Vocational choice may be considered as a process of procuring, integrating, and applying information. During the 1960s, several vocational theorists explored vocational choice behaviour based on psychological decision theory (Blau, Gustad, Jesser, Parnes, & Wilcock, Reference Blau, Gustad, Jesser, Parnes and Wilcock1956; Brayfield, Reference Brayfield1963), and the general decision-making conceptual framework assumes that the presence of a decision maker, a decision situation, and relevant information are obtained both from internal and external persons (Jepsen & Dilley, Reference Jepsen and Dilley1974). During the decision process, a decision maker must collect all kinds of information, as probability and uncertainty are key decision-making characteristics. Thus, job seekers must search for information regarding a decision task and evaluate the applicability of that information. Job seekers will encounter information from various sources, and a choice will be made from several alternatives. Thus, taking advice is a central component to realistic decision making (Yaniv & Klienberger, Reference Yaniv and Kleinberger2000). In China, exhortatory culture has a long history. For example, in The Book of Songs and The Book of Han there are some writings about persuading and taking advice. For job seekers, others’ advice is an important information source when facing a vocational decision. In particular, the vocational decisions of Chinese people are usually influenced by significant others. Bonaccio and Dalal (Reference Bonaccio and Dalal2006) provided an example whereby college graduates were likely to consult parents and peers regarding whether to accept a job offer. However, in real vocational decision-making situations, job seekers may ask for advice from others, but then ignore or even refuse to accept others’ advice. Similarly, graduates may ask their parents, friends, teachers, and so on for advice about their career, but they do not always take others’ advice. Therefore, it is useful to determine what factors affect whether job seekers take others’ advice.
To clarify factors that influence advice taking and how they exert this influence, researchers developed a paradigm referred to as the Judge-Advisor System (JAS; Sniezek & Buckley, Reference Sniezek and Buckley1995; Sniezek & Van Swol, Reference Sniezek and Van Swol2001). In the judgment and decision-making literature, the JAS is an important research framework that has been predominantly used to study the offering and receipt of advice throughout the decision-making processes (Bonaccio & Dalal, Reference Bonaccio and Dalal2006). This paradigm allows researchers to study the unique decision-making roles of both ‘judges’ and ‘advisors’, as well as their interactions. In a JAS study, judges are asked to make an initial decision after examining information relevant to the decision; they then receive advice from advisors after making the initial decision. Judges then make a final decision based on this additional information. Some researchers use the JAS paradigm to explore the effect of confidence expressed by either the advisor or judge on taking advice (Price & Stone, Reference Price and Stone2004), type of task (Sniezek & Van Swol, Reference Sniezek and Van Swol2001), solicited and unsolicited advice (Gino, Reference Gino2008; Yaniv & Kleinberger, Reference Yaniv and Kleinberger2000), or the effect of trust (Kang, Pang, & Zhang, Reference Kang, Pang and Zhang2014). In the JAS, the relationship between decision maker and advisor is a dynamic interaction. Decision makers look for advisors’ advice positively on the one hand, and advisors offer advice and feedback to decision makers on the other. It is generally recognised that characteristics of both the advisor and the decision maker influence advice taking (Gino & Schweitzer, Reference Gino and Schweitzer2008).
