FACTORS INFLUENCING BEHAVIOR OF MUTUAL FUND INVESTORS IN BENGALURU CITY - A STRUCTURAL EQUATION MODELING APPROACH

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1 Special Issue for International Conference on Business Research, Dept of Commerce, Faculty of Science and Humanities SRM Institute of Science & Technology, Kattankulathur, Tamilnadu. FACTORS INFLUENCING BEHAVIOR OF MUTUAL FUND INVESTORS IN BENGALURU CITY - A STRUCTURAL EQUATION MODELING APPROACH 1 MAHESH KUMAR.T, 2 Dr. M. JEGADEESHWARAN 1 Assistant Professor, Department of Commerce, FSH, SRM IST, Kattankulathur Assistant Professor, School of Commerce, Bharathiar University, Coimbatore Abstract- Development of an economy necessarily depends upon its financial system and the rate of new capital formation, which can be achieved by mobilizing savings and adopting an investment pattern. Savings form an important source of capital formation. A mutual fund is an ideal investment vehicle for today s complex and modern financial scenario. It appoints professionally qualified and experienced staff that manages each of these functions on a full time basis. The large pool of money collected in the fund allows it to hire such staff at a very low cost to each investor. Hence, the present study is such an attempt to find out the factors influencing behavior of mutual funds investors in Bengaluru City. The main aim of the study is to develop a regression model for escalating level of awareness, behavior and problems of investors towards mutual funds. The tools used for this study were regression analysis and SEM using Smart PLS. The study concluded that the model fit gives wisdom to the mutual fund companies, which are in business of making the schemes to the investors. The impact of the model and the way it is structured provides a clear depiction to the industry the importance of the factors and benefits of interweave. Keywords: Behavior, Attitude, Mutual Funds, Regression Analysis, SEM Approach. INTRODUCTION Investing in various types of assets is an interesting activity that attracts people from all walks of life with respect to their occupation, economic status, education and family background. When a person has more money than he/she requires for current consumption, he/she would be coined as potential investor. The investor who is having extra cash could invest it in securities or in any other assets like gold or real estate or could simply deposit it in his/her bank account. At present, a wide variety of investment avenues are open to the investors to suit their needs and nature. Knowledge about the mutual funds enables the investors to choose investment intelligently. The required level of return and the risk tolerance decide the choice of the investor. REVIEW OF LITERATURE P.Sasirekha and U.Jerinabi (2015) 1 were conducted a study to find out the level of awareness and attitude towards investment and risk with regards to information technology professionals in Coimbatore city. The sampling technique adopted for the study was multistage sampling with the sample size of 482 IT professionals. The study was based on both primary and secondary data. ANOVA and chi-square were used for analysis. Hence, the study concluded that the level of awareness for individuals in IT professionals was only at medium level, because they are not professional investors. Sreelatha Reddy and Lalitha Narayanan (2015) 2 in their paper studied the awareness and preferences of working women as investors for different investment options available to them. The main objective of the study is to found out the difference in perception of investors in the decision of investing on the basis of risk and return. The 246 respondents were chosen by the convenient sampling and the data were analyzed using chi-square test, ANOVA, factor analysis, regression analysis, etc., the study observed that among all the investment avenues, investments in Provident fund followed by Post office MIS are considered to be the safest and most preferred by the respondents. Neha S Shukla (2016) 3 the study aims to measure the investment pattern of individuals had been made about investors preference towards investment avenues and the study focused on the salaried personnel only. The descriptive research design was used by the researcher, both primary and secondary data sources were used. For the purpose of study total of 100 respondents had been studied with the convenience sampling method. It concluded that different respondents invest in different avenues, it was evident that they tend to invest much in fixed deposits, post office schemes, gold and silver. M.Jegadeeshwaran & Mahesh Kumar.T (2017) 4 in their study they explored the growth and performance of Mutual Funds with its different schemes and evaluation of Mutual Fund investments with the help of analyzing the data such as Assets Under Management, Net Resources mobilized by Mutual Funds etc.., The tools used such as CAGR, ANOVA, t-test and Regression. They found out the relationship between the UTI and other Mutual Fund Institutions. Hence, the study concluded that the performance in the Mutual Funds of AUM attaining positive growth and total resources mobilized by Bank sponsored and FI sponsored having such impact in the growth of Indian Mutual Fund Industry. M.Jegadeeshwaran and Mahesh Kumar.T (2018) 5 their study aimed to make an analysis of the factors