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Research Journal of Finance and Accounting ISSN 2222-1697 (Paper) ISSN 2222-2847 (Online) Vol.11, No.3, 2020 www.iiste.org Determinants of Investment Intention in Micro and Small Enterprises Among Business College Students in East Gojjam Zone Simon Nahusenay Ejigu Assistant Professor in Accounting and Finance College of Business and Economics, Debre Markos University Yichilal Simegn Filatie Lecturer in Accounting and Finance College of Business and Economics, Debre Markos University Abstract This study examines factors influencing the investment intentions in MSE among business college students in East Gojjam Zone. A conceptual frame work was designed by integrating seven constructs from theory of planned behavior (Ajzen, 1991), investment decisions predicting model (Azwadi, 2011) and previous studies. Accordingly, attitude, subjective norms, perceived behavioral control, perceived risk, perceived return, perceived trust and financial literacy were taken as predictors of investments intentions in micro and small businesses. The study used a self-administered questionnaire of a sample of 254 final year students of higher educational institutions under the areas of business during 2017/18 academic year. The sample was drawn from six higher educational institutions operating in East Gojjam zone using stratified sampling technique. Statistical analysis was conducted using SPSS version 20.0. In this study correlation analysis was carried out to show the direction of relationships among the dimensions included in the model. Moreover, multiple regression analysis was conducted to determine the predictive values of the constructs. The findings revealed that financial literacy, perceived behavioral control, perceived return, attitude, perceived trust and perceived risk were significant predictors of student’s intention to invest in the micro and small enterprises. Subjective norm was not statistically significant in affecting intention though it has a negative relationship with intention to invest. Finally, it is recommended Colleges, universities and MSE development agency have to take valuable efforts by conducting training on investment alternatives and benefits and entrepreneurial workshop programs to students to change their attitude and develop positive and risk taking behavioral intention towards investment and entrepreneurial endeavor and make them to realize the importance of self-employment. Keywords: Determinants, Business students, investment intention, attitude, MSE DOI: 10.7176/RJFA/11-3-02 Publication date: February 29th 2020 1. Introduction 1.1. Background of the study Investment behavior is critical to an individual’s future and that decision may be contingent on many factors. It has been argued that attitudes among other variables can predict the investment decision process (East, 1993). Prior research has suggested that the improvement of education in financial management significantly correlates with decision-making on critical investment issues (Chen and Volpe, 1998). For example Chen and Volpe (1998) deduce that an individual’s level of financial knowledge influences their opinions and impinge on their decisions. Micro and Small Enterprises here after (MSEs) are one of the institutions given recognition in the country’s industry development plan and is the fact that it serves as vehicles for employment opportunities at urban center and as it underpin the economic development. Thus they should be given prior attention as they are important and serve for sustainable source of job opportunities to our country. Ethiopia has prioritized on MSE development for economic growth, employment generation and building an industrial economy. To this end, in 1997 the government has designed a National MSEs development and promotion strategy which facilitates and paves the ground for the growth and development of the sector. The strategy was revised in 2010/11 with renewed interests and more ambitious targets on employment and number of entrepreneurs and transition to medium size level. The primary objective of the strategy framework was to create a favorable environment for MSEs so that MSEs could facilitate economic growth, create long-term jobs, strengthen cooperation between MSEs, provide the basis for medium and large scale enterprises and promote export. In this strategy framework, the government prioritized those enterprises having features like manufacturing and processing (Berihu, Abebaw, and Biruk, 2014) Empirical reviews of Lusardi and Mitchell (2006) revealed that many persons did not have the adequate knowledge of basic economic concepts required to make investment decisions. Thus, there is a need to conduct 12 Research Journal of Finance and Accounting ISSN 2222-1697 (Paper) ISSN 2222-2847 (Online) Vol.11, No.3, 2020 www.iiste.org research on factors, other than knowledge, that could influence investment intentions. This study will look at factors influencing the investment intentions of business college students by applying Ajzen’s (1991) theory of planned behavior, Azwadi’s (2011) Investment decisions predicting model and financial literacy theory (from prior studies). 