Chinese culture places emphasis on collectivism, unlike the predominantly individualistic culture in Western countries (Spencer-Oatey, Reference Spencer-Oatey2000). People from collectivistic cultures tend to desire relational harmony and obey authority (Feng & Feng, Reference Feng and Feng2013). Therefore, Chinese people are more likely to perceive and understand others’ messages (Triandis & Suh, Reference Triandis and Suh2002; Wu & Rubin, Reference Wu and Rubin2000). More than 2,200 years ago in the Shui Nan, Han Feizi indicated that advisors should try to understand others’ minds so that their advice would fit others’ intentions. In the practice of career guidance, we also found that job seekers may have expectations of choice during the vocational decision-making process before they consult the advice from others. Some job seekers’ orientation toward vocational choice may be related to the positive outcomes (e.g., hopes, wishes, and aspirations), while others’ expectations may be concerned with the negative outcomes (e.g., duties, obligations, and responsibilities). According to regulatory focus theory (Higgins, Reference Higgins1997), the former is the promote orientation, while the latter is prevented orientation. What is regulatory focus theory? Indeed, it is a goal pursuit theory that places special emphasis on the relation between the motivational orientation of the actor and the strategic means used by that actor when pursuing a goal (Higgins, Reference Higgins2000, Reference Higgins2005). According to regulatory focus theory, people with promotion goals are sensitive to gains and non-gains, whereas people with prevention goals are sensitive to losses and non-losses. The theory also distinguishes two different means for goal pursuit, which are eagerness mean and vigilance mean (Crowe & Higgins, Reference Crowe and Higgins1997). There are two natural fits between promote orientation and the use of eagerness means, and between prevent orientation and the use of vigilance means (Cesario, Higgins, & Scholer, Reference Cesario, Higgins and Scholer2008; Higgins, Reference Higgins1997). Regulatory fit effects may increase the value of what people do in the process of achieving goals, and make people feel right about what they are doing. Conversely, people will experience negative emotions when there is a fit violation (Camacho, Higgins, & Luger, Reference Camacho, Higgins and Luger2003). Research evidence has demonstrated that affective and non-affective states are influential information sources during judgments and decision making (Clore, Reference Clore, Martin and Tesser1992; Clore et al., Reference Clore, Wyer, Dienes, Gasper, Gohm, Isbell, Martin and Clore2001). For vocational decision makers, affective states can produce regulatory fit or conflict when receiving advice that promotes either standard orientation conditions or prevention orientation conditions, because job seekers with different target orientations for vocational choice may also have different attitudes toward others’ advice. That is to say, advice taking may be influenced by the consistency between job seekers’ expectations and advisors’ proposals. If a job seeker tends to get benefit from a job, and the advice from others emphasises that the job is stable, offers a high income, provides abundant social security and more opportunities, the job seeker would feel more energised and motivated, and likely to accept others’ advice. In contrast, a job seeker would feel more frustrated and discouraged if others’ suggestions emphasised that the job was unstable, offered a low-income, caused high stress, and was not consistent with their goals; these negative feelings would reduce the likelihood of taking others’ advice. Therefore, the present study assumes that a decision maker will be more likely to adopt others’ advice within a regulatory fit rather than an unfit condition. In other words, promotion orientation-eager and prevention orientation-vigilant strategies will lead job seekers to take others’ advice. However, promotion orientation-vigilant and prevention orientation-eager strategies will restrain the reception of others’ advice. Furthermore, regulatory fit effect was influenced by framing negative feedback (Kung, Kim, Yang, & Cheng, Reference Kung, Kim, Yang and Cheng2016). Therefore, experiment 1 will explore this assumption under the conditions that advice strategy is manipulated effectually.
Regulatory fit causes a decision maker to ‘feel right’ about what she/he is doing (Righetti, Finkenauer, & Rusbult, Reference Righetti, Finkenauer and Rusbult2011), and this feeling could be transferred to one's own evaluation (Cesario, Grant, & Higgins, Reference Cesario, Grant and Higgins2004); however, less is known about whether ‘feeling right’ is the actual reason a decision maker will take advice within a regulatory fit condition. The feelings-as-information theory assumes that people attend to their emotional state as a source of information (Schwarz, Reference Schwarz, Van Lange, Kruglanski and Higgins2012), and feeling good (due to regulatory fit) produces other positive feelings (i.e., importance and correctness) that can be transferred onto the evaluation of various objects (Camacho et al., Reference Camacho, Higgins and Luger2003; Higgins et al., Reference Higgins, Idson, Freitas, Spiegel and Molden2003). Thus, the evaluation of others’ advice should be more positive because of right feeling due to the resultant positive feelings. However, feeling good does not always play an important role in certain persuasion contexts or decision tasks. Higgins and colleagues (Reference Higgins, Idson, Freitas, Spiegel and Molden2003) drew participants’ attention toward the correct source for the positive feelings and guided them to attribute the right feeling to the regulatory fit effect, rather than the rightness or wrongness of others’ advice, thereby diminishing the relevance of their effect during a price evaluation task. Here, regulatory fit no longer increased the price that individuals were willing to pay for an item; that is, the effect of regulatory fit would reduce or even eliminate the decision when participants realised the source of their feelings or whether they could correctly detect the emotion type. Therefore, the regulatory fit effect could be a form of misattribution (Cesario et al., Reference Cesario, Grant and Higgins2004), and this effect could stem from decision makers confusing the source of their feelings toward characteristics of the evaluation target (Aaker & Lee, Reference Aaker and Lee2006). According to this view, if job seekers take others’ advice because it feels right, which stems from the regulatory fit effect during the vocational decision-making process, then the possibility of taking advice would be reduced when job seekers are aware of the actual source of their positive emotions. For the present study, we are interested in whether the regulatory fit effect will be reduced or even disappear within these attribution conditions; this issue is tested in experiment 2.
