Sensation seeking and automobile insurance coverage decisions: A moderated mediation model of gender and risk perception

Main Article Content

Shi-jie Jiang
Feiyun Xiang
Iris Yang
Cite this article:  Jiang, S.-j., Xiang, F., & Yang, I. (2023). Sensation seeking and automobile insurance coverage decisions: A moderated mediation model of gender and risk perception. Social Behavior and Personality: An international journal, 51(11), e12774.


Abstract
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We explored how and when sensation seeking influences consumers’ automobile insurance purchasing behavior by taking risk perception as a mediator and gender as a moderator. We collected data from 413 participants who purchased automobile liability insurance in China and employed the SPSS PROCESS macro for moderated mediation analysis. Our results revealed that sensation seeking had an indirect effect on insurance coverage purchasing behavior through risk perception, and that this mediating effect was moderated by gender. Men with higher (vs. lower) sensation seeking were more likely to have a lower risk perception and tended to purchase less insurance coverage. However, the indirect effect of sensation seeking was not significant among women. Our findings provide insight into the psychological mechanisms that influence consumers’ automobile insurance purchasing behavior.

Theoretically, a rational customer should purchase actuarially fair insurance coverage, which is equivalent to an expected loss (Doherty & Schlesinger, 1990). However, an individual’s insurance decision rarely follows the traditional rule of insurance purchasing in maximizing expected utility (Kunreuther et al., 2013). To explain insurance purchasing behaviors, psychological theories have been adopted, such as sensation seeking (Golden et al., 2016; Wong & Carducci, 1991) and risk perception (Li et al., 2021; Rosi et al., 2021). Gender differences in financial decision making, including insurance coverage decisions, have also been explored in some studies (e.g., Powell & Ansic, 1997), and gender differences have been found in personality traits, such as sensation seeking (Zuckerman et al., 1978). However, there has been no comprehensive study of the joint impact of sensation seeking, risk perception, and gender differences on insurance purchasing behavior, especially with regard to automobile voluntary liability insurance. Therefore, this study explored this impact by employing a moderated mediation framework with risk perception as a mediator and gender as a moderator.

Unlike automobile collision insurance, where the coverage depends on the value of the consumer’s car, automobile voluntary liability insurance estimates the amount of loss that the consumer will be obligated to pay to the victims. Since potential automobile liability exposure is theoretically unlimited, there is no easy way to determine how much liability insurance a consumer should purchase. This makes it difficult to assess the severity of the potential loss because the exact amount that must be paid if the driver is liable for the accident is unknown (Hamilton et al., 2002). Hence, we believed that consumers’ individual differences would have an impact on coverage decisions for this type of insurance policy.

This study contributes to the insurance literature in several ways: First, previous studies have addressed the impact of sensation seeking on insurance purchasing behavior (Wong & Carducci, 1991). However, we believe that the amount of insurance coverage individuals prefer to pay will play a more crucial role in the field of insurance marketing (Holtan, 2001). Second, psychological studies on insurance purchasing behavior have placed substantial emphasis on catastrophic risks, such as flooding (Botzen et al., 2013). Instead, we considered insurance coverage decisions for everyday risks that people may encounter when driving. Finally, we proposed a moderated mediation framework to examine the roles of risk perception and gender differences in the link between sensation seeking and insurance coverage. This mechanism informs the impact of individual differences on insurance purchasing, which will help to enrich the insurance literature. 

According to Zuckerman (1994), sensation seeking is defined by the search for experiences and feelings that are “varied, novel, complex, and intense, [and by the readiness to] take physical, social, legal, and financial risks for the sake of such experiences” (p. 27). Sensation seeking has been used to explain risky behavior in daily financial decision-making procedures, such as insurance purchasing (Wong & Carducci, 1991), credit card maxing out, and difficulty with paying bills (Worthy et al., 2010).

Sensation seeking affects people’s purchase decision making regarding automobile insurance for three reasons: First, high sensation seekers see themselves as less at risk and less likely to be involved in traffic accidents because they tend to be unrealistically optimistic (Horvath & Zuckerman, 1993; Rosenbloom, 2003). Second, high (vs. low) sensation seekers enjoy the returns brought by financial risk taking (Worthy et al., 2010), value money (Sjöberg & Engelberg, 2009), and allocate fewer attentional resources to negative outcomes (Cservenka et al., 2013). Finally, high sensation seekers have a high tolerance for financial risk since they often take risks to seek thrills (Rabbani et al., 2019; Wong & Carducci, 2015). Therefore, we believed high sensation seekers would tend to purchase lower insurance coverage than would low sensation seekers.

