Determinants of financial market knowledge and practical financial experience in a sample of college students.
An increasing body of literature identifies the need to improve financial literacy of young adults to enhance the nation's wealth building interest and capacity over time. Inadequate financial knowledge has the potential to create a disproportionate distribution of wealth, savings, and capital formation (Chinen & Endo, 2012; Kosier, 2010). Higher levels of financial literacy are associated with greater financial stability, larger contributions to retirement accounts and pension plans as well as greater accumulation of household wealth (Behrman, Olivia, Soo & Bravo, 2012).
Wealth inequality can have a negative impact on family well-being by impairing their economic development in communities and as a nation as a whole (Shapiro, 2013). Indeed, the combination of the disparity in opportunities to utilize financial knowledge and the impact of societal economic barriers make lower income people, in general, and people of color, in particular, vulnerable to financial peril and circumstances that contribute to poor economic outcomes.
A review of social science literature suggests that a majority of minority youth graduate from high school and college without adequate understanding of money and finance (Sherraden, 2010; Vitt et. al., 2000). It should be noted that financial behavior is learned early in life, and this knowledge coupled with established values, attitudes, and experiences impact how financial decisions are made (Shuchardt et. al., 2009). Parents directly and indirectly influence their children and often times pass their misunderstanding of financial knowledge or lack thereof to their children. Indeed, Williams, Grizzell and Burrell (2011) found that the absence of financial literacy severely impacted the level and quality of advice given to urban youth by their African American parents on issues such as savings, money management and investing. If Black parents lack the necessary instruments, knowledge and experience to develop a fundamental financial education, it is reasonable to infer that their children will possess the same or lower levels of financial literacy.
This study presents empirical data that identify positive and negative influences on the awareness of financial markets and financial practical experiences of predominantly Black young adults.
Due to the fluctuations in the economic climate, both domestically and globally, it is becoming of greater importance to effectively manage personal finances (Lusardi & Tufano, 2009). Without the proper understanding of financial concepts, tools, and instruments, it is increasingly more difficult to sufficiently prepare for future and current financial needs. Indeed, the problems of insufficient financial resources are particularly acute in communities of color.
Compared to Whites, minorities lag in financial asset accumulations and in financial knowledge. In a study conducted by Chen and Volpe (1988) to assess financial literacy of students through testing their knowledge of personal finance, Blacks scored the lowest compared to other ethnic groups across all categories of financial knowledge questions (Robb & James, 2009). Hamilton and Darity (2016) also suggested that even when Black families have a "middle class job" and earn a middle class income, poor White families still accrued more wealth assets than Blacks. Analysis of households lacking savings revealed that forty-seven percent (47%) were African-American households compared to nineteen percent (19%) being Caucasian households (Grant, 2015). Seventy-six percent of Whites maintain interest-bearing accounts compared to 43% of Blacks. Fewer Blacks own stock or bond mutual funds (48% vs. 61%, individual stocks (38% vs. 54%) or money market accounts (26% vs. 43%), (Kosier, 2010). Middle class Blacks are more likely than Whites to have decreased their savings to make it through the recession according to 2010 and 2016 Ariel Black Investor Surveys. Even among high income Blacks, only 62% own stocks or mutual funds compared to 82% of Whites (Gutter & Fontes, 2006; Sordid, 2007). Furthermore, after deducting the family car as an "asset", the median Black family in America will only have a net worth of $1,700 dollars in comparison to Whites who will roughly have $116,800 dollars (Weissmann, 2014). An analysis conducted by the Corporations for Enterprise Development states that it would take Blacks two-hundred and twenty-eight years to accumulate the same amount of wealth that Whites have today (Davidson, 2016).
The effects of insufficient financial resources have long-lasting generational consequences. According to Goetz et al. (2011) having a higher debt, being minority, and lacking savings, impacted the likelihood of completing college. Black students are one-third less likely to complete their degrees, often due to greater financial burden (Hamilton & Darity, 2016). Experts attribute lower investment rates of Blacks to poor instruction on financial topics in public schools and misconceptions about the risk of stocks within parts of the Black community (Lusardi & Mitchell, 2011). This lack of understanding results in poor decision making in homes of minorities.
