Factors Influencing the Motivation to Pursue a Career in Financial Planning*

Self-determination theory (SDT) is an empirically verified psychological theory of human motivation and personality that assumes that individuals are intrinsically motivated by fulfilling their need for autonomy (relating to interest and choice) and competence (Ryan & Deci 2000) through learning, growth and challenge (Deci & Ryan 1985), While SDT is concerned with these specific needs, it also acknowledges the influence of the social environment (Deci & Ryan 1985) which we propose to further address through social learning theory, as shown in our conceptual model.

Autonomy around choice of career influences motivation with pessimistic views about an individual’s control over the career decision-making process decreasing personal motivation to pursue a particular career. This is because the individual perceives it as unworthy of investment or pursuit, when measured against the perceived uncertain outcome or failure (Saka, Gati, & Kelly 2008). Conversely, those who have had the opportunity to self-direct their career choice in line with their own interests and abilities have been found to have enhanced intrinsic motivation (Deci & Ryan 1985; Frederick & Ryan 1995).

Intrinsic motivation concerns the internal reward of action/s taken by an individual. In public service careers, this has been characterised as feelings of happiness and satisfaction when engaging in work that impacts people and is aligned with their own value system (Chen,Chen & Xu 2018). Further, there has been considerable debate around whether tangible extrinsic rewards can undermine intrinsic motivation (Deci, Koestner & Ryan 1999; Eisenberger & Cameron 1996; Ryan & Deci 2000) with extrinsic rewards such as a high salary signifying what people ‘want’ as opposed to what they ‘need’ (Tang, Tang, & Luna-Arocas 2005).

SDT has been used to explain career choice by suggesting that individuals desire a role where they con express their own values, attitudes and personal abilities through engaging with problems. For example, Williams, Saizow, Ross & Deci (1997) found that ‘interest’ was the strongest variable regarding motivators of career-choice in a study on medical clerkship experiences. The study showed that perceived interest in speciality choice increased the likelihood of selecting that residency or motivation to pursue a specific specialisation. Further, individuals in the study were provided with an opportunity to use personal abilities through engaging problems and those who perceived competence in solving these problems in a corresponding medical speciality were more likely to choose a career in that specialty. Likewise, it follows that individuals who have been provided with an opportunity to use their personal abilities to solve personal finance problems, and have done so successfully, may perceive themselves to be competent in this area and be more likely to pursue a career in financial planning.

Social learning theory suggests that individuals learn through the observation of others in social contexts. The behaviours observed would be imitated, learned, or modelled through the result of the observed behaviour. For example, individuals can attempt to imitate positive behaviours through observation of a role model. Social learning developed from behaviourist theories and was first defined as personality consisting of learned habits (Delprato & Midgley 1992). Imperatively, social learning influences social normative beliefs (Flay & Petraitis 1994).

Social learning, regarding career choice, can affect attitudes, values, behaviours and, subsequently, motivation for choosing a career (Tones, Pillay & Kelly 2011). It is possible that social learning is responsible for the age of those entering the financial planning profession in Australia which is much higher than other comparable vocations such as accounting, banking and finance (Cull 2009) with 43 per cent of financial advisers aged over 50 years old (William-Smith 2017), Males also dominate the profession with only 20 percent of Australian financial planners identifying as female (De Gori 2019). Thus, it is likely that observations of others may influence the decision to choose (or not to choose) financial planning as a career, Further, as financial planning is not yet recognised in Australia as a stand-alone discipline, it is less likely to form part of career discussions during the school years and more likely to be considered as a career later in life once one has had an opportunity to be exposed to the discipline through further education, observation or life experiences. Additionally, the socialisation process that has seen males traditionally pursue careers requiring mathematical skills (Betz & Hackett 1981) may be responsible for more males choosing a career in financial planning than their female counterparts. Further, it follows that the number of females pursuing financial planning as a career have been influenced by traditional gender stereotypes that place the focus on men being the ones that oversee financial matters.

