Tell Me What I Wanted to Hear: Confirmation ... - Wiley Online Library

APPLIED PSYCHOLOGY: AN INTERNATIONAL REVIEW, 2018, 67 (4), 686–722 doi: 10.1111/apps.12145

Tell Me What I Wanted to Hear: Confirmation Effect in Lay Evaluations of Financial Expert Authority Tomasz Zaleskiewicz* and Agata Gasiorowska SWPS University of Social Sciences and Humanities, Poland

In real life, people engage in interactive decision processes by consulting with experts. However, before taking advice, they must recognise the authority of an expert to assess the quality of the advice. The main goal of this research was to investigate how the confirmation effect affects lay evaluations of the epistemic authority of financial experts. Experiment 1 showed that lay people tend to ascribe greater epistemic authority to those experts whose advice confirms peoples opinions, both measured and manipulated. Experiment 2 revealed that when participants own opinions are not salient, people tend to evaluate experts authority as higher when their advice confirms social norms. In Experiment 3 we jointly investigated the effects of participants own opinions and social norms on the evaluations of authority. When both sources of expertise were made salient, decision-makers favoured advice confirming their own beliefs and used it to evaluate experts authority. Three interpretations of the role confirmation plays in the experts authority evaluations are proposed: (1) self-defensive strategies; (2) processing fluency; and (3) psychological consequences of na€ıve realism. The paper discusses practical implications of the results. We propose that increasing consumers knowledge about biases might protect their evaluations of financial advice from being susceptible to the confirmation effect.

INTRODUCTION

Advice Taking in Decision-Making In the real world, people often make judgments and decisions without having access to or understanding of professional knowledge that is necessary to reasonably address the questions they face. Patients have to make choices

* Address for correspondence: Tomasz Zaleskiewicz, SWPS University of Social Sciences and Humanities, Wroclaw Faculty of Psychology, Ostrowskiego 30B, 53-238 Wroclaw, Poland. Email: [email protected] The research project presented in this paper has been financed by the National Science Centre grant UMO-2012/05/B/HS6/00268 and the SWPS University of Social Sciences and Humanities grant BST/WROC/2017/A/11. C 2018 International Association of Applied Psychology. V

2

LAY EVALUATION OF FINANCIAL EXPERTS 687

among several medical treatments, consumers decide how to invest their money, individuals in a judicial proceeding consider what legal argumentation to use, and so on. In such cases, people typically engage in an interactive decision process by consulting with others (Harvey & Fisher, 1997; Heath & Gonzalez, 1995; Yaniv, 2004a, 2004b). For example, they turn to experts for advice to be more confident that they are making more informed decisions. However, before people start collecting information from various sources of expertise, they have to decide with whom to interact. Searching for advice when making financial choices related to investing, insuring oneself or paying taxes might be the most common examples. In the United States the size of the financial advice sector has been consistently increasing in recent years and there are a few thousand firms that offer consumers the chance to consult about their financial decisions (see http://www.apfa.net). This means that clients have to find a way of differentiating between worse and better experts and to find out which cues indicate a high-quality expert. Only those experts whose advice is perceived as valid and trustworthy are considered by people to be authorities in a particular field and can exert a determinative influence on their decisions (Kruglanski, 1989). Twyman, Harvey, and Harries (2008) analysed how naive decision-makers make their risk estimates and documented that the effect of advice about risk depends on their trust in the advisors competence (see also Siegrist, Earle, & Gutscher, 2003). However, the issue that remains problematic in this context refers to the question of how lay people not possessing professional knowledge get to know who is a better and more competent expert and whom they should trust to a higher degree. If uninformed people are not able to use analytical thinking, they must rely on intuitive processing and gut feelings, rendering their evaluations more susceptible to errors and biases (Gilovich, Griffin, & Kahneman, 2002; Kahneman, 2003). In the present paper, we propose that peoples desire to use motivated reasoning in general and confirmatory thinking in particular (Kunda, 1999) might affect their evaluations of expert authority. The main assumption is that lay peoples evaluations of financial experts authority might be distorted by the confirmation (my side) effect,1 that is, the tendency to overweight (underweight) information that is consistent (inconsistent) with ones pre-existing beliefs (Baron, 2000; Nickerson, 1998). The experimental project that will be presented in this paper empirically showed that experts whose advice is more consistent with lay peoples own preferences (opinions) tend to be perceived as having greater authority.

1 In the present paper, we use the term confirmation effect instead of confirmation bias, because the latter seems to be more appropriate for classic interpretations referring to cognitive inclinations in hypothesis testing (Klayman & Ha, 1987; Nickerson, 1998; see also the discussion on different interpretations of the term bias in Pronin, Gilovich, & Ross, 2004). C 2018 International Association of Applied Psychology. V

688 ZALESKIEWICZ AND GASIOROWSKA

3

Research on advice taking and utilising knowledge provided by others has been examined in at least two interrelated disciplines: behavioural decisionmaking (Bonaccio & Dalal, 2006; Shanteau, 1992; Sniezek, Schrah, & Dalal, 2004; Soll & Larrick, 2009; Yaniv, 2004a, 2004b) and cognitive/social psychology (Kruglanski, 2012; Kruglanski, Raviv, Bar-Tal, Raviv, Sharvit, Ellis, Bar, Pierro, & Mannetti, 2005). Researchers studying the field of judgment and decision-making (JDM) have typically focused on how lay people combine quantitative information received from others (experts or other group members), for example, how they use numbers provided by several advisors in making probabilistic forecasts (Harvey & Fischer, 1997; Yaniv, 2004a, 2004b; Yaniv & Kleinberger, 2000; Yates, Price, Lee, & Ramirez, 1996). Only a few JDM studies have examined the issue of how people use qualitative advice, for example in making decisions on matters of taste (Yaniv, Choshen-Hillel, & Milyavsky, 2011). However, projects related to knowledge formation have studied how people subjectively assimilate qualitative knowledge provided by different authorities (e.g. experts) and under which conditions they tend to rely on it (Kruglanski, 1989; Kruglanski et al., 2005). The present paper proposes argumentation based on the lay epistemic theory concerned with knowledge acquisition (Kruglanski, 1980, 1989, 2012) and presents results from a series of experiments conducted to show how lay people intuitively evaluate the authority of experts in the field of personal finance.

Epistemic Authority The central concept for our project is epistemic authority (EA), introduced by Kruglanski as a part of his lay epistemic theory (Kruglanski, 1989, 2012). EA is defined as “the extent to which an individual is inclined to treat a sources information as incontrovertible evidence for her or his judgment” (Kruglanski, 2012, p. 212). The term EA is used to refer to peoples subjective beliefs about a source of knowledge or expertise. Different sources (e.g. experts) can acquire EA to the extent that an individual believes they possess characteristics that give them such authority (Raviv, Bar-Tal, Raviv, & Abin, 1993). Once people recognise a certain source as an EA, they tend to accept the knowledge it provides as true and factual, assimilate it, and rely on it. The concept of EA is akin to the notion of source credibility, which refers to a combination of perceived expertise and trustworthiness. EA can override other types of information and exert a determining influence on individuals opinions and behaviour. People process the information from a source with greater EA more extensively, are more certain of it, and tend to act in accordance with its implications. In the lay epistemology framework, EA functions as a “stopping mechanism”. It stops the hypothesis generation sequence and promotes crystallisation of confident knowledge (Kruglanski, 2012; Kruglanski et al., 2005). Individuals may be willing to follow the advice provided by people C 2018 International Association of Applied Psychology. V

4


perceived as having EA without testing it or considering alternatives; they may also be more confident about decisions based on recommendations given by experts with high EA (Kruglanski, Orehek, Dechesne, & Pierro, 2010). For example, if decision-makers ascribe high EA to some consultants, they will make choices based on advice (e.g. financial advice) provided by these consultants without searching for other sources of knowledge. The importance of EA in knowledge formation and decision-making has spurred researchers to try to find out what factors lend a source to EA. Recent research in health psychology has demonstrated that patients attributed greater EA to physicians who recommended an active treatment (inoculation or prenatal genetic tests) over those who advised against it (i.e. recommended maintaining the status quo) or gave no recommendation at all (Barnoy, Levy, & Bar-Tal, 2009; Barnoy, Ofra, & Bar-Tal, 2012; BarTal, Stasiuk, & Maksymiuk, 2013; Stasiuk, Bar-Tal, & Maksymiuk, 2016). Similar results were reported by Zaleskiewicz, Gasiorowska, Stasiuk, Maksymiuk, and Bar-Tal (2016), who studied how consumers perceive the EA of financial advisors and showed that individuals attributed greater authority to those consultants who advised action in the context of considering whether to take out a mortgage. However, the latter authors also preliminarily documented that assigning greater authority to experts recommending action might result from consumers desire to reach congruence between their own opinions and expert recommendations. Raviv et al. (1993) examined the perception of the EA of political leaders and showed that people tended to attribute higher EA to the politicians whose ideologies were closer to their own views. Interestingly, greater EA was assigned to leaders holding the same political orientation not only in the political knowledge domain, but also in the general knowledge domain. Taken together, these studies suggest the possibility that the same advice may lead to assigning different levels of EA depending on what a persons a priori opinion or belief is and how much the experts advice is congruent with this opinion.