Given the large disparities between Whites and Blacks, even among the high income wage earners, there is a significant need for minority populations to obtain intensive financial literacy education which could explain their options regarding investing, wealth accumulation, college and retirement savings (Kossier, 2010; Census Bureau, 2001). However, to develop optimal, culturally appropriate financial literacy education programs that can achieve the aforementioned objectives, it is important to understand the factors which govern motivation and interest in improving financial knowledge among minority populations. Therefore, the goal of this study is to identify the factors which influence the minority student's interest in attaining financial knowledge and in improving market awareness.
RESEARCH QUESTIONS AND HYPOTHESES
The literature review guided the framing of the following research questions and related hypotheses:
(1) Will familiarity with financial market conditions increase the interest and knowledge of young adults in college?
(2) Will the awareness of financial market conditions (particularly the volatility of the previous five years) provide an environment which increases financial market intimidation in young adults?
(3) Will familiarity with financial market conditions, interest in financial markets, financial market knowledge, financial market intimidation and psychological hardiness influence practical financial experience of young adults in college?
(4) Will awareness of financial market conditions influence practical financial experience?
Based on the above research questions, the following hypotheses have been developed and tested:
Hi: Familiarity with financial market conditions, interest in financial markets, financial market knowledge, financial market intimidation, and psychological hardiness will influence awareness of financial market conditions.
H2: Familiarity with financial market conditions, interest in financial markets, financial market knowledge, financial market intimidation, and psychological hardiness will influence practical financial experience.
H3: Awareness of financial market conditions will influence practical financial experience.
Sample and Data Collection
The survey packet was administered during class times to various students across the campus of a comprehensive university located in the southeastern part of the United States. It contained eight instruments and took approximately 15 minutes to complete. All research participants were volunteers. Of the 145 questionnaires distributed, 145 students responded and the questionnaires were useable for a response rate of 100 percent. The sample demographics were 43% males and 57% female, with 87% Black majority and Caucasian, Hispanic, Asian and American Indian at 2% each and 54% other. Ninety-eight percent of the sample was between 1723 years. Eighty-six percent of the sample was business majors, with 26% percent freshmen, 34% sophomore, 17% juniors, 16% seniors and 6% graduate students.
In the present study, we used the following constructs to develop and test the hypothesized model shown in Figure 1. Unless stated otherwise, we used a Likert-type response format for the survey items.
Awareness of Financial Market Conditions. Eight items were used to assess this construct. The scale was developed by Ford et al (2007). The Cronbach alpha was .90.
Practical Financial Experience. We used four items developed by Ford et al (2007) to measure this construct. The alpha was .72.
Familiarity with Financial Market Conditions. Ford et al (2007) developed a 16 items scale to assess this construct. Subjects responded using anchors ranging from Not Familiar At All (1) to Very Familiar (5). The alpha was .89.
Interest in Financial Markets. Eight items developed by Ford et al (2007) were used to assess market interest. The alpha was .90.
Financial Market Knowledge. This construct was measured by four multiple choice items that were developed by Ford et al (2007). The number of items correct was then used as the financial market score and converted to a percentage for analysis purposes.
Financial Market Intimidation. To assess this construct we used 10 items from the scale developed by Ford et al (2007). The alpha was .87.
Psychological Hardiness. The authors of this study used the five item scale developed by Maddi (1999) to measure this construct. The alpha was .84.
The proposed model presented in Figure 1 was tested using structural equation modeling to evaluate the research hypotheses by using the Linear Structural Relations (LISREL) computer program (Joreskog & Sorbom, 1993). For each construct, composite scores were formed and subsequently used as the input for the variables in the nomological network.
The means, standard deviations, and zero-order correlations are provided in Table 1. Correlations among the constructs were in the expected direction and consistent with the literature.
Common Method Variance Tests
Because all constructs were measured using self-reports, the authors examined whether common method variance was a serious issue. As recommended by Podsakoff and Organ (1986), Harman's one-factor test was performed. In this test, all survey items were entered together into an unrotated factor analysis and the results were examined. If substantial common method variance is present, then either a single factor would emerge or one general factor would account for most of the total variance explained in the items (Podsakoff & Organ, 1986). After entering the 59 items into the factor analysis model, 12 factors emerged from the analysis, and the first factor only accounted for 22.134 percent of the total variance. In addition, no general factor emerged from the factor analysis. Thus, common method variance was not deemed a serious issue in this study.