Social learning contexts can affect career choice through shaping individuals’ values and perceptions. For example, Li (2017) found rural students scored higher than metropolitan students on self-development in a questionnaire on vocational values due to the social context of the students’ geographic location, as farmers bore most social obligations yet had poorer welfare outcomes and lower self-esteem. Further, individuals are more likely to choose a career based on their experiences in certain geographic locations where they feel they are accepted (Datti 2009). This not only demonstrates associative experiences as a medium for social learning but cements how exposure to serendipitous events can affect motivation for entering a profession (Bright, Pryor, Wilkenfeld & Earl 2005).

Socioeconomic background is a powerful predictor of career choice, particularly where extreme poverty is involved as this can impact on other elements such as learning opportunities which are directly linked to aptitude, a key driver for developing strong self-efficacy which impacts on career choice (Lent, Brown & Hackett 1994). The learning environment to which individuals are exposed may also be influenced by gender and ethnic based socialisation processes with educational access issues, faculty-student relations and social integration playing an important role (Hackett, Betz, Casas & Rocha-Singh 1992).

Finally, other environmental factors such as exposure to role models (Hackett, Esposito & O’Halloran 1989; Quimby & De Santis 2006); emotional and financial support (Lent, Lopez, Lopez & Sheu 2008; Rogers & Creed 2011), barriers (e.g. financial, personal, social/family) (Lent, Brown, Talleyrand, McPartland, Davis, Chopra, Alexander, Suthakaran & Chai 2002) and network contacts (Tümen 2017) can all exert influence on career choice.

Agency and communion, also called the “big two” (Abele & Wojciszke 2014), are theoretical concepts representing two fundamental approaches to living one’s life (Sheldon & Cooper 2008). While both are essential modes of functioning, individuals vary with respect to the strength of their preferred orientation. Agency refers to a person behaving as a separate individual while communion involves participation of the individual as part of a larger social unit (Bakan 1966). Agency is characterised by self-protection, mastery, self-promotion, and self-expansion with a focus on self-profitability and task-functioning, where in contrast, communion is characterised by cooperation, openness, care, and connection with others and involves a focus on other-profitability and social functioning (Abele & Wojciszke 2014; Howle et al. 2017; Sheldon & Cooper 2008). For example, a person who is primarily focused on agency will be concerned with finding a job that they perceive to have high status, where they have a reasonable amount of autonomy and can apply their skills to earn a high salary. whereas a person focused more on communion may be more concerned with finding a job where they can form relationships with others.

Researchers have sought to understand career choice using agency and communion through goal congruence theory. This theory holds that there are two types of careers that exist to fulfil agentic and communal goals: things-careers (e.g. engineering) and people-careers (e.g. nursing). Things-careers are perceived as fulfilling agentic career goals well, but not communal career goals, with the reverse applying for people-careers (Diekman, Brown, Johnston & Clark 2010; Diekman, Steinberg, Belanger & Clark 2017). As men are typically stereotyped as agentic and women as communal (Bell & Burkley 2014; Martin & Ruble 2004), it follows that there may also be gender differences in agentic (e.g. wanting status) and communal (e.g. wanting to help others) career goals (Tellhed, Bâckström & Björklund 2018). This was supported by Pohlmann (2001) who found women tended to rate communal career goals as more important than agentic goals and vice versa for men. Further, Eccles and Wang (2016) found that individuals who valued working with people (a communal career goal) in the final year of schooling, were less likely to choose a things-career ten years later. Studies have focused on careers that are seen as having either agentic or communal goals, with limited studies on careers that are observed to have both agentic and communal goals.