Confirmation Effect in Knowledge Formation Research that has not been directly focused on analysing knowledge formation also seems to support the hypothesis that EA evaluation would be distorted by the need for confirmation. Both classical and more recent social psychology work on attitude polarisation revealed that people holding strong opinions on different issues process empirical evidence in a biased manner, revealing the prior belief effect (Edwards & Smith, 1996). They tend to accept information supporting their initial beliefs and critically evaluate disconfirming evidence (Lord, Ross, & Lepper, 1979; Lundgren & Prislin, 1998). Edwards and Smith (1996) proposed the disconfirmation C 2018 International Association of Applied Psychology. V


5

model and provided empirical evidence showing that arguments inconsistent with prior beliefs related to such issues as, for example, the death penalty or abortion, are scrutinised longer, subjected to more extensive refutational analyses, and perceived to be weaker than arguments congruent with prior beliefs. Similarly, Ditto and Lopez (1992) showed that people are motivated sceptics, that is, they process and examine information inconsistent with their beliefs more critically and more carefully than beliefs-consistent information (see also Ditto, Scepansky, Munro, Apanovitch & Lockhart, 1998). In other words, people experience greater uncertainty regarding the validity of the preference-inconsistent information. Research in group behaviour also suggests that interpersonal cognitive consistency plays an important role in how people perceive and evaluate one another. Mojzisch, Kerschreiter, Faulm€ uller, Vogelgesang and Schulz-Hardt (2014) have studied collective decision processes and found that participants evaluated their partners in dyads as more competent when these partners communicated information that was consistent with participants preferences. Preference-consistent information itself was also perceived as more important and accurate than preference-inconsistent information. In the same vein, Minson, Liberman and Ross (2011) and Liberman, Minson, Bryan, and Ross (2011) have documented that people engaged in a dyadic collaboration failed to give due weight to their partners estimates when these estimates diverged from their own beliefs. Research in social psychology described above has consistently shown that people are strongly motivated to defend their attitudes and beliefs even at the price of lowered accuracy of judgments or evaluations they produce (Minson et al., 2011). Yaniv (2004a) proposed an analogy between attitude change and advice use and argued that similar psychological factors might be responsible for these two processes. Knowing that people are strongly determined to defend their opinions by ignoring disconfirming evidence, one might assume that a similar tendency would have an effect on information search in the advice-taking context. Indeed, when participants provided their judgments on the basis of their own opinions and advice presented to them, they revealed egocentric discounting of anothers opinion; that is, they placed a higher weight on their own opinion than on the advisors suggestion (Yaniv, 2004a; Yaniv & Kleinberger, 2000; Yaniv & Milyavsky, 2007). Yaniv, Choshen-Hillel, and Milyavsky (2009) argue that advisees might overweight advice that is consistent with their preferences because congruence with advisors is rewarding and it reduces cognitive effort. These authors also reported that when people receive advice close to their own opinions they are less willing to change their initial estimates and indicate greater confidence in their final estimates. Schultze, Rakotoarisoa, and Schulz-Hardt (2015) confirmed the above effects in their research and showed that decision-makers weighted advice to a lesser degree when it C 2018 International Association of Applied Psychology. V

6

LAY EVALUATION OF FINANCIAL EXPERTS

691

deviated from their own initial opinions.2 Moreover, Ecken and Pibernik (2015) have recently shown that peoples tendency to ignore advice as a result of their reluctance to update prior beliefs might be observed not only in lay evaluations, but also in long-term professional judgments.

Social Norms, the Construction of Preferences, and Confirmation Effect One question that arises in the context of the results reviewed above is what happens when peoples own opinions are not salient or people are uncertain about their preferences? We argue that in this case decision-makers might be motivated to confirm more general social norms that are related to a particular behaviour (financial behaviour in the present project). Social norms and the knowledge of what are the typical behaviours of others might be used as a basis for forming ones own preferences, opinions and actions (Aarts & Dijksterhuis, 2003; Cialdini, Reno, & Kallgren, 1990; Nolan, Schultz, Cialdini, Goldstein, & Griskevicius, 2008; Schultz, Nolan, Cialdini, Goldstein, Griskevicius, 2007). For example, Cialdini et al. (1990) examined peoples readiness to litter depending on which social norm for littering was made salient. In one condition, the experimenters have heavily littered the floor with handbills or paper cups (a cue that littering is socially accepted), and in another condition, they have cleaned the area of all litter (a cue that littering is not socially accepted). The authors found that the participants in the experiment littered more in a littered environment than in a clean environment, which suggests that they tended to construct their preferences and to act in accordance with salient social norms. Similar findings were reported later by Schultz et al. (2007), who found that households preferences on energy consumptions depended on the descriptive normative message on average neighbourhood energy usage. These researchers concluded that their results revealed a strong constructive potential of social norms. In general, social psychology research has shown that people show a strong need to conform to the norms that are important for the group they are part of (Aronson, Wilson, & Akert, 2007; Cialdini & Goldstein, 2004). We assume that if people are not sure what their own beliefs are in a particular domain, but they are aware of what behaviour is most typical for and valued by other people from their social group, they would form their preferences in line with the salient norms, because they would try to conform to the common rules. In the context of the present research we might say that lay decision makers who are uncertain about their own opinions would value advice congruent with a social norm more than advice that contradicts such a norm. 2 It should be noted, however, that Schultze et al. (2015) found that people might also underweight advice when its distance from their initial estimates is low. C 2018 International Association of Applied Psychology. V


7

Overview of the Present Project The results presented above suggest that the need for congruence (confirmation) plays an important role in an interactive judgment process, when people exchange information with other group members or search for advice from experts. Therefore, it seems reasonable to hypothesise that the desire to confirm ones own beliefs or more general social norms would also affect the process of evaluating advisors EA. However, prior research on the confirmation effect was typically not directly related to practical, everyday decisions (e.g. consumer financial decisions). For example, tasks that were used by researchers to study egocentric discounting in advice taking instructed the participants to assess such values as length/weight of something or the year an event occurred (e.g. Yaniv, 2004a). Therefore, in the present project we intended to investigate advisees evaluations using scenarios that would simulate real life financial choices to show how scientific knowledge on the confirmation effect might be used in an applied context and to better understand how consumer decisions based on financial advice might be distorted. The first part of the present project documents how peoples evaluations of the authority of financial experts might be affected by the (in)congruence between expert advice and their own beliefs. This is the most common way the confirmation effect is examined: researchers assume that people tend to confirm their preferences. In real life situations, it sometimes happens that lay people do not have clear preferences on what to choose, because of the lack of experience or necessary knowledge. In such a case, they construct their preferences ad hoc by referring to other peoples observable actions. In our project, we investigate both possibilities listed above by testing how lay evaluations of expert authority might be influenced by the (in)congruence of advice with either consumers own beliefs (Experiment 1) or beliefs constructed ad hoc on the basis of social norms, that is, the common behaviour of others (Experiment 2). Our prediction is that lay people will ascribe greater authority to experts whose advice supports their own opinions irrespective of whether they are based on peoples own preferences or on social norms. However, we also assume that when people have access to both their own opinions and social norms, they will confirm the former rather than the latter in their evaluations of expert advice. We examine this assumption in Experiment 3. In the following three experiments, we investigated the confirmation effect in the domain of financial advising. We chose this particular domain to test our hypotheses because consumers who search for advice from financial consultants usually do not have access to clear cues informing them about the experts competence. In other words, it is not obvious which factors inform them about the level of knowledge possessed by a financial advisor. On the contrary, when patients have to judge the authority of physicians, they might base their evaluations on such evidence as a professional title, an academic C 2018 International Association of Applied Psychology. V

8


degree or a place in the organisational hierarchy (e.g. hospital coordinator). Therefore, the evaluation of epistemic authority in the financial domain seems to depend to a higher degree on vague information and, as a consequence, be more susceptible to distortions. In all three experiments, we manipulated advisors recommendations, so that they might have become consistent or conflicting with participants preferences. Moreover, we manipulated the participants preferences regarding financial behaviour. In Experiment 1, we manipulated participants opinions on financial products (insuring and investing) and assumed that participants preferences while reading the scenarios would adhere to these opinions. In Experiment 2, we manipulated general social norms and assumed that when lay peoples opinions have not been made salient, they would construe their preferences on the basis of a salient norm, and their evaluations of expert authority would depend on whether the experts advice confirms this norm. Finally, in Experiment 3, both sources of opinions (general social norm and participants opinions) were manipulated. We assumed that peoples own opinions would be a stronger basis for preferences formation than the behaviour of other people. In addition to manipulating opinions on financial products, we also measured participants real preferences related to purchasing these products. Therefore, the analyses in all three experiments used both manipulated opinions and measured participants opinions as independent variables. In all three experiments, we also tested whether the impact of (in)congruence of participants opinions and expert advice on the EA evaluation would be moderated by participants own knowledge of finance. According to Kruglanski et al. (2005), ones own subjective knowledge in a particular domain is reflected by the level of self-epistemic authority (SEA)—the degree to which individuals perceive themselves as authorities in this domain. It might be hypothesised that for lay people with high SEA, receiving agreement (confirmation) from an expert would be self-validating. Therefore, they will ascribe greater EA to the expert whose advice is congruent with their own opinions. However, when people low in SEA receive a confirmatory message from an advisor, they might experience some ambivalence; therefore, their EA evaluations will not strongly depend on the degree to which advice is congruent with their opinions (Kruglanski et al., 2005).

EXPERIMENT 1: PEOPLE’S SEARCH FOR CONFIRMATION OF THEIR OWN OPINIONS The main goal of Experiment 1 was to test the general hypothesis that lay people ascribe greater EA to the financial consultant whose recommendation is congruent with their opinions. To empirically test this hypothesis, we conducted an experiment in which we manipulated both participants opinions C 2018 International Association of Applied Psychology. V


9

and advisors recommendations concerning two different financial products (insuring oneself and investing in the stock market). Such a combination of the two manipulation procedures allowed us to investigate effects of both congruence and incongruence of opinions and recommendations on the EA evaluation. The existence of the confirmation effect was also investigated by measuring participants own opinions on the two financial activities. The expectation was that advising in a way that is consistent with participants measured opinions would lead to ascribing greater EA to the financial advisor. We used two different financial products and two different operationalisations of participants opinions (measurement and manipulation) to test the robustness of the potential confirmation effect in the evaluation of expert EA. More formally, we hypothesised that the evaluations of experts epistemic authority would be predicted by the interaction of the participants own opinions (both measured and manipulated) with the type of advice (H1). We expected that: H1a: In the case of a positive participants opinion, advice in favour of the product would lead to a higher evaluation of the advisors authority than the advice against the product. H1b: In the case of a negative participants opinion, advice against the product would lead to a higher evaluation of advisor authority than the advice in favour of the product.

Moreover, we expected that the above-mentioned interaction resembling the confirmation effect would be moderated by participants self-epistemic authority in finances (SEA). More formally, we hypothesised that: H1c: The two-way interaction between expert advice and participants opinions would be the strongest for participants scoring high on SEA in finances, and the weakest or absent for those scoring low on this variable.