Test of the Model
The two-step approach to structural equation modeling was employed (Anderson & Gerbing, 1988). First, the measurement model was inspected for satisfactory fit indices. After establishing satisfactory model fit, the structural coefficients were interpreted.
The measurement model had acceptable fit indices, [[chi square](10)= 13.837, p=.181, GFI= .97, NFI= .92, CFI= .97, NNFI= .94, RMSEA= .053, [chi square]/df= 1.383]. That is, the Chi-square statistic was at its minimum, and the p-value was nonsignificant. The GFI was above its recommended threshold level of 0.90 (Hair, Anderson, Tatham & Black, 1998), and the RMSEA was less than 0.08, indicative of an acceptable model (Steiger & Lind, 1980). The Chi-square divided by the degrees of freedom coefficient was less than three, which indicates acceptable model fit (Arbuckle & Wothke, 1995). The CFI, NFI, and NNFI all exceeded .90, indicating an acceptable fit of the model to the data (Bentler & Bonett, 1980).
Table 2 presents the structural coefficients for the model. Awareness of financial market conditions was one of two endogenous variables in our study. Hypothesis 1 stated that factors such as familiarity with financial market conditions, interest in financial markets, financial market knowledge, financial market intimidation, and psychological hardiness would influence awareness of financial market conditions. Partial support was established for Hypothesis 1 because the path from familiarity with financial market conditions to awareness of financial market conditions was significant and in a positive direction. Also, the path from interest in financial markets to awareness of financial market conditions was significant and in a positive direction. However, financial market knowledge, financial market intimidation, and psychological hardiness were not significant predictors of awareness of financial market conditions in the model.
Practical financial experience was the second endogenous variable in our model. Partial support was also established for Hypothesis 2, which stated that familiarity with financial market conditions, interest in financial markets, financial market knowledge, financial market intimidation, and psychological hardiness would influence practical financial experience. The path from familiarity with financial market conditions to practical financial experience was significant and in a positive direction. The path from interest in financial markets to practical financial experience was significant and in a positive direction. Likewise, the path from financial market knowledge to practical financial experience was significant and in a positive direction. The path from financial market intimidation to practical financial experience was significant and in a negative direction. Psychological hardiness was not a significant predictor of practical financial experience. Hypothesis 3, which stated that awareness of financial market conditions would influence practical financial experience, was supported because the path was significant and in a positive direction.
Familiarity with financial market conditions and interest in financial markets influenced awareness of financial market conditions. Familiarity with financial market conditions, interest in financial markets, financial market knowledge, and financial market intimidation influenced practical financial experience in our model. Awareness of financial market conditions influenced practical financial experience. As noted in Table 2 the R-square values for awareness of financial market conditions and practical financial experience were 55 percent and 45 percent, respectively.
Our findings suggest that financial literacy workshops should focus on educating young African-American adults on how the markets work. Furthermore, financial literacy workshops should provide practical experience which may be useful in improving financial market interest and awareness. Financial literacy educators may use these findings to revise curriculum so that African-American students will receive more financial market knowledge and practical financial experiences in the form of interactive games and simulations whereby long-term positive and negative impacts of financial decisions can be tested and demonstrated under real-life scenarios. By targeting financial literacy education to the characteristics described in this study, educators can increase market interest among young adults who in turn will share that knowledge with older family members and begin to influence financial decision-making in economically vulnerable populations (Hogarth, Beverly & Hilgert, 2003). This strategy could have a positive impact on individuals, families, communities and the country as a whole.
The findings of this study contribute to the existing body of knowledge because this research identifies factors that may influence awareness of financial market conditions and practical financial experience among younger adults. Another contribution of the current research is that the sample contained a large percentage of Blacks, which adds to the richness of the extant literature.
LIMITATIONS OF THIS STUDY
As is true of most empirical research, the current research has some limitations. First, the cross-sectional design of the study does not allow for causal inferences. Another limitation of the study was that we used a four item measure to capture financial market knowledge of research participants. It is conceivable that a more comprehensive measure of financial market knowledge would yield better findings. All data were collected via self-report measures, which may lead to the problem of common method bias and inflated the predictive relationships. However, as recommended by Podsakoff and Organ (1986) and detailed in the results section, we conducted Harmon's One Factor test, which did not indicate that common method variance was problematic in our structural equation model. Because of our modest sample size, these findings are tentative and we encourage replication.