EXPERIMENT 1
Method
Participants and Design
In China, college students are the most typical job seekers and employee group, and their vocational decision-making behaviours can reflect general job seekers’ psychological characteristics and patterns to some extent. Therefore, this study mainly selected college students as participants to take part in the experiment. In total, 102 Northwest Normal University undergraduates (51 men and 51 women) participated in this experiment and were paid a small remuneration. Their average age was 23.27 years old (SD = 3.29). All participants were asked to complete a vocational decision-making task and were told their decision would be provided as advice during the task.
All participants were assigned to one of four cells in a 2 (regulatory orientation: promotion or prevention) × 2 (advice frame: eager or vigilant strategy) between-subjects design. The impact of advice on participants’ decisions was evaluated by the weight of advice (WOA). The WOA reflected how much a participant weighed the advice she/he received. Participants were naive to the task and the hypotheses under investigation.
Procedure
Upon arrival at the laboratory, participants were randomly divided into two groups. First, every participant was given two copies of material about searching for a job. The content of the two copies was identical, including job-seeking information and a decision balance sheet. All participants were told to carefully read and complete the decision balance sheet for themselves and answer two questions according to their rating scores regarding different jobs in the decision balance sheet. The first question asked about a job that was chosen (initial decision) and the second question asked about why he chose or gave up the job. For example, ‘I would choose a job as a middle school teacher, because this job is stable, with a better reputation, and I will have more free time with my family’ and ‘I am willing to give up work as a salesman, because this kind of work is unstable, with low income, long working hours and great stress’. After participants filled out the two copies of sheets about job decisions, one of the two copies was kept by the participants and the other was submitted to the experimenter. According to the job decision sheets submitted by participants, the experimenter recorded data regarding every participant's initial decision and reasons for choosing or giving up a job, to be used as advice for others.
Then, all participants were instructed to complete a pencil-and-paper maze task to prime their regulatory orientations (Friedman & Förster, Reference Friedman and Förster2001). One group completed the promotion-cue task, and the task depicted a cartoon mouse trapped inside a maze, but a piece of Swiss cheese was lying outside the maze. Participants needed to help the mouse find a way to get to the Swiss cheese. We posited that completion of this version of the maze task would activate both the semantic concept of ‘seeking nurturance’ and the procedural representation coding movement toward the desired end state of nurturance. The other group completed the prevention-cue task, which depicted a cartoon mouse trapped inside a maze, and an owl hovering above the maze ready to capture the mouse at any time. Participants were asked to help the mouse escape the maze. Completion of this version of the maze task was posited to activate the semantic concept of ‘seeking security’ as well as the procedural representation coding movement toward the desired end state of safety (Friedman & Förster, Reference Friedman and Förster2001). This type of maze task has been widely used in previous studies as a regulatory orientation induction (Lee, Keller, & Sternthal, Reference Lee, Keller and Sternthal2010). This task's validity has been demonstrated (see Pham & Avnet, Reference Pham and Avnet2004).