Moreover, previous studies have shown that risk perception affects people’s insurance decision making. Kunreuther (2006) indicated that people with low levels of risk perception are not worried about losses, so they are unwilling to buy insurance; in contrast, when people’s risk perception increases, their interest in buying insurance will also rise. The lower the risk perception, the less demand for insurance (Zhou-Richter et al., 2010). In this study we anticipated that sensation seeking and risk perception would be interdependent in affecting risk taking. Sensation seeking affects people’s financial risk-taking behavior through risk perception (Zhang et al., 2016), so that high sensation seekers tend to possess low perceptions of risk (Zuckerman, 1979). If an individual’s risk perception exceeds their maximum tolerable level, they will take measures to avoid related risks (Dowling, 1986). Therefore, low sensation seekers may perceive that a higher probability of future financial losses exceeds their maximum level of tolerance. Consequently, they will be willing to purchase a high amount of automobile insurance to reduce the risk of future losses.

The effect of gender differences on financial risk taking has been supported in many studies (see, e.g., Bannier & Neubert, 2016; Lemaster & Strough, 2014). Powell and Ansic (1997) found that women tend to select the widest insurance coverage, while men prefer the lowest cost cover. Men also tend to score higher than women do on sensation-seeking measures (e.g., McDaniel & Zuckerman, 2003; Zuckerman, 1994), which leads to gender differences in the same decision-making situation, such as whether to engage in working-holiday tourism and traffic violations (e.g., Meng & Han, 2018; Oppenheim et al., 2016). Therefore, people of different genders who possess the same sensation-seeking score may make different decisions about purchasing automobile insurance.

In summary, we anticipated that risk perception would mediate the relationship between sensation seeking and insurance coverage, and that gender would moderate the paths from sensation seeking to insurance coverage, and from sensation seeking to risk perception (see Figure 1). Our hypothesis was as follows: Gender will moderate the strength of the negative indirect effect of sensation seeking on the chosen amount of the automobile liability insurance coverage through the mediator of risk perception, such that the mediating effect is stronger for men than for women.

 

Table/Figure

Figure 1. Research Model

Method

Participants

Participants had purchased automobile insurance and paid the insurance premium for the coming year from PING AN Insurance (Group) Company of China or China Life Insurance (Group) Company. We recruited 450 participants and received valid responses from 413, of whom 226 (54.7%) were men and 187 (45.3%) were women. Their ages ranged between 18 and 55 years (M = 30.78, SD = 7.79). In terms of educational attainment, 301 participants (72.9%) had received a bachelor’s degree or higher, and the rest had a lower level of education. For occupation, 193 (46.7%) were office and administrative staff and 220 (53.3%) were field staff. The median annual income was CNY 75,000 (USD 11,610). Among the participants, 42.4% had a driving history of more than 5 years. The mean annual premium paid for automobile liability insurance was CNY 1,784.36 (USD 276.22) and the standard deviation was CNY 1,538.13 (USD 238.10).

Procedure

The participants were recruited by a survey company in China between February 1 and March 31, 2022. They were assured that their information and responses to the survey would be kept confidential and used only for this study. The participants were also informed that there were no right or wrong answers and that they could stop the survey at any time. All participants gave informed consent before beginning the survey and were allocated 20 minutes to fill it in online. A retail gift voucher of CNY 20 (USD 3.10) was given to those who completed the questionnaire.

Measures

The survey contained four parts: (1) participants’ demographic information, (2) a risk-perception scale, (3) a sensation-seeking scale, and (4) a question asking about the purchase amount of automobile liability insurance coverage for the coming year. 

The risk perception measure, adapted from Knuth et al. (2015), asks “What percent chance do you think there is that you will have a traffic accident in the next year? Please write the number in the parentheses: (_%).” The mean and standard deviation of risk perception scores were 18.78% and 9.42%.

The Chinese version (Wang et al., 2000) of the sensation-seeking measure (Zuckerman et al., 1978) consists of 40 items. A sample item is “I like to have new and exciting experiences and sensations even if they are a little frightening, unconventional, or illegal.” One point is awarded for answering “yes” and zero points are allocated for “no.” The scale exhibited good internal consistency in this study (α = .80).