Method Participants. In the first step, the minimal sample size for Experiment 1 and for the two other experiments was calculated. Zaleskiewicz et al. (2016), who previously investigated determinants of EA evaluation in finance, reported a medium sized (partial g2 5 .116, p < .001) interaction effect of participants opinions and experts recommendations on the evaluation of financial experts EA. Therefore, in order to determine the sample size in the present project, we conducted a priori power analyses using G*Power (Faul, Erdfelder, Lang, & Buchner, 2007). Results suggested that, given an alpha of .05 and conventionally assumed power of .80, a sample of 62 total participants would be C 2018 International Association of Applied Psychology. V

10


required to detect an interaction effect size of .116. For that reason, we aimed at recruiting at least 60 participants per condition in each of the three experiments presented in this paper. We conducted an online experiment with a representative sample of Polish adults aged 21 or older. The initial sample consisted of N 5 523 participants (49.5% women; Mage 5 42.88 years, SD 5 14.04). As we intended to investigate lay evaluations of the experts EA in the financial domain, we excluded from analyses those participants who were potentially proficient in finance, that is, those who declared that their profession is related to finance management (financial or insurance advisor, customer service in financial institutions etc.). The final sample consisted of N 5 440 participants (48.9% women, Mage 5 43.02 years, SD 5 14.34). Procedure. The participants were randomly assigned to one of the eight conditions in a 2 (product: investment vs life insurance; within-subject factor) 3 2 (participants opinion: positive vs negative; between-subject factor) 3 2 (advice: pro vs against the product; between-subject factor) mixed design experiment. Participants were recruited by a professional research company. Participation in the experiment was voluntary and participants received compensation in line with the company rules. Participants were informed that participation in the experiment was anonymous and they could drop out at any time. All materials and correspondence with participants were in the Polish language. After giving informed consent, participants were asked to provide information on gender, age, education, and profession. Although we examined only laypeople, they still might have differed in their perception of their own knowledge in finance, irrespective of their actual expertise. For that reason, they were asked to assess their own epistemic authority (SEA) in finances. The assessment was made using two items from the Epistemic Authority scale by Barnoy, Levy, and Bar-Tal (2009), modified to measure SEA (“I have a great deal of knowledge in finances”, “It is possible to rely on my financial knowledge wholeheartedly”; Cronbachs a 5 .896).3 Each question was answered on a sixpoint scale from 1 5 “definitely disagree” to 6 5 “definitely agree”. The two questions were averaged, forming the index of SEA (M 5 3.16, SD 5 1.11, observed range 1–6). After that, participants were asked to answer two questions to provide their own opinions on the degree to which investing and purchasing life insurance are necessary. The questions were: (1) “What is your opinion on investing on 3

We have chosen these two items on the basis of the highest item-total correlation found in the pilot study conducted with the complete 9-item version of the SEA in finances scale on the group of N 5 355 participants (65.4% women; Mage 5 31.39 years, SD 5 7.738). C 2018 International Association of Applied Psychology. V


11

the stock market by a Polish citizen with average income?” and (2) the same question with life insurance substituted for investing. Each question was answered on a five-point scale from 1 5 “it is definitely unnecessary” to 5 5 “it is definitely necessary”. Descriptive statistics were, respectively, M 5 2.38, SD 5 0.934 for the opinion on investing and M 5 3.74, SD 5 0.938 for the opinion on insuring oneself, and the observed range for both questions was 1– 5. We did not directly ask about participants preferences concerning investing and life insurance, but instead used an indirect question to prevent potential interference with the manipulation of participants opinions in the scenarios. After answering these questions, participants read two scenarios, presented in a random order. In the life insurance scenario, participants were asked to imagine that they attended a routine annual meeting with the insurance agent, and that during this meeting the talk turned to the discussion of life insurance. Next, the consultants advice accompanied by a very short justification was provided. In the “advice against” condition, the advisor recommended against buying the life insurance, as it was quite expensive. In the “advice pro” condition, the advisor recommended buying the insurance, as it was inexpensive. The recommendation of the advisor was followed by a brief description of the clients opinion. In the “positive opinion” condition, participants were informed that they were also interested in this kind of insurance because they believed it was very profitable. In the “negative opinion” condition, participants read that they were not convinced about the idea of purchasing life insurance because they believed that it was full of losses. In the investment scenario, participants were asked to imagine that they went to the bank just to change their telephone contact number, and while the advisor was changing the information in the bank system, the talk turned to discussion of investing. In the “advice against” condition, the advisor recommended against opening an investment account, as it was quite expensive and not really profitable. In the “advice pro” condition, the advisor recommended opening the account, as it was inexpensive and very profitable. The recommendation provided by the advisor was again followed by a brief description of the clients opinion. In the “positive opinion” condition participants were informed that they were interested in individual investing in the stock market because they believed it was very profitable. In the “negative opinion” condition participants realised that they were not convinced about the idea of individual investing, because they believed that it was full of losses. After reading each scenario, participants were asked to answer six questions that together assessed the EA attributed to the advisor presented in the scenario, adjusted for the content of the scenario (e.g. “To what extent do you think the financial (insurance) advisor is an expert in investing (life insurance)?”). Each question was answered on a six-point scale from 1 5 “definitely not” to 6 5 “definitely yes”. The scale (Cronbachs a 5 .894 for the investment advisor and .896 for the insurance advisor) was adapted from Barnoy, Ofra, C 2018 International Association of Applied Psychology. V

12


and Bar-Tal (2012). The average score on the EA scale for each scenario served as the dependent variable.

Results Confirmation Effect. To test research hypothesis H1, a 2 (product: investment vs life insurance; within-subject factor) 3 2 (participants manipulated opinion: positive vs negative; between-subject factor) 3 2 (advice: pro vs against the product; between-subject factor) repeated measures ANOVA was conducted. In line with our hypothesis, a significant two-way interaction between advice and participants manipulated opinion was found, F(1, 436) 5 24.99, p < .001, g2 5 .054, indicating a possible confirmation effect. The three-way interaction between advice, participants manipulated opinion and product was not significant, F(1, 436) 5 0.743, p 5 .39, g2 5 .002, indicating that the two-way interaction mentioned above did not depend on the type of financial product. We also observed a significant but weak interaction between the type of financial product and advice, F(1, 436) 5 9.66, p 5 .002, g2 5 .022. No other effects were significant: product: F(1, 436) 5 1.61, p 5 .21, g2 5 .004; advice: F(1, 436) 5 0.12, p 5 .73, g2 < .001; participants manipulated opinion: F(1, 436) 5 0.40, p 5 .53, g2 5 .001; product by participants manipulated opinion: F(1, 436) 5 0.74, p 5 .39, g2 5 .002. Further analyses confirmed the two-way interaction between advice and participants manipulated opinion for both investment account, F(1, 436) 5 16.479, p < .001, g2 5 .036, and life insurance, F(1, 436) 5 23.07, p < .001, g2 5 .050. Planned comparisons for the life insurance scenario revealed that, in line with hypothesis H1a, when the participants were asked to imagine that they held a positive opinion towards the insurance, they assigned higher EA to the advisor who recommended buying the product (M 5 3.64, SD 5 0.84) than to the one who recommended against it (M 5 3.05, SD 5 1.02), F(1, 436) 5 20.68, p < .001, g2 5 .045. However, when the participants were asked to imagine that they held a negative opinion towards the insurance, the effect reversed: They assigned lower EA to the advisor who recommended buying the product (M 5 3.19, SD 5 0.92) than to the one who recommended against it (M 5 3.48, SD 5 1.04), F(1, 436) 5 4.97, p 5 .026, g2 5 .01, supporting hypothesis H1b. A similar pattern of results was found when analysing the investment account scenario. Planned comparisons revealed that when the participants were asked to imagine that they held a positive opinion towards investing in the stock market, they assigned higher EA to the advisor who recommended opening the investment account (M 5 3.46, SD 5 0.89) than to the one who recommended against it (M 5 3.19, SD 5 1.10), F(1, 436) 5 4.38, p 5 .037, g2 5 .01, which again supports hypothesis H1a. When the participants were asked to imagine that they held a negative opinion towards investing, the effect C 2018 International Association of Applied Psychology. V


13

was the opposite and in line with hypothesis H1b: they assigned lower EA to the advisor who recommended opening the account (M 5 3.01, SD 5 0.80) than to the one who recommended against it (M 5 3.47, SD 5 0.98), F(1, 436) 5 13.38, p < .001, g2 5 .03. Confirmation Effect Revisited. Next, we tested hypothesis H1 using the opinion on life insurance and investing in the stock market held by participants and measured before they read the scenarios. If this measured opinion interacted with advice provided by an expert in predicting the advisors EA, it would be an additional test of the existence of the confirmation effect. We conducted two multiple regression analyses, with the level of EA ascribed to an insurance advisor or an investment advisor as dependent variables, respectively. The regressions included three predictors: the experimental manipulation of the advice (pro vs against the product), participants measured opinions on investing/insuring, and the interaction of these two variables.4 All variables were z-scored prior to the analysis to allow for standardised regression coefficients in the output. Analysing the predictors of the EA ascribed to the insurance advisor, we found that the regression model with experimental manipulation of advice, participants measured opinions on insuring and their interaction as predictors was significant, F(3, 436) 5 4.910, p 5 .002, R2 5 .033. We found that no significant effect was exerted by either experimental manipulation of advice (b 5 .075, SE 5 .047, t 5 1.58, p 5 .11, 95% CI [2.018, .167]), or the participants measured opinions on insuring (b 5 .009, SE 5 .047, t 5 0.19, p 5 .85, 95% CI [2.084, .102]). However, as expected, the interaction between advice and the participants measured opinions was significant (b 5 .165, SE 5 .047, t 5 3.495, p < .001, 95% CI [.070, .258]). In other words, the impact of the advice provided by an expert on his or her perceived EA depended on the opinion toward insurance held by the participant. To investigate the nature of the moderation effect, two types of conditional effect (simple slopes) analyses were performed. First, the relationship between IV (advice) and DV (assessment of advisor EA) was investigated at three levels 4

We also conducted regression analyses with experimental manipulation of the advice (pro vs against the product), both participants measured and manipulated opinions on investing/ insuring, and all interactions between these variables as predictors. These analyses confirmed the significance of two-way interactions between opinions (measured or manipulated) and recommendations for both insurance and investment accounts (ps < .001). The two-way interactions between participants manipulated and measured opinions did not reach the significance level for either product (ps > .18). The three-way interactions between recommendations, manipulated opinions, and measured opinions were also not significant (ps > .36). The insignificance of these three-way interactions and the lack of two-way interactions between manipulated opinions and measured opinions demonstrate that the two operationalisations of opinions did not interfere with each other. C 2018 International Association of Applied Psychology. V

14


FIGURE 1. The level of EA ascribed to the advisor as a function of participants’ measured opinions on insuring and experimental manipulation of advice. Tags represent groups of participants scoring low, moderate, and high on the opinion of life insurance and are based on mean value and 1/2 1 SD from the mean.

of the moderator (opinion held by participants): mean, 1 SD above, and 1 SD below mean (see Figure 1). The association at the lowest level of the moderator (M – 1SD 5 2.80), the most negative opinion on insuring held by participants, was not significant (b 5 2.090, SE 5 0.067, t 5 21.36, p 5 .17, 95% CI [2.222, .041]). For the moderate level of the moderator (M 5 3.74), the association between experimental manipulation of advice and the EA assigned to the advisor was also not significant (b 5 .075, SE 5 .047, t 5 1.58, p 5 .11, 95% CI [2.018, .167]). For the highest level of the moderator (M 1 1SD 5 4.68), the effect of advice on perceived advisors EA was significant and positive (b 5 .240, SE 5 .067, t 5 3.595, p < .001, 95% CI [.109, .371]), indicating that when participants held a positive opinion towards insuring, they perceived the advisor who recommended buying the insurance as more competent than the advisor who recommended not buying it. This result supported in a different way hypothesis H1a. However, the pick-a-point approach is considered controversial due to the arbitrariness of choosing points (M 1/2 1SD) for a traditional simple slopes analysis (Hayes, 2013). Thus, in a second conditional effect analysis, we used the Johnson–Neyman technique for probing significant interactions (Hayes, 2013; Preacher, Rucker, & Hayes, 2007). In this technique, “regions of significance” are mathematically derived over the full spectrum of the moderator values for which the relationship between predictor and DV is significant. If the confidence interval for the point estimate of the conditional effect does not contain zero, predictor and dependent variables are regarded as significantly related. The relationship between advice and assessment of advisors EA was negative and significant when the raw scores of the participants measured opinions C 2018 International Association of Applied Psychology. V