RECOMMENDATIONS FOR FUTURE RESEARCH
A future area of inquiry would be to examine the behavior of this model when using a more comprehensive measure of financial market knowledge. Another interesting research avenue would be to consider whether credit score is a mediator in this nomological network. We also believe that longitudinal designs are needed in this area to examine the behavior of these constructs to determine whether they wax or wane over time.
When reviewing the barriers to financial education, it was consistently noted that there may be persistent financial apprehensions within minority households, and certain persistently under-resourced communities are likely lacking resources, knowledge, experience and access for themselves and to share with the next generation (Braunstein & Welch, 2002; Ferguson, 2008) The goal of this study was determine how these factors may influence financial market awareness and interest in young adult/late adolescence African-American college students.
The current research investigated the antecedents of awareness of financial market conditions and practical financial experience of university students. Familiarity with financial market conditions and interest in financial markets influenced awareness of financial market conditions. Familiarity with financial market conditions, interest in financial markets, financial market knowledge, and financial market intimidation influenced practical financial experience in our model. Our findings also indicate that interest in financial markets influence one's practical financial experiences. In addition, awareness of financial market conditions predicted practical financial experience. However, financial market knowledge, financial market intimidation, and psychological hardiness were not significant predictors of awareness of financial market conditions in the model.
Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411-423.
Arbuckle, J. L., & Wothke, W. (1995). AMOS 4.0 User's Guide. Chicago: Smallwaters Corporation.
Behrman, J.R, Mitchell, O. S., Soo, C. K., & Bravo, D. (2012). How financial literacy affects household wealth accumulation. American Economic Review, 102(3), 300-304.
Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88, 588-606.
Bollen, K. A., & Stine, R. A. (1992). Bootstrapping goodness-of-fit measures in structural equation models. Sociological Methods and Research, 21, 205-229.
Braunstein, S., & Welch, C. (2002). Financial literacy: An overview of practice, research , and policy. Federal Reserve Bulletin, 445-457.
Chinen, K., & Endo, H. (2012). Effects of attitude and background on personal financial ability: A student survey in the United States. International Journal of Management, 29(1), 33-46.
Davidson, K.(201 "It Would Take 228 Years for Black Families to Amass Wealth of White Familie)s, Analysis Says." Wall Street Journal. N.p., 9 Aug. 2016. Web
Ferguson, N. (2008). The ascent of money: A financial history of the world. New York: Penguin Group.
Ford, M.W., Devoto, S., Kent, D.W., & Harrison, T. (2007). Threat, intimidation, and student financial market knowledge: An empirical study. Journal of Education for Business, 82(3), 131-139.
Gale, W. G., Harris, B. H., & Levine, R. (2012). Raising household saving: does financial education work? Social Security Bulletin, 72(2), 39-48. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/22799137
Goetz, J., Cude, B. J., Nielsen, R. B., Chatterjee, S., & Mimura, Y. (2011). College-based personal finance education: Student interest in three delivery methods. Journal of Financial Counseling and Planning, (706), 27-42. Retrieved from http://6aa7f5c4a9901a3e1a1682793cd11f5a6b732d29.gripelements.com/pdf/vol_22_issu e_1_goetz_cude_nielsen.pdf
Grant, E.(2016). "Forty-Seven Percent of Black Families Have No Emergency Savings." Black Enterprise. N.p., 31 Mar. 2015. Web. 18 Nov. 2016.
Gutter, M.S., & Fontes, A. (2006). Racial differences in risky assett ownership: A two stage model of investment decision making process. Financial Counseling & Planning, 17(2), 64-78.
Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate data analysis. New York: MacMillan.
Hamilton, D., & William Da, Jr. "The Political Economy of Education, Financial Literacy ..." N.p., 25 May 2016. Web. 18 Nov. 2016.