After all participants completed the pencil-and-paper maze task, the experimenter provided advice to every subject according to his/her initial decision and the design of the experimental variables. To avoid confusion between the advice frame and occupational choice, the opposite of the participant's initial occupational choice was provided, then the advice frame was set to eager or vigilant strategy. If the participant's initial decision was to choose A and lose B, then, under the promotion orientation condition, the experimenter gave advice about choosing B and emphasised the benefits of B (e.g., higher wage, treatment is better, more time with family) to fit a promotion orientation and eager strategy. In the unfit condition with a promotion orientation and vigilant strategy, the experimenter gave advice about choosing B but highlighted the drawbacks of choosing A (e.g., the wages are lower, lack of opportunity for promotion). Under the prevention orientation condition, the experimenter gave advice about choosing B, but highlighted the drawbacks of choosing A (e.g., the wages are lower, lack of opportunity for promotion) to fit a prevention orientation and vigilant strategy. In the unfit condition with a prevention orientation and eager strategy, the experimenter gave advice about choosing B and emphasised the benefits of B (e.g., the wages are higher, treatment is better, more time with family).
In contrast, if a participant's initial decision was to choose B and lose A, then, under the promotion orientation condition, the experimenter gave advice about choosing A and emphasised the benefits of A; or gave advice about choosing A but emphasised the drawbacks of choosing B. Under the prevention orientation condition, the experimenter gave advice about choosing A but emphasised the drawbacks of choosing B; or gave advice about choosing A and emphasised the benefits of A. Finally, participants were instructed to complete the vocational decision task again (final estimate) based on the advice they received.
Dependent Measures
To measure the degree to which participants used the advice they received, we used the WOA (WOA = |final estimate — initial estimate|/|advice-initial estimate|).
The WOA reflected how much a participant weighed the advice she/he received; this indicator has been previously applied in several studies (see Gino & Moore, Reference Gino and Moore2007; Yaniv, Reference Yaniv2004b). In the studies presented here, the initial estimate was the point estimate provided after participants understood the material about searching for a job, and the final estimate was the point estimate provided after participants received the decision balance sheet (including estimate scores about a job) and reasons for choosing the job. If the final estimate is equal to the initial estimate, then WOA is equivalent to zero, meaning that he/she did not change his/her initial decision after receiving the advice. In contrast, if there is a complete shift of the initial estimate towards the advice, then the final estimate will be equal to the received advice and WOA will be equal to 1. WOA values greater than 1 occur when the judge's final estimate overshoots the advice. In the present study, we followed the common procedure used in the literature (Yaniv, Reference Yaniv2004a, Reference Yaniv2004b) and opted to change values above 1 to 1.
Results and Discussion
The Analysis of WOA
In experiment 1, we changed values above 1 to 1 in 4% of the cases, and analysed WOA validity under different conditions. Table 1 shows the WOA descriptive statistic values in the combined conditions.
WOA Descriptive Statistic Values Across the Combined Conditions
A 2 (promotion or prevention) × 2 (eager or vigilant strategy) univariate analysis of variance (ANOVA) with mean WOA as the dependent variable revealed that the interaction between advice frame and regulatory orientation was significant, F(1, 98) = 9.749, p < .05, η2 = 0.09. A simple main effects analysis suggested that the WOA was higher when using an eager as opposed to a vigilant strategy within the prevention orientation condition, F(1, 49) = 5.679, p < .05, η2 = 0.104. Conversely, mean WOA for the eager strategy was lower than the vigilant strategy within the prevention orientation condition, F(1, 49) = 4.126, p < .05, η 2 = 0.078 (see Figure 1). However, the main effect of the regulatory orientation, F(1,98) = 0.516, p > .05, η2 = 0.005, and the advice frame, F(1,98) = 0.069, p > .05, η2 = 0.001, were not significant.
Interaction between advice strategy and regulatory orientation on the WOA.
The results suggest that regulatory fit plays a role in vocational decision-making processes. Promotion orientation and an eager strategy seem to be a natural fit, whereby people try to accept others’ advice to ensure positive outcomes. Meanwhile, prevention orientation and a vigilant strategy provided a fit, whereby individuals would be more apt to refuse advice to avoid negative consequences (Higgins, Reference Higgins2000). These results are in line with a previous study revealing that appeals presented in a ‘gain’ frame were more persuasive when the message was promotion focused; loss-framed appeals were more persuasive when the message was prevention focused (Lee & Aaker, Reference Lee and Aaker2004). However, what remains unclear is the nature of the regulatory fit effect on deciding to take advice. Cesario et al. (Reference Cesario, Grant and Higgins2004) believed that the regulatory fit effect was a ‘misattribution’; here, a correct attribution would reduce regulatory fit effects. Therefore experiment 2 was conducted to address this possibility and reveal the mechanism underlying how taking advice is influenced by the regulatory fit effect.