15

on insuring were below 2.39 (standardised score below 21.434), and positive and significant when they were above 3.84 (standardised score above 0.111). Such results support our hypothesis by demonstrating that individuals holding a particular opinion on insuring perceived the advisor who was confirming their opinion with proposed advice as a better expert than the advisor whose recommendation was contradictory to their opinion, revealing the confirmation effect. We observed the same pattern of results when analysing predictors of the EA ascribed to the investment advisor. The regression model with experimental manipulation of advice, participants measured opinions of investing in the stock market and their interaction as predictors was significant, F(3, 436) 5 7.155, p < .001, R2 5 .047. We found no significant effect of experimental manipulation (b 52057, SE 5 .047, t 5 21.22, p 5 .223, 95% CI [2.149, .035]), and marginally significant effect of the participants measured opinion on investing (b 5 2.083, SE 5 .047, t 5 21.77, p 5 .08, 95% CI [2.175, .009]). Again, as expected, the interaction between the advice and the participants own opinion was significant (b 5 .190, SE 5 .047, t 5 4.061, p < .001, 95% CI [.098, .282]), indicating that the impact of the advice provided by an expert on his or her perceived EA depended on the opinion toward investing held by participants. To investigate the nature of the interaction effect, we again performed two types of conditional effect (simple slopes) analyses. First, the relationship between IV (advice) and DV (assessment of advisors EA) was investigated at three levels of the moderator: mean, 1 SD above and 1 SD below mean (see Figure 2). The association at the lowest level of the moderator (M – 1SD 5 1.45), the most negative opinion on investing held by participants, was significant and negative (b 5 2.247, SE 5 .066, t 5 23.74, p < .001, 95% CI [2.377, 2.117]), indicating that, in line with hypothesis H1b, in this case the advisor who recommended opening the investment account was perceived as less competent than the advisor who recommended not doing so. For the moderate level of the moderator (M 5 2.80), the association between experimental manipulation of advice and the EA assigned to advisor was not significant (b 5 2.057, SE 5 .047, t 5 21.219, p 5 .223, 95% CI [2.149, .035]). For the highest level of the moderator (M 1 1SD 5 3.31), the effect of advice on advisors EA was significant and positive (b 5 .133, SE 5 .066, t 5 2.011, p 5 .045, 95% CI [.003, .263]), indicating that when participants held a positive opinion towards investing, they perceived the advisor who recommended opening the investment account as more competent than the advisor who recommended avoiding such activity, supporting hypothesis H1a. The analysis of Johnson–Neyman regions of significance revealed that the relationship between advice and assessment of advisors EA was negative and significant when the raw score of the participants own opinion on investing was below 2.20 (z-score below 20.19), and positive and significant when the C 2018 International Association of Applied Psychology. V

16


701

FIGURE 2. The level of EA ascribed to the advisor as a function of participants’ measured opinions on investing in the stock market and experimental manipulation of advice. Tags represent groups of participants scoring low, moderate, and high on the opinion of investing in the stock market and are based on mean value and 1/2 1 SD from this mean value.

raw score of the participants own opinion on investing was above 3.29 (z-score above 0.98). Such results indicate, analogically to results concerning decisions on insurance, that individuals holding a particular opinion on investing perceived the advisor who was supporting their opinion as a better expert than the advisor whose recommendation was contradictory to their opinion, revealing the confirmation effect and supporting hypotheses H1a and H1b. SEA. In the final part of data analysis, we tested the hypothesis that the strength of the confirmation effect depends on the level of SEA in finances declared by participants (hypothesis H1c). We conducted four regression analyses with the experimental manipulations of the advice (pro vs against the product), opinion on insuring/investing (manipulated in the scenario as positive vs negative or measured with two questions before reading the scenarios), participants SEA in finances and all interactions between these variables as predictors. All variables were z-scored prior to the analysis to allow for standardised regression coefficients in the output. The results of the regression analyses confirmed the significant interactions between the recommendation and the manipulation of participants opinions via the different scenarios, for both the insurance scenario (b 5 .214, SE 5 .046, t 5 4.663, p < .001, 95% CI [.124, .304]) and the investment scenario (b 5 .182, SE 5 .047, t 5 3.895, p < .001, 95% CI [.090, .273]). Also, the interactions between the recommendation and participants opinions measured before the scenario were significant (respectively, b 5 .151, SE 5 .046, C 2018 International Association of Applied Psychology. V


17

t 5 3.252, p 5 .001, 95% CI [.060, .242], for the insurance scenario and b 5 .188, SE 5 .047, t 5 4.204, p < .001, 95% CI [.095, .280], for the investment scenario). None of the three-way interactions between advice, opinion and SEA were significant (ps > .170). This implies that the confirmation effect in ascribing EA to the financial advisor did not depend on the level of participants SEA in finances, which does not support hypothesis H1c.

Discussion Results of Experiment 1 fully confirmed our predictions stating that lay people who search for the confirmation of their opinions attribute greater authority to financial consultants whose advice is congruent with these opinions. The presence of the confirmation effect has been shown in two different ways. Firstly, we found that the EA evaluation depended on the congruency between opinions that were made salient by the experimental manipulation and the advisors recommendations. When advisors recommended action (inaction), they were perceived as better experts by those participants who were induced to hold positive (negative) opinions regarding purchasing two different financial products (i.e. insurance or investment account). Secondly, participants were more strongly motivated to assign greater EA to those consultants whose advice was congruent with their own opinions on whether having the insurance/investment account is profitable. In other words, the effect of the confirmation effect on lay evaluations of financial experts EA has been documented for two different products and for two different operationalisations of lay peoples opinions on the profitability of financial activities. Interestingly, no moderation effect of the participants subjective knowledge in finances reflected by their SEA level was observed. It might suggest that the impact of the confirmation effect on EA evaluations is universal and does not depend on how competent an individual feels in the financial domain. The results found in Experiment 1 refer to the situation in which decisionmakers hold their own opinions on the profitability of different courses of action. However, as we have pointed out in the introduction, this is not always the case. Sometimes people might be uncertain about their beliefs or opinions. As we proposed in the introduction, in such cases decision-makers might be motivated to confirm more general social norms that are related to a particular behaviour. Our assumption was that if people do not have access to their own beliefs in a particular domain, but they are aware of what behaviour is most typical for and valued by other people from their social group, they would form their preferences in line with the salient norms, because they would try to conform to the common rules. If so, we might expect that lay evaluations of financial experts EA would reflect peoples search for confirmation of salient social norms. This expectation was tested in Experiment 2. C 2018 International Association of Applied Psychology. V

18


EXPERIMENT 2: PEOPLE’S SEARCH FOR CONFIRMATION OF SALIENT SOCIAL NORMS Experiment 2 was carried out to test the hypothesis that when lay peoples own opinions were not made salient they would express the desire to confirm social norms in their evaluations of the authority of financial experts, because these social norms would form a basis for their preferences. In order to verify this hypothesis, we manipulated the valence of the social norm so that it might have become congruent or incongruent with expert advice that also was manipulated. Our expectation was that participants would ascribe greater EA to financial consultants whose advice was consistent with the social norm, irrespective of whether the advisor recommended action or inaction. However, one of the aims of this experiment was to demonstrate that it is not enough to generally recommend action or inaction congruent with the valence of the salient norm, but the norm must be related to a particular domain (the financial domain in our case). Therefore, we manipulated not only the valence of the norm (positive vs negative), but also the content of the norm (related to finances vs not related to finances). We expected to observe the confirmation effect only when the participants received information on the social norm related to finances, but not when they were informed about norms unrelated to this domain. More formally, we expected a significant three-way interaction between the advice, content of the norm, and valence of the norm in predicting the evaluations of expert authority. The decomposition of this three-way interaction should reveal a significant two-way interaction between the type of advice and the valence of the social norm, but only when the norm concerns financial behaviours (H2). In detail, similarly to Experiment 1, we predicted that: H2a: In the case of the positive social norm related to finances, the advice in favour of the product would lead to a higher evaluation of advisor authority than the advice against the product. H2b: In the case of the negative social norm related to finances, the advice against the product would lead to a higher evaluation of advisor authority than the advice in favour of the product.

As in the previous experiment, the possibility of a moderation effect of SEA was examined. We expected that the effect hypothesised in H2 would be moderated by participants self-epistemic authority in finances (SEA): H2c: The two-way interaction between expert advice and general social norms concerning financial behaviour will be the strongest for participants scoring high on SEA in finances, and the weakest or even absent for those scoring low on this variable. C 2018 International Association of Applied Psychology. V


19

Method Participants. We conducted an online experiment with a representative sample of Polish adults aged 21 and older (sample was different than in Experiment 1). The initial sample consisted of N 5 483 participants (50.5% women; Mage 5 44.23 years, SD 5 14.36). Analogically to Experiment 1, we excluded from analyses those participants who were potentially proficient in finance. The final sample consisted of N 5 407 participants (48.9% women, Mage 5 44.46 years, SD 5 14.44). Procedure. Participants were randomly assigned to one of the eight conditions in the 2 (norm content: related finances vs not related finances) 3 2 (valence of norm: positive vs negative) 3 2 (advice: pro vs against the product) between-subject experiment. Participants were recruited by a professional research company. Participation in the experiment was voluntary and participants received compensation in line with company rules. Participants were informed that participation in the experiment was anonymous and that they could drop out at any point. All materials and correspondence with participants were in the Polish language. After giving informed consent, participants were asked to provide information on gender, age, education, and profession. Then, they were asked to answer questions measuring their own EA regarding finances (SEA, Cronbachs a 5 .924, M 5 3.151, SD 5 1.158, observed range 1–6) and their opinion on investing (same as in Experiment 1, M 5 2.440, SD 5 0.854 for the opinion on investing, observed range 1–5). After answering these questions, participants were asked to read a short text. To manipulate the content of the norm, the text concerned either investing or going to a cinema. The valence of the norm was manipulated by informing the participants that recent studies have shown either an increase or a decrease in peoples interest in investing (norm related to finances) or going to a cinema (norm not related to finances) among Polish citizens. This latter manipulation was supported by providing reports prepared by journalists and commentators who observed an increase/decrease in peoples interest in investing/going to a cinema. Participants were also requested to jot down three potential reasons or explanations of such trends. After that, on the next web page participants were asked to imagine that they went to the bank just to change their telephone contact number, and while the advisor was changing the information in the bank system, the talk turned to a discussion on investing. Next, as in Experiment 1, the consultants advice accompanied by a very short justification was provided. In the “advice against” condition the advisor recommended not opening the investment account, as it was quite expensive and not really profitable. In the “advice pro” condition the advisor recommended opening the account as it was inexpensive and very C 2018 International Association of Applied Psychology. V

20


profitable. After reading the scenario, participants were asked to answer six questions that together assessed the EA attributed to the advisor presented in the scenario, identical to Experiment 1 (Cronbachs a 5 .920). The average score on the EA scale served as the dependent variable.