Hirad, A., & Zorn, P. M. (2001). A little knowledge is a good thing: Empirical evidence of the effectiveness of pre-purchase homeownership counseling. Retrieved March 8, 2013, from http://www.freddiemac.com/corporate/reports/pdf/homebuyers_study.pdf
Hogarth, J. M., Beverly, S. G., & Hilgert, M. (2003). Patterns of financial behaviors: Implications for community educators and policy makers discussion draft--February, 2003, 1-28. Retrieved from ihttp://www.federalreserve.gov/communityaffairs/national/ca_conf_suscommdev/pdf/hog arthjeanne.pdf
Joreskog, K.G., & Sorbom, D. (1993). LISREL 8: User's reference guide. Chicago, IL: Scientific Software International.
Kochlar, R., Fry, R., & Taylor, P. (2011). Wealth gaps rise to record highs between Whites, Blacks and Hispanics. Pew Research Center. Retrieved from http://www.persocialfriends.org/2011/07/26wealth-gaps-rise-to-record-highs -between-Whites-blacks-hispanics/
Kosier, J. (2010). The Ariel investments 2010 Black investor survey: Saving and investing among higher income African American and White Americans. Retreived March 8, 2013 from www.arielinvestments.com/repository/func.download/filecatid.219/
Lusardi, A., & Mitchell, O. S. (2011). Financial literacy and retirement planning in the United States. Journal of Pension Economics and Finance, 10(4), 509-525.
Lusardi, A., & Tufano, P. (2009). Debt literacy, financial experiences, and overindebtedness. Cambridge. Retrieved from http://www.nber.org/papers/w14808
Maddi, S.R. (1999). The personality construct of hardiness: Effects of experiencing, coping and strain. Consulting Psychology Journal of Practice and Research, 51, 83-94.
Mandell, L. (2008). The Financial Literacy of Young American Adults. JumpStart coalition for personal financial literacy. Retrieved from www.jumpstart.org/assets/files/2008SurveyBook.pdf
Podaskoff, P.M., & Organ, D.W. (1986). Self -reports in organizational research: Problems and prospects. Journal of Management, 12(4), 531-544.
Robb, C.A., & James III, R.N. (2009). Associations between individual characteristics and financial knowledge among college students. Journal of Personal Finance, 8, 170-184.
Shapiro, T., Meschede, T., & Osoro, S. (2013). The roots of the widening racial wealth gap: Explaining the black-white economic divide. Waltham, MA: The Institute on Assets and Social Policy, Brandeis University.
Sherraden, M. S. (2010). Financial capability: What is it, and how can it be created? St. Louis.
Schuchardt, J., Hanna, S.D., Hira, T.K., Lyons, A.C., Palmer, L., & Xiao, J.J. (2009). Financial literacy and education research priorities. Journal of Financial Counseling & Planning, 20(1), 84-95.
Sorid, D. (2007). Employers discover a troubling racial split in 401(k) plans. The Washington Post. Retrieved March 8, 2013, from http://www.washingtonpost.com/wp-dyn/content/article/2007/10/13/AR2007101300073_pf.html
Steiger, J. H., & Lind, J. C. (1980). Statistically-based tests for the number of common factors. Paper presented at the Annual Meeting of the Psychometric Society, Iowa City, IO.
U.S. Department of Commerce. (2011). United States Bureau of the Census State & County Quick Facts. Retrieved from http://quickfacts.census.gov/qfd/states/51/5135000.html
U.S. Department of the Treasury. (2013). President's Advisory Council on Financial Capability Final Report President's Advisory Council on Financial Capability January 29, 2013. Retrieved from http://www.treasury.gov/resource-center/financial-education/Pages/Advisory.aspx.
Vitt, L.A., Anderson, C., Kent, J., Lyte, D., Slengenthaler, J., & Ward, J. (2000). Personal finance and the rush to competence: Financial literacy education in the United States. The Fannie May Foundation Institute for Socio-Financial Studies.
