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A study on the perception of investors towards small saving schemes.
Abstract:
It is very much necessary for institutions offering investment instruments to study about the perception of investors towards various investment instruments because it influences the saving behaviour of investors. Hence, this study attempts to measure the nature of perception of investors using a five-point scale. To have a better understanding, investors are segmented into three groups based on their perception by using cluster analysis. The study has used correspondence analysis, chi-square test, analysis of variance and discriminant analysis to understand the impact of perception on saving behaviour of investors and the factors which determine the perception of investors towards saving instruments.

Key words : Perception of investor, Small saving schemes, Perceptual factors, Segmentation of investors, Determinants of perception.

Article Type:
Report
Authors:
Kasilingam, R.
Jayabal, G.
Pub Date:
07/01/2009
Publication:
Name: Paradigm Publisher: Institute of Management Technology Audience: Academic Format: Magazine/Journal Subject: Business, general Copyright: COPYRIGHT 2009 Institute of Management Technology ISSN: 0971-8907
Issue:
Date: July-Dec, 2009 Source Volume: 13 Source Issue: 2
Geographic:
Geographic Scope: India Geographic Code: 9INDI India
Accession Number:
238426580
Full Text:
Introduction

Perception of investors about saving schemes will have a significant impact on the saving behaviour of people. For example, people who have positive perception about the scheme in which they have invested will continue to invest in the same scheme. Very often, they will start investing on other schemes from the same institutions. People with positive perception might tell good things about the schemes to other people. In fact, they might act as unpaid publicity agents. Hence, it is necessary to study about the nature of perception that exists among investors about saving schemes and institutions offering such instruments.

Review of Literature

Karthikeyan (2001) has conducted research on Small Investors' Perception on Post Office Saving Schemes and found that there was significant difference among the four age groups, in the level of awareness for Kisan Vikas Patra (KVP), National Savings Schemes (NSS), and Deposit Scheme for Retired Employees (DSRE), and the overall score confirmed that the level of awareness among investors in the old age group was higher than in those of the young age group. No difference was observed between male and female investors except for the NSS and KVP. Out of the factors analysed, necessity of life and tax benefits were the two major ones that influence the investors both in semi-urban and urban areas. Majority (73.3 per cent) of investors of both semi-urban and urban areas were very much willing to invest in small savings schemes in future provided they have more for savings.

Gavini and Athma (1999) found that social considerations, tax benefits, and provision for old age were the reasons cited for saving in urban areas, whereas to provide for old age was the main reason in rural areas. Among the post office schemes, Indira Vikas Patra (IVP), KVP and Post Office Recurring Deposit Account (PORD) were the most popular, in both urban and rural areas.

Somasundaram (1998) has found that bank deposits and chit funds were the best known modes of savings among investors and the least known modes were Unit Trust of India (UTI) schemes and plantation schemes. Attitudes of investors were highly positive and showed their intention to save for better future. Nearly two-thirds of the investors were satisfied with their savings. Both income and expenses of a family influenced the level of satisfaction over savings. A large proportion of investors were concerned about their children's well-being. Among the dissatisfied investors, majority were of the opinion that cost of living was too high. The most common mode of investment was bank deposits. However, a shift was noticed from bank deposits to other forms of investment. Almost all the investors had invested in gold and silver. Among several parameters in investing, safety of money was considered to be the most important element. Next, the investors expected regular return from their investments.

National Council of Applied Economic Research (NCAER) (1961) 'Urban Saving Survey' noticed that irrespective of occupation followed and educational level and age attained, households in each group thought saving for the future was desirable. It was found that desire to make provision for emergencies was a very important motive for saving and importance was given next to 'saving for old age'. Among motives for saving, provision for emergencies, old age, and purchase of house occur with same frequencies in all occupational and educational groups. The proportion of households expressing a preference for financial assets increases with the level of education. The preference for financial assets, especially bank accounts and small savings, while rising markedly with education, does not seem to increase with income, except at the lowest end of income distribution. Thus, it would appear that efforts must be taken to popularize financial forms of savings particularly among the less educated members of upper-income group. Profitability seems to be the most important motive for determining saving preference. Safety is another significant consideration for most people and liquidity ranked third.