influencing behavior of IT company employees through the data collection from the sources of information on the various schemes of savings, their income level of savings. The select IT company employees in Bengaluru had been taken for the study; the tools such as Reliability analysis, Factor analysis and Regression analysis have been used to analyze the data. They found that the factors such as Return and Tax Savings have positive relationship with Attitude. Tax Savings has positive impact on Attitude which means the tax savings cause impact in Attitude. Return has minimum relationship with Attitude which implies there is low response between the changes in the Mutual funds having diversified portfolio gives better returns and Mutual Funds give higher return than other investments. STATEMENT OF THE PROBLEM Mutual funds act as a gateway to enter into big companies hitherto to an ordinary investor with his small International Journal of Research in Engineering, IT and Social Sciences Page 61

2 investment. Mutual fund companies have a number of schemes. The investors decision making, investment strategy, expectations etc are closely related to the behavior of investors. Mutual fund market is highly influenced by this behavior and attitude of investors. In India, though the mutual fund industry has been in existence since 1964 (with the establishment of UTI), no major study has been done regarding the investors behavior towards performance of mutual funds. Hence, this study has made an attempt to examine the investors attitude and behavior towards performance of mutual funds. OBJECTIVES OF THE STUDY To analyze the reasons for attitude and factors influencing behavior To develop a regression model for escalating level of awareness, behavior and problems of investors towards mutual funds. METHODOLOGY OF THE STUDY Collection of data The primary data of this study were collected from the investors of IT Company employees in Bengaluru City with the help of well structured questionnaire. This study is developed to understand the investment behavior of the respondents towards mutual funds. Sampling method Purposive sampling method was adopted to analyze the behavior of investors towards mutual funds in Bengaluru city. By applying Krejice Morgan s sample determination method, 384 respondents were selected. 32 investors from 12 mutual fund companies make the total sample size of 384. Tools used for analysis The primary data have been analyzed by using the statistical tools like ANOVA, Regression analysis and Structural Equation Modeling. ANALYSIS AND INTERPRETATION Regression Analysis on the Attitude and Factors Influencing Behavior Table 1 - Model summary of Attitude and Factors Influencing Behavior Adjusted R Std. Error of Model R R Square Durbin-Watson Square the Estimate a a. Predictors: (Constant), Tax Savings, Future, Return, Investment b. Dependent Variable: Attitude The above table 1 depicts model summary for impact of Factors Influencing Behavior on Attitude. When Attitude is a dependent variable, R = which means that there is a very strong relationship. R-square is indicating that 64.0 per cent of performance variation is accounted for the combined linear impact of independent variables. Adjusted R square value is 0.636, implying that the model has accounted for 63.6 per cent of the variance in the criterion variable. Table 2 - Coefficients of Factors Influencing Behavior on Attitude The above table 2 shows the coefficients for impact of Factors Influencing Behavior on Attitude. It implies that Investment and Tax Savings are significant at 5 per cent significance level. Beta value shows that Investment Return and Tax Savings have positive relationship with Attitude. Tax Savings has positive impact on Attitude which means the tax savings cause impact in Attitude. Return has minimum relationship with Attitude which implies there is low response between the changes in the Mutual funds having diversified portfolio gives better returns and Mutual Funds give higher return than other investments. Structural Equation Modeling Structural Equation Modeling (SEM) is a family of statistical models that seek to explain the relationship among multiple variables. It examines the structure of interrelationships expressed in a series of equations, similar to a series of multiple regression equations. These equations depict all of the relationships among the constructs (The Dependent and Independent Variables) involved in the analysis. (Hair B. B., 2013). Outer Model Assessment (Measurement Model) The assessment of the measurement model focus on the reliability and validity of each latent construct for the reflective and formative constructs respectively. The reflective model evaluation, the three constructs namely, Awareness, Attitude and Problems are assessed by their indicator reliability, internal consistency, convergent validity, discriminant validity (Hair B. B., 2013). The formative model evaluation, construct as Behavior is assessed with its multicollinearity (VIF indices), outer weights, t statistics. International Journal of Research in Engineering, IT and Social Sciences Page 62

