risky alternative, there was no endowment effect. There was no implicit ambiguity medium effect in this experiment. We explored the influence of the self-esteem on the decision-making preferences in the experiment 6. The two factors of mixed experimental design were adopted. The independent variable 1:self-esteem level was the between-subjects variable. The second independent variables: make decision for oneself and need to take responsibility for their own decision; make decision for their own companies and need to take responsibility for their own decision; make decision for their own companies and need not to take responsibility for their own decision; was the within-subjects variable. The dependent variable:the subjects' choice rate to the risky program (Program 1) and the ambiguity program (program 2 and program 3). The results showed that:the choice rate of three programs was basically the same for the subjects of the low self-esteem when they were decision-maker. They tend to ambiguity aversion when they are employee and need to take responsibility for the consequences of the decision-making. They tend to ambiguity seeking when they are employee and need not to take responsibility for the consequences of the decision-making. The subjects of the high self-esteem tend to risk seeking and ambiguity avoiding in these three conditions. Subjects of high self-esteem compared with the low self-esteem ones and medium self-esteem were more likely to ambiguity avoiding when need to bear the responsibility for the consequences of decision-making. Subjects of low self-esteem compared with the high self-esteem ones and medium self-esteem were more likely to ambiguity seeking when need not to bear the responsibility for the consequences of decision-making. The theory of defensive response that high self-esteem individuals were more defensive than individuals of low self-esteem was supported in this study.
Integration of the above-mentioned experimental results, we draw the following conclusions: ambiguity aversion is not stable. Subjects'decision-making preferences are not the same in different scenarios, so the ambiguity decision-making preference is a scenario-dependent. From the perspective of the probability process, the decision-making process of ambiguity decision-making and risk decision-making seems to be the same. The difference only existed in the decision process. When the difference between the two alternatives was large, decision-making was easy, and when he difference between the two alternatives was small, will produce a decision-making conflicts, and the decision-making was difficulty.This demonstrated that the ambiguity decision-making seems to be a unique, complex risky decision-making.
引文
陈雪峰,张志学(2009).认知闭合需要评述.心理科学进展17(1),51-55.
陈荣,何枫(2008).小概率权重问题及其市场应用.心理学报40， 210-218
冯廷勇(2007).一种不确定情景中决策过程的认知与神经机制研究：[博士学位论文].重庆：西南大学,27-28
魏景汉,罗跃嘉(2002).认知事件相关脑电位教程.北京：经济日报出版社,32-40
张运红,郭春彦(2008).知觉和语义表征关系的ERP研究,科学通报,24,3086-3095
张凤华(2009).不同模糊程度下模糊决策的决策偏好,心理学探新6,51-55
张凤华,邱江,杨群,张庆林(2009).传递性推理的ERP研究,心理发展与教育4,,68-74
张凤华,王金娥,张庆林(2007).事件相关电位P300与蓝斑-去甲肾上胰素交感神经系统的研究与过展,中国组织工程研究与临床康复,11(5),965-967
张士昌,曹靖宇(2003).对决策偏好的理性思考,山东社会科学,2003,3,116-119
Bechara, A., Damasio, H., Tranel, D.& Damasio, A.R. et al. (1997). Deciding advantageously before knowing the advantageous strategy. Science,275,1293-1295.
Bechara, A., Damasio, H., Tranel, D.& Damasio, A.R.(2005).The Iowa Gambling Task and the somatic marker hypothesis:some questions and answers. TRENDS in Cognitive Sciences,9, 159-162.
Bechara, A., Damasio, H.,& Damasio, A.R.(2003). Role of amygdale in decision-making. Annals of the NewYork Academy of Science,985,356-369.
Bechara, A.(2004). The role of emotion in decision-making:Evidence from neurological patients with orbitofrontal damage. Brain and Cognition,55,30-40.
Blackwood, N., Ffytche, D., Simmons, A., Bentall, R., Murray, R., Howard, R.(2004).The cerebellum and decision making under uncertainty. Cognitive Brain Research,20,46-53.