Securities and Exchange Board of India (SEBI) and NCAER (2000) 'Survey of Indian Investors' has reported that safety and liquidity were the primary considerations which determined the choice of an asset. Ranked by an ascending order of risk perception fixed deposit accounts in bank were considered very safe, followed by gold, units of UTI-US64, fixed deposits of non-government companies, mutual funds, equity shares, and debentures. Households' preference for instruments in which they commonly invested matched the risk perception. Bank deposits, which had an appeal across all income classes, and tax-saving schemes were preferred by middle-income and higher-income groups. There was a correlation between the income levels and investments of households in market-related securities.

Tamilkodi (1983) has stated that small savings schemes have a psychological appeal and it provides an opportunity for ordinary men, women, and even children to park their savings. It reaches a large number of people and covers a wide range of areas. She also suggested that efforts should be taken to simplify the procedure of small savings schemes to suit the needs of illiterate and socially downtrodden people. Further, she suggested an increase in the rate of interest of small savings schemes to meet the challenges of commercial banks.

Jayaraman (1987) has stated that instead of issuing special bonds for unearthing black money the Government of India can encourage investment of black money in various small savings schemes. He further stressed the need to draft the assistance of voluntary agencies at the school and college level for further mobilization of savings.

Arangasami (1992) has observed that more and more dependence on mobilization of resources through small savings will ensure and promote self-reliance. He concluded that the Central government should give proper assistance and encouragement to the small savings agencies, which will be useful not only in mobilization of funds but also for the economic development.

The study by Mukhi (1989) has revealed that NSC has been one of the most popular tax savings instruments in this country. He has stated that contractors and others who have to provide security while bidding for contracts find it extremely convenient to buy NSC and pledge these to the appropriate authorities while earning 12 per cent per annum on the pledged securities. He also stated that the major attraction of NSC is its simplicity. Even the average investor does not have to scratch his head to understand the scheme.

Methodology

The primary data have been collected by conducting survey among teachers working in government colleges and universities in Tamil Nadu using a well-structured questionnaire. The population size was 11,867 and the sample size of 614 was arrived at by using formula n = [Z.sup.2] * p * q * N/ [e.sup.2] * (N-1) + [Z.sup.2] * p * q (Kothari 2004) where n is the minimum sample size required. The 614 sample respondents were selected by using multistage random sampling. The questionnaires were distributed to all 614 selected respondents in person by the researcher. After repeated persuasion only 586 filled in questionnaires were received. For the purpose of final analysis 552 questionnaires were used after rejecting some of the questionnaires which were not completed properly. The non-response rate and rejection rate totally amounts to 10 per cent. The margin of error for the present sample size of 552 is 1.454 per cent. The content validity of the questionnaire was verified by panel validation and criterion validity and construct validity have been tested using correlation analysis. The reliability of the survey instrument was tested using Cronbach alpha method. The alpha value is 0.7763, Hotilins T-squared value is 1179, F value is 113.74 and the significant value is 0.0000. This means that the statements are reliable at more than 99 percentage level of confidence.

Perceptual Factors

To understand the perception of investors about the small saving schemes, twenty-three statements were identified. Each statement describes one aspect of perception. The opinions of investors were collected in Likert five-point scale. Studying all the twenty-three perceptions would have been tedious and, in fact, not necessary also. So factor analysis was used to reduce variables into smaller number of manageable variables by exploring common dimensions available among the variables. The variables which had common response and high correlation were grouped under a common factor. Variables which did not have any significant effect were suppressed. The reduced factors should be distinct from each other.

First, the suitability of data for the purpose of factor analysis was tested using two analyses, namely, KMO test and Bartlett's test of sphericity. The Kaiser-Meyer-Olkin Measure of sampling adequacy is a statistic which indicates the proportion of variance in the variables which might be caused by new factors. High values generally indicate that a factor analysis may be useful with the data. If the value is less than 0.50, the results of the factor analysis probably will not be very useful.

Table 1 shows that the KMO value is 0.791, which signifies that the factor analysis is useful with the data. The chi-square value for Bartlett's test of sphericity is 2491.04 and the significant value is 0.000 which is significant at more than 99 per cent level of confidence. This means that the data are very much suitable for factor analysis.

The next step in the process is to decide about the number of factors to be derived. The rule of thumb is applied to choose the number of factors for which 'Eigen values' with greater than unity is taken by using Principal component Analysis method. The component matrix so formed is further rotated orthogonally using varimax rotation algorithm.

