To date, many researchers have investigated the structure of people's risk preferences. They focused on different decision domains like the financial, social, or health domains. The findings showed that, contrary to classical decision theories, risky decisions are affected by various factors like framing (e.g., Tversky and Kahneman, 1981), the source of the probability information (Hertwig et al., 2004), any previous experience (e.g., Sekścińska, 2015a), the decision maker's individual traits (e.g., Campbell et al., 2004), or even the activation of a different social role (Sekścińska et al., 2016). This signifies that decisions made in different domains (even when they are made concurrently) should not be described by the same and stable utility function. Slovic (1972) showed that people may be risk-averse in one domain and risk-seeking in another because the variance of returns is not a consistent predictor of risk-taking. Other researchers (Weber et al., 2002; Hanoch et al., 2006) have also showed that people are not consistently risk-averse or risk-seeking across all decision domains. Furthermore, Kusev et al. (2009) provided evidence that variation in the content of decisions leads to variation in financial risk preferences. Moreover, Vlaev et al. (2010) postulated that risk preferences may differ depending on the decision domain because the reference point may be different for various domains, for instance, monetary gambling vs. insurance. Vlaev et al. (2010) conducted a study in which they distinguished between monetary gambles, hazard losses, investment, insurance, pension provision, job salary change, and mortgage buying. The results of the study showed that risk attitude estimation is strongly dependent on the financial decision domain.

Kahneman and Tversky (1979) in their Prospect theory showed the function of value for gains and losses. They argued that this function is: (1) defined on deviations from the reference point; (2) concave for gains and convex for losses; and (3) steeper for losses than for gains (ibid.). These arguments lead to the conclusion that people may behave differently depending on the frame of the decision—gains or losses. The findings from studies presented by the authors of the Prospect theory (Kahneman and Tversky, 1979, 2000) followed by studies conducted by Kusev et al. (2009, 2011) and Vlaev et al. (2010), support the hypothesis that decisions under risk may vary depending on the frame of the decision: framed as either loss or gain.

Taking the findings from the aforementioned studies into account, it seems worthwhile investigating the mechanisms underlying risky financial decisions in order to distinguish between the propensity to make the decision in different domains (i.e., investment and gambling) and in different frames (i.e., gain vs. loss).

The factors that determine people's preferences for risks have been a subject of interest to researchers in the field of psychology for the last decades. Many findings have identified different psychological variables that influence risky financial decisions, for example, personality traits (e.g., narcissism—Foster et al., 2009, 2011; Sekścińska, 2015b; sensation-seeking and locus of control—Wong and Carducci, 2016), attitudes toward money (e.g., Sekścińska, 2015b), and affect-based motivation (e.g., Aspara and Tikkanen, 2011). In this paper, we would like to focus on one psychological factor that seems to be important in explaining people's financial risk preferences based on a theoretical framework as well as on a few studies conducted to date in this field. The focus will be on the promotion and prevention motivational system described by Higgins in the Regulatory Focus Theory (Higgins, 1997, 1998).

The Regulatory Focus Theory refers to the two distinct motivational systems that regulate all goal-directed behaviors (Higgins, 1997, 1998). Higgins (1997) distinguishes between promotion and prevention motivational systems (or regulatory focuses). The promotion motivational system is activated by growth needs; therefore, it is characterized as the motivation to attain growth and nurturance. The promotion system concentrates on achievements and aspirations and endeavors to bring one's actual self into alignment with one's ideal self. The promotion system concerns positive states, the pleasurable presence of positive outcomes or the painful lack of positive outcomes (e.g., gains vs. non-gains). Promotion-focused individuals use approach strategic means to achieve their goals. Moreover, the promotion system is inclined toward challenges and risks (Higgins, 1997, 1998; Higgins et al., 2001; Florack et al., 2013). In contrast, the prevention motivational system is activated by safety needs, therefore, it is connected with the motivation to achieve security. The prevention system concentrates on commitments, duty, fulfillment of responsibilities, protection and safety, and bringing one's actual self into alignment with one's ought self. The prevention system is concerned with negative states and the avoidance of negative outcomes; therefore, it is focused on the pleasurable absence of negative outcomes and the painful presence of negative outcomes (e.g., non-losses vs. losses). Prevention-focused individuals are prone to use avoidance strategic means to achieve their goals. Furthermore, the prevention system is connected with a preference for stability (Higgins, 1997, 1998; Higgins et al., 2001; Florack et al., 2013). The aforementioned characteristics of motivation systems lead to the conclusion that a promotion- and prevention-focus may lead to different decisions and the use of different decision-making strategies.