Participants also answered the question “What is the amount of automobile liability insurance coverage you purchased for the coming year?” The insured amount ranged from CNY 100,000 (USD 15,480) to CNY 3,000,000 (USD 464,400), with a mean of CNY 833,777 (USD 129,068) and a standard deviation of CNY 350,610 (USD 54,274).

Results

Correlation Analysis

According to the bivariate correlation analysis results in Table 1, sensation seeking was negatively correlated with insurance coverage and risk perception. Further, risk perception was positively correlated with insurance coverage. Finally, gender was negatively correlated with sensation seeking, meaning men received higher sensation-seeking scores than women did.

Table 1. Bivariate Correlation Analysis Results

Table/Figure
Note. IC = the amount of liability insurance coverage; Gen = gender (0 = men, 1 = women); Edu = level of education (0 = junior college graduate or lower, 1 = bachelor’s degree or higher); Occ = occupation (0 = internal staff, 1 = field staff); Inc = average annual income; Dri = driving years; Pre = automobile liability insurance premium.
* p < .05. ** p < .01.

Table 1 also includes the correlation coefficients between the four main variables (sensation seeking, risk perception, insurance coverage, and gender) and control variables. Sensation seeking was negatively related to age and the premium of automobile liability insurance. The premium of automobile liability insurance was positively related to insurance coverage, since insurance companies calculate the premium partly based on the amount of insurance coverage chosen by consumers. Risk perception was positively related to the premium of automobile liability insurance. Average income level was positively related to risk perception and insurance coverage. In addition, the correlations between the four main variables remained significant after adjusting for other confounding factors, such as age and level of education. The detailed results are available upon request.

Moderated Mediation Effects Testing

We used Model 8 of the PROCESS macro to examine the proposed model. The results presented in Table 2 suggest that the proposed model fit the data reasonably well.

Table 2. Test Results of Moderated Mediation Effect

Table/Figure
Note. SS = sensation seeking; RP = risk perception; IC = the amount of liability insurance coverage; Edu = education; Occ = occupation; Inc = average annual income; Dri = driving years; Ln(Pre) = logarithm of automobile insurance premium; DV = dependent variable; CI = confidence interval; LL = lower limit; UL = upper limit.
* p < .05. ** p < .01.

Although the results of the dependent variable model in Table 2 show that the interaction of gender × sensation seeking was nonsignificant, the indirect effects of sensation seeking on insurance coverage through risk perception may still be moderated by gender because this test did not quantify the relationship between gender and indirect effects (Chang et al., 2017). As suggested by Hayes (2022), the significance of moderated indirect effects should be based on the index of moderated mediation. As shown at the bottom of Table 2, the 95% bias-corrected bootstrapped confidence interval of the index of moderated mediation did not contain 0, suggesting that the indirect effect of sensation seeking on insurance coverage through risk perception was moderated by gender.

The significant moderation effects were further examined by analyzing the indirect effect of sensation seeking on insurance coverage for different genders (see Table 3). We also examined whether the direct effects were moderated by gender. According to the results in Table 3, sensation seeking influenced individuals’ insurance coverage choices only among men, regardless of whether the association was mediated by risk perception. However, this influence was not significant among women.

Table 3. Conditional Direct and Indirect Effects

Table/Figure
Note. SS = sensation seeking; IC = the amount of liability insurance coverage; RP = risk perception; CI = confidence interval; LL = lower limit; UL = upper limit.
* p < .05. ** p < .01.

We also controlled for age, level of education, annual household income, occupation, and driving years. In general, automobile insurance premiums had a positive relationship with risk perception and insurance coverage, whereas annual household income had a positive relationship only with insurance coverage.

Discussion


Our study analyzed how consumers’ individual differences influence their insurance purchasing behavior. Specifically, we examined the mediating role of risk perception and the moderating role of gender in the relationship between sensation seeking and automobile liability insurance coverage. Supporting our hypothesis, we found that women’s insurance coverage decisions do not fluctuate with their sensation-seeking score (a nonsignificant conditional direct and indirect effect), whereas men tend to purchase less automobile insurance coverage when they have higher sensation-seeking scores (a significant negative conditional direct and indirect effect). According to DeJoy (1992), men have a greater optimism bias than women do. When deciding whether to purchase automobile liability insurance, men, as sensation seekers, perceive a lower risk of car accidents so they tend to purchase lower insurance coverage. For women, this phenomenon is not observed due to the absence of an optimism bias. This result is consistent with that of Reniers et al. (2016), who found that, compared to women, men perceive behavioral risk as less risky, report taking more risks, and are less sensitive to negative outcomes.