By performing factor analysis, twenty-three variables are reduced into seven component factors otherwise called perceptual factors (Table 2). Each component factor includes some statements which are otherwise called variables. Each component represents perception of investors about one particular aspect of investment variable like investment institutions, and statements under each factor explains the feature of such perceptual factor. The seven perceptual factors which have Eigen values more than unity alone are taken for consideration. The seven perceptual factors represent around 55 per cent of total variance which is very significant and the remaining variance is explained by other factors. The first perceptual factor explains more than 9 per cent of total variance and other six perceptual factors accounts for the remaining 46 per cent of variance.

Development

The list of seven component factors along with their labels and variables (statements along with loading) included under these factors are listed below. Percentage of people agreeing with each perceptual factor and percentage of people who do not agree with it are given in the Table 3.

Convenient Set-up

This is the predominant perceptual factor which describes 9 per cent of total variance. Table 4 gives information about the statements included under this component factor of perception along with their loadings. The table shows that this factor of perception contains variables related to agent's role in mobilizing the savings which has the highest loadings. The other variables included under this factor are related to sufficiency of number of agents and role of post offices in mobilizing savings of people. As all the variables included under this component factor of perception are related to providing convenience to the investor, this factor can be called as convenient set-up. Investors prefer to have convenient arrangements to make investments. They also consider convenience as the most important criterion while evaluating any investment. The convenience may be required while making investment and also at the time of getting regular return and capital redemption at the end. Every investor will have some kind of perception about institutional set up depending on what kind of convenience and inconvenience they have enjoyed during their investment activities.

Around 75 per cent of investors are satisfied with the number of agents available to provide service to them and they also expressed their satisfaction about the services provided by post offices as a small saving collection channel (Table 3). The salaried class investors are satisfied with the existing set-up available for small saving schemes. If the collection on small savings has to be increased, it has to be taken to other sections of investors by providing convenient service to them. Only a small percentage of people have negative perception about arrangements available to mobilize small saving schemes.

Populist Schemes

The second component factor also explains about 9 per cent of total variance. The first two statements (variables) included under this component factor are related to Private Provident Fund (PPF) which is useful to the unorganized sector. The other statements talk about different small saving schemes and the purpose of the government offering those schemes (Table 5). The government is offering saving schemes not only to mobilize fund for its development activities but also to protect the interest of small investors from being cheated away by unscrupulous people. Some of the schemes like PORD and Post Office Time Deposit (POTD) are really meant to help small investors. PPF is a provident fund scheme meant for unorganized people. The government is giving attractive interest and tax incentive mainly to help the investing public. The statements related to these perceptions are grouped under one factor and that factor can be called populist schemes.

More than 61 per cent of people are in agreement with the perceptual factor that the government is offering small savings schemes to help small investors. Only around 3 per cent of people do not agree with this perceptual factor (Table 3).

Government Aid

The third perceptual factor is about investor's expectation from the government. People with this attitude expect everything from the government. They want the government to offer saving schemes. They also want the government to give advances against these schemes if the investor wants money more urgently. These people look for government aid in every respect of their actions (Table 6).

Around 13 per cent of people are not in agreement with the idea of post office giving advance against small saving securities. More than half of the people are non committal about the role of government in offering saving schemes and loan against those schemes (Table 3).

Nationalistic

The next perceptual factor is about patriotic feeling of investors. Every Indian has certain amount of patriotic feeling and some people really want to contribute something towards the development of their nation. People with this kind of perception think that all investors should park their funds only on national saving instruments. They also have a positive opinion about the saving habit of Indian citizens. The variables loaded under this component factor talk about various aspects of this perceptual factor (Table 7).

Table 3 shows that around 45 per cent of people have positive nationalistic attitude. More than 55 per cent of people are neither favourable nor unfavourable to the idea of using the postman for colleting postal deposit. Only 10 per cent of people are not in agreement with the opinion that all Indians do have good saving habit (Table 3).

Not Necessary

An attitude of 'not necessary' is another perceptual factor. Investors who have capitalistic thinking have the opinion that the government need not offer any investment schemes. The people with this kind of attitude think that post office is a place meant for effecting communication (Table 8). People with this kind of perception think that bank is a better place of investment than post offices. They also feel that some of the schemes have attractive features and such schemes can be continued but should be managed by private people.

