Financial Executive Orientation, Information Source, and Financial Satisfaction of Young Adults

Consulting Information Sources and Personal Finance

The research model in this study examines individual behaviors regarding individual choices of consulting information when making financial and investment decisions. Reports and publications suggest that people use various information sources. Literature reveals several major and popular types of consulting information sources with which people have varying degrees of preferences (Helman & Paladino, 2004; Loibl & Hira, 2006). Adults have preferences regarding delivery of personal, financial information (Rhine & Toussaint-Comeau, 2002), and the influence of peer-based advice is increasing, whereas traditional sources are decreasing (Aarkstore Enterprise, 2011). We thus hypothesize that young adults rely on both online and offline sources when seeking financial advice.

Individual Financial Styles and Choice of Information Sources

Research suggests that individual financial behaviors such as choices of information sources might be influenced by personal factors, especially personal financial orientations. Investors’ financial investment decisions are subject to attitudes, beliefs, preferences (Kalra Sahli & Pratap Arora, 2012), personality traits (Durand, Newby, & Sanghani, 2008), and social experiences (Hira & Brinkman, 1992). Traditionally, financial and economic researchers assume people are rational and make investment choices based on net utility gains that maximize desired outcomes (Markowitz, 1952). A rational investor begins with beliefs about future performances and chooses the right investment, attempting to maximize anticipated returns. However, behavioral researchers argue that an investor’s decisions are seemingly irrational, guided by a complex decision-making process and subjective perceptions (Simon, 1955). Thus, additional alternatives and influences must be considered when assessing investment decisions.

In recent years, the influence of human emotions and personality traits when predicting investors’ decisions attracted the attention of many scholars (Durand et al., 2008; Shiv, Loewenstein, & Bechara, 2005; Shiv, Loewenstein, Bechara, Damasio, & Damasio, 2005). A popular personality inventory that is used when understanding investor behaviors such as how individuals trade (Camgoz, Karan, & Ergeneli, 2012) is Norman’s (1963) Big Five personality traits (extraversion, agreeableness, conscientiousness, emotional stability, and culture). Financial behaviorists use these dimensions broadly to understand how individuals trade (Camgoz et al., 2012). Similarly, the Myers–Briggs Type Indicator (Myers, McCaulley, & Most, 1985) was also recommended by financial professionals to understand investors (Gregory, 2014; Yook, 2014).

Marketing literature suggests that consumers’ personalities affect financial behaviors (Endler & Rosenstein, 1997; Mowen, 1999; Sujan, 2001). For example, narcissism associates positively with compulsive consumption (Rose, 2007). Impulsivity is a predictor of additive behaviors (Acton, 2003; Miller & Brown, 1991) in which impulsive young adults tend to carry higher credit card balances (Mansfield, Pinto, & Parente, 2003) because of poor self-regulation. College students who are emotionally unstable, introverted, materialistic, and require constant stimulation are more likely to exhibit impulsive spending and misuse credit cards (Pirog & Roberts, 2007). The central message is that investment preferences that guide an investor are complex and might be influenced by various factors such as personality, emotional state, cognitive ability, risk tolerance, attitudes, and knowledge with investments and peer groups, among other variables. We thus argue that the ability to manage personal finances includes both internal and external drivers. For this study, we focused on young adults’ cognitive (e.g., planning and organizing) and emotional factors (e.g., anxiety and impulsive spending), adapted from Spinella et al. (2007). Based on evidence about the role of prefrontal systems in personal financial management and with supports from studies about clinical populations, functional neuroimaging, and both subjective and objective neuropsychological measures, Spinella et al. (2007) establish the Executive Personal Finance Scale with data on its correlations with income, credit card debt, and investments. The Scale includes four factors, impulse control (IC), organization (ORG), planning (PL), and motivational driver (MD; see Table 1 for the included items by this study). They suggest that the factors correlate with financial attitudes and behaviors and use of various forms of financial investments. Therefore, we propose following hypotheses:

Financial Outcomes and Choice of Consulting Information Sources

The model uses financial satisfaction as an indicator of financial outcomes. The literature on personal finance suggests that various types of information preferences in personal financial decisions relate to real and behavioral financial outcomes, which in turn lead to and are reflected by personal financial satisfaction (Davis & Helmick, 1985; Joo & Grable, 2004). First, mass media have always influenced individual personal financial/consuming decisions and financial outcomes for youths and others (Davidson, 2012; Roberts, 1998). Similar to other financial information sources, mass media provide financial advice that can indirectly or directly change financial knowledge and behaviors (Joo & Grable, 2004). Second, it is reported that students learned most about credit card use from parents and relatives (Pinto et al., 2005). Information obtained from parents, media, and schools, but not peers, relate to decreased credit card debt (Pinto et al., 2005). Third, a large portion of young adults attempt to garner social acceptance and gravitate toward advice from peers on how to spend their money and manage finances. Empirical evidence suggests that individual financial and economic outcomes of youth consumers (Shim, Barber, Card, Xiao, & Serido, 2010) are related to their social interactions with peers and other social structures. Fourth, people seek help from financial advisors for financial outcomes. A Rand study suggests that individuals who solicit advice improve performance (Hung & Yoong, 2010), although other research conflicts with this finding. For example, Marsden, Zick, and Mayer (2011) use retirement planning data, comparing people who have and have not met with a financial advisor. They find that working with an advisor relates to important financial planning (i.e., goal setting, calculation of retirement needs, retirement account diversification, etc.) but does not relate to self-reported retirement savings or short-term growth in retirement account asset values.