Underlying both agentic and communal goals is the concept of self-efficacy. Self-efficacy is the belief in one’s ability to achieve goals. It has been known to affect motivation in career choice (Bandura et al. 2001) with studies confirming that perceived self-efficacy influences both educational and occupational endeavours (Hackett, 1995; Lent, Brown & Hackett 1994). However, perceived self-efficacy does not always match objective indicators of actual ability (Bandura 1989). For example, evidence has shown that career interests of women are limited by their own views of their mathematical skills which they perceive as too weak for a number of traditionally male-dominated occupations even though measurement tests show their mathematical ability to be appropriate for such roles (Betz & Hackett 1981). Thus, self-efficacy beliefs hove the power to eliminate potentially rewarding occupations from the career choice inventory, which can have several economic and psychological implications (Brown & Lent 1996). Further, those with a stronger sense of self-efficacy may not pursue certain careers if they perceive barriers to the entry or success of that career (Holland 1985; Mitchell & Krumboltz 1996). Self-efficacy is closely related to confidence (Rogers & Creed 2011 ; Befz, Klein & Taylor 1996) which is known to be influenced by social experiences and thus linked with social learning theory.

Career choice theory suggests that individuals desire to work where they can express their personality (Holland 1959). The ‘big-five’ personality traits have been widely used in academic psychology to describe human personality and have often been referred to as the ‘OCEAN’ inventory, representing Openness, Conscientiousness, Extraversion, Agreeableness and Neuroticism. While there have been a number of different instruments, names, and conceptualizations used to describe the ‘big-five’ (Costa & McCrae 1992; Digman and Inouye 1986; Goldberg 1990; Norman 1963; Trapnell & Wiggins 1990; Tupes & Christal 1961 reprinted 1992), they are all addressing the same phenomenon (Costa & McCrae 1992). To measure these big five personality traits, Goldberg (1992) developed the Big-Five Factor markers from an International Personality Item Pool (IPIP) being Extraversion, Agreeableness, Conscientiousness, Emotional Stability (the opposite of Neuroticism) and Intellect/lmagination (similar to Openness). This is often referred to as the Five-Factor Model (FFM) of personalily.

Numerous studies have investigated the relationship between an individual’s personality type and fields of career choice (Borow 1982). For example, higher conscientiousness has been associated with a greater likelihood of membership in the conventional-dominant profile (occupations generally following set routines and procedures) while individuals with a high realistic-dominant profile (occupations generally following practical and hands-on activities) indicated a 1 in 4 chance of STEM major choice (Perera & Mcllveen 2018). Personality traits have also been found to be predictive of career choice behaviours in a range of occupational areas (Tomšik 2018; Tomšik & Gatial 2018) and linked to other career choice variables such as work attitude and values (Tokar, Fischer & Subich 1998). Similarly, the big-five personality traits have been found to affect motivation for choosing traditional careers. For example, ‘conscientiousness’ has been significantly correlated with all intrinsic motives for choosing teaching as a career (Tomšik 2018) and the personality trait ‘neuroticism’ has been found to be related to occupational choices involving routine, less complexity and less independent work (Spector, Jex & Chen 1995). Personality measures such as the big-five have also been found to be valid predictors of various job-related criteria (Tokar, Fischer & Subich 1998).

The sample includes two types of participants: financial advisers in Australia (71%) and students (29%) who are enrolled in an accredited financial planning unit recognised by the Financial Adviser Standards and Ethics Authority (FASEA). There was no incentive provided to participate in the research and the research project was approved by the Human Research Ethics Committee of the authors’ affiliated university and conducted in accordance with the Declaration of Helsinki. The financial adviser sample was recruited via an announcement in an electronic newsletter issued by the Financial Planning Association of Australia² and students were recruited via notices from lecturers who were members of the Financial Planning Academic Forum (FPAF)³. Informed consent was obtained from all participants, Recruitment took place from the second half of 2019 to the beginning of 2020.

The sample included 125 individual questionnaire responses. Of these, 22 responses had missing information and were not usable, resulting in 103 usable responses. The survey sample consisted of 73 (71%) individuals who were currently working as financial advisers. The remaining 30 participants (29%) were comprised of professionals who held a professional designation but not currently working as an adviser (5.8%), individuals studying towards a degree and/or designation but not working as an adviser (17.4%), and those not currently studying or holding a professional designation (5.8%) (possibly recent graduates, para-planners, retired, or between jobs). Almost half of the total sample (48.5%) were currently studying towards a degree and/or designation. Fifty-four percent of the sample were male and 46% were female and 67% had a bachelor degree or higher, with 60% holding a professional designation (for example, Certified Financial Planner (CFP), Certified Practising Accountant (CPA)). English was predominantly the first language of the sample participants (89%) but across the sample were 11 different first languages. Respondents represented ages across all working age brackets; 18-29 year olds (14%), 30-39 year olds (21%), 40-49 year olds (33%)⁴,50-59 year olds (19%) and 60-69 year olds (13%), with the younger age groups holding a larger proportion of respondents not currently working as a financial adviser.