Bogacz, R.(2007). Optimal decision-making theories:linking neurobiology with behaviour. TRENDS in Cognitive Sciences,11,118-125.
Brand, M., Fujiwar, E., Borsutzky, S., Kalbe, E.,& Kessler, J.(2005). Decision-Making Deficits of Korsakoff Patients in a New Gambling Task With Explicit Rules:Associations With Executive Functions. Neuropsychology,19,267-277.
Brand, M., Labudda K.,& Markowitsch, H.J.(2006). Neuropsychological correlates of decision-making in ambiguous and risky situations. Neural Networks,19,1266-1276.
Brand, M., Kalbe, E., Labudda, K., Fujiwara, E., Kessler, J.,& Markowitsch, H. J.(2005). Decision-making impairments in patients with pathological gambling. Psychiatry Research,133, 91-99.
Brand, M., Grabenhorst, F., Starcke, K., Vandekerckhove, M. M.P.,& Markowitsch, H. J.(2007). Role of the amygdala indecisions under ambiguity and decisions under risk:Evidence from patients with Urbach-Wiethe disease. Neuropsychologia,45,1305-1317.
Brown, T.C. (2005). Loss aversion without the endowment effect, and other explanations for the WTA-WTP disparity. Journal of Economic Behavior & Organization,57,367-379
Burgess, N., Maguire, E. A., Spiers, H. J., O'Keefe, J.(2001). A temporoparietal and prefrontal network for retrieving the spatial context of lifelike events. Neurolmage,14,439-530.
Camerer, C.F.,&Weber, M. (1992). Recent developments in modeling preferences:uncertainty and ambiguity. Journal of Risk and Uncertainty,5(4),325-370.
Chien-H. L., Shih-C. C., Kao, D.T., Chaang-Y.K. (2006). The role of emotions in the endowment effect. Journal of economic psychology,27,589-597
Clark, L., Cools, R.,& Robbins,T.W.(2004). The neuropsychology of ventral prefrontal cortex: Decision-making and reversal learning. Brain and Cognition,55,41-53.
Climcher, P.W., Rustichini, A.(2004). Neuroeconomics:The consilience of Brain and decision. Science,306,447-452
Critchley, H.D., Mathias, C.J.,& Dolan, R.J. (2001). Neural activity in the human brain relating to uncertainty and arousal during anticipation. Neuron,29,537-545.
Demiralp, T., Ademoglu, A., Comerchero, M.,& Polich, J. (2001). Wavelet analysis of P3a and P3b. Brain Topography,13,251-267.
Denes-Raj, V.,& Epstein, S. (1994). Conflict between intuitive and rational processing:When people behave against their better judgment. Journal of Personality and Social Psychology,66, 819-829.
De Ven, N.V., Zeelenberg, M.,& Dijk, E. V.(2005). Buying and selling exchange goods:outcome information, curiosity and the endownment effect. Journal of Economic Psychology,26, 459-468.
Dijk, E. V.,& Zeelenberg, M. (2003). The discounting of ambiguous information in economic
decision making. Journal of Behavioral Decision Making,16,341-352.
Dijk, E. V.,& Zeelenberg, M. (2007).When curiosity killed regret:avoiding or seeking the unknown in decision-making under uncertainty. Journal of Experimental Social Psychology,43,656-662
Donchin, E.(1980). Surprise!…Surprise? Presidential address,18(5),493-513
Einhorn, H. J.,& Hogarth, R. M. (1985). Ambiguity and uncertainty in probabilistic inference. Psychological Review,92,433-461.
Ellsberg, D.. Risk, ambiguity, and the savage axioms. Quarterly Journal of Economics,1961,75, 643-669.
Fox, C.R.,&Weber, M.(2002). Ambiguity Aversion, Comparative Ignorance and Decision Context. Organizational Behavior and Human Decision Processes,88,476-498.
Fiorillo, C.D., Tobler, P.N.,& Schultz, W.(2003). Discrete coding of reward probability and uncertainty by dopamine neurons. Science,299,1898-1902.