Only 13 per cent of the people have the view that the government need not offer any saving schemes. Around 41 per cent of the people are not agreeing for idea of privatizing the small savings schemes (Table 3).

Awareness

The next component factor is about the awareness level of investors on small savings schemes. The statements in Table 9 explain that the people with this kind of perception feel that the awareness level of small saving schemes in particular and investment instruments in general are very little among the public. The investors feel that awareness is the most important factor which determines the saving pattern of any individual. The public also state that the duty of the government is not only to offer attractive schemes but also to make the people aware of those schemes by giving advertisement.

Around 27 per cent of people feel that the awareness level about small saving instruments in particular and saving instruments in general is very less. They also have the view that government spending on advertisement to popularize those small saving instruments is also very less. Only 7.6 per cent of people are satisfied with their level of awareness. More number of people (65 per cent) are not worried too much about their level of awareness (Table 3).

Savings and Development

This attitude has two features and explains around 6 per cent of variance. The two statements included under this factor explain that the people with this kind of perception feel that household saving is essential for the development of nation. To improve the level of saving of households, more number of attractive schemes must be introduced (Table 10).

Around 77 per cent of people feel that saving is essential for individuals and important for the development of the nation. Only 2 per cent of people have negative opinion (Table 3).

Segmentation of Investors

Investors can be classified into three categories based on the perception they have on small savings schemes and institutional arrangements available for those schemes. They are classified into three segments because the difference among the coefficients is significant only in three cases on the hierarchical cluster. For the purpose of classification of investors K-Means cluster is used. Table 11 shows the mean values of all the perceptual factors for the three final clusters. The mean values of perceptual factors explain the attributes of each cluster. For instance, the mean value of the perceptual factor savings and development for the first cluster is 4.08 and the mean value of perceptual factor awareness for the same cluster is 3.15. This means that the first-cluster people have high positive perception on the necessity of savings and its importance for national development and they have only limited agreement on the opinion fovouring more advertisement by the government to increase the awareness level of investors. It is also noted from the table that no particular perceptual factor is heavily loaded on any particular cluster segment. The rank of the clusters on every perceptual factor is also given in the table. The description of the characteristics of all the three clusters or segments along with the label is given below.

High Positive Perception

The first cluster has high mean value in all the perceptual factors. This cluster is ranked first in all the seven perceptual factors. The average score of this cluster is 3.70. This means that people under this segment strongly agree with the existence of such attitude with them. Since this segment has high positive attitude about the various aspects of small saving schemes, this group can be designated as highly positive perception investors. The mean value for saving and development perceptual factor is 4.08. This shows that this segment of people has high positive perception about the requirement of savings for the individual and to the nation.

Positive Perception

The second cluster can be designated as positive perception cluster because it has secured II rank in the perceptual factors of convenient set-up, populist schemes, government aid, nationalistic, and saving and development and III rank in the factors 'not necessary' and awareness. This segment of people is in agreement with the existence of convenient set-up, populist schemes, government aid, nationalistic, and savings and development perceptions because their mean score is more than three in those perceptual factors. The average mean score of this segment is 3.33 which means people under this segment are just above neutral in their perception.

Negative Perception

The mean values in the third cluster for four perceptual factors are around three and for the other three perceptual factors less than three. The average score of all the perceptual factors is less than three. This means that this segment of people do not have positive perception. This segment of people secured rank II in the perceptual factors of 'not necessary' and awareness. These two perceptual factors are negative in nature. So this segment can be christened as negative perception cluster.

Table 11 shows that the three clusters differ in mean value of all the seven perceptual factors. The analysis of variance indicates (Table 12) that the differences that exist among the three clusters in the mean values of seven perceptual factors are significant. The significant value for six perceptual factors is 0.000 and for awareness it is 0.005. This indicates that the mean values of all the seven perceptual factors are significantly different among the three clusters. This also means that all the seven perceptual factors are influencing significantly in dividing people into three segments based on their perceptions.

Table 13 indicates that around 148 investors out of 552 are in cluster I which is the high positive perception group and 250 out of 552 investors are in the positive perception group. This means that around 27 per cent of investors are in the high positive perception segment and 45 per cent in the positive perception group. The negative perception investors account only for 28 per cent of the population.