In terms of practical implication of our findings, in past years insurance companies have tried to implement market segmentation based on demographic variables, consumers’ purchasing behavior, and geographic location. Our results indicate that insurers should apply psychographic segmentation through the division of individuals’ values, personalities, and attitudes, in order to help consumers make appropriate insurance purchasing decisions.

Our study has several limitations. First, we focused on only one insurance product. Other types of insurance policies, such as homeowners’ insurance and life insurance, could also be tested to understand the underlying psychological processes of insurance product purchasing decisions. Second, since our participants were clients of a Chinese insurance company, the results may apply only to people with a Chinese cultural background. According to Hayakawa et al. (2000), automobile insurance purchasing decisions vary across countries. Thus, we recommend that future studies include participants from different cultures and examine whether the findings vary. Last, this study used the sensation-seeking personality trait to examine insurance purchasing behavior. A review of personality research in insurance contexts (see, e.g., Botzen et al., 2013) suggests that other personality concepts (e.g., regulatory focus) could be considered in future work.

References

Bannier, C. E., & Neubert, M. (2016). Gender differences in financial risk taking: The role of financial literacy and risk tolerance. Economics Letters, 145, 130–135.
 
Botzen, W. J. W., de Boer, J., & Terpstra, T. (2013). Framing of risk and preferences for annual and multi-year flood insurance. Journal of Economic Psychology, 39, 357–375.
 
Chang, L.-Y., Wu, S.-Y., Chiang, C.-E., & Tsai, P.-S. (2017). Depression and self-care maintenance in patients with heart failure: A moderated mediation model of self-care confidence and resilience. European Journal of Cardiovascular Nursing, 16(5), 435–443.
 
Cservenka, A., Herting, M. M., Mackiewicz Seghete, K. L., Hudson, K. A., & Nagel, B. J. (2013). High and low sensation seeking adolescents show distinct patterns of brain activity during reward processing. NeuroImage, 66, 184–193.
 
DeJoy, D. M. (1992). An examination of gender differences in traffic accident risk perception. Accident Analysis & Prevention, 24(3), 237–246.
 
Doherty, N. A., & Schlesinger, H. (1990). Rational insurance purchasing: Consideration of contract nonperformance. The Quarterly Journal of Economics, 105(1), 243–253.
 
Dowling, G. R. (1986). Perceived risks: The concept and its measurement. Psychology & Marketing, 3(3), 193–210.
 
Golden, L. L., Brockett, P. L., Ai, J., & Kellison, B. (2016). Empirical evidence on the use of credit scoring for predicting insurance losses with psycho-social and biochemical explanations. North American Actuarial Journal, 20(3), 233–251.
 
Hamilton, K. L., Ferguson, C. L., & Cook, M. A. (2002). Personal risk management and property-liability insurance. American Institute for Chartered Property Casualty Underwriters.
 
Hayakawa, H., Fischbeck, P. S., & Fischhoff, B. (2000). Traffic accident statistics and risk perceptions in Japan and the United States. Accident Analysis & Prevention, 32(6), 827−835.
 
Hayes, A. F. (2022). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach (3rd ed.). The Guilford Press.
 
Holtan, J. (2001). Optimal insurance coverage under bonus-malus contracts. ASTIN Bulletin: The Journal of the International Actuarial Association, 31(1), 175–186.
 
Horvath, P., & Zuckerman, M. (1993). Sensation seeking, risk appraisal, and risky behavior. Personality and Individual Differences, 14(1), 41–52.
 
Knuth, D., Kehl, D., Hulse, L., Spangenberg, L., Brähler, E., & Schmidt, S. (2015). Risk perception and emergency experience: Comparing a representative German sample with German emergency survivors. Journal of Risk Research, 18(5), 581–601.
 
Kunreuther, H. C. (2006). Disaster mitigation and insurance: Learning from Katrina. The Annals of the American Academy of Political and Social Science, 604(1), 208–227.
 
Kunreuther, H. C., Pauly, M. V., & McMorrow, S. (2013). Insurance & behavioral economics: Improving decisions in the most misunderstood industry. Cambridge University Press.
 
Lemaster, P., & Strough, J. (2014). Beyond Mars and Venus: Understanding gender differences in financial risk tolerance. Journal of Economic Psychology, 42, 148–160.
 