A summary of the demographic information for the sample is provided in Table 1 and an age distribution of the sample showing those currently working as a financial adviser is shown in Table 2.

In addition, there were 14 interviews undertaken as part of the study, Of these interviews, twelve were with practising financial advisers and two were with financial planning students who were not currently working as a financial adviser.

To answer the research questions, the study adopted a mixed methods approach utilizing both a survey instrument and interviews. These were approved for use by the university’s human research ethics committee. The anonymous survey instrument was administered online via Qualtrics and included demographic questions (e,g. age, education, gender, first language), whether the respondent was a student or financial adviser, questions relating to reasons for choosing to study and work in financial planning, salary expectations, and the perceived skills requirements of financial advisers. In addition, the survey instrument included fifty Likert scale questions using the Big-Five factor markers from the IPIP developed by Goldberg (1992) to measure Extraversion, Agreeableness, Conscientiousness, Emotional Stability and Intellect/lmagination. The personality questions were scored in accordance with the IPIP scoring instructions (Goldberg 1992).

Participants were also asked to suggest ways to promote financial planning as a study option and/ or future career via free response questions and were given an opportunity to provide any additional information they felt was relevant to the research via free response. Participants were asked to indicate their interest in participating in an interview and ‘yes’ responses were redirected to another Qualtrics survey to provide contact details (stored separately from the survey data) to allow them to be contacted for an interview. The survey instrument was tested on a small sample of three, including two industry professionals and one student and minor amendments to structure and wording of questions were made accordingly to ensure ease of completion and comprehensibility. A sample of the instrument is contained in the appendix.

The interview phase of the research involved semi-structured face-to-face, over-the-phone, or video web interviews with participants (dependant on location of participant). Written consent was obtained from all participants to undertake the interviews which were recorded on a digital recording device and subsequently transcribed in preparation for thematic analysis. A total of fourteen interviews were conducted.

Data from the Qualtrics survey was downloaded and entered into Statistical Package for the Social Sciences (SPSS) version 25 for statistical analysis. The file was checked for missing data and accuracy of coding and screened for outliers. Frequency tables along with one-sample t tests, independent samples t tests and bivariate correlation analyses were used to interpret the data and answer the research questions. Free responses from the survey were subjected to thematic analysis which involved allocating codes for each major theme which were able to be included with the statistical analyses. Illustrative direct quotes from participants were electronically recorded in a coding document. Deductive coding was completed concurrently with inductive coding according to key concepts and theories. Coding was undertaken independently by two researchers and then reviewed by both researchers. Any inconsistencies during this process were discussed between the researchers to clarify conflicting interpretations and arrive at a joint decision (Barbour 2001 ; Campbell et al. 2013). The coding was tested for inter-coder reliability and no significant differences were noted.

A thematic analysis of the 14 interview transcriptions was conducted using the six phases of thematic analysis: data familiarization; generating initial codes; searching forthemes; reviewing themes; defining themes; and producing a report (Braun & Clarke 2006). Major themes established from theories in the literature (social learning, personality theory, autonomy, and interest) were identified in the data and recoded in a coding document. Additional themes were also found in the data (unexpected events and benefits) which included explicit semantic themes and latent themes or concepts behind motivations. These were classified into categorical broad themes with sub-themes in each broad theme and coded accordingly. A database was compiled to record these themes and sub-themes along with illustrative direct quotes. The themes were subjected to an analytical narrative and tallied accordingly. A second researcher continually reviewed the codes and corresponding classification of themes and inter-coder reliability revealed no significant differences.