Higgins (1997; 1998; Higgins et al., 2001) postulated, on the one hand, that promotion and prevention motivational systems can be understood as a relatively stable, chronic disposition but, on the other, momentary situations may temporarily induce either a promotion or prevention focus. The chronic disposition might have been developed from an early age during socialization (Higgins et al., 2001; Lockwood et al., 2002) while the situational motivation could have been influenced by the characteristics of a task (Shah et al., 1998; Zhou and Pham, 2004), and the experiences of the individual in a present or preceding context (Higgins et al., 1994). Therefore, motivational systems can be treated as a chronic individual difference variable that can also be measured using the Regulatory Focus Questionnaire (Higgins et al., 2001). It can also be situationally induced using different priming tools like feedback messages or task instructions with gain/non-gain information (activation promotion motivation) or non-loss/loss information (activating prevention motivation; Förster et al., 2003), or by a task in which the participants are asked to generate reports of their hopes/aspirations and duties/obligations (Chernev, 2004). There is lack of studies on decision making that analyze the role of situationally induced promotion and prevention motivation concurrently that would take the individual's chronic motivational system into account. However, it seems worthwhile investigating the mechanisms underlying decision making, taking the two aspects of motivational orientation into account. Therefore, in our studies we investigated the role of both chronic and situationally induced motivation.

During the last decades, many studies on the chronic motivational systems and situational motivation have shown that the promotion and prevention motivational focuses described by Higgins may influence people's decisions. Previous studies have shown that when multiple pieces of information are available, promotion motivated individuals process different kinds of information than prevention motivated people (Chernev, 2004; Florack et al., 2010). Promotion motivated individuals are focused on positive information, while prevention motivation leads to an attentiveness to negative information (Keller and Bless, 2008). Moreover, individuals with a promotional system are more likely to have inner impulses and emotions while making their choices (Pham and Avnet, 2004, 2009; Florack et al., 2010; Greifeneder and Keller, 2012). Förster et al. (2003) showed that people with chronic or situationally-induced promotion motivation perform faster and less accurately in simple drawing tasks compared to participants with prevention motivation.

Recent studies proffer that the promotion and prevention motivational systems exert an important impact on judgments, decisions, choices, and behavior in consumer contexts (Florack et al., 2010; Rybarczyk-Adamska et al., 2012). The results showed that people prefer those characteristics and product types that are compatible with their motivational system (Chernev, 2004; Foerster and Werth, 2007). Moreover, people would rather select those products that were advertised in accordance to their motivational system (Aaker and Lee, 2001; Cesario et al., 2004). A series of studies (Herzenstein et al., 2007) showed that promotion-motivated people declare a higher propensity to buying novel, high-tech goods than prevention-motivated people. What is more, promotion-focused people own more newly launched high-tech products than prevention-focused consumers. Wu and Kao's (2011) studies have shown that promotion-motivated individuals tend to select a greater variety of products than prevention-motivated individuals when they are allowed to buy only one item at a time for each consumption occasion (choice sequence). However, when consumers are allowed to buy several items at a time for each following consumption occasion, the effect is exactly the opposite—prevention-motivated people select a greater variety of products. Other studies showed that prevention-motivated people rate the utilitarian characteristics of products higher than promotion-motivated individuals, while people who have a promotion system rate hedonistic product characteristics higher (Chernev, 2004; Zawadzka and Niesiobędzka, 2010; Roy and Ng, 2012).

Far fewer studies have been conducted on the relations between motivational orientation and financial behavior. To the best of our knowledge, there are only two studies that have investigated the role of promotion/prevention motivational systems in the savings area. The studies of Cho et al. (2014) showed that in accordance with the Regulatory Focus Theory, the promotion motivational system is connected with positive attitudes toward saving. The Regulatory Focus Theory distinguishes between two types of goals: promotion goals associated with safety needs and prevention goals related to nurturance needs (Higgins, 1987). Cho et al. (2014) found evidence that both prevention-related and promotion-related saving goals increased the likelihood of intentional saving, which seems to be contrary to the theoretical framework. Moreover, participants who were promotion motivated were less prone to save for prevention goals, while for prevention-motivated individuals the effect was exactly the opposite.