Fukui, H., Murai, T., Fukuyama, H., Hayashi, T., Hamakawa, T.(2005). Functional activity related to risk anticipation during performance of the Iowa gambling task. NeuroImage,24,253-259.
Folstein, J.R.& Van Petten, C. (2008). Influence of cognitive control and mismatch on the N2 component of the ERP:A review. Society for Psychophysiological Research, Psychophysiology, 45,152-170.
Ghirardato, P., Maccheroni, F.,& Marinacci, M.(2004). Differentiating ambiguity and ambiguity attitude. Journal of Economic Theory,118,133-173.
Gilboa, L., Schmeidler, D.(1989). J, Math, Econ,18,141.
Hoffrage, U., Gigerenzer, G., Krauss, S.,& Martignon, L.(2002). Representation facilitates reasoning:what natural frequencies are and what they are not. Cognition,84,343-352.
Huettel, S.A., Song, A.W.,& McCarthy, G. (2005). Decisions under uncertainty:probabilistic context influences activity of prefrontal and parietal cortices. J. Neurosci.,25,3304-3311.
Huettel, S.A., Stowe, C.J., Gordon, E.M., Warner, B.T.,& Platt, M.L.(2006). Neural Signatures of Economic Preferences for Risk and Ambiguity. Neuron,49,765-775.
Hsu, M., Bhatt, M., Adolphs, R., Tranel, D.,& Camerer, C. F. (2005). Neural systems responding to degrees of uncertainty in human decision-making. Science,310,1680-1683.
Knight, F. H.. Risky, uncertainty, and profit. Boston:Houghton-Mifflin,1921.
Krain, A.L., Arbuckle, R., Wilson, A. M., Castellanos, F. X.,& Milham, M. P.(2006). Distinct neural mechanisms of risk and ambiguity:A meta-analysis of decision-making. Neurolmage,32,477-484.
Kirsten, G. V., Ricarda, I. S.,& von Cramon, D. Y. (2003). Predicting events of varying probability:uncertainty investigated by fMRI. Neurolmage,19,271-280.
Leland, D.S., Arce, E., Feinstein, J.S.,& Paulus, M.P.(2006). Young adult stimulant users'increased striatal activation during uncertainty is related to impulsivity. Neurolmage,33,725-731.
Maddock, R. J.(1999). The retrosplenial cortex and emotion:new insights from functional neuroimaging of the human brain. Trends of Neuroscience,22,310-316.
Maddock, R. J., Garrett, A. S., Buonocore, M. H.(2002). Posterior cingulate cortex activation by emotional words:fMRI evidence from a valence decision task. Hum. Brain Mapping,18, 30-41.
Ohara, S., Wang, L., Ku, Y., Lenz, F.A.., Hsiao, S.S., Hong, B.,& Zhou, Y.D. (2008). Neural activities of tactile cross-modal working memory in humans:an event-related potential study. Neuroscience,152,692-702.
Ohara, S., Lenz, F., Zhou, Y.D(2006). Sequential neural processes of tactile-visual cross-modal working memory. Neuroscience,139,299-309.
Pigott, S., Milner, B.(1993). Memory for different aspects of complex visual scenes after unilateral temporal- or frontal-lobe resection. Neuropsychologia,31,1-15.
Platt, M.L,& Huettel, S.A. (2008). Risky business:the neuroeconomics of decision making under uncertainty. Nature Neuroscience,11,398-403.
Plott, C.R.,& Zeiler, K.(2005). The willingness to pay-willingness to accept gap, the "endowment effect," subject misconceptions, and experimental procedures for eliciting valuations. The American economic review,95(3),530-545.
Polich, J.,& Comerchero, M. D. (2003). P3a from visual stimuli:Typicality, task, and topography. Brain Topography,15,141-152.
Pulford, B.D.,& lman, A.M. (2008). Size doesn't really matter:Ambiguity aversion in Ellsberg urns with few balls. Experimental Psychology,55,31-37.
Ratcliff, R., Thapar, A.,& Mckoon, G.(2003). A diffusion model analysis of the effects of aging on brightness discrimination. Percept. Psychophys,65,523-535.