Both quantitative and qualitative data from the survey instrument and interviews were triangulated to provide richer data and more comprehensive responses to the research questions. Interviews allowed for a deeper understanding and interpretation of the quantitative responses provided in the survey. While statistical analyses can precisely measure variables, link causation and provide measures of significance, the qualitative data can assist in explaining why the results are significant and further confirm quantitative results (Neuman 2006; Veal 2005). The triangulation of the survey responses and interview transcripts further validated the data and allowed for a more holistic analysis of the factors that motivate an individual to choose a career in financial planning. Further, career choice theory, social learning theory and personality theory assisted in explaining the results and answering the research questions.

More than 91% of the survey sample had completed formal tertiary education and 48.5% were currently undertaking further study. To respond to RQ1, the survey instrument asked respondents what motivated them to choose financial planning as a study option. A summary of the responses is shown in Table 3.The highest frequency of responses was found for ‘want to help others’ (56.3% of respondents), closely followed by ‘employment opportunities’ (53.4%) and ‘interest/enjoyment’ (46.6%), providing support for the interest, enjoyment and inherent satisfaction aspects of SDT.

Noticeably, no respondents indicated that their motivation to study financial planning was influenced by high school studies or high school teachers, Further, the number of respondents who were encouraged by their family to study financial planning was very low, comprising only 2.7% of all responses, This indicates that financial advisers had a high level of autonomy in choosing their career, an important intrinsic motivation explained by SDT.

A significant difference in motivation was found between age groups, with a higher proportion of those aged 18-29 years motivated to study financial planning because they enjoy working with numbers, X² (1, N = 103) = 9.97, p = .04. This suggests that younger people who have less life experience and possibly less exposure to financial planning perceive that financial planning largely involves working with numbers and possibly are less aware of the ‘people’ side of financial planning and the ability of financial planning to help others. This age group also included a lower proportion of those currently working as a financial adviser (28.6% of the age group) compared to other age groups that ranged progressively from 68.2% (30-39 years) to 84.6% (60-69 years), These results support the possible influence of the competence aspect of SDT.

Considering that salary expectations have been cited as a possible extrinsic motivating factor for career choice, respondents were asked to indicate their annual salary expectation for a qualified financial adviser, Results showed the mean salary expectation to be $130,984 per annum, with a range from $40,000 through to $230,000. The mean salary expected by a working financial adviser (M = $139,462.74; SD = 50,807) was higher than respondents who were not currently working as a financial adviser (M = $110,354.60; SD = 32,947). Descriptive results can be found in Table 4. A t test revealed a statistically significant difference between salary expectations of those currently working as a financial adviser and those not currently working as a financial adviser, t(81.86) = -3.44, p = <.00l. Table 5 shows the results of the independent samples t test. The manually calculated effect size (r² = .12) is between Cohen’s (1988) guidelines for a medium effect (.09) and a large effect (.25).

As the demand for qualified licensed financial advisers in Australia is much higher than supply, it is plausible that those currently working as financial advisers may also expect a higher salary than those who are not currently working as an adviser (e.g. full-time students, retiring advisers or new entrants), Further, as current financial advisers are nowexpected by lawto undertake additional tertiary study, it follows that they may expect to be compensated for this through their salary. Pearson product-moment correlations were performed between qualification level (e.g. school level, diploma, advanced diploma, bachelor degree, masters degree) and salary expectation using an alpha level of .05. Scatterplots suggested the assumption of correlation was satisfactory. Table 6 shows a relatively strong, positive and significant relationship between qualification level and salary expectation, r(101) = .38, p < .001. This is further illustrated in Figure 2, suggesting that financial advisers expect to earn a higher salary as they obtain higher level qualifications. It follows that salary expectations may have some bearing on the motivation to pursue additional study in financial planning.

Figure 2:

In response to RQ2, the survey asked respondents who identified as currently working os financial adviser to explain via a free response, what factors motivated them to become a financial adviser. Results showed the main reason for becoming a financial adviser was ‘to help others’ (53.6%), followed by ‘work experience’ (33.9%) and ‘interest’ (26.8%) (see Table 5). These results mirror those for RQ1, with the main factors motivating an individual to study financial planning being the same major factors that motivated financial advisers to choose a career in financial planning.