There are only a few studies on motivational systems and investment decisions. Zhou and Pham (2004) postulated that investors identify and categorize financial instruments using separate mental accounts in which the financial product may be seen as representative of promotion vs. prevention. In their study, investments in stocks and trading accounts were related to promotion motivation, while mutual fund or Individual Retirement Account (IRA) investments were connected to prevention motivation. Moreover, Zhou and Pham's (2004) study showed that people who make choices regarding promotion investment products are more sensitive to gains, while people who make financial decisions regarding promotion instruments are more sensitive to losses. Promotion motivation is linked with approaching growth from the status quo, while prevention motivation is connected with avoiding the aggravation of a status quo, therefore, Florack et al. (2013) postulated that, consequently, prevention-motivated people are supposed to use less risky and more conservative tactics in pursuing a goal, while individuals with a promotion focus tend to even follow high-risk opportunities. Levine et al. (2000) conducted a study that showed that in the nonfinancial context of decisions (participants indicated whether or not they have seen a nonsense word presented earlier during the study), situationally promotion-motivated people make riskier decisions than situationally prevention-motivated individuals. There is also one study in the financial context that showed that prevention-motivated people tend to invest in financial instruments with minimal risk and small returns because those instruments are rated high on the crucial dimension of safety (Florack and Hartmann, 2007). However, four experiments (Scholer et al., 2010) provided evidence that individuals in a state of loss (perception of the negative shift from the status quo) with prevention motivation (both chronic and situationally-induced) exhibited risk seeking as long as the risky option was the only way to return to the previous status quo. However, if a sure (safe) option is available and it can lead back to the reference point (previous status quo), prevention motivation predicts risk aversion. These findings are in accordance with the theoretical framework, while Higgins (2009) stated that people who are prevention-motivated are more sensitive to negative shifts from the status quo than to the positive ones, while the effect for promotion-motivated individuals is exactly the opposite. Chernev's (2004) studies confirmed Higgins' statement and showed that prevention-motivated individuals have a greater preference for the maintenance of the status quo than promotion-motivated ones. Moreover, the results of these studies showed that framing the decision as either a gain or loss does not reverse the above mentioned preference for status quo maintenance.

The results described in the literature provide evidence that the motivational systems (described in the Focus Regulatory Theory) are influencing people's decision making however they are not giving any direct indicators as to how the motivational systems might influence financial decisions (also the risky once), especially when the individual is making decisions that are crucial for everyday life, for instance, whether to spend money for consumption immediately or postpone this decision and to later save or invest this amount. Therefore, in our studies we investigated how promotion and prevention motivational systems influence the propensity to consume, save, and invest. The distinction between saving and investing seems to be crucial. Both financial decisions are connected to delayed gratification, however, investing unlike saving is associated with the probability of losing money (the level of riskiness depends on the type of financial instrument) and, at the same time, investing is connected more with the possibility of changing the financial status quo. Therefore, the question arises as to whether a higher promotion orientation would motivate people to invest (as a way to multiply their money), while a higher prevention orientation would result in a greater propensity to save money (as a way of maintaining the financial status quo), or perhaps promotion motivation would lead to a preference for saving over consumption (collecting more money and meeting growth needs), and investing over saving (multiplying the money already owned), when prevention-motivated people would prefer both saving and investing over consumption whilst only taking into account relatively safe financial instruments (to feel financially secure). Moreover, to date there is only one study indicating that motivational systems influence people's financial risk preferences (the aforementioned study of Florack and Hartmann, 2007). Therefore, in order to verify and complement these results, in our study we not only analyze the propensity to invest but also the risk preferences in the investment and gambling domains, taking into account both chronic and situationally induced motivation.

A two-way analysis of variance (ANOVA) was conducted to explore the difference in the chronic promotion and prevention system between participants opting for different categories of financial activity (consumption, saving and investing). A significant effect was observed for both the promotion [F_{(2, 1091)} = 13.52, p < 0.001, η² = 0.03, Table 1] and the prevention [F_{(2, 1091)} = 5.44, p < 0.005, η² = 0.02, Table 1] systems. Bonferroni corrected post-hoc comparisons show that the differences in the levels of the promotion system between all three groups were significant (investing vs. saving: p < 0.005; saving vs. consumption: p < 0.002; investing vs. consumption: p < 0.001). Significant differences in the levels of the prevention system were observed between consumption and saving (p < 0.005), and between consumption and investing (p < 0.01).