Results Confirmation effect. To test hypothesis H2, a 2 (norm content: related to finances vs not related to finances) 3 2 (valence of norm: positive vs negative) 3 2 (advice: pro vs against the product) between-subjects ANOVA was conducted. We found a significant three-way interaction between norm content, its valence and advice, F(1, 399) 5 4.449, p 5 .038, g2 5 .011, and a marginally significant two-way interaction between norm valence and advice, F(1, 399) 5 3.047, p 5 .082, g2 5 .008. No other effects were significant: norm valence by norm content: F(1, 399) 5 1.952, p 5 .169, g2 5 .005; norm content by advice: F(1, 399) 5 0.420, p 5 .517, g2 5 .001; advice: F(1, 399) 5 0.214, p 5 .644, g2 5 .001; norm content: F(1, 399) 5 0.027, p 5 .871, g2 < .001; norm valence: F(1, 399) 5 2.013, p 5 .157, g2 5 .005. Further examination of the three-way interaction revealed that, in line with our expectation, the interaction between norm valence and advice was significant only when participants read the text about investing in the stock market, F(1, 216) 5 8.354, p 5 .004, g2 5 .037, and not when they viewed the text unrelated to finances, F(1, 183) 5 0.050, p 5 .824, g2 < .001, indicating the existence of the confirmation effect. The decomposition of this significant interaction using planned contrasts showed that when participants were induced to think that investing in the stock market has become more popular in Poland (positive norm towards investing), they evaluated an advisor recommending opening the investment account as having greater EA (M 5 3.274, SD 5 0.975) than the advisor recommending against investing (M 5 2.906, SD 5 1.062), F(1, 216) 5 3.929, p 5 .049, g2 5 .018, supporting hypothesis H2a. On the contrary, and in line with hypothesis H2b, when participants were induced to think that investing was becoming less popular (negative norm towards investing), they ascribed greater EA to the advisor recommending against the investment account (M 5 3.289, SD 5 0.981) than the advisor recommending opening such an account (M 5 2.883, SD 5 0.935), F(1, 216) 5 4.425, p 5 .037, g2 5 .020 (see Figure 3). Confirmation Effect Revisited. Our analysis also investigated whether the opinion on investing in the stock market held by participants and measured before they read the scenarios interacted with the advice provided by an expert. If so, it would be an additional test of the existence of a confirmation effect in the EA evaluations. We conducted a multiple regression analysis with the level of EA ascribed to the investment advisor as a dependent variable and three C 2018 International Association of Applied Psychology. V


21

FIGURE 3. The level of EA ascribed to the advisor as a function of experimental manipulations of advice and the norm concerning investing in the stock market.

predictors: the experimental manipulation of the advice (pro vs against the product), the participants opinions on investing measured at the beginning of the experiment, and the interaction of these two variables. All variables were zscored prior to the analysis to allow for standardised regression coefficients in the output. Analysing the predictors of the EA ascribed to the investment advisor, we found that the regression model with experimental manipulation of advice, participants opinion on investing and their interaction as predictors was significant, F(3, 403) 5 7.955, p < .001, R2 5 .056. However, we found that no significant effect was exerted by either experimental manipulation (b 5 .019, SE 5 .048, t 5 0.403, p 5 .687, 95% CI [2.076, .115]), or the interaction between the advice and the participants opinion (b 5 .016, SE 5 .049, t 5 0.327, p 5 .743, 95% CI [2.080, .111]). The only significant effect was observed in the case of participants measured opinions on investing (b 5 .234, SE 5 .049, t 5 4.810, p < .001, 95% CI [.138, .329]), indicating that the more participants believed that investing in the stock market is good or profitable for an average Polish citizen, the higher level of EA they ascribed to the advisor. In sum, we have not demonstrated in Experiment 2 that participants wanted to confirm their own opinions on investing while evaluating the EA of an advisor. SEA. In the final part of the analysis we tested hypothesis H2c that the confirmation effect depends on the level of SEA in finances declared by participants. We conducted a regression analysis with the experimental manipulations of the advice (pro vs against the product), norm valence (positive vs negative), C 2018 International Association of Applied Psychology. V

22


participants SEA in finances and all interactions between these variables as predictors. Only the data from participants who read the finance-related text were used in the analysis. All variables were z-scored prior to the analysis, to allow for standardised regression coefficients in the output. The results of the analysis confirmed the significance of the two-way interaction between the recommendation and norm valence (b 5 .172, SE 5 .063, t 5 2.714, p < .001). However, as in Experiment 1, the subjective knowledge of finances declared by participants did not affect their proneness to confirmation effect, as the threeway interaction between recommendation, the valence of the norm related to finances, and SEA was not significant (b 5 .075, SE 5 .066, t 5 1.139, p 5 .258).

Discussion The most important result of Experiment 2 was that lay people who make their evaluations of the financial advisors EA express the desire for confirmation even if their own opinions have not been made salient, which supported hypothesis H2. This experiment documented that greater EA was attributed to those financial consultants whose recommendation was consistent with the behaviour that is common and valued by people who are part of the same society as our participants. More precisely, when financial consultants advice was congruent with the salient social norm, they were perceived as better experts than when their recommendation was inconsistent with this norm. This result again showed the existence of the confirmation effect in lay evaluations of the authority of financial consultants and indicated another source of this effect in the perception of the experts advice quality. Similarly to Experiment 1, no moderation effect of the SEA variable was found (disconfirming hypothesis H2c). This result further indicated the universality of the desire to confirm ones own beliefs (represented by a common rule of behaviour in this case) in EA evaluations. Contrary to the results of Experiment 1, no interaction between participants own opinions (i.e. measured opinions) and manipulated advice was found. This is not surprising if we take into account the significant effect of the social norm by advice manipulation. It seems that when information on common social behaviour is salient, ones own beliefs become less available and people are more strongly motivated to confirm social norms. However, we might hypothesise that when information on both ones own opinions and social norms is salient, people would engage in confirming the former. To investigate this interpretation in a more detailed way, we conducted Experiment 3, in which participants opinions and social norms were manipulated at the same time. C 2018 International Association of Applied Psychology. V


23

EXPERIMENT 3: PEOPLE’S OPINIONS VS SALIENT SOCIAL NORMS Experiment 1 showed that when lay peoples own opinions are salient, people use them in their evaluations of the quality of financial advice. Results of Experiment 2 documented that when these opinions have not been made salient, naive decision-makers tend to ascribe greater EA to those experts whose advice is congruent with a dominant social norm. These two experiments revealed two different sources of the confirmation effect in the perception of the authority of financial experts. The present experiment was conducted to investigate how lay people make their EA evaluations when they can recognise both their own opinions and social norms (common rules of behaviour). We speculated that in this specific case ones own beliefs would prevail over social norms and people would tend to confirm their opinions and ignore what is known about the dominant behaviour of other consumers. To test this assumption, we conducted Experiment 3, in which we manipulated both participants opinions and the valence of social norms concerning investing in the stock market. Formally, we hypothesised that the evaluations of experts epistemic authority would be predicted by the interaction of participants opinions with the type of advice, but not by the interaction of general social norms with the type of advice (H3). We presumed that the decomposition of the expected significant interaction will be as follows: H3a: In the case of a positive participants opinion, the advice in favour of the product would lead to a higher evaluation of advisor authority than the advice against the product. H3b: In the case of a negative participants opinion, the advice against the product would lead to a higher evaluation of advisor authority than the advice in favour of the product.

As in previous experiments, we again expected that the above-mentioned effect hypothesised in H3 would be moderated by participants self-epistemic authority in finances (SEA): H3c: The two-way interaction between expert advice and participants opinions will be the strongest for participants scoring high on SEA in finances, and the weakest or absent for those scoring low on this variable.

Method Participants. We conducted a between-subjects online experiment with a representative sample of Polish adults aged 21 and older (different than in C 2018 International Association of Applied Psychology. V

24


Experiments 1 and 2). The initial sample consisted of N 5 471 participants (51.4% women; Mage 5 43.97 years, SD 5 14.15). As in Experiments 1 and 2, we excluded from analyses those participants who potentially were proficient in finances. The final sample consisted of N 5 389 participants (50.4% women, Mage 5 44.44 years, SD 5 14.31). Procedure. Participants were recruited by a professional research company. Participation in the experiment was voluntary and participants received compensation in line with company rules. Participants were informed that participation in the experiment was anonymous and that they could drop out at any point. All materials and correspondence with participants were in the Polish language. Participants were randomly assigned to one of the eight conditions in a 2 (financial norm valence: positive vs negative) 3 2 (advice: pro vs against the product) 3 2 (participants opinion: positive vs negative) between-subject experiment. After giving informed consent, participants were asked to provide information on gender, age, education, and profession. Then, all were asked to answer questions measuring SEA regarding finances and their opinion on investing (same as in Experiments 1 and 2; for SEA: Cronbachs a 5 .937, M 5 3.146, SD 5 1.149, observed range 1–6; for opinion on investing: M 5 2.38, SD 5 0.799, observed range 1–5). After participants answered these questions, they were asked to read a fragment of a report describing either increasing or decreasing interest in investing in the stock market, depending on the condition (same texts as in Experiment 2), and to jot down three potential reasons or explanations of such a trend. Then, participants were asked to read one of the four versions of the investment scenario (same as in Experiment 1), in which we manipulated the recommendation provided by the advisor (against vs pro opening the investment account) and the participants opinions on this product (positive vs negative). After reading the scenario, participants were asked to answer six questions assessing the EA attributed to the advisor presented in the scenario, identical to Experiments 1 and 2 (Cronbachs a 5 .871). The average score on the EA scale served as the dependent variable.