The results also showed that enjoy working with people’ rated higher than enjoy working with numbers’ as motivating factors influencing the choice to pursue a career in financial planning. Many financial adviser respondents also indicated that working with both people and numbers’ motivated them to become a financial adviser. Further, the category ‘interest’ returned some responses that highlighted the interest in working with numbers which was further supported by interview transcriptions. For example:

I grew up finishing high school ot the point of the globe I financiol crisis... So that really sort of kicked off an interest in all things finance, budgeting, investment. That kind of thing. So it was always a personal interest of mine and it was all about trying to find a career that I could enjoy and once I heard that financial planning existed, in my mind, the two morried up as pretty much the exact same thing so I thought I could do a career doing exactly what I personally enjoy doing.

While the results have shown intrinsic motivation to be an important factor in choosing a career in financial planning, the influence of extrinsic factors was also examined through a survey question about working conditions. While only 6.8% of free responses from financial advisers indicated that working conditions influenced the choice to pursue a career in financial planning, 100% of survey respondents chose at least one of the working conditions provided. The type of ‘working condition’ with the highest frequency was work/life balance’ (62.5%), followed by clientele and flexible working hours. Figure 3 provides a visual representation of responses using a histogram.

Figure 3:

Of the twelve working conditions influencing the motivation to choose a career in financial planning, the top four all related to working with clients and working flexibility, Interview findings supported the survey results and provided further insight into the flexible working conditions expected in financial planning, such as being able to set their own hours. The ‘Other’ category included ability to help others and skills diversification, While working conditions were initially viewed to be potential extrinsic motivations, these findings instead provide further support to more intrinsic motivations outlined in SDT such as autonomy and interest.

Salary ranked fifth out of 12 working conditions selected by participants, representing 37%. This was further supported by three of the fourteen interviewees who indicated that while not the main motivator, salary was a contributing factor in their career choice.

To respond to RQ3, there was an optional open-ended, free response question included in the survey asking what (if any) life experiences may have led to the motivation to pursue a career in financial planning. Interviews with respondents provided further insight as to the social learning that occurred through these life experiences. Thematic analysis identified four main themes being financial hardship; exposure to benefits provided by financial advisers through family or friends; engagement with the financial planning profession, and ability to help others. A summary of the frequency of responses pertaining to the influence of life experiences on choosing financial planning as a career from both the survey and the interviews are included in Table 8.

Financial hardship rated highly in both surveys and interviews as a motivational factor in choosing a career in financial planning. This was a somewhat unexpected but important finding and supports the survey findings in Table 3 and Table 5 that indicate the main motivation to pursue a career in financial planning is to help others.

Free responses from surveys and interview responses included several comments as to how financial hardship earlier in life had led respondents to consider a career in financial planning, Some interviewees also reflected on how their own parents’ financial struggles impacted on them as a child and how that motivated them to work in financial planning:

... watching my own parents struggle with cash flow and things like that, really set me with the desire to be able to help people.

I can tell you now, my life experience from the time I was about eight years old has led to a career of financial planning, definitely. 1100 per cent know that my early childhood and teen experience has picked my career. I was a child of immigrant parents, first generation. Money swung in and out of our lives. They were bankrupt.

Other respondents experienced financial hardship as an adult. This occurred due to a myriad of reasons, including poor financial choices or a major life event, such as an economic recession, illness or divorce. For example:

Following separation and inability to meet obligations I was unsure where to turn for help - made me realise we needed more planners.

I have experienced highs and lows, lived through recession, drought and good times. I have seen the positive difference that good advice can bring.

Consistent with social learning theory, results suggested that choosing a career in financial planning is influenced by the observation of financial advisers in social contexts, such as observing the benefits provided by financial advisers to close family or friends. For example:

I’ve seen the benefits my family have gained from having a relationship with a financial planner.