To verify the differences in the promotion and prevention systems between participants who chose sure and probable options in a risk propensity (gambling) task (both in the gain and loss frame), four t-test analyses were conducted. In the gain frame, significant differences were observed in the level of the promotion system [t₍₁₀₉₁₎ = 2.886, p < 0.005, Cohen's d = 0.23, Table 2], while the difference in the level of the prevention system was not significant [t₍₁₀₉₁₎ = 1.261; p > 0.05; Cohen's d = 0.10, Table 2]. Analogously, in the loss frame, significant differences were observed in the level of the promotion system [t₍₁₀₉₁₎ = 2.026, p < 0.05, Cohen's d = 0.15, Table 2], while the difference in the level of the prevention system was not significant [t₍₁₀₉₁₎ = 1033; p > 0.05; Cohen's d = 0.07, Table 2].

The results of Study 1 showed that a higher level of chronic promotion motivation was associated with the preference for investments over savings and savings over consumption. Moreover, those participants that tended to invest or save money rather than consume money had a higher level of chronic prevention motivation. In terms of risky financial decisions in both the gain and loss decision frame, a higher level of chronic promotion motivation was related to the preference for the non-sure option over the sure one. However, there were no significant differences in the level of chronic prevention motivation between participants who chose the sure and non-sure options.

To conduct the statistical analysis, the chronic promotion and chronic prevention variables were re-coded into binary variables (low vs. high level), the medians were split points.

A 2 (situational motivation) × 2 (chronic promotion level) × 2 (chronic prevention level) × 3 (financial choice category) mixed-design analysis of variance (ANOVA) was conducted. The main effect of situational motivation was not significant [F_{(1, 539)} = 0.12, p < 0.74, η² = 0.001, Table 3]. No significant main effects of chronic promotion [F_{(1, 539)} = 1.47, p < 0.23, η² = 0.003, Table 3] and chronic prevention [F_{(1, 539)} = 1.47, p < 0.23, η² = 0.003, Table 3] were observed either. A significant main effect of the financial choice category was found [F_{(1.68, 905.15)} = 92.09, p < 0.001, η² = 0.15, Table 3]. There were significant differences in the amount of money assigned between consumption and saving (p < 0.001), consumption and investing (p < 0.001), and saving and investing (p < 0.001).

The two-way interactions between the chronic promotion level and the financial choice category [F_{(1.68, 905.15)} = 2.04, p = 0.14, η² = 0.004], and between the chronic prevention level and the financial choice category [F_{(1.68, 905.15)} = 0.65, p = 0.50, η² = 0.001] were not significant. However, a significant interaction between the situational motivation and the financial choice category occurred [F_{(1.68, 905.15)} = 11.52, p < 0.001, η² = 0.02].

The three-way interactions between the chronic promotion, the chronic prevention, and the financial choice category [F_{(1.68, 905.15)} = 2.56, p < 0.07, η² = 0.01], as well as between the situational motivation, the chronic prevention, and the financial choice category [F_{(1.68, 905.15)} = 2.46, p < 0.08, η² = 0.01] showed a tendency toward significance. No significant three-way interaction between the situational motivation, the chronic prevention, and the financial choice category was observed [F_{(1.68, 905.15)} = 0.25, p < 0.74, η² < 0.01].

To correctly interpret the significant interaction between the situational motivation and the financial choice category pair-wise comparisons, using the Bonferroni correction for multiple comparisons were conducted. They showed that people whose promotion motivation was activated tended to spend significantly less money on consumption and saving and more money on investing than participants from the situational prevention group (consumption: p = 0.005; saving: p = 0.001; investing: p < 0.001, Table 4).

This was followed by 2 (situational motivation) × 2 (chronic promotion level) × 2 (chronic prevention level) × 3 (investment category) mixed-design analysis of variance (ANOVA). The main effect of the situational motivation was not significant [F_{(1, 539)} = 1.03, p = 0.31, η² = 0.002, Table 5]. No significant main effects of chronic promotion [F_{(1, 539)} = 1.03, p = 0.31, η² = 0.002, Table 5] and chronic prevention [F_{(1, 539)} = 1.03, p = 0.31, η² = 0.002, Table 5] were observed. A significant main effect of the investment category was found [F_{(1.87, 1009.89)} = 69.05, p < 0.001, η² = 0.11, Table 5]. There were significant differences in the amount of money assigned between bonds and balanced mutual funds (p < 0.001), balanced mutual funds and stocks (p < 0.001), and bonds and stocks (p < 0.001).