Testing suitability of segments

Table 14 contains Wilks' Lambda, the F statistic, its degrees of freedom and significance level. Wilks' Lambda is the ratio of the within-groups sum of squares to the total sum of squares. Wilks' Lambda in this case ranges from 0.6 to 0.9. The Wilks' Lambda for awareness perceptual factor is 0.981 which is very high. The mean values of awareness among three clusters are 3.15, 2.96, and 3.01. This means that the three clusters do not differ very much on awareness. The difference on 'not necessary perceptual factor' is highly significant. The significance value for the variability is 0.000 for six perceptual factors except awareness which is 0.005. This indicates that the differences among clusters on all perceptual factors are significant.

The discriminant diagram (Figure 1) shows that all the three clusters are distinctive clusters having different group centroids and different mean values. The cluster members are aligned separately from other group members. This testifies that the cluster segmentation is correct.

Table 15 gives details about degree of success of the classification on the basis of perceptual factors. The number and percentage of cases correctly classified and misclassified are displayed in the table. Here 144 cases or 97.3 per cent investors of high positive segment are correctly classified and only four cases are included in the positive cluster. From this it can be clearly inferred that the segmentation of investors based on perceptual factors is correct by more than 94.9 per cent.

[FIGURE 1 OMITTED]

Two discriminant functions can be formed when there are three clusters (Table 16). The Eigen value is high for both the functions which indicates that there is a good variability between the two functions. The canonical correlation measures the association between the two functions and seven perceptual factors. The coefficient of canonical correlation is high for both the functions. This indicates that there is a strong relationship between the two functions and the seven perceptual factors. The Wilks' Lambda for two functions are 0.195 and 0.484. This indicates that the group means are different. The significance value for both the functions is 0.000. The low Wilks' Lambda and very low significant value indicates that both the functions are significant and both the functions are useful to describe the characteristics of the population.

The structure matrix (Table 17) contains within group correlations of each predictor variable with the canonical function. This matrix provides another way of studying the usefulness of each variable in the discriminant function. For each variable, an asterisk indicates its largest absolute correlation with one of the canonical functions. With each function, these marked variables are then ordered by the size of the correlation. The strongest correlations for the first six perceptual factors occur with function 1. The variable 'not necessary' has its strongest correlation with function 2. 'Not necessary' is the only perceptual factor available in function 2. This means that 'not necessary' is a distinctively different perceptual factor. So the two functions may be Z1=0.436 x Nationalistic + 0.430 x Convenient Setup + 0.409 x Savings and Development + 0.407 x Government Aid + 0.311 x Populist Schemes + 0.091 x Awareness; and Z2 = -0.713 x 'Not Necessary'. Both these two functions are significant discriminant functions which will explain the characteristics of the investors.

Impact of Perception

Here, the impact of perception is analysed by identifying its association with investment on the range of small saving schemes. The chi-square test shows that there exists a significant association between these two.

Range of small saving investment

There are seven small saving schemes and people might invest in one or more than one schemes. The investors are classified into concentrated, extended, and diversified based on the number of schemes in which they have invested. To find out the association between perception and investment on the range of small saving schemes the correspondence analysis is used. The correspondence diagram (Figure 2) illustrates that people with negative perception will invest on only one or two schemes and when the perception changes towards positive direction they tend to invest on many schemes. People with high positive perception might invest on five to seven schemes. This means that both perception and range of investment are moving in the same direction. The chi-square value for this association is 29.795 and its significance is 0.000. This indicates that range of investment and perception have significant association.

[FIGURE 2 OMITTED]

Risk-Bearing Capacity

Based on the risk bearing capacity the investors are classified into three categories, namely, risk-free category, moderate risk takers, and high risk takers. The optimal scaling diagram (Figure 3) shows that investors who have negative perception about small saving schemes are high risk takers and investors who are not willing to take risk have high positive perception about small saving schemes because small saving schemes do not have any risk.

[FIGURE 3 OMITTED]

Determinants of Perception

From the analysis presented so far it is clear that investors' perception has an impact on investment pattern of people. Now, it is necessary to know the factors which determine the perception of investors.