Similarly, interview findings indicate that serendipitous events exposing individuals to the financial planning profession can provide a medium for social learning and affect motivation to choose financial planning as a career. For example, two interview participants detailed unexpected offers to gain work experience in financial planning when they were students in a related (but not financial planning) university degree:

I think financial planning was only one elective back then, And I was a third year undergraduate and there was probably a need to work out what job I was going to do. And a friend’s uncle ran a financial planning business. So I did some work experience...

Another interview participant who was trained as an accountant found themselves out of work and was offered to work with a financial planner:

I was out of work and a friend of mine was a financial planner and he said why don’t you come and work for me’.

Life experiences across a range of social contexts were also responsible for highlighting that financial planners had the ability to help others. This was a common theme amongst both free responses and interviews where respondents indicated how their life experiences influenced their motivation to pursue a career in financial planning to help others. For example:

I grew up in Central Queensland out in the bush where people often didn’t have a lot of money, and the experience of knowing a lot of people who were very, very poor and also watching my own parents struggle with cash flow and things like that, really set me with the desire to be able to help people.

In responding to RQ3, the findings from this study reveal that social learning through life experiences has a significant bearing on the motivation to pursue a career in financial planning to help others. For some respondents, this was influenced by social situations involving financial hardship, or where financial advice was provided with beneficial outcomes. To a lesser degree, some respondents pursued a career in financial planning due to job opportunities provided by their social networks. While these social experiences support social learning theory and previous empirical studies on career choice, the specific nature of the narratives provided by respondents in this study highlight the uniqueness of financial planning as the skill of working with numbers is able to be used to help others. It follows that the choice to pursue a career in financial planning may involve both agentic and communal goals.

As discussed earlier, goal congruence theory holds that there are two opposing categories of careers that exist to fulfil one’s goals in life: things-careers to fulfil agentic goals; and people-careers to fulfil communal goals. RQ4 asks ‘Is choosing a career in financial planning congruent with agentic or communal goals?’. Responses to the previous research questions have highlighted that helping others was the strongest motivating factor for both choosing to study financial planning (RQ1) and to become a financial adviser (RQ2), as indicated by more than half of the respondents. Further, 32% of responses for those studying financial planning and 12.5% of financial adviser responses also suggested that they were motivated by an interest in numbers and 10.7% of free responses from financial advisers showed an interest in both working with both people and numbers (refer Tables 3 and 7). The results were further supported by interviewees who explained how being financially minded as well as helping people fitted well with financial planning:

Well, I think a lot of people - well, I guess virtually everyone I spoke to sort of like considered it for me a bit of a natural fit because they always thought that I was like financially minded and I did have some certain things happen in my life where you know I really had to devote a lot of my time and energy to helping other people.

Pearson product-moment correlations were performed between enjoying working with numbers and helping others with α = .05. The results strongly supported the dual motivation of enjoying working with numbers and helping people and were statistically significant, r = .40, p < .001. This suggests that those motivated to pursue a career in financial planning did so because of their interest in numbers as well as their interest in people. This is a significant finding as depending on the occupation, career choice theories and assessment tools tend to place more value on either numerical Things’ skills or people skills but not equal importance to both. For example, engineering is viewed as a career requiring numerical skills while those such as nursing and teaching are seen to value people skills more highly.

The findings of this study in determining the motivations for pursuing a career in financial planning have revealed a hybrid category of careers exists, that we will call people-things careers.

The Big Five personality test (Goldberg 1992) was administered as part of the questionnaire to determine if choosing a career in financial planning is more likely to be associated with any one personality trait, as posed by RQ5. The five factors: (1) Extraversion, (2) Agreeableness, (3) Conscientiousness, (4) Emotional Stability (Neuroticism) and (5) Intellect/lmagination were measured using questions from the IPIP developed by Goldberg (1992). Responses were made on a five-point Likert scale ranging from strongly agree (5) to strongly disagree (1), with ten questions for each of the five factors. The personality questions were scored in accordance with the IPIP scoring instructions (Goldberg, 1992). The 50-item scale had acceptable internal consistency reliability with a Cronbach’s alpha of .88.