The interaction between the investment category and the chronic promotion level was significant [F_{(1.87, 1009.89)} = 2.88, p < 0.05, η² = 0.01], however, no significant interaction between the investment category and the chronic prevention level was observed [F_{(1.87, 1009.89)} = 1.10, p = 0.33 η² = 0.002]. An interaction effect between the situational motivation and the investment category was also observed [F_{(1.87, 1009.89)} = 9.75; p < 0.001, η² = 0.02].

The interaction effect between the chronic prevention level, the chronic promotion level, and the investment category was significant [F_{(1.87, 1009.89)} = 3.16, p < 0.05, η² = 0.01]. However, the interactions between the situational motivation, the investment category, and the chronic promotion level [F_{(1.87, 1009.89)} = 0.40, p = 0.66, η² < 0.01], as well as the chronic prevention level [F_{(1.87, 1009.89)} = 1.08, p = 0.34, η² = 0.01] were not significant.

Finally, the interaction between the chronic promotion level, the chronic prevention level, the situational motivation and the investment category was not statistically significant [F_{(1.87, 1009.89)} = 0.08, p = 0.91, η² < 0.01].

To correctly interpret the significant interactions between the situational motivation and the investment category, as well as between the chronic promotion level and the investment category the Bonferroni corrected post-hoc tests were conducted. The results showed that participants with a higher chronic promotional motivation were prone to spend significantly more money on balanced investment funds (p = 0.05) and less money on stocks (p = 0.001) compared to lower promotional people. No difference was observed between the high and low promotional groups in terms of their propensity to invest in bonds (p = 0.23). Moreover, Bonferroni corrected post-hoc comparisons revealed that participants with a situational promotional motivation were less prone to invest in bonds (p < 0.001) and demonstrated a greater tendency to invest in balanced investment funds (p < 0.002) than participants with situational prevention motivation. There was no significant difference in the propensity to invest in stocks between participants with situational promotion and prevention motivation (p = 0.16).

In order to perform follow-up tests, the data set was split according to the levels of variables involved in significant interaction between the chronic prevention level, the chronic promotion level, and the investment category. The set was first divided into the three investment category subsets (bonds, balanced investment funds, and stocks). Three 2 (chronic prevention level) by 2 (chronic promotion level) ANOVAs were conducted. The interaction between the chronic promotion and the prevention level was significant for the most risky category of investment instruments—stocks [F_{(1, 543)} = 5.69, p < 0.05, η² = 0.01]. No significant interaction was observed for bonds [F_{(1, 544)} = 2.20, p = 0.14, η² = 0.004] and balanced investment fund categories [F_{(1, 544)} = 0.50, p < 0.48, η² = 0.001]. To correctly interpret the obtained interactions, the Bonferroni corrected post-hoc tests were run. The results showed that participants who were low-prevention motivated were prone to invest less money in stocks than those who were high-prevention motivated as long as the low-prevention motivated person was also low-promotion motivated (p < 0.02).

This was followed by a 2 (situational motivation) × 2 (chronic promotion level) × 2 (chronic prevention level) analysis of variance (ANOVA) to analyze the differences in the riskiness of the created portfolios. The main effect of situational motivation was significant [F_{(1, 539)} = 11.16, p < 0.001, η² = 0.02, Table 6]. No significant principal effects of chronic promotion [F_{(1, 539)} = 2.87, p = 0.09, η² = 0.005, Table 6] and chronic prevention [F_{(1, 539)} = 1.84, p = 0.18, η² = 0.003, Table 6] were observed.

Furthermore, the interaction between chronic promotion and chronic prevention was significant [F_{(1, 539)} = 5.17, p < 0.05, η² = 0.01], while no significant interaction effects between situational motivation and both chronic levels of motivational systems [chronic promotion: F_{(1, 539)} = 0.68, p = 0.41, η² = 0.001; chronic prevention: F_{(1, 539)} = 1.60, p = 0.21, η² = 0.003] were observed. The interaction effect between the chronic prevention level, the chronic promotion level and situational motivation was not significant [F_{(1, 539)} = 0.13, p = 0.71, η² < 0.001].