Age and Work Experience

Age is a demographic variable and its impact on perception of people is tested using chi-square test. The chi-square value for the association is 11.749 and its significance is 0.019. This indicates that there exists an association between age and perception. To find out which age category people have association with what kind of perception, correspondence analysis is used. Figure 4 illustrates that people below the age of forty years have negative perception about small saving schemes because youngsters would like to take risk which is not there in small saving schemes. When they grow up, they change the attitude and they develop high positive attitude at the age of forty-nine, and afterwards their perception level gets stabilized. This indicates that the association is not only significant but meaningful.

The optimal scaling diagram (Figure 5) shows that people with an experience of more than thirty years have positive perception. This is also like an association identified for age. People with more than thirty years of experience might be on the verge of retirement. People who wait for retirement might be interested in depositing their money with government-sponsored schemes like small saving schemes. So, there is a good chance of having positive perception. This relationship is very close and the level of significance in the chi-square test is 0.003.

[FIGURE 4 OMITTED]

[FIGURE 5 OMITTED]

Investment Experience

Investment experience is calculated based on the year on which investors have started investing in small saving schemes. To analyse the association between years of experience and perception, chi-square test is carried out and correspondence analysis is also used. Chi-square value for the association is 16.288 and its significance is 0.012. This indicates that there exists a significant association between experience and perception. The correspondence analysis diagram (Figure 6) illustrates that people with one to five years of experience have negative perception and people with six to eight years of experience have high positive perception and people with experience above nine years have positive perception. This association reveals that people with less experience have negative perception and after five years of experience they start to develop positive perception and reaches its peak within another four years, and then the level of perception gets stabilized. This impact might be due to age effect because this association is like that of what is stated for age.

[FIGURE 6 OMITTED]

Tax deduction

The association between tax deduction and perception is significant as per chi-square test (the chi-square value is 14.688 and its significance is 0.023). The optimal scaling diagram (Figure 7) signifies that people who have less tax deduction have high positive perception and people who have tax deduction between Rs1000 and Rs2500 per month are with positive cluster segment; and people who have high tax deduction per month in the salary have negative perception. People who pay more tax might feel that investments in small saving schemes are not effective to reduce their tax burden and consequently have negative perception. Hence, there exists an inverse relationship between perception and tax payment.

[FIGURE 7 OMITTED]

Figure 8 shows the overall relationship between perception of investors and other variables. The perception of investors is influenced by age, experience, and level of tax deduction. The perception of investors has an impact on their range of small saving investment and risk-bearing capacity.

[FIGURE 8 OMITTED]

Discriminant Function

From the correspondence analysis, it is clear that age, experience, and tax payment have influence on the perception of an individual investor. By using discriminant analysis the extent of influence of these three variables on the perception of investors can be determined. Discriminant analysis gives two discriminant functions to study the level of perception of investors. Though two functions are in existence, one function is a redundant function here because all the three variables are highly loaded in the first function itself. The discriminant function which can be formed from the structure matrix is Z1 = 0.908 * Experience + 0.791 * Tax deduction + 0.634 * Age (Table 18).

Though all the three variables are important, it is necessary to know which is the discriminating variable that decides the nature of perception of individual investor. This can be identified by using step-wise discriminant analysis. The discriminant analysis shows that experience is the only one discriminant factor (Table 19).

In the step-wise discriminant analysis, first all the three variables will not be included for the analysis and in the first step experience is taken for analysis and the other two variables are not included for the analysis. The analysis is over with the first step itself. This means that experience is the only discriminating variable (Table 20).

Conclusion

From the analysis presented here, it is clear that perception of investors has an impact on their risk-bearing capacity and range of investment. It is also stated that perception is influenced by age, experience, and tax payment and it has an association with saving motives and behaviour of individuals. Discriminant analysis shows that experience is the discriminating factor and it is also to be remembered that if people get good service and good return during their investment tenure, they will have positive perception, otherwise negative perception will persist.

References

Antonides, G., and N.L. Van Der Sar, (1990), 'Individual expectations, risk perception and preferences in relation to investment decision-making', Journal of Economic Psychology, 11(2), pp. 227-45.

Arangasami, A., (1992), 'A study of small savings schemes in Tamil Nadu with special reference to Madras District during 1981-82 to 1990-91', unpublished thesis, University of Madras, Tamilnadu, India.