1.2. Statement of Problem Despite the government improves SME as a means for creating job opportunities, there are 1.4 million unemployed youth in the country. From this amount of unemployed youth, graduate unemployed accounts 50%. From this around 30% are business graduates (CSA, 2014). 50, 000 Ethiopian graduates have just joined the search for the job market. Majority of them will not be employed soon and a good number of them are may be unemployable at all (Mandefro, 2012). According to the International Labor Organization (ILO) currently urban youth unemployment in Ethiopia stands at an appalling 40%. Terrifyingly many of these young Ethiopians who are out of the job market are not only unemployed, but also unemployable due mostly to the poor level of education they have received. The number of college and university graduates who spend the first few years after school looking for jobs has dramatically increased over the past five years. According to the Central Statistics Authority's (2014) report, more than twenty thousand graduates were jobless. With the Ethiopian economy advancing at a snail's pace, the job market could not absorb the relatively skilled human resources, thereby leaving tens of thousands people at the crossroads. But in the real world business students learn more about entrepreneurship and investment areas and then are expected to be professionals of business decision making. On the other hand, business students in various private colleges and public universities are expected to learn about investment and entrepreneurship equally. Therefore, this study was addressed the following research questions. 1. How is the intention of business college students towards whether invest in SME to be self-employed or be employee of an organization? 2. To what extent Attitude, Perceived Risk, Subjective Norms, Perceived Return, Perceived Trust, Financial Literacy and Perceived Behavioral Control determines business college students’ investment intention in SME? 1.3. Objectives of the study The objective of this study is to assess the determinant factors of investment intention in micro and small enterprises among business college students in east Gojjam zone. Specifically this study is aimed to: 1. Examine business college students’ intention whether to invest in SME to be self-employed or be employee of an organization. 2. Evaluate the influence of Attitude, Perceived Risk, Subjective Norms, Perceived Return, Perceived Trust, Financial Literacy and Perceived Behavioral Control on business college students’ investment intention in new micro and small enterprises. 1.4. Scope and limitation of the study Although wide range of variables were expected to be studied, this study contemplates on examination of the influence of attitude, perceived behavioral control and subjective norms from theory of planned behaviour (TPB), perceived risk, perceived trust, perceived return from investment decisions predicting models (IDPM) and financial literacy from previous studies on business students’ investment intention in new MSEs. The study was conducted in business colleges found in east Gojjam zone, using students as the respondents. It does not survey all students in colleges but only those in business related students. The study was focused on final year level 3, level 4 and first degree graduating students of each Business College located in east Gojjam zone. 1.5. Significance of the study This study may benefit both theory and practices. First, researchers in this direction have been neglected and most of it had been done in the culture of other world countries which may not be directly applied to developing countries like Ethiopia. Therefore, an attempt directed at examining the determinant factors of the investment intention of business students (as a potential investor) in this regard can be a one step closer in increasing the awareness of the concerned bodies. Results reached from this study are also expected to give important messages to policy makers in education. Finally, the study can pave the way for future study in the area. 2. Review of Related Literatures 2.1. Theoretical Framework It is obvious that no one is willing to accept any risk toward any financial issues. From this point, we should study carefully and deeply how potential investors think toward investment, as well as, we should know the 13 Research Journal of Finance and Accounting ISSN 2222-1697 (Paper) ISSN 2222-2847 (Online) Vol.11, No.3, 2020 www.iiste.org factors that influence potential investors to make decision on investment. There had been theories and models developed by scholars to predict the potential investors’ intention in making investment decisions. Furthermore, the investor behavior predicting models and theories studied investment features and their effect on investors’ behavior. Three influential theories and models are reviewed in this study: theory of reasoned action (Fishbein & Ajzen, 1975), Investment Decisions Predicting Model (Azwadi, 2011) as well as the theory of planned behavior (Ajzen, 1991). 