EXPERIMENT 2
Method
Participants and Design
Participants were 128 North-West Normal University undergraduates (62 men, 66 women) who were paid for their participation. The average participant age was 24.73 years old (SD = 2.90).
All participants were assigned to one of four cells in a 2 (orientation: promotion or prevention) × 2 (advice frame: eager or vigilant) × 2 (attribution type: attribution or non-attribution) between-subjects design. Participants were asked to complete a vocational decision-making task and submit their decision balance sheets and the answer sheets about choosing or giving up a certain job to the experimenter. WOA was, once again, the dependent variable.
Procedure
The pencil-and-paper maze task was used to induce regulatory orientation (Friedman & Förster, Reference Friedman and Förster2001). Participants were asked to write down five strategies or methods to attain their goal. For the eager strategy condition, participants were asked to write five strategies or methods that would ensure that their desires were smoothly attained. For the vigilant strategy condition, participants wrote down five strategies or methods that would help them avoid negative consequences (incorrect behaviour) so as to fulfill their duties and obligations. Thus, there were four types of fit between regulatory orientation and advice strategy: promotion-eager, promotion-vigilant, prevention-vigilant, and prevention-eager (Cesario et al., Reference Cesario, Grant and Higgins2004).
Participants were then assigned to an attribution or non-attribution condition. In the attribution condition, participants’ attention was drawn to the source of the regulatory fit experience before they received the message to reduce the confusion. Fitting groups were given the following instructions: ‘Research shows that people can experience positive feelings when using proper means to achieve a goal. Please pay attention to how you are feeling and then precisely estimate this feeling from 1 (little) to 7 (very deep).’ Participants in the non-fit condition were told: ‘Research shows that people can experience negative feelings when using improper means to achieve a goal. Please pay attention to any negative feelings and then precisely estimate this feeling from 1 (little) to 7 (very deep)’ (Cesario et al., Reference Cesario, Grant and Higgins2004). In the non-attribution condition, we did not tell participants to notice the source of their feelings but directly presented advice and asked participants to make a decision. If there were any differences between the attribution groups, we could conclude that these differences were the result of affective attributions.
Results and Discussion
In experiment 2, we changed values above 1 to 1 in 2% of the cases, and analysed WOA validity under different conditions. Table 2 shows the WOA descriptive statistics for the combined conditions.
WOA Descriptive Statistic Values in the Combined Conditions
An overall 2 (orientation: promotion or prevention) × 2 (advice frame: eager or vigilant) × 2 (attribution type: attribution or non-attribution) ANOVA on the mean WOA values showed that the interaction between orientation and advice frame, F(1,120) = 5.157, p < .05, η2 = 0.041, was significant. A simple main effects analysis suggested that WOA was higher when using an eager as opposed to a vigilant strategy within the prevention orientation condition, F(1,62) = 2.593, p < .05, η2 = 0.025. Conversely, mean WOA for the eager strategy was lower than the vigilant strategy within the prevention orientation condition, F(1,62) = 3.442, p < .05, η2 = 0.053 (see Figure 2). These results are consistent with the result of experiment 1.
Interaction between orientation and advice frame on the WOA.
There was also a significant interaction among orientation, advice frame and attribution types, F(1, 120) = 4.88, p < .05, η2 = 0.038. Simple main effects analysis suggested that there was no significant interaction between orientation and advice frame under the attribution condition, F(1, 62) = 0.03, p > .05, η2 = 0.001 (see Figure 3a). In contrast, the interaction between orientation and advice frame was significant under the non-attribution condition, F(1, 58) = 13.306, p < .05, η2 = 0.187, and WOA was higher when using an eager as opposed to a vigilant strategy within the promotion orientation condition, F(1, 29) = 8.517, p < .05, η2 = 0.227. Conversely, mean WOA for the eager strategy was lower than the vigilant strategy within the prevention orientation condition, F(1, 29) = 3.991, p < .05, η2 = 0.147 (see Figure 3b). These results showed that attribution could reduce the influence of the regulatory fit effect.