Ribem, R. A. (1996). Fuzzy multiple attribute decision making a review and new preference elicitation technique. Fuzzy sets and systems,78,155-181.
Roca, M., Hogarth, R.M.,&Maule,A.J.(2006). Ambiguity seeking as a result of the status quo bias. Journal of Risk and Uncertainty,32(3),175-194.
Roca,M.,&Maule, A.J. (2009). The effect of endowment on the demand for probabilistic information, Organization behavior and Human decision process,109,56-66.
Rottenstreich, Y.,& Kivetz, R.(2006). On decision making without likelihood judgment. Organizational Behavior and Human Decision Processes,101,74-88.
Ruff, C., Knauff, M., Spreer, J. (2003). Reasoning and working memory:common and distinct neuronal processes. Neuropsychologia,41,1241-1253.
Rode, C., Cosmides, L., Hell, W.,& Tooby, J. (1999). When and why do people avoid unknow probabilities in decisions under uncertainty? Testing some predictions from optimal forging theory. Cognition,72,269-304.
Rustichini, A.(2005). Emotion and Reason in Making Decisions. SCIENCE,310,1624-1625.
Samuelson, W.,& Zeckhauser,R.(1988). Status quo bias in decision making. Journal of Risk and Uncertainty,1,7-59.
Sinz, H., Zamarian, L., Benke, T., Wenning, G.K.,& Delazer, M.(2008). Impact of ambiguity and risk on decision making in mild Alzheimer's disease. Neuropsychologia,46,2043-2055.
Slovic, P.,& Lichtenstein, S. (1971). Comparison of Bayesian and regression approaches to the study of information processing in judgment. Organizational Behavior and Human Performance,6,649-744.
Smith, K., Dickhaut, J., McCabe, K.,& Pardo, J.V.(2002). Neuronal Substrates for Choice Under Ambiguity, Risk, Gains, and Losses. Management Science,48,711-718.
Spiers, H. J., Burgess, N., Maguire, E. A., Baxendale, S. A., Hartley, T., Thompson, P. J., et al. (2001). Unilateral temporal lobectomy patients show lateralized topographical and episodic memory deficits in a virtual town. Brain,124,2476-2489.
Stephens, D. W.,& Krebs, J. R. (1986). Foraging theory. Princeton, NJ:Princeton University Press.
Strahilevitz,M.A.,&Loewenstein,G.(1998). The effect of ownership history on the valuation of objects. Journal of consumer research,25,276-289.
Thaler, R.H.(1980). Towards a positive theory of consumer choice. Journal of economic behavior and organization,1,39-60
Vickers, D.. Evidence for an accumulator model of psychophysical discrimination. Ergonomics, 1970,13,37-58.
Volz, K. G., Schubotz, R. I.,& Cramon, D. Y.. Predicting events of varying probability:uncertainty investigated by fMRI. NeuroImage,2003,19,271-280.
Yoshida W.,&Ishii S. Resolution of uncertainty in prefrontal cortex. Neuron,2006,50,781-789.
陈荣,何枫(2008).小概率权重问题及其市场应用.心理学报40， 210-218
冯廷勇(2007).一种不确定情景中决策过程的认知与神经机制研究：[博士学位论文].重庆：西南大学,27-28
魏景汉,罗跃嘉(2002).认知事件相关脑电位教程.北京：经济日报出版社,32-40
张运红,郭春彦(2008).知觉和语义表征关系的ERP研究,科学通报,24,3086-3095
张凤华(2009).不同模糊程度下模糊决策的决策偏好,心理学探新6,51-55
张凤华,邱江,杨群,张庆林(2009).传递性推理的ERP研究,心理发展与教育4,,68-74
张凤华,王金娥,张庆林(2007).事件相关电位P300与蓝斑-去甲肾上胰素交感神经系统的研究与过展,中国组织工程研究与临床康复,11(5),965-967
张士昌,曹靖宇(2003).对决策偏好的理性思考,山东社会科学,2003,3,116-119
Bechara, A., Damasio, H., Tranel, D.& Damasio, A.R. et al. (1997). Deciding advantageously before knowing the advantageous strategy. Science,275,1293-1295.