To correctly interpret the obtained significant interaction between the chronic promotion and the chronic prevention motivational systems pair-wise comparisons, using the Bonferroni correction for multiple comparisons were run. The results showed that participants with a low chronic promotion system were prone to build significantly more risky portfolios than people with a high promotion system if their chronic prevention system was low (p < 0.005). No significant difference was observed between participants differing in terms of the chronic promotion system when their prevention system was high (p = 0.84).

To verify the differences in the promotion and the prevention systems and situationally induced motivation between participants who chose a sure or probable option in a risk propensity (gambling) task, two 2 (chronic promotion) × 2 (chronic prevention) × 2 (situational motivation) ANOVA's were conducted. One for the gain decision frame and one for the loss decision frame. At the beginning, we analyzed choices in a gain frame. The main effect of situational motivation was significant [F_{(1, 540)} = 5.78, p = 0.02, η² = ‘0.01, Table 7] as was the main effect of the chronic promotion motivation system [F_{(1, 540)} = 10.25, p < 0.001, η² = 0.02, Table 7]. No significant main effects of the chronic prevention motivational system was observed [F_{(1, 540)} = 2.81, p = 0.09, η² = 0.005, Table 7]. The interaction between chronic promotion and chronic prevention was not significant [F_{(1, 540)} = 0.29, p < 0.54, η² = 0.001]. The two-way interactions between situational motivation and chronic promotion [F_{(1, 540)} = 2.23, p < 0.14, η² = 0.004], and chronic prevention [F_{(1, 540)} = 0.45, p < 0.51, η² = 0.001] were also not significant. No significant three-way interaction between chronic promotion, chronic prevention, and situational motivation was observed [F_{(1, 540)} = 0.74, p < 0.39, η² = 0.001].

The choices in a loss frame were then analyzed. The main effect of situational motivation was significant [F_{(1, 540)} = 13.33, p < 0.001, η² = 0.03, Table 7], as was the main effect of the chronic promotion motivation system [F_{(1, 540)} = 6.35, p < 0.02, η² = 0.01, Table 7]. No significant main effects of the chronic prevention motivational system were observed [F_{(1, 540)} = 1.18, p < 0.28, η² = 0.002, Table 7]. The interactions between chronic promotion and chronic prevention [F_{(1, 540)} = 0.05, p = 0.82, η² < 0.001], and between situational motivation and chronic prevention [F_{(1, 540)} = 0.19, p < 0.67, η² < 0.001] were not significant. However, the interaction between situational motivation and chronic promotion [F_{(1, 540)} = 10.27, p < 0.001, η² = 0.02] was significant. No significant three-way interaction between chronic promotion, chronic prevention, and situational motivation was observed [F_{(1, 540)} = 0.28, p < 0.60, η² = 0.001]. In order to correctly interpret the obtained interaction effect, the data set was split according to the levels of the chronic promotion motivation system. Further χ² tests showed that situational promotion induced participants to choose the not-sure option significantly more often than people from the prevention experimental group when their chronic promotion level was high [χ(1)2 = 18.55, p < 0.001]. No significant difference was observed for people with low chronic promotion motivation [χ(1)2 = 0.82, p = 0.85].

The results of Study 2 showed that people with induced promotion motivation are prone to spend less money on current consumption and savings and more on investments than the participants from the prevention experimental group.

Regarding investment instrument preferences, the participants with higher chronic promotion motivation were prone to spend more money on balanced funds and less money on stocks than low-promotion motivated individuals. Low-chronic prevention motivated people were less prone to invest in stocks than high-chronic prevention motivated individuals as long as their promotion motivation level was also low. Moreover, the participants with induced promotion motivation were prone to invest less in bonds and more in balanced funds than the prevention experimental group.

Significant differences were also observed in terms of the riskiness of the created portfolio. Those participants with their promotion system activated built more risky portfolios than individuals with their prevention system induced. Moreover, the chronic level of motivational systems was also important. Participants with a low level of their promotion system built more risky portfolios than high-promotion motivated individuals as long as their prevention system was also low.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewers TZ, AC and the handling Editor declared their shared affiliation, and the handling Editor states that the process nevertheless met the standards of a fair and objective review.