2.1.1. Theory of Reasoned Action (TRA) Even though not concentrating in investment decisions distinctively, the Theory of Reasoned Action has been commonly used to explain behavioral intentions. The original theory was developed by Fishbein & Ajzen (1975). According to this theory, Intention is influenced by attitude and subjective norms. On the other hand, subjective norm was explained as “an individual’s perception of whether the behavior should be performed”. This would be driven by the motivation that an individual has to act in accordance with opinions from people who are important to the individual (Fishbein and Ajzen, 1975). Figure 2.1 Theory of Reasoned Action (TRA) (Fishbein and Ajzen, 1975). 2.1.2. Theory of Planned Behavior (TPB) Subsequent to the original TRA theory, Ajzen (1991) extended the TRA and establish theory of Planned Behavior. Ajzen argued that behavioral intention can find expression in behavior only if the behavior in question is under volitional control. In many instances behavior would be influenced by non-motivational factors such as availability of resources. This is called perceived behavioral control according to Ajzen. Therefore, attitude, subjective norms and perceived behavioral control are directly influencing the intention to invest (Ajzen, 1991). Figure2-2: Theory of Planned Behavior (Ajzen, 1991) According to Azjen’s (1987, 1991) theory of planned behavior (TPB) there are three predictors of intention. These are attitude toward the behavior, subjective norms, and the degree of perceived behavior control. He explains that attitude towards a behavior is a reflection of the individual’s appraisal of the behavior, and the appraisal may be placed along a continuum running from favorable to unfavorable. He indicates that the more favorable the appraisal the greater the intention. 2.1.3. Investment Decisions Predicting Model Investment Decisions Predicting Model (IDPM) is also a derivative of the theory of reasoned action. IDPM was developed to predict Individual Investors’ Intention to invest or to forecast investment behavior of individual investors for business decisions. According to IDPM, among different groups of investors, individual potential investors are generally less able to objectively evaluate risks and returns associated with a new business, and tend to be emotionally biased in their investing decisions. Therefore their decisions may be formed as a result of 14 Research Journal of Finance and Accounting ISSN 2222-1697 (Paper) ISSN 2222-2847 (Online) Vol.11, No.3, 2020 www.iiste.org perceived risks and returns, which `mean that attitude towards investment is jointly influenced by three main constructs; perceived risk (PRSK), perceived returns (PRTN) and perceived trust (PTRS). (Azwadi, 2011). Figure 2.3: Investment decisions Predicting Model (Azwadi, 2011) 2.2. Financial literacy The results indicated that the financial literacy of the UAE investors is far from the needed level. The financial literacy level was found to be affected by income level, education level and work place activity. High income respondents hold high educational degrees, and those who work in the field of finance/banking or investment had as expected higher financial literacy level than others. Specifically, women have lower level of financial literacy than men. Finally, the results indicate there is a significant relationship between financial literacy and investment decision (Kalli &Hussein, 2008). 2.3. Review of Empirical Studies According to Philmore Alleyne and Tracey Broome (2010) Factors Influencing Investment Decisions of Potential Investors include Investment Intentions, Attitudes, Subjective Norms, Perceived Behavioral Control, Risk Propensity. Prior research has shown that students are not receiving sound education on financial investments and as a result have inadequate knowledge on investing (HSR 1993). Mandell (1997) felt that students were leaving school unprepared to make important financial decisions. Volpe, Chen and Pavlicko (1996) found that university students scored on average 44% in their test on knowledge of investments, thus suggesting inadequate knowledge. Ashen (1991) proposed the theory of planned behaviour by adding another factor, perceived behavioral control. The theory of planned behaviour posits that attitudes, subjective norms and perceived behavioral control are determinants of behavioral intention and actual behaviour. Intention is assumed to be a necessary condition for voluntary action, which may be triggered by perceived opportunities (Janzen, 1991). Beck and Ajzen (1991) state that “as a general, the more favorable the attitude and subjective norm with respect to