Of the five personality factors measured, the sample showed the personality domain of tagreeobleness’ to rank highly on the scale, with M = 41.43 and Mdn = 42 (out of a total score of 50). This was closely followed by ‘conscientiousness’ (M = 40.68, Mdn = 41). The total scores for each of the five personality domains are shown in Table 9.

Interviews supported this finding with ‘agreeableness’ ranking highest on the thematic analysis with 33 counts from a total of 64 (51.6%) for personality traits, as indicated in Table 10.

Given that the personality trait of ‘agreeableness’ is characterised by altruism, helpfulness, optimism, and friendliness, it can be expected that the motivation to become a financial planner to help others would be related to a higher score for agreeableness.

Further, it follows that the personality trait of ‘intellect’ which involves curiosity, creativity and intelligence would be expected to be positively associated with the motivation to become a financial planner because one enjoys working with numbers. Using results for ‘motivation to study financial planning’ as a proxy for motivation to pursue a career in financial planning, bivariate correlation analyses were used to test the following hypotheses:

Hl : Agreeableness will be positively and significantly related to the motivation to help others by choosing to pursue a career in financial planning.

H2: Intellect will be positively and significantly related to the motivation to work with numbers by pursuing a career in financial planning.

Pearson product-moment correlations were performed between agreeableness and helping others, and intellect and working with numbers, using an alpha level of .05. Results are shown in Table 11. A moderate positive relationship was found between agreeableness and wanting to help others (H1) with statistical significance at the .051 level (r= .22, p = .051), with those with an ‘agreeable’ personality more likely to be motivated to pursue a career in financial planning to help others than those with other personality traits.

A moderate positive relationship was found between intellect and working with numbers (H2) with a high statistical significance (r = .24, p < .05) suggesting that those with the ‘intellect’ personality trait may be more likely to pursue a career in financial planning due to their enjoyment in working with numbers. The correlation analyses also showed enjoying working with numbers was strongly positively correlated with wanting to help others, with very high statistical significance (r = .4, p < .001) suggesting the enjoyment in working with numbers for those pursuing a career in financial planning also motivates them to use these skills to help others. This also assists in responding to RQ4, showing that a combination of both agentic and communal goals influence the motivation to pursue a career in financial planning.

The personality trait of agreeableness is often linked with careers such as nursing or teaching and other roles involving working with people where they are seen to be empathetic, and helpful. Conscientiousness on the other hand is more closely linked with technical more problem-solving roles requiring dependability and strong organisation skills such as those skills traditionally associated with accounting or engineering. The fact that those choosing to pursue a financial planning career scored highly across both personalities demonstrates the uniqueness of financial planning which requires characteristics of both agreeableness and conscientiousness. Interview respondents provided further insight to this phenomenon:

But financial planners themselves seem to need a personality that is quite people orientated. Definitely need a lot of empathy and the ability to connect with people and really find out what they like. What they’re trying to achieve. And really connect to them on a personal level. So people skills is probably priority for a financial planner though all the technical skills need to underly that.

Well there’s probably a range of personalities that can do okay in financial planning. Definitely there’s space for a people person. If you can talk to people and win their confidence, get them to talk to you about their finances and what they want to achieve, so good people skills definitely helps. But you also need to have good technical ability and an ability with numbers.

I think having the dual combination of being a people person and having technical aptitude for numbers and strategic thinking helps.

With the literature often associating ‘agreeableness’ with careers that are dominated by females such as nursing and teaching, the findings for this study were surprising as financial planning is a career dominated by males.To test for gender differences within the sample, an independent t test was conducted on each of the personality domains for any significant gender differences. The results are displayed in Table 12.

A statistically significant difference was found between males and females, †(73.39) = 2.45, p = 0.017 for the personality domain of ‘agreeableness’. The ‘agreeableness’ score was higher for females (M = 42.86, SD = 4) than it was for males (M = 40.17, SD = 5.73). This indicates that while financial planners in general were more likely to have the personality trait of ‘agreeableness’, females choosing to pursue a career in financial planning were more also more likely than their male counterparts to have the personality trait of agreeableness.