Interaction between orientation and advice frame on the WOA under the attribution condition.
Interaction between orientation and advice frame on the WOA under the non-attribution condition.
The main effects of orientation, F(1,120) = 0.297, p > .05, η2 = 0.002, advice frame, F(1,120) = 0.055, p > .05, η2 = 0.001, and attribution type, F(1,120) = 2.084, p > .05, η2 = 0.017, were not significant.
General Discussion
Since Sniezek and Buckley (Reference Sniezek and Buckley1995) proposed the JAS, researchers have been trying to more accurately explain advice-taking behaviour. Results have shown that several factors influence decision makers’ willingness to take advice, including egocentric biases (Krueger, Reference Krueger2003), advice costs (Gino, Reference Gino2008), and so on. However, the regulatory focus theory provides a new explanation for taking advice. That is, advice-taking behaviour may be affected by the regulatory fit effect (Polman, Reference Polman2012). With a higher regulatory fit, motivation toward goal pursuit is stronger (Brockner, Higgins, & Low, Reference Brockner, Higgins and Low2004; Higgins, Reference Higgins2000); meanwhile, individual goal pursuit is also affected by interpersonal regulatory fit (Righetti, Finkenauer, & Rusbult, Reference Righetti, Finkenauer and Rusbult2011). Thus, with the JAS, when the decision maker's regulatory focus and advisor's advice strategy fit, the decision maker is more apt to take the advice. Conversely, when the decision maker's regulatory focus and advisor's advice strategy are in conflict, the decision maker is less likely to take the advice. Furthermore, framing negative feedback affected receivers’ regulatory fit experience (Kung, Kim, Yang, & Cheng, Reference Kung, Kim, Yang and Cheng2016). Experiment 1 involved a vocational decision task and primed regulatory focus with the pencil-and-paper maze task. This was done to compare differences between participants’ WOAs during an eager strategy advice condition and a vigilant strategy advice condition using opposite choice. Results revealed a significant interaction between regulatory orientation and advice strategy. When job seekers are promoting orientation for vocation choice and advisors provide eager advice, or when job seekers are preventing orientation and advisors provide vigilant advice, there is a natural fit between regulatory orientation and strategy of providing advice. Under such conditions, job seekers are more inclined to take others’ advice. Experiment 2 also showed the interactions between orientations and advice frames was significant; under the non-attribution condition, the results were also consistent with the result of experiment 1. These results support our hypotheses and indicate that promotion orientation-eager and prevention orientation-vigilant strategies will increase the possibility of taking advice.
Why does regulatory fit lead job seekers to take others’ advice? This is probably related to the interdependence in Chinese culture. Unlike those of Westerners, East Asians’ decisions are more likely to be governed by a reciprocity norm (Shen, Wan, & Wyer, Reference Shen, Wan and Wyer2009). Therefore, decision makers are easily influenced by others and tend to take others’ advice that is consistent with their expectations. Moreover, it is a hedonic principle that people approach pleasure and avoid pain. For decision makers who are faced with uncertainty situations, it is probably related with the objective judgment for the outcome value. The essentiality nature of giving someone advice, Han Feizi pointed out, is such that we must gloss over others’ self-satisfaction and avoid or cover up others’ self-shamed things. Higgins (Reference Higgins2000) believed that regulatory fit can increase the value of the actions of decision makers. Emotion is an important factor that affects behavioural choices and judgments. It is logical to predict that participants would depend on their subjective feelings during this type of uncertain vocational decision context (Cesario et al., Reference Cesario, Grant and Higgins2004). However, the regulatory fit effect is probably derived from misattributions. Job seekers are more likely to believe that their vocational choices are valuable because of a fit between regulatory orientation and strategy of providing advice. However, if advisors have not fully considered every alternative, and only conformed to the job seekers’ expected orientation, then the value experience from fit may lead job seekers to make a wrong decision. Therefore, job seekers must be aware that they are taking advice as a result of the ‘right’ experience.