Results Confirmation Effect. To test hypothesis H3, we conducted a 2 (financial norm valence: positive vs negative) 3 2 (advice: pro vs against the product) 3 2 (participants manipulated opinions: positive vs negative) between-subjects ANOVA. The three-way interaction between norm valence, advice and participants opinions was not significant, F(1, 381) 5 1.488, p 5 .223, g2 5 .004. In line with our expectations, we observed a significant interaction between the advisors recommendation and participants opinions, F(1, 381) 5 12.833, C 2018 International Association of Applied Psychology. V


25

p < .001, g2 5 .039. No other effects reached the conventional level of significance: norm valence by advice: F(1, 381) 5 2.058, p 5 .116, g2 5 .006; norm valence by opinion: F(1, 381) 5 2.902, p 5 .089, g2 5 .008; norm valence: F(1, 381) 5 0.070, p 5 .791, g2 < .001; advice: F(1, 381) 5 0.585, p 5 .445, g2 5 .002; participants opinion: F(1, 381) 5 0.226, p 5 .635, g2 5 .001. Further examination of the two-way interaction between the participants manipulated opinions and recommendation again indicated the existence of the confirmation effect. Planned comparisons revealed that, in line with hypothesis H3a, when the participants were asked to imagine that they held a positive opinion towards investing in the stock market, they assigned higher EA to the advisor who recommended opening the investment account (M 5 3.316, SD 5 0.922) than to the one who recommended against it (M 5 3.021, SD 5 0.884), F(1, 385) 5 5.444, p 5 .020, g2 5 .014. However, when the participants were asked to imagine that they held a negative opinion towards investing, we found the opposite effect hypothesised in H3b: They tended to assign lower EA to the advisor who recommended opening the account (M 5 2.912, SD 5 0.799) than to the one who recommended not doing so (M 5 3.328, SD 5 1.036), F(1, 385) 5 7.781, p 5 .002, g2 5 .024. Confirmation Effect Revisited. We further examined whether the advice provided by an expert interacted with the opinion on investing in the stock market held by participants measured before they read the scenarios. If so, it would be an additional test of the existence of the confirmation effect. We carried out a multiple regression analysis with the level of EA ascribed to the investment advisor as a dependent variable, and the experimental manipulation of the advice (pro vs against the product), norm valence (positive vs negative), participants measured opinion on investing, and the interaction of these three variables as predictors.5 As in all previous analyses, all variables were zscored prior to this analysis. We found that the regression model with experimental manipulation of advice, participants opinions on investing and their interaction as predictors of the EA ascribed to the investment advisor was significant, F(3, 385) 5 5.206, 5 We also conducted regression analysis with experimental manipulation of the advice (pro vs against the product), both participants measured and manipulated opinions, and all interactions between these variables as predictors. This analysis confirmed the significance of two-way interactions between opinions (measured or manipulated) and recommendations (ps .005). The two-way interaction between participants manipulated and measured opinions did not reach the significance level (p 5 .490). The three-way interaction between recommendations, manipulated opinions, and measured opinions was also not significant (p 5 .727). The insignificance of this three-way interaction and the lack of two-way interaction between manipulated opinions and measured opinions demonstrate that the two operationalisations of opinions did not interfere with each other. C 2018 International Association of Applied Psychology. V

26


711

FIGURE 4. The level of EA ascribed to the advisor as a function of participants’ measured opinions on investing in the stock market and experimental manipulation of advice. Tags represent groups of participants scoring low, moderate, and high on the opinion of investing in the stock market and are based on mean value and 1/2 1 SD from the mean.

p 5 .002, R2 5 .039. The three-way interaction between norm valence, advice and participants opinion was not significant (b 5 2.038, SE 5 .051, t 5 2.74, p 5 .456, 95% CI [2.139, .062]). In line with our expectations, we observed a significant interaction between the advisors recommendation and participants opinions (b 5 .140, SE 5 .051, t 5 2.757, p 5 .006, 95% CI [.040, .241]). Also, the effect of participants opinion was significant (b 5 .143, SE 5 .051, t 5 2.808, p 5 .005, 95% CI [.043, .243]). None of the other effects reached the conventional level of significance; norm valence: b 5 2.030, SE 5 .050, t 5 2.591, p 5 .555, 95% CI [2.129, .070]; advice: b 5 2.002, SE 5 .050, t 5 2.040, p 5 .968, 95% CI [2.101, .097]; norm valence by advice: b 5 .047, SE 5 .050, t 5 0.928, p 5 .354, 95% CI [2.052, .146]; norm valence by participants opinion: b 5 2.050, SE 5 .051, t 5 2.747, p 5 .456, 95% CI [2.139, .063]. To examine the interaction between participants opinion on investing and the recommendation, we performed two types of conditional effect (simple slopes) analyses. First, the relationship between IV (advice) and DV (assessment of advisors EA) was investigated at three levels of the moderator: mean, 1 SD above and 1 SD below mean (see Figure 4). The association at the lowest level of the moderator (M – 1SD 5 1.581), the most negative opinion on investing held by participants, was significant and negative (b 5 2.145, SE 5 0.071, t 5 22.039, p 5 .04, 95% CI [2.284, 2.005]), indicating that in this case, the advisor who recommended opening the investment account was perceived as less competent than the advisor who recommend not doing so. For the C 2018 International Association of Applied Psychology. V


27

moderate level of the moderator (M 5 2.378), the association between experimental manipulation of advice and the EA assigned to advisor was not significant (b 5 2.005, SE 5 .050, t 5 20.110, p 5 .912, 95% CI [2.104, .093]). For the highest level of the moderator (M 1 1SD 5 3.179), the effect of advice on advisors EA was marginally significant and positive (b 5 .134, SE 5 .071, t 5 1.882, p 5 .061, 95% CI [2.006, 0.273]), suggesting that when participants held a positive opinion towards investing, they perceived the advisor who recommended opening the investment account as more competent than the advisor who recommended avoiding such investment activity. Altogether, these results supported hypothesis H3. The analysis of the Johnson–Neyman regions of significance demonstrated that the relationship between advice and assessment of advisors EA was negative and significant when the raw score for the participants opinion of investing was below 1.637 (z-score below 20.927), and positive and significant when the raw score for participants opinion of investing was above 3.247 (zscore above 1.088). Such results again supported hypothesis H3, implying that individuals holding a particular opinion on investing perceived the advisor who agreed with their opinion as being a better expert than the advisor whose recommendation was contradictory to their opinion, revealing the confirmation effect. SEA. Finally, we again explored whether the existence of a confirmation effect depends on the SEA level in finances declared by participants. To test hypothesis H3c, we conducted two regression analyses with the experimental manipulations of the advice (pro vs against the product), opinion (manipulated in the scenario as positive vs negative or participants opinion of investing measured before the scenario), participants SEA in finances, and all interactions between these variables as predictors. All variables were z-scored prior to the analysis. The results of the first regression analysis confirmed the predicted significant interaction between the recommendation and the participants opinions (b 5 .181, SE 5 .050, t 5 3.644, p < .001, 95% CI [.083, .279]). The three-way interaction between advice, the participants opinions, and SEA was not significant (b 5 .009, SE 5 .050, t 5 .188, p 5 .851, 95% CI [2.089, .108]). Also, the second regression analysis confirmed the predicted interaction between the recommendation and participants opinions of investing (b 5 .155, SE 5 .050, t 5 3.050, p 5 .002, 95% CI [.055, .255]). Unlike in the two earlier experiments, the three-way interaction between advice, participants opinions and SEA was significant (b 5 2.138, SE 5 .046, t 5 23.018, p 5 .002, 95% CI [2.227, 2.048]). However, the examination of this interaction did not support hypothesis H3c stating that individuals with higher SEA in finances should demonstrate the strongest confirmation effect, as the agreement from an expert in their case would be self-validating. The interaction between advice and opinion C 2018 International Association of Applied Psychology. V

28


at the lowest level of SEA was significant (b 5 .293, SE 5 0.072, t 5 4.050, p < .001, 95% CI [.151, .435]), as it was for the moderate level of SEA (b 5 .155, SE 5 .051, t 5 3.050, p 5 .002, 95% CI [.055, .255]). For the highest level of the moderator, the interaction effect was not significant (b 5 .017, SE 5 .064, t 5 .272, p 5 .786, 95% CI [2.109, .143]), revealing no confirmation effect.

Discussion The last experiment again showed that lay evaluations of the EA of experts in the financial domain tended to be affected by the need for confirmation. This experiment also demonstrated that when both ones own opinions and social norms concerning financial behaviour were salient, the former prevails over the latter, which supported hypothesis H3. In other words, if peoples own beliefs are salient, they want to confirm them even if these beliefs differ from what is typical for other society members. Results of the regression analysis were also supportive of the claim that the search for confirmation affects peoples evaluations of experts authority: greater EA was assigned to those financial consultants whose advice was confirming participants own opinions on the profitability of the engagement in investment activities. Once again, the detailed statistical analysis did not support hypothesis H3c that subjective knowledge in finances (represented by the SEA factor) moderated the confirmation effect on the EA perception.

GENERAL DISCUSSION

Summary of the Results The main aim of the present experimental project was to document how lay peoples need to confirm their own opinions affects their evaluations of the EA of experts in the domain of finance. In Experiment 1, we demonstrated that lay people ascribed greater epistemic authority to those experts whose advice confirmed their opinions, irrespective of whether these opinions were measured with a scale or experimentally manipulated. The results of Experiment 2 revealed that when peoples own opinions were not salient, people tended to evaluate experts authority as higher when their advice was congruent with social norms revealing the most common financial behaviour. Finally, in Experiment 3, we jointly investigated the effects of participants own opinions and social norms on the evaluations of expert authority. When both sources of expertise were made salient, decision-makers favoured advice confirming their own beliefs and used it to evaluate experts authority. Altogether, results from the three experiments showed that people tended to ascribe greater EA to those financial consultants whose advice was congruent with peoples preferences, C 2018 International Association of Applied Psychology. V


29

constructed on the basis of either peoples own opinions or social norms reflecting common behaviour in society. The confirmation effect in EA evaluation was found for two different products (insurance and investment accounts) and held for two separate indicators of opinions (manipulated in an experiment and measured with two questionnaire questions). Our results clearly indicated that when decision-makers evaluate recommendations provided by experts it might be more important for them to confirm their private beliefs or norms respected by other group members than to search for rational cues regarding advice quality. Because literally the same advice differently influenced EA evaluations depending on a priori opinion or the salient social norm, it seems justified to conclude that these evaluations were at least partly distorted.