Li, Z., Man, S. S., Chan, A. H. S., & Zhu, J. (2021). Integration of theory of planned behavior, sensation seeking, and risk perception to explain the risky driving behavior of truck drivers. Sustainability, 13(9), Article 5214.
 
McDaniel, S. R., & Zuckerman, M. (2003). The relationship of impulsive sensation seeking and gender to interest and participation in gambling activities. Personality and Individual Differences, 35(6), 1385–1400.
 
Meng, B., & Han, H. (2018). Investigating individuals’ decision formation in working-holiday tourism: The role of sensation-seeking and gender. Journal of Travel & Tourism Marketing, 35(8), 973–987.
 
Oppenheim, I., Oron-Gilad, T., Parmet, Y., & Shinar, D. (2016). Can traffic violations be traced to gender-role, sensation seeking, demographics and driving exposure? Transportation Research Part F: Traffic Psychology and Behaviour, 43, 387–395.
 
Powell, M., & Ansic, D. (1997). Gender differences in risk behaviour in financial decision-making: An experimental analysis. Journal of Economic Psychology, 18(6), 605–628.
 
Rabbani, A. G., Yao, Z., & Wang, C. (2019). Does personality predict financial risk tolerance of pre-retiree baby boomers? Journal of Behavioral and Experimental Finance, 23, 124–132.
 
Reniers, R. L. E. P., Murphy, L., Lin, A., Bartolomé, S. P., & Wood, S. J. (2016). Risk perception and risk-taking behaviour during adolescence: The influence of personality and gender. PLoS ONE, 11(4), Article e0153842.
 
Rosenbloom, T. (2003). Risk evaluation and risky behavior of high and low sensation seekers. Social Behavior and Personality: An international journal, 31(4), 375–386.
 
Rosi, A., van Vugt, F. T., Lecce, S., Ceccato, I., Vallarino, M., Rapisarda, F., … Cavallini, E. (2021). Risk perception in a real-world situation (COVID-19): How it changes from 18 to 87 years old. Frontiers in Psychology, 12, Article e646558.
 
Sjöberg, L., & Engelberg, E. (2009). Attitudes to economic risk taking, sensation seeking and values of business students specializing in finance. Journal of Behavioral Finance, 10(1), 33–43.
 
Wang, W., Wu, Y.-X., Peng, Z.-G., Lu, S.-W., Wang, G.-P., Fu, X.-M., & Wang, Y.-H. (2000). Test of sensation seeking in a Chinese sample. Personality and Individual Differences, 28(1), 169–179.
 
Wong, A., & Carducci, B. J. (1991). Sensation seeking and financial risk taking in everyday money matters. Journal of Business and Psychology, 5, 525–530.
 
Wong, A., & Carducci, B. (2015). Do sensation seeking, control orientation, ambiguity, and dishonesty traits affect financial risk tolerance? Managerial Finance, 42(1), 34–41.
 
Worthy, S. L., Jonkman, J., & Blinn-Pike, L. (2010). Sensation-seeking, risk-taking, and problematic financial behaviors of college students. Journal of Family and Economic Issues, 31, 161–170.
 
Zhang, L., Zhang, C., & Shang, L. (2016). Sensation-seeking and domain-specific risk-taking behavior among adolescents: Risk perceptions and expected benefits as mediators. Personality and Individual Differences, 101, 299–305.
 
Zhou-Richter, T., Browne, M. J., & Gründl, H. (2010). Don’t they care? Or, are they just unaware? Risk perception and the demand for long-term care insurance. The Journal of Risk and Insurance, 77(4), 715–747.
 
Zuckerman, M. (1979). Sensation seeking beyond the optimum level of arousal. Lawrence Erlbaum Associates.
 
Zuckerman, M. (1994). Behavioral expressions and biosocial bases of sensation seeking. Cambridge University Press.
 
Zuckerman, M., Eysenck, S. B., & Eysenck, H. J. (1978). Sensation seeking in England and America: Cross-cultural, age and sex comparisons. Journal of Consulting and Clinical Psychology, 46(1), 139–149.

Bannier, C. E., & Neubert, M. (2016). Gender differences in financial risk taking: The role of financial literacy and risk tolerance. Economics Letters, 145, 130–135.
 
Botzen, W. J. W., de Boer, J., & Terpstra, T. (2013). Framing of risk and preferences for annual and multi-year flood insurance. Journal of Economic Psychology, 39, 357–375.
 