3 Outer Model Assessment for Reflective Constructs The reflective constructs of study namely, Awareness, Problems and Attitude are assessed. Construct Awareness Problems Attitude Test Factor loading Aware Aware Prob Prob Prob Atti Atti Atti Table 3 - Measurement of Reflective Constructs Internal Indicator Convergent Consistency Reliability Validity Reliability AVE Note Aware 6 - Mutual fund reduces risk by diversification. Aware 17 - Earning returns through equity scheme are tax free if investor holding more than a year. Debt scheme tax will be vary based on the holding period. Prob 4 - It is difficult to remember loads laid by different mutual fund houses. Composite Reliability (R 2 ) Reliability Cornbach s Alpha Discriminant Validity Sq.Root of AVE Prob 6 - It is difficult to recognize fund reputation. Prob 16 - It is difficult to get clarity about funds investment portfolio. Atti 3 - It is profitable. Atti 5 - It postpones the joy of today to an uncertain tomorrow. Atti 6 - It is a tough task but it is a must. Table 4 Discriminant Validity Sqrt of AVE should be > Correlations of latent variables Attitude Awareness Problems Sq.Root of AVE Attitude Awareness Problems The Adjusted R 2 value is 62% which explains that the predictors of the model namely, Awareness, Factors influencing behavior and problems together contribute up to 62% of the dependent variable Attitude. Path Table 5 Loadings (to be referred for reflective) Path Co-efficient t-statistics (original sample (0)) Reflective Constructs Weights (to be referred for constructive) Path Coefficient t-statistics International Journal of Research in Engineering, IT and Social Sciences Page 63

4 Aware17 Awareness Aware 6 Awareness Prob 16 Problems Prob 4 Problems Prob 6 Problems Atti 3 Attitude Atti 5 Attitude Atti 6 Attitude Investment Behavior Tax savings Behavior From the above table 5, it is inferred that the t- statistics for both reflective constructs paths and formative construct path are significant as their t-values are greater than 1.96 for 5 percent level of significance. Hence, the model developed supports the theory with the statistical proof. Table 6 Calculation of R 2 effect value and Q 2 effect value R Square included Q Square included Awareness Q Square not to be calculated for formative constructs (Hair 2003) Problems Attitude Behavior NA For Attitude R Square excluded Q Square excluded f 2 q 2 Attitude Behavior For Behavior R Square excluded Q Square excluded f 2 q 2 Behavior Investment Behavior - Tax savings Table 7 Consolidated table showing f 2 and q 2 endogenous constructs Awareness Problems Attitude f 2 q 2 f 2 q 2 f 2 q 2 Awareness Problems Attitude Behavior Dependent Variable Attitude Table 8 the effect size - consolidated table Independent f 2 f 2 effect q 2 q 2 effect Variable Awareness Large Large Problems Medium Large Behavior Small NA NA International Journal of Research in Engineering, IT and Social Sciences Page 64

5 INTERPRETATION REPORTING THE INNER MODEL Adjusted R-Square: The adjusted R 2 explains the coefficient of determinant and the variance in predicting the overall model. (Ghozali, 2013) (Hair et al, 2013), (W.W.Chin, 2010) suggest that 0.25(weak), 0.50(Moderate) and 0.75(strong) indices. In the current model, the adjusted R-square is 0.62 for Attitude. This means, awareness, problems and factors influencing behavior together explain upto 62% (with higher moderate) of variance of attitude. Effect Size f 2 : Effect size examines how large is the influence of exogenous variable on the endogenous variable. (Cohen, 1992) Suggest 0.02 (weak), 0.15 (moderate) and 0.35(strong) indices. In the model developed, the f 2 effect size for Attitude to Behavior ( slightly moderate), Behavior to Investment ( Medium), Behavior to Tax savings ( small). Effect size for behavior (being formative construct) is not to be calculated. (Hair et al, 2014) Predictive relevance (Q 2 and q 2 ): (Ghozali, 2013) (W.W.Chin, 2010) Q 2 >0 represents the model has predictive relevance with model verification as 0.02(weak), 0.15(moderate) and 0.35(strong) indices. In the model developed the q2 for attitude - awareness ( large) and attitude problems ( large). The predictive relevance Q square is not to be calculated for behavior being a formative endogenous construct. (Hair et al, 2014). t- statistics: Boot strapping is applied for the significance of the path coefficient with two tails of 5 % level of significance. The t statistics for all the path coefficients are greater than 1.96 confirming the significant path relationship with the constructs. Redundancy: (Ghozali, 2013) (W.W.Chin, 2010) (Hair et al, 2014) suggests the (small), (0.25 (moderate), (big) model fit for the level of endogenous variable. In the model developed, the Redundancy scores for Awareness ( large fit), Problems ( Moderate fit) and Attitude ( Large fit) show casing the overall model fit of the model developed. DISCUSSION AT THE MODEL The current study is aimed at developing a model for escalating the stay of behavior of investors. The coefficient of determination, R 2 is 0.62 for Factors influencing behavior exert a significant high positive impact on attitude (b=0.785, p<0.05), awareness has a significant negative impact on attitude (b= , p<0.05) and problems has a significant positive impact on behavior (b=0.570, p<0.05). Further, problems exert a significant positive impact (b=0.080, p<0.05) on attitude, awareness show a significant positive impact (b=0.091, p<0.05) on behavior. Hence it is concluded that there is negative relationship between the awareness and attitude, there is a positive relationship between the problems