behaviour, and the greater the perceived behavioral control; the stronger should be an individual’s intention to perform the behaviour under consideration” East (1993) applied the theory of planned behaviour to explaining investment decisions. He found that attitudes, subjective norm and perceived behavioral control were significantly related to investment decision. Sitkin and Weingart (1995) developed a 5-item scale for measuring business risk propensity. They argued that risk propensity is a behaviour that evolves as part of experiential learning. Thus, this study seeks to explore whether the theory of planned behaviour, investment decision predicting model and financial literacy can significantly predict intentions to invest among future investors. 2.4. Conceptual framework/integrated research model Based on the available literatures, theories and models, the researchers tried to identify the most important factors that influence investment intention. These factors include: variables of the TPB, IDPM and Financial Literacy. As a result, the research general model consists of the following variables: 15 Research Journal of Finance and Accounting ISSN 2222-1697 (Paper) ISSN 2222-2847 (Online) Vol.11, No.3, 2020 www.iiste.org Figure 2.4: Conceptual Framework of the Study (Developed by the Researchers). 3. Research Methodology This study used a cross-sectional design using a survey questionnaire. The sample was chosen from students of target institutions in a final year business course during 2017/18. Students at these public and private higher institutions served as surrogates for those decision makers in the study. Prior studies have used students as surrogates in decision making (Ashton and Kramer, 1980; Hughes and Gibson, 1989) and (Krueger and Dickson, 1994). All participants were volunteers and received no class credit for participation. In this study, primary data sources were searched to meet the research objectives. Primary data were collected with questionnaire. Questionnaire was distributed to the selected graduating class students of different departments under the area of business and economics. To evaluate the relationship between planned behavior, investment decisions and financial literacy, researchers were formulate the questionnaire based on the literature (e.g. East, 1993; Buchan (2005), Kennedy (2013); and Azwadi, (2011). All variables of TPB and IDPM models Financial Literacy were measured with 5point Likert scale ranging from (1=strongly disagree) to (5=strongly agree). The target population of the study was business decision makers. Business students at the public and private higher institutions served as surrogates for those decision makers in the study (Ashton and Kramer, 1980; Hughes and Gibson, 1989) and (Krueger and Dickson, 1994). To establish the sample frame, a list of level 3, level 4 & degree graduating class students were obtained from the colleges. Accordingly, level 3, level 4 and degree graduating class students of Dimma College, Tropical College, Washera Broad View College, New Man Business College, DMU business & Economics College and GABST College were selected. These institutions were chosen purposively due to their seniority. 3.1. Sampling technique and Sample size determination In this study, Stratified sampling technique was used because the population from which a sample was drawn from different colleges. According to Andy field (2000), the sample size required in regression models is depend on the size of the effect that we are trying to detect. Yogesh (2006), suggested that one should select 1030% of the population for the sample. The researchers took the middle limit (20%) with the assumption that the larger the sample size, the more reliable of the data. Thus, 20% of the total populations of sampled institutions were taken as a sample size and which accounts for 270 respondents. This satisfies the above rule of thumb. 16 Research Journal of Finance and Accounting ISSN 2222-1697 (Paper) ISSN 2222-2847 (Online) Vol.11, No.3, 2020 www.iiste.org Then, the sample size was determined proportionally using: n1/N1σ1 = n2/N2σ2 = ......... = nk /Nkσk Where σ1, σ2 ...and σkdenote the standard deviations of the k strata, N1, N2… Nkdenote the Sizes of the k strata and n1, n2… nkdenote the sample sizes of k strata.The respondents are taken proportionally from each stratum as presented in table 3.1 below. Table 3.1: Sampling distribution among colleges Institution No. of business GC students (n) 463 185 181 172 202 147 1,350 DMU, business & economics college Dimma college New Man college Washera Broadview college Tropical College GABST college Total Total population (N) 1,350 1,350 1,350 1,350 1,350 1,350 Sample (N**) 93 37 36 34 40 30 270 **Ni=n/N(S), Where S is the sample size considered for the study. 