In addition, social media is found to influence how individuals learn and build financial literacy (Way & Wong, 2010). Research suggests that social media have become increasingly important to individuals learning about financial matters that are essential to building financial competency and individuals follow opinion leaders through blogs and social sites regarding personal financial topics on savings, retirement planning, investment selection, and so forth (Way, Wong, & Gibbons, 2011). Chen, De, Hu, and Hwang (2012) find that advice from social media such as Seeking Alpha associates strongly with contemporaneous and subsequent stock returns and helps predict earnings surprises. Consequently, we argue that social media is an important method of communication and information-seeking for young adults. Young adults are becoming more self-directed and might base investment decisions on content found through social media. They might also conduct information searches across multiple platforms, both online and offline, seeking financial advice.

Moreover, personal finance outcomes such as family income, net worth, household resources, household debt-to-income ratio, perceived changes to financial conditions over time, and financial aspirations influence financial satisfaction (Davis & Helmick, 1985). Financial behaviors, stress, knowledge, solvency, and risk tolerance can affect financial satisfaction. Because the literature suggests that information sources relate to various outcome indicators, although it is beyond the scope of this study to examine them all, the model examined in this study uses financial satisfaction as an overarching outcome indicator of individual financial information preferences.

Constructs and Instrument

A survey was designed with items adapted from extant research (Cogent Research, 2012; Spinella et al., 2007). The questions in the survey focused on demographics, four antecedent constructs about personal financial execution orientation, one behavior construct about individual choices of using consulting information sources, and one outcome variable about individual satisfaction with personal finance status (Cogent Research, 2012). The four personal financial execution orientation factors (i.e., impulse control, organization, planning, and motivational driver) are adapted from the Executive Personal Finance Scale (Spinella et al., 2007). Consulting information sources include family and relatives, friends, professional advisors and bankers, social and online media, and mass media such as magazines and newspapers. Table 1 shows the constructs, along with items for each and outer loadings for all items in the model. All constructs were measured with two items, except preferred consulting sources, which had one, and financial planning, which had three. Regarding social media and online resources, the one question used for each of the five consulting sources read, “To what extent do you agree with the statement that ‘when I have to make a financial decision, I prefer to consult social media’?” A Likert-type scale was used for all items, ranging from 1 (strongly disagree) to 5 (strongly agree).

The Sample

The survey was conducted online through Snap Survey from April 15 to May 1, 2013. The study used a combination of convenience and stratified sampling. A link to the survey was sent to about 750 individuals who were friends, relatives, and coworkers of 50 undergraduate business students in Southern California. The students were asked to stratify targeted people whom they had access to according to age, gender, race, and occupation, and then approached 15 of the stratified contacts with the survey.

Respondent Characteristics

Four hundred eighty adults responded to the survey, respondents who were outside the age range were dropped. Our final sample included 229 respondents who were between the ages of 18 and 25 years old. Of the 229 young consumer respondents, males and females were represented nearly equally in the sample. About 5% (N = 11) were married. In terms of education, 58.08% (N = 133) had high school diplomas, 17.47% associate’s degrees (N = 40), 20.52% bachelor’s degrees, and 3.07% (N = 7) masters’ degrees or higher. About 30.57% (N = 70) were Asian or Pacific Islander, 26.64% (N = 61) Hispanic or Latino, 24.89% (N = 57) White, and 6.55% (N = 15) American Indian and Alaskan Native.

Analytic Procedures

Structural equation modeling was used to test the model, exploring sequential relationships among variables concerning personal financial orientation, satisfaction, and consultation choices of information sources.

Measurement Model Results

The factor outer loadings and t values of the remaining items are shown in Table 1. The remaining items’ factor outer loadings were above the threshold of .70. Shown in Table 2, the model with the remaining items was largely robust, and cross-loadings were minimal. The measures had sound convergent validity, discriminant validity, and internal consistency. Average variance extracted (AVE) ranged from 0.74 to 0.92, which exceeded the recommended minimum of 0.5 (Gefen & Straub, 2005). The square roots of the AVEs were higher than the cross-construct correlations, which demonstrate acceptable convergent and discriminant validity. Cronbach’s alpha coefficients exceeded .7 (except for motivation, which was close to .7), and the composite reliability of all constructs exceeded 0.7, indicating adequate internal consistency.