Chang, L.-Y., Wu, S.-Y., Chiang, C.-E., & Tsai, P.-S. (2017). Depression and self-care maintenance in patients with heart failure: A moderated mediation model of self-care confidence and resilience. European Journal of Cardiovascular Nursing, 16(5), 435–443.
 
Cservenka, A., Herting, M. M., Mackiewicz Seghete, K. L., Hudson, K. A., & Nagel, B. J. (2013). High and low sensation seeking adolescents show distinct patterns of brain activity during reward processing. NeuroImage, 66, 184–193.
 
DeJoy, D. M. (1992). An examination of gender differences in traffic accident risk perception. Accident Analysis & Prevention, 24(3), 237–246.
 
Doherty, N. A., & Schlesinger, H. (1990). Rational insurance purchasing: Consideration of contract nonperformance. The Quarterly Journal of Economics, 105(1), 243–253.
 
Dowling, G. R. (1986). Perceived risks: The concept and its measurement. Psychology & Marketing, 3(3), 193–210.
 
Golden, L. L., Brockett, P. L., Ai, J., & Kellison, B. (2016). Empirical evidence on the use of credit scoring for predicting insurance losses with psycho-social and biochemical explanations. North American Actuarial Journal, 20(3), 233–251.
 
Hamilton, K. L., Ferguson, C. L., & Cook, M. A. (2002). Personal risk management and property-liability insurance. American Institute for Chartered Property Casualty Underwriters.
 
Hayakawa, H., Fischbeck, P. S., & Fischhoff, B. (2000). Traffic accident statistics and risk perceptions in Japan and the United States. Accident Analysis & Prevention, 32(6), 827−835.
 
Hayes, A. F. (2022). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach (3rd ed.). The Guilford Press.
 
Holtan, J. (2001). Optimal insurance coverage under bonus-malus contracts. ASTIN Bulletin: The Journal of the International Actuarial Association, 31(1), 175–186.
 
Horvath, P., & Zuckerman, M. (1993). Sensation seeking, risk appraisal, and risky behavior. Personality and Individual Differences, 14(1), 41–52.
 
Knuth, D., Kehl, D., Hulse, L., Spangenberg, L., Brähler, E., & Schmidt, S. (2015). Risk perception and emergency experience: Comparing a representative German sample with German emergency survivors. Journal of Risk Research, 18(5), 581–601.
 
Kunreuther, H. C. (2006). Disaster mitigation and insurance: Learning from Katrina. The Annals of the American Academy of Political and Social Science, 604(1), 208–227.
 
Kunreuther, H. C., Pauly, M. V., & McMorrow, S. (2013). Insurance & behavioral economics: Improving decisions in the most misunderstood industry. Cambridge University Press.
 
Lemaster, P., & Strough, J. (2014). Beyond Mars and Venus: Understanding gender differences in financial risk tolerance. Journal of Economic Psychology, 42, 148–160.
 
Li, Z., Man, S. S., Chan, A. H. S., & Zhu, J. (2021). Integration of theory of planned behavior, sensation seeking, and risk perception to explain the risky driving behavior of truck drivers. Sustainability, 13(9), Article 5214.
 
McDaniel, S. R., & Zuckerman, M. (2003). The relationship of impulsive sensation seeking and gender to interest and participation in gambling activities. Personality and Individual Differences, 35(6), 1385–1400.
 
Meng, B., & Han, H. (2018). Investigating individuals’ decision formation in working-holiday tourism: The role of sensation-seeking and gender. Journal of Travel & Tourism Marketing, 35(8), 973–987.
 
Oppenheim, I., Oron-Gilad, T., Parmet, Y., & Shinar, D. (2016). Can traffic violations be traced to gender-role, sensation seeking, demographics and driving exposure? Transportation Research Part F: Traffic Psychology and Behaviour, 43, 387–395.
 
Powell, M., & Ansic, D. (1997). Gender differences in risk behaviour in financial decision-making: An experimental analysis. Journal of Economic Psychology, 18(6), 605–628.
 
Rabbani, A. G., Yao, Z., & Wang, C. (2019). Does personality predict financial risk tolerance of pre-retiree baby boomers? Journal of Behavioral and Experimental Finance, 23, 124–132.
 
Reniers, R. L. E. P., Murphy, L., Lin, A., Bartolomé, S. P., & Wood, S. J. (2016). Risk perception and risk-taking behaviour during adolescence: The influence of personality and gender. PLoS ONE, 11(4), Article e0153842.
 