Bechara, A., Damasio, H., Tranel, D.& Damasio, A.R.(2005).The Iowa Gambling Task and the somatic marker hypothesis:some questions and answers. TRENDS in Cognitive Sciences,9, 159-162.
Bechara, A., Damasio, H.,& Damasio, A.R.(2003). Role of amygdale in decision-making. Annals of the NewYork Academy of Science,985,356-369.
Bechara, A.(2004). The role of emotion in decision-making:Evidence from neurological patients with orbitofrontal damage. Brain and Cognition,55,30-40.
Blackwood, N., Ffytche, D., Simmons, A., Bentall, R., Murray, R., Howard, R.(2004).The cerebellum and decision making under uncertainty. Cognitive Brain Research,20,46-53.
Bogacz, R.(2007). Optimal decision-making theories:linking neurobiology with behaviour. TRENDS in Cognitive Sciences,11,118-125.
Brand, M., Fujiwar, E., Borsutzky, S., Kalbe, E.,& Kessler, J.(2005). Decision-Making Deficits of Korsakoff Patients in a New Gambling Task With Explicit Rules:Associations With Executive Functions. Neuropsychology,19,267-277.
Brand, M., Labudda K.,& Markowitsch, H.J.(2006). Neuropsychological correlates of decision-making in ambiguous and risky situations. Neural Networks,19,1266-1276.
Brand, M., Kalbe, E., Labudda, K., Fujiwara, E., Kessler, J.,& Markowitsch, H. J.(2005). Decision-making impairments in patients with pathological gambling. Psychiatry Research,133, 91-99.
Brand, M., Grabenhorst, F., Starcke, K., Vandekerckhove, M. M.P.,& Markowitsch, H. J.(2007). Role of the amygdala indecisions under ambiguity and decisions under risk:Evidence from patients with Urbach-Wiethe disease. Neuropsychologia,45,1305-1317.
Brown, T.C. (2005). Loss aversion without the endowment effect, and other explanations for the WTA-WTP disparity. Journal of Economic Behavior & Organization,57,367-379
Burgess, N., Maguire, E. A., Spiers, H. J., O'Keefe, J.(2001). A temporoparietal and prefrontal network for retrieving the spatial context of lifelike events. Neurolmage,14,439-530.
Camerer, C.F.,&Weber, M. (1992). Recent developments in modeling preferences:uncertainty and ambiguity. Journal of Risk and Uncertainty,5(4),325-370.
Chien-H. L., Shih-C. C., Kao, D.T., Chaang-Y.K. (2006). The role of emotions in the endowment effect. Journal of economic psychology,27,589-597
Clark, L., Cools, R.,& Robbins,T.W.(2004). The neuropsychology of ventral prefrontal cortex: Decision-making and reversal learning. Brain and Cognition,55,41-53.
Climcher, P.W., Rustichini, A.(2004). Neuroeconomics:The consilience of Brain and decision. Science,306,447-452
Critchley, H.D., Mathias, C.J.,& Dolan, R.J. (2001). Neural activity in the human brain relating to uncertainty and arousal during anticipation. Neuron,29,537-545.
Demiralp, T., Ademoglu, A., Comerchero, M.,& Polich, J. (2001). Wavelet analysis of P3a and P3b. Brain Topography,13,251-267.
Denes-Raj, V.,& Epstein, S. (1994). Conflict between intuitive and rational processing:When people behave against their better judgment. Journal of Personality and Social Psychology,66, 819-829.
De Ven, N.V., Zeelenberg, M.,& Dijk, E. V.(2005). Buying and selling exchange goods:outcome information, curiosity and the endownment effect. Journal of Economic Psychology,26, 459-468.
Dijk, E. V.,& Zeelenberg, M. (2003). The discounting of ambiguous information in economic
decision making. Journal of Behavioral Decision Making,16,341-352.