3.2. Data analysis The data collected from returned questionnaire were entered into an excel spreadsheet for analysis. The data were sorted to group questions according to applicable constructs under test. In this study, multiple regression analyses were performed using statistical package for social science (SPSS) version 20.0. It is useful to evaluate the predictive power of the TPB and IDPM variables and financial literacy (Baron and Kenny, 1986; Alleyne and Broome, 2010; and Kennedy, 2013). As discussed in the literature review in this study, a framework is developed based on the investment decisions predicting model (IDPM), the theory of planned behavior (TPB) and previous studies (Financial literacy). Thus, parameters for the following functional relationships will be estimated in the following equation: INT = β +β ATT β SNS+ β PBC + β PRR+ β PRT + β PTT + β7FLT + ε 0 1 + 2 3 4 5 6 Where: INT=investment intention of students on MSE,PRR= perceived risk, PRT= perceived return, PTT= perceived trust, ATT= attitude, SNS=subjective norms, PBC= perceived behavioral control, FLT=financial literacy, and ε = is the error term for any missing variable in behavior of human account, assumed to distribute normally with zero mean and σ standard deviation and is independent of the error terms associated with all other observations.β0 , is the intercept value of the regression surface. 4. Results and Discussion This chapter presents the analysis, discussion and inferences made on the basis of the responses obtained. All the data obtained were coded and entered in to SPSS version 20.0 and inferences were made based on the result. Two hundred seventy questionnaires were managed to Business College students located in east Gojjam zone. A total of 254 useable copies of the questionnaire were returned. The percentage of the useable copies of the questionnaire returned was 94 percent. 17 Research Journal of Finance and Accounting ISSN 2222-1697 (Paper) ISSN 2222-2847 (Online) Vol.11, No.3, 2020 www.iiste.org 4.1. Demographic Profile of Respondents (N=254) Table 4.1 Characteristics of respondents Variables Gender Category Frequency Percent Male 199 78.3 Female 55 21.7 Age 18-25 230 90.6 25-30 10 3.9 30 and above 14 5.5 Family Occupation Merchant 26 10.2 Farmer 203 79.9 Government Employee 25 9.8 Education Level Level 3 65 25.6 Level 4 96 37.8 Degree 93 36.6 Future intention To be self-employed by investing in SME 65 25.6 To be employee of any institution 189 74.4 As shown in table 4.1, there were more males than females with a ratio of 78:22 respectively. Majority of the respondents were between the ages of 18-25 years and accounts for 90.6%. Most of their families’ occupation is farming. This table also shows that level 3 (25.6%), level 4 (37.8%) and degree (36.6%) graduating class students during the study period were participating in the study as respondents. From the above table, it also showed business college students’ intention whether to invest in small and micro enterprises to be self-employed or be employee of an organization. As it can be observed from the future job preference category of the table, majority of the respondents (74.4%) have an intention to be employee of any organization whereas about only 25.6% of them intends to be self-employed through investing in small and micro enterprises. Why? This is a question in line with the main objective of this study and determinant factors were discussed in the multiple regression part of this chapter. 4.2. Correlations between Predictors and the Dependent Variable Table 4.2. Correlation table Variables 1. PRk 2. PRr 3. PTt 4. FLc 5. PBC 6. SNs 7. ATT 8. INT 1 Pearson Correlation N Pearson Correlation Sig. (1-tailed) N Pearson Correlation Sig. (1-tailed) N Pearson Correlation Sig. (1-tailed) N Pearson Correlation Sig. (1-tailed) N Pearson Correlation Sig. (1-tailed) N Pearson Correlation Sig. (1-tailed) N Pearson Correlation Sig. (1-tailed) N 1 254 .173** .003 254 .241** .000 254 .118* .030 254 .268** .000 254 .162** .005 254 -.047 .228 254 -.054 .195 254 2 3 4 5 6 7 8 1 254 .514** .000 254 .474** .000 254 .430** .000 254 -.078 .108 254 .368** .000 254 .529** .000 254 **. Correlation is significant at the 0.01 level (1-tailed). *. Correlation is significant at the 0.05 level (1- tailed) (Source: researchers’ computation with SPSS) 18 1 254 .473** .000 254 .453** .000 254 .029 .324 254 .354** .000 254 .501** .000 254 1 254 .478** .000 254 .104* .049 254 .443** .000 254 .617** .000 254 1 254 -.170** .003 254 .503** .000 254 .581** .000 254 1 254 -.242** .000 254 -.105* .048 254 1 254 .525** .000 254 1 254 Research Journal of Finance and Accounting ISSN 2222-1697 (Paper) ISSN 2222-2847 (Online) Vol.11, No.3, 2020 www.iiste.org As it shown in the correlation matrix, each variable is perfectly correlated with itself and so r=1 along the diagonal of the table. Intention to invest is negatively related to perceived risk (with Pearson correlation coefficient of r=-0.054, but it is statistically insignificant, p>0.05) and significant negative relationship with subjective norms (with a Pearson correlation coefficient of r=-0.105, p<0.05). The Pearson correlation matrix also shows a significant positive relationship between perceived return (r=0.529, p<0.01), perceived trust (r=0.501, p<0.01), financial literacy (r=0.617, p<0.01), perceived behavioral control (r=0.581, p<0.01), Attitude (r=0.525, p<0.01) and the intention to invest in micro and small enterprises. 