Weissmann, J. (Ed.). (2014, December 15). The Wealth Gap Between Blacks and Whites Is Even More Enormous(and Shameful) Than You Think. Retrieved from http://www.slate.com/blogs/moneybox/2014/12/15/the_black_white_wealth_gap_it_s_bi gger_than_you_even_think.html
Williams, D., Grizzell, B., & Burrell, D. (2011). An applied case study analysis of potential societal importance of financial literacy education for African American and Latino American adolescents. International Journal of Interdisciplinary Social Sciences, 6(3), 245-260. Retrieved from http://iji.cgpublisher.com/product/pub.88/prod.1436
Ruby L. Beale
Simone O. Heyliger
Ulysses J. Brown, III
Chevanese S. Brown
Savannah State University
Ruby L. Beale is a professor and Chair of Business Administration at the Hampton University's School of Business. Dr. Beale earned her Ph.D. from University of Michigan, Ann Arbor and is the author and co-author of several articles and books. She is the Co-PI of a grant in Financial Literacy.
Ulysses J. Brown, III is professor of management in the College of Business Administration at Savannah State University. Dr. Brown earned his Ph.D. from Jackson State University. His research addresses management education, organizational performance in military units and propensity for military service.
Simone O. Heyliger is an associate professor in the School of Pharmacy at Hampton University. Dr. Heyliger earned her Ph.D. from Florida A & M University in Tallahassee and is the author and co-author of several articles.
Breanna Logue is a graduate student who is currently enrolled in the Masters of Business Administration Program in the Hampton University's School of Business.
Chevanese S. Brown is an assistant professor in the College of Business Administration at Savannah State University. She earned her Ph.D. from Louisiana State University, Baton Rouge. Dr. Brown is a certified practitioner for the KAI (Kirton's Adaption and Innovation Inventory). Her research interests are in cognitive styles, creativity, management education, and entrepreneurship.
Caption: Figure 1 Hypothesized Model
Table 1 Means, Standard Deviations, and Pearson Zero-Order Correlations Variables Mean s.d. 1 3 4 5 6 1. AFMC 21.22 5.96 2. PFEX 14.40 3.22 518 ** 3. FWMC 37.15 11.11 .661 ** .387 ** 4.IFMA 25.04 6.11 .454 ** .432 ** 255 ** 5. FMKN 33.62 23.82 .001 .121 .011 .092 6. FMIN 25.21 6.49 -.113 -.103 -.135 -.132 -.181 * 7. PSYH 14.57 4.14 .105 .042 .117 .117 0.099 Variables 7 1. AFMC 2. PFEX 3. FWMC 4.IFMA 5. FMKN 6. FMIN 7. PSYH .090 * p < .05 ** p < .01. AFMC=Awareness of Financial Market Conditions; PFEX= Practical Financial Experience; FWMC = Familiarity with Market Conditions; IFMA = Interest in Financial Markets; FMKN = Financial Market Knowledge; FMIN = Financial Market Intimidation; PSYH = Psychological Hardiness. Table 2 Unstandardized Path Coefficients for the Model Parameter Path T-Value Coefficient A. Awareness of Financial Market Conditions 1. Familiarity with Financial Market Conditions 0.32 10.60 * 2. Interest in Financial Markets 0.33 6.11 * 3. Financial Market Knowledge -0.01 -.33 4. Financial Market Intimidation -0.04 -0.82 5. Psychological Hardiness 0.01 0.13 B. Practical Financial Experience 1. Familiarity with Financial Market Conditions 0.08 1.97 * 2. Interest in Financial Markets 0.19 4.71 * 3. Financial Market Knowledge 0.12 2.32 * 4. Financial Market Intimidation -0.09 -3.00 * 5. Psychological Hardiness 0.02 0.45 6. Awareness of Financial Market Conditions 0.20 3.57 * Parameter [R.sup.2] A. Awareness of Financial Market Conditions 55% 1. Familiarity with Financial Market Conditions 2. Interest in Financial Markets 3. Financial Market Knowledge 4. Financial Market Intimidation 5. Psychological Hardiness B. Practical Financial Experience 45% 1. Familiarity with Financial Market Conditions 2. Interest in Financial Markets 3. Financial Market Knowledge 4. Financial Market Intimidation 5. Psychological Hardiness 6. Awareness of Financial Market Conditions * p < .05
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|Author:||Beale, Ruby L.; Heyliger, Simone O.; Logue, Breanna; Brown, Ulysses J., III; Brown, Chevanese S.|
|Publication:||International Journal of Business, Accounting and Finance (IJBAF)|
|Date:||Dec 22, 2016|
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