Dijk, E. V.,& Zeelenberg, M. (2007).When curiosity killed regret:avoiding or seeking the unknown in decision-making under uncertainty. Journal of Experimental Social Psychology,43,656-662
Donchin, E.(1980). Surprise!…Surprise? Presidential address,18(5),493-513
Einhorn, H. J.,& Hogarth, R. M. (1985). Ambiguity and uncertainty in probabilistic inference. Psychological Review,92,433-461.
Ellsberg, D.. Risk, ambiguity, and the savage axioms. Quarterly Journal of Economics,1961,75, 643-669.
Fox, C.R.,&Weber, M.(2002). Ambiguity Aversion, Comparative Ignorance and Decision Context. Organizational Behavior and Human Decision Processes,88,476-498.
Fiorillo, C.D., Tobler, P.N.,& Schultz, W.(2003). Discrete coding of reward probability and uncertainty by dopamine neurons. Science,299,1898-1902.
Fukui, H., Murai, T., Fukuyama, H., Hayashi, T., Hamakawa, T.(2005). Functional activity related to risk anticipation during performance of the Iowa gambling task. NeuroImage,24,253-259.
Folstein, J.R.& Van Petten, C. (2008). Influence of cognitive control and mismatch on the N2 component of the ERP:A review. Society for Psychophysiological Research, Psychophysiology, 45,152-170.
Ghirardato, P., Maccheroni, F.,& Marinacci, M.(2004). Differentiating ambiguity and ambiguity attitude. Journal of Economic Theory,118,133-173.
Gilboa, L., Schmeidler, D.(1989). J, Math, Econ,18,141.
Hoffrage, U., Gigerenzer, G., Krauss, S.,& Martignon, L.(2002). Representation facilitates reasoning:what natural frequencies are and what they are not. Cognition,84,343-352.
Huettel, S.A., Song, A.W.,& McCarthy, G. (2005). Decisions under uncertainty:probabilistic context influences activity of prefrontal and parietal cortices. J. Neurosci.,25,3304-3311.
Huettel, S.A., Stowe, C.J., Gordon, E.M., Warner, B.T.,& Platt, M.L.(2006). Neural Signatures of Economic Preferences for Risk and Ambiguity. Neuron,49,765-775.
Hsu, M., Bhatt, M., Adolphs, R., Tranel, D.,& Camerer, C. F. (2005). Neural systems responding to degrees of uncertainty in human decision-making. Science,310,1680-1683.
Knight, F. H.. Risky, uncertainty, and profit. Boston:Houghton-Mifflin,1921.
Krain, A.L., Arbuckle, R., Wilson, A. M., Castellanos, F. X.,& Milham, M. P.(2006). Distinct neural mechanisms of risk and ambiguity:A meta-analysis of decision-making. Neurolmage,32,477-484.
Kirsten, G. V., Ricarda, I. S.,& von Cramon, D. Y. (2003). Predicting events of varying probability:uncertainty investigated by fMRI. Neurolmage,19,271-280.
Leland, D.S., Arce, E., Feinstein, J.S.,& Paulus, M.P.(2006). Young adult stimulant users'increased striatal activation during uncertainty is related to impulsivity. Neurolmage,33,725-731.
Maddock, R. J.(1999). The retrosplenial cortex and emotion:new insights from functional neuroimaging of the human brain. Trends of Neuroscience,22,310-316.
Maddock, R. J., Garrett, A. S., Buonocore, M. H.(2002). Posterior cingulate cortex activation by emotional words:fMRI evidence from a valence decision task. Hum. Brain Mapping,18, 30-41.
Ohara, S., Wang, L., Ku, Y., Lenz, F.A.., Hsiao, S.S., Hong, B.,& Zhou, Y.D. (2008). Neural activities of tactile cross-modal working memory in humans:an event-related potential study. Neuroscience,152,692-702.
Ohara, S., Lenz, F., Zhou, Y.D(2006). Sequential neural processes of tactile-visual cross-modal working memory. Neuroscience,139,299-309.