Cesario et al. (Reference Cesario, Grant and Higgins2004) tested for the role of the feeling right transfer mechanism. They found that when participants were aware of the correct source of their feeling, the regulatory fit effect on persuasion was eliminated. The objective of experiment 2 was to examine whether the regulatory fit effect would be reduced or even disappear under the attribution condition within a vocational decision-making task. The results showed a significant interaction among orientation, advice frame and attribution type, and the results are consistent with previous studies. There was a significant interaction between orientation and advice frame under the non-attribution condition; however, under the attribution condition, there was not a significant interaction between orientation and advice frame. These results showed that attribution indeed reduced the influence of the regulatory fit effect; however, the regulatory fit effect was not removed completely, because the interaction between orientation and advice frame was significant, and the mean WOA value in the fit condition was higher than in the no-fit condition. This may be because decision makers maintain consistency by giving greater weight to fit advice (Harries, Yaniv, & Harvey, Reference Harries, Yaniv and Harvey2004; Yaniv, Reference Yaniv1997) and by assigning greater weight to advice that is consistent with their own prior decision (Yaniv, Reference Yaniv2004a, Reference Yaniv2004b). It could also result because regulatory fit reduces job seekers’ need to put more cognitive effort into a task (Savadori, Van Swol, & Sniezek, Reference Savadori, Van Swol and Sniezek2001); therefore, job seekers’ attribution could not completely eliminate these effects of fitting.
Regulatory fit affects job seekers’ evaluation of the value of a vocational choice. The present study observed that regulatory fit increases the likelihood of taking advice, and correct attribution will reduce the regulatory fit effect on taking advice. It is useful to examine regulatory fit and attributions within an actual vocational decision-making setting and the process of providing advice to job seekers, or during the process of career counselling. According to the results of the present study, career counsellors should attempt to lead job seekers to be more rational when estimating the value of others’ advice. That is, career counsellors should guide job seekers to understand the regulatory fit effect and to explore the source of their feelings of ‘rightness’. For job seekers, they should maintain value neutrality or realise that the regulatory fit effect can promote taking advice; this will lead them to employ more rational and objective attitudes toward others’ advice. Additionally, if an advisor wishes to promote a decision maker's willingness to take advice, the advisors could prevent the decision maker from perceiving the actual source of their feelings of satisfaction.
The employment problem has become one of the most important issues in Chinese society; therefore, it is necessary to provide effective employment guidance for job seekers based on empirical evidence. The present study included different vocational decision-making conditions and found that job seekers’ advice-taking was influenced by the regulatory fit effects; however, this effect was likely to be weakened in the correct attribution condition. These results of the present study may aid actual employment guidance. While the participants were undergraduate students and not equivalent to all job seekers, they were typical job seekers. In Chinese society, there are various job-seeker groups; for example, college graduates, laid-off workers, and migrant workers; vocational decision-making behaviour and minds are different and these differences also exist among individuals. Moreover, as experiment 1 controlled the effect of occupational choice in an advisor's advice through using the opposite choice to avoid confusion between advice frame and occupational choice, then what would emerge when the support occupational choice is used? Further studies should explore the differences of regulatory fit effect under the support advice and opposite advice conditions. After all, practical vocational decisions tend to be more complex and unlike the manipulation of the experimental conditions. Specifically, there is a different regulatory focus when a job seeker makes a choice for him/herself versus others in the situation of interpersonal communication (Polman, Reference Polman2012). Therefore, differences between individuals should be considered in vocational consulting practice; other influential factors on advice taking, such as trust level, authority, type of advice given, and social culture should be considered. In future research, we will employ a case study method to explore the fit effect between regulation orientation and advice strategy to understand the influence of correct attribution on advice taking with the regulatory fitting.
Acknowledgments
This work was supported by the Northwest Normal University Young Teachers’ Scientific Research Capacity Promotion Project (Humanities and Social Sciences) (SKGG14010) and the National Social Science Fund for Distinguished Young Scholars of China (13CSH074).
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