Rosenbloom, T. (2003). Risk evaluation and risky behavior of high and low sensation seekers. Social Behavior and Personality: An international journal, 31(4), 375–386.
 
Rosi, A., van Vugt, F. T., Lecce, S., Ceccato, I., Vallarino, M., Rapisarda, F., … Cavallini, E. (2021). Risk perception in a real-world situation (COVID-19): How it changes from 18 to 87 years old. Frontiers in Psychology, 12, Article e646558.
 
Sjöberg, L., & Engelberg, E. (2009). Attitudes to economic risk taking, sensation seeking and values of business students specializing in finance. Journal of Behavioral Finance, 10(1), 33–43.
 
Wang, W., Wu, Y.-X., Peng, Z.-G., Lu, S.-W., Wang, G.-P., Fu, X.-M., & Wang, Y.-H. (2000). Test of sensation seeking in a Chinese sample. Personality and Individual Differences, 28(1), 169–179.
 
Wong, A., & Carducci, B. J. (1991). Sensation seeking and financial risk taking in everyday money matters. Journal of Business and Psychology, 5, 525–530.
 
Wong, A., & Carducci, B. (2015). Do sensation seeking, control orientation, ambiguity, and dishonesty traits affect financial risk tolerance? Managerial Finance, 42(1), 34–41.
 
Worthy, S. L., Jonkman, J., & Blinn-Pike, L. (2010). Sensation-seeking, risk-taking, and problematic financial behaviors of college students. Journal of Family and Economic Issues, 31, 161–170.
 
Zhang, L., Zhang, C., & Shang, L. (2016). Sensation-seeking and domain-specific risk-taking behavior among adolescents: Risk perceptions and expected benefits as mediators. Personality and Individual Differences, 101, 299–305.
 
Zhou-Richter, T., Browne, M. J., & Gründl, H. (2010). Don’t they care? Or, are they just unaware? Risk perception and the demand for long-term care insurance. The Journal of Risk and Insurance, 77(4), 715–747.
 
Zuckerman, M. (1979). Sensation seeking beyond the optimum level of arousal. Lawrence Erlbaum Associates.
 
Zuckerman, M. (1994). Behavioral expressions and biosocial bases of sensation seeking. Cambridge University Press.
 
Zuckerman, M., Eysenck, S. B., & Eysenck, H. J. (1978). Sensation seeking in England and America: Cross-cultural, age and sex comparisons. Journal of Consulting and Clinical Psychology, 46(1), 139–149.

Table/Figure

Figure 1. Research Model


Table 1. Bivariate Correlation Analysis Results

Table/Figure
Note. IC = the amount of liability insurance coverage; Gen = gender (0 = men, 1 = women); Edu = level of education (0 = junior college graduate or lower, 1 = bachelor’s degree or higher); Occ = occupation (0 = internal staff, 1 = field staff); Inc = average annual income; Dri = driving years; Pre = automobile liability insurance premium.
* p < .05. ** p < .01.

Table 2. Test Results of Moderated Mediation Effect

Table/Figure
Note. SS = sensation seeking; RP = risk perception; IC = the amount of liability insurance coverage; Edu = education; Occ = occupation; Inc = average annual income; Dri = driving years; Ln(Pre) = logarithm of automobile insurance premium; DV = dependent variable; CI = confidence interval; LL = lower limit; UL = upper limit.
* p < .05. ** p < .01.

Table 3. Conditional Direct and Indirect Effects

Table/Figure
Note. SS = sensation seeking; IC = the amount of liability insurance coverage; RP = risk perception; CI = confidence interval; LL = lower limit; UL = upper limit.
* p < .05. ** p < .01.

This work was financially supported by the Key Talents Project of Guangzhou University (RZ2021011) and the Guangzhou Basic Research Program Jointly Funded by Municipal Schools (202201020150).

The data that support the findings of this study are available on request from the corresponding author.

All authors performed material preparation, data collection, and analysis, and read and approved the final draft. Shi-Jie Jiang and Feiyun Xiang wrote the first draft of the manuscript. Iris Yang was responsible for review and editing of the final manuscript.

Feiyun Xiang, School of Mathematics and Information Science, Guangzhou University, Guangzhou Higher Education Mega Center, No. 230, Outer Ring West Road, Guangzhou, People’s Republic of China. Email: [email protected]

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