4.3. Multiple regression results In this study, multiple regression analysis was carried out to get the predictive values of the constructs considered. Since the model is developed in such a way that each construct is being affected by other constructs, it is necessary to carry out a separate regression analysis against each variable which are considered to be affected by other variables. This was basically made to determine the linear combination of the constructs. Tables 4.3, 4.4 and 4.5 present the results from the multiple regressions carried out using Attitude, Perceived Risk, Subjected Norms, Perceived Return, Perceived Trust, Financial Literacy and Perceived Behavioral Control as the independent variable and intention to invest as a dependent variable. This was done to determine the best linear combination of attitude for predicting intention to invest in the micro and small enterprises. Table 4.3 model summary (2) Model Summaryb Model R 1 .751 a. b. a R Square Adjusted R Square Std. Error of the Estimate Durbin-Watson .564 .552 .57660 1.837 Predictors: (Constant), Attitude, Perceived Risk, Subjective Norms, Perceived Return, Perceived Trust, Financial Literacy, Perceived Behavioral Control Dependent Variable: Intention to invest ANOVAb Table 4.4 ANOVA table (2) Sum of Squares Df Mean Square F Sig. Regression 105.910 7 15.130 45.507 .000a Residual 81.788 246 .332 Total 187.698 253 Model 1 a. b. Predictors: (Constant), Attitude, Perceived Risk, Subjective Norms, Perceived Return, Perceived Trust, Financial Literacy, Perceived Behavioral Control Dependent Variable: Intention to invest Coefficientsa Table 4.5 coefficients (2) Unstandardized Coefficients Model 1 Standardized Coefficients B Std. Error (Constant) .516 .282 Perceived Risk -.072 .035 Perceived Return .173 .054 Perceived Trust .137 Financial Literacy Perceived Control T Sig. 1.829 .069 -.096 -2.076 .168 3.177 .060 .123 .300 .055 .243 Subjective Norms Attitude Behavioral Tolerance VIF .039 .833 1.200 .002 .632 1.583 2.296 .023 .613 1.631 .304 5.487 .000 .576 1.736 .054 .260 4.509 .000 .531 1.882 -.027 .041 -.031 -.666 .506 .824 1.214 .122 .048 .138 2.566 .011 .612 1.633 19 Beta Co-linearity Statistics Research Journal of Finance and Accounting ISSN 2222-1697 (Paper) ISSN 2222-2847 (Online) Vol.11, No.3, 2020 Model Summaryb Table 4.3 model summary (2) Model 1 a. www.iiste.org R R Square Adjusted R Square Std. Error of the Estimate Durbin-Watson .751a .564 .552 .57660 1.837 Predictors: (Constant), Attitude, Perceived Risk, Subjective Norms, Perceived Return, Perceived Trust, Financial Literacy, Perceived Behavioral Control Dependent Variable: Intention to invest (Source: regression result) From table 4.3, it can be seen that the R Square value for the model showed that 56.4% of the variance in the model can be predicted from the independence variables: Attitude, Perceived Risk, Subjective Norms, Perceived Return, Perceived Trust, Financial Literacy and Perceived Behavioral Control. Table 4.4 gives the ANOVA test on the general significance of the model. As p is less than 0.05, the model is significant. Thus, Attitude, Perceived Risk, Subjective Norms, Perceived Return, Perceived Trust, Financial Literacy and Perceived Behavioral Control significantly predict the dependent variable intention to invest in micro and small enterprises (F=45.507; p<0.05). Table 4.5 showed the standardized beta coefficients. A unit change in the independent variables, Attitude, Perceived Risk, Subjective Norms, Perceived Return, Perceived Trust, Financial Literacy and Perceived Behavioral Control would produce an effect on the dependent variable, intention. From this table, Financial literacy (β=0.304, p<0.01) and Perceived Behavioral Control (β=0.260, p<0.01) had the highest impact on intention. The largest t values for Financial literacy (t=5.487) and Perceived Behavioral Control (t=4.509) and their corresponding low p values (p<0.01 for both) supports the result for financial literacy and Perceived Behavioral Control for which there are high beta coefficients. Perceived return (at 99%), perceived trust and attitude (at 99%) are statistically significant and all have positive influence on intention. Moreover, perceived risk (β=-0.096, p<0.05) and subjective norms (β=-0.031, p>0.05) have negative relationship with intention to invest in micro and small enterprises. This indicates that perceived risk significantly influences intention negatively. But the influence of subjective norms on intention is statistically insignificant. Thus, the model for predicting intention becomes: INT=0.516-0.096PRK+0.168PRT+0.123PTT+0.304FLT+0.260PBC-0.031SNS+0.138ATT Table 4.4 to 4.5 depicts the results of