Psychological Mechanisms Behind the Confirmation Effect in Lay Evaluations of Expert Advice and Future Studies Why are people so strongly motivated to confirm either their own opinions or social norms when evaluating experts authority? To answer this question, we ought to elaborate more precisely on the psychological nature of the confirmation effect. Nickerson (1998) argued that confirmation bias “connotes the seeking or interpreting of evidence in ways that are partial to existing beliefs, expectations, or a hypothesis in hand” (p. 175). This definition resembles a classical cognitive interpretation proposed by Klayman and Ha (1987) who introduced the term positive test strategy, meaning that “people tend to test hypotheses by looking at instances where the target property is hypothesised to be present or is known to be present” (p. 225). Such an approach to the study of the confirmation effect entails that this inclination amounts to a selective search for information and discrimination in the use of it. However, the confirmation effect might also be understood as a part of the broader phenomenon of “motivated reasoning” (Kunda, 1987, 1990; Mercier & Sperber, 2011; Molden & Higgins, 2005). Research has shown that people engage in “motivated thinking” to defend their beliefs and to preserve a positive view of themselves (Mercier & Sperber, 2011) or to minimise negative and maximise positive affective states (Westen, Blagov, Harenski, Kilts, & Hamann, 2006). Even if lay people do not possess expert knowledge of a given area and hence feel that they have to turn to an expert for advice, they still can have their own opinions or beliefs on issues in the area. Lay people often hold naive theories of reality (e.g. economic reality; see Furnham & Lewis, 1986; Lea, Tarpy, & Webley, 1987) that help them to structure and understand the world surrounding them and expect that new knowledge would be consistent with these theories. Therefore, expert advice that disconfirms peoples own view might be perceived as a threat to self-worth, because it challenges their sense of self as C 2018 International Association of Applied Psychology. V

30


competent, intelligent, rational, and able to control the environment (Steele, 1988). Disconfirming recommendations might evoke dissonant cognitions and give rise to negative emotional arousal, discomfort, and unpleasant tension (Zanna & Cooper, 1974). To cope with such threats, people initiate different defensive strategies that include dismissing or denying the threatening (e.g. disconfirming) information (Sherman & Cohen, 2006). Defensive responses might take the form of rationalising and interpreting evidence in a way congenial to ones desires and expectations (Aronson, 1968; Festinger, 1957; Greenwald, 1980). For example, research on decision-making has shown that people exhibit confirmation bias in post-decision information processing to avoid cognitive dissonance and regret (Joseph, Larrick, Steele, & Nisbett, 1992). Decision-makers are strongly determined to bolster alternatives they have chosen by favouring their positive aspects, depreciating their negative aspects, and rejecting evidence disconfirming their positive a priori judgment of the chosen option (Svenson, 1992, 1996). In light of the above argumentation we propose that lay people who evaluate the authority of experts favour advice confirming their own beliefs, because they are motivated to sustain self-integrity and maintain their view of themselves as competent in the area. In other words, bolstering confirmatory and depreciating disconfirmatory advice might be interpreted as a psychological strategy initiated to defend self-worth. Another interpretation of our results refers to the role associative processes play in peoples intuitive or naive judgments (Morewedge & Kahneman, 2010). It seems that attributing greater EA to some experts as a consequence of searching for confirmation might be explained by employing intuitive System 1 rather than rational System 2 in the evaluation process (Kahneman, 2003, 2011). In particular, it is possible that when forming their EA evaluations, people rely on how easily and fluently they can process information received from an expert. Consistency creates fluency (Winkielman, Huber, Kavanagh, & Schwarz, 2011), and therefore advice that is consistent with an advisees own opinions is more likely to be processed in a fluent and more effortless way. Alter and Oppenheimer (2009), who investigated the processing fluency phenomenon, have proposed that experience of fluency produces feelings of confidence, truth, and pleasure. Furthermore, more fluent processing and cognitive ease are associated with positive affective experiences (Topolinski, Likowski, Weyers, & Strack, 2009; Winkielman & Cacioppo, 2001). Because processing advice congruent with ones own beliefs is rewarding—that is, easier—more automatic/intuitive, more familiar and more pleasant, receiving confirmatory advice might be associated with feelings of truthfulness, trustworthiness, and validity. Therefore, as a consequence, recommendations congruent with ones own opinions lead to ascribing greater authority to its source, that is, an expert offering it. C 2018 International Association of Applied Psychology. V


31

Finally, the third interpretation of the association between the confirmation effect and the EA evaluations that was found in the present research might be related to the naive realism phenomenon. People are called naive realists because they typically assume that they perceive the world objectively and believe that others share their perceptions (Pronin, 2007, 2008; Ross & Ward, 1996). If people realise that others disagree with them, they might come to believe that others are either uninformed or biased (Pronin, Gilovich, & Ross, 2004). Pronin, Lin and Ross (2002) proposed that people exhibit the bias blind spot, that is, they see others as more susceptible to cognitive and motivational biases than themselves. Taking this into account, we might speculate that our participants attributed greater EA to the advisors who confirmed their opinions because they perceived them as less biased, better informed or more rational in general. The three interpretations presented above do not have to be regarded as competitive or mutually exclusive, as they share some common features. All of them refer to either positive feelings when advice is confirmatory of ones expectations (fluency, experiencing self-integrity or interacting with experts perceived as more rational) or negative feelings when advice disconfirms a priori expectations (cognitive difficulty, experiencing threat to the self or interacting with advisors perceived as biased). Furthermore, dissonant cognitions that result from receiving contradicting advice are not only more difficult to process but also might be perceived as threatening to self-worth and motivate an individual to initiate defensive strategies. However, even if some interconnections between these three explanations can be displayed, one of them might dominate in how accurately it discloses sources of distortions in EA evaluations. Further research is required to investigate the ways self-defences, cognitive ease and naive realism might explain how peoples need for confirmation affects their perceptions of experts authority. In future studies, we plan to test whether and to what extent self-esteem, fluency of cognitive processing and perceived advisors susceptibility to biases mediate the interrelationships among lay peoples opinions, experts advice, and the evaluation of an experts epistemic authority. We expect that the congruence between advice and the participants own opinion would increase: (1) the participants self-esteem; (2) the participants fluency of processing of advice; and (3) perceptions of an expert as less biased. These effects would in turn cause ascription of greater authority to the expert. On the other hand, advice disconfirming the participants beliefs would decrease self-esteem and fluency of processing, and increase perceptions of an expert as biased. We predict that in such a case the evaluation of the experts EA would be harmed. Moreover, because in this project we based our experiments on scenarios, in future studies we plan to examine whether the participants actual decisions would follow recommendations given by experts. C 2018 International Association of Applied Psychology. V

32


The present research sought to study the evaluation of the EA of experts in the financial domain. Subsequent studies should examine whether the same or similar effects appear when lay people evaluate the quality of expertise in other areas. For example, it would be interesting to analyse how lay decision-makers form their EA perceptions when more unambiguous cues for expertise quality are also available (e.g. in the domain of medicine, engineering or law).

Practical Implications The results of the present experimental project offer several practical implications. The most important effect that was reported in this paper suggests that lay people tend to perceive financial advisors as more competent when advisors give recommendations congruent with peoples own preferences. The real life consequence of this effect seems to be straightforward: If advisors first recognise the clients beliefs concerning the financial product and then adjust the recommendation to these beliefs, they would appear more competent in the eye of the client irrespective of the actual quality of the advice. We point at this possibility, but we do not propose it as proper and professional behaviour of any advisor. Manipulating recommendations to increase perceived authority, irrespective of whether they are profitable for clients or financial advisors, is strongly unethical and blameworthy. The most important practical application of the results we found in our experiments would be increasing lay peoples awareness of biases that might occur while interacting with an advisor. Customers should be trained to recognise the sources of their conviction that they met a professional advisor who gives recommendations in their best interest. They should also be informed that their reliance on expert advice might result only from the fact that this advice was consistent with their own beliefs. Finally, financial clients should learn to deal with recommendations that are opposite to their opinions. As we proposed in the General Discussion section, advice inconsistent with the clients own preferences might be harmful for their selfesteem, be more difficult to process, and lead to perceiving an expert as biased, but at the same time might increase the chances of making a good decision.

REFERENCES Aarts, H., & Dijksterhuis A. (2003). The silence of the library: Environment, situational norm, and social behavior. Journal of Personality and Social Psychology, 84, 18–28. Alter, A.L., & Oppenheimer, D.M. (2009). Uniting the tribes of fluency to form metacognitive cation. Personality and Social Psychology Review, 13, 219–235. Aronson, E. (1968). Dissonance theory: Progress and problems. In R.P. Abelson, E. Aronson, W.J. McGuire, T.M. Newcomb, M.J. Rosenberg, & P.H. Tannenbaum (Eds.), Theories of cognitive consistency: A sourcebook (pp. 5–27). Chicago: Rand McNally. C 2018 International Association of Applied Psychology. V


33

Aronson, E., Wilson, T.D., & Akert, R.M. (2007). Social psychology (6th edn). Upper Saddle River, NJ: Pearson Prentice Hall. Barnoy, S., Levy, O., & Bar-Tal, Y. (2009). Nurse or physician: Whose recommendation influences the decision to take genetic tests more? Journal of Advanced Nursing, 66(4), 806–813. Barnoy, S., Ofra, L., & Bar-Tal, Y. (2012). What makes patients perceive their health care worker as an epistemic authority. Nursing Inquiry, 19(2), 128–133. Baron, J. (2000). Thinking and deciding (3rd edn). New York: Cambridge University Press. Bar-Tal, Y., Stasiuk, K., & Maksymiuk, R. (2013). Patients perceptions of physicians epistemic authority when recommending flu inoculation. Health Psychology, 32, 706–709. Bonaccio, S., & Dalal, R.S. (2006). Advice taking and decision-making: An integrative literature review, and implications for the organizational sciences. Organizational Behavior and Human Decision Processes, 101, 127–151. Cialdini, R.B., & Goldstein, N.J. (2004). Social influence: Compliance and conformity. Annual Review of Psychology, 55, 591–621. Cialdini, R.B., Reno, R.R., & Kallgren, C.A. (1990). A focus theory of normative conduct: Recycling the concept of norms to reduce littering in public places. Journal of Personality and Social Psychology, 58, 1015–1026. Ditto, P.H., & Lopez, D.L. (1992). Motivated skepticism: Use of differential decision criteria for preferred and nonpreferred conclusions. Journal of Personality and Social Psychology, 63, 568–584. Ditto, P.H., Scepansky, J.A., Munro, G.D., Apanovitch, A.M., & Lockhart, L.K. (1998). Motivated sensitivity to preference-inconsistent information. Journal of Personality and Social Psychology, 75, 53–69. Ecken, P. & Pibernik, R. (2015). Hit or miss: What leads experts to take advice for long-term judgments? Management Science, 62, 2002–2021. Edwards, K. & Smith, E.E. (1996). A disconfirmation bias in the evaluation of arguments. Journal of Personality and Social Psychology, 71, 5–24. Faul, F., Erdfelder, E., Lang, A.-G., & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39, 175–191. Festinger, L. (1957). A theory of cognitive dissonance. Stanford, CA: Stanford University Press. Furnham, A., & Lewis, A. (1986). The economic mind: The social psychology of economic behavior. New York: St Martins Press. Gilovich, T., Griffin, D., & Kahneman, D. (2002). Heuristics and biases: The psychology of intuitive judgment. New York: Cambridge University Press. Greenwald, A.G. (1980). The totalitarian ego: Fabrication and revision of personal history. American Psychologist, 35, 603–618. Harvey, N., & Fischer, I. (1997). Taking advice: Accepting help, improving judgment, and sharing responsibility. Organizational Behavior and Human Decision Processes, 70, 117–133. Hayes, A.F. (2013). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. New York: Guilford Press.