Pigott, S., Milner, B.(1993). Memory for different aspects of complex visual scenes after unilateral temporal- or frontal-lobe resection. Neuropsychologia,31,1-15.
Platt, M.L,& Huettel, S.A. (2008). Risky business:the neuroeconomics of decision making under uncertainty. Nature Neuroscience,11,398-403.
Plott, C.R.,& Zeiler, K.(2005). The willingness to pay-willingness to accept gap, the "endowment effect," subject misconceptions, and experimental procedures for eliciting valuations. The American economic review,95(3),530-545.
Polich, J.,& Comerchero, M. D. (2003). P3a from visual stimuli:Typicality, task, and topography. Brain Topography,15,141-152.
Pulford, B.D.,& lman, A.M. (2008). Size doesn't really matter:Ambiguity aversion in Ellsberg urns with few balls. Experimental Psychology,55,31-37.
Ratcliff, R., Thapar, A.,& Mckoon, G.(2003). A diffusion model analysis of the effects of aging on brightness discrimination. Percept. Psychophys,65,523-535.
Ribem, R. A. (1996). Fuzzy multiple attribute decision making a review and new preference elicitation technique. Fuzzy sets and systems,78,155-181.
Roca, M., Hogarth, R.M.,&Maule,A.J.(2006). Ambiguity seeking as a result of the status quo bias. Journal of Risk and Uncertainty,32(3),175-194.
Roca,M.,&Maule, A.J. (2009). The effect of endowment on the demand for probabilistic information, Organization behavior and Human decision process,109,56-66.
Rottenstreich, Y.,& Kivetz, R.(2006). On decision making without likelihood judgment. Organizational Behavior and Human Decision Processes,101,74-88.
Ruff, C., Knauff, M., Spreer, J. (2003). Reasoning and working memory:common and distinct neuronal processes. Neuropsychologia,41,1241-1253.
Rode, C., Cosmides, L., Hell, W.,& Tooby, J. (1999). When and why do people avoid unknow probabilities in decisions under uncertainty? Testing some predictions from optimal forging theory. Cognition,72,269-304.
Rustichini, A.(2005). Emotion and Reason in Making Decisions. SCIENCE,310,1624-1625.
Samuelson, W.,& Zeckhauser,R.(1988). Status quo bias in decision making. Journal of Risk and Uncertainty,1,7-59.
Sinz, H., Zamarian, L., Benke, T., Wenning, G.K.,& Delazer, M.(2008). Impact of ambiguity and risk on decision making in mild Alzheimer's disease. Neuropsychologia,46,2043-2055.
Slovic, P.,& Lichtenstein, S. (1971). Comparison of Bayesian and regression approaches to the study of information processing in judgment. Organizational Behavior and Human Performance,6,649-744.
Smith, K., Dickhaut, J., McCabe, K.,& Pardo, J.V.(2002). Neuronal Substrates for Choice Under Ambiguity, Risk, Gains, and Losses. Management Science,48,711-718.
Spiers, H. J., Burgess, N., Maguire, E. A., Baxendale, S. A., Hartley, T., Thompson, P. J., et al. (2001). Unilateral temporal lobectomy patients show lateralized topographical and episodic memory deficits in a virtual town. Brain,124,2476-2489.
Stephens, D. W.,& Krebs, J. R. (1986). Foraging theory. Princeton, NJ:Princeton University Press.
Strahilevitz,M.A.,&Loewenstein,G.(1998). The effect of ownership history on the valuation of objects. Journal of consumer research,25,276-289.
Thaler, R.H.(1980). Towards a positive theory of consumer choice. Journal of economic behavior and organization,1,39-60
Vickers, D.. Evidence for an accumulator model of psychophysical discrimination. Ergonomics, 1970,13,37-58.
Volz, K. G., Schubotz, R. I.,& Cramon, D. Y.. Predicting events of varying probability:uncertainty investigated by fMRI. NeuroImage,2003,19,271-280.
Yoshida W.,&Ishii S. Resolution of uncertainty in prefrontal cortex. Neuron,2006,50,781-789.