Baskaran, R., (1997), 'Marketing Strategies for National Savings Scheme in Tamil Nadu', unpublished thesis, Madurai Kamaraj University, Madurai, India.

Gavini, Augustine, L., and Prashanth Athma, (1999), 'Small Saving Schemes of Post Office Need to Be Known More', Southern Economist, 37(20), February 15, pp. 13-14.

Jayaraman, R., (1987), A study of small savings schemes in North Arcot District', 1976-86, unpublished thesis, University of Madras, Tamilnadu, India.

Karthikeyan, B., (2001), 'Small Investors' Perception on Post Office Small Savings Schemes', unpublished thesis, Madras University, Tamilnadu, India.

Kothari, C.R., (2004), 'Research Methodology - Methods and techniques', New Delhi: New Age International Publishers, 2nd Edition.

Mukhi, M.D., (1989), 'NSCs: A saving grace', Business World, 6-19 December, 1989, pp. 107-120.

NCAER, (1961), 'Savings in India', New Delhi. SEBI-NCAER, (2000), 'Survey of Indian Investor', Mumbai.

Somasundaram, V.K., (1998), 'A Study on Savings and Investment Pattern of Salaried Class in Coimbatore district', unpublished thesis, Bharathiyar University, Coimbatore, Tamilnadu.

Tamilkodi, A.P.P., (1983), 'Small Savings Schemes in Tamil Nadu: A Trend Study (1970-80)', unpublished thesis, University of Madras, Tamilnadu.

R. Kasilingam, Assistant Professor, Alagappa Institute of Management, Karaikudi, Tamil Nadu, India. Email: kasimeena@gmail.com

G. Jayabal, Reader, Alagappa Institute of Management, Karaikudi, Tamil Nadu, India. Email: gjbal@rediffmail.com
Table 1: KMO Test

Kaiser-Meyer-Olkin Measure of      0.791
Sampling Adequacy

Bartlett's    Approx. Chi-Square   2491.041
Test of       df                   253
Sphericity    Sig.                 0.000

Table 2: List of perceptual factors with percentage of
variance explained

Factors             Eigen   % Variance   % Cumulative
                    Value   Explained       Variance

Convenient Set-up   4.531       9.406          9.406

Populist Schemes    1.923       9.402         18.808

Government Aid      1.468       8.126         26.934

Nationalistic       1.446       7.911         34.845

Not Necessary       1.394       7.812         42.657

Awareness           1.053       6.927         49.584

Savings and         1.019       6.192         55.776
Development

Table 3: Frequency for Perceptual Factors

Factors                     Agree      %    Neutral     %

Convenient Set-up             416    75.4      119    21.6
Populist Schemes              340    61.6      196    35.5
Government Aid                192    34.8      289    52.4
Nationalistic                 248    44.9      249    45.1
Not Necessary                  73    13.2      254    46
Awareness                     150    27.2      360    65.2
Savings and Development       425     77       112    20.3

Factors                   Disagree     %

Convenient Set-up              17     3.1
Populist Schemes               16     2.9
Government Aid                 71    12.9
Nationalistic                  55    10.0
Not Necessary                 225    40.8
Awareness                      42     7.6
Savings and Development        15     2.7

Table 4: Factor loadings for convenient set-up

Factors                                       Loadings

Agents play a vital role in mobilizing the      0.701
savings of people

Betterment of services may attract more         0.694
investors towards the schemes.

No. of agents are sufficient to provide         0.538
service to investors

Post offices play an effective role in          0.517
mobilizing small savings, particularly
from the middle and poor classes in the
rural areas

Table 5: Factor loadings for populist schemes

Factors                                    Loadings

PPF is really helping the unorganized        0.742
sector

Postal saving really helps the small         0.734
investor

Government is giving high interest to        0.595
small saving than bank interest only to
help the small investor

Post office employees are customer-          0.457
friendly to the investors

Table 6: Factor loadings for Government AID

Factors                                       Loadings

Post offices may give advances against          0.670
small saving certificate

All small saving schemes are                    0.570
government-sponsored schemes

I know all the features of small saving         0.534
schemes

Table 7: Factor loading for national interest

Factors                                          Loadings

Postman can be used for collection of               0.722
postal deposit

All Indians should put money in                     0.688
productive saving instruments