and attitude and finally there is a highly positive relationship among behavior towards attitude. There are enormous problems faced by every investor towards mutual funds. This result addresses a common opinion, that investing in mutual funds belongs to the complex financial matters, that most people do not feel comfortable or literate enough with. General willingness and especially plans to invest in mutual funds will be lower for individuals that have low conviction and self-efficacy to make the appropriate financial decisions and to select the right mutual funds compared to individuals that fully trust in their abilities. Again, the link to attitude is obvious: once an individual perceives himself in control of the financial decisions and able to select the right mutual funds, he will likely feel more comfortable with investing and have a more positive attitude on this activity. FINDINGS BASED ON REGRESSION ANALYSIS It indicates that Investment and Tax Savings are significant at 5 per cent significance level. Beta value shows that Investment Return and Tax Savings have positive relationship with Attitude. Tax Savings has positive impact on Attitude which means the tax savings cause impact in Attitude. Return has minimum relationship with Attitude which implies there is low response between the changes in the Mutual funds having diversified portfolio gives better returns and Mutual Funds give higher return than other investments. FINDINGS BASED ON MODEL BUILDING Indicator Reliability: It is evident that the individual factor loadings for the three reflective constructs awareness, problems and attitude are greater than 0.60 confirming the indicator reliability of the factors. Internal consistency: It is evident that internal consistency of the three reflective constructs awareness (0.886), problems (0.779) and attitude (0.870) confirming the good internal consistency. The reliability of the measures by calculating the Cronbach s alpha is also found to be greater than the prescribed limits with awareness (0.742), problems (0.713) and attitude (0.775). Convergent Validity: It is evident from the table that the AVE scores of awareness (0.795), problems (0.540) and attitude (0.690) are greater than the prescribed limits confirming the good convergent validity and explaining that the items converged well on their respective constructs. Discriminant Validity: It is evident that the square root of AVE for awareness (0.8916), problems (0.7348) and attitude (0.8306) are greater than the inter-correlation loadings of the three constructs confirming the constructs differ well from each other. SUGGESTIONS 1. Mutual funds may provide loan facility to investors against mutual fund units in order to attract more customers. 2. The use of e-commerce and robot - advisory platforms as mutual fund distribution channels would help increase the penetration of the mutual funds amongst young tech - savvy investors. 3. Mutual fund companies should avail technology disruption to the investors. Because, it is going to play a major role in increasing awareness enabling distribution and simplifying the investment process. CONCLUSION The model fit gives wisdom to the mutual fund company, which are in business of making the schemes to the investors. The impact of the model and the way it is structured provides a clear depiction to the industry the importance of the factors and benefits of interweave. The evidence from the data analysis for this model is that the factors when identified and related as given in the model, provides an opportunity to the organization and investors to acquire the best of successful new business solution to International Journal of Research in Engineering, IT and Social Sciences Page 65

6 mutual fund schemes. The SEM approach shows that there exists relationship between the factors. The interaction has resulted in a complex but interesting framework. This work facilitated in listing, integrating and understanding the relationship of the factors influencing behavior to the model development. In a nutshell this work has identified the relationships of the listed factors and its impact on successful new model development. The structural equation modeling has been used to understand the interactions with factors. REFERENCES 1. Sasirekha.P and U.Jerinabi, Investor s attitude towards investment and risk Indian Journal of Applied Research, vol:5, issue 9, Sep 2015, ISSN X, p.p Sreelatha Reddy and Lalitha Narayanan, Investment pattern of working women in the twin cities of Hyderabad and Secunderabad - A Study, ASIAN Journal of Management Research, vol 6, issue 1, 2015 ISSN (online) p.p Neha S Shukla, Investment preferences towards investment avenues with special reference to salaried personnel in North Gujarat Region, IJSART - vol 2, issue 1, Jan 2016, p.p Jegadeeshwaran.M & Mahesh Kumar.T, A Study on Growth and Performance of Mutual Funds in India, Indian Journal of Applied Research, Vol.7, Issue 8, Aug 2017, ISSN X, IF: 4.897, IC Value: 79.96, p.p : Jegadeeshwaran.M and Mahesh Kumar.T, A Study on Factors Influencing Behavior of Investors towards Mutual Funds (With Special Reference to IT Company Employees in Bengaluru City), International Journal of Creative Research Thoughts (IJCRT), ISSN: , Volume - 6, Issue: 2, April 2018, IF: 5.97, p.p: International Journal of Research in Engineering, IT and Social Sciences Page 66