regression analysis of each model; the result shows that intention is individually and co-jointly predicted by perceived risk (β=-0.096, p<0.05), perceived return (β=0.168, p<0.01), perceived trust (β=0.123, p<0.05), financial literacy (β=0.304, p<0.01), perceived behavioral control (β=0.260, p<0.01), subjective norms (β=-0.031, p>0.05;statistically insignificant) and attitude (β=0.138, p<0.05). These variables together explain 56.4% of the variance on intention to invest in micro and small enterprises (coefficient of determination (R2) is 0.564). Hence, hypotheses 1, 4, 6, 8, 9 and 12 were supported. But hypothesis 10 was rejected. Intention to invest has strong relationship with financial literacy which is significant at 99% (β=0.304). This indicates that financial literacy is the most influential factor that affects intention to invest. Based on the regression analysis, perceived return is not predicted by perceived risk (β=0.052, p>0.05) while explaining 26.7% of the variance on perceived return (coefficient of determination is 0.267). Hence, hypothesis 5 is not supported. Whereas, perceived return is predicted by perceived trust (β=0.501, p<0.01) while explain 26.7% of the variance on perceived return. Thus hypothesis 3 is supported. Perceived trust significantly influences perceived risk (β=0.241, p<0.01); it explains the 5.8% of the variance on perceived risk. Hence hypothesis 2 is supported. Perceived return do not significantly predict subjective norms (β=-0.078, p>0.05) while explaining 0.6% of the variance on subjected norms. Hence hypothesis 11 is rejected. Perceived behavioral control is significantly influence by financial literacy (β=0.478, p<0.01) while explaining 22.8% of the variance on Perceived behavioral control (coefficient of determination (R2) is 0.228). Hence hypothesis 12 is accepted. Generally, most of the hypotheses stated are supported and significant at 99% and 95% level of significance. In addition, these hypotheses derived from TPB, IDPM and other previous empirical studies support the various models and empirical studies. 5. Conclusion and Recommendation 5.1. Conclusion This study tried to examine the investment intention of business students to invest in micro and small enterprises and the major determinants for this. The findings showed that majority of Business College students intend to be employee of any organization rather than to be self-employed through investing in small and micro enterprises. Regression analysis was conducted using perceived return, attitude, subjective norms, perceived behavioral 20 Research Journal of Finance and Accounting ISSN 2222-1697 (Paper) ISSN 2222-2847 (Online) Vol.11, No.3, 2020 www.iiste.org control, perceived risk as independent variables and intention as dependent variable, this was basically done to get the best linear combinations of the constructs as well as to get predictive values of individual predictors for testing the hypotheses proposed (Kamel et al., 2011). Most of the hypotheses were found to be acceptable and logical. Most of the findings of this study were conform well to theories and prior studies. The findings revealed that the six factors included in the model (perceived risk, perceived return, perceived trust, attitude and perceived behavioral control) were significant in affecting the business students’ intention to invest in MSE. However, one of the factors included in the model (subjective norms) was not statistically significant in affecting intention though it has a negative relationship with intention to invest. Results also revealed that the construct financial literacy plays the most important role, followed by perceived behavioral control, perceived return and attitude in predicting an individual potential job seeker’s intention to invest in the micro and small enterprises. Hence financial literacy is the dominant factor in predicting behavioral intentions to invest in new micro businesses. 5.2. Recommendations Based on the analysis and conclusion of the study, the researchers forward the following recommendations for administrative bodies, students, colleges and universities.  Graduating class students, as a potential investor, should be encouraged and supported by micro and small enterprises development agency through offering trainings and access to necessary infrastructures.  Students should read and follow the science and try to change their intention from being employees of an organization to self-employed by breaking the social norms, behavioral controls, and peer & family pressures.  Colleges, universities and MSE development agency have to take valuable efforts by conducting training on investment alternatives and benefits and entrepreneurial workshop programs to students to change their attitude and develop positive and risk taking behavioral intention towards investment and entrepreneurial endeavor and make them to realize the importance of self-employment. 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