All Indians do have good saving habit               0.667

Table 8: Factor loading for not necessary factor

Factors                                          Loadings

Government need not offer any saving                0.755
schemes

Bank is a better place of investment than           0.666
post office

Small savings should be privatized to get           0.517
more return

Table 9: Factor loading for awareness factor

Factors                                       Loadings

Government is not spending adequate             0.736
money for advertisement on small
savings

Awareness level of small savings               -0.734
schemes among public is very less

Table 10: Factor loading for savings and development

Factors                                         Loadings

Household savings help the economic               0.765
development of the country

Range of products(schemes) in small               0.502
savings must be increased

Table 11: Investors Segmentation

                         Cluster Segments

Perceptions               1     Rank    2     Rank    3     Rank

Convenient Set-up        3.94    I     3.85    II    3.10   III
Populist Schemes         3.79    I     3.59    II    3.19   III
Government Aid           3.62    I     3.29    II    2.77   III
Nationalistic            3.74    I     3.53    II    2.70   III
Not Necessary            3.61    I     2.20   III    2.66    II
Awareness                3.15    I     2.96   III    3.01    II
Saving and Development   4.08    I     3.90    II    3.20   III
Average                  3.70          3.33          2.95

Table 12: ANOVA

                              F    Sig.

Convenient Set-up        122.117   0.000
Populist Schemes          46.711   0.000
Government Aid            75.098   0.000
Nationalistic            109.159   0.000
Not Necessary            324.828   0.000
Awareness                  5.362   0.005
Saving and Development    95.458   0.000

Table 13: Number of cases in each cluster

Cluster    1   148.000   27%
Segments   2   250.000   45%
           3   154.000   28%
Valid          552.000

Table 14: Wilks' Lambda for Perpetual Factors

Perceptions     Wilks'        F    df1   df2   Sig.
                Lambda

Convenient      0.692    122.117    2    549   0.000
Set-up

Populist        0.855    46.711     2    549   0.000
Schemes

Government      0.785    75.098     2    549   0.000
Aid

Nationalistic   0.715    109.159    2    549   0.000

Not             0.458    324.828    2    549   0.000
Necessary

Awareness       0.981     5.362     2    549   0.005

Saving and      0.742    95.458     2    549   0.000
Development

Table 15: Correctness of Classification

                                   Predicted Group Membership

                                   High    Positive   Negative
Perception                      Positive   Cluster    Cluster    Total
Segmentation                    Cluster

Count   High Positive Cluster       144          4          0     148
        Positive Cluster              7        234          9     250
        Negative Cluster              2          6        146     154
        High Positive Cluster      97.3        2.7         .0   100.0
%       Positive Cluster            2.8       93.6        3.6   100.0
        Negative Cluster            1.3        3.9       94.8   100.0

94.9% of original grouped cases correctly classified.

Table 16: Eigen Values for Discriminant Functions

Function   Eigen      % of     Cumulative    Canonical
           value    Variance       %        Correlation

1          1.478      58.1        58.1         0.772
2          1.064      41.9       100.0         0.718

Function   Wilks'     Chi-        dof          Sig.
           Lambda    square

1          0.195    891.201        14          0.000
2          0.484    395.783        6           0.000

Table 17: Structure Matrix

                             Function

                           1          2

Nationalistic            0.436 *    0.331
Convenient Set-up        0.430 *    0.402
Saving and Development   0.409 *    0.307
Government Aid           0.407 *    0.164
Populist Schemes         0.311 *    0.161
Awareness                0.091 *   -0.084
Not Necessary            0.659     -0.713 *

Table 18: Structure Matrix

                      Function

                      1        2

Experience      0.908 *    -0.419
Tax Deduction   0.791 *     0.539
Age             0.634 *    -0.332

Table 19: Variables in the Analysis

Step                Tolerance   F to Remove

 1     Experience     1.000        4.219

Table 20: Variables not in the Analysis

Step                   Tolerance   Min.        F to Enter   Wilks'
                                   Tolerance                Lambda

0      Age             1.000       1.000       2.088        0.991
       Experience      1.000       1.000       4.219        0.983
       Tax Deduction   1.000       1.000       3.393        0.986

1      Age             0.494       0.494       0.004        0.983
       Tax Deduction   0.759       0.759       1.646        0.976
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