C 2018 International Association of Applied Psychology. V

34


Heath, C., & Gonzalez, R. (1995). Interaction with others increases decision confidence but not decision quality: Evidence against information collection views of interactive decision making. Organizational Behavior and Human Decision Processes, 61, 305–326. Joseph, R.A., Larrick, R.P., Steele, C.M., & Nisbett, R.E. (1992). Protecting the self from the negative consequences of risky decisions. Journal of Personality and Social Psychology, 62, 26–37. Kahneman, D. (2003). A perspective on judgment and choice: Mapping bounded rationality. American Psychologist, 58, 697–720. Kahneman, D. (2011). Thinking, fast and slow. New York: Farrar, Strauss, Giroux. Klayman, J., & Ha, Y.W. (1987). Confirmation, disconfirmation, and information in hypothesis testing. Psychological Review, 94, 211–228. Kruglanski, A.W. (1980). Lay epistemo-logic—process and contents: Another look at attribution theory. Psychological Review, 87, 70–87. Kruglanski, A.W. (1989). Lay epistemics and human knowledge: Cognitive and motivational bases. New York: Springer Science1Business Media. Kruglanski, A.W. (2012). Lay epistemic theory. In P.A.M. van Lange, A.W. Kruglanski & E.T. Higgins (Eds.), Handbook of theories of social psychology (Vol. 1, pp. 201–223). London: Sage. Kruglanski, A.W., Orehek, E., Dechesne, M., & Pierro, A. (2010). Lay epistemic theory: The motivational, cognitive, and social aspects of knowledge formation. Social and Personality Psychology Compass, 4, 939–950. Kruglanski, A.W., Raviv, A., Bar-Tal, D., Raviv, A., Sharvit, K., Ellis, S., Bar, R., Pierro, A., & Mannetti, L. (2005). Says who? Epistemic authority effects in social judgment. In M.P. Zanna (Ed.), Advances in experimental social psychology (pp. 345–392). New York: Academic Press. Kunda, Z. (1987). Motivated inference: Self-serving generation and evaluation of causal theories. Journal of Personality and Social Psychology, 53, 636–647. Kunda, Z. (1990). The case for motivated reasoning. Psychological Bulletin, 108, 480–498. Kunda, Z. (1999). Social Cognition: Making Sense of People. Cambridge, MA: MIT Press. Lea, S.E.G., Tarpy, R.M., & Webley, P. (1987). The individual in the economy. Cambridge, MA: Cambridge University Press. Liberman, V., Minson, J.A., Bryan, C.J., & Ross, L. (2011). Naive realism and capturing the “wisdom of dyads”. Journal of Experimental Social Psychology, 48, 507–512. Lord, C.S., Ross, L., & Lepper, M. (1979). Biased assimilation and attitude polarization: The effects of prior theories on subsequently considered evidence. Journal of Personality and Social Psychology, 37, 2098–2109. Lundgren, S.R., & Prislin, R. (1998). Motivated cognitive processing and attitude change. Personality and Social Psychology Bulletin, 24, 715–726. Mercier, H., & Sperber, D. (2011). Why do humans reason? Arguments for an argumentative theory. Behavioral and Brain Sciences, 34, 57–111. Minson, J.A., Liberman, V., & Ross, L. (2011). Two to tango: Effects of collaboration and disagreement on dyadic judgment. Personality and Social Psychology Bulletin, 37, 1325–1338.



35

Mojzisch, A., Kerschreiter, R., Faulm€ uller, N., Vogelgesang, F., & Schulz-Hardt, S. (2014). The consistency principle in interpersonal communication: Consequences of preference confirmation and disconfirmation in collective decision making. Journal of Personality and Social Psychology, 106, 961–977. Molden, D.C., & Higgins, E.T. (2005) Motivated thinking. In K. Holyoak & B. Morrison (Eds.) Handbook of thinking and reasoning (pp. 295–320). New York: Cambridge University Press. Morewedge, C.K., & Kahneman, D. (2010). Associative processes in intuitive judgment. Trends in Cognitive Sciences, 14, 435–440. Nickerson, R.S. (1998). Confirmation bias: A ubiquitous phenomenon in many guises. Review of General Psychology, 2, 175–220. Nolan, J.M., Schultz, P.W., Cialdini, R.B., Goldstein, N.J., & Griskevicius, V. (2008). Normative social influence is underdetected. Personality and Social Psychology Bulletin, 34, 913–23. Preacher, K.J., Rucker, D.D., & Hayes, A.F. (2007). Addressing moderated mediation hypotheses: Theory, methods, and prescriptions. Multivariate Behavioral Research, 42, 185–227. Pronin, E. (2007). Perception and misperception of bias in human judgment. Trends in Cognitive Science, 11, 37–43. Pronin, E. (2008). How we see ourselves and how we see others. Science, 320(5880), 1177–1180. Pronin, E., Gilovich, T., & Ross, L. (2004). Objectivity in the eye of the beholder: divergent perceptions of bias in self versus others. Psychological Review, 111, 781–799. Pronin, E., Lin, D.Y., & Ross, L. (2002). The bias blind spot: Perceptions of bias in self versus others. Personality and Social Psychology Bulletin, 28, 369–381. Raviv, A., Bar-Tal, D., Raviv, A., & Abin, R. (1993). Measuring epistemic authority: Studies of politicians and professors. European Journal of Personality, 7, 119–138. Ross, L., & Ward, A. (1996). Naive realism in everyday life: Implications for social conflict and misunderstanding. In T. Brown, E.S. Reed & E. Turiel (Eds.), Values and Knowledge (pp. 103–135). Hillsdale, NJ: Erlbaum. Schultz, P.W., Nolan, J.M., Cialdini, R.B., Goldstein, N.J., & Griskevicius, V. (2007). The constructive, destructive, and reconstructive power of social norms. Psychological Science, 18, 429–434. Schultze, T., Rakotoarisoa, A., & Schulz-Hardt, S. (2015). Effects of distance between initial estimates and advice on advice utilization. Judgment and Decision Making, 10, 144–171. Shanteau, J. (1992). Competence in experts: The role of task characteristics. Organizational Behavior and Human Decision Processes, 53, 252–266. Sherman, D.K., & Cohen, G.L. (2006). The psychology of self-defense: Selfaffirmation theory. In M.P. Zanna (Ed.), Advances in experimental social psychology (Vol. 38, pp. 183–242). San Diego, CA: Academic Press. Siegrist, M., Earle, T., & Gutscher, H. (2003). Test of a trust and confidence model in the applied context of electromagnetic field (EMF) risks. Risk Analysis, 23, 705–716. Sniezek, J.A., Schrah, G.E., & Dalal, R.S. (2004). Improving judgment with prepaid expert advice. Journal of Behavioral Decision Making, 17, 173–190.


36


721

Soll, J.B., & Larrick, R.P. (2009). Strategies of revising judgment: How (and how well) people use others opinions. Journal of Experimental Psychology: Learning, Memory and Cognition, 35, 780–805. Stasiuk, K., Bar-Tal, Y., & Maksymiuk, R.A. (2016). The effect of physicians treatment recommendations on their epistemic authority: The medical expertise bias. Journal of Health Communication: International Perspectives, 21, 92–99. Steele, C.M. (1988). The psychology of self-affirmation: Sustaining the integrity of the self. In L. Berkowitz (Ed.), Advances in experimental social psychology (Vol. 21, pp. 261–302). San Diego, CA: Academic Press. Svenson, O. (1992). Differentiation and consolidation theory of human decision making: A frame of reference for the study of pre- and post decision processes. Acta Psychologica, 80, 143–168. Svenson, O. (1996). Decision making and the search for fundamental psychological regularities: What can be learned from a process perspective? Organizational Behavior and Human Decision Processes, 65, 252–267. Topolinski, S., Likowski, K.U., Weyers, P., & Strack, F. (2009). The face of fluency: Semantic coherence automatically elicits a specific pattern of facial muscle reactions. Cognition and Emotion, 23, 260–271. Twyman, M., Harvey, N., & Harries, C. (2008). Trust in motives, trust in competence: Separate factors determining the effectiveness of risk communication. Judgment and Decision Making, 3, 111–120. Westen, D., Blagov, P.S., Harenski, K., Kilts, C., & Hamann, S. (2006). Neural bases of motivated reasoning: An fMRI study of emotional constraints on partisan political judgment in the 2004 U.S. presidential election. Journal of Cognitive Neuroscience, 18, 1947–1958. Winkielman, P., & Cacioppo, J.T. (2001). Mind at ease puts a smile on the face: Psychophysiological evidence that processing facilitation increases positive affect. Journal of Personality and Social Psychology, 81, 989–1000. Winkielman, P., Huber, D.E., Kavanagh, L., & Schwarz, N. (2012). Fluency of consistency: When thoughts fit nicely and flow smoothly. In B. Gawronski & F. Strack (Eds.), Cognitive consistency: A fundamental principle in social cognition (pp. 89–111). New York: Guilford Press. Yaniv, I. (2004a). Receiving other peoples advice: Influence and benefit. Organizational Behavior and Human Decision Processes, 93, 1–13. Yaniv, I. (2004b). The benefit of additional opinions. Current Directions in Psychological Science, 13, 75–78. Yaniv, I., Choshen-Hillel, S., & Milyavsky, M. (2009). Spurious consensus and opinion revision: Why might people be more confident in their less accurate judgments? Journal of Experimental Psychology: Learning, Memory, and Cognition, 35, 558–563. Yaniv, I., Choshen-Hillel, S., & Milyavsky, M. (2011). Receiving advice on matters of taste: Similarity, majority influence, and taste discrimination. Organizational Behavior and Human Decision Processes, 115, 111–120. Yaniv, I., & Kleinberger, E. (2000). Advice taking in decision making: egocentric discounting and reputation formation. Organizational Behavior and Human Decision Processes, 83, 260–281.



37

Yaniv, I., & Milyavsky, M. (2007). Using advice from multiple sources to revise and improve judgment. Organizational Behavior and Human Decision Processes, 103, 104–120. Yates, J.F., Price, P.C., Lee, J., & Ramirez, J. (1996). Good probabilistic forecasters: The “consumers” perspective. International Journal of Forecasting, 12, 41–56. Zaleskiewicz, T., Gasiorowska, A., Stasiuk, K., Maksymiuk, R., & Bar-Tal, Y. (2016). Lay evaluation of financial experts: The action advice effect and confirmation bias. Frontiers in Psychology, 7, 1476. Zanna, M.P., & Cooper J. (1974). Dissonance and the pill: An attribution approach to studying the arousal properties of dissonance. Journal of Personality and Social Psychology, 29, 703–709.