Overall Structural Equation Modeling Results

We used SmartPLS to test hypotheses. SmartPLS fits the needs of a predictive-causal analysis (Chin & Newsted, 1995; Wold, 1982), and it requires fewer data specification constraints because this study borrowed measurements from other studies. Standardized regression coefficients of the path analysis for the structural model are shown in Figure 2. Results demonstrate that four factors (e.g., impulse control, motivational driver, financial planning, and organization) predict preference for information sources to some extent. Impulse control (−.161, p < .01), motivational driver (.177, p < .01), and financial planning (.205, p < .001) accounted for 12% of the variance in personal financial consultation decisions to ask spouses and/or family members. Impulse control (.228, p < .001) and financial planning (.249, p < .001) accounted for 10% of young adults’ preferences for friends and/or colleagues. Financial planning (.372, p < .001) accounted for 14% of young adult’s preferences for professional financial advisers such as bankers, accountants, and others. Impulse control (.398, p < .001), motivational driver (−.263, p < 0.001), and financial organization (.178, p < .05) accounted for 23% of young adults’ preferences for online and social media. Impulse control (.183, p < .01) and financial planning (.197, p < .001) accounted for 9% of young adults’ preferences for magazines, newspapers, and other mass media. Results also suggest that preferences for information sources explain some variance in satisfaction with current personal financial status: 0% choosing family, 1.5% for friends, 4% for financial professionals, 3% for social media, and 1% for mass media.

Figure 2.

Structural equation analysis results—personal financial orientation and choice of consulting sources.

*p < .1. **p < .05. ***p < .001.

Results on the Associations of Information Sources With Financial Executive Orientation and Financial Satisfaction

Conclusions and Contributions

As for the young adults, this study suggests that two financial executive orientations—impulse control and financial planning—influence young adults’ information choices for financial decisions. The two orientations differentiate people regarding preferences for consulting sources. Young adults lacking impulse control are more likely to consult with online, mass media, and social media sources but are less likely to consult with family members and spouses. Those reporting an orientation of financial planning tend to use a range of information sources other than online and social media. This study also finds that motivation and financial organization orientations influence information choices. Young adults are motivated to make money are more likely to consult with family members and relatives, and are more likely to consult with online and social media if they are good at financial organization but unmotivated to make money. This study suggests that choices of financial information sources influence satisfaction with financial statuses. Those who consult information sources other than family members and spouses are more likely to be satisfied with their financial situations. Among various information sources, young adults are most likely to be satisfied with their finances when information is derived from financial professionals, then by social media and online sources, and then by magazines/mass media and friends/colleagues.

This study contributes to extant literature by revealing characteristics of those young adults who use social media and the Internet as information sources for financial decision. Young adults who seek online sources and social media for investment decisions belong to a group; they are less financially planned than others are but represent the only group that is more likely to be financially organized, although they lack control when spending and are unmotivated to make money. Although less satisfied than those who consult with financial advisers and bankers, they are more likely to be satisfied with their financial situations than those seeking information from sources such as family and spouses, friends and colleagues, and magazines and mass media.

Limitations and Future Research

One limitation of this study relates to the research instrument. This study uses personal financial orientation and execution traits as predictors of personal financial information source choice. Other studies suggest that personality traits can also be adapted to examine financial and retirement planning decision (Gregory, 2014; Yook, 2014); instruments such as the Myers–Briggs Type Indicator (Myers et al., 1985) might be more appropriate for such studies. Future research should be conducted using other instruments. This study also limits its scope to one population—young adults. Future research on other populations, with comparisons, would prevent common method bias and further validate the research instrument. In addition, this study limits its scope to one outcome factor and several general financial information choices without explaining the specifics about these information sources, especially for those who use social media and online sources. Future research should assess details concerning information sources and other predictors and outcomes of information source choices. Finally, data collection was through a network of young adults in Southern California and was thus limited in scope and generalization. Future research should use random, scientific sampling to obtain data throughout regions of the United States and other countries.

Practical Implications

This study contributes to personal finance literature with findings from a research model, which offers important implications for young adults, financial institutions, professional advisors, and policymakers. For young adults, this study suggests they should seek financial advice from sources other than family members alone. Financial institutions and professional advisors should serve young adults through existing methods because they remain the best ways to achieve financial satisfaction. They should also broaden services to include other sources such as social media and the Internet because young adults are engaged with those sources. Policymakers should evaluate the sources they design to reach various groups in the population and design programs that consider the effectiveness of such sources and the preferences of those groups. Findings from this study provide insights on building the best information source for young adults, particularly, and the population, generally—a professionals-led, social-media platform from which families and peers, as groups, can obtain information, improve financial literacy, access advice, and make decisions. In the near future, more individuals might strive to achieve personal-finance excellence through such platforms, regardless of financial executive orientations.