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Advice taking is a crucial part of decision-making and has attracted the interest of scholars across the world. Laboratory research on advice taking has revealed several robust phenomena, such as sensitivity to advice quality or a tendency to underutilize advice. Despite extensive investigations in different countries, cultural differences in advice taking remain understudied. Knowing whether such cultural differences exist would not only be interesting from an academic standpoint but might also have consequences for multinational organizations and businesses. Here, we argue that prior laboratory research on cultural differences in advice taking is hindered by confounding factors, particularly the confound between participants’ cultural background and task difficulty. To draw a valid conclusion about cultural differences in advice taking, it is vital to develop a decision task devoid of this confound. Here, we develop such a judgment task and demonstrate that the core phenomena of advice taking manifest in a sample of German participants. We then use this task in a cross-national comparison of German and Chinese participants. While the core phenomena of advice taking consistently manifested in both samples, some differences emerged. Most notably, Chinese participants were more receptive of advice, even though they still underutilized it. This greater reliance on advice was driven by Chinese participants’ greater preference for averaging their own and the advisor’s judgments. We discuss how our findings extend current understanding of the nuanced interplay between cultural values and the dynamics of advice taking.

Following up on a recent debate, we examined advice taking in dyads compared to individuals in a set of three studies (total N = 303 dyads and 194 individuals). Our first aim was to test the replicability of an important previous finding, namely that dyads heed advice less than individuals because they feel more confident in the accuracy of their initial judgments. Second, we aimed to explain dyads’ behavior based on three premises: first, that dyads understand that the added value of an outside opinion diminishes when the initial pre-advice judgment is made by two judges rather than one judge (given that the dyad members’ opinions are independent of each other); second, that they fail to recognize when the assumption of independence of opinions does not hold; and third, that the resistance to advice commonly observed in individuals persists in groups but is neither aggravated nor ameliorated by the group context. The results of our studies show consistently that previous findings on advice taking in dyads are replicable. They also support our hypothesis that groups exhibit a general tendency to heed advice less than individuals, irrespective of whether the accuracy of their initial judgments warrants this behavior. Finally, based on the three assumptions mentioned above, we were able to make accurate predictions about advice taking in dyads, prompting us to postulate a general model of advice taking in groups of arbitrary size.

We investigate decision-making in the Judge-Advisor-System where one person, the ``judge'', wants to estimate the number of a certain entity and is given advice by another person. The question is how to combine the judge's initial estimate and that of the advisor in order to get the optimal expected outcome. A previous approach compared two frequently applied strategies, taking the average or choosing the better estimate. In most situations, averaging produced the better estimates. However, this approach neglected a third strategy that judges frequently use, namely a weighted mean of the judges' initial estimate and the advice. We compare the performance of averaging and choosing to weighting in a theoretical analysis. If the judge can, without error, detect ability differences between judge and advisor, a straight-forward calculation shows that weighting outperforms both of these strategies. More interestingly, after introducing errors in the perception of the ability differences, we show that such imperfect weighting may or may not be the optimal strategy. The relative performance of imperfect weighting compared to averaging or choosing depends on the size of the actual ability differences as well as the magnitude of the error. However, for a sizeable range of ability differences and errors, weighting is preferable to averaging and more so to choosing. Our analysis expands previous research by showing that weighting, even when imperfect, is an appropriate advice taking strategy and under which circumstances judges benefit most from applying it.

Six experiments investigated how the distance between one's initial opinion and advice relates to advice utilization. Going beyond previous research, we relate advice distance to both relative adjustments and absolute adjustments towards the advice, and we also investigate a second mode of advice utilization, namely confidence shifts due to social validation. Whereas previous research suggests that advice is weighted less the more it differs from one's initial opinion, we consistently find evidence of a curvilinear pattern. Advice is weighted less when advice distance is low and when it is high. This is in particular because individuals are much more likely to retain their initial opinions in the light of near advice. Also, absolute opinion adjustments towards the advice increases in a monotone fashion as advice distance increases. This finding is in contrast to the predictions of the theoretical framework previous studies on advice distance are based on, social judgment theory. Instead, they data are more in line with a simple stimulus-response model suggesting that absolute adjustments towards the advice increase with advice distance but---potentially---with diminished sensitivity. Finally, our data show that advice can be utilized even when it receives zero weight during belief revision. The closer advice was to the initial opinions, the more it served as a means for social validation, increasing decision-makers' confidence in the accuracy of their final opinions. Thus, our findings suggest that advice utilization is a